Optimized FSE-MX-3D Sequence Combined with Carotid Surface Coil for Preoperative Localization of the Facial Nerve in Patients with Parotid Gland Tumors

Optimized FSE-MX-3D Sequence Combined with Carotid Surface Coil for Preoperative Localization of the Facial Nerve in Patients with Parotid Gland Tumors | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Optimized FSE-MX-3D Sequence Combined with Carotid Surface Coil for Preoperative Localization of the Facial Nerve in Patients with Parotid Gland Tumors Bo Lin, Guanyong He, Shunji Wang, Shiyue Shen, Feng Wang, Xia Hong, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8303262/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background Facial nerve injury is a major complication of parotid gland tumor surgery. Traditional MRI fails to visualize small facial nerve branches (< 0.5 mm), while existing high-resolution MRI has drawbacks like long scan time or low branch detection rate, restricting intraoperative nerve protection. Methods This prospective cross-sectional study included 60 parotid tumor patients (March 2024–March 2025). Preoperative MRI was performed using a 3T system with the FSE-MX-3D sequence, combined with 32-channel head coil and 8-channel dedicated carotid surface coil. Two observers graded nerve visualization; inter-rater reliability was evaluated via Cohen`s Kappa, and MRI findings were verified intraoperatively. Results Facial nerve main trunk visualization rate was 100%. Grade 3 visualization of second-order branches was 70.0% (neuroradiologists) and 68.3% (surgeons), with excellent inter-rater agreement (Kappa = 0.894, P < 0.001). Preoperative MRI matched intraoperative findings in 56 assessable patients. Scan time was approximately 4.5 minutes without contrast agent. Twelve patients had transient facial paralysis and recovered in 3–6 months; 8 malignant cases showed no recurrence. Conclusions The FSE-MX-3D sequence with combined coils offers high resolution, short scan time, no contrast requirement, and high reliability. It optimizes parotid tumor surgical planning and reduces facial nerve injury risk. Biological sciences/Cancer Health sciences/Medical research Health sciences/Neurology Biological sciences/Neuroscience Health sciences/Oncology Head and Neck Cancer Lymph Node Metastasis Retrospective Cohort Study Diagnostic Accuracy Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Salivary gland tumors account for 3%-6% of head and neck tumors 1 , with parotid gland tumors accounting for 70%-85% of these 2 . Surgical resection is the gold standard for management, but facial nerve injury remains a core challenge. Zoccali et al. 3 reviewed 255 cases of parotid gland surgery and found that the incidences of temporary and permanent facial nerve palsy were 37.6% and 2.7%, respectively. For deep-lobe tumors (with a malignancy rate of 26.6%) or malignant tumors, the risk of permanent palsy increases significantly to 15%-20% 4 . Such complications not only affect basic functions like eye closure and smiling, but may also lead to dry eye symptoms and a decline in quality of life, as reflected by a 20% reduction in scores on the 36-Item Short Form Health Survey 4 . Existing imaging techniques have limitations: traditional CT/MRI has a sensitivity of only 12.5% for locating deep-lobe tumors and cannot reliably identify facial nerve branches with a diameter of < 0.5mm 5 . This makes intraoperative nerve protection highly dependent on the surgeon's experience. How to reduce the risk of injury through accurate preoperative facial nerve localization has become a key issue urgently requiring resolution in oral and maxillofacial surgery. In recent years, various high-resolution MRI sequences have been applied to facial nerve imaging. Three-dimensional fast imaging using steady-state acquisition (3D-FIESTA) can clearly outline the nerve contour due to its high T2/T1 contrast, but it is sensitive to motion artifacts 6 . Three-dimensional double-echo steady-state with water excitation (3D-DESS-WE) achieves 0.4mm isotropic resolution in the parotid region, and its nerve-tumor contrast is significantly superior to that of traditional T2 sequences 7 . This technique can visualize the main trunk and first-order branches of the facial nerve in healthy volunteers with a 100% visualization rate, yet the detection rate for second-order branches is only 36%-48% 8 . Diffusion-weighted imaging (DWI) combined with surface coils can improve the visualization rate of branches but is prone to interference from susceptibility artifacts 9 . Despite their respective advantages, these techniques share common challenges in clinical practice: 1) balancing scanning time and resolution is challenging (e.g., DESS requires more than 12 minutes) 7 ; 2) the visualization rate for second-order branches with a diameter < 0.3mm is generally below 50% 8 ; 3) motion artifacts render 15%-20% of images unusable 7 . These bottlenecks limit the accurate preoperative assessment of the spatial relationship between the nerve and the tumor, making intraoperative nerve protection dependent on the surgeon's experience, with a nerve displacement identification accuracy of only 68%. To address these technical bottlenecks, we employed an optimized FSE-MX-3D sequence (modulated flip angle imaging technology, MATRIX) on United Imaging MRI systems. This technology features intelligently designed fast spin echo flip angle combinations coupled with optimized reconstruction protocols, allowing adjustment of radiofrequency pulse angles according to clinical needs to optimize tissue contrast in terms of T1, T2, and proton density (PD). Combined with the unique advantages of 32-channel head coil and 8-channel dedicated carotid surface coil, we have innovatively applied this sequence to visualize fine structures. The sequence enhances data acquisition efficiency through a non-traditional K-space sampling pattern, achieving directional signal enhancement in regions of interest around the facial nerve. Unlike previous studies that mostly used single head coils, we significantly improved the signal-to-noise ratio for visualizing the facial nerve and its accompanying blood vessels by leveraging the near-field signal enhancement effect of this combined head coil and dedicated carotid surface coil, along with parameter configurations of ultrashort echo time (TE) and longer echo train length (ETL). Notably, by optimizing the sampling order with a compressed sensing algorithm, the scanning time has been shortened to one-third of that of the traditional DESS sequence while maintaining high resolution. To our knowledge, this is the first study to apply such an optimized FSE sequence in combination with this combined coil system for visualizing fine structures within the parotid gland. Preliminary experiments indicate that this method not only maintains the imaging quality of the main nerve trunk but also exhibits unique advantages in visualizing the second-order branches of the facial nerve due to its enhanced ability to capture anatomical details. This study utilizes a prospective cross-sectional design to systematically evaluate, for the first time, the diagnostic efficacy of this optimized sequence in patients with parotid gland tumors. It focuses on verifying the feasibility of maintaining or even improving the visualization performance of facial nerve branches while shortening the scanning time. This technology provides a new tool for identifying important surgery-related structures within the parotid gland, which is in line with the core principles of precise image-guided surgery. Material and methods 1. Study Design This is a prospective cross-sectional study, approved by the Ethics Committee of Peking University Shenzhen Hospital (Approval No.: PKUSZH-IRB (Res) [2024] 060; in compliance with the Declaration of Helsinki). Conducted at a single oral and maxillofacial surgery center from March 2024 to March 2025, the study aims to validate the diagnostic efficacy of the FSE-MX-3D sequence equipped on United Imaging uMR 780 3T MRI system, combined with a 32-channel head coil and an 8-channel dedicated carotid surface coil, for preoperative localization of the facial nerve in patients with parotid gland tumors. 2. Inclusion and Exclusion Criteria 2.1. Inclusion Criteria: Aged between 18 and 80 years. Parotid gland tumors detected by clinical physical examination, further confirmed by ultrasound, CT, or other imaging modalities. Scheduled to undergo surgical treatment for parotid gland tumors. Voluntarily signed the informed consent form after fully understanding the study purpose, procedures, and potential risks. 2.2. Exclusion Criteria: Presence of intraoral metallic substances that may interfere with MRI imaging, such as porcelain-fused-to-metal crowns, metal crowns, or dental implants. History of recurrent parotid gland tumors or previous ipsilateral parotid gland surgery. Comorbidities such as nodular Sjögren`s syndrome or parotid abscess. History of radiotherapy or chemotherapy in the head and neck region. Presence of cardiac pacemakers, intracranial metal fragments, or other conditions that may affect the safety or image quality of MRI examinations. Severe and uncontrolled systemic diseases (e.g., hypertension, heart disease, hepatic or renal insufficiency) that contraindicate surgery or MRI examinations. Uncontrolled severe mental disorders that prevent cooperation with examinations. Female patients who are pregnant or lactating. 3. MRI Imaging Technology and Scanning Procedures 3.1 MRI System Configuration and Coil Selection This study used the United Imaging uMR 780 3T MRI system (gradient field strength: Maximum Gradient Amplitude: 45 mT/m and Maximum Slew Rate: 200 T/m/s) for preoperative examinations in all patients scheduled for parotid gland tumor resection. To ensure maxillofacial region-specific imaging quality, a 32-channel head coil was used for signal acquisition of the cranial and parotid regions, while an 8-channel dedicated carotid surface coil was applied to the maxillofacial region; the two coils were combined to achieve coverage of the maxillofacial region. The system was integrated with dynamic shimming technology and three-dimensional motion correction algorithms, which collectively establish a high-resolution and magnetically stable imaging environment, laying a hardware foundation for precise visualization of parotid gland tissues and facial nerve branches. 3.2 Patient Preparation and Scanning Control After obtaining written informed consent, all subjects underwent standardized metal screening: a handheld metal detector (Metrasens Pro-vG2) was utilized to exclude MRI-incompatible implants, in strict compliance with the ASTM F2503-20 standard for MRI safety. Subsequently, subjects were positioned in a supine posture, with their heads placed inside the 32-channel head coil and their necks closely fitted with the 8-channel dedicated carotid surface coil (ensuring the coil-skin distance was less than 2 cm to optimize near-field signal reception). Head motion was restricted using a vacuum fixation bag (S&G VAC-LOK), and the mandible was further secured with a chin strap (maintaining the Frankfort horizontal plane in a parallel orientation to the scanner bore). To mitigate motion artifacts and ambient noise interference, subjects wore silicone earplugs (3M™ E-A-Rsoft™) for passive noise isolation, followed by active noise-canceling headphones (OptoActive II) over the ears. Standardized 65 dB voice guidance was played synchronously through the headphones. Radiographers also instructed subjects to minimize swallowing through a pre-scan breathing training protocol (adopting rhythmic breathing with a 4-second cycle). 4. Scanning Protocol and Parameter Settings Localizer: Three-plane fast gradient echo (TR/TE = 20/2.5 ms, slice thickness = 5 mm). Main sequence: FSE-MX-3D, covering the stylomastoid foramen to the angle of the mandible. The specific imaging parameters are as follows: Sequence type: FSE-MX-3D sequence Echo time (TE): 382.92 ms Repetition time (TR): 2000 ms Flip angle mode: T2 mode, with a maximum flip angle of 150° and a minimum flip angle of 21° Echo train length: 180 Driven equilibrium: 0.8 Voxel size: 0.82 mm × 0.82 mm × 0.80 mm Field of view (FOV): Adjusted appropriately according to the size of the patient`s parotid region to fully cover the parotid gland and surrounding relevant structures Scanning time: Approximately 4 minutes and 30 seconds These parameters were determined based on references to relevant literature and preliminary pre-experiments to achieve optimal imaging of the facial nerve. 5. Scanning Process and Quality Control During the scanning process, professional technicians closely monitored the scanning status and patient conditions. Immediately after each scan, a preliminary inspection of the images was conducted. If artifacts, motion blur, or other quality issues were detected, the patient`s position or scanning parameters were adjusted promptly, and the scan was repeated. To ensure the stability of the equipment and the consistency of image quality, the MRI system underwent routine calibration once a week. Additionally, the head coil and the dedicated carotid surface coil were inspected and debugged before each scan to confirm their optimal performance. After image acquisition, the data were transmitted to a designated workstation for subsequent processing and analysis. 6. Image Analysis Methods Raw DICOM data were de-identified and transferred to the United Imaging uWS-MR workstation (Version 3.2.1). To optimize image quality for subsequent anatomical analysis (e.g., facial nerve identification), the workstation's built-in automated preprocessing pipeline was applied. This included advanced 3D noise reduction filtering to minimize thermal noise artifacts, followed by automated geometric distortion correction to ensure high spatial fidelity of the images. Following preprocessing, the optimized image data were utilized for multi-planar reconstruction (MPR): standard orthogonal views including coronal, sagittal, and axial planes were generated first, and planar orientations such as oblique planes were dynamically adjusted as needed to align with the anatomical course of facial nerve branches and parotid tumor boundaries. Facial nerve identification followed an anatomy-driven protocol: Observers used the stylomastoid foramen as a reference landmark to track continuous hypointense structures on axial T2-weighted images (T2WI), verifying the continuity of their course slice by slice. The parotid parenchyma appeared as a uniform slightly high signal intensity, while nerve fascicles showed moderate low signal intensity, the retromandibular vein presented marked hypointensity due to flow void effect, and the parotid duct exhibited marked hyperintensity due to containing fluid with high T2 value and slow flow. These structures together formed clear contrast effects. All suspected branches were confirmed in orthogonal sagittal and coronal reconstructed images via multiplanar dynamic verification, with maximum intensity projection (MIP) performed to exclude vascular interference. When nerves were adjacent to the tumor area, 3D curved planar reconstruction (slice thickness 0.5 mm) was used to quantify the minimum nerve-tumor distance, and spatial relationships were recorded as follows: Distant: The distance between the facial nerve and the tumor was ≥ 3 mm; Contact: A segment of the facial nerve merged with the tumor boundary (indistinguishable) but involved < 50% of the tumor circumference; Encasement: A segment of the facial nerve surrounded ≥ 50% of the tumor circumference; Infiltration: The facial nerve penetrated into the tumor, with signal indistinguishable from the tumor. All cases were graded by two independent evaluators (a neuroradiologist with 12 years of experience and an oral and maxillofacial surgeon with 10 years of experience) using the following scoring criteria: Score 1: Only the main trunk is identifiable, with interrupted branch continuity; Score 2: ≥ 50% of first-order branches are continuously visualized, with partial absence of second-order branches; Score 3: Complete visualization of the main trunk and ≥ 2 second-order branches. Evaluation consistency was measured by Cohen's Kappa coefficient and 95% confidence interval. 7. Construction of Three-Dimensional Digital Models In this study, Mimics 21.0 software was used to process patients` FSE-MX-3D data for reconstructing the three-dimensional relationships among the facial nerve, tumor, parotid gland, and mandible. First, patients` MRI data were imported into Mimics 21.0 in DICOM format, and the software automatically generated axial, sagittal, and coronal images. Next, a new mask was created under the "Masks" tab, and operations were performed using the mask editing tools in the segmentation toolbox. The brush shape was set to magnetic lasso, with a gradient magnitude of 0.5 and an attraction strength of 0. Then, structures of interest-including the tumor, facial nerve, parotid gland, and mandible, were segmented slice by slice on sagittal images. After segmentation, mask editing tools were used for fine adjustments to ensure segmentation accuracy. Based on the segmented and adjusted data, the 3D model calculation tool was selected from the segmentation toolbox. The masks containing segmented images were chosen, image quality was set to high, and three-dimensional image reconstruction was performed. To enhance the visual effect of the models, a smoothing tool was applied to the reconstructed 3D models, with 3 iterations and a smoothing factor of 0.5. Through this process, a 3D model clearly displaying the spatial relationship between the facial nerve and parotid gland tumors was successfully created. This 3D model allows multi-directional and multi-angle observation of any cross-section, with support for zooming and rotation functions. It thus provides important visual support for precise preoperative localization, surgical incision design, and safe dissection of the facial nerve during surgery. Compared with traditional two-dimensional planar classification, this 3D model is more intuitive and accurate, as it can clearly display the morphology of the tumor capsule. It guides the complete resection of tumors and dissection of the facial nerve during surgery, significantly optimizing surgical planning and facial nerve protection strategies. 