Clinical Utility of 3D-TOF MRA and CTA in Predicting Short-Term Prognosis After Endovascular Treatment for Carotid Web–Related Ischemic Stroke

Clinical Utility of 3D-TOF MRA and CTA in Predicting Short-Term Prognosis After Endovascular Treatment for Carotid Web–Related Ischemic Stroke | 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 Clinical Utility of 3D-TOF MRA and CTA in Predicting Short-Term Prognosis After Endovascular Treatment for Carotid Web–Related Ischemic Stroke Bo Wang, Nan Jin, Tingting Wang, Yanfei Zhang, Guorui Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7388366/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To investigate the relationship between imaging characteristics derived from three-dimensional time-of-flight magnetic resonance angiography (3D-TOF MRA) and multiphase computed tomography angiography (CTA), and short-term outcomes following endovascular treatment in patients with ischemic stroke associated with carotid web (CaW). Methods This retrospective study analyzed clinical and imaging data of 157 ischemic stroke patients with confirmed CaW who underwent endovascular treatment. Based on the modified Rankin Scale (mRS) score at 3-month follow-up, patients were divided into a good outcome group (n = 78) and a poor outcome group (n = 20). Clinical and imaging parameters were compared between the two groups. Multivariate logistic regression analysis was performed to identify independent predictors of poor short-term outcomes. Receiver operating characteristic (ROC) curves were constructed to evaluate the predictive value of 3D-TOF MRA and CTA scores. Results Multivariate logistic regression identified age, hypertension, hyperlipidemia, stroke severity, ICU admission, infarct size, 3D-TOF MRA score, and CTA score as independent predictors of poor short-term outcome (P < 0.05). ROC analysis demonstrated good predictive performance, with areas under the curve (AUC) of 0.877 for the 3D-TOF MRA score, 0.892 for the CTA score, and 0.926 for the combined model. Conclusion Imaging characteristics from 3D-TOF MRA and CTA are valuable predictors of short-term outcomes after endovascular treatment in ischemic stroke patients with CaW, and may serve as important references for clinical decision-making. 3D time-of-flight magnetic resonance angiography computed tomography angiography carotid web ischemic stroke short-term prognosis Figures Figure 1 Figure 2 Figure 3 Introduction Carotid web (CaW) is a rare structural abnormality of the carotid artery intima, characterized by a shelf-like fibrous membrane protruding into the arterial lumen, significantly altering local hemodynamics[1]. Recent studies have identified CaW as an important cause of cryptogenic ischemic stroke. In affected patients, CaW can induce local blood flow stasis and turbulence, predisposing to in situ thrombus formation at the web and subsequent distal cerebral infarction via an artery-to-artery embolic mechanism. However, its exact pathophysiological mechanisms remain incompletely understood[2].Although endovascular therapies, such as mechanical thrombectomy, are now standard treatments for ischemic stroke and have been shown to effectively recanalize occluded vessels and improve cerebral perfusion[3, 4],neurological recovery after intervention varies considerably among patients with CaW. This suggests that factors beyond successful recanalization—such as collateral circulation capacity—may play a critical role in clinical outcomes[5]. Currently, digital subtraction angiography (DSA) is regarded as the gold standard for evaluating collateral circulation due to its high spatial and temporal resolution. However, its clinical utility is limited by its invasive nature, the risk of contrast-induced nephrotoxicity, and radiation exposure[6].Noninvasive imaging modalities such as three-dimensional time-of-flight magnetic resonance angiography (3D-TOF MRA) and computed