Three-dimensional T2-weighted fast field echo imaging in the determination of the relationship between the intraparotid facial nerve and parotid tumors

Three-dimensional T2-weighted fast field echo imaging in the determination of the relationship between the intraparotid facial nerve and parotid 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 Research Article Three-dimensional T2-weighted fast field echo imaging in the determination of the relationship between the intraparotid facial nerve and parotid tumors Yihua Wang, Haowen Zheng, Jian Jiang, Liangjie Lin, Haitao Huang, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7604757/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Mar, 2026 Read the published version in European Journal of Medical Research → Version 1 posted 9 You are reading this latest preprint version Abstract Background To assess the performance of three-dimensional T2-weighted fast field echo imaging (3D-T2-FFE) in the visualization of the intraparotid facial nerve (IFN) and localization of tumors. Methods Magnetic resonance imaging data from sixty-four patients who underwent 3D-T2-FFE were retrospectively enrolled. The identification certainty of IFN on 3D-T2-FFE was scored with an arbitrary scale of 0–3. The parotid gland was divided into superior and inferior parts, with the level of the earlobe serving as the reference. The tumor location was categorized as deep or superficial directly on 3D-T2-FFE images and indirectly by the facial nerve line (FNL) and the retromandibular vein line (RMVL). Surgical localization was considered the reference standard. The accuracy, sensitivity, and specificity of each method for localizing parotid lesions were compared using the McNemar test. Results The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value for deep lobe lesions in the superior part of the parotid gland using the direct method were 97.8%, 92.3%, 100.0%, 100.0%, and 96.9%, respectively. The 3D-T2-FFE method showed significantly higher sensitivity and specificity than those of FNL ( p 0.05). The relationship between the tumor and the main trunk of the IFN was correctly predicted in 93.3% and 100% of 3D-T2-FFE images in the superior and inferior parts of the parotid glands, respectively. Conclusions 3D-T2-FFE can provide detailed morphological information on the nerve in relation to adjacent parotid gland structures and tumors before surgery. parotid gland intraparotid facial nerve magnetic resonance imaging salivary gland neoplasms magnetic resonance neurography Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background The anatomical structure of the parotid gland is complex[ 1 ]. The extracranial segment of the facial nerve and its main branches are mainly located in the parotid gland, which separates the superficial and deep lobes[ 2 ]. In the healthy parotid gland, the intraparotid facial nerve (IFN) does not adhere to the parotid gland tissue because of the nerve membrane[ 3 ]. However, when tumors occur, the anatomical position of the IFN may change, and adhesions with tumors may also develop, causing increased difficulty in completely excising the tumor while preserving nerve function[ 4 ]. Clinically, the incidence of facial nerve injury is significantly higher in tumors of the deep lobe than in the superficial lobe and inferior part of the parotid gland[ 5 ]. The established indirect methods for separating intraparotid lesions into superficial or deep, such as the facial nerve line (FNL) and retromandibular vein line (RMVL), are often used to evaluate the course of IFN roughly, but are not entirely accurate. The RMVL is perpendicular to the lateral edge of the retromandibular vein. The FNL connects the lateral margin of the posterior belly of the digastric muscle to the lateral margin of the ascending ramus of the mandible. Therefore, a good depiction of IFN before operation is of great significance in effectively protecting IFN during operation and improving patients’ quality of life after operation [ 2 , 6 ]. Especially in malignant tumors, the presurgical evaluation of IFN infiltration is crucial for patients and surgeons to be aware of. Magnetic resonance neurography (MRN) offers an ideal technique for visualizing parotid tumors surrounded by neurovascular structures, particularly in the IFN region [ 7 , 8 ]. However, at present, the tissue contrast for IFN in magnetic resonance imaging (MRI) is not sufficient, and the vascular signal cannot be suppressed entirely. Some studies[ 7 , 9 – 11 ] have utilized the three-dimensional constructive interference in steady-state (3D-CISS) sequence, the three-dimensional fast imaging employing steady-state acquisition (3D-FIESTA) sequence, and other high-resolution MRI sequences to demonstrate the IFN. However, these methods demonstrate IFN with hypointensity relative to the parotid gland parenchyma, and the contrast is not particularly obvious. Since then, the three-dimensional double-echo steady-state with water excitation (3D-DESSwe) sequence and the three-dimensional reversed fast imaging with steady-state precession and diffusion-weighted (3D-PSIF-DWI) sequence have also been gradually used for the display of IFN[ 12 – 15 ]. The IFN and parotid gland duct show hyperintensity, which improves the display of IFN. However, this method can lead to confusion in distinguishing the nerve from the duct, and the imaging sequence is complex [ 13 – 15 ]. In this study, 3D T2-weighted fast field echo imaging (3D-T2-FFE) was attempted using a fast steady-state free precession (SSFP)[ 16 ] sequence with a low turning angle, isotropic volumetric acquisition, and the shortest repetition and echo times for the visualization of IFN. Combined with effective fat suppression and 3D curvilinear planar reconstruction, 3D-T2-FFE may help clarify the relationship between the tumor and nerve. The other sequences have obtained a large number of clinical validations, but the application value of 3D-T2-FFE in parotid tumors has not been systematically evaluated. Thus, this study aimed to assess the performance of IFN and the localization of tumors in 3D-T2-FFE. Methods Patients enrollment The institutional review board of our hospital approved our retrospective study (license number: PJ-KS-KY-2023-578). This study includes 111 patients who were confirmed with parotid gland tumors in our hospital between May 2019 to October 2023. Inclusion criteria were: (1) parotid gland tumor patients with complete clinical information (included complete and detailed surgical records, clarified the location of tumor and the facial nerve) and confirmed pathological type; (2) no contraindication to MRI examination, and 3.0T MRI examination within 1 week before treatment (including the 3D-T2-FFE sequence); (3) no surgery or other injury in parotid glands before the MRI examination. Exclusion criteria were: (1) motion artifacts affected the IFN observation; (2) other clinically proven parotid disorders; (3) multiple tumors in the parotid glands bilaterally, affecting the score. The flow chart of patient inclusion and exclusion is shown in Fig. 1 . All included patients underwent surgical treatment in the Department of Stomatology at our hospital within one week of the MRI examination. All extracted tumor tissues were routinely subjected to histopathological examination after surgery. MR imaging Axial T1-weighted imaging (T1WI), axial fat-suppressed T2-weighted imaging (T2WI), and 3D-T2-FFE imaging were performed using a 3.0T MR scanner (Ingenia CX; Philips Healthcare, Best, the Netherlands) with a 32-channel phase-array head coil. The scanning parameters were listed in Table 1 . Table 1 Scan Parameters of T1WI, T2WI and 3D-T2-FFE TR (ms) TE (ms) Voxel (mm) FOV (mm) Matrix NSA FA T 1 WI 466.00 8.10 0.55×0.72×4.00 200×200×89 364×257×18 1 90° T 2 WI 2122.00 112.00 0.70×0.70×4.00 300×300×89 428×428×18 1 90° 3D-T2-FFE 8.30 4.10 0.65×0.65×1.00 220×220×65 340×339×130 2 30° 3D-T2-FFE, three-dimensional T2-weighted imaging fast field echo; T1WI, T1-weighted imaging; T2WI, T2-weighted imaging; TR, repetition time; TE, echo time; FOV, field of view; NSA, number of signal average; FA, flip angle. Images were automatically transferred to Intellispace Portal (ISP v9.0, Philips Healthcare) workstation for analysis: The curvilinear planar reconstruction (CPR), three-dimensional multiplanar reconstruction, and image evaluation were performed by two experienced radiologists in MRI diagnosis independently (radiologists 1 and 2 have 3 and 20 years of MRI diagnosis experience, respectively) who were blinded to clinical information. The evaluation results were finally compared with the intraoperative records. Evaluation of the demonstration of IFN in the contralateral parotid gland The two observers evaluated the display of the IFN main trunk and two divisions (temporofacial division and cervicofacial division) in the bilateral parotid glands (Fig. 2 ). The identification certainty of IFN was scored independently on the tumor side and the contralateral sides with four grades as follows[ 17 , 18 ]: 0, the anatomical structure was not visible; 1, the main trunk can be visible but two division was not visible, and the signal intensity of IFN was lower than that of cerebellum; 2, the main trunk can be visible, temporofacial or cervicofacial division was visible and the signal intensity of IFN was lower than that of cerebellum; 3, the main trunk and two division was visible, the signal was equivalent to the normal cerebellum. Two observers measured the facial nerve signal intensity value on the reconstructed image. Regions of interest (ROIs) were placed at the nerve where it enters the parotid parenchyma and the place where the nerve enters the parotid parenchyma at a distance of about 5 ~ 10 mm. The size of the ROI was about 1 ~ 5 mm 2 . At the same time, the signal intensity value of the parotid parenchyma was measured in the same slice. The ROI was approximately 10 ~ 15 mm 2 , avoiding parotid ducts and small vessels in the parotid gland as much as possible. The signal intensity ratio (SIR) is the ratio between signal intensities of the facial nerve and the parotid gland in the same slice (Fig. 2 ). Localization of parotid gland tumors with 3D-T2-FFE and indirect methods Because the facial nerve trunk could not be shown at score 0, images of cases scoring 1 and above in the tumor side of the parotid gland were selected, and cases scoring 0 were excluded (Fig. 1 ). On the reconstructed coronal 3D-T2-FFE images, the parotid gland was divided into the superior and inferior parts with the earlobe level as reference[ 19 ]. When the most significant slice of the tumor was ≥ 50% located above the earlobe level, the tumor was considered to be the superior tumor. Conversely, it was deemed to be located in the inferior part of the parotid gland. The tumor