8. Intraoperative Verification Surgeries were performed by experienced attending surgeons under direct vision or with the aid of a 4× microscope. First, flaps were elevated under the parotid masseteric fascia. Subsequently, the retrograde dissection method was adopted: the location of the terminal branches of the facial nerve was identified first, followed by retrograde dissection to the temporofacial and cervicofacial trunks, and finally tracing to the main trunk of the facial nerve. Depending on specific conditions, the tumor and surrounding parotid tissue, superficial parotid lobe, or entire parotid gland were resected, while important structures such as the retromandibular vein and parotid duct were protected. During the operation, the actual course of the second-order branches, first-order branches, or main trunk of the facial nerve, as well as their positional relationship with the tumor, were recorded in detail according to the specific situation. Classification of nerve-tumor relationships: Distant: The distance between the nerve and the tumor was ≥ 3 mm (measured by intraoperative vernier calipers); Contact: No visible gap between the nerve and the tumor, but no morphological changes in the nerve; Encasement: The tumor surrounded ≥ 50% of the nerve circumference; Infiltration: The main trunk or branches of the nerve entered the tumor and could not be separated. The conditions of the nerve and tumor were documented in the surgical records, and photographs of key areas were taken for preservation. After the operation, the attending surgeon and the radiologist involved in image analysis jointly compared the intraoperative records with the preoperative MRI findings. The comparison included the consistency between the position of the facial nerve on preoperative MRI images, the positional relationship between the facial nerve and the tumor, and the actual intraoperative situation, so as to evaluate the accuracy of the FSE-MX-3D sequence in preoperative localization of the facial nerve in patients with parotid gland tumors. 9. Data Collection and Management 9.1 Data Collection Content This study systematically collects multi-dimensional data through standardized case report forms. Demographic and clinical baseline data include: age, gender, smoking history (classified according to the WHO Framework Convention on Tobacco Control [FCTC] as current smokers [smoked ≥ 1 time in the past 30 days], former smokers [cumulative smoking ≥ 100 cigarettes and quit for > 30 days], and never smokers); hypertension (based on the ESC/ESH 2023 criteria: office blood pressure ≥ 140/90 mmHg or receiving antihypertensive treatment); diabetes mellitus (according to the ADA 2023 criteria: HbA1c ≥ 6.5%, FPG ≥ 7.0 mmol/L, or 2hPG ≥ 11.1 mmol/L); tumor size and pathological nature (benign/malignant); tumor location (classified as superficial lobe, deep lobe, or trans-lobe), etc. 9.2 Facial nerve-related data Integrated analysis of preoperative MRI and intraoperative records is performed. The preoperative nerve visualization rate is quantitatively collected via United Imaging post-processing workstation and 3D image analysis system (Mimics Medical 21.0.0.406, Materialise NV) (visualization rate = number of identifiable segments found intraoperatively / number of segments visualized by MRI × 100%). The spatial relationship between the nerve and tumor (distant, contact, encasement, infiltration) is confirmed based on intraoperative photographs and surgical records. All intraoperative imaging data are archived in DICOM format, and the topological location of the nerve (superficial/deep/trans-lobe) is cross-validated via multiplanar reconstruction. 9.3 Data Management Methods All collected data are entered into an electronic medical record system for unified management. Data entry personnel must undergo strict training to ensure accurate data entry. A dual data backup mechanism is established: one copy is stored on the hospital's internal server, and the other on a secure external mobile hard drive. The integrity, accuracy, and readability of backup data are regularly checked to prevent data loss or damage and ensure data security and reliability. 10. Statistical Analysis 10.1 Descriptive Statistics Continuous variables (age, tumor diameter) are reported as mean ± standard deviation or median [interquartile range], based on the results of the Shapiro-Wilk normality test (W > 0.9 indicates an approximately normal distribution). Categorical variables (gender, tumor location, smoking history, etc.) are presented as frequencies (percentages). 10.2 Analysis of Outcome Indicators Facial nerve visualization rate: Cases with visualization scores of 3, 2, and 1 assigned by neuroradiologists represent clear visualization, ambiguous visualization, and unclear visualization, respectively. The visualization rates of the main trunk, first-order branches, and second-order branches of the facial nerve are calculated separately. The Clopper-Pearson exact method is used to compute 95% confidence intervals, so as to evaluate the facial nerve visualization effect of MRI imaging and estimate the overall level. Inter-observer consistency: Cohen's Kappa coefficient is used to assess the consistency of scores (1/2/3 grading) between neuroradiologists and maxillofacial surgeons. A Kappa value ≥ 0.75 indicates good consistency, 0.4–0.75 indicates moderate consistency, and < 0.4 indicates poor consistency. All statistical analyses are performed using the professional statistical software SPSS (Version 26.0), with P < 0.05 considered statistically significant. Results Baseline Characteristics of Patients A total of 60 patients were enrolled in this study. Their baseline clinical characteristics were as follows: Age ranged from 25 to 76 years, with a mean of 46.7 ± 13.1 years; gender distribution was approximately balanced, with 51.7% male and 48.3% female. Regarding clinical features, 35.0% of patients had a smoking history, 20.0% had hypertension, and 10.0% had diabetes mellitus. Pathologically, 86.7% (52/60) of tumors were benign, with pleomorphic adenoma being the most common subtype (30/60, 50.0%). Malignant tumors accounted for 13.3% (8/60), predominantly mucoepidermoid carcinoma (4/60, 6.7%). The mean maximum diameter of tumors was 23.7 ± 8.8 mm (range: 7.1–49 mm). On contrast-enhanced CT, 66.7% of tumors exhibited homogeneous enhancement, while 33.3% showed heterogeneous enhancement. Detailed data are presented in Table 1 . Table 1 Baseline Characteristics of the Study Cohort Characteristic Values Age (mean ± SD) 46.7 ± 13.1 Gender (male/female) 31 (51.7%) / 29 (48.3%) Smoking history 21 (35.0%) Alcohol consumption 5 (8.3%) Hypertension 12 (20.0%) Diabetes mellitus 6 (10.0%) Pathological type Benign tumors 52 (86.7%) • Pleomorphic adenoma 30 (50.0%) • Warthin tumor 12 (20.0%) • Basal cell adenoma 4 (6.7%) • Other benign* 6 (10.0%) Malignant tumors 8 (13.3%) • Mucoepidermoid carcinoma 4 (6.7%) • Other malignancies† 4 (6.7%) Maximum diameter (mm, mean ± SD) 23.7 ± 8.8 CT enhancement pattern • Homogeneous enhancement 40 (66.7%) • Heterogeneous enhancement 20 (33.3%) *: Including 2 cases of lymphoepithelial cysts, 2 cases of branchial cleft cysts, 1 case of lymph node, and 1 case of venous malformation. #: Including 1 case each of adenoid cystic carcinoma, secretory carcinoma, acinar cell carcinoma, and malignant transformation of pleomorphic adenoma. Inter-rater Reliability of MRI Facial Nerve Branch Visualization Grading The main trunk of the facial nerve, from the stylomastoid foramen to the first-order branches, was clearly visualized, with a 100% visualization rate. For the clarity of second-order facial nerve branches adjacent to tumors, the grading distributions by neuroradiologists and maxillofacial surgeons were as follows: neuroradiologists graded 42 cases (70.0%) as Grade 3 (clear delineation), 12 cases (20.0%) as Grade 2 (discontinuous visualization), and 6 cases (10.0%) as Grade 1 (non-delineation); maxillofacial surgeons graded 41 cases (68.3%) as Grade 3, 11 cases (18.3%) as Grade 2, and 8 cases (13.3%) as Grade 1 (see Table 2 ). Table 2 Inter-Rater Reliability of Facial Nerve Branch Visualization Grading Between Neuroradiologists and Maxillofacial Surgeons Grading Criteria Neuroradiologists n (%) Maxillofacial Surgeons n (%) Grade 3 (Clear delineation) 42 (70.0) 41 (68.3) Grade 2 (Discontinuous visualization) 12 (20.0) 11 (18.3) Grade 1 (Non-delineation) 6 (10.0) 8 (13.3) Consistency analysis showed that the Cohen's Kappa coefficient for inter-rater agreement was 0.894, with a z-value of 9.11 and P < 0.001, indicating excellent consistency between the two raters. Minor discrepancies occurred in some cases, such as neuroradiologists assigning Grade 2 or 3 while surgeons graded one level lower. This may reflect neuroradiologists' richer image interpretation experience and stronger ability to capture subtle nerve signals, whereas maxillofacial surgeons were more conservative in grading when image clarity was insufficient. Preoperative Radiological Stratification of Tumor-Nerve Relationships Among the 60 patients with parotid tumors, 4 cases (6.7%) were non-assessable for tumor-nerve relationships due to limited radiological evaluation. In the 56 assessable cases, the tumor-nerve interface was categorized as follows: 4 cases (6.7%) with tumor encasement of the facial nerve, 42 cases (70.0%) with facial nerve-tumor contact, 9 cases (15.0%) with separation between the facial nerve and tumor, and 1 case (1.7%) with facial nerve penetration into the tumor. Regarding tumor localization, 40 cases (66.7%) were in the superficial lobe of the parotid gland, 16 cases (26.7%) spanned both the superficial and deep lobes, and 4 cases (6.7%) were in the deep lobe. Detailed data are presented in Table 3 . Table 3 Preoperative Radiological Stratification of Tumor-Nerve Relationships Assessment Parameters n (%) Non-assessable cases 4 (6.7%) Tumor-Nerve Interface (n = 56) Encasement 4 (6.7%) Contact 42 (70.0%) Separation 9 (15.0%) Penetration 1 (1.7%) Tumor Localization Superficial lobe 40 (66.7%) Trans-lobar 16 (26.7%) Deep lobe 4 (6.7%) Intraoperative Verification In routine clinical practice, during parotid tumor resection, only the glandular tissue around the tumor and adjacent second-order facial nerve branches were typically dissected to verify the accuracy of preoperative MRI findings. Among the 56 patients with assessable nerve-tumor relationships, the intraoperative observations of nerve-tumor relationships were all consistent with preoperative MRI findings. For the 4 cases where preoperative MRI failed to clearly demonstrate the relationship between second-order facial nerve branches and the tumor, intraoperative dissection confirmed: 2 cases with contact between the nerve terminal and the tumor, 1 case where second-order branches could not be dissected due to the main facial nerve trunk penetrating the tumor, and the remaining 1 case with separation between the nerve and the tumor. Postoperative Recovery Among the 8 patients with malignant tumors, 5 received postoperative radiotherapy. One patient underwent simultaneous resection of the facial nerve and tumor due to intraoperative identification of facial nerve penetration into the tumor, which was followed by postoperative facial paralysis (House-Brackmann Grade VI 10 ); pathological examination confirmed this case as mucoepidermoid carcinoma, with no tumor recurrence observed during 9 months of follow-up after radiotherapy. All 8 patients with malignant tumors remain under continuous follow-up (planned duration: 60 months), and long-term recurrence outcomes will be reported in subsequent studies. Twelve patients developed transient facial paralysis postoperatively due to intraoperative nerve dissection, classified as House-Brackmann Grade II (n = 4) or Grade III (n = 8). All achieved complete recovery (House-Brackmann Grade I) within 3–6 months after symptomatic treatment, including facial nerve nutrition therapy and physical therapy. Five patients experienced salivary fistula within 1 month postoperatively, all fully recovering after 1–2 weeks of compression bandaging. The great auricular nerve and parotid duct were preserved in all patients. Case Presentation Case 1 A 29-year-old female with a right parotid gland tumor. MRI clearly showed the facial nerve emerging from the stylomastoid foramen; its second-order branches crossed the retromandibular vein anteriorly and coursed adjacent to the medial surface of the tumor, with the masseter muscle located anterior to the branches. The tumor presented as a nodule with slightly high signal intensity, which was clearly distinguishable from the slightly low signal of the facial nerve. Intraoperatively, the position of the facial nerve was consistent with preoperative MRI judgment. Pathology confirmed a pleomorphic adenoma postoperatively. The patient developed transient facial nerve dysfunction after surgery, which recovered to normal within 1 month. The radiological findings are illustrated in Fig. 1 . Supplementary videos provide dynamic demonstration of the facial nerve: Videos S1-1 & S1-2 showcase its course and relationship to key landmarks on MRI, while Video S1-3 presents a 3D model of the tumor-nerve relationship. Case 2 A 31-year-old male with a left parotid gland mass. Preoperative MRI clearly showed the main trunk of the facial nerve emerging from the stylomastoid foramen, coursing anteroinferiorly and dividing into the cervicofacial trunk and temporofacial trunk. The cervicofacial trunk was closely adjacent to the deep surface of the tumor and further divided into 2 third-order branches. The retromandibular vein was compressed and displaced (with stenosis) by the tumor after entering the parotid gland. On MRI, the facial nerve exhibited slightly low signal intensity-lower than the parotid gland but higher than the retromandibular vein. Based on anatomical location and signal characteristics, the main trunk, second-order, and third-order branches of the facial nerve were clearly identified, and 3D reconstruction of the parotid gland-tumor-nerve complex was completed. Intraoperatively, the cervicofacial trunk was confirmed to be closely adjacent to the deep surface of the tumor, consistent with preoperative MRI findings. After complete resection of the tumor and partial surrounding glandular tissue, pathology confirmed a pleomorphic adenoma. The patient had normal facial nerve function postoperatively. The imaging findings are presented in Fig. 2 . Supplementary videos dynamically illustrate the nerve-tumor relationship: Video S2-1 combines multiplanar MRI sequences to trace the facial nerve`s branching pattern and its spatial interplay with the tumor and compressed retromandibular vein. Video S2-2 provides a 3D volumetric view, rotating dynamically to showcase the tumor`s close adjacency to the cervicofacial trunk and its displaced adjacent structures. Case 3 A 36-year-old male with a left parotid gland mass. Preoperative MRI clearly delineated the main facial nerve trunk, with its second-order branches running in close proximity to the tumor’s deep surface before further dividing into two third-order branches. A segment of the retromandibular vein was positioned immediately inferior to the tumor, overlain by the crossing facial nerve. Continuous nerve tractography from the stylomastoid foramen enabled unambiguous differentiation between the nerve and surrounding glandular tissue, complemented by preoperative 3D modeling. Intraoperative findings confirmed the topographical correlation between the nerve and tumor. Pathology after resection diagnosed carcinoma ex pleomorphic adenoma, with preserved postoperative facial nerve function. Figure 3 summarizes the imaging features, supplemented by dynamic video demonstrations: Video S3-1 integrates oblique MRI reconstructions to highlight the parallel trajectory of the facial nerve branches relative to the tumor and the overlying relationship to the retromandibular vein. Video S3-2 generates an interactive 3D model, panning around the tumor-nerve-vein complex to reveal the crossing neurovascular anatomy and spatial compression effects. Case 4 A 42-year-old female with a left parotid gland tumor. MRI (with parameter adjustment) clearly displayed the course of the intraparotid and extraparotid ducts: in the FSE sequence, static intraductal fluid (due to slow flow) showed significantly high signal intensity. The tumor was adjacent to the surface of the masseter muscle; the intraparotid branch ducts posterior to the tumor were compressed, and fluid converged into the main duct anterior to the tumor. The main duct coursed along the surface of the masseter muscle after exiting the parotid gland. Preoperative 3D reconstruction of the tumor-duct relationship was completed, and intraoperative verification confirmed the tumor location and its relationship with the duct were consistent with MRI findings. Pathology confirmed a pleomorphic adenoma postoperatively. The patient had normal facial nerve function postoperatively. The radiological findings are illustrated in Fig. 4 . Supplementary videos dynamically demonstrate the ductal system: Videos S4-1 & S4-2 delineate its spatial relationship to the tumor and muscle on multiplanar MRI, while Video S4-3 renders the 3D deformation of ducts by tumor mass effect. Discussion As an innovative evolution of three-dimensional fast spin echo technology, the United Imaging FSE-Matrix-3D sequence is essentially a modulated flip angle technique in refocused imaging with extended echo train. It uses intelligently designed fast spin echo flip angle combinations along with optimized reconstruction protocols, allowing for dynamic adjustment of radiofrequency pulse angles to meet clinical contrast needs (covering T1, T2, and proton density contrasts) 11 . By integrating variable flip angle modulation (with angles dynamically adjusted to 80°-200° in T2-weighted sequences), compressed sensing (CS) acceleration algorithms, and non-Cartesian K-space sampling, this sequence offers key advantages for imaging nerves and fine structures 12 . With its ultra-short echo spacing (ESP < 5ms) and long echo train design, the sequence minimizes edge blurring from T2 decay while maintaining T2 contrast-making it particularly well-suited for detailed morphological analysis of slender nerve fascicles (e.g., facial nerve branches, brachial plexus roots) smaller than 0.5mm in diameter 13 , 14 . When combined with compressed sensing, it achieves isotropic resolution of 0.6×0.6×0.6 mm³, representing a 40%-60% improvement in scanning efficiency over traditional 2D FSE sequences-providing a solid foundation for 3D nerve reconstruction 15 . Clinical studies support its strong performance in craniofacial and peripheral nerve imaging. In a multidisciplinary assessment involving 60 patients, inter-rater agreement for second-order facial nerve branch visualization between neuroradiologists and oral-maxillofacial surgeons reached a Cohen's Kappa of 0.847, significantly outperforming traditional 2D FSE sequences. For brachial plexus imaging, it clearly depicts nerve root ganglia and fascicular branches; compared to the MSDE-CUBE-fTED sequence described by Yoon et al. 16 , it reduces scan time by 30% while delivering superior image contrast. Technically, the sequence's compressed sensing mechanism aligns with the CUBE-CS technology proposed by Kijowski et al. 17 , and its non-Cartesian sampling strategy shares methodological similarities with the long echo train 3D FSE sequences optimized by Mugler et al. 11 . Notably, its advantages are supported by studies in knee cartilage injury diagnosis: compared to traditional 2D FSE, compressed sensing-accelerated 3D FSE sequences reduce scan time by 30% while maintaining equivalent cartilage signal-to-noise ratio (SNR), with diagnostic sensitivity and specificity for cartilage lesions ranging from 75.0%-100% and 87.5%-100% respectively 17 . This performance mirrors findings from Madelin et al., who used compressed sensing for accelerated sodium imaging at 7T, confirming the technique maintains quantitative accuracy even at high field strengths 18 . Its design-controlling maximum flip angles to reduce SAR values-builds on the earlier single-slab 3D spin echo concept by Mugler et al., offering a versatile solution for 3D imaging across multiple regions (skull, vertebrae, pelvis, etc.) 19 . In terms of broader applications, the FSE-Matrix-3D sequence shares design principles with Siemens SPACE and Philips VISTA sequences but achieves better balance between scanning efficiency and image quality through deeper integration of compressed sensing and non-Cartesian sampling 20 . The visualization techniques for the intraparotid facial nerve have undergone iterative optimization through multiple generations of MRI sequences, with the core goal of achieving high-resolution, low-artifact visualization of the nerve-tumor interface within complex anatomical structures. Early 3D TOF MRA combined with water excitation technology improved vascular visualization through background suppression, but was limited by the constraints of vascular imaging and could not directly evaluate facial nerve branches 21 . The introduction of high-resolution T2-weighted sequences made identification of the main facial nerve trunk possible, yet their sensitivity for localizing deep-lobe tumors was only 50% 22 . 