Accuracy of 7T High-Resolution Vessel Wall Imaging versus CTA in Middle Cerebral Artery Stenosis: A DSA-Based Validation Study

Accuracy of 7T High-Resolution Vessel Wall Imaging versus CTA in Middle Cerebral Artery Stenosis: A DSA-Based Validation Study | 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 Accuracy of 7T High-Resolution Vessel Wall Imaging versus CTA in Middle Cerebral Artery Stenosis: A DSA-Based Validation Study Chuanghui Zhou, Mengting Hu, Chunlun Xiao, Yicheng Hsu, Wei Chen, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9130002/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Objective : To compare the accuracy, agreement, and reproducibility of 7-Tesla high-resolution vessel wall imaging (7T HR-VWI) and computed tomography angiography (CTA) for quantitative assessment of middle cerebral artery (MCA) stenosis using Digital subtraction angiography (DSA) as the reference standard. Materials and methods: This retrospective study recruited 115 patients with non-cardioembolic ischemic stroke between September 2022 and September 2025, comprising 122 MCA stenotic lesions. Two blinded radiologists independently measured stenosis severity (based on diameter and area) and stenotic length using CTA and HR-VWI images. Method agreement between CTA/7T HR-VWI and DSA was assessed using concordance correlation coefficient (CCC) and Bland–Altman analysis. Bland–Altman analysis was used to evaluate systematic (constant) bias and proportional bias between measurement methods. Intraclass correlation coefficients (ICC) were calculated to assess inter- and intra-observer repeatability. Results: Diameter-based stenosis CCC was 0.81 for CTA and 0.92 for HR-VWI; area-based stenosis CCC was 0.76 for CTA and 0.87 for HR-VWI. Bland-Altman biases were 0.06(95% LoA, -0.04, 0.15) and 0.02(95% LoA, -0.07, 0.10) for CTA and HR-VWI, respectively. Lesion length CCC was 0.91 for CTA and 0.94 for HR-VWI, with biases of 0.48(95% LoA, -2.35, 1.4) and 0.04(95% LoA, -1.49, 1.57). Inter- and intra-observer ICCs ranged from 0.83 to 0.97 for CTA and 0.94 to 0.99 for HR-VWI. Conclusion: 7T HR-VWI provides a more accurate and reproducible assessment of intracranial artery stenosis and lesion length compared with CTA, suggesting its potential as a reliable imaging tool for evaluating stenotic lesions. Middle cerebral artery Atherosclerotic stenosis 7-T High resolution vessel wall imaging Computed tomography angiography Digital subtraction angiography Figures Figure 1 Figure 2 Figure 3 1. Introduction Intracranial atherosclerotic stenosis (ICAS) represents a chronic, progressive atherosclerotic process involving plaque formation within the cerebral arteries, which serves as a major underlying etiology of ischemic stroke [ 1 , 2 ]. This pathological progression typically evolves over an extended period until plaque burden reaches a hemodynamically significant degree, substantially impeding cerebral perfusion, or until vulnerable plaque components rupture or embolize, leading to acute thromboembolic occlusion. The landmark Warfarin-Aspirin Symptomatic Intracranial Disease (WASID) trial established that stenosis exceeding 70% is associated with a substantially elevated risk of stroke, primarily due to flow limitation or plaque-related embolism [ 3 ]. Annual stroke rates attributable to hemodynamically significant intracranial stenosis range from 7% to 24% [ 4 , 5 ], with severe stenosis identified as an independent predictor of stroke recurrence [ 6 , 7 ]. Clinical management of symptomatic ICAS typically involves optimal medical therapy, with endovascular interventions such as balloon angioplasty or stenting reserved for carefully selected cases refractory to pharmacological treatment. This treatment paradigm underscores the critical importance of obtaining precise and reliable measurements of stenosis severity to stratify patient risk and guide appropriate therapeutic decisions. In clinical practice, digital subtraction angiography (DSA) remains the reference standard for luminal and hemodynamic assessment due to its superior spatial and temporal resolution [ 8 – 10 ]. However, its invasive nature, associated procedural risks, and radiation exposure limit its routine application, particularly for the longitudinal monitoring of plaque progression. In acute stroke and transient ischemic attack settings, computed tomography angiography (CTA) is widely employed due to its rapid acquisition time and capacity to evaluate both anterior and posterior circulations. Nevertheless, CTA demonstrates a tendency to overestimate stenosis severity compared with DSA [ 11 – 13 ]. This discrepancy may significantly influence the planning of both medical and interventional management strategies. As an emerging alternative, high-resolution vessel wall imaging (HR-VWI) enables direct visualization of intracranial arterial walls and atherosclerotic plaques, providing valuable insights into the etiology of stenotic lesions [ 14 , 15 ]. Furthermore, 7T MRI delivers enhanced spatial resolution and signal-to-noise ratio, improving vessel wall boundary delineation and supporting more accurate evaluation of small vessels [ 16 , 17 ]. This advanced imaging approach has been increasingly applied in intracranial atherosclerotic disease assessment, yielding refined anatomical detail and improved detection of subtle lesions [ 18 , 19 ]. However, a direct, systematic comparison of 7T HR-VWI with CTA against the DSA reference standard is still lacking for Middle cerebral artery (MCA) stenosis. Thus, this study aims to evaluate the reproducibility and quantification of 7T HR-VWI and CTA against DSA in the context of MCA stenosis. 2. Materials and methods 2.1 Study Population This retrospective study was conducted at a tertiary academic medical center between September 2022 and September 2025. The study was performed in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the First Affiliated Hospital of Army Medical University (Approval No. KY2023167), with a waiver of informed consent. The inclusion criteria were as follows: (1) age > 18 years; (2) diagnosis of non-cardioembolic acute ischemic stroke caused by middle cerebral artery (MCA) atherosclerotic plaques; (3) patients who underwent CTA and 7T MRI examinations prior to DSA and before any endovascular revascularization treatment; (4) a time interval of no more than four weeks between CTA, MRI, and DSA examinations. The exclusion criteria were: (1) complete occlusion of the MCA; (2) poor image quality or severe artifacts; (3) inability to reliably measure stenosis length or luminal diameter at the stenotic segment. The patient selection workflow is presented in Fig. 1 . 2.2 Digital Subtraction Angiography (DSA) All patients underwent digital subtraction angiography (DSA) examinations using a Siemens Axiom Artis Z neuroangiography system (Siemens, Germany). During the procedure, conventional right femoral artery puncture was performed, and an arterial sheath (RSA60K10SQ, Terumo, Japan; batch number: 220108VA) was inserted at the puncture site to establish an access route for angiography. Subsequently, the angiographic catheter was advanced to the common carotid artery segment for contrast injection. For intracranial anterior circulation imaging, iopamidol contrast agent (Omnipaque, GE Healthcare, USA) was used, with a total injection volume of 12 mL and a flow rate of 5 mL/s. Image acquisition included standard Towne and lateral projections to ensure clear visualization and comprehensive assessment of the intracranial arteries. 2.3 CT Image Acquisition All head and neck CTA examinations were performed using Siemens SOMATOM Definition Flash and SOMATOM Force scanners (Siemens Healthineers, Erlangen, Germany). Patients were positioned supine, head first, with the head maintained in a neutral position and properly immobilized. Prior to scanning, patients were instructed to breathe calmly and avoid swallowing or head movement to minimize motion artifacts. A three-phase injection protocol was applied: an initial 30 mL saline flush injected intravenously at 5 mL/s, followed by iopamidol contrast agent (Omnipaque 350, GE Healthcare, WI, USA) administered at a weight-based dose of 1.0–1.5 mL/kg body weight (maximum volume ≤ 90 mL), and finally a second 30 mL saline flush at the same flow rate. Bolus tracking was used with the region of interest placed in the ascending aorta, and image acquisition was triggered automatically after reaching the predefined attenuation threshold. The scan range extended from the aortic arch to the vertex. The acquisition time for each CTA scan was approximately 4–5 seconds. The main scanning parameters were as follows: tube current 250 mAs, tube voltage 120 kV, pitch 1.45, rotation time 0.5 s, collimation 128 × 0.6 mm², slice thickness 0.6 mm, field of view 230 × 230 mm², matrix size 512 × 512. 2.4 MRI Image Acquisition All patients underwent MRA on a 7.0 T MRI system (MAGNETOM Terra, Siemens Healthineers, Erlangen, Germany) equipped with a 32-channel head coil. A three-dimensional fast spin-echo sequence with variable flip angles (SPACE) was used to obtain high-resolution, isotropic 3D images. The detailed imaging parameters were as follows: repetition time (TR) / echo time (TE) = 1250 / 23 ms; field of view (FOV) = 180 × 180 mm²; matrix = 400 × 400; slice thickness = 0.45 mm; voxel size = 0.45 × 0.45 × 0.45 mm³; number of slices = 256; acquisition time = 6 min 45 s. 2.5 Vascular Measurements and Stenosis Calculation 2.5.1 DSA Image Measurements DSA images were independently assessed by a senior neurointerventional physician with 9 years of experience. On the Towne projection showing the maximal opacification of the MCA segment, the following measurements were obtained for both MCAs: (1) length of stenosis (L); (2) diameter at the point of maximal stenosis (d); (3) proximal normal diameter (D). For stenosis length, if the stenotic segment was tortuous and extended, a segmented polyline method was used; the lengths of all segments were summed to obtain the final stenosis length. Because DSA provides two-dimensional images, luminal area cannot be measured. 