location was categorized as deep or superficial lobes on the 3D-T2-FFE images. When the tumor was located entirely on the medial side of the IFN and its branches, or ≥ 50% of the tumor was located on the medial side, it was defined as a tumor of the deep lobe. The above was the direct method. On the contrary, it was located in the superficial lobe[ 20 ]. The two indirect methods, the FNL and RMVL, were also recorded on axial T2-weighted images. The RMVL is perpendicular to the lateral edge of the retromandibular vein, and the FNL connects the lateral margin of the posterior belly of the digastric muscle to the lateral margin of the ascending ramus of the mandible[ 21 ]. The standard for deep and superficial lobes was the same as that mentioned above. The two observers used direct 3D-T2-FFE and indirect FNL and RMVL methods for tumor location. If there were divergent assessments, a consensus was reached through discussion. The relationship between the tumor and IFN Finally, the relationship between the tumor and IFN trunk was evaluated on the reconstructed images. The IFN was considered invaded when the main trunk of IFN was wholly or partially encased by the tumor (a tumor surrounding of>50% or 100% of the circumference of IFN on the reconstructed image)[ 22 ], and the distal segment of IFN was not visible. Additionally, apart from the above, it was considered that IFN was non-invasive. Surgical findings The relationship between IFN and a parotid tumor was confirmed by reviewing the surgical report. This was considered the reference standard and used to determine the diagnostic performance of the researched methods evaluated in this study. Statistical analysis For statistical analyses, we used SPSS (version 25.0; IBM Corp., Armonk, NY, USA) and MedCalc (version 20; MedCalc Software Ltd, Ostend, Belgium). The interobserver reliability was assessed via intraclass correlation coefficient (ICC) and Kappa test (excellent, ICC > 0.75 or Kappa ≥ 0.85; good, ICC: 0.60 ~ 0.74 or Kappa: 0.60 ~ 0.85; fair, ICC: 0.40 ~ 0.59 or Kappa: 0.45 ~ 0.60; poor, ICC < 0.40 or Kappa < 0.45). The patient's age and SIR were tested for normal distribution using the Shapiro-Wilk test. The Mann-Whitney U test was used to compare the difference in SIR between the healthy and tumor groups. Chi-square test or Fisher's exact test was used to compare categorical variables. The diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for localizing parotid lesions using each method were calculated and compared using the McNemar test. Differences with p < 0.05 were considered statistically significant. Results Based on inclusion and exclusion criteria, a total of 64 patients from May 2019 to October 2023 were included for image analysis. The age of patients in the superficial lobe group was 26 ~ 87 years, with a mean age of (56.9 ± 15.5) years. At the same time, the age in the deep lobe group was 26 ~ 69 years, with a mean age of (51.7 ± 11.9) years. No statistically significant difference was found in the age, gender, and pathology type between the deep and superficial lobe groups ( p > 0.05) (Table 2 ). Table 2 Patients Confirmed by Surgery Clinical outcomes P Superficial lobe (n = 47) Deep lobe (n = 17) Age 56.9 ± 15.5 51.7 ± 11.9 0.142 Gender 0.717 Male 30 10 Female 17 7 Histologic types Benign tumor 0.202 Pleomorphic adenoma 23 9 Warthin tumor 11 2 Base cell adenoma 3 2 Acidophile adenoma 2 0 Neurinoma 0 2 Papillary cystadenoma 1 0 Malignant tumor >0.99 Squamous cell carcinoma 1 1 Adenoid cystic carcinoma 1 0 Acinic cell carcinoma 1 0 Secretory carcinoma 1 0 Malignant neurofibroma 1 0 Salivary duct carcinoma 1 0 Basal cell adenocarcinoma 1 0 Poorly-differentiated carcinoma 0 1 No statistically significant difference was found in age, gender, or pathology type between the deep and superficial lobe groups. Detectability of IFN on 3D-T2-FFE For the IFN visibility score of the contralateral side (Kappa = 0.667), 26 cases were scored 3 (40.6%), 20 were scored 2 (31.3%), and 18 were scored 1 (28.1%). For the IFN visibility score of the tumor side (Kappa = 0.693), 18 cases were scored 3 (28.1%), 21 were scored 2 (32.8%), and 25 were scored 1 (39.1%). The display rates (Kappa = 0.797) of the IFN main trunk, temporofacial division, and cervicofacial division in the healthy parotid gland on reconstructed images were 100%, 67.2%, and 60.9%, respectively. The display rates (Kappa = 0.602) of the main trunk, temporofacial division, and cervicofacial division on the tumor side were 100%, 60.9%, and 35.9%, respectively. Interobserver agreement was good for the parameters of IFN and parotid parenchyma signal values, as assessed by two independent readers (ICC > 0.70). The SIR on the healthy side was 1.76 (1.29, 2.10), and 1.57 (1.17, 2.13) on the tumor side. There was no statistically significant difference between the contralateral side and tumor side in visibility score ( p = 0.270), display rates ( p = 0.238), and IFN SIR ( p = 0.336) (Table 3 ). Table 3 Detectability of IFN on 3D-T2-FFE healthy group (n = 64) tumor group (n = 64) P display rate 0.238 IFN main trunk (%) 64(100.0%) 64(100.0%) temporofacial division(%) 43(67.2%) 39(60.9%) cervicofacial division (%) 39(60.9%) 23(35.9%) IFN SIR 1.76(1.29, 2.10) 1.57(1.17, 2.13) 0.336 Score 0.270 3 26 18 2 20 21 1 18 25 0 0 0 There was no statistically significant difference between the contralateral side and tumor side in visibility score ( p = 0.270), display rates ( p = 0.238), and IFN SIR ( p = 0.336). Localization of parotid gland tumors with 3D-T2-FFE and indirect methods Intraoperative records showed that 17 cases were located in the deep lobe, and 47 cases were located in the superficial lobe. Interobserver agreement was good for the parameters of tumor localization as assessed by two independent readers. (direct method: Kappa = 0.752; FNL: Kappa = 0.736; RMVL: Kappa = 0.712). (1) superior part of the parotid gland : Intraoperative records showed that 13 cases were located in the deep lobe of the parotid gland, and 45 cases were located in the superficial lobe. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy for determining the localization of tumors in the deep lobe of the parotid gland on 3D-T2-FFE reconstructed images were 92.3%, 100.0%, 100.0%, 96.9%, and 97.8%, respectively. The sensitivity, specificity, PPV, NPV, and accuracy of the FNL methods for assessing deep lobe tumors of the parotid gland were 46.2%, 81.3%, 50.0%, 78.8%, and 71.1%, respectively. The sensitivity, specificity, PPV, NPV, and accuracy of RMVL methods for assessing were 61.5%, 93.8%, 80.0%, 85.7%, and 84.4%, respectively. 3D-T2-FFE showed significantly better sensitivity and specificity than those of FNL (sensitivity: p = 0.031, specificity: p = 0.031, Table 4 ), and there was no significant difference in accuracy between 3D-T2-FFE and FNL. There was no significant difference in sensitivity, specificity, and accuracy between 3D-T2-FFE and RMVL (all p >0.05, Table 4 ) (Figs. 3 – 4 ). Table 4 Diagnostic Performance of Localization of Parotid Tumors in the Superior Group with Three Methods Surgical findings Diagnostic performance (deep lobe lesions)(%)* Deep (n = 13) Superficial (n = 32) Accuracy Sensitivity Specificity PPV NPV Direct Deep 12 0 97.8% 92.3% 100.0% 100.0% 96.9% Superficial 1 32 FNL Deep 6 6 71.1% 46.2%* 81.3%* 50.0% 78.8% Superficial 7 26 ( P >0.99) ( P = 0.031) ( P = 0.031) RMVL Deep 8 2 84.4% 61.5% 93.8% 80.0% 85.7% Superficial 5 30 ( P >0.99) ( P = 0.125) ( P = 0.500) *Statistical analyses ( P values) were performed comparing the direct method with each indirect method. 3D-T2-FFE showed significantly better sensitivity and specificity than those of FNL. FNL, facial nerve line; NPV, negative predictive value; PPV, positive predictive value; RMVL, retromandibular vein line. (2) inferior part of the parotid gland : Intraoperative records showed that 4 cases were in the deep lobe, and 15 cases were in the superficial lobe. The sensitivity, specificity, PPV, NPV, and accuracy for determining the localization of tumors in the deep lobe of the parotid gland on 3D-T2-FFE reconstructed images were 50.0%, 100.0%, 100.0%, 88.2%, and 89.5%, respectively. The sensitivity, specificity, PPV, NPV, and accuracy of the FNL method for assessing deep lobe tumors of the parotid gland were 25.0%, 86.7%, 33.3%, 81.3%, 73.7%, and those for RMVL were 50.0%, 93.3%, 66.7%, 87.5%, 84.2%, respectively. There was no significant difference in sensitivity, specificity, and accuracy among the three methods ( p > 0.05, Table 5 ). Table 5 Diagnostic Performance of Localization of Parotid Tumors in the Inferior Group with Three Methods Surgical findings Diagnostic performance (deep lobe lesions)(%)* Deep (n = 4) Superficial (n = 15) Accuracy Sensitivity Specificity PPV NPV Direct Deep 2 0 89.5% 50.0% 100.0% 100.0% 88.2% Superficial 2 15 FNL Deep 1 2 73.7% 25.0% 86.7% 33.3% 81.3% Superficial 3 13 ( P >0.99) ( P >0.99) ( P = 0.50) RMVL Deep 2 1 84.2% 50.0% 93.3% 66.7% 87.5% Superficial 2 14 ( P >0.99) ( P >0.99) ( P >0.99) There was no significant difference in sensitivity, specificity and accuracy among three methods. FNL, facial nerve line; NPV, negative predictive value; PPV, positive predictive value; RMVL, retromandibular vein line. The relationship between tumors and the main trunk of IFN (1) superior part of the parotid gland : IFN invasion was confirmed by intraoperative records in 4 patients, and the facial nerve trunk was not invaded in 41 patients. The 3D-T2-FFE images showed facial nerve trunk invasion in the parotid gland in 7 patients, and the images of 38 patients showed no invasion. 3D-T2-FFE sequences were better in assessing facial nerve trunk invasion, with an accuracy of 93.3%, and no significant difference was shown when compared with the intraoperative results ( p = 0.248) (Fig. 5 ) (Supplementary Table). (2) inferior part of the parotid gland : the facial nerve trunk was not invaded in all 19 patients, as confirmed by intraoperative records. 