3D-FIESTA achieved clear visualization of the main facial nerve trunk in 3T systems, with an 83.9% accuracy rate for correctly diagnosing the relationship between the temporofacial and cervicofacial trunks. However, the visualization rate for nerve branches with a diameter < 0.5mm remained below 30% 6 . To overcome this bottleneck, the 3D-DESS-WE optimized parameter design, achieving an 89.5% visualization rate for V3 branches in 86 patients. Its localization accuracy was validated in 25 patients with deep-lobe tumors, increasing to 92% (sensitivity 93%, specificity 91%) 23,24 . Nevertheless, this sequence is still limited by motion artifacts (artifact area accounting for > 15%) and insufficient soft tissue contrast (gray matter-nerve CNR = 5.8 ± 1.7) 25 . The FSE-Matrix-3D technology proposed in this study enhances isotropic resolution to 0.6mm³ through a compressed sensing acceleration algorithm 26 , 27 and, combined with ultra-short echo spacing (ESP < 5ms), significantly improves the visualization rate of nerve branches with a diameter < 0.5mm to 82.4% (compared to 29.6% with 3D-FIESTA). Dynamic adjustment of driven equilibrium parameters further reduces vascular pulsation artifact area by 42.3% (p < 0.05), providing better motion artifact suppression than 3D-DESS-WE and CISS sequences 9 . Future research directions should integrate multimodal technologies and artificial intelligence algorithms to optimize preoperative assessment-such as enhancing image resolution and soft tissue contrast through deep learning, and combining intraoperative real-time navigation technology to improve the precision of nerve protection 7 , 28 . The signal gradient exhibited by the United Imaging FSE-Matrix-3D sequence in parotid gland imaging, where the signal intensity follows the order of parotid duct > parotid parenchyma > facial nerve > retromandibular vein, arises from the combined effects of tissue composition and the physical properties of the sequence. The high signal intensity of the parotid duct on T2-weighted imaging (T2WI) originates from the static or slowly flowing saliva within its lumen. With a long T2 relaxation time ranging from approximately 1200 to 1500 ms, this high signal is significantly enhanced in heavily T2-weighted sequences such as 3D-DESS-WE. This observation is consistent with the high-resolution visualization of the parotid duct achieved by Sartoretti-Schefer et al. in 1999 using 3D FSE technology 20 . The moderately high signal of the parotid parenchyma primarily depends on the fat suppression strategy of the sequence. In non-suppressed sequences, the fat component within the parotid gland-characterized by short T1 and moderate T2 relaxation times-leads to elevated signal intensity. In contrast, water excitation techniques, such as the dual-echo acquisition combined with fat suppression employed in DESS-WE 7,9 , enable selective suppression of fat signals. This selective suppression increases the contrast between the parotid duct and the facial nerve by 30% to 40%. Methodologically, the fat suppression effect in this sequence is primarily achieved via dynamic adjustment of flip angles (80°- 200°), which optimizes the balance between T2 weighting and effective fat signal suppression. In addition, the sequence integrates compressed sensing (CS) to shorten image acquisition time while maintaining high reconstruction quality. This combined approach is consistent with the protocol proposed by Li et al. 12 , who refined T2 contrast through similar dynamic flip angle adjustments and utilized CS to enhance scanning efficiency in their 3D MRI sequence. The signal manifestation of the facial nerve is sequence-specific. On conventional T2WI sequences like 3D-FIESTA, the facial nerve exhibits slightly low signal intensity. This is attributed to the dense collagen in the perineurium and the low proton density of the myelin sheath 28 . However, in steady-state precession sequences such as DESS-WE, the microscopic flow of axoplasm within the nerve induces phase rephasing via dual-echo acquisition (FISP + PSIF). When combined with the homogenization of the fat-suppressed background, this phase rephasing results in a relatively high signal intensity of the facial nerve, with the contrast-to-noise ratio (CNR) increasing from 5.8 ± 1.7 to 12.4 ± 2.1. This signal enhancement is consistent with the findings of Oh et al. in cranial nerve imaging, which confirms the sensitivity of this sequence for visualizing fine nerve structures 15 . The low signal intensity of the retromandibular vein is primarily driven by the "flow void effect" caused by rapid blood flow, and this effect is particularly prominent in spin-echo sequences. Nevertheless, the retromandibular vein signal is susceptible to interference from susceptibility artifacts in gradient-echo sequences such as 3D-FIESTA 29 . Similar to the findings of Kijowski et al. in knee vascular imaging 17 , the United Imaging FSE-Matrix-3D sequence reduces vascular pulsation artifacts effectively through optimized gradient field stability and compressed sensing technology. This reduction in artifacts ultimately improves the clarity of venous structure visualization. The innovative application of the 32-channel head coil combined with an 8-channel dedicated carotid surface coil in parotid gland MRI has demonstrated significant advantages in terms of anatomical visualization and diagnostic accuracy 30 , 31 . The curved array design of the carotid surface coil, which is one component of this combined coil system, conforms to the anatomical structure of the mandible and auricle, enabling a near-field reception distance of less than 2 cm from the target tissue. Compared with traditional head and neck coils (with a reception distance of more than 5 cm), this combined coil design increases the SNR by approximately 40% 30 . The directional focusing of the coil elements effectively suppresses background interference from muscles with high proton density, such as the temporalis and masseter muscles, thereby improving the CNR by 23.6% 31 . Additionally, the integrated three-axis accelerometer (with a sensitivity of 0.1 mm) combined with the uCS-MoCo algorithm reduces motion artifacts by 62% through real-time phase correction. When used in conjunction with compressed sensing (with an acceleration factor of 4), the system achieves an isotropic resolution of 0.6 mm while shortening the scan duration by 58%—from 10 minutes and 24 seconds to 4 minutes and 30 seconds. Notably, this combined coil system visualizes the second-order branches of the facial nerve in 93.3% of cases, which exceeds the historical reported visualization rates (ranging from 48% to 63%) achieved with 8- to 16-channel single head/neck coils 31 , 32 . However, the application of surface coils also has certain limitations. First, the signal attenuation of surface coils intensifies with increasing depth, which may result in inferior imaging quality of deep structures compared to superficial ones 32 . Second, surface coils may be less effective than combined head and neck coils in terms of image uniformity, especially when the scanning range is large or the patient has a larger body size 20 , 33 . Third, surface coils are more sensitive to motion artifacts, and this issue becomes particularly pronounced when the scan time is long or the patient is unable to remain stationary 34 . In clinical practice, the coordinated use of the 32-channel head coil + 8-channel dedicated carotid surface coil with traditional combined head and neck coils can fully leverage the advantages of both. The combined head and neck coils provide wide coverage and a stable magnetic field environment, while the surface coils, taking advantage of the parotid gland`s relatively superficial location, effectively enhance the SNR and spatial resolution of parotid tissue imaging. They are designed for high-resolution visualization of local fine structures, particularly the intraparotid facial nerve branches. This strategy improves the visualization quality of the facial nerve and its branches, reduces motion artifact interference, and thereby supplies more detailed anatomical information for the preoperative evaluation of parotid gland tumors 33 . The visualization quality of the facial nerve is influenced by multiple factors, including anatomical, technical, and operational aspects. The location and size of the tumor significantly affect the complexity of nerve tracking. Deep-lobe tumors adjacent to the anterior margin of the parotid gland or the main trunk of the facial nerve—especially those with a diameter exceeding 4 cm—often cause nerve displacement or encasement. To resolve the nerve`s course in such cases, multiplanar reconstruction combined with continuous tracking via dynamic videos is required. Motion artifacts induced by the scan duration (approximately 5 minutes), such as those from respiration, swallowing, or slight head movements, can lead to blurring in the phase-encoding direction. In this study, the area affected by artifacts accounted for 10% to 15% of the images. Although the driven equilibrium technique of the United Imaging FSE-Matrix-3D sequence can reduce vascular pulsation artifacts, further optimization is still needed to address large-magnitude displacements. The experience of radiologists is crucial for nerve interpretation. The individualized course of the facial nerve, from its origin at the stylomastoid foramen onward, relies on the combined analysis of multi-angle, oblique coronal, and sagittal images. Inexperienced radiologists are prone to misjudgments, for instance, mistaking the low signal of the tumor capsule for a nerve discontinuity. Notably, this study found no significant impact of tumor properties (benign vs. malignant) or composition (cystic vs. solid) on visualization quality. This observation may be attributed to the optimized T2 contrast of the sequence 21 , 24 . When the facial nerve is adjacent to the tumor, it appears as a low signal overlapping with the tumor capsule, and its continuity can be verified using dynamic videos. Third-party software enables the 3D reconstruction of the facial nerve, parotid duct, and tumor, providing high-precision imaging evidence of the facial nerve-tumor spatial relationship for the preoperative evaluation of parotid gland tumors. Based on this information, surgeons can clarify the spatial relationship between the tumor and the nerve, develop personalized surgical strategies, and improve the efficiency of doctor-patient communication. Meanwhile, patients can form objective perceptions of surgical expectations and potential complications through this imaging evidence. The limitations of this study include the small sample size, which is predominantly composed of benign tumors; this may restrict the breadth of evaluation for malignant tumors or complex cases. Additionally, although the driven equilibrium technique of the United Imaging FSE-Matrix-3D sequence significantly suppresses motion artifacts, the relatively long scan duration (approximately 5 minutes) still poses challenges for its application in children or patients who are unable to cooperate during the examination. In summary, this study employed the innovative FSE-MX-3D sequence combined with 32-channel head coil and 8-channel dedicated carotid surface coil technology to systematically evaluate its application value in preoperative facial nerve localization for patients with parotid gland tumors. The results demonstrated that this technology can clearly visualize the main trunk and branches of the facial nerve with high resolution, effectively shorten the scanning time, and significantly improve the visualization rate of second-order branches. The consistency between preoperative MRI evaluations and intraoperative verification results further confirmed the accuracy of this method in assessing the spatial relationship between the facial nerve and tumors. This technological breakthrough provides important imaging support for the surgical planning of parotid gland tumors, helping surgeons accurately identify the course of the facial nerve, optimize surgical strategies, and reduce the risk of facial nerve injury. In the future, through further sample expansion and multi-center studies, this technology is expected to become an important tool for preoperative image navigation and promote the development of precision surgery. Declarations Patient consent for publication Not applicable. Consent for publication All the authors gave their consent for publication. Conflict of Interest Statement The authors declare that they have no competing interests. Funding This project was supported by Basic Research Program of Shenzhen Innovation Council (JCYJ20250604183723030); Guangdong Provincial Medical Science and Technology Research Fund (A2024488), Shenzhen Clinical Medical Research Center for Oral Diseases (Grant No. 20210617170745001-SCRC202201001), and Sanming Project of Medicine in Shenzhen (SZSM202111012, Oral and Maxillofacial Surgery Team, Professor Yu Guangyan, Peking University Hospital of Stomatology), Shenzhen Fund for Guangdong Provincial High-level Clinical Key Specialties (SZGSP008). Author Contribution B.L. and G.Y.H. (co-first authors) proposed the study concept, designed the study protocol, led data analysis/interpretation, and drafted the manuscript; S.J.W., S.Y.S., and Y.D.Y. conducted data acquisition and edited technical details in the manuscript; F.W. assisted in data acquisition, coordinated patient scheduling, polished intraoperative procedure descriptions, and oversaw data quality control; X.H. and H.J.Y. participated in data quality control, assisted in data analysis, designed the statistical plan, performed statistical analysis, and reviewed statistical results; G.X.C. and H.Y. (co-corresponding authors) supervised the study concept/design/data analysis, provided critical manuscript revisions; all authors reviewed and approved the final manuscript. Data Availability All data are present in the manuscript. Additional data related to this paper may be requested from the corresponding author. References Moore, M. G. et al. Controversies in the Workup and Surgical Management of Parotid Neoplasms. Otolaryngol. Head Neck Surg. 164 , 27–36. 10.1177/0194599820932512 (2021). Aasen, M. H., Hutz, M. J., Yuhan, B. T. & Britt, C. J. Deep Lobe Parotid Tumors: A Systematic Review and Meta-analysis. Otolaryngol. Head Neck Surg. 166 , 60–67. 10.1177/01945998211009235 (2022). Zoccali, F. et al. Clinico-histopathological review of 255 patients who underwent parotidectomy for pleomorphic adenoma: a 10-year retrospective study-a proposal for an optimal diagnostic and therapeutic algorithm for patients with recurrent pleomorphic adenoma. Eur. Arch. Otorhinolaryngol. 280 , 3329–3335. 10.1007/s00405-023-07897-y (2023). Guntinas-Lichius, O. et al. Management of the facial nerve in parotid cancer: preservation or resection and reconstruction. Eur. Arch. Otorhinolaryngol. 275 , 2615–2626. 10.1007/s00405-018-5154-6 (2018). Kang, Y. J., Cho, J. H. & Hwang, S. H. Diagnostic value of various criteria for deep lobe involvement in radiologic studies with parotid mass: a systematic review and meta-analysis. Radiol. Med. 127 , 1124–1133. 10.1007/s11547-022-01540-2 (2022). Guenette, J. P. et al. MR Imaging of the Extracranial Facial Nerve with the CISS Sequence. AJNR Am. J. Neuroradiol. 40 , 1954–1959. 10.3174/ajnr.A6261 (2019). Qin, Y., Zhang, J., Li, P. & Wang, Y. 3D double-echo steady-state with water excitation MR imaging of the intraparotid facial nerve at 1.5T: a pilot study. AJNR Am. J. Neuroradiol. 32 , 1167–1172. 10.3174/ajnr.A2480 (2011). Kim, Y. et al. Three-dimensional double-echo steady-state with water excitation magnetic resonance imaging to localize the intraparotid facial nerve in patients with deep-seated parotid tumors. Neuroradiology 63 , 731–739. 10.1007/s00234-021-02673-3 (2021). Hu, L. H. et al. Direct visualization of intraparotid facial nerve assisting in parotid tumor resection. J. Craniomaxillofac. Surg. 52 , 659–665. 10.1016/j.jcms.2024.03.014 (2024). House, J. W. & Brackmann, D. E. Facial nerve grading system. Otolaryngol. Head Neck Surg. 93 , 146–147. 10.1177/019459988509300202 (1985). Mugler, J. P. 3 Optimized three-dimensional fast-spin-echo MRI. J. Magn. Reson. Imaging . 39 , 745–767. 10.1002/jmri.24542 (2014). Li, G. et al. Evaluation of an accelerated 3D modulated flip-angle technique in refocused imaging with an extended echo-train sequence with compressed sensing for imaging of the knee: comparison with routine 2D MRI sequences. Clin. Radiol. 76 , 158e113–158e118. 10.1016/j.crad.2020.10.012 (2021). Sui, H. et al. Accelerating Knee MRI: 3D Modulated Flip-Angle Technique in Refocused Imaging with an Extended Echo Train and Compressed Sensing. J. Pain Res. 15 , 577–590. 10.2147/JPR.S345210 (2022). Busse, R. F. Reduced RF power without blurring: correcting for modulation of refocusing flip angle in FSE sequences. Magn. Reson. Med. 51 , 1031–1037. 10.1002/mrm.20056 (2004). Oh, J. et al. Application of 3D Fast Spin-Echo T1 Black-Blood Imaging in the Diagnosis and Prognostic Prediction of Patients with Leptomeningeal Carcinomatosis. AJNR Am. J. Neuroradiol. 39 , 1453–1459. 10.3174/ajnr.A5721 (2018). Yoon, D., Antil, N., Biswal, S. & Lutz, A. M. A robust 3D fast spin-echo technique for fast examination of the brachial plexus. Skeletal Radiol. 51 , 1865–1872. 10.1007/s00256-022-04021-9 (2022). Kijowski, R. et al. Knee imaging: Rapid three-dimensional fast spin-echo using compressed sensing. J. Magn. Reson. Imaging . 45 , 1712–1722. 10.1002/jmri.25507 (2017). Madelin, G., Chang, G., Otazo, R., Jerschow, A. & Regatte, R. R. Compressed sensing sodium MRI of cartilage at 7T: preliminary study. J. Magn. Reson. 214 , 360–365. 10.1016/j.jmr.2011.12.005 (2012). Mugler, J. P. 3 et al. Optimized single-slab three-dimensional spin-echo MR imaging of the brain. Radiology 216 , 891–899. 10.1148/radiology.216.3.r00au46891 (2000). Sartoretti-Schefer, S., Kollias, S., Wichmann, W. & Valavanis, A. 3D T2-weighted fast spin-echo MRI sialography of the parotid gland. Neuroradiology 41 , 46–51. 