2.5.2 CTA and HR-VWI Image Measurements CTA and HR-VWI images were independently measured in a double-blind manner by two experienced radiologists (with 10 and 15 years of experience, respectively). Each radiologist repeated the measurements after a 3-month interval to evaluate inter- and intra-observer reproducibility. All images were imported into the same Siemens post-processing workstation for multiplanar reconstruction (MPR). CTA series and non-contrast T1-weighted SPACE sequences were used for three-plane reconstruction to obtain MCA segment images. The measurement procedures were similar to those used for DSA. However, CTA/MRI additionally allowed luminal area quantification: (1). Independently inspect bilateral MCAs and determine the point of maximal stenosis. (2). Generate oblique-coronal MPR images parallel to the MCA long axis and short-axis MPR images perpendicular to the long axis, and use curved planar reformation (CPR) to display the curved MCA lumen along a single plane. (3). Measure the length of stenosis on MPR/CPR images; measure the diameter and area at maximal stenosis, as well as the proximal normal diameter and area, on MPR images. If multiple stenotic lesions were present within the same MCA, only the most severe stenosis was selected for measurement and subsequent analysis for that artery. If the contralateral MCA is free of stenosis, the corresponding normal site is used for luminal diameter and area measurement. 2.5.3 Stenosis Calculation According to the Warfarin–Aspirin Symptomatic Intracranial Disease (WASID) criteria [ 6 ], the degree of stenosis was calculated based on the measured parameters as follows: 1) Diameter-based stenosis: $$\:Diameter\:Based\:Stenosis\%=\left(1-\frac{d}{D}\right)\text{ⅹ}100\%\:\:\left(1\right)$$ 2) Area-based stenosis: $$\:Area\:Based\:Stenosis\%=\left(1-\frac{a}{A}\right)\text{ⅹ}100\%\:\:\left(2\right)$$ where \(\:d\) is the diameter at the maximal stenosis, \(\:D\) is the diameter of the proximal normal segment, \(\:a\) is the lumen area at the maximal stenosis, and \(\:A\) is the lumen area of the proximal normal segment. 2.7 Statistical Analysis Statistical analyses were performed using the SciPy package in Python 3.11.0. Inter- and intra-observer consistency was assessed using the intraclass correlation coefficient (ICC; 0.9, excellent), and methodological agreement between CTA and DSA, as well as between 7T MRI and DSA, was evaluated using the concordance correlation coefficient (CCC; 0.95, excellent). Bland–Altman plots were also used to assess systematic bias and limits of agreement. Differences between CTA and DSA, and between 7T MRI and DSA, were assessed using the Wilcoxon signed-rank test, and Cohen’s d was calculated to quantify the magnitude of differences between measurements, with larger absolute values indicating greater differences. For all analyses, quantitative measurements were calculated as the mean of two repeated measurements from both radiologists. A P-value < 0.05 was considered statistically significant. 3. Results 3.1. Patient characteristics Among the initial 240 patients, 125 were excluded: 68 due to incomplete imaging data, 35 due to poor CTA or MRI image quality that prevented measurement, and 22 due to vascular occlusion. Ultimately, 115 patients with 122 stenotic vessels (59 left-sided and 63 right-sided) were included in the analysis. Among these patients, 81 were male and 34 female, with a mean age of 55.9 ± 10.6 years. Figure 2 shows an example of a 56-year-old female patient with stenosis of the right middle cerebral artery (M1 segment) on CTA and HR-VWI. 3.2 Methodological Agreement Table 1 summarizes the agreement between CTA, 7T HR-VWI, and DSA for diameter-based stenosis, area-based stenosis, and lesion length measurements. CTA and DSA showed poor consistency in diameter-based stenosis measurement (CCC = 0.81, 95% CI: 0.78–0.93, P < 0.01, |d|=0.78), whereas HR-VWI demonstrated moderate to high consistency (CCC = 0.92, 95% CI: 0.90–0.95, P < 0.001, |d|=0.35). Bland-Altman analysis revealed biases of 0.06 for CTA and 0.02 for HR-VWI, with 95% limits of agreement (LoA) of − 0.04 to 0.15 and − 0.07 to 0.10, respectively (Fig. 3 a, b). Table 1 Agreement Between CTA, 7T MRI, and DSA for Diameter-Based Stenosis, Area-Based Stenosis, and Lesion Length Measurements. Methods Mean ± SD CCC * (95%CI) P |d| Diameter-Based Stenosis DSA 0.59 ± 0.12 - - - CTA 0.53 ± 0.11 0.81 [0.78, 0.93] < 0.01 0.78 HR-VWI 0.57 ± 0.12 0.92 [0.90, 0.95] < 0.01 0.35 Area-Based Stenosis - - CTA 0.63 ± 0.12 0.76 [0.70, 0.84] < 0.01 0.64 HR-VWI 0.61 ± 0.14 0.87 [0.85, 0.93] 0.02 0.22 Lesion length (mm) DSA 4.62 ± 2.40 - - - CTA 5.07 ± 2.28 0.91 [0.89, 0.94] < 0.01 0.48 HR-VWI 4.62 ± 2.11 0.94 [0.92, 0.96] 0.70 0.03 CCC* refers to the concordance correlation coefficient between CTA/7T MRI and DSA (CCC: poor, 0.95); p indicates P-values derived from comparisons with DSA results using the Wilcoxon signed-rank test; d indicates the magnitude of differences between groups. For area-based stenosis, CTA showed poor agreement with DSA (CCC = 0.76, 95% CI: 0.70–0.84, P < 0.001, |d|=0.64), while HR-VWI demonstrated slightly higher agreement (CCC = 0.87, 95% CI: 0.85–0.93, P = 0.02, |d|=0.22). The biases were 0.02 for CTA and 0.04 for HR-VWI, with 95% LoA of − 0.19 to 0.16 and − 0.14 to 0.06, respectively (Fig. 3 c, d). Regarding lesion length, CTA slightly overestimated measurements (5.07 ± 2.28 mm vs. 4.62 ± 2.40 mm), whereas HR-VWI showed high concordance with DSA (4.62 ± 2.11 mm). CCC values were 0.91 (95% CI: 0.89–0.94) for CTA and 0.94 (95% CI: 0.92–0.96) for HR-VWI, with biases of 0.48mm and 0.04mm, and 95% LoA of − 2.35 to 1.40 and − 1.49 to 1.57, respectively (Fig. 3 e, f). 3.3 Inter- and Intra-Observer Consistency Inter-observer and intra-observer agreement for diameter-based stenosis, area-based stenosis, and lesion length measurements obtained from CTA and HR-VWI are summarized in Table 2 . For CTA, the inter-/intra-observer ICCs for diameter-based stenosis, area-based stenosis, and lesion length were 0.86/0.87, 0.83/0.83, and 0.94/0.97, respectively. Correspondingly, HR-VWI demonstrated higher reproducibility, with inter-/intra-observer ICCs of 0.94/0.95, 0.94/0.94, and 0.99/0.98. Table 2 Inter- and Intra-Observer Intraclass Correlation Coefficients for CTA and 7T MRI Measurements. CTA HR-VWI Inter-observer Intra-observer Inter-observer Intra-observer Diameter-Based 0.86 [0.72, 0.93] 0.87 [0.75, 0.94] 0.94 [0.87, 0.97] 0.95 [0.89, 0.97] Area-Based 0.83 [0.67, 0.92] 0.83 [0.67, 0.91] 0.94 [0.88, 0.97] 0.94 [0.88, 0.97] Lesion length 0.94 [0.88, 0.97] 0.97 [0.94, 0.99] 0.99 [0.97, 0.99] 0.98 [0.96, 0.99] 4. Discussion The present study provides compelling evidence supporting the clinical value of 7T HR-VWI in the evaluation of MCA stenosis. Our analysis yielded two principal findings that carry significant implications for neurovascular imaging practice. First, 7T HR-VWI demonstrated superior intra- and inter-observer reproducibility compared to CTA, indicating greater measurement consistency across different readers and interpretation sessions. Second, and perhaps more critically, diameter-based measurements of MCA stenosis severity derived from 7T HR-VWI exhibited substantially stronger agreement with DSA than those obtained from CTA. This enhanced agreement with the reference standard suggests that 7T HR-VWI may represent a more reliable alternative to conventional CTA for pre-procedural planning and stenosis quantification in neurovascular interventions. The critical importance of accurate and timely intracranial vasculopathic diagnosis cannot be overstated in contemporary cerebrovascular medicine. Diagnostic delays or errors in characterizing MCA stenosis significantly increase morbidity risk, potentially leading to devastating neurological outcomes [ 20 , 21 ]. While intra-arterial DSA remains the undisputed reference standard for comprehensive vascular assessment, its invasive nature, coupled with associated procedural risks and substantial resource requirements, has prompted the widespread adoption of less invasive alternatives in routine clinical practice. Among these, CTA and magnetic resonance angiography (MRA) have emerged as first-line diagnostic tools in many institutions. This transition from invasive to non-invasive imaging modalities represents a significant paradigm shift in neurovascular diagnostics, though it simultaneously introduces new challenges in measurement accuracy, standardization, and clinical validation. The fundamental distinction between these imaging approaches lies in their underlying visualization principles and diagnostic capabilities. Unlike DSA, which primarily provides luminographic information through contrast-filled vessel lumens, CTA and MRA enable multiplanar visualization of vessels and permit preliminary evaluation of the vessel wall and surrounding structure [ 22 , 23 ]. This technological difference carries profound clinical implications, particularly in the context of rapidly evolving neurointerventional practices where detailed vascular anatomical information beyond mere lumenography is increasingly crucial for procedural planning, device selection, and therapeutic decision-making. The landscape of endovascular treatment (EVT) has undergone remarkable transformation in recent years, characterized by a notable trend toward the use of large-bore aspiration catheters. This technological evolution has simultaneously heightened the importance of precise vessel sizing in pre-procedural planning. While larger catheters may theoretically enhance first-pass efficacy and improve aspiration performance [ 24 ], their implementation raises legitimate concerns about potential vessel trauma, endothelial injury, and oversizing—particularly when device selection relies primarily on pre-procedural CTA measurements rather than intraprocedural DSA [ 25 , 26 ]. The current clinical preference for deploying the largest feasible catheter prior to DSA acquisition primarily aims to minimize time to reperfusion—a critical factor