3D-T2-FFE images revealed that there was no invasion of the IFN and no clear contact between the tumor and the main trunk in all 19 patients (Supplementary Table). Discussion In this study, 3D-T2-FFE showed high spatial resolution and tissue contrast for visualization of IFN and its primary branches in the parotid gland. The sensitivity and specificity for localizing parotid gland tumors by 3D-T2-FFE were significantly better than those of FNL. Additionally, the invasion status of parotid gland tumors can be observed on 3D-T2-FFE, which is an essential step in preserving the integrity of IFN before surgery. The IFN is difficult to identify on conventional MRI images due to its lack of contrast with the surrounding parotid parenchyma[ 23 , 24 ]. In recent years, most studies on IFN have been based on T2-weighted MRI (characterized by hyperintensity), but the detection rate of IFN varies due to differences in imaging sequences[ 8 , 24 , 25 ]. In a previous study[ 24 ], the identification of the main trunk of IFN is consistent. Distally, the alignment and morphological variability of the temporofacial and cervicofacial branches are greater than those of the main trunk of the IFN, which may contribute to inaccuracies in mapping the distal regions of these branches. Detectability of IFN on 3D-T2-FFE In the present study, the 3D-T2-FFE sequence was highly effective for visualizing the main trunk, temporofacial, and cervicofacial divisions of IFN. Visualization metrics revealed no significant differences between bilateral IFN and the nerves, indicating a symmetric bilateral distribution. However, the distal branches of the temporofacial and cervicofacial trunks in the present study were thin and easily confused with the parotid ducts, which showed hyperintensity on T2WI, and were also difficult to distinguish from the nerve. Kim et al.[ 21 ] visualized the facial nerve using the 3D-DESSwe sequence. This sequence successfully visualized the main trunk, temporofacial division, and cervicofacial division in 100%, 48%, and 36% of cases, respectively. In our study, visualization rates of the temporofacial and cervicofacial divisions were modestly lower on tumor-affected sides compared to healthy sides. At the same time, detection rates on healthy sides exceeded those previously reported by Kim et al[ 21 ]. Except for the main trunk, the detection rates of the two branches were slightly lower than those in the present study. These differences appear to be mainly attributed to different study subjects. Kim et al.[ 21 ] enrolled the patients with deep-lobe parotid tumors, where tumor location in some cases compromised visualization of the two major facial nerve divisions, resulting in moderately reduced detection rates. Localization of parotid gland tumors with 3D-T2-FFE and indirect methods In the superior part of the parotid gland, the direct method showed high sensitivity, specificity, and accuracy. The T2-FFE sequence was highly effective for visualizing the IFN, and tumor localization was more reliably determined using T2-FFE than with conventional indirect methods. Only one patient with the tumor in the deep lobe was classified as the superficial lobe during the evaluation process. The sensitivity and specificity of the 3D-T2-FFE were significantly improved in comparison to FNL. In a previous study[ 26 ], the accuracy of FNL for the assessment of deep lobe tumors is limited because FNL is influenced by the size of the lesion and the significant variation in the position of the posterior belly of the diastasis[ 1 , 27 ]. This study showed no significant difference between RMVL and 3D-T2-FFE in the superior part of the parotid gland. The RMVL method was more effective in the indirect methods, with a correct prediction of the parotid mass location in 84.4% of cases[ 28 ]. Although specificity (93.8%) was excellent, the variable position of RMVL, which a tumor can displace, was believed to lower the sensitivity of RMVL for parotid tumor localization[ 29 ]. In the inferior parotid gland, the facial nerve was mainly divided into primary branches or smaller secondary branches, and the localization of the tumor to the facial nerve branches was usually unclear. In this study, no significant difference was observed between the direct and indirect methods for determining tumor locations. 3D-T2-FFE showed a relatively low sensitivity for tumor localization, which was comparable to that of RMVL. Since the RMVL method is easier to use, it may have more diagnostic value than the direct method and the FNL method in the inferior part of the parotid gland. However, the indirect methods were unable to demonstrate IFN, and the direct method can serve as an essential complement. The relationship between tumors and IFN The IFN’s displacement, contact, or invasion by tumors makes it difficult to discern the relationship between them, which is one of the critical factors affecting postoperative IFN function[ 30 ]. Especially in the intraoperative period, IFN can be engulfed and invaded by tumors with distal branches that are invisible, which may lead to IFN injury. In a previous study[ 31 ], the relationship between the IFN and tumor was classified as displacement, contact, invasion, and unaffected, with displacement and contact distinguished by the presence of normal parotid tissue between the IFN and the tumor. However, this study found that it was usually difficult to differentiate between tumor displacement and contact on the images. However, the distal branch of the IFN at the site of extrusion or contact could still be identified. When the main trunk of IFN is difficult to trace on the image, it may suggest that the nerve has been invaded or encircled by the tumor[ 32 ]. Therefore, in this study, the relationship between IFN and the tumor was classified into invasion and non-invasion categories, and there was no statistically significant difference between the nerve invasion classification by 3D-T2-FFE and the intraoperative results. However, in this study, five tumors that appeared to be invasive on 3D-T2-FFE images turned out to be non-invasive at surgery. Compared with intraoperative records, the distal nerve was not clearly shown in 4 cases because it was adjacent to or in contact with the tumor. In one case, we misinterpreted it as nerve invasion because the tumor crossed the cervicofacial and temporofacial branches, and the distal branches were too thin to be detected on 3D-T2-FFE images. In addition, some studies[ 32 , 33 ] have suggested that invasion of the IFN by malignant tumors may lead to thickening and signal enhancement of the IFN. Still, in this study, the IFN of two patients was invaded by the tumor, which encircled or adhered to the nerve, while the thickening and signal enhancement of the IFN were not demonstrated. However, in this study, the small number of facial nerves invaded by tumors may lead to bias in statistical results. Four patients who confirmed tumor nerve invasion during surgery were reflected in the preoperative evaluation of magnetic resonance imaging. It can also be speculated that the 3D-T2-FFE sequence has a specific role in evaluating facial nerve invasion. Limitations Despite the promising results of 3D-T2-FFE, this study had several limitations. First, we only qualitatively assessed the visibility of IFN and the invasion of IFN by the tumor. It may be necessary to rely on diffusion tensor tractography to predict nerve invasion quantitatively[ 33 , 34 ]. This retrospective study has a limited sample size, necessitating future larger-scale investigations to validate the findings. We did not compare the 3D-T2-FFE with other relevant methods, and further studies are necessary to assess the differences among multiple MRN techniques. In addition, the number of tumors in the deep lobe of the parotid gland was small, which may have introduced potential biases during the assessment. The distal fine branches of the facial nerve within the parotid gland exhibit considerable anatomical variation. In our study, the visualization of these distal branches was limited, resulting in an insufficient evaluation of them. Future studies may require further optimization of scanning protocols to enhance their visualization. Finally, we did not objectively assess the effect of the parotid parenchymal signal on the visibility of IFN, which warrants further investigation. Conclusions 3D-T2-FFE can display the IFN in the parotid gland directly and localize the tumor more accurately than conventional indirect methods in the superior parotid group. In the inferior parotid group, the RMVL method was recommended for the tumor localization. Additionally, 3D-T2-FFE can be used to assess the relationship between the tumor and IFN, which may help reduce the risk of IFN injury during surgery. Therefore, 3D-T2-FFE can be used as an essential complementary imaging method for clinical applications. Abbreviations CPR curvilinear planar reconstruction CISS constructive inference in steady-state DESSwe double-echo steady-state with water excitation DW diffusion weighted FNL facial nerve line FFE fast field echo FIESTA fast imaging employing steady-state acquisition FISP fast imaging with steady-state precession ICC intraclass correlation coefficient IFN intraparotid facial nerve MRI magnetic resonance imaging MRN magnetic resonance neurography NPV negative predictive value PPV positive predictive value PSIF reversed fast imaging with steady-state precession RMVL retromandibular vein line ROI region of interest SIR signal intensity ratio SSFP steady-state free precession TR time of repetition TE time of echo Declarations Ethics approval and consent to participate: This study was approved by the Ethics Committee of The First Affiliated Hospital of Dalian Medical University (license number: PJ-KS-KY-2023-578), certifying that the study was conducted in accordance with the ethical standards outlined in the 1964 Declaration of Helsinki and its subsequent amendments, or with comparable ethical standards. Consent for publication: In accordance with the legislative requirements of our country and the approval granted by the Ethics Committee of the First Affiliated Hospital of Dalian Medical University, the need for written informed consent from the participants was waived for this study. Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests: The authors declare that they have no competing interests. Funding: This study was supported by the Medical Education Research Project of Liaoning Province (No. 2022-N005-05). Authors' contributions: Yihua Wang: writing-original draft preparation, statistical analysis, data acquisition. Haowen Zheng: data acquisition. Jian Jiang: statistical analysis, writing, reviewing, and editing. Liangjie Lin: software, visualization, and writing—review and editing. Haitao Huang and Juntao Ma: investigation, resources, and data curation. Qingwei Song: resources and data curation. Lijun Wang: methodology, supervision, writing, reviewing, and editing. Ailian Liu: supervision. Acknowledgments: The authors would like to thank all participants for their valuable support in this study. References Ishibashi M, Fujii S, Kawamoto K, Nishihara K, Matsusue E, Kodani K, 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. 2010;52(11):1037-45. https://doi.org/10.1007/s00234-010-0718-1. Ozgen Mocan B. Imaging anatomy and pathology of the intracranial and intratemporal facial nerve. Neuroimaging Clin N Am. 2021;31(4):553-70. https://doi.org/10.1016/j.nic.2021.06.001. Chhabda S, Leger DS, Lingam RK. Imaging the facial nerve: a contemporary review of anatomy and pathology. 