tomography angiography (CTA) have been widely used in cerebrovascular assessment. Nonetheless, the sensitivity and specificity of these techniques for visualizing collateral circulation in patients with carotid web (CaW) remain a subject of debate. For example, 3D-TOF MRA can clearly visualize the circle of Willis without the need for contrast agents, but it has limited capability in detecting slow-flow collaterals[7].In contrast, CTA enables rapid assessment of vascular occlusion severity but lacks the ability to quantify microcirculatory perfusion[8].The combination of 3D-TOF MRA and CTA offers complementary advantages, providing a more comprehensive evaluation of cerebral vasculature. This combined approach enhances the accuracy of assessing CaW-related occlusions and stenoses, and improves collateral circulation assessment by integrating information across multiple angles and time points. Such multimodal imaging can compensate for the limitations of single-modality techniques in identifying slow flow, visualizing small-caliber vessels, and evaluating hemodynamic status, thereby offering more reliable imaging evidence to support clinical decision-making[9, 10]. Moreover, most existing studies have focused on the association between a single imaging modality and stroke prognosis, while systematic investigations on the combined application of 3D-TOF MRA and CTA in the evaluation of CaW-related stroke remain lacking [11].To address this gap, the present study aimed to explore the relationship between combined imaging features from 3D-TOF MRA and CTA and short-term functional outcomes after endovascular treatment in patients with ischemic stroke associated with CaW.By retrospectively analyzing imaging data from patients who underwent endovascular therapy, we compared imaging parameters across different prognostic groups and assessed their predictive value.This study seeks to establish a prognosis prediction model based on multimodal imaging, providing a reference for individualized clinical management and offering new insights into the underlying mechanisms of CaW-related ischemic stroke. Methods Study population From January 2023 to March 2025, a total of 98 patients with ischemic stroke and confirmed carotid web (CaW) who underwent endovascular treatment at No. 905 Hospital of PLA Navy (China) were consecutively enrolled.Inclusion criteria were as follows: (1) diagnosis of ischemic stroke according to established criteria[ 12 ], with imaging confirmation of CaW; (2) age between 18 and 80 years; (3) symptom onset to hospital presentation within 48 hours; (4) first-ever ischemic stroke; (5) provision of written informed consent. Exclusion criteria included: (1) preexisting neurological deficits; (2) coagulopathy or abnormal coagulation profile; (3) ischemic stroke secondary to hematologic disorders, cardioembolic sources, or granulomatous diseases; (4) severe dysfunction of vital organs (heart, lungs, liver, kidneys); (5) presence of malignancy; (6) impaired consciousness or psychiatric disorders interfering with cooperation. Measurement s Participant Characteristics :Demographic and clinical data were collected, including sex, age, body mass index (BMI), smoking history, alcohol consumption, hypertension, diabetes mellitus, coronary artery disease, hyperlipidemia, stroke severity, intravenous thrombolysis, ICU admission, infarct volume, arterial occlusion site, lesion location, Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification, neutrophil count, platelet count, and serum creatinine levels. All data were obtained from the hospital’s electronic medical record system.. 