in determining neurological outcomes following acute ischemic stroke. However, this "one-size-fits-most" approach potentially overlooks the nuanced need for individualized device selection to optimize both safety and efficacy. The seminal study by Rogers et al. compellingly highlighted this concern by demonstrating that CTA systematically overestimates MCA diameter relative to DSA, with a median discrepancy of 0.4 mm [ 27 ]. This systematic overestimation underscores a fundamental limitation of CTA-first sizing strategies, especially in modern neurointerventional workflows where thrombectomy devices are frequently selected before intra-procedural DSA is performed. In this evolving clinical context, the improved agreement of 7T HR-VWI with DSA, as robustly demonstrated in our study, supports its potential utility in enabling more reliable pre-interventional vessel assessment. This enhanced accuracy could prove invaluable in aiding the selection of appropriately sized devices while simultaneously mitigating procedural risks associated with vessel injury from oversized catheters or inadequate thrombus engagement from undersized devices. The implications extend beyond mere measurement accuracy to encompass potentially improved clinical outcomes through optimized device-vessel compatibility. High-resolution vessel wall imaging signifies a substantial advancement in cerebrovascular assessment, offering superior accuracy in delineating pathological changes compared to conventional luminal imaging techniques. The evolution of this technology has followed a clear trajectory toward higher field strengths and improved spatial resolution. Evidence from Liu et al. indicates that even at 3T, HR-VWI enables precise assessment of middle cerebral artery stenosis, consistently outperforming CTA and demonstrating superior concordance with DSA as the reference standard [ 28 ]. Similarly, Gong et al. reported excellent agreement between 3T HR-VWI and DSA in luminal evaluation, while time-of-flight magnetic resonance angiography (TOF-MRA) showed limited diagnostic performance in direct comparisons [ 29 ]. The diagnostic capability of HR-VWI reaches its current apex at 7T, representing the optimal clinical modality for detailed vessel wall assessment available today. The elevated magnetic field strength at 7T affords substantial gains in spatial resolution and signal-to-noise ratio [ 30 ], facilitating refined characterization of plaque morphology and composition beyond the capabilities of 3T systems [ 31 , 32 ]. These technical advantages translate directly to improved diagnostic confidence, particularly in evaluating complex plaque characteristics, identifying vulnerable plaque features, and assessing vessel wall remodeling—capabilities that remain fundamentally limited in conventional angiographic techniques. Furthermore, the ability to visualize plaque components, including intraplaque hemorrhage, lipid-rich necrotic cores, and fibrous caps, provides invaluable insights into stroke pathogenesis and risk stratification that transcend mere luminal assessment. The optimal methodology for quantifying arterial stenosis—specifically the ongoing debate between diameter versus area-based measurements—remains a subject of considerable discussion in vascular imaging research. The literature presents conflicting perspectives on this fundamental measurement approach, reflecting the complexity of vascular geometry and its clinical implications. Samarzija et al. reported that diameter-based CTA measurements significantly underestimated carotid stenosis severity and recommended the area method due to its superior predictive power for correct stenosis classification and closer agreement with color Doppler ultrasound (CDUS) [ 33 ]. Supporting this view, Zhang et al. observed only moderate agreement between CTA area measurements and DSA diameter stenosis, noting particularly poor correlation between diameter and area measurements in vessels with markedly non-circular lumens compared to those with circular configurations [ 34 ]. Bucek et al. further reinforced the value of area assessment, demonstrating better inter-observer agreement and stronger correlation with DSA for CTA area measurements than for diameter-based approaches [ 35 ]. However, this perspective favoring area measurements is not universally accepted within the scientific community. Carnicelli et al. found no significant difference between diameter and area measurements when using CDUS as a reference standard [ 36 ]. Similarly, Van Prehn et al. reported comparable correlation coefficients for both methods against ultrasound and concluded that diameter measurements provide an adequate approximation of area-based assessment [ 37 ]. Most notably, Bartlett et al. directly contended that minimal diameter measurements reliably predict the more computationally complex area-based quantification [ 38 ], emphasizing the practical utility of diameter assessment in clinical workflows. In the context of these conflicting findings across previous studies, our investigation demonstrated consistently superior performance with diameter-based measurements for assessing MCA stenosis using both CTA and, more importantly, 7T HR-VWI. These results align more closely with the conclusions of Bartlett et al. [ 38 ], suggesting that in MCA evaluation specifically, the minimal diameter method provides sufficient accuracy while offering substantial practical advantages in clinical measurement workflows. This finding carries significant implications for clinical practice, as diameter measurements typically require less processing time and computational resources compared to area-based assessments, potentially facilitating more efficient integration into busy neurovascular imaging protocols without compromising diagnostic accuracy. Several limitations of this study warrant consideration. First, the retrospective design introduces potential recall bias; however, this was mitigated through repeated image evaluations conducted at scheduled intervals, with readers blinded to patient identifiers and clinical details. Second, the recruitment of participants based on clinical history may have introduced selection bias. To address this concern, the analysis focused on an objective comparison of HR-VWI and CTA in evaluating stenotic severity, rather than on establishing definitive diagnoses. Third, the limited clinical availability of 7T HR-VWI must be acknowledged; nevertheless, the primary objective of this study was to perform a methodological comparison between advanced vessel wall imaging and conventional angiographic techniques, rather than to advocate for immediate clinical implementation. In summary, 7T HR-VWI demonstrates superior accuracy, agreement with DSA, and reproducibility compared with CTA for quantitative assessment of MCA stenosis and lesion length. These findings support the potential utility of 7T HR-VWI as a reliable noninvasive imaging tool for precise evaluation of intracranial arterial stenotic lesions. Abbreviations ICAS: Intracranial atherosclerotic stenosis WASID: Warfarin-Aspirin Symptomatic Intracranial Disease DSA : Digital subtraction angiography CTA : Computed tomography angiography HR-VWI : high-resolution vessel wall imaging MCA : Middle cerebral artery TR : Repetition time TE : Echo time FOV : field of view MPR : multiplanar reconstruction CPR : curved planar reformation ICC : Intraclass correlation coefficients CCC : Concordance correlation coefficient LoA : Limits of agreement MRA : Magnetic resonance angiography EVT :Endovascular treatment Declarations Acknowledgements We are grateful for the support of the 7T Magnetic Resonance Translational Medicine Research Center Special Construction Fund [424Z2Q31] and the 7T Magnetic Resonance Special Fund Project of the First Affiliated Hospital of the Army Medical University [20247TZD01] for this research. Funding This work was supported by the 7T Magnetic Resonance Translational Medicine Research Center Special Construction Fund [424Z2Q31]; and the 7T Magnetic Resonance Special Fund Project of the First Affiliated Hospital of the Army Medical University [20247TZD01]. Author information * Chuanghui Zhou and Mengting Hu contributed equal to this work. Authors and Affiliations Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing 400000, China Chuanghui Zhou, Mengting Hu, Chunlun Xiao, Wei Chen, Pinzhen Chen, He Liu, Min He, Jiafei Chen MR Research Collaboration Team, Siemens Healthineers Ltd, Shanghai 200000, China Yicheng Hsu Contributions Chuanghui Zhou: Methodology, Investigation, Writing - Original Draft. Mengting Hu: Methodology, Data acquisition, Writing - Original Draft. Chunlun Xiao: Formal analysis, Data Curation. Yicheng Hsu: Software, Statistical analysis. Wei Chen: Conceptualization, Writing - Review & Editing. Pinzhen Chen: Writing - Review & Editing. He Liu: Validation, Writing - Review & Editing. Min He: Investigation, Supervision. Jiafei Chen: Project administration, Funding acquisition, Writing - Review & Editing Ethics declarations Ethics approval and consent to participate The study was performed in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the First Affiliated Hospital of Army Medical University (Approval No. KY2023167), with a waiver of informed consent. Consent for publication Not applicable. Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Data availability The dataset and code used in this study can be obtained from the corresponding author upon reasonable request. References Feldmann E, Daneault N, Kwan E, et al. 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Improvement in accuracy of diagnosis of carotid artery stenosis with duplex ultrasound scanning with combined use of linear array 7.5 MHz and convex array 3.5 MHz probes: validation versus 489 arteriographic procedures. J Vasc Surg. 2003;37:1240–7. Lee NJ, Chung MS, Jung SC, et al. Comparison of High-Resolution MR Imaging and Digital Subtraction Angiography for the Characterization and Diagnosis of Intracranial Artery Disease. AJNR Am J Neuroradiol. 