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1","display":"","copyAsset":false,"role":"figure","size":643340,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of patient inclusion and exclusion.\u003c/p\u003e\n\u003cp\u003eIFN, the intraparotid facial nerve; RNVL, retromandibular vein line; FNL, facial nerve line.\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7604757/v1/2638e8646492b9e77ccb0456.png"},{"id":94917601,"identity":"d00c18b5-8463-4453-ab22-e396a6d4a2dd","added_by":"auto","created_at":"2025-11-01 11:53:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":673658,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(\u003c/strong\u003ea) Facial nerve main trunk (yellow arrow), temporofacial division (red arrow), and cervicofacial division (white arrow) (label 1: brain hemisphere, label 2: cerebellar hemisphere, label 3: parotid gland). (b) The three-dimensional reconstructed image displayed the main trunk of the facial nerve, its temporofacial division, and its cervicofacial division. (c)\u003cstrong\u003e \u003c/strong\u003eMeasurement of signal intensity values of IFN. ROIs were outlined at the point where IFN entered the parotid parenchyma (white arrow) and about 5-10 mm from the nerve's entry into the parotid parenchyma (yellow arrow), with the ROI size of 5 mm\u003csup\u003e2\u003c/sup\u003e (label 4: cerebellar hemisphere, label 5: mastoid process, label 6: parotid gland, label 7: pinna). (d) Measurement of parotid parenchyma signal intensity with the ROI size of 15 mm\u003csup\u003e2\u003c/sup\u003e. IFN: intraparotid facial nerve; ROI, regions of interest.\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7604757/v1/44d642ec7f10e2a5e444425f.png"},{"id":94917624,"identity":"9ec65492-1d7d-4e6e-a2fd-bc55f52f2be7","added_by":"auto","created_at":"2025-11-01 11:53:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":7816759,"visible":true,"origin":"","legend":"\u003cp\u003eA 68-year-old man with a pleomorphic adenoma of the left parotid gland. (a) T2WI showed a heterogeneous signal mass in the left parotid gland. (b~d) The 3D-T2-FFE image (b), CPR-reconstructed image (c), and three-dimensional reconstructed image (d) demonstrated the main trunk of the facial nerve posterolaterally displaced by the tumor (T) (arrow). CPR,curvilinear planar reconstruction;T2WI, T2-weighted imaging; 3D-T2-FFE, three-dimensional T2-weighted fast field echo imaging.\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7604757/v1/1678270882362b2b5ea1c120.png"},{"id":94917598,"identity":"ccb7d85e-2133-4f68-ba23-fd5a31c422d0","added_by":"auto","created_at":"2025-11-01 11:53:49","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":5283781,"visible":true,"origin":"","legend":"\u003cp\u003eA 29-year-old woman with pleomorphic adenoma of the right parotid gland. (a) T2WI showed a heterogeneous signal mass in the right parotid gland. (b~e) The 3D-T2-FFE image (b), (d~f) the CPR-reconstructed image (c), and the three-dimensional reconstructed image (d~e) showed the facial nerve (arrow) encircling the deep surface of the mass (T). (f) Surgery showed that the main trunk (blue arrow), the temporofacial division (white arrow), and the cervicofacial division (yellow arrow) were located at the deep surface of the mass. CPR, curvilinear planar reconstruction;T2WI, T2-weighted imaging; 3D-T2-FFE, three-dimensional T2-weighted fast field echo imaging.\u003c/p\u003e","description":"","filename":"figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7604757/v1/6617dd85cb6c2cf4152e5474.png"},{"id":94917609,"identity":"61ab713d-0d6f-4218-88ff-ce08c634aac3","added_by":"auto","created_at":"2025-11-01 11:53:50","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":4785616,"visible":true,"origin":"","legend":"\u003cp\u003eA 64-year-old man with squamous cell carcinoma of the right parotid gland. (a) T2WI. (b~d) The coronal T2-FFE, CPR image, and three-dimensional reconstructed image demonstrated that the main trunk of the facial nerve (arrow) was engulfed by the carcinoma (T), and the distal segment of the main trunk was not visible. CPR,curvilinear planar reconstruction; T2WI, T2-weighted imaging; T2-FFE, three-dimensional T2-weighted fast field echo imaging.\u003c/p\u003e","description":"","filename":"figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7604757/v1/984884f447da7d1ac6e76000.png"},{"id":104250709,"identity":"048f11ef-c700-459a-93f5-762eb4449513","added_by":"auto","created_at":"2026-03-09 16:06:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":18873877,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7604757/v1/d7b3e874-94ec-4bf0-bd6d-63fa9f720d71.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Three-dimensional T2-weighted fast field echo imaging in the determination of the relationship between the intraparotid facial nerve and parotid tumors","fulltext":[{"header":"Background","content":"\u003cp\u003eThe anatomical structure of the parotid gland is complex[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The extracranial segment of the facial nerve and its main branches are mainly located in the parotid gland, which separates the superficial and deep lobes[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In the healthy parotid gland, the intraparotid facial nerve (IFN) does not adhere to the parotid gland tissue because of the nerve membrane[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, when tumors occur, the anatomical position of the IFN may change, and adhesions with tumors may also develop, causing increased difficulty in completely excising the tumor while preserving nerve function[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Clinically, the incidence of facial nerve injury is significantly higher in tumors of the deep lobe than in the superficial lobe and inferior part of the parotid gland[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The established indirect methods for separating intraparotid lesions into superficial or deep, such as the facial nerve line (FNL) and retromandibular vein line (RMVL), are often used to evaluate the course of IFN roughly, but are not entirely accurate. The RMVL is perpendicular to the lateral edge of the retromandibular vein. The FNL connects the lateral margin of the posterior belly of the digastric muscle to the lateral margin of the ascending ramus of the mandible. Therefore, a good depiction of IFN before operation is of great significance in effectively protecting IFN during operation and improving patients\u0026rsquo; quality of life after operation [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Especially in malignant tumors, the presurgical evaluation of IFN infiltration is crucial for patients and surgeons to be aware of.\u003c/p\u003e\u003cp\u003eMagnetic resonance neurography (MRN) offers an ideal technique for visualizing parotid tumors surrounded by neurovascular structures, particularly in the IFN region [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, at present, the tissue contrast for IFN in magnetic resonance imaging (MRI) is not sufficient, and the vascular signal cannot be suppressed entirely. Some studies[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] have utilized the three-dimensional constructive interference in steady-state (3D-CISS) sequence, the three-dimensional fast imaging employing steady-state acquisition (3D-FIESTA) sequence, and other high-resolution MRI sequences to demonstrate the IFN. However, these methods demonstrate IFN with hypointensity relative to the parotid gland parenchyma, and the contrast is not particularly obvious. Since then, the three-dimensional double-echo steady-state with water excitation (3D-DESSwe) sequence and the three-dimensional reversed fast imaging with steady-state precession and diffusion-weighted (3D-PSIF-DWI) sequence have also been gradually used for the display of IFN[\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The IFN and parotid gland duct show hyperintensity, which improves the display of IFN. However, this method can lead to confusion in distinguishing the nerve from the duct, and the imaging sequence is complex [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn this study, 3D T2-weighted fast field echo imaging (3D-T2-FFE) was attempted using a fast steady-state free precession (SSFP)[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] sequence with a low turning angle, isotropic volumetric acquisition, and the shortest repetition and echo times for the visualization of IFN. Combined with effective fat suppression and 3D curvilinear planar reconstruction, 3D-T2-FFE may help clarify the relationship between the tumor and nerve. The other sequences have obtained a large number of clinical validations, but the application value of 3D-T2-FFE in parotid tumors has not been systematically evaluated. Thus, this study aimed to assess the performance of IFN and the localization of tumors in 3D-T2-FFE.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003ePatients enrollment\u003c/h2\u003e\u003cp\u003e The institutional review board of our hospital approved our retrospective study (license number: PJ-KS-KY-2023-578). This study includes 111 patients who were confirmed with parotid gland tumors\u003c/p\u003e\u003cp\u003ein our hospital between May 2019 to October 2023. Inclusion criteria were: (1) parotid gland tumor patients with complete clinical information (included complete and detailed surgical records, clarified the location of tumor and the facial nerve) and confirmed pathological type; (2) no contraindication to MRI examination, and 3.0T MRI examination within 1 week before treatment (including the 3D-T2-FFE sequence); (3) no surgery or other injury in parotid glands before the MRI examination. Exclusion criteria were: (1) motion artifacts affected the IFN observation; (2) other clinically proven parotid disorders; (3) multiple tumors in the parotid glands bilaterally, affecting the score. The flow chart of patient inclusion and exclusion is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAll included patients underwent surgical treatment in the Department of Stomatology at our hospital within one week of the MRI examination. All extracted tumor tissues were routinely subjected to histopathological examination after surgery.