3D-TOF MRA Assessment All patients underwent magnetic resonance imaging using a 3.0 Tesla MRI scanner (Siemens, Germany), including routine T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI) in axial planes. The acquired 3D-TOF MRA raw images were transferred to a dedicated 3D post-processing software for image reconstruction and analysis. Visualization and interpretation were performed using volume rendering (VR), multiplanar reconstruction (MPR), and maximum intensity projection (MIP) techniques (see Fig. 1 ). CTA Assessment Multiphase CTA imaging was performed using a multi-detector CT scanner (GE, USA). Nonionic iodinated contrast agent (iopamidol) was injected via the median cubital vein using a dual-barrel high-pressure injector at a rate of 5 mL/s, with a total volume of approximately 70–80 mL. An automatic bolus-tracking technique was employed, with the trigger threshold set at 120 Hounsfield units (HU) in the aortic arch. The arterial phase scan was initiated immediately upon reaching the threshold, followed by venous and delayed phase scans at fixed time delays (e.g., 5 seconds and 10 seconds), completing a three-phase imaging protocol. All imaging data were transferred to a workstation for post-processing using volume rendering (VR), maximum intensity projection (MIP), and multiplanar reconstruction (MPR) techniques. These images were used to evaluate the degree of vascular occlusion and the dynamic perfusion status of collateral circulation (see Fig. 2 ). Imaging Feature Scoring : Both raw and reconstructed images were independently reviewed by two experienced radiologists. In cases of disagreement, the two reviewers discussed the findings and reached a consensus. A 5-point collateral circulation grading system was used, defined as follows:0 points: 0 points(No collateral perfusion) ;1 point(Persistent perfusion defect);2 points(Partial perfusion defect);3 points:(Slow collateral flow to the ischemic area);4 points(Rapid collateral flow to the ischemic area)[ 13 ].Both 3D-TOF MRA and multiphase CTA findings were scored accordingly. For CTA, collateral grading was performed separately for each imaging phase, and the highest score among the three phases was recorded as the final collateral score.The diagnosis of carotid web was primarily based on CTA imaging. Diagnostic criteria included a thin, shelf-like intraluminal filling defect located on the posterior or posterolateral wall of the carotid bulb, without evidence of calcified plaques or atherosclerotic stenosis. In selected cases, MRA findings were used to support the diagnosis. Outcome Assessment Patients were followed up for 3 months via outpatient visits. All 157 patients completed follow-up. Functional outcomes were assessed using the modified Rankin Scale (mRS) [9] , which scores disability severity from 0 to 5. A score of > 2 or death was defined as a poor outcome, whereas a score of ≤ 2 was considered a favorable outcome [ 14 ]. Based on these criteria, patients were divided into a favorable outcome group (n = 102) and a poor outcome group (n = 55). Statistical Analysis All statistical analyses were performed using SPSS version 26.0 (IBM, Armonk, NY, USA). Continuous variables were expressed as mean ± standard deviation (x̄ ± s), and categorical variables were presented as counts and percentages (%). Comparisons between groups were conducted using the t -test for continuous variables and the chi-square test for categorical variables. Multivariate logistic regression analysis was performed to identify factors independently associated with short-term outcomes. The predictive value of the scoring methods was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). A two-sided P value < 0.05 was considered statistically significant. Results As shown in Table 1 , significant differences were observed between the poor outcome group and the good outcome group in terms of age, presence of hypertension, presence of hyperlipidemia, stroke severity, ICU admission, infarct volume, proportion of large-artery atherosclerosis, 3D-TOF MRA scores, and CTA scores (P < 0.05). Table 1 Comparison of Short-Term Prognosis After Interventional Therapy in Ischemic Stroke Patients with Carotid Web (CaW) Variable