2016;37:2245–50. Giglioli C, Cecchi E, Sciagrá R, et al. COmparison between COronary THrombus aspiration with Angiojet® or Export® catheter in patients with ST-elevation myocardial infarction submitted to primary angioplasty: The COCOTH Study. Int J Cardiol. 2016;203:757–62. Zaidat OO, Castonguay AC, Linfante I et al. First Pass Effect: A New Measure for Stroke Thrombectomy Devices. Stroke. 2018;49:660–666. Goldman D, Reddi P, Al-Kawaz M, et al. Higher intracranial positioning of an 8 Fr guide catheter improves efficacy of aspiration thrombectomy in large vessel occlusion stroke. J Neurointerv Surg. 2025;17:e345–8. Rogers P, Parker E, Marangoni M et al. Discrepancies in Vessel Diameter Measurements Between CTA and DSA in MCA M1 Occlusions: An Interobserver Study. Can Assoc Radiol J 2025:8465371251356908. Safain MG, Rahal JP, Patel S, et al. Superior performance of cone-beam CT angiography in characterization of intracranial atherosclerosis. J Neurosurg. 2014;121:441–9. Gong Y, Cao C, Guo Y, et al. Quantification of intracranial arterial stenotic degree evaluated by high-resolution vessel wall imaging and time-of-flight MR angiography: reproducibility, and diagnostic agreement with DSA. Eur Radiol. 2021;31:5479–89. Zwartbol MHT, van der Kolk AG, Ghaznawi R, et al. Intracranial Vessel Wall Lesions on 7T MRI (Magnetic Resonance Imaging). Stroke. 2019;50:88–94. Lopez Gonzalez MR, Foo SY, Holmes WM, et al. Atherosclerotic Carotid Plaque Composition: A 3T and 7T MRI-Histology Correlation Study. J Neuroimaging. 2016;26:406–13. Zwartbol MH, van der Kolk AG, Kuijf HJ, et al. Intracranial vessel wall lesions on 7T MRI and MRI features of cerebral small vessel disease: The SMART-MR study. J Cereb Blood Flow Metab. 2021;41:1219–28. Samarzija K, Milosevic P, Jurjevic Z, et al. Grading of carotid artery stenosis with computed tomography angiography: whether to use the narrowest diameter or the cross-sectional area. Insights Imaging. 2018;9:527–34. Zhang Z, Berg M, Ikonen A, et al. Carotid stenosis degree in CT angiography: assessment based on luminal area versus luminal diameter measurements. Eur Radiol. 2005;15:2359–65. Bucek RA, Puchner S, Haumer M, et al. CTA quantification of internal carotid artery stenosis: application of luminal area vs. luminal diameter measurements and assessment of inter-observer variability. J Neuroimaging. 2007;17:219–26. Carnicelli AP, Stone JJ, Doyle A, et al. Cross-sectional area for the calculation of carotid artery stenosis on computed tomographic angiography. J Vasc Surg. 2013;58:659–65. van Prehn J, Muhs BE, Pramanik B, et al. Multidimensional characterization of carotid artery stenosis using CT imaging: a comparison with ultrasound grading and peak flow measurement. Eur J Vasc Endovasc Surg. 2008;36:267–72. Bartlett ES, Symons SP, Fox AJ. Correlation of carotid stenosis diameter and cross-sectional areas with CT angiography. AJNR Am J Neuroradiol. 2006;27:638–42. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 12 May, 2026 Reviews received at journal 02 May, 2026 Reviewers agreed at journal 28 Apr, 2026 Reviewers agreed at journal 22 Apr, 2026 Reviewers agreed at journal 22 Apr, 2026 Reviewers agreed at journal 13 Apr, 2026 Reviewers invited by journal 09 Apr, 2026 Editor assigned by journal 23 Mar, 2026 Submission checks completed at journal 23 Mar, 2026 First submitted to journal 23 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9130002","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":624533462,"identity":"9e6fa350-8f65-488b-ba65-475e04657d79","order_by":0,"name":"Chuanghui Zhou","email":"","orcid":"","institution":"Department of Radiology, Southwest Hospital, Army Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chuanghui","middleName":"","lastName":"Zhou","suffix":""},{"id":624533463,"identity":"87baa3d8-5bc0-4214-b543-e92bf4d83359","order_by":1,"name":"Mengting Hu","email":"","orcid":"","institution":"Department of Radiology, Southwest Hospital, Army Medical University","correspondingAuthor":false,"prefix":"","firstName":"Mengting","middleName":"","lastName":"Hu","suffix":""},{"id":624533464,"identity":"e2439450-dd15-49f9-b20d-57888268f2b8","order_by":2,"name":"Chunlun Xiao","email":"","orcid":"","institution":"Department of Radiology, Southwest Hospital, Army Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chunlun","middleName":"","lastName":"Xiao","suffix":""},{"id":624533465,"identity":"fa8eadd0-7f79-40f9-8a6e-39d5f6a14796","order_by":3,"name":"Yicheng Hsu","email":"","orcid":"","institution":"MR Research Collaboration Team, Siemens Healthineers Ltd, Shanghai 200000, China","correspondingAuthor":false,"prefix":"","firstName":"Yicheng","middleName":"","lastName":"Hsu","suffix":""},{"id":624533466,"identity":"6d9ddf5f-ffdb-4ee1-99ef-1afab9b65740","order_by":4,"name":"Wei Chen","email":"","orcid":"","institution":"Department of Radiology, Southwest Hospital, Army Medical University","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Chen","suffix":""},{"id":624533467,"identity":"d073b729-2fad-48e4-ae74-ae38d5d5daef","order_by":5,"name":"Pinzhen Chen","email":"","orcid":"","institution":"Department of Radiology, Southwest Hospital, Army Medical University","correspondingAuthor":false,"prefix":"","firstName":"Pinzhen","middleName":"","lastName":"Chen","suffix":""},{"id":624533468,"identity":"bb8aa7a4-e675-4a2e-9e66-3982e92c669d","order_by":6,"name":"He Liu","email":"","orcid":"","institution":"Department of Radiology, Southwest Hospital, Army Medical University","correspondingAuthor":false,"prefix":"","firstName":"He","middleName":"","lastName":"Liu","suffix":""},{"id":624533469,"identity":"9298e1e8-6742-403b-b521-af5196557027","order_by":7,"name":"Min He","email":"","orcid":"","institution":"Department of Radiology, Southwest Hospital, Army Medical University","correspondingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"He","suffix":""},{"id":624533470,"identity":"4078e2ff-e4d7-4b04-9ea7-7eaff6e719b7","order_by":8,"name":"Jiafei Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYDACCRA2YOBnYGY+ABVKIE6LZAMzW2ID8VqAQLKBgceQOC38s5uPPbAosJPgZ+f5/uhmzmEGfvYcA4afO/BYcudYuoGEQbKEZDPvxubcbYcZJHveGDD2nsGtxUAix0xCwoC5zuAwVIvBjRwDZsY2fFryvwG11EvYH+Z5CNZiT1hLDhtQy2GgRTyMEFskCGiRuJEGcthxCYnDbIazc7el80iceVZwsBePFv4Zyc+kJf5US/D3H37wOXebtRx/e/LGBz/xaAEBZgkkDg+IOIBfAwMD4wdCKkbBKBgFo2BkAwDuYUmHf9/EvQAAAABJRU5ErkJggg==","orcid":"","institution":"Department of Radiology, Southwest Hospital, Army Medical University","correspondingAuthor":true,"prefix":"","firstName":"Jiafei","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2026-03-15 16:23:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9130002/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9130002/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107484601,"identity":"8dddb23b-b7e5-4ce8-854f-343e92fce206","added_by":"auto","created_at":"2026-04-22 02:32:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":154549,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of patient recruitment.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9130002/v1/0ec81a29edcef0eb614ac102.png"},{"id":107255037,"identity":"ea409ace-6f3c-469c-9703-2d0d4d72e5ba","added_by":"auto","created_at":"2026-04-19 12:07:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":418623,"visible":true,"origin":"","legend":"\u003cp\u003eA 56-year-old female patient with stenosis of the right MCA (M1 segment). (a, d) show the normal reference segment; (b, e) show the stenotic segment in oblique sagittal reconstruction; (c, f) show the stenotic segment in cross-sectional reconstruction. DSA measured a stenosis of 66.7% with a length of 3.5 mm; CTA measured 56.98% stenosis based on diameter and 73.02% based on area, with a length of 4.05 mm; HR-VWI measured 65.12% stenosis based on diameter and 74.36% based on area, with a length of 3.15 mm.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9130002/v1/ef19b9bc14fc440c456f5725.png"},{"id":107484679,"identity":"3a36a5e6-bcb3-42d7-87d3-447ad0302189","added_by":"auto","created_at":"2026-04-22 02:32:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":474125,"visible":true,"origin":"","legend":"\u003cp\u003eBland-Altman analysis plots comparing CTA and MRI with DSA. (a, b) Diameter-based stenosis; (c, d) Area-based stenosis; (e, f) Lesion length. The light read dashed line represents the mean bias. The gray dashed line is ± 1.96 SD limits.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9130002/v1/bf6f2445ef551ced0cad4d42.png"},{"id":109219801,"identity":"f6cce8de-c5fe-4723-84b6-cb886cfa8985","added_by":"auto","created_at":"2026-05-13 20:04:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1265711,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9130002/v1/e1787dc6-90bd-4c37-9c01-36def840c6ac.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Accuracy of 7T High-Resolution Vessel Wall Imaging versus CTA in Middle Cerebral Artery Stenosis: A DSA-Based Validation Study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIntracranial atherosclerotic stenosis (ICAS) represents a chronic, progressive atherosclerotic process involving plaque formation within the cerebral arteries, which serves as a major underlying etiology of ischemic stroke [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This pathological progression typically evolves over an extended period until plaque burden reaches a hemodynamically significant degree, substantially impeding cerebral perfusion, or until vulnerable plaque components rupture or embolize, leading to acute thromboembolic occlusion. The landmark Warfarin-Aspirin Symptomatic Intracranial Disease (WASID) trial established that stenosis exceeding 70% is associated with a substantially elevated risk of stroke, primarily due to flow limitation or plaque-related embolism [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Annual stroke rates attributable to hemodynamically significant intracranial stenosis range from 7% to 24% [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], with severe stenosis identified as an independent predictor of stroke recurrence [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Clinical management of symptomatic ICAS typically involves optimal medical therapy, with endovascular interventions such as balloon angioplasty or stenting reserved for carefully selected cases refractory to pharmacological treatment. This treatment paradigm underscores the critical importance of obtaining precise and reliable measurements of stenosis severity to stratify patient risk and guide appropriate therapeutic decisions.