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eMR imaging\u003c/h3\u003e\n\u003cp\u003eAxial T1-weighted imaging (T1WI), axial fat-suppressed T2-weighted imaging (T2WI), and 3D-T2-FFE imaging were performed using a 3.0T MR scanner (Ingenia CX; Philips Healthcare, Best, the Netherlands) with a 32-channel phase-array head coil. The scanning parameters were listed 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\u003eScan Parameters of T1WI, T2WI and 3D-T2-FFE\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026times;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026times;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026times;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTR\u003c/p\u003e\u003cp\u003e(ms)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTE\u003c/p\u003e\u003cp\u003e(ms)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eVoxel\u003c/p\u003e\u003cp\u003e(mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFOV\u003c/p\u003e\u003cp\u003e(mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMatrix\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNSA\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eFA\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eT\u003c/b\u003e\u003csub\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sub\u003e\u003cb\u003eWI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e466.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c4\"\u003e\u003cp\u003e0.55\u0026times;0.72\u0026times;4.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c5\"\u003e\u003cp\u003e200\u0026times;200\u0026times;89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c6\"\u003e\u003cp\u003e364\u0026times;257\u0026times;18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e90\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eT\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e\u003cb\u003eWI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2122.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e112.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c4\"\u003e\u003cp\u003e0.70\u0026times;0.70\u0026times;4.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c5\"\u003e\u003cp\u003e300\u0026times;300\u0026times;89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c6\"\u003e\u003cp\u003e428\u0026times;428\u0026times;18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e90\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e3D-T2-FFE\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c4\"\u003e\u003cp\u003e0.65\u0026times;0.65\u0026times;1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c5\"\u003e\u003cp\u003e220\u0026times;220\u0026times;65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c6\"\u003e\u003cp\u003e340\u0026times;339\u0026times;130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e30\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e3D-T2-FFE, three-dimensional T2-weighted imaging fast field echo; T1WI, T1-weighted imaging; T2WI, T2-weighted imaging; TR, repetition time; TE, echo time; FOV, field of view; NSA, number of signal average; FA, flip angle.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eImages were automatically transferred to Intellispace Portal (ISP v9.0, Philips Healthcare) workstation for analysis: The curvilinear planar reconstruction (CPR), three-dimensional multiplanar reconstruction, and image evaluation were performed by two experienced radiologists in MRI diagnosis independently (radiologists 1 and 2 have 3 and 20 years of MRI diagnosis experience, respectively) who were blinded to clinical information. The evaluation results were finally compared with the intraoperative records.\u003c/p\u003e\n\u003ch3\u003eEvaluation of the demonstration of IFN in the contralateral parotid gland\u003c/h3\u003e\n\u003cp\u003eThe two observers evaluated the display of the IFN main trunk and two divisions (temporofacial division and cervicofacial division) in the bilateral parotid glands (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The identification certainty of IFN was scored independently on the tumor side and the contralateral sides with four grades as follows[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]: 0, the anatomical structure was not visible; 1, the main trunk can be visible but two division was not visible, and the signal intensity of IFN was lower than that of cerebellum; 2, the main trunk can be visible, temporofacial or cervicofacial division was visible and the signal intensity of IFN was lower than that of cerebellum; 3, the main trunk and two division was visible, the signal was equivalent to the normal cerebellum.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTwo observers measured the facial nerve signal intensity value on the reconstructed image. Regions of interest (ROIs) were placed at the nerve where it enters the parotid parenchyma and the place where the nerve enters the parotid parenchyma at a distance of about 5\u0026thinsp;~\u0026thinsp;10 mm. The size of the ROI was about 1\u0026thinsp;~\u0026thinsp;5 mm\u003csup\u003e2\u003c/sup\u003e. At the same time, the signal intensity value of the parotid parenchyma was measured in the same slice. The ROI was approximately 10\u0026thinsp;~\u0026thinsp;15 mm\u003csup\u003e2\u003c/sup\u003e, avoiding parotid ducts and small vessels in the parotid gland as much as possible. The signal intensity ratio (SIR) is the ratio between signal intensities of the facial nerve and the parotid gland in the same slice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eLocalization of parotid gland tumors with 3D-T2-FFE and indirect methods\u003c/h3\u003e\n\u003cp\u003eBecause the facial nerve trunk could not be shown at score 0, images of cases scoring 1 and above in the tumor side of the parotid gland were selected, and cases scoring 0 were excluded (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOn the reconstructed coronal 3D-T2-FFE images, the parotid gland was divided into the superior and inferior parts with the earlobe level as reference[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. When the most significant slice of the tumor was \u0026ge;\u0026thinsp;50% located above the earlobe level, the tumor was considered to be the superior tumor. Conversely, it was deemed to be located in the inferior part of the parotid gland.\u003c/p\u003e\u003cp\u003eThe tumor location was categorized as deep or superficial lobes on the 3D-T2-FFE images. When the tumor was located entirely on the medial side of the IFN and its branches, or \u0026ge;\u0026thinsp;50% of the tumor was located on the medial side, it was defined as a tumor of the deep lobe. The above was the direct method. On the contrary, it was located in the superficial lobe[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The two indirect methods, the FNL and RMVL, were also recorded on axial T2-weighted images. The RMVL is perpendicular to the lateral edge of the retromandibular vein, and the FNL connects the lateral margin of the posterior belly of the digastric muscle to the lateral margin of the ascending ramus of the mandible[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The standard for deep and superficial lobes was the same as that mentioned above. The two observers used direct 3D-T2-FFE and indirect FNL and RMVL methods for tumor location. If there were divergent assessments, a consensus was reached through discussion.\u003c/p\u003e\n\u003ch3\u003eThe relationship between the tumor and IFN\u003c/h3\u003e\n\u003cp\u003eFinally, the relationship between the tumor and IFN trunk was evaluated on the reconstructed images.\u003c/p\u003e\u003cp\u003eThe IFN was considered invaded when the main trunk of IFN was wholly or partially encased by the tumor (a tumor surrounding of\u0026gt;50% or 100% of the circumference of IFN on the reconstructed image)[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], and the distal segment of IFN was not visible. Additionally, apart from the above, it was considered that IFN was non-invasive.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eSurgical findings\u003c/h2\u003e\u003cp\u003eThe relationship between IFN and a parotid tumor was confirmed by reviewing the surgical report.\u003c/p\u003e\u003cp\u003eThis was considered the reference standard and used to determine the diagnostic performance of the researched methods evaluated in this study.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eFor statistical analyses, we used SPSS (version 25.0; IBM Corp., Armonk, NY, USA) and MedCalc (version 20; MedCalc Software Ltd, Ostend, Belgium). The interobserver reliability was assessed via intraclass correlation coefficient (ICC) and Kappa test (excellent, ICC\u0026thinsp;\u0026gt;\u0026thinsp;0.75 or Kappa\u0026thinsp;\u0026ge;\u0026thinsp;0.85; good, ICC: 0.60\u0026thinsp;~\u0026thinsp;0.74 or Kappa: 0.60\u0026thinsp;~\u0026thinsp;0.85; fair, ICC: 0.40\u0026thinsp;~\u0026thinsp;0.59 or Kappa: 0.45\u0026thinsp;~\u0026thinsp;0.60; poor, ICC\u0026thinsp;\u0026lt;\u0026thinsp;0.40 or Kappa\u0026thinsp;\u0026lt;\u0026thinsp;0.45). The patient's age and SIR were tested for normal distribution using the Shapiro-Wilk test. The Mann-Whitney U test was used to compare the difference in SIR between the healthy and tumor groups. Chi-square test or Fisher's exact test was used to compare categorical variables. The diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for localizing parotid lesions using each method were calculated and compared using the McNemar test. Differences with \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eBased on inclusion and exclusion criteria, a total of 64 patients from May 2019 to October 2023 were included for image analysis. The age of patients in the superficial lobe group was 26\u0026thinsp;~\u0026thinsp;87 years, with a mean age of (56.9\u0026thinsp;\u0026plusmn;\u0026thinsp;15.5) years. At the same time, the age in the deep lobe group was 26\u0026thinsp;~\u0026thinsp;69 years, with a mean age of (51.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.9) years. No statistically significant difference was found in the age, gender, and pathology type between the deep and superficial lobe groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (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\u003ePatients Confirmed by Surgery\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eClinical outcomes\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSuperficial lobe\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;47)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDeep lobe\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;17)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e56.9\u0026thinsp;\u0026plusmn;\u0026thinsp;15.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.142\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.717\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHistologic types\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBenign tumor\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.202\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePleomorphic adenoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWarthin tumor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBase cell adenoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcidophile adenoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeurinoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePapillary cystadenoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMalignant tumor\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026gt;0.