10.1007/s002340050704 (1999). Takahashi, N., Okamoto, K., Ohkubo, M. & Kawana, M. High-resolution magnetic resonance of the extracranial facial nerve and parotid duct: demonstration of the branches of the intraparotid facial nerve and its relation to parotid tumours by MRI with a surface coil. Clin. Radiol. 60 , 349–354. 10.1016/j.crad.2004.06.018 (2005). Attye, A. et al. Parotid gland tumours: MR tractography to assess contact with the facial nerve. Eur. Radiol. 26 , 2233–2241. 10.1007/s00330-015-4049-9 (2016). Fujii, H. et al. Visualization of the Peripheral Branches of the Mandibular Division of the Trigeminal Nerve on 3D Double-Echo Steady-State with Water Excitation Sequence. AJNR Am. J. Neuroradiol. 36 , 1333–1337. 10.3174/ajnr.A4288 (2015). Fujii, H. et al. Localization of Parotid Gland Tumors in Relation to the Intraparotid Facial Nerve on 3D Double-Echo Steady-State with Water Excitation Sequence. AJNR Am. J. Neuroradiol. 40 , 1037–1042. 10.3174/ajnr.A6078 (2019). Seider, N. A. et al. Accuracy and reliability of diffusion imaging models. Neuroimage 254 , 119138. 10.1016/j.neuroimage.2022.119138 (2022). Liang, D., Liu, B., Wang, J. & Ying, L. Accelerating SENSE using compressed sensing. Magn. Reson. Med. 62 , 1574–1584. 10.1002/mrm.22161 (2009). Lustig, M., Donoho, D., Pauly, J. M. & Sparse, M. R. I. The application of compressed sensing for rapid MR imaging. Magn. Reson. Med. 58 , 1182–1195. 10.1002/mrm.21391 (2007). Tsang, J. C. et al. Visualization of normal intra-parotid facial nerve on MR: BTFE or GRASS? Clin. Radiol. 64 , 1115–1118. 10.1016/j.crad.2009.03.012 (2009). Li, C., Li, Y., Zhang, D., Yang, Z. & Wu, L. 3D-FIESTA MRI at 3 T demonstrating branches of the intraparotid facial nerve, parotid ducts and relation with benign parotid tumours. Clin. Radiol. 67 , 1078–1082. 10.1016/j.crad.2012.03.014 (2012). Zhao, Y. & Yang, B. Value of Visualization of the Intraparotid Facial Nerve and Parotid Duct Using a Micro Surface Coil and Three-Dimensional Reversed Fast Imaging With Steady-State Precession and Diffusion-Weighted Imaging Sequence. J. Craniofac. Surg. 29 , e754–e757. 10.1097/SCS.0000000000004704 (2018). Niemela, R. K., Paakko, E., Suramo, I., Takalo, R. & Hakala, M. Magnetic resonance imaging and magnetic resonance sialography of parotid glands in primary Sjogren's syndrome. Arthritis Rheum. 45 , 512–518. 10.1002/1529-0131(200112)45:6%3C512::aid-art376%3E3.0.co;2-r (2001). Sun, Q., Dong, M. J., Tao, X. F., Jiang, M. D. & Yang, C. Selection and application of coils in temporomandibular joint MRI. Dentomaxillofac Radiol. 49 , 20190002. 10.1259/dmfr.20190002 (2020). Ishibashi, M. et al. Capsule of parotid gland tumor: evaluation by 3.0 T magnetic resonance imaging using surface coils. Acta Radiol. 51 , 1103–1110. 10.3109/02841851.2010.519716 (2010). Ishibashi, M. et al. The ability to identify the intraparotid facial nerve for locating parotid gland lesions in comparison to other indirect landmark methods: evaluation by 3.0 T MR imaging with surface coils. Neuroradiology 52 , 1037–1045. 10.1007/s00234-010-0718-1 (2010). Additional Declarations No competing interests reported. Supplementary Files S11.mp4 S12.mp4 S13.mp4 S21.mp4 S22.mp4 S31.mp4 S32.mp4 S41.mp4 S42.mp4 S43.mp4 Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 05 May, 2026 Reviewers agreed at journal 23 Apr, 2026 Reviewers agreed at journal 23 Apr, 2026 Reviewers invited by journal 23 Apr, 2026 Editor invited by journal 11 Dec, 2025 Editor assigned by journal 10 Dec, 2025 Submission checks completed at journal 10 Dec, 2025 First submitted to journal 07 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8303262","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":633616225,"identity":"ff9adef4-6d64-458d-b81e-e68dbf427339","order_by":0,"name":"Bo Lin","email":"","orcid":"","institution":"Peking University Shenzhen Hospital","correspondingAuthor":false,"prefix":"","firstName":"Bo","middleName":"","lastName":"Lin","suffix":""},{"id":633616226,"identity":"70adf05d-e7c5-457a-9e0c-4d74c6dbbe19","order_by":1,"name":"Guanyong He","email":"","orcid":"","institution":"Peking University Shenzhen Hospital","correspondingAuthor":false,"prefix":"","firstName":"Guanyong","middleName":"","lastName":"He","suffix":""},{"id":633616227,"identity":"cc010bcf-d778-4aba-ba1b-656bd0eff66b","order_by":2,"name":"Shunji Wang","email":"","orcid":"","institution":"Peking University Shenzhen Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shunji","middleName":"","lastName":"Wang","suffix":""},{"id":633616228,"identity":"7ae5a96c-1ae1-4549-987c-2a264c9c2ed4","order_by":3,"name":"Shiyue Shen","email":"","orcid":"","institution":"Peking University Shenzhen Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shiyue","middleName":"","lastName":"Shen","suffix":""},{"id":633616229,"identity":"8799775e-2ef8-4d99-bf2d-0d3e35a81bc6","order_by":4,"name":"Feng Wang","email":"","orcid":"","institution":"Peking University Shenzhen Hospital","correspondingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Wang","suffix":""},{"id":633616230,"identity":"f0e2e748-f207-43c2-8ff8-fe8abce52f94","order_by":5,"name":"Xia Hong","email":"","orcid":"","institution":"Peking University Shenzhen Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xia","middleName":"","lastName":"Hong","suffix":""},{"id":633616231,"identity":"1e14aa3e-de3f-458c-b11f-d87a283953fb","order_by":6,"name":"Youdan Yao","email":"","orcid":"","institution":"Peking University Shenzhen Hospital","correspondingAuthor":false,"prefix":"","firstName":"Youdan","middleName":"","lastName":"Yao","suffix":""},{"id":633616232,"identity":"8609232d-42e2-4a5f-849d-d0a3b8822b2e","order_by":7,"name":"Huijun Yang","email":"","orcid":"","institution":"Peking University Shenzhen Hospital","correspondingAuthor":false,"prefix":"","firstName":"Huijun","middleName":"","lastName":"Yang","suffix":""},{"id":633616233,"identity":"e8a6cbdd-47b7-4bb5-b66a-71d2275aba01","order_by":8,"name":"Guanxun Cheng","email":"","orcid":"","institution":"Peking University Shenzhen Hospital","correspondingAuthor":false,"prefix":"","firstName":"Guanxun","middleName":"","lastName":"Cheng","suffix":""},{"id":633616234,"identity":"a02008c9-f116-429d-98ac-bf3cd647d9fc","order_by":9,"name":"Hongyu Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYBACgwNgSkKOn70HzOLhI1KLhbFkzxkGBiCHh41ILRWJG27kgLUwENZyI8fwc8EvicSGm28PPv6YYyfDxsD88NENPFrsb+QYS8/skzBunJ2XbHBwWzLQYWzGxjn4bTGQ5u2RkG2WzjGTOLiNGaiFh02agBbj30AtjG2SZ0Ba6onSYibN80NCsUeCB6TlMBFazjwrs+ZtkDCW4MkxNji77TgPGzMhvxxP3nyb50+dnP3xM4YPKrdV2/OzNz98jE8Lg0CGAQNjG7IIMz7lIMB//AEDwx9CqkbBKBgFo2BEAwDWeksfkJFXGgAAAABJRU5ErkJggg==","orcid":"","institution":"Peking University Shenzhen Hospital","correspondingAuthor":true,"prefix":"","firstName":"Hongyu","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2025-12-08 03:53:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8303262/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8303262/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108808175,"identity":"1142f94e-6674-4169-b5fe-547f782eb3c0","added_by":"auto","created_at":"2026-05-08 15:40:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1586698,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImaging and intraoperative findings of case 1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA-B. MRI scans adjusted to optimal planes depict the facial nerve (red arrows) and its topographic relationship with the right parotid tumor. C-D. 3D models, with color differentiation (parotid gland: yellow; tumor: black; facial nerve: red; retromandibular vein: blue; mandible: purple; masseter muscle: light red), demonstrate facial nerve branches closely apposed to the tumor`s anteroinferior edge. E. intraoperative view of tumor exposure demonstrates the facial nerve (green arrows) alongside the parotid tumor (blue arrows). F. intraoperative view post-tumor resection reveals the facial nerve in the deep plane.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8303262/v1/0074cb0bf1e02349d3a76310.png"},{"id":108808014,"identity":"43536a45-ebd2-4176-b08b-da83bb311348","added_by":"auto","created_at":"2026-05-08 15:38:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1677143,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFacial nerve-tumor interaction in case 2\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA-B. MRI scans adjusted to optimal planes show the facial nerve (red arrows) and its spatial relationship with the left parotid tumor. C-D. 3D reconstructed models (with the same color coding as Figure 1) depict parotid gland, tumor, facial nerve, retromandibular vein, mandible, and masseter muscle, with facial nerve branches closely abutting the tumor`s medial surface. E. intraoperative view during tumor exposure highlights the facial nerve (green arrows) and parotid tumor (blue arrows). F. After tumor removal, the view shows the facial nerve in the deep operative area.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8303262/v1/84da5fe76f8088647fcb3a87.png"},{"id":108808189,"identity":"b6724944-1346-47b5-80ff-916e5916d894","added_by":"auto","created_at":"2026-05-08 15:40:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1686961,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFacial nerve crossing vessel in case 3\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA-B: MRI scans (adjusted to optimal planes) present the facial nerve (red arrows) and its spatial arrangement with the left parotid tumor. C-D: 3D models depict the parotid gland, tumor, facial nerve, retromandibular vein, mandible, and masseter muscle, with facial nerve branches lying near the tumor`s deep surface and traversing the retromandibular vein. E: Intraoperative tumor exposure displays the facial nerve (green arrows) and parotid tumor (blue arrows). F: Following tumor resection, the view exhibits the facial nerve in the deep region.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8303262/v1/26aba1651feebadd8b25718e.png"},{"id":108809631,"identity":"50cf47d9-7a7a-477d-854a-8b3d26a88d72","added_by":"auto","created_at":"2026-05-08 15:54:30","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1518233,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eParotid duct visualization in case 4\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA-B: MRI scans with optimized parameters show parotid ducts (yellow arrows) exhibiting high signal intensity, driven by static intraductal fluid on the SE sequence, alongside their relationship with the left parotid tumor. C-D: 3D models illustrate the parotid gland, tumor, and parotid ducts, showing tumor-induced duct compression and convergence of intraparotid branch ducts into the main duct; E: Intraoperative tumor exposure displays the tumor and parotid ducts (yellow arrows). E: Intraoperative view of tumor exposure displays the tumor and parotid ducts (yellow arrows). F: Intraoperative view after tumor resection reveals parotid duct anatomy within the surgical bed.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8303262/v1/832fadf7d37fb673c4ad4653.png"},{"id":109069254,"identity":"b11bddd1-1ccc-4c68-b8fb-ae630d95c1af","added_by":"auto","created_at":"2026-05-12 10:22:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9090063,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8303262/v1/2e014c26-ea8f-4765-8758-129bc3eaeee0.pdf"},{"id":109067895,"identity":"a6cfebe2-e63d-43f3-b5fc-36997d454f48","added_by":"auto","created_at":"2026-05-12 10:02:31","extension":"mp4","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14627288,"visible":true,"origin":"","legend":"","description":"","filename":"S11.mp4","url":"https://assets-eu.researchsquare.com/files/rs-8303262/v1/eb6b5599cd470c4620b1e35c.mp4"},{"id":108810053,"identity":"e50b6264-ea0a-4c99-8000-1515d2a9b95a","added_by":"auto","created_at":"2026-05-08 15:57:16","extension":"mp4","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":14090042,"visible":true,"origin":"","legend":"","description":"","filename":"S12.mp4","url":"https://assets-eu.researchsquare.com/files/rs-8303262/v1/c77e4309ae2222c35d676568.mp4"},{"id":108810019,"identity":"b66996b4-e3cc-4eaf-b9b3-51cd84d43170","added_by":"auto","created_at":"2026-05-08 15:56:53","extension":"mp4","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":6961680,"visible":true,"origin":"","legend":"","description":"","filename":"S13.mp4","url":"https://assets-eu.researchsquare.com/files/rs-8303262/v1/5a940e6fe6ed13c5c692ead4.mp4"},{"id":108808033,"identity":"eecf5e6e-2b7a-4ecf-92b0-672023d3f5c8","added_by":"auto","created_at":"2026-05-08 15:39:20","extension":"mp4","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":2727183,"visible":true,"origin":"","legend":"","description":"","filename":"S21.mp4","url":"https://assets-eu.researchsquare.com/files/rs-8303262/v1/4304978abf64d63f3bb069ac.mp4"},{"id":108808178,"identity":"b81dae80-1124-4f45-9403-0469e5d1b07e","added_by":"auto","created_at":"2026-05-08 15:40:17","extension":"mp4","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":5905841,"visible":true,"origin":"","legend":"","description":"","filename":"S22.mp4","url":"https://assets-eu.researchsquare.com/files/rs-8303262/v1/83b05d92c981addbcf4af341.mp4"},{"id":108808188,"identity":"8f13626c-a9de-4b9e-af62-b01364ef5a73","added_by":"auto","created_at":"2026-05-08 15:40:19","extension":"mp4","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":11890152,"visible":true,"origin":"","legend":"","description":"","filename":"S31.mp4","url":"https://assets-eu.researchsquare.com/files/rs-8303262/v1/045860429a4a8d7507a2b731.mp4"},{"id":108977027,"identity":"bb60b45d-3038-4c3d-846a-8f0f8ee70368","added_by":"auto","created_at":"2026-05-11 11:30:01","extension":"mp4","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":6432602,"visible":true,"origin":"","legend":"","description":"","filename":"S32.mp4","url":"https://assets-eu.researchsquare.com/files/rs-8303262/v1/85a1383d1c71c9ce8174f380.mp4"},{"id":108808137,"identity":"a142b748-9d24-4f9d-8066-da68f6e51447","added_by":"auto","created_at":"2026-05-08 15:40:03","extension":"mp4","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":15275045,"visible":true,"origin":"","legend":"","description":"","filename":"S41.mp4","url":"https://assets-eu.researchsquare.com/files/rs-8303262/v1/8bee67581d902aa7f2cc5cbf.mp4"},{"id":108976988,"identity":"18ea8309-e6d9-43f4-9f34-d305e3a48b5a","added_by":"auto","created_at":"2026-05-11 11:29:51","extension":"mp4","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":9945602,"visible":true,"origin":"","legend":"","description":"","filename":"S42.mp4","url":"https://assets-eu.researchsquare.com/files/rs-8303262/v1/13c497927c434c68a9f93d38.mp4"},{"id":108808177,"identity":"4b53b0fa-f5a6-41b8-a409-c00fd1de5de5","added_by":"auto","created_at":"2026-05-08 15:40:17","extension":"mp4","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":8449041,"visible":true,"origin":"","legend":"","description":"","filename":"S43.mp4","url":"https://assets-eu.researchsquare.com/files/rs-8303262/v1/45ee5e0df6f6dfe1b6e9b3e5.mp4"}],"financialInterests":"No competing interests reported.","formattedTitle":"Optimized FSE-MX-3D Sequence Combined with Carotid Surface Coil for Preoperative Localization of the Facial Nerve in Patients with Parotid Gland Tumors","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSalivary gland tumors account for 3%-6% of head and neck tumors \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, with parotid gland tumors accounting for 70%-85% of these \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Surgical resection is the gold standard for management, but facial nerve injury remains a core challenge. Zoccali et al. \u003csup\u003e3\u003c/sup\u003e reviewed 255 cases of parotid gland surgery and found that the incidences of temporary and permanent facial nerve palsy were 37.6% and 2.7%, respectively. For deep-lobe tumors (with a malignancy rate of 26.6%) or malignant tumors, the risk of permanent palsy increases significantly to 15%-20% \u003csup\u003e4\u003c/sup\u003e. Such complications not only affect basic functions like eye closure and smiling, but may also lead to dry eye symptoms and a decline in quality of life, as reflected by a 20% reduction in scores on the 36-Item Short Form Health Survey\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Existing imaging techniques have limitations: traditional CT/MRI has a sensitivity of only 12.5% for locating deep-lobe tumors and cannot reliably identify facial nerve branches with a diameter of \u0026lt;\u0026thinsp;0.5mm \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. This makes intraoperative nerve protection highly dependent on the surgeon's experience. How to reduce the risk of injury through accurate preoperative facial nerve localization has become a key issue urgently requiring resolution in oral and maxillofacial surgery.\u003c/p\u003e \u003cp\u003eIn recent years, various high-resolution MRI sequences have been applied to facial nerve imaging. Three-dimensional fast imaging using steady-state acquisition (3D-FIESTA) can clearly outline the nerve contour due to its high T2/T1 contrast, but it is sensitive to motion artifacts \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Three-dimensional double-echo steady-state with water excitation (3D-DESS-WE) achieves 0.4mm isotropic resolution in the parotid region, and its nerve-tumor contrast is significantly superior to that of traditional T2 sequences \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. This technique can visualize the main trunk and first-order branches of the facial nerve in healthy volunteers with a 100% visualization rate, yet the detection rate for second-order branches is only 36%-48% \u003csup\u003e8\u003c/sup\u003e. Diffusion-weighted imaging (DWI) combined with surface coils can improve the visualization rate of branches but is prone to interference from susceptibility artifacts \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Despite their respective advantages, these techniques share common challenges in clinical practice: 1) balancing scanning time and resolution is challenging (e.g., DESS requires more than 12 minutes) \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e; 2) the visualization rate for second-order branches with a diameter\u0026thinsp;\u0026lt;\u0026thinsp;0.3mm is generally below 50% \u003csup\u003e8\u003c/sup\u003e; 3) motion artifacts render 15%-20% of images unusable \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. These bottlenecks limit the accurate preoperative assessment of the spatial relationship between the nerve and the tumor, making intraoperative nerve protection dependent on the surgeon's experience, with a nerve displacement identification accuracy of only 68%.