\u003c/p\u003e \u003cp\u003eIn clinical practice, digital subtraction angiography (DSA) remains the reference standard for luminal and hemodynamic assessment due to its superior spatial and temporal resolution [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, its invasive nature, associated procedural risks, and radiation exposure limit its routine application, particularly for the longitudinal monitoring of plaque progression. In acute stroke and transient ischemic attack settings, computed tomography angiography (CTA) is widely employed due to its rapid acquisition time and capacity to evaluate both anterior and posterior circulations. Nevertheless, CTA demonstrates a tendency to overestimate stenosis severity compared with DSA [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This discrepancy may significantly influence the planning of both medical and interventional management strategies.\u003c/p\u003e \u003cp\u003eAs an emerging alternative, high-resolution vessel wall imaging (HR-VWI) enables direct visualization of intracranial arterial walls and atherosclerotic plaques, providing valuable insights into the etiology of stenotic lesions [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Furthermore, 7T MRI delivers enhanced spatial resolution and signal-to-noise ratio, improving vessel wall boundary delineation and supporting more accurate evaluation of small vessels [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. This advanced imaging approach has been increasingly applied in intracranial atherosclerotic disease assessment, yielding refined anatomical detail and improved detection of subtle lesions [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, a direct, systematic comparison of 7T HR-VWI with CTA against the DSA reference standard is still lacking for Middle cerebral artery (MCA) stenosis.\u003c/p\u003e \u003cp\u003eThus, this study aims to evaluate the reproducibility and quantification of 7T HR-VWI and CTA against DSA in the context of MCA stenosis.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Population\u003c/h2\u003e \u003cp\u003eThis retrospective study was conducted at a tertiary academic medical center between September 2022 and September 2025. The study was performed in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the First Affiliated Hospital of Army Medical University (Approval No. KY2023167), with a waiver of informed consent. The inclusion criteria were as follows: (1) age\u0026thinsp;\u0026gt;\u0026thinsp;18 years; (2) diagnosis of non-cardioembolic acute ischemic stroke caused by middle cerebral artery (MCA) atherosclerotic plaques; (3) patients who underwent CTA and 7T MRI examinations prior to DSA and before any endovascular revascularization treatment; (4) a time interval of no more than four weeks between CTA, MRI, and DSA examinations. The exclusion criteria were: (1) complete occlusion of the MCA; (2) poor image quality or severe artifacts; (3) inability to reliably measure stenosis length or luminal diameter at the stenotic segment. The patient selection workflow is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Digital Subtraction Angiography (DSA)\u003c/h2\u003e \u003cp\u003eAll patients underwent digital subtraction angiography (DSA) examinations using a Siemens Axiom Artis Z neuroangiography system (Siemens, Germany). During the procedure, conventional right femoral artery puncture was performed, and an arterial sheath (RSA60K10SQ, Terumo, Japan; batch number: 220108VA) was inserted at the puncture site to establish an access route for angiography. Subsequently, the angiographic catheter was advanced to the common carotid artery segment for contrast injection. For intracranial anterior circulation imaging, iopamidol contrast agent (Omnipaque, GE Healthcare, USA) was used, with a total injection volume of 12 mL and a flow rate of 5 mL/s. Image acquisition included standard Towne and lateral projections to ensure clear visualization and comprehensive assessment of the intracranial arteries.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 CT Image Acquisition\u003c/h2\u003e \u003cp\u003eAll head and neck CTA examinations were performed using Siemens SOMATOM Definition Flash and SOMATOM Force scanners (Siemens Healthineers, Erlangen, Germany). Patients were positioned supine, head first, with the head maintained in a neutral position and properly immobilized. Prior to scanning, patients were instructed to breathe calmly and avoid swallowing or head movement to minimize motion artifacts. A three-phase injection protocol was applied: an initial 30 mL saline flush injected intravenously at 5 mL/s, followed by iopamidol contrast agent (Omnipaque 350, GE Healthcare, WI, USA) administered at a weight-based dose of 1.0\u0026ndash;1.5 mL/kg body weight (maximum volume\u0026thinsp;\u0026le;\u0026thinsp;90 mL), and finally a second 30 mL saline flush at the same flow rate. Bolus tracking was used with the region of interest placed in the ascending aorta, and image acquisition was triggered automatically after reaching the predefined attenuation threshold. The scan range extended from the aortic arch to the vertex. The acquisition time for each CTA scan was approximately 4\u0026ndash;5 seconds. The main scanning parameters were as follows: tube current 250 mAs, tube voltage 120 kV, pitch 1.45, rotation time 0.5 s, collimation 128 \u0026times; 0.6 mm\u0026sup2;, slice thickness 0.6 mm, field of view 230 \u0026times; 230 mm\u0026sup2;, matrix size 512 \u0026times; 512.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 MRI Image Acquisition\u003c/h2\u003e \u003cp\u003eAll patients underwent MRA on a 7.0 T MRI system (MAGNETOM Terra, Siemens Healthineers, Erlangen, Germany) equipped with a 32-channel head coil. A three-dimensional fast spin-echo sequence with variable flip angles (SPACE) was used to obtain high-resolution, isotropic 3D images. The detailed imaging parameters were as follows: repetition time (TR) / echo time (TE)\u0026thinsp;=\u0026thinsp;1250 / 23 ms; field of view (FOV)\u0026thinsp;=\u0026thinsp;180 \u0026times; 180 mm\u0026sup2;; matrix\u0026thinsp;=\u0026thinsp;400 \u0026times; 400; slice thickness\u0026thinsp;=\u0026thinsp;0.45 mm; voxel size\u0026thinsp;=\u0026thinsp;0.45 \u0026times; 0.45 \u0026times; 0.45 mm\u0026sup3;; number of slices\u0026thinsp;=\u0026thinsp;256; acquisition time\u0026thinsp;=\u0026thinsp;6 min 45 s.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Vascular Measurements and Stenosis Calculation\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.5.1 DSA Image Measurements\u003c/h2\u003e \u003cp\u003eDSA images were independently assessed by a senior neurointerventional physician with 9 years of experience. On the Towne projection showing the maximal opacification of the MCA segment, the following measurements were obtained for both MCAs: (1) length of stenosis (L); (2) diameter at the point of maximal stenosis (d); (3) proximal normal diameter (D). For stenosis length, if the stenotic segment was tortuous and extended, a segmented polyline method was used; the lengths of all segments were summed to obtain the final stenosis length. Because DSA provides two-dimensional images, luminal area cannot be measured.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.5.2 CTA and HR-VWI Image Measurements\u003c/h2\u003e \u003cp\u003eCTA and HR-VWI images were independently measured in a double-blind manner by two experienced radiologists (with 10 and 15 years of experience, respectively). Each radiologist repeated the measurements after a 3-month interval to evaluate inter- and intra-observer reproducibility. All images were imported into the same Siemens post-processing workstation for multiplanar reconstruction (MPR). CTA series and non-contrast T1-weighted SPACE sequences were used for three-plane reconstruction to obtain MCA segment images.\u003c/p\u003e \u003cp\u003eThe measurement procedures were similar to those used for DSA. However, CTA/MRI additionally allowed luminal area quantification: (1). Independently inspect bilateral MCAs and determine the point of maximal stenosis. (2). Generate oblique-coronal MPR images parallel to the MCA long axis and short-axis MPR images perpendicular to the long axis, and use curved planar reformation (CPR) to display the curved MCA lumen along a single plane. (3). Measure the length of stenosis on MPR/CPR images; measure the diameter and area at maximal stenosis, as well as the proximal normal diameter and area, on MPR images.\u003c/p\u003e \u003cp\u003eIf multiple stenotic lesions were present within the same MCA, only the most severe stenosis was selected for measurement and subsequent analysis for that artery. If the contralateral MCA is free of stenosis, the corresponding normal site is used for luminal diameter and area measurement.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.5.3 Stenosis Calculation\u003c/h2\u003e \u003cp\u003eAccording to the Warfarin\u0026ndash;Aspirin Symptomatic Intracranial Disease (WASID) criteria [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], the degree of stenosis was calculated based on the measured parameters as follows:\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003e1) Diameter-based stenosis:\u003c/h3\u003e\n\u003cp\u003e \u003cdiv id=\"Equa\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:Diameter\\:Based\\:Stenosis\\%=\\left(1-\\frac{d}{D}\\right)\\text{ⅹ}100\\%\\:\\:\\left(1\\right)$$\u003c/div\u003e \u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003e2) Area-based stenosis:\u003c/h3\u003e\n\u003cp\u003e \u003cdiv id=\"Equb\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:Area\\:Based\\:Stenosis\\%=\\left(1-\\frac{a}{A}\\right)\\text{ⅹ}100\\%\\:\\:\\left(2\\right)$$\u003c/div\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:d\\)\u003c/span\u003e\u003c/span\u003e is the diameter at the maximal stenosis, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:D\\)\u003c/span\u003e\u003c/span\u003e is the diameter of the proximal normal segment, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:a\\)\u003c/span\u003e\u003c/span\u003e is the lumen area at the maximal stenosis, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:A\\)\u003c/span\u003e\u003c/span\u003e is the lumen area of the proximal normal segment.