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSquamous cell carcinoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdenoid cystic carcinoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcinic cell carcinoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecretory carcinoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMalignant neurofibroma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSalivary duct carcinoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBasal cell adenocarcinoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoorly-differentiated carcinoma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eNo statistically significant difference was found in age, gender, or pathology type between the deep and superficial lobe groups.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eDetectability of IFN on 3D-T2-FFE\u003c/h2\u003e\u003cp\u003eFor the IFN visibility score of the contralateral side (Kappa\u0026thinsp;=\u0026thinsp;0.667), 26 cases were scored 3 (40.6%), 20 were scored 2 (31.3%), and 18 were scored 1 (28.1%). For the IFN visibility score of the tumor side (Kappa\u0026thinsp;=\u0026thinsp;0.693), 18 cases were scored 3 (28.1%), 21 were scored 2 (32.8%), and 25 were scored 1 (39.1%).\u003c/p\u003e\u003cp\u003eThe display rates (Kappa\u0026thinsp;=\u0026thinsp;0.797) of the IFN main trunk, temporofacial division, and cervicofacial division in the healthy parotid gland on reconstructed images were 100%, 67.2%, and 60.9%, respectively. The display rates (Kappa\u0026thinsp;=\u0026thinsp;0.602) of the main trunk, temporofacial division, and cervicofacial division on the tumor side were 100%, 60.9%, and 35.9%, respectively. Interobserver agreement was good for the parameters of IFN and parotid parenchyma signal values, as assessed by two independent readers (ICC\u0026thinsp;\u0026gt;\u0026thinsp;0.70). The SIR on the healthy side was 1.76 (1.29, 2.10), and 1.57 (1.17, 2.13) on the tumor side.\u003c/p\u003e\u003cp\u003eThere was no statistically significant difference between the contralateral side and tumor side in visibility score (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.270), display rates (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.238), and IFN SIR (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.336) (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\u003eDetectability of IFN on 3D-T2-FFE\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ehealthy group (n\u0026thinsp;=\u0026thinsp;64)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003etumor group (n\u0026thinsp;=\u0026thinsp;64)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003edisplay rate\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.238\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIFN main trunk (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e64(100.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64(100.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003etemporofacial division(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43(67.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39(60.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecervicofacial division (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39(60.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23(35.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIFN SIR\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.76(1.29, 2.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.57(1.17, 2.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.336\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eScore\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.270\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eThere was no statistically significant difference between the contralateral side and tumor side in visibility score (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.270), display rates (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.238), and IFN SIR (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.336).\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eLocalization of parotid gland tumors with 3D-T2-FFE and indirect methods\u003c/h2\u003e\u003cp\u003eIntraoperative records showed that 17 cases were located in the deep lobe, and 47 cases were located in the superficial lobe. Interobserver agreement was good for the parameters of tumor localization as assessed by two independent readers. (direct method: Kappa\u0026thinsp;=\u0026thinsp;0.752; FNL: Kappa\u0026thinsp;=\u0026thinsp;0.736; RMVL: Kappa\u0026thinsp;=\u0026thinsp;0.712).\u003c/p\u003e\u003cp\u003e(1) \u003cb\u003esuperior part of the parotid gland\u003c/b\u003e: Intraoperative records showed that 13 cases were located in the deep lobe of the parotid gland, and 45 cases were located in the superficial lobe. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy for determining the localization of tumors in the deep lobe of the parotid gland on 3D-T2-FFE reconstructed images were 92.3%, 100.0%, 100.0%, 96.9%, and 97.8%, respectively. The sensitivity, specificity, PPV, NPV, and accuracy of the FNL methods for assessing deep lobe tumors of the parotid gland were 46.2%, 81.3%, 50.0%, 78.8%, and 71.1%, respectively. The sensitivity, specificity, PPV, NPV, and accuracy of RMVL methods for assessing were 61.5%, 93.8%, 80.0%, 85.7%, and 84.4%, respectively.\u003c/p\u003e\u003cp\u003e3D-T2-FFE showed significantly better sensitivity and specificity than those of FNL (sensitivity:\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031, specificity: \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031, Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), and there was no significant difference in accuracy between 3D-T2-FFE and FNL. There was no significant difference in sensitivity, specificity, and accuracy between 3D-T2-FFE and RMVL (all \u003cem\u003ep\u003c/em\u003e\u0026gt;0.05, Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDiagnostic Performance of Localization of Parotid Tumors in the Superior Group with Three Methods\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" 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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eSurgical findings\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c8\" namest=\"c4\"\u003e\u003cp\u003eDiagnostic performance (deep lobe lesions)(%)*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDeep\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSuperficial\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;32)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAccuracy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSensitivity\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSpecificity\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePPV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNPV\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDirect\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDeep\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e97.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e92.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e100.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e96.9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSuperficial\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFNL\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDeep\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e71.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e46.2%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e81.3%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e50.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e78.8%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSuperficial\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026gt;0.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRMVL\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDeep\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e84.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e61.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e93.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e80.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e85.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSuperficial\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026gt;0.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.125)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.500)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e*Statistical analyses (\u003cem\u003eP\u003c/em\u003e values) were performed comparing the direct method with each indirect method. 3D-T2-FFE showed significantly better sensitivity and specificity than those of FNL.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003eFNL, facial nerve line; NPV, negative predictive value; PPV, positive predictive value; RMVL, retromandibular vein line.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e(2) \u003cb\u003einferior part of the parotid gland\u003c/b\u003e: Intraoperative records showed that 4 cases were in the deep lobe, and 15 cases were in the superficial lobe. The sensitivity, specificity, PPV, NPV, and accuracy for determining the localization of tumors in the deep lobe of the parotid gland on 3D-T2-FFE reconstructed images were 50.0%, 100.0%, 100.0%, 88.2%, and 89.5%, respectively. The sensitivity, specificity, PPV, NPV, and accuracy of the FNL method for assessing deep lobe tumors of the parotid gland were 25.0%, 86.7%, 33.3%, 81.3%, 73.7%, and those for RMVL were 50.0%, 93.3%, 66.7%, 87.5%, 84.2%, respectively. There was no significant difference in sensitivity, specificity, and accuracy among the three methods (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDiagnostic Performance of Localization of Parotid Tumors in the Inferior Group with Three Methods\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" 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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eSurgical findings\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c8\" namest=\"c4\"\u003e\u003cp\u003eDiagnostic performance (deep lobe lesions)(%)*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDeep\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;4)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSuperficial\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAccuracy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSensitivity\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSpecificity\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePPV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNPV\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDirect\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDeep\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e89.