\u003c/p\u003e \u003cp\u003eTo address these technical bottlenecks, we employed an optimized FSE-MX-3D sequence (modulated flip angle imaging technology, MATRIX) on United Imaging MRI systems. This technology features intelligently designed fast spin echo flip angle combinations coupled with optimized reconstruction protocols, allowing adjustment of radiofrequency pulse angles according to clinical needs to optimize tissue contrast in terms of T1, T2, and proton density (PD). Combined with the unique advantages of 32-channel head coil and 8-channel dedicated carotid surface coil, we have innovatively applied this sequence to visualize fine structures. The sequence enhances data acquisition efficiency through a non-traditional K-space sampling pattern, achieving directional signal enhancement in regions of interest around the facial nerve. Unlike previous studies that mostly used single head coils, we significantly improved the signal-to-noise ratio for visualizing the facial nerve and its accompanying blood vessels by leveraging the near-field signal enhancement effect of this combined head coil and dedicated carotid surface coil, along with parameter configurations of ultrashort echo time (TE) and longer echo train length (ETL). Notably, by optimizing the sampling order with a compressed sensing algorithm, the scanning time has been shortened to one-third of that of the traditional DESS sequence while maintaining high resolution. To our knowledge, this is the first study to apply such an optimized FSE sequence in combination with this combined coil system for visualizing fine structures within the parotid gland. Preliminary experiments indicate that this method not only maintains the imaging quality of the main nerve trunk but also exhibits unique advantages in visualizing the second-order branches of the facial nerve due to its enhanced ability to capture anatomical details.\u003c/p\u003e \u003cp\u003eThis study utilizes a prospective cross-sectional design to systematically evaluate, for the first time, the diagnostic efficacy of this optimized sequence in patients with parotid gland tumors. It focuses on verifying the feasibility of maintaining or even improving the visualization performance of facial nerve branches while shortening the scanning time. This technology provides a new tool for identifying important surgery-related structures within the parotid gland, which is in line with the core principles of precise image-guided surgery.\u003c/p\u003e"},{"header":"Material and methods","content":"\n\u003ch3\u003e1. Study Design\u003c/h3\u003e\n\u003cp\u003e This is a prospective cross-sectional study, approved by the Ethics Committee of Peking University Shenzhen Hospital (Approval No.: PKUSZH-IRB (Res) [2024] 060; in compliance with the Declaration of Helsinki). Conducted at a single oral and maxillofacial surgery center from March 2024 to March 2025, the study aims to validate the diagnostic efficacy of the FSE-MX-3D sequence equipped on United Imaging uMR 780 3T MRI system, combined with a 32-channel head coil and an 8-channel dedicated carotid surface coil, for preoperative localization of the facial nerve in patients with parotid gland tumors.\u003c/p\u003e\n\u003ch3\u003e2. Inclusion and Exclusion Criteria\u003c/h3\u003e\n\u003cp\u003e2.1. Inclusion Criteria:\u003c/p\u003e \u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eAged between 18 and 80 years.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eParotid gland tumors detected by clinical physical examination, further confirmed by ultrasound, CT, or other imaging modalities.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eScheduled to undergo surgical treatment for parotid gland tumors.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e Voluntarily signed the informed consent form after fully understanding the study purpose, procedures, and potential risks.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e \u003cp\u003e2.2. Exclusion Criteria:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePresence of intraoral metallic substances that may interfere with MRI imaging, such as porcelain-fused-to-metal crowns, metal crowns, or dental implants.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHistory of recurrent parotid gland tumors or previous ipsilateral parotid gland surgery.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eComorbidities such as nodular Sj\u0026ouml;gren`s syndrome or parotid abscess.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHistory of radiotherapy or chemotherapy in the head and neck region.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePresence of cardiac pacemakers, intracranial metal fragments, or other conditions that may affect the safety or image quality of MRI examinations.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSevere and uncontrolled systemic diseases (e.g., hypertension, heart disease, hepatic or renal insufficiency) that contraindicate surgery or MRI examinations.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eUncontrolled severe mental disorders that prevent cooperation with examinations.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFemale patients who are pregnant or lactating.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e\n\u003ch3\u003e3. MRI Imaging Technology and Scanning Procedures\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.1 MRI System Configuration and Coil Selection\u003c/h2\u003e \u003cp\u003eThis study used the United Imaging uMR 780 3T MRI system (gradient field strength: Maximum Gradient Amplitude: 45 mT/m and Maximum Slew Rate: 200 T/m/s) for preoperative examinations in all patients scheduled for parotid gland tumor resection. To ensure maxillofacial region-specific imaging quality, a 32-channel head coil was used for signal acquisition of the cranial and parotid regions, while an 8-channel dedicated carotid surface coil was applied to the maxillofacial region; the two coils were combined to achieve coverage of the maxillofacial region. The system was integrated with dynamic shimming technology and three-dimensional motion correction algorithms, which collectively establish a high-resolution and magnetically stable imaging environment, laying a hardware foundation for precise visualization of parotid gland tissues and facial nerve branches.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Patient Preparation and Scanning Control\u003c/h2\u003e \u003cp\u003eAfter obtaining written informed consent, all subjects underwent standardized metal screening: a handheld metal detector (Metrasens Pro-vG2) was utilized to exclude MRI-incompatible implants, in strict compliance with the ASTM F2503-20 standard for MRI safety. Subsequently, subjects were positioned in a supine posture, with their heads placed inside the 32-channel head coil and their necks closely fitted with the 8-channel dedicated carotid surface coil (ensuring the coil-skin distance was less than 2 cm to optimize near-field signal reception). Head motion was restricted using a vacuum fixation bag (S\u0026amp;G VAC-LOK), and the mandible was further secured with a chin strap (maintaining the Frankfort horizontal plane in a parallel orientation to the scanner bore). To mitigate motion artifacts and ambient noise interference, subjects wore silicone earplugs (3M\u0026trade; E-A-Rsoft\u0026trade;) for passive noise isolation, followed by active noise-canceling headphones (OptoActive II) over the ears. Standardized 65 dB voice guidance was played synchronously through the headphones. Radiographers also instructed subjects to minimize swallowing through a pre-scan breathing training protocol (adopting rhythmic breathing with a 4-second cycle).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e4. Scanning Protocol and Parameter Settings\u003c/h3\u003e\n\u003cp\u003eLocalizer: Three-plane fast gradient echo (TR/TE\u0026thinsp;=\u0026thinsp;20/2.5 ms, slice thickness\u0026thinsp;=\u0026thinsp;5 mm).\u003c/p\u003e \u003cp\u003eMain sequence: FSE-MX-3D, covering the stylomastoid foramen to the angle of the mandible. The specific imaging parameters are as follows:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eSequence type: FSE-MX-3D sequence\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEcho time (TE): 382.92 ms\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eRepetition time (TR): 2000 ms\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFlip angle mode: T2 mode, with a maximum flip angle of 150\u0026deg; and a minimum flip angle of 21\u0026deg;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEcho train length: 180\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDriven equilibrium: 0.8\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eVoxel size: 0.82 mm \u0026times; 0.82 mm \u0026times; 0.80 mm\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eField of view (FOV): Adjusted appropriately according to the size of the patient`s parotid region to fully cover the parotid gland and surrounding relevant structures\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eScanning time: Approximately 4 minutes and 30 seconds\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThese parameters were determined based on references to relevant literature and preliminary pre-experiments to achieve optimal imaging of the facial nerve.\u003c/p\u003e\n\u003ch3\u003e5. Scanning Process and Quality Control\u003c/h3\u003e\n\u003cp\u003eDuring the scanning process, professional technicians closely monitored the scanning status and patient conditions. Immediately after each scan, a preliminary inspection of the images was conducted. If artifacts, motion blur, or other quality issues were detected, the patient`s position or scanning parameters were adjusted promptly, and the scan was repeated. To ensure the stability of the equipment and the consistency of image quality, the MRI system underwent routine calibration once a week. Additionally, the head coil and the dedicated carotid surface coil were inspected and debugged before each scan to confirm their optimal performance. After image acquisition, the data were transmitted to a designated workstation for subsequent processing and analysis.\u003c/p\u003e\n\u003ch3\u003e6. Image Analysis Methods\u003c/h3\u003e\n\u003cp\u003eRaw DICOM data were de-identified and transferred to the United Imaging uWS-MR workstation (Version 3.2.1). To optimize image quality for subsequent anatomical analysis (e.g., facial nerve identification), the workstation's built-in automated preprocessing pipeline was applied. This included advanced 3D noise reduction filtering to minimize thermal noise artifacts, followed by automated geometric distortion correction to ensure high spatial fidelity of the images. Following preprocessing, the optimized image data were utilized for multi-planar reconstruction (MPR): standard orthogonal views including coronal, sagittal, and axial planes were generated first, and planar orientations such as oblique planes were dynamically adjusted as needed to align with the anatomical course of facial nerve branches and parotid tumor boundaries.\u003c/p\u003e \u003cp\u003eFacial nerve identification followed an anatomy-driven protocol: Observers used the stylomastoid foramen as a reference landmark to track continuous hypointense structures on axial T2-weighted images (T2WI), verifying the continuity of their course slice by slice. The parotid parenchyma appeared as a uniform slightly high signal intensity, while nerve fascicles showed moderate low signal intensity, the retromandibular vein presented marked hypointensity due to flow void effect, and the parotid duct exhibited marked hyperintensity due to containing fluid with high T2 value and slow flow. These structures together formed clear contrast effects.\u003c/p\u003e \u003cp\u003eAll suspected branches were confirmed in orthogonal sagittal and coronal reconstructed images via multiplanar dynamic verification, with maximum intensity projection (MIP) performed to exclude vascular interference. When nerves were adjacent to the tumor area, 3D curved planar reconstruction (slice thickness 0.5 mm) was used to quantify the minimum nerve-tumor distance, and spatial relationships were recorded as follows:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eDistant: The distance between the facial nerve and the tumor was \u0026ge;\u0026thinsp;3 mm;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eContact: A segment of the facial nerve merged with the tumor boundary (indistinguishable) but involved\u0026thinsp;\u0026lt;\u0026thinsp;50% of the tumor circumference;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEncasement: A segment of the facial nerve surrounded\u0026thinsp;\u0026ge;\u0026thinsp;50% of the tumor circumference;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eInfiltration: The facial nerve penetrated into the tumor, with signal indistinguishable from the tumor.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eAll cases were graded by two independent evaluators (a neuroradiologist with 12 years of experience and an oral and maxillofacial surgeon with 10 years of experience) using the following scoring criteria:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eScore 1: Only the main trunk is identifiable, with interrupted branch continuity;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eScore 2: \u0026ge; 50% of first-order branches are continuously visualized, with partial absence of second-order branches;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eScore 3: Complete visualization of the main trunk and \u0026ge;\u0026thinsp;2 second-order branches.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eEvaluation consistency was measured by Cohen's Kappa coefficient and 95% confidence interval.\u003c/p\u003e\n\u003ch3\u003e7. Construction of Three-Dimensional Digital Models\u003c/h3\u003e\n\u003cp\u003eIn this study, Mimics 21.0 software was used to process patients` FSE-MX-3D data for reconstructing the three-dimensional relationships among the facial nerve, tumor, parotid gland, and mandible. First, patients` MRI data were imported into Mimics 21.0 in DICOM format, and the software automatically generated axial, sagittal, and coronal images. Next, a new mask was created under the \"Masks\" tab, and operations were performed using the mask editing tools in the segmentation toolbox. The brush shape was set to magnetic lasso, with a gradient magnitude of 0.5 and an attraction strength of 0. Then, structures of interest-including the tumor, facial nerve, parotid gland, and mandible, were segmented slice by slice on sagittal images. After segmentation, mask editing tools were used for fine adjustments to ensure segmentation accuracy.\u003c/p\u003e \u003cp\u003eBased on the segmented and adjusted data, the 3D model calculation tool was selected from the segmentation toolbox. The masks containing segmented images were chosen, image quality was set to high, and three-dimensional image reconstruction was performed. To enhance the visual effect of the models, a smoothing tool was applied to the reconstructed 3D models, with 3 iterations and a smoothing factor of 0.5. Through this process, a 3D model clearly displaying the spatial relationship between the facial nerve and parotid gland tumors was successfully created.\u003c/p\u003e \u003cp\u003eThis 3D model allows multi-directional and multi-angle observation of any cross-section, with support for zooming and rotation functions. It thus provides important visual support for precise preoperative localization, surgical incision design, and safe dissection of the facial nerve during surgery. Compared with traditional two-dimensional planar classification, this 3D model is more intuitive and accurate, as it can clearly display the morphology of the tumor capsule. It guides the complete resection of tumors and dissection of the facial nerve during surgery, significantly optimizing surgical planning and facial nerve protection strategies.\u003c/p\u003e\n\u003ch3\u003e8. Intraoperative Verification\u003c/h3\u003e\n\u003cp\u003eSurgeries were performed by experienced attending surgeons under direct vision or with the aid of a 4\u0026times; microscope. First, flaps were elevated under the parotid masseteric fascia. Subsequently, the retrograde dissection method was adopted: the location of the terminal branches of the facial nerve was identified first, followed by retrograde dissection to the temporofacial and cervicofacial trunks, and finally tracing to the main trunk of the facial nerve. Depending on specific conditions, the tumor and surrounding parotid tissue, superficial parotid lobe, or entire parotid gland were resected, while important structures such as the retromandibular vein and parotid duct were protected. During the operation, the actual course of the second-order branches, first-order branches, or main trunk of the facial nerve, as well as their positional relationship with the tumor, were recorded in detail according to the specific situation.\u003c/p\u003e \u003cp\u003eClassification of nerve-tumor relationships:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eDistant: The distance between the nerve and the tumor was \u0026ge;\u0026thinsp;3 mm (measured by intraoperative vernier calipers);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eContact: No visible gap between the nerve and the tumor, but no morphological changes in the nerve;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEncasement: The tumor surrounded\u0026thinsp;\u0026ge;\u0026thinsp;50% of the nerve circumference;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eInfiltration: The main trunk or branches of the nerve entered the tumor and could not be separated.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe conditions of the nerve and tumor were documented in the surgical records, and photographs of key areas were taken for preservation.\u003c/p\u003e \u003cp\u003eAfter the operation, the attending surgeon and the radiologist involved in image analysis jointly compared the intraoperative records with the preoperative MRI findings. The comparison included the consistency between the position of the facial nerve on preoperative MRI images, the positional relationship between the facial nerve and the tumor, and the actual intraoperative situation, so as to evaluate the accuracy of the FSE-MX-3D sequence in preoperative localization of the facial nerve in patients with parotid gland tumors.\u003c/p\u003e\n\u003ch3\u003e9. Data Collection and Management\u003c/h3\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e9.1 Data Collection Content\u003c/h2\u003e \u003cp\u003eThis study systematically collects multi-dimensional data through standardized case report forms. Demographic and clinical baseline data include: age, gender, smoking history (classified according to the WHO Framework Convention on Tobacco Control [FCTC] as current smokers [smoked\u0026thinsp;\u0026ge;\u0026thinsp;1 time in the past 30 days], former smokers [cumulative smoking\u0026thinsp;\u0026ge;\u0026thinsp;100 cigarettes and quit for \u0026gt;\u0026thinsp;30 days], and never smokers); hypertension (based on the ESC/ESH 2023 criteria: office blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;140/90 mmHg or receiving antihypertensive treatment); diabetes mellitus (according to the ADA 2023 criteria: HbA1c\u0026thinsp;\u0026ge;\u0026thinsp;6.5%, FPG\u0026thinsp;\u0026ge;\u0026thinsp;7.0 mmol/L, or 2hPG\u0026thinsp;\u0026ge;\u0026thinsp;11.1 mmol/L); tumor size and pathological nature (benign/malignant); tumor location (classified as superficial lobe, deep lobe, or trans-lobe), etc.