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Statistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using the SciPy package in Python 3.11.0. Inter- and intra-observer consistency was assessed using the intraclass correlation coefficient (ICC; \u0026lt;0.5, poor; 0.5\u0026ndash;0.75, moderate; 0.75\u0026ndash;0.9, good; \u0026gt;0.9, excellent), and methodological agreement between CTA and DSA, as well as between 7T MRI and DSA, was evaluated using the concordance correlation coefficient (CCC; \u0026lt;0.90, poor; 0.90\u0026ndash;0.95, moderate; \u0026gt;0.95, excellent). Bland\u0026ndash;Altman plots were also used to assess systematic bias and limits of agreement. Differences between CTA and DSA, and between 7T MRI and DSA, were assessed using the Wilcoxon signed-rank test, and Cohen\u0026rsquo;s d was calculated to quantify the magnitude of differences between measurements, with larger absolute values indicating greater differences. For all analyses, quantitative measurements were calculated as the mean of two repeated measurements from both radiologists. A P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Patient characteristics\u003c/h2\u003e \u003cp\u003eAmong the initial 240 patients, 125 were excluded: 68 due to incomplete imaging data, 35 due to poor CTA or MRI image quality that prevented measurement, and 22 due to vascular occlusion. Ultimately, 115 patients with 122 stenotic vessels (59 left-sided and 63 right-sided) were included in the analysis. Among these patients, 81 were male and 34 female, with a mean age of 55.9\u0026thinsp;\u0026plusmn;\u0026thinsp;10.6 years. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows an example of a 56-year-old female patient with stenosis of the right middle cerebral artery (M1 segment) on CTA and HR-VWI.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Methodological Agreement\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the agreement between CTA, 7T HR-VWI, and DSA for diameter-based stenosis, area-based stenosis, and lesion length measurements. CTA and DSA showed poor consistency in diameter-based stenosis measurement (CCC\u0026thinsp;=\u0026thinsp;0.81, 95% CI: 0.78\u0026ndash;0.93, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, |d|=0.78), whereas HR-VWI demonstrated moderate to high consistency (CCC\u0026thinsp;=\u0026thinsp;0.92, 95% CI: 0.90\u0026ndash;0.95, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, |d|=0.35). Bland-Altman analysis revealed biases of 0.06 for CTA and 0.02 for HR-VWI, with 95% limits of agreement (LoA) of \u0026minus;\u0026thinsp;0.04 to 0.15 and \u0026minus;\u0026thinsp;0.07 to 0.10, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, b).\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\u003eAgreement Between CTA, 7T MRI, and DSA for Diameter-Based Stenosis, Area-Based Stenosis, and Lesion Length Measurements.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethods\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u003cem\u003e\u0026plusmn;\u003c/em\u003e\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCCC\u003csup\u003e*\u003c/sup\u003e (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e|d|\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiameter-Based Stenosis\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.59\u0026thinsp;\u003cem\u003e\u0026plusmn;\u003c/em\u003e\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCTA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.53\u0026thinsp;\u003cem\u003e\u0026plusmn;\u003c/em\u003e\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.81 [0.78, 0.93]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR-VWI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.57\u0026thinsp;\u003cem\u003e\u0026plusmn;\u003c/em\u003e\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.92 [0.90, 0.95]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArea-Based Stenosis\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 \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCTA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.63\u0026thinsp;\u003cem\u003e\u0026plusmn;\u003c/em\u003e\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.76 [0.70, 0.84]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR-VWI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.61\u0026thinsp;\u003cem\u003e\u0026plusmn;\u003c/em\u003e\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87 [0.85, 0.93]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLesion length (mm)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.62\u0026thinsp;\u003cem\u003e\u0026plusmn;\u003c/em\u003e\u0026thinsp;2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCTA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e5.07\u0026thinsp;\u003cem\u003e\u0026plusmn;\u003c/em\u003e\u0026thinsp;2.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91 [0.89, 0.94]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR-VWI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.62\u0026thinsp;\u003cem\u003e\u0026plusmn;\u003c/em\u003e\u0026thinsp;2.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.94 [0.92, 0.96]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eCCC* refers to the concordance correlation coefficient between CTA/7T MRI and DSA (CCC: poor, \u0026lt; 0.90; moderate, 0.90\u0026ndash;0.95; excellent, \u0026gt; 0.95); \u003cem\u003ep\u003c/em\u003e indicates P-values derived from comparisons with DSA results using the Wilcoxon signed-rank test; \u003cem\u003ed\u003c/em\u003e indicates the magnitude of differences between groups.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFor area-based stenosis, CTA showed poor agreement with DSA (CCC\u0026thinsp;=\u0026thinsp;0.76, 95% CI: 0.70\u0026ndash;0.84, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, |d|=0.64), while HR-VWI demonstrated slightly higher agreement (CCC\u0026thinsp;=\u0026thinsp;0.87, 95% CI: 0.85\u0026ndash;0.93, P\u0026thinsp;=\u0026thinsp;0.02, |d|=0.22). The biases were 0.02 for CTA and 0.04 for HR-VWI, with 95% LoA of \u0026minus;\u0026thinsp;0.19 to 0.16 and \u0026minus;\u0026thinsp;0.14 to 0.06, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, d).\u003c/p\u003e \u003cp\u003eRegarding lesion length, CTA slightly overestimated measurements (5.07\u0026thinsp;\u0026plusmn;\u0026thinsp;2.28 mm vs. 4.62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.40 mm), whereas HR-VWI showed high concordance with DSA (4.62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.11 mm). CCC values were 0.91 (95% CI: 0.89\u0026ndash;0.94) for CTA and 0.94 (95% CI: 0.92\u0026ndash;0.96) for HR-VWI, with biases of 0.48mm and 0.04mm, and 95% LoA of \u0026minus;\u0026thinsp;2.35 to 1.40 and \u0026minus;\u0026thinsp;1.49 to 1.57, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee, f).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Inter- and Intra-Observer Consistency\u003c/h2\u003e \u003cp\u003eInter-observer and intra-observer agreement for diameter-based stenosis, area-based stenosis, and lesion length measurements obtained from CTA and HR-VWI are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. For CTA, the inter-/intra-observer ICCs for diameter-based stenosis, area-based stenosis, and lesion length were 0.86/0.87, 0.83/0.83, and 0.94/0.97, respectively. Correspondingly, HR-VWI demonstrated higher reproducibility, with inter-/intra-observer ICCs of 0.94/0.95, 0.94/0.94, and 0.99/0.98.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInter- and Intra-Observer Intraclass Correlation Coefficients for CTA and 7T MRI Measurements.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\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\u003eCTA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eHR-VWI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInter-observer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntra-observer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInter-observer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIntra-observer\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiameter-Based\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.86 [0.72, 0.93]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.87 [0.75, 0.94]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.94 [0.87, 0.97]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.95 [0.89, 0.97]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArea-Based\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.83 [0.67, 0.92]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.83 [0.67, 0.91]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.94 [0.88, 0.97]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.94 [0.88, 0.97]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLesion length\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.94 [0.88, 0.97]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.97 [0.94, 0.99]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.99 [0.97, 0.99]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.98 [0.96, 0.99]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe present study provides compelling evidence supporting the clinical value of 7T HR-VWI in the evaluation of MCA stenosis. Our analysis yielded two principal findings that carry significant implications for neurovascular imaging practice. First, 7T HR-VWI demonstrated superior intra- and inter-observer reproducibility compared to CTA, indicating greater measurement consistency across different readers and interpretation sessions. Second, and perhaps more critically, diameter-based measurements of MCA stenosis severity derived from 7T HR-VWI exhibited substantially stronger agreement with DSA than those obtained from CTA. This enhanced agreement with the reference standard suggests that 7T HR-VWI may represent a more reliable alternative to conventional CTA for pre-procedural planning and stenosis quantification in neurovascular interventions.