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e50.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e100.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e88.2%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSuperficial\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFNL\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDeep\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e86.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e33.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e81.3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSuperficial\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026gt;0.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026gt;0.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRMVL\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDeep\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e84.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e50.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e93.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e66.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e87.5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSuperficial\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026gt;0.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026gt;0.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026gt;0.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003eThere was no significant difference in sensitivity, specificity and accuracy among three methods.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003eFNL, facial nerve line; NPV, negative predictive value; PPV, positive predictive value; RMVL, retromandibular vein line.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eThe relationship between tumors and the main trunk of IFN\u003c/h2\u003e\u003cp\u003e(1) \u003cb\u003esuperior part of the parotid gland\u003c/b\u003e: IFN invasion was confirmed by intraoperative records in 4 patients, and the facial nerve trunk was not invaded in 41 patients. The 3D-T2-FFE images showed facial nerve trunk invasion in the parotid gland in 7 patients, and the images of 38 patients showed no invasion. 3D-T2-FFE sequences were better in assessing facial nerve trunk invasion, with an accuracy of 93.3%, and no significant difference was shown when compared with the intraoperative results (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.248) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) (Supplementary Table).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e(2) \u003cb\u003einferior part of the parotid gland\u003c/b\u003e: the facial nerve trunk was not invaded in all 19 patients, as confirmed by intraoperative records. 3D-T2-FFE images revealed that there was no invasion of the IFN and no clear contact between the tumor and the main trunk in all 19 patients (Supplementary Table).\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, 3D-T2-FFE showed high spatial resolution and tissue contrast for visualization of IFN and its primary branches in the parotid gland. The sensitivity and specificity for localizing parotid gland tumors by 3D-T2-FFE were significantly better than those of FNL. Additionally, the invasion status of parotid gland tumors can be observed on 3D-T2-FFE, which is an essential step in preserving the integrity of IFN before surgery.\u003c/p\u003e\u003cp\u003eThe IFN is difficult to identify on conventional MRI images due to its lack of contrast with the surrounding parotid parenchyma[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In recent years, most studies on IFN have been based on T2-weighted MRI (characterized by hyperintensity), but the detection rate of IFN varies due to differences in imaging sequences[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In a previous study[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], the identification of the main trunk of IFN is consistent. Distally, the alignment and morphological variability of the temporofacial and cervicofacial branches are greater than those of the main trunk of the IFN, which may contribute to inaccuracies in mapping the distal regions of these branches.\u003c/p\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eDetectability of IFN on 3D-T2-FFE\u003c/h2\u003e\u003cp\u003eIn the present study, the 3D-T2-FFE sequence was highly effective for visualizing the main trunk, temporofacial, and cervicofacial divisions of IFN. Visualization metrics revealed no significant differences between bilateral IFN and the nerves, indicating a symmetric bilateral distribution. However, the distal branches of the temporofacial and cervicofacial trunks in the present study were thin and easily confused with the parotid ducts, which showed hyperintensity on T2WI, and were also difficult to distinguish from the nerve.\u003c/p\u003e\u003cp\u003eKim et al.[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] visualized the facial nerve using the 3D-DESSwe sequence. This sequence successfully visualized the main trunk, temporofacial division, and cervicofacial division in 100%, 48%, and 36% of cases, respectively. In our study, visualization rates of the temporofacial and cervicofacial divisions were modestly lower on tumor-affected sides compared to healthy sides. At the same time, detection rates on healthy sides exceeded those previously reported by Kim et al[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Except for the main trunk, the detection rates of the two branches were slightly lower than those in the present study. These differences appear to be mainly attributed to different study subjects. Kim et al.[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] enrolled the patients with deep-lobe parotid tumors, where tumor location in some cases compromised visualization of the two major facial nerve divisions, resulting in moderately reduced detection rates.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eLocalization of parotid gland tumors with 3D-T2-FFE and indirect methods\u003c/h2\u003e\u003cp\u003eIn the superior part of the parotid gland, the direct method showed high sensitivity, specificity, and accuracy. The T2-FFE sequence was highly effective for visualizing the IFN, and tumor localization was more reliably determined using T2-FFE than with conventional indirect methods. Only one patient with the tumor in the deep lobe was classified as the superficial lobe during the evaluation process. The sensitivity and specificity of the 3D-T2-FFE were significantly improved in comparison to FNL. In a previous study[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], the accuracy of FNL for the assessment of deep lobe tumors is limited because FNL is influenced by the size of the lesion and the significant variation in the position of the posterior belly of the diastasis[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study showed no significant difference between RMVL and 3D-T2-FFE in the superior part of the parotid gland. The RMVL method was more effective in the indirect methods, with a correct prediction of the parotid mass location in 84.4% of cases[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Although specificity (93.8%) was excellent, the variable position of RMVL, which a tumor can displace, was believed to lower the sensitivity of RMVL for parotid tumor localization[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn the inferior parotid gland, the facial nerve was mainly divided into primary branches or smaller secondary branches, and the localization of the tumor to the facial nerve branches was usually unclear. In this study, no significant difference was observed between the direct and indirect methods for determining tumor locations. 3D-T2-FFE showed a relatively low sensitivity for tumor localization, which was comparable to that of RMVL. Since the RMVL method is easier to use, it may have more diagnostic value than the direct method and the FNL method in the inferior part of the parotid gland. However, the indirect methods were unable to demonstrate IFN, and the direct method can serve as an essential complement.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eThe relationship between tumors and IFN\u003c/h2\u003e\u003cp\u003eThe IFN\u0026rsquo;s displacement, contact, or invasion by tumors makes it difficult to discern the relationship between them, which is one of the critical factors affecting postoperative IFN function[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Especially in the intraoperative period, IFN can be engulfed and invaded by tumors with distal branches that are invisible, which may lead to IFN injury. In a previous study[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], the relationship between the IFN and tumor was classified as displacement, contact, invasion, and unaffected, with displacement and contact distinguished by the presence of normal parotid tissue between the IFN and the tumor. However, this study found that it was usually difficult to differentiate between tumor displacement and contact on the images. However, the distal branch of the IFN at the site of extrusion or contact could still be identified. When the main trunk of IFN is difficult to trace on the image, it may suggest that the nerve has been invaded or encircled by the tumor[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Therefore, in this study, the relationship between IFN and the tumor was classified into invasion and non-invasion categories, and there was no statistically significant difference between the nerve invasion classification by 3D-T2-FFE and the intraoperative results.\u003c/p\u003e\u003cp\u003eHowever, in this study, five tumors that appeared to be invasive on 3D-T2-FFE images turned out to be non-invasive at surgery. Compared with intraoperative records, the distal nerve was not clearly shown in 4 cases because it was adjacent to or in contact with the tumor. In one case, we misinterpreted it as nerve invasion because the tumor crossed the cervicofacial and temporofacial branches, and the distal branches were too thin to be detected on 3D-T2-FFE images. In addition, some studies[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] have suggested that invasion of the IFN by malignant tumors may lead to thickening and signal enhancement of the IFN. Still, in this study, the IFN of two patients was invaded by the tumor, which encircled or adhered to the nerve, while the thickening and signal enhancement of the IFN were not demonstrated. However, in this study, the small number of facial nerves invaded by tumors may lead to bias in statistical results. Four patients who confirmed tumor nerve invasion during surgery were reflected in the preoperative evaluation of magnetic resonance imaging. It can also be speculated that the 3D-T2-FFE sequence has a specific role in evaluating facial nerve invasion.