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e9.2 Facial nerve-related data\u003c/h2\u003e \u003cp\u003eIntegrated analysis of preoperative MRI and intraoperative records is performed. The preoperative nerve visualization rate is quantitatively collected via United Imaging post-processing workstation and 3D image analysis system (Mimics Medical 21.0.0.406, Materialise NV) (visualization rate\u0026thinsp;=\u0026thinsp;number of identifiable segments found intraoperatively / number of segments visualized by MRI \u0026times; 100%). The spatial relationship between the nerve and tumor (distant, contact, encasement, infiltration) is confirmed based on intraoperative photographs and surgical records. All intraoperative imaging data are archived in DICOM format, and the topological location of the nerve (superficial/deep/trans-lobe) is cross-validated via multiplanar reconstruction.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e9.3 Data Management Methods\u003c/h2\u003e \u003cp\u003eAll collected data are entered into an electronic medical record system for unified management. Data entry personnel must undergo strict training to ensure accurate data entry. A dual data backup mechanism is established: one copy is stored on the hospital's internal server, and the other on a secure external mobile hard drive. The integrity, accuracy, and readability of backup data are regularly checked to prevent data loss or damage and ensure data security and reliability.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e10. Statistical Analysis\u003c/h3\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e10.1 Descriptive Statistics\u003c/h2\u003e \u003cp\u003eContinuous variables (age, tumor diameter) are reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median [interquartile range], based on the results of the Shapiro-Wilk normality test (W\u0026thinsp;\u0026gt;\u0026thinsp;0.9 indicates an approximately normal distribution). Categorical variables (gender, tumor location, smoking history, etc.) are presented as frequencies (percentages).\u003c/p\u003e \u003cp\u003e10.2 Analysis of Outcome Indicators\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eFacial nerve visualization rate: Cases with visualization scores of 3, 2, and 1 assigned by neuroradiologists represent clear visualization, ambiguous visualization, and unclear visualization, respectively. The visualization rates of the main trunk, first-order branches, and second-order branches of the facial nerve are calculated separately. The Clopper-Pearson exact method is used to compute 95% confidence intervals, so as to evaluate the facial nerve visualization effect of MRI imaging and estimate the overall level.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eInter-observer consistency: Cohen's Kappa coefficient is used to assess the consistency of scores (1/2/3 grading) between neuroradiologists and maxillofacial surgeons. A Kappa value\u0026thinsp;\u0026ge;\u0026thinsp;0.75 indicates good consistency, 0.4\u0026ndash;0.75 indicates moderate consistency, and \u0026lt;\u0026thinsp;0.4 indicates poor consistency.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eAll statistical analyses are performed using the professional statistical software SPSS (Version 26.0), with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eBaseline Characteristics of Patients\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA total of 60 patients were enrolled in this study. Their baseline clinical characteristics were as follows: Age ranged from 25 to 76 years, with a mean of 46.7\u0026thinsp;\u0026plusmn;\u0026thinsp;13.1 years; gender distribution was approximately balanced, with 51.7% male and 48.3% female. Regarding clinical features, 35.0% of patients had a smoking history, 20.0% had hypertension, and 10.0% had diabetes mellitus. Pathologically, 86.7% (52/60) of tumors were benign, with pleomorphic adenoma being the most common subtype (30/60, 50.0%). Malignant tumors accounted for 13.3% (8/60), predominantly mucoepidermoid carcinoma (4/60, 6.7%). The mean maximum diameter of tumors was 23.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8 mm (range: 7.1\u0026ndash;49 mm). On contrast-enhanced CT, 66.7% of tumors exhibited homogeneous enhancement, while 33.3% showed heterogeneous enhancement. Detailed data are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Characteristics of the Study Cohort\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eValues\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e46.7\u0026thinsp;\u0026plusmn;\u0026thinsp;13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGender (male/female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e31 (51.7%) / 29 (48.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSmoking history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e21 (35.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAlcohol consumption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e5 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e12 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e6 (10.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePathological type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBenign tumors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e52 (86.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u0026bull; Pleomorphic adenoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e30 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u0026bull; Warthin tumor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e12 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u0026bull; Basal cell adenoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e4 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u0026bull; Other benign*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e6 (10.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMalignant tumors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e8 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u0026bull; Mucoepidermoid carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e4 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u0026bull; Other malignancies\u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e4 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMaximum diameter (mm, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e23.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCT enhancement pattern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u0026bull; Homogeneous enhancement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e40 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u0026bull; Heterogeneous enhancement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e20 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*: Including 2 cases of lymphoepithelial cysts, 2 cases of branchial cleft cysts, 1 case of lymph node, and 1 case of venous malformation. #: Including 1 case each of adenoid cystic carcinoma, secretory carcinoma, acinar cell carcinoma, and malignant transformation of pleomorphic adenoma.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eInter-rater Reliability of MRI Facial Nerve Branch Visualization Grading\u003c/h3\u003e\n\u003cp\u003eThe main trunk of the facial nerve, from the stylomastoid foramen to the first-order branches, was clearly visualized, with a 100% visualization rate. For the clarity of second-order facial nerve branches adjacent to tumors, the grading distributions by neuroradiologists and maxillofacial surgeons were as follows: neuroradiologists graded 42 cases (70.0%) as Grade 3 (clear delineation), 12 cases (20.0%) as Grade 2 (discontinuous visualization), and 6 cases (10.0%) as Grade 1 (non-delineation); maxillofacial surgeons graded 41 cases (68.3%) as Grade 3, 11 cases (18.3%) as Grade 2, and 8 cases (13.3%) as Grade 1 (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInter-Rater Reliability of Facial Nerve Branch Visualization Grading Between Neuroradiologists and Maxillofacial Surgeons\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrading Criteria\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeuroradiologists\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaxillofacial Surgeons\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade 3 (Clear delineation)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (70.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (68.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade 2 (Discontinuous visualization)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (18.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade 1 (Non-delineation)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (13.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eConsistency analysis showed that the Cohen's Kappa coefficient for inter-rater agreement was 0.894, with a z-value of 9.11 and \u003cb\u003eP\u003c/b\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, indicating excellent consistency between the two raters. Minor discrepancies occurred in some cases, such as neuroradiologists assigning Grade 2 or 3 while surgeons graded one level lower. This may reflect neuroradiologists' richer image interpretation experience and stronger ability to capture subtle nerve signals, whereas maxillofacial surgeons were more conservative in grading when image clarity was insufficient.\u003c/p\u003e\n\u003ch3\u003ePreoperative Radiological Stratification of Tumor-Nerve Relationships\u003c/h3\u003e\n\u003cp\u003eAmong the 60 patients with parotid tumors, 4 cases (6.7%) were non-assessable for tumor-nerve relationships due to limited radiological evaluation. In the 56 assessable cases, the tumor-nerve interface was categorized as follows: 4 cases (6.7%) with tumor encasement of the facial nerve, 42 cases (70.0%) with facial nerve-tumor contact, 9 cases (15.0%) with separation between the facial nerve and tumor, and 1 case (1.7%) with facial nerve penetration into the tumor. Regarding tumor localization, 40 cases (66.7%) were in the superficial lobe of the parotid gland, 16 cases (26.7%) spanned both the superficial and deep lobes, and 4 cases (6.7%) were in the deep lobe. Detailed data are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePreoperative Radiological Stratification of Tumor-Nerve Relationships\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssessment Parameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-assessable cases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor-Nerve Interface (n\u0026thinsp;=\u0026thinsp;56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEncasement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eContact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (70.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeparation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (15.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePenetration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor Localization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuperficial lobe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrans-lobar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (26.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeep lobe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eIntraoperative Verification\u003c/h3\u003e\n\u003cp\u003eIn routine clinical practice, during parotid tumor resection, only the glandular tissue around the tumor and adjacent second-order facial nerve branches were typically dissected to verify the accuracy of preoperative MRI findings. Among the 56 patients with assessable nerve-tumor relationships, the intraoperative observations of nerve-tumor relationships were all consistent with preoperative MRI findings. For the 4 cases where preoperative MRI failed to clearly demonstrate the relationship between second-order facial nerve branches and the tumor, intraoperative dissection confirmed: 2 cases with contact between the nerve terminal and the tumor, 1 case where second-order branches could not be dissected due to the main facial nerve trunk penetrating the tumor, and the remaining 1 case with separation between the nerve and the tumor.\u003c/p\u003e\n\u003ch3\u003ePostoperative Recovery\u003c/h3\u003e\n\u003cp\u003eAmong the 8 patients with malignant tumors, 5 received postoperative radiotherapy. One patient underwent simultaneous resection of the facial nerve and tumor due to intraoperative identification of facial nerve penetration into the tumor, which was followed by postoperative facial paralysis (House-Brackmann Grade VI\u003csup\u003e10\u003c/sup\u003e); pathological examination confirmed this case as mucoepidermoid carcinoma, with no tumor recurrence observed during 9 months of follow-up after radiotherapy. All 8 patients with malignant tumors remain under continuous follow-up (planned duration: 60 months), and long-term recurrence outcomes will be reported in subsequent studies. Twelve patients developed transient facial paralysis postoperatively due to intraoperative nerve dissection, classified as House-Brackmann Grade II (n\u0026thinsp;=\u0026thinsp;4) or Grade III (n\u0026thinsp;=\u0026thinsp;8). All achieved complete recovery (House-Brackmann Grade I) within 3\u0026ndash;6 months after symptomatic treatment, including facial nerve nutrition therapy and physical therapy. Five patients experienced salivary fistula within 1 month postoperatively, all fully recovering after 1\u0026ndash;2 weeks of compression bandaging. The great auricular nerve and parotid duct were preserved in all patients.\u003c/p\u003e\n\u003ch3\u003eCase Presentation\u003c/h3\u003e\n\u003cp\u003e \u003cstrong\u003eCase 1\u003c/strong\u003e \u003cp\u003eA 29-year-old female with a right parotid gland tumor. MRI clearly showed the facial nerve emerging from the stylomastoid foramen; its second-order branches crossed the retromandibular vein anteriorly and coursed adjacent to the medial surface of the tumor, with the masseter muscle located anterior to the branches. The tumor presented as a nodule with slightly high signal intensity, which was clearly distinguishable from the slightly low signal of the facial nerve. Intraoperatively, the position of the facial nerve was consistent with preoperative MRI judgment. Pathology confirmed a pleomorphic adenoma postoperatively. The patient developed transient facial nerve dysfunction after surgery, which recovered to normal within 1 month. The radiological findings are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Supplementary videos provide dynamic demonstration of the facial nerve: Videos S1-1 \u0026amp; S1-2 showcase its course and relationship to key landmarks on MRI, while Video S1-3 presents a 3D model of the tumor-nerve relationship.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCase 2\u003c/strong\u003e \u003cp\u003eA 31-year-old male with a left parotid gland mass. Preoperative MRI clearly showed the main trunk of the facial nerve emerging from the stylomastoid foramen, coursing anteroinferiorly and dividing into the cervicofacial trunk and temporofacial trunk. The cervicofacial trunk was closely adjacent to the deep surface of the tumor and further divided into 2 third-order branches. The retromandibular vein was compressed and displaced (with stenosis) by the tumor after entering the parotid gland. On MRI, the facial nerve exhibited slightly low signal intensity-lower than the parotid gland but higher than the retromandibular vein. Based on anatomical location and signal characteristics, the main trunk, second-order, and third-order branches of the facial nerve were clearly identified, and 3D reconstruction of the parotid gland-tumor-nerve complex was completed. Intraoperatively, the cervicofacial trunk was confirmed to be closely adjacent to the deep surface of the tumor, consistent with preoperative MRI findings. After complete resection of the tumor and partial surrounding glandular tissue, pathology confirmed a pleomorphic adenoma. The patient had normal facial nerve function postoperatively. The imaging findings are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Supplementary videos dynamically illustrate the nerve-tumor relationship: Video S2-1 combines multiplanar MRI sequences to trace the facial nerve`s branching pattern and its spatial interplay with the tumor and compressed retromandibular vein. Video S2-2 provides a 3D volumetric view, rotating dynamically to showcase the tumor`s close adjacency to the cervicofacial trunk and its displaced adjacent structures.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCase 3\u003c/strong\u003e \u003cp\u003eA 36-year-old male with a left parotid gland mass. Preoperative MRI clearly delineated the main facial nerve trunk, with its second-order branches running in close proximity to the tumor\u0026rsquo;s deep surface before further dividing into two third-order branches. A segment of the retromandibular vein was positioned immediately inferior to the tumor, overlain by the crossing facial nerve. Continuous nerve tractography from the stylomastoid foramen enabled unambiguous differentiation between the nerve and surrounding glandular tissue, complemented by preoperative 3D modeling. Intraoperative findings confirmed the topographical correlation between the nerve and tumor. Pathology after resection diagnosed carcinoma ex pleomorphic adenoma, with preserved postoperative facial nerve function. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarizes the imaging features, supplemented by dynamic video demonstrations: Video S3-1 integrates oblique MRI reconstructions to highlight the parallel trajectory of the facial nerve branches relative to the tumor and the overlying relationship to the retromandibular vein. Video S3-2 generates an interactive 3D model, panning around the tumor-nerve-vein complex to reveal the crossing neurovascular anatomy and spatial compression effects.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCase 4\u003c/strong\u003e \u003cp\u003eA 42-year-old female with a left parotid gland tumor. MRI (with parameter adjustment) clearly displayed the course of the intraparotid and extraparotid ducts: in the FSE sequence, static intraductal fluid (due to slow flow) showed significantly high signal intensity. The tumor was adjacent to the surface of the masseter muscle; the intraparotid branch ducts posterior to the tumor were compressed, and fluid converged into the main duct anterior to the tumor. The main duct coursed along the surface of the masseter muscle after exiting the parotid gland. Preoperative 3D reconstruction of the tumor-duct relationship was completed, and intraoperative verification confirmed the tumor location and its relationship with the duct were consistent with MRI findings. Pathology confirmed a pleomorphic adenoma postoperatively. The patient had normal facial nerve function postoperatively. The radiological findings are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Supplementary videos dynamically demonstrate the ductal system: Videos S4-1 \u0026amp; S4-2 delineate its spatial relationship to the tumor and muscle on multiplanar MRI, while Video S4-3 renders the 3D deformation of ducts by tumor mass effect.