\u003c/p\u003e \u003cp\u003eThe critical importance of accurate and timely intracranial vasculopathic diagnosis cannot be overstated in contemporary cerebrovascular medicine. Diagnostic delays or errors in characterizing MCA stenosis significantly increase morbidity risk, potentially leading to devastating neurological outcomes [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. While intra-arterial DSA remains the undisputed reference standard for comprehensive vascular assessment, its invasive nature, coupled with associated procedural risks and substantial resource requirements, has prompted the widespread adoption of less invasive alternatives in routine clinical practice. Among these, CTA and magnetic resonance angiography (MRA) have emerged as first-line diagnostic tools in many institutions. This transition from invasive to non-invasive imaging modalities represents a significant paradigm shift in neurovascular diagnostics, though it simultaneously introduces new challenges in measurement accuracy, standardization, and clinical validation.\u003c/p\u003e \u003cp\u003eThe fundamental distinction between these imaging approaches lies in their underlying visualization principles and diagnostic capabilities. Unlike DSA, which primarily provides luminographic information through contrast-filled vessel lumens, CTA and MRA enable multiplanar visualization of vessels and permit preliminary evaluation of the vessel wall and surrounding structure [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. This technological difference carries profound clinical implications, particularly in the context of rapidly evolving neurointerventional practices where detailed vascular anatomical information beyond mere lumenography is increasingly crucial for procedural planning, device selection, and therapeutic decision-making.\u003c/p\u003e \u003cp\u003eThe landscape of endovascular treatment (EVT) has undergone remarkable transformation in recent years, characterized by a notable trend toward the use of large-bore aspiration catheters. This technological evolution has simultaneously heightened the importance of precise vessel sizing in pre-procedural planning. While larger catheters may theoretically enhance first-pass efficacy and improve aspiration performance [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], their implementation raises legitimate concerns about potential vessel trauma, endothelial injury, and oversizing\u0026mdash;particularly when device selection relies primarily on pre-procedural CTA measurements rather than intraprocedural DSA [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe current clinical preference for deploying the largest feasible catheter prior to DSA acquisition primarily aims to minimize time to reperfusion\u0026mdash;a critical factor in determining neurological outcomes following acute ischemic stroke. However, this \"one-size-fits-most\" approach potentially overlooks the nuanced need for individualized device selection to optimize both safety and efficacy. The seminal study by Rogers et al. compellingly highlighted this concern by demonstrating that CTA systematically overestimates MCA diameter relative to DSA, with a median discrepancy of 0.4 mm [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. This systematic overestimation underscores a fundamental limitation of CTA-first sizing strategies, especially in modern neurointerventional workflows where thrombectomy devices are frequently selected before intra-procedural DSA is performed.\u003c/p\u003e \u003cp\u003e In this evolving clinical context, the improved agreement of 7T HR-VWI with DSA, as robustly demonstrated in our study, supports its potential utility in enabling more reliable pre-interventional vessel assessment. This enhanced accuracy could prove invaluable in aiding the selection of appropriately sized devices while simultaneously mitigating procedural risks associated with vessel injury from oversized catheters or inadequate thrombus engagement from undersized devices. The implications extend beyond mere measurement accuracy to encompass potentially improved clinical outcomes through optimized device-vessel compatibility.\u003c/p\u003e \u003cp\u003eHigh-resolution vessel wall imaging signifies a substantial advancement in cerebrovascular assessment, offering superior accuracy in delineating pathological changes compared to conventional luminal imaging techniques. The evolution of this technology has followed a clear trajectory toward higher field strengths and improved spatial resolution. Evidence from Liu et al. indicates that even at 3T, HR-VWI enables precise assessment of middle cerebral artery stenosis, consistently outperforming CTA and demonstrating superior concordance with DSA as the reference standard [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Similarly, Gong et al. reported excellent agreement between 3T HR-VWI and DSA in luminal evaluation, while time-of-flight magnetic resonance angiography (TOF-MRA) showed limited diagnostic performance in direct comparisons [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe diagnostic capability of HR-VWI reaches its current apex at 7T, representing the optimal clinical modality for detailed vessel wall assessment available today. The elevated magnetic field strength at 7T affords substantial gains in spatial resolution and signal-to-noise ratio [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], facilitating refined characterization of plaque morphology and composition beyond the capabilities of 3T systems [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. These technical advantages translate directly to improved diagnostic confidence, particularly in evaluating complex plaque characteristics, identifying vulnerable plaque features, and assessing vessel wall remodeling\u0026mdash;capabilities that remain fundamentally limited in conventional angiographic techniques. Furthermore, the ability to visualize plaque components, including intraplaque hemorrhage, lipid-rich necrotic cores, and fibrous caps, provides invaluable insights into stroke pathogenesis and risk stratification that transcend mere luminal assessment.\u003c/p\u003e \u003cp\u003eThe optimal methodology for quantifying arterial stenosis\u0026mdash;specifically the ongoing debate between diameter versus area-based measurements\u0026mdash;remains a subject of considerable discussion in vascular imaging research. The literature presents conflicting perspectives on this fundamental measurement approach, reflecting the complexity of vascular geometry and its clinical implications. Samarzija et al. reported that diameter-based CTA measurements significantly underestimated carotid stenosis severity and recommended the area method due to its superior predictive power for correct stenosis classification and closer agreement with color Doppler ultrasound (CDUS) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Supporting this view, Zhang et al. observed only moderate agreement between CTA area measurements and DSA diameter stenosis, noting particularly poor correlation between diameter and area measurements in vessels with markedly non-circular lumens compared to those with circular configurations [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Bucek et al. further reinforced the value of area assessment, demonstrating better inter-observer agreement and stronger correlation with DSA for CTA area measurements than for diameter-based approaches [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, this perspective favoring area measurements is not universally accepted within the scientific community. Carnicelli et al. found no significant difference between diameter and area measurements when using CDUS as a reference standard [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Similarly, Van Prehn et al. reported comparable correlation coefficients for both methods against ultrasound and concluded that diameter measurements provide an adequate approximation of area-based assessment [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Most notably, Bartlett et al. directly contended that minimal diameter measurements reliably predict the more computationally complex area-based quantification [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], emphasizing the practical utility of diameter assessment in clinical workflows.\u003c/p\u003e \u003cp\u003eIn the context of these conflicting findings across previous studies, our investigation demonstrated consistently superior performance with diameter-based measurements for assessing MCA stenosis using both CTA and, more importantly, 7T HR-VWI. These results align more closely with the conclusions of Bartlett et al. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], suggesting that in MCA evaluation specifically, the minimal diameter method provides sufficient accuracy while offering substantial practical advantages in clinical measurement workflows. This finding carries significant implications for clinical practice, as diameter measurements typically require less processing time and computational resources compared to area-based assessments, potentially facilitating more efficient integration into busy neurovascular imaging protocols without compromising diagnostic accuracy.