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eDespite the promising results of 3D-T2-FFE, this study had several limitations. First, we only qualitatively assessed the visibility of IFN and the invasion of IFN by the tumor. It may be necessary to rely on diffusion tensor tractography to predict nerve invasion quantitatively[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. This retrospective study has a limited sample size, necessitating future larger-scale investigations to validate the findings. We did not compare the 3D-T2-FFE with other relevant methods, and further studies are necessary to assess the differences among multiple MRN techniques. In addition, the number of tumors in the deep lobe of the parotid gland was small, which may have introduced potential biases during the assessment. The distal fine branches of the facial nerve within the parotid gland exhibit considerable anatomical variation. In our study, the visualization of these distal branches was limited, resulting in an insufficient evaluation of them. Future studies may require further optimization of scanning protocols to enhance their visualization. Finally, we did not objectively assess the effect of the parotid parenchymal signal on the visibility of IFN, which warrants further investigation.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003e3D-T2-FFE can display the IFN in the parotid gland directly and localize the tumor more accurately than conventional indirect methods in the superior parotid group. In the inferior parotid group, the RMVL method was recommended for the tumor localization. Additionally, 3D-T2-FFE can be used to assess the relationship between the tumor and IFN, which may help reduce the risk of IFN injury during surgery. Therefore, 3D-T2-FFE can be used as an essential complementary imaging method for clinical applications.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCPR curvilinear planar reconstruction\u003c/p\u003e\n\u003cp\u003eCISS constructive inference in steady-state\u003c/p\u003e\n\u003cp\u003eDESSwe double-echo steady-state with water excitation\u003c/p\u003e\n\u003cp\u003eDW diffusion weighted\u003c/p\u003e\n\u003cp\u003eFNL facial nerve line\u003c/p\u003e\n\u003cp\u003eFFE fast field echo\u003c/p\u003e\n\u003cp\u003eFIESTA fast imaging employing steady-state acquisition\u003c/p\u003e\n\u003cp\u003eFISP fast imaging with steady-state precession\u003c/p\u003e\n\u003cp\u003eICC intraclass correlation coefficient\u003c/p\u003e\n\u003cp\u003eIFN intraparotid facial nerve \u003c/p\u003e\n\u003cp\u003eMRI magnetic resonance imaging\u003c/p\u003e\n\u003cp\u003eMRN magnetic resonance neurography\u003c/p\u003e\n\u003cp\u003eNPV negative predictive value\u003c/p\u003e\n\u003cp\u003ePPV positive predictive value\u003c/p\u003e\n\u003cp\u003ePSIF reversed fast imaging with steady-state precession\u003c/p\u003e\n\u003cp\u003eRMVL retromandibular vein line\u003c/p\u003e\n\u003cp\u003eROI region of interest\u003c/p\u003e\n\u003cp\u003eSIR signal intensity ratio\u003c/p\u003e\n\u003cp\u003eSSFP steady-state free precession\u003c/p\u003e\n\u003cp\u003eTR time of repetition\u003c/p\u003e\n\u003cp\u003eTE time of echo\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e This study was approved by the Ethics Committee of The First Affiliated Hospital of Dalian Medical University (license number: PJ-KS-KY-2023-578), certifying that the study was conducted in accordance with the ethical standards outlined in the 1964 Declaration of Helsinki and its subsequent amendments, or with comparable ethical standards.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e In accordance with the legislative requirements of our country and the approval granted by the Ethics Committee of the First Affiliated Hospital of Dalian Medical University, the need for written informed consent from the participants was waived for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis study was supported by the Medical Education Research Project of Liaoning Province (No. 2022-N005-05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u0026nbsp;\u003c/strong\u003eYihua Wang: writing-original draft preparation, statistical analysis, data acquisition. Haowen Zheng: data acquisition. Jian Jiang: statistical analysis, writing, reviewing, and editing. Liangjie Lin: software, visualization, and writing\u0026mdash;review and editing. Haitao Huang and Juntao Ma: investigation, resources, and data curation. Qingwei Song: resources and data curation. Lijun Wang: methodology, supervision, writing, reviewing, and editing. Ailian Liu: supervision.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e The authors would like to thank all participants for their valuable support in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eIshibashi M, Fujii S, Kawamoto K, Nishihara K, Matsusue E, Kodani K, 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. 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Correlation between preoperative predictions and surgical findings in the parotid surgery for tumors. Head Face Med. 2016;12:4. https://doi.org/10.1186/s13005-016-0100-6.\u003c/li\u003e\n\u003cli\u003eJin H, Kim BY, Kim H, Lee E, Park W, Choi S, et al. Incidence of postoperative facial weakness in parotid tumor surgery: a tumor subsite analysis of 794 parotidectomies. BMC Surg. 2019;19(1):199. https://doi.org/10.1186/s12893-019-0666-6.\u003c/li\u003e\n\u003cli\u003eRouchy R, Atty\u0026eacute; A, Medici M, Renard F, Kastler A, Grand S, et al. Facial nerve tractography: a new tool for the detection of perineural spread in parotid cancers. Eur Radiol. 2018;28(9):3861-71. https://doi.org/10.1007/s00330-018-5318-1.\u003c/li\u003e\n\u003cli\u003eBarajas RFJ, Hess CP, Phillips JJ, Von Morze CJ, Yu JP, Chang SM, et al. Super-resolution track density imaging of glioblastoma: histopathologic correlation. AJNR Am J Neuroradiol. 2013;34(7):1319-25. https://doi.org/10.3174/ajnr.A3400.\u003c/li\u003e\n\u003cli\u003eDivi V, Fatt MA, Mukherji SK, Bradford CR, Chepeha DB, Wolf GT, et al. Use of cross-sectional imaging in predicting facial nerve sacrifice during surgery for parotid neoplasms. ORL J Otorhinolaryngol Relat Spec. 2004;66(5):262-6. https://doi.org/10.1159/000081123.\u003c/li\u003e\n\u003cli\u003eAtty\u0026eacute; A, Karkas A, Tropr\u0026eacute;s I, Roustit M, Kastler A, Bettega G, et al. Parotid gland tumours: MR tractography to assess contact with the facial nerve. Eur Radiol. 2016;26(7):2233-41. https://doi.org/10.1007/s00330-015-4049-9.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"parotid gland, intraparotid facial nerve, magnetic resonance imaging, salivary gland neoplasms, magnetic resonance neurography","lastPublishedDoi":"10.21203/rs.3.rs-7604757/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7604757/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eTo assess the performance of three-dimensional T2-weighted fast field echo imaging (3D-T2-FFE) in the visualization of the intraparotid facial nerve (IFN) and localization of tumors.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eMagnetic resonance imaging data from sixty-four patients who underwent 3D-T2-FFE were retrospectively enrolled. The identification certainty of IFN on 3D-T2-FFE was scored with an arbitrary scale of 0\u0026ndash;3. The parotid gland was divided into superior and inferior parts, with the level of the earlobe serving as the reference. The tumor location was categorized as deep or superficial directly on 3D-T2-FFE images and indirectly by the facial nerve line (FNL) and the retromandibular vein line (RMVL). Surgical localization was considered the reference standard. The accuracy, sensitivity, and specificity of each method for localizing parotid lesions were compared using the McNemar test.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe accuracy, sensitivity, specificity, positive predictive value, and negative predictive value for deep lobe lesions in the superior part of the parotid gland using the direct method were 97.8%, 92.3%, 100.0%, 100.0%, and 96.9%, respectively. The 3D-T2-FFE method showed significantly higher sensitivity and specificity than those of FNL (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the superior part of the parotid gland, and there was no significant difference in sensitivity, specificity, and accuracy between 3D-T2-FFE and RMVL (\u003cem\u003ep\u003c/em\u003e\u0026gt;0.05). The relationship between the tumor and the main trunk of the IFN was correctly predicted in 93.3% and 100% of 3D-T2-FFE images in the superior and inferior parts of the parotid glands, respectively.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003e3D-T2-FFE can provide detailed morphological information on the nerve in relation to adjacent parotid gland structures and tumors before surgery.\u003c/p\u003e","manuscriptTitle":"Three-dimensional T2-weighted fast field echo imaging in the determination of the relationship between the intraparotid facial nerve and parotid tumors","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-01 11:53:18","doi":"10.21203/rs.3.rs-7604757/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-13T15:56:05+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-05T05:32:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"180587170332839588641944006782516036976","date":"2025-12-12T12:05:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-03T01:24:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"38266697362770209157206314458160632652","date":"2025-11-03T00:25:29+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-21T19:44:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-18T14:54:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-18T12:26:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Medical Research","date":"2025-09-13T05:13:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"335ef7f4-1d0d-4e70-95f0-b14367c0ec49","owner":[],"postedDate":"November 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-09T16:02:42+00:00","versionOfRecord":{"articleIdentity":"rs-7604757","link":"https://doi.org/10.1186/s40001-026-04133-1","journal":{"identity":"european-journal-of-medical-research","isVorOnly":false,"title":"European Journal of Medical Research"},"publishedOn":"2026-03-02 15:58:12","publishedOnDateReadable":"March 2nd, 2026"},"versionCreatedAt":"2025-11-01 11:53:18","video":"","vorDoi":"10.1186/s40001-026-04133-1","vorDoiUrl":"https://doi.org/10.1186/s40001-026-04133-1","workflowStages":[]},"version":"v1","identity":"rs-7604757","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7604757","identity":"rs-7604757","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}