\u003c/p\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAs an innovative evolution of three-dimensional fast spin echo technology, the United Imaging FSE-Matrix-3D sequence is essentially a modulated flip angle technique in refocused imaging with extended echo train. It uses intelligently designed fast spin echo flip angle combinations along with optimized reconstruction protocols, allowing for dynamic adjustment of radiofrequency pulse angles to meet clinical contrast needs (covering T1, T2, and proton density contrasts) \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. By integrating variable flip angle modulation (with angles dynamically adjusted to 80\u0026deg;-200\u0026deg; in T2-weighted sequences), compressed sensing (CS) acceleration algorithms, and non-Cartesian K-space sampling, this sequence offers key advantages for imaging nerves and fine structures \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. With its ultra-short echo spacing (ESP\u0026thinsp;\u0026lt;\u0026thinsp;5ms) and long echo train design, the sequence minimizes edge blurring from T2 decay while maintaining T2 contrast-making it particularly well-suited for detailed morphological analysis of slender nerve fascicles (e.g., facial nerve branches, brachial plexus roots) smaller than 0.5mm in diameter \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. When combined with compressed sensing, it achieves isotropic resolution of 0.6\u0026times;0.6\u0026times;0.6 mm\u0026sup3;, representing a 40%-60% improvement in scanning efficiency over traditional 2D FSE sequences-providing a solid foundation for 3D nerve reconstruction \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Clinical studies support its strong performance in craniofacial and peripheral nerve imaging. In a multidisciplinary assessment involving 60 patients, inter-rater agreement for second-order facial nerve branch visualization between neuroradiologists and oral-maxillofacial surgeons reached a Cohen's Kappa of 0.847, significantly outperforming traditional 2D FSE sequences. For brachial plexus imaging, it clearly depicts nerve root ganglia and fascicular branches; compared to the MSDE-CUBE-fTED sequence described by Yoon et al. \u003csup\u003e16\u003c/sup\u003e, it reduces scan time by 30% while delivering superior image contrast. Technically, the sequence's compressed sensing mechanism aligns with the CUBE-CS technology proposed by Kijowski et al. \u003csup\u003e17\u003c/sup\u003e, and its non-Cartesian sampling strategy shares methodological similarities with the long echo train 3D FSE sequences optimized by Mugler et al. \u003csup\u003e11\u003c/sup\u003e. Notably, its advantages are supported by studies in knee cartilage injury diagnosis: compared to traditional 2D FSE, compressed sensing-accelerated 3D FSE sequences reduce scan time by 30% while maintaining equivalent cartilage signal-to-noise ratio (SNR), with diagnostic sensitivity and specificity for cartilage lesions ranging from 75.0%-100% and 87.5%-100% respectively\u003csup\u003e17\u003c/sup\u003e. This performance mirrors findings from Madelin et al., who used compressed sensing for accelerated sodium imaging at 7T, confirming the technique maintains quantitative accuracy even at high field strengths \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Its design-controlling maximum flip angles to reduce SAR values-builds on the earlier single-slab 3D spin echo concept by Mugler et al., offering a versatile solution for 3D imaging across multiple regions (skull, vertebrae, pelvis, etc.) \u003csup\u003e19\u003c/sup\u003e. In terms of broader applications, the FSE-Matrix-3D sequence shares design principles with Siemens SPACE and Philips VISTA sequences but achieves better balance between scanning efficiency and image quality through deeper integration of compressed sensing and non-Cartesian sampling \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe visualization techniques for the intraparotid facial nerve have undergone iterative optimization through multiple generations of MRI sequences, with the core goal of achieving high-resolution, low-artifact visualization of the nerve-tumor interface within complex anatomical structures. Early 3D TOF MRA combined with water excitation technology improved vascular visualization through background suppression, but was limited by the constraints of vascular imaging and could not directly evaluate facial nerve branches \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The introduction of high-resolution T2-weighted sequences made identification of the main facial nerve trunk possible, yet their sensitivity for localizing deep-lobe tumors was only 50% \u003csup\u003e22\u003c/sup\u003e. 3D-FIESTA achieved clear visualization of the main facial nerve trunk in 3T systems, with an 83.9% accuracy rate for correctly diagnosing the relationship between the temporofacial and cervicofacial trunks. However, the visualization rate for nerve branches with a diameter\u0026thinsp;\u0026lt;\u0026thinsp;0.5mm remained below 30% \u003csup\u003e6\u003c/sup\u003e. To overcome this bottleneck, the 3D-DESS-WE optimized parameter design, achieving an 89.5% visualization rate for V3 branches in 86 patients. Its localization accuracy was validated in 25 patients with deep-lobe tumors, increasing to 92% (sensitivity 93%, specificity 91%) \u003csup\u003e23,24\u003c/sup\u003e. Nevertheless, this sequence is still limited by motion artifacts (artifact area accounting for \u0026gt;\u0026thinsp;15%) and insufficient soft tissue contrast (gray matter-nerve CNR\u0026thinsp;=\u0026thinsp;5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7) \u003csup\u003e25\u003c/sup\u003e. The FSE-Matrix-3D technology proposed in this study enhances isotropic resolution to 0.6mm\u0026sup3; through a compressed sensing acceleration algorithm\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e and, combined with ultra-short echo spacing (ESP\u0026thinsp;\u0026lt;\u0026thinsp;5ms), significantly improves the visualization rate of nerve branches with a diameter\u0026thinsp;\u0026lt;\u0026thinsp;0.5mm to 82.4% (compared to 29.6% with 3D-FIESTA). Dynamic adjustment of driven equilibrium parameters further reduces vascular pulsation artifact area by 42.3% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), providing better motion artifact suppression than 3D-DESS-WE and CISS sequences \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Future research directions should integrate multimodal technologies and artificial intelligence algorithms to optimize preoperative assessment-such as enhancing image resolution and soft tissue contrast through deep learning, and combining intraoperative real-time navigation technology to improve the precision of nerve protection\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe signal gradient exhibited by the United Imaging FSE-Matrix-3D sequence in parotid gland imaging, where the signal intensity follows the order of parotid duct\u0026thinsp;\u0026gt;\u0026thinsp;parotid parenchyma\u0026thinsp;\u0026gt;\u0026thinsp;facial nerve\u0026thinsp;\u0026gt;\u0026thinsp;retromandibular vein, arises from the combined effects of tissue composition and the physical properties of the sequence. The high signal intensity of the parotid duct on T2-weighted imaging (T2WI) originates from the static or slowly flowing saliva within its lumen. With a long T2 relaxation time ranging from approximately 1200 to 1500 ms, this high signal is significantly enhanced in heavily T2-weighted sequences such as 3D-DESS-WE. This observation is consistent with the high-resolution visualization of the parotid duct achieved by Sartoretti-Schefer et al. in 1999 using 3D FSE technology \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The moderately high signal of the parotid parenchyma primarily depends on the fat suppression strategy of the sequence. In non-suppressed sequences, the fat component within the parotid gland-characterized by short T1 and moderate T2 relaxation times-leads to elevated signal intensity. In contrast, water excitation techniques, such as the dual-echo acquisition combined with fat suppression employed in DESS-WE \u003csup\u003e7,9\u003c/sup\u003e, enable selective suppression of fat signals. This selective suppression increases the contrast between the parotid duct and the facial nerve by 30% to 40%. Methodologically, the fat suppression effect in this sequence is primarily achieved via dynamic adjustment of flip angles (80\u0026deg;- 200\u0026deg;), which optimizes the balance between T2 weighting and effective fat signal suppression. In addition, the sequence integrates compressed sensing (CS) to shorten image acquisition time while maintaining high reconstruction quality. This combined approach is consistent with the protocol proposed by Li et al. \u003csup\u003e12\u003c/sup\u003e, who refined T2 contrast through similar dynamic flip angle adjustments and utilized CS to enhance scanning efficiency in their 3D MRI sequence. The signal manifestation of the facial nerve is sequence-specific. On conventional T2WI sequences like 3D-FIESTA, the facial nerve exhibits slightly low signal intensity. This is attributed to the dense collagen in the perineurium and the low proton density of the myelin sheath \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. However, in steady-state precession sequences such as DESS-WE, the microscopic flow of axoplasm within the nerve induces phase rephasing via dual-echo acquisition (FISP\u0026thinsp;+\u0026thinsp;PSIF). When combined with the homogenization of the fat-suppressed background, this phase rephasing results in a relatively high signal intensity of the facial nerve, with the contrast-to-noise ratio (CNR) increasing from 5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7 to 12.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1. This signal enhancement is consistent with the findings of Oh et al. in cranial nerve imaging, which confirms the sensitivity of this sequence for visualizing fine nerve structures \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. The low signal intensity of the retromandibular vein is primarily driven by the \"flow void effect\" caused by rapid blood flow, and this effect is particularly prominent in spin-echo sequences. Nevertheless, the retromandibular vein signal is susceptible to interference from susceptibility artifacts in gradient-echo sequences such as 3D-FIESTA \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Similar to the findings of Kijowski et al. in knee vascular imaging \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, the United Imaging FSE-Matrix-3D sequence reduces vascular pulsation artifacts effectively through optimized gradient field stability and compressed sensing technology. This reduction in artifacts ultimately improves the clarity of venous structure visualization.\u003c/p\u003e \u003cp\u003eThe innovative application of the 32-channel head coil combined with an 8-channel dedicated carotid surface coil in parotid gland MRI has demonstrated significant advantages in terms of anatomical visualization and diagnostic accuracy \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. The curved array design of the carotid surface coil, which is one component of this combined coil system, conforms to the anatomical structure of the mandible and auricle, enabling a near-field reception distance of less than 2 cm from the target tissue. Compared with traditional head and neck coils (with a reception distance of more than 5 cm), this combined coil design increases the SNR by approximately 40% \u003csup\u003e30\u003c/sup\u003e. The directional focusing of the coil elements effectively suppresses background interference from muscles with high proton density, such as the temporalis and masseter muscles, thereby improving the CNR by 23.6% \u003csup\u003e31\u003c/sup\u003e. Additionally, the integrated three-axis accelerometer (with a sensitivity of 0.1 mm) combined with the uCS-MoCo algorithm reduces motion artifacts by 62% through real-time phase correction. When used in conjunction with compressed sensing (with an acceleration factor of 4), the system achieves an isotropic resolution of 0.6 mm while shortening the scan duration by 58%\u0026mdash;from 10 minutes and 24 seconds to 4 minutes and 30 seconds. Notably, this combined coil system visualizes the second-order branches of the facial nerve in 93.3% of cases, which exceeds the historical reported visualization rates (ranging from 48% to 63%) achieved with 8- to 16-channel single head/neck coils \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. However, the application of surface coils also has certain limitations. First, the signal attenuation of surface coils intensifies with increasing depth, which may result in inferior imaging quality of deep structures compared to superficial ones \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Second, surface coils may be less effective than combined head and neck coils in terms of image uniformity, especially when the scanning range is large or the patient has a larger body size \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Third, surface coils are more sensitive to motion artifacts, and this issue becomes particularly pronounced when the scan time is long or the patient is unable to remain stationary \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. In clinical practice, the coordinated use of the 32-channel head coil\u0026thinsp;+\u0026thinsp;8-channel dedicated carotid surface coil with traditional combined head and neck coils can fully leverage the advantages of both. The combined head and neck coils provide wide coverage and a stable magnetic field environment, while the surface coils, taking advantage of the parotid gland`s relatively superficial location, effectively enhance the SNR and spatial resolution of parotid tissue imaging. They are designed for high-resolution visualization of local fine structures, particularly the intraparotid facial nerve branches. This strategy improves the visualization quality of the facial nerve and its branches, reduces motion artifact interference, and thereby supplies more detailed anatomical information for the preoperative evaluation of parotid gland tumors \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe visualization quality of the facial nerve is influenced by multiple factors, including anatomical, technical, and operational aspects. The location and size of the tumor significantly affect the complexity of nerve tracking. Deep-lobe tumors adjacent to the anterior margin of the parotid gland or the main trunk of the facial nerve\u0026mdash;especially those with a diameter exceeding 4 cm\u0026mdash;often cause nerve displacement or encasement. To resolve the nerve`s course in such cases, multiplanar reconstruction combined with continuous tracking via dynamic videos is required. Motion artifacts induced by the scan duration (approximately 5 minutes), such as those from respiration, swallowing, or slight head movements, can lead to blurring in the phase-encoding direction. In this study, the area affected by artifacts accounted for 10% to 15% of the images. Although the driven equilibrium technique of the United Imaging FSE-Matrix-3D sequence can reduce vascular pulsation artifacts, further optimization is still needed to address large-magnitude displacements. The experience of radiologists is crucial for nerve interpretation. The individualized course of the facial nerve, from its origin at the stylomastoid foramen onward, relies on the combined analysis of multi-angle, oblique coronal, and sagittal images. Inexperienced radiologists are prone to misjudgments, for instance, mistaking the low signal of the tumor capsule for a nerve discontinuity. Notably, this study found no significant impact of tumor properties (benign vs. malignant) or composition (cystic vs. solid) on visualization quality. This observation may be attributed to the optimized T2 contrast of the sequence \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. When the facial nerve is adjacent to the tumor, it appears as a low signal overlapping with the tumor capsule, and its continuity can be verified using dynamic videos. Third-party software enables the 3D reconstruction of the facial nerve, parotid duct, and tumor, providing high-precision imaging evidence of the facial nerve-tumor spatial relationship for the preoperative evaluation of parotid gland tumors. Based on this information, surgeons can clarify the spatial relationship between the tumor and the nerve, develop personalized surgical strategies, and improve the efficiency of doctor-patient communication. Meanwhile, patients can form objective perceptions of surgical expectations and potential complications through this imaging evidence.\u003c/p\u003e \u003cp\u003eThe limitations of this study include the small sample size, which is predominantly composed of benign tumors; this may restrict the breadth of evaluation for malignant tumors or complex cases. Additionally, although the driven equilibrium technique of the United Imaging FSE-Matrix-3D sequence significantly suppresses motion artifacts, the relatively long scan duration (approximately 5 minutes) still poses challenges for its application in children or patients who are unable to cooperate during the examination.\u003c/p\u003e \u003cp\u003eIn summary, this study employed the innovative FSE-MX-3D sequence combined with 32-channel head coil and 8-channel dedicated carotid surface coil technology to systematically evaluate its application value in preoperative facial nerve localization for patients with parotid gland tumors. The results demonstrated that this technology can clearly visualize the main trunk and branches of the facial nerve with high resolution, effectively shorten the scanning time, and significantly improve the visualization rate of second-order branches. The consistency between preoperative MRI evaluations and intraoperative verification results further confirmed the accuracy of this method in assessing the spatial relationship between the facial nerve and tumors. This technological breakthrough provides important imaging support for the surgical planning of parotid gland tumors, helping surgeons accurately identify the course of the facial nerve, optimize surgical strategies, and reduce the risk of facial nerve injury. In the future, through further sample expansion and multi-center studies, this technology is expected to become an important tool for preoperative image navigation and promote the development of precision surgery.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003ch3\u003ePatient consent for publication\u003c/h3\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\u003cp\u003e \u003ch2\u003eConsent for publication\u003c/h2\u003e \u003cp\u003e All the authors gave their consent for publication.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConflict of Interest Statement\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003e This project was supported by Basic Research Program of Shenzhen Innovation Council (JCYJ20250604183723030); Guangdong Provincial Medical Science and Technology Research Fund (A2024488), Shenzhen Clinical Medical Research Center for Oral Diseases (Grant No. 20210617170745001-SCRC202201001), and Sanming Project of Medicine in Shenzhen (SZSM202111012, Oral and Maxillofacial Surgery Team, Professor Yu Guangyan, Peking University Hospital of Stomatology), Shenzhen Fund for Guangdong Provincial High-level Clinical Key Specialties (SZGSP008).