\u003c/p\u003e \u003cp\u003eSeveral limitations of this study warrant consideration. First, the retrospective design introduces potential recall bias; however, this was mitigated through repeated image evaluations conducted at scheduled intervals, with readers blinded to patient identifiers and clinical details. Second, the recruitment of participants based on clinical history may have introduced selection bias. To address this concern, the analysis focused on an objective comparison of HR-VWI and CTA in evaluating stenotic severity, rather than on establishing definitive diagnoses. Third, the limited clinical availability of 7T HR-VWI must be acknowledged; nevertheless, the primary objective of this study was to perform a methodological comparison between advanced vessel wall imaging and conventional angiographic techniques, rather than to advocate for immediate clinical implementation.\u003c/p\u003e \u003cp\u003eIn summary, 7T HR-VWI demonstrates superior accuracy, agreement with DSA, and reproducibility compared with CTA for quantitative assessment of MCA stenosis and lesion length. These findings support the potential utility of 7T HR-VWI as a reliable noninvasive imaging tool for precise evaluation of intracranial arterial stenotic lesions.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eICAS:\u003c/strong\u003e Intracranial atherosclerotic stenosis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWASID:\u003c/strong\u003e Warfarin-Aspirin Symptomatic Intracranial Disease\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDSA\u003c/strong\u003e: Digital subtraction angiography\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCTA\u003c/strong\u003e: Computed tomography angiography\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHR-VWI\u003c/strong\u003e: high-resolution vessel wall imaging\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMCA\u003c/strong\u003e: Middle cerebral artery\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTR\u003c/strong\u003e: Repetition time\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTE\u003c/strong\u003e: Echo time\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFOV\u003c/strong\u003e: field of view\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMPR\u003c/strong\u003e: multiplanar reconstruction\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCPR\u003c/strong\u003e: curved planar reformation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eICC\u003c/strong\u003e: Intraclass correlation coefficients\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCCC\u003c/strong\u003e: Concordance correlation coefficient\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLoA\u003c/strong\u003e: Limits of agreement\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMRA\u003c/strong\u003e:\u0026nbsp;Magnetic resonance angiography\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEVT\u003c/strong\u003e:Endovascular treatment\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful for the support of the 7T Magnetic Resonance Translational Medicine Research Center Special Construction Fund [424Z2Q31] and the 7T Magnetic Resonance Special Fund Project of the First Affiliated Hospital of the Army Medical University [20247TZD01] for this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the 7T Magnetic Resonance Translational Medicine Research Center Special Construction Fund [424Z2Q31]; and the 7T Magnetic Resonance Special Fund Project of the First Affiliated Hospital of the Army Medical University [20247TZD01].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e*\u003c/sup\u003eChuanghui Zhou and Mengting Hu contributed equal to this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDepartment of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing 400000, China\u003c/p\u003e\n\u003cp\u003eChuanghui Zhou, Mengting Hu, Chunlun Xiao, Wei Chen, Pinzhen Chen, He Liu, Min He, Jiafei Chen\u003c/p\u003e\n\u003cp\u003eMR Research Collaboration Team, Siemens Healthineers Ltd, Shanghai 200000, China\u003c/p\u003e\n\u003cp\u003eYicheng Hsu\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChuanghui Zhou:\u0026nbsp;Methodology, Investigation, Writing - Original Draft. Mengting Hu: Methodology, Data acquisition, Writing - Original Draft.\u0026nbsp;Chunlun Xiao: Formal analysis, Data Curation.\u0026nbsp;Yicheng Hsu: Software, Statistical analysis.\u0026nbsp;Wei Chen: Conceptualization, Writing - Review \u0026amp; Editing.\u0026nbsp;Pinzhen Chen: Writing - Review \u0026amp; Editing.\u0026nbsp;He Liu: Validation, Writing - Review \u0026amp; Editing.\u0026nbsp;Min He:\u0026nbsp;Investigation, Supervision.\u0026nbsp;Jiafei Chen: Project administration, Funding acquisition, Writing - Review \u0026amp; Editing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was performed in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the First Affiliated Hospital of Army Medical University (Approval No. KY2023167), with a waiver of informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset and code used in this study can be obtained from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFeldmann E, Daneault N, Kwan E, et al. 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J Neuroimaging. 2007;17:219\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarnicelli AP, Stone JJ, Doyle A, et al. Cross-sectional area for the calculation of carotid artery stenosis on computed tomographic angiography. J Vasc Surg. 2013;58:659\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Prehn J, Muhs BE, Pramanik B, et al. Multidimensional characterization of carotid artery stenosis using CT imaging: a comparison with ultrasound grading and peak flow measurement. Eur J Vasc Endovasc Surg. 2008;36:267\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBartlett ES, Symons SP, Fox AJ. Correlation of carotid stenosis diameter and cross-sectional areas with CT angiography. AJNR Am J Neuroradiol. 2006;27:638\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmim","sideBox":"Learn more about [BMC Medical Imaging](http://bmcmedimaging.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmim/default.aspx","title":"BMC Medical Imaging","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Middle cerebral artery, Atherosclerotic stenosis, 7-T High resolution vessel wall imaging, Computed tomography angiography, Digital subtraction angiography","lastPublishedDoi":"10.21203/rs.3.rs-9130002/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9130002/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e: To compare the accuracy, agreement, and reproducibility of 7-Tesla high-resolution vessel wall imaging (7T HR-VWI) and computed tomography angiography (CTA) for quantitative assessment of middle cerebral artery (MCA) stenosis using Digital subtraction angiography (DSA) as the reference standard.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and methods: \u003c/strong\u003eThis retrospective study recruited 115 patients with non-cardioembolic ischemic stroke between September 2022 and September 2025, comprising 122 MCA stenotic lesions. Two blinded radiologists independently measured stenosis severity (based on diameter and area) and stenotic length using CTA and HR-VWI images. Method agreement between CTA/7T HR-VWI and DSA was assessed using concordance correlation coefficient (CCC) and Bland–Altman analysis. Bland–Altman analysis was used to evaluate systematic (constant) bias and proportional bias between measurement methods. Intraclass correlation coefficients (ICC) were calculated to assess inter- and intra-observer repeatability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eDiameter-based stenosis CCC was 0.81 for CTA and 0.92 for HR-VWI; area-based stenosis CCC was 0.76 for CTA and 0.87 for HR-VWI. Bland-Altman biases were 0.06(95% LoA, -0.04, 0.15) and 0.02(95% LoA, -0.07, 0.10) for CTA and HR-VWI, respectively. Lesion length CCC was 0.91 for CTA and 0.94 for HR-VWI, with biases of 0.48(95% LoA, -2.35, 1.4) and 0.04(95% LoA, -1.49, 1.57). Inter- and intra-observer ICCs ranged from 0.83 to 0.97 for CTA and 0.94 to 0.99 for HR-VWI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003e7T HR-VWI provides a more accurate and reproducible assessment of intracranial artery stenosis and lesion length compared with CTA, suggesting its potential as a reliable imaging tool for evaluating stenotic lesions.\u003c/p\u003e","manuscriptTitle":"Accuracy of 7T High-Resolution Vessel Wall Imaging versus CTA in Middle Cerebral Artery Stenosis: A DSA-Based Validation Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-19 12:07:06","doi":"10.21203/rs.3.rs-9130002/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-12T22:18:31+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T10:48:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"37618815116000938393258677388064601715","date":"2026-04-29T03:02:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"337705541147772072852558768041194872597","date":"2026-04-22T18:34:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"100288916640015348400459734192764928837","date":"2026-04-22T15:29:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"270749859606593564637543093817457589355","date":"2026-04-13T17:01:23+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-09T13:01:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-23T10:11:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-23T08:13:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Imaging","date":"2026-03-23T07:46:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmim","sideBox":"Learn more about [BMC Medical Imaging](http://bmcmedimaging.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmim/default.aspx","title":"BMC Medical Imaging","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ebc496e8-731a-42f9-9c0c-ea3ced1ef17e","owner":[],"postedDate":"April 19th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-12T22:18:31+00:00","index":63,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T10:48:56+00:00","index":62,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-19T12:07:07+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-19 12:07:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9130002","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9130002","identity":"rs-9130002","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}