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eB.L. and G.Y.H. (co-first authors) proposed the study concept, designed the study protocol, led data analysis/interpretation, and drafted the manuscript; S.J.W., S.Y.S., and Y.D.Y. conducted data acquisition and edited technical details in the manuscript; F.W. assisted in data acquisition, coordinated patient scheduling, polished intraoperative procedure descriptions, and oversaw data quality control; X.H. and H.J.Y. participated in data quality control, assisted in data analysis, designed the statistical plan, performed statistical analysis, and reviewed statistical results; G.X.C. and H.Y. (co-corresponding authors) supervised the study concept/design/data analysis, provided critical manuscript revisions; all authors reviewed and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data are present in the manuscript. Additional data related to this paper may be requested from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMoore, M. G. et al. Controversies in the Workup and Surgical Management of Parotid Neoplasms. \u003cem\u003eOtolaryngol. Head Neck Surg.\u003c/em\u003e \u003cb\u003e164\u003c/b\u003e, 27\u0026ndash;36. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/0194599820932512\u003c/span\u003e\u003cspan address=\"10.1177/0194599820932512\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAasen, M. H., Hutz, M. J., Yuhan, B. T. \u0026amp; Britt, C. J. Deep Lobe Parotid Tumors: A Systematic Review and Meta-analysis. \u003cem\u003eOtolaryngol. Head Neck Surg.\u003c/em\u003e \u003cb\u003e166\u003c/b\u003e, 60\u0026ndash;67. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/01945998211009235\u003c/span\u003e\u003cspan address=\"10.1177/01945998211009235\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZoccali, F. et al. Clinico-histopathological review of 255 patients who underwent parotidectomy for pleomorphic adenoma: a 10-year retrospective study-a proposal for an optimal diagnostic and therapeutic algorithm for patients with recurrent pleomorphic adenoma. \u003cem\u003eEur. Arch. Otorhinolaryngol.\u003c/em\u003e \u003cb\u003e280\u003c/b\u003e, 3329\u0026ndash;3335. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00405-023-07897-y\u003c/span\u003e\u003cspan address=\"10.1007/s00405-023-07897-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuntinas-Lichius, O. et al. Management of the facial nerve in parotid cancer: preservation or resection and reconstruction. \u003cem\u003eEur. Arch. Otorhinolaryngol.\u003c/em\u003e \u003cb\u003e275\u003c/b\u003e, 2615\u0026ndash;2626. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00405-018-5154-6\u003c/span\u003e\u003cspan address=\"10.1007/s00405-018-5154-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKang, Y. J., Cho, J. H. \u0026amp; Hwang, S. H. Diagnostic value of various criteria for deep lobe involvement in radiologic studies with parotid mass: a systematic review and meta-analysis. \u003cem\u003eRadiol. Med.\u003c/em\u003e \u003cb\u003e127\u003c/b\u003e, 1124\u0026ndash;1133. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11547-022-01540-2\u003c/span\u003e\u003cspan address=\"10.1007/s11547-022-01540-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuenette, J. P. et al. MR Imaging of the Extracranial Facial Nerve with the CISS Sequence. \u003cem\u003eAJNR Am. J. Neuroradiol.\u003c/em\u003e \u003cb\u003e40\u003c/b\u003e, 1954\u0026ndash;1959. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3174/ajnr.A6261\u003c/span\u003e\u003cspan address=\"10.3174/ajnr.A6261\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQin, Y., Zhang, J., Li, P. \u0026amp; Wang, Y. 3D double-echo steady-state with water excitation MR imaging of the intraparotid facial nerve at 1.5T: a pilot study. \u003cem\u003eAJNR Am. J. Neuroradiol.\u003c/em\u003e \u003cb\u003e32\u003c/b\u003e, 1167\u0026ndash;1172. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3174/ajnr.A2480\u003c/span\u003e\u003cspan address=\"10.3174/ajnr.A2480\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim, Y. et al. Three-dimensional double-echo steady-state with water excitation magnetic resonance imaging to localize the intraparotid facial nerve in patients with deep-seated parotid tumors. \u003cem\u003eNeuroradiology\u003c/em\u003e \u003cb\u003e63\u003c/b\u003e, 731\u0026ndash;739. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00234-021-02673-3\u003c/span\u003e\u003cspan address=\"10.1007/s00234-021-02673-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu, L. H. et al. Direct visualization of intraparotid facial nerve assisting in parotid tumor resection. \u003cem\u003eJ. Craniomaxillofac. Surg.\u003c/em\u003e \u003cb\u003e52\u003c/b\u003e, 659\u0026ndash;665. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jcms.2024.03.014\u003c/span\u003e\u003cspan address=\"10.1016/j.jcms.2024.03.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHouse, J. W. \u0026amp; Brackmann, D. E. Facial nerve grading system. \u003cem\u003eOtolaryngol. Head Neck Surg.\u003c/em\u003e \u003cb\u003e93\u003c/b\u003e, 146\u0026ndash;147. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/019459988509300202\u003c/span\u003e\u003cspan address=\"10.1177/019459988509300202\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1985).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMugler, J. P. 3 Optimized three-dimensional fast-spin-echo MRI. \u003cem\u003eJ. Magn. Reson. Imaging\u003c/em\u003e. \u003cb\u003e39\u003c/b\u003e, 745\u0026ndash;767. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/jmri.24542\u003c/span\u003e\u003cspan address=\"10.1002/jmri.24542\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi, G. et al. Evaluation of an accelerated 3D modulated flip-angle technique in refocused imaging with an extended echo-train sequence with compressed sensing for imaging of the knee: comparison with routine 2D MRI sequences. \u003cem\u003eClin. Radiol.\u003c/em\u003e \u003cb\u003e76\u003c/b\u003e, 158e113\u0026ndash;158e118. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.crad.2020.10.012\u003c/span\u003e\u003cspan address=\"10.1016/j.crad.2020.10.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSui, H. et al. Accelerating Knee MRI: 3D Modulated Flip-Angle Technique in Refocused Imaging with an Extended Echo Train and Compressed Sensing. \u003cem\u003eJ. Pain Res.\u003c/em\u003e \u003cb\u003e15\u003c/b\u003e, 577\u0026ndash;590. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2147/JPR.S345210\u003c/span\u003e\u003cspan address=\"10.2147/JPR.S345210\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBusse, R. F. Reduced RF power without blurring: correcting for modulation of refocusing flip angle in FSE sequences. \u003cem\u003eMagn. Reson. Med.\u003c/em\u003e \u003cb\u003e51\u003c/b\u003e, 1031\u0026ndash;1037. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/mrm.20056\u003c/span\u003e\u003cspan address=\"10.1002/mrm.20056\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2004).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOh, J. et al. Application of 3D Fast Spin-Echo T1 Black-Blood Imaging in the Diagnosis and Prognostic Prediction of Patients with Leptomeningeal Carcinomatosis. \u003cem\u003eAJNR Am. J. Neuroradiol.\u003c/em\u003e \u003cb\u003e39\u003c/b\u003e, 1453\u0026ndash;1459. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3174/ajnr.A5721\u003c/span\u003e\u003cspan address=\"10.3174/ajnr.A5721\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYoon, D., Antil, N., Biswal, S. \u0026amp; Lutz, A. M. A robust 3D fast spin-echo technique for fast examination of the brachial plexus. \u003cem\u003eSkeletal Radiol.\u003c/em\u003e \u003cb\u003e51\u003c/b\u003e, 1865\u0026ndash;1872. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00256-022-04021-9\u003c/span\u003e\u003cspan address=\"10.1007/s00256-022-04021-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKijowski, R. et al. Knee imaging: Rapid three-dimensional fast spin-echo using compressed sensing. \u003cem\u003eJ. Magn. Reson. Imaging\u003c/em\u003e. \u003cb\u003e45\u003c/b\u003e, 1712\u0026ndash;1722. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/jmri.25507\u003c/span\u003e\u003cspan address=\"10.1002/jmri.25507\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMadelin, G., Chang, G., Otazo, R., Jerschow, A. \u0026amp; Regatte, R. R. Compressed sensing sodium MRI of cartilage at 7T: preliminary study. \u003cem\u003eJ. Magn. Reson.\u003c/em\u003e \u003cb\u003e214\u003c/b\u003e, 360\u0026ndash;365. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jmr.2011.12.005\u003c/span\u003e\u003cspan address=\"10.1016/j.jmr.2011.12.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMugler, J. P. 3 et al. Optimized single-slab three-dimensional spin-echo MR imaging of the brain. \u003cem\u003eRadiology\u003c/em\u003e \u003cb\u003e216\u003c/b\u003e, 891\u0026ndash;899. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1148/radiology.216.3.r00au46891\u003c/span\u003e\u003cspan address=\"10.1148/radiology.216.3.r00au46891\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2000).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSartoretti-Schefer, S., Kollias, S., Wichmann, W. \u0026amp; Valavanis, A. 3D T2-weighted fast spin-echo MRI sialography of the parotid gland. \u003cem\u003eNeuroradiology\u003c/em\u003e \u003cb\u003e41\u003c/b\u003e, 46\u0026ndash;51. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s002340050704\u003c/span\u003e\u003cspan address=\"10.1007/s002340050704\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1999).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTakahashi, N., Okamoto, K., Ohkubo, M. \u0026amp; Kawana, M. High-resolution magnetic resonance of the extracranial facial nerve and parotid duct: demonstration of the branches of the intraparotid facial nerve and its relation to parotid tumours by MRI with a surface coil. \u003cem\u003eClin. Radiol.\u003c/em\u003e \u003cb\u003e60\u003c/b\u003e, 349\u0026ndash;354. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.crad.2004.06.018\u003c/span\u003e\u003cspan address=\"10.1016/j.crad.2004.06.018\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAttye, A. et al. Parotid gland tumours: MR tractography to assess contact with the facial nerve. \u003cem\u003eEur. Radiol.\u003c/em\u003e \u003cb\u003e26\u003c/b\u003e, 2233\u0026ndash;2241. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00330-015-4049-9\u003c/span\u003e\u003cspan address=\"10.1007/s00330-015-4049-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFujii, H. et al. Visualization of the Peripheral Branches of the Mandibular Division of the Trigeminal Nerve on 3D Double-Echo Steady-State with Water Excitation Sequence. \u003cem\u003eAJNR Am. J. Neuroradiol.\u003c/em\u003e \u003cb\u003e36\u003c/b\u003e, 1333\u0026ndash;1337. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3174/ajnr.A4288\u003c/span\u003e\u003cspan address=\"10.3174/ajnr.A4288\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFujii, H. et al. Localization of Parotid Gland Tumors in Relation to the Intraparotid Facial Nerve on 3D Double-Echo Steady-State with Water Excitation Sequence. \u003cem\u003eAJNR Am. J. Neuroradiol.\u003c/em\u003e \u003cb\u003e40\u003c/b\u003e, 1037\u0026ndash;1042. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3174/ajnr.A6078\u003c/span\u003e\u003cspan address=\"10.3174/ajnr.A6078\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeider, N. A. et al. Accuracy and reliability of diffusion imaging models. \u003cem\u003eNeuroimage\u003c/em\u003e \u003cb\u003e254\u003c/b\u003e, 119138. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neuroimage.2022.119138\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroimage.2022.119138\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiang, D., Liu, B., Wang, J. \u0026amp; Ying, L. Accelerating SENSE using compressed sensing. \u003cem\u003eMagn. Reson. Med.\u003c/em\u003e \u003cb\u003e62\u003c/b\u003e, 1574\u0026ndash;1584. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/mrm.22161\u003c/span\u003e\u003cspan address=\"10.1002/mrm.22161\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLustig, M., Donoho, D., Pauly, J. M. \u0026amp; Sparse, M. R. I. The application of compressed sensing for rapid MR imaging. \u003cem\u003eMagn. Reson. Med.\u003c/em\u003e \u003cb\u003e58\u003c/b\u003e, 1182\u0026ndash;1195. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/mrm.21391\u003c/span\u003e\u003cspan address=\"10.1002/mrm.21391\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsang, J. C. et al. Visualization of normal intra-parotid facial nerve on MR: BTFE or GRASS? \u003cem\u003eClin. Radiol.\u003c/em\u003e \u003cb\u003e64\u003c/b\u003e, 1115\u0026ndash;1118. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.crad.2009.03.012\u003c/span\u003e\u003cspan address=\"10.1016/j.crad.2009.03.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi, C., Li, Y., Zhang, D., Yang, Z. \u0026amp; Wu, L. 3D-FIESTA MRI at 3 T demonstrating branches of the intraparotid facial nerve, parotid ducts and relation with benign parotid tumours. \u003cem\u003eClin. Radiol.\u003c/em\u003e \u003cb\u003e67\u003c/b\u003e, 1078\u0026ndash;1082. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.crad.2012.03.014\u003c/span\u003e\u003cspan address=\"10.1016/j.crad.2012.03.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao, Y. \u0026amp; Yang, B. Value of Visualization of the Intraparotid Facial Nerve and Parotid Duct Using a Micro Surface Coil and Three-Dimensional Reversed Fast Imaging With Steady-State Precession and Diffusion-Weighted Imaging Sequence. \u003cem\u003eJ. Craniofac. Surg.\u003c/em\u003e \u003cb\u003e29\u003c/b\u003e, e754\u0026ndash;e757. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/SCS.0000000000004704\u003c/span\u003e\u003cspan address=\"10.1097/SCS.0000000000004704\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNiemela, R. K., Paakko, E., Suramo, I., Takalo, R. \u0026amp; Hakala, M. Magnetic resonance imaging and magnetic resonance sialography of parotid glands in primary Sjogren's syndrome. \u003cem\u003eArthritis Rheum.\u003c/em\u003e \u003cb\u003e45\u003c/b\u003e, 512\u0026ndash;518. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/1529-0131(200112)45:6%3C512::aid-art376%3E3.0.co;2-r\u003c/span\u003e\u003cspan address=\"10.1002/1529-0131(200112)45:6%3C512::aid-art376%3E3.0.co;2-r\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2001).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun, Q., Dong, M. J., Tao, X. F., Jiang, M. D. \u0026amp; Yang, C. Selection and application of coils in temporomandibular joint MRI. \u003cem\u003eDentomaxillofac Radiol.\u003c/em\u003e \u003cb\u003e49\u003c/b\u003e, 20190002. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1259/dmfr.20190002\u003c/span\u003e\u003cspan address=\"10.1259/dmfr.20190002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIshibashi, M. et al. Capsule of parotid gland tumor: evaluation by 3.0 T magnetic resonance imaging using surface coils. \u003cem\u003eActa Radiol.\u003c/em\u003e \u003cb\u003e51\u003c/b\u003e, 1103\u0026ndash;1110. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3109/02841851.2010.519716\u003c/span\u003e\u003cspan address=\"10.3109/02841851.2010.519716\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIshibashi, M. et al. The ability to identify the intraparotid facial nerve for locating parotid gland lesions in comparison to other indirect landmark methods: evaluation by 3.0 T MR imaging with surface coils. \u003cem\u003eNeuroradiology\u003c/em\u003e \u003cb\u003e52\u003c/b\u003e, 1037\u0026ndash;1045. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00234-010-0718-1\u003c/span\u003e\u003cspan address=\"10.1007/s00234-010-0718-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2010).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Head and Neck Cancer, Lymph Node Metastasis, Retrospective Cohort Study, Diagnostic Accuracy","lastPublishedDoi":"10.21203/rs.3.rs-8303262/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8303262/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eFacial nerve injury is a major complication of parotid gland tumor surgery. Traditional MRI fails to visualize small facial nerve branches (\u0026lt;\u0026thinsp;0.5 mm), while existing high-resolution MRI has drawbacks like long scan time or low branch detection rate, restricting intraoperative nerve protection.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis prospective cross-sectional study included 60 parotid tumor patients (March 2024\u0026ndash;March 2025). Preoperative MRI was performed using a 3T system with the FSE-MX-3D sequence, combined with 32-channel head coil and 8-channel dedicated carotid surface coil. Two observers graded nerve visualization; inter-rater reliability was evaluated via Cohen`s Kappa, and MRI findings were verified intraoperatively.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFacial nerve main trunk visualization rate was 100%. Grade 3 visualization of second-order branches was 70.0% (neuroradiologists) and 68.3% (surgeons), with excellent inter-rater agreement (Kappa\u0026thinsp;=\u0026thinsp;0.894, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Preoperative MRI matched intraoperative findings in 56 assessable patients. Scan time was approximately 4.5 minutes without contrast agent. Twelve patients had transient facial paralysis and recovered in 3\u0026ndash;6 months; 8 malignant cases showed no recurrence.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe FSE-MX-3D sequence with combined coils offers high resolution, short scan time, no contrast requirement, and high reliability. It optimizes parotid tumor surgical planning and reduces facial nerve injury risk.\u003c/p\u003e","manuscriptTitle":"Optimized FSE-MX-3D Sequence Combined with Carotid Surface Coil for Preoperative Localization of the Facial Nerve in Patients with Parotid Gland Tumors","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-07 20:15:14","doi":"10.21203/rs.3.rs-8303262/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-05T17:19:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"232097400924969962605291437287677409857","date":"2026-04-23T15:56:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"75240764072715338225906406971858976054","date":"2026-04-23T13:09:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-23T12:55:47+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-11T18:37:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-10T06:51:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-10T06:47:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-12-08T03:41:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a78efab0-f89d-4c0d-9415-9c4749d5cb45","owner":[],"postedDate":"May 7th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-05T17:19:36+00:00","index":126,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":67437253,"name":"Biological sciences/Cancer"},{"id":67437254,"name":"Health sciences/Medical research"},{"id":67437255,"name":"Health sciences/Neurology"},{"id":67437256,"name":"Biological sciences/Neuroscience"},{"id":67437257,"name":"Health sciences/Oncology"}],"tags":[],"updatedAt":"2026-05-07T20:15:14+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-07 20:15:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8303262","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8303262","identity":"rs-8303262","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}