Poor Prognosis Group (n = 55) Good Prognosis Group (n = 102) χ²/t P Gender 0.499 0.480 Male 35(63.64) 59(57.84) Female 20(36.36) 43(42.16) Age (years) 68.98 ± 12.01 61.44 ± 12.54 2.419 0.018 BMI (kg/m²) 23.44 ± 1.87 23.06 ± 2.14 0.726 0.470 Smoking history 0.310 0.578 Yes 3 (15.00%) 16 (20.51%) No 17 (85.00%) 62 (79.49%) Alcohol consumption history 0.001 0.975 Yes 2 (10.00%) 8 (10.26%) No 18 (90.00%) 70 (89.74%) Hypertension 4.021 0.045 Yes 14 (70.00%) 35 (44.87%) No 6 (30.00%) 43 (55.13%) Diabetes 0.312 0.576 Yes 8 (40.00%) 26 (33.33%) No 12 (60.00%) 52 (66.67%) Coronary heart disease 1.043 0.307 Yes 8 (40.00%) 22 (28.21%) No 12 (60.00%) 56 (71.79%) Hyperlipidemia 4.071 0.044 Yes 11 (55.00%) 25 (32.05%) No 9 (45.00%) 53 (67.95%) Severity of illness 9.235 0.010 Mild 2 (10.00%) 31 (39.74%) Moderate 5 (25.00%) 23 (29.49%) Severe 13 (65.00%) 24 (30.77%) IV thrombolysis 0.095 0.758 Yes 10 (50.00%) 36 (46.15%) No 10 (50.00%) 42 (53.85%) ICU admission 5.031 0.025 Yes 13 (65.00%) 29 (37.18%) No 7 (35.00%) 49 (62.82%) Cerebral infarct area (mm²) 59.46 ± 8.82 45.29 ± 6.71 7.877 0.000 Arterial occlusion site 2.788 0.594 Internal carotid artery 5 (25.00%) 25 (32.05%) M1 segment 7 (35.00%) 33 (42.31%) ICA and M1 segment 6 (30.00%) 12 (15.38%) Basilar artery 1 (5.00%) 6 (7.69%) Vertebral artery (V4 segment) 1 (5.00%) 2 (2.56%) Lesion location 0.359 0.549 Anterior circulation 17 (85.00%) 70 (89.74%) Posterior circulation 3 (15.00%) 8 (10.26%) TOAST classification 6.054 0.048 Large artery atherosclerosis 6 (30.00%) 40 (51.28%) Cardioembolism 7 (35.00%) 28 (35.90%) Other 7 (35.00%) 10 (12.82%) Neutrophil count (×10⁹/L) 7.23 ± 2.67 6.71 ± 1.33 1.233 0.221 Platelet count (×10⁹/L) 241.25 ± 23.69 235.58 ± 26.17 0.880 0.381 Serum creatinine (µmol/L) 80.27 ± 12.41 82.10 ± 13.25 0.558 0.578 3D-TOF MRA score 1.65 ± 0.53 2.95 ± 0.98 5.707 0.000 CTA score 1.75 ± 0.65 3.06 ± 0.85 6.418 0.000 As presented in Table 2 , multivariate analysis identified age, presence of hypertension, hyperlipidemia, stroke severity, infarct volume, 3D-TOF MRA score, and CTA score as independent predictors of short-term functional outcome after endovascular treatment in patients with ischemic stroke associated with CaW ( P < 0.05). Table 2 Multivariate Logistic Regression Analysis of Factors Influencing Short-Term Prognosis After Interventional Therapy in Ischemic Stroke Patients with Carotid Web (CaW) Variable β SE Wald P OR Value 95% Confidence Interval Age 0.65 0.321 4.1 0.043 1.196 1.021–3.594 Hypertension (No = 1, Yes = 2) -0.797 0.397 4.03 0.045 0.451 0.207–0.981 Hyperlipidemia (No = 1, Yes = 2) -0.82 0.333 6.064 0.014 0.44 0.229–0.846 Severity of illness (Mild = 1, Moderate = 2, Severe = 3) -0.996 0.445 5.01 0.025 0.369 0.154–0.884 Cerebral infarct area 4.014 1.194 11.302 0.001 55.368 5.332–574.923 3D-TOF MRA score -2.793 1.197 5.444 0.020 0.061 0.006–0.640 CTA score -4.07 1.245 10.687 0.001 0.017 0.001–0.196 Constant -7.419 1.232 36.263 0.000 – – Receiver operating characteristic (ROC) curve analysis demonstrated that 3D-TOF MRA score, CTA score, and the combined imaging assessment all had good predictive value for short-term outcomes in patients with CaW-related ischemic stroke following endovascular treatment. The area under the curve (AUC) values were 0.877, 0.892, and 0.926, respectively ( P < 0.05).See Table 3 and Fig. 3 for details. Table 3 ROC Curve Results for 3D-TOF MRA and CTA Scores in Predicting Short-Term Prognosis After Interventional Therapy in Ischemic Stroke Patients with Carotid Web (CaW) Variable AUC 95% CI Sensitivity Specificity Optimal Cut-off P 3D-TOF MRA Score 0.877 0.805–0.948 0.885 0.750 1.830 0.000 CTA Score 0.892 0.821–0.963 0.885 0.750 1.995 0.000 Combined Assessment 0.93 0.867–0.986 0.897 0.800 – 0.00 The ROC curves illustrate the predictive performance of 3D time-of-flight magnetic resonance angiography (3D-TOF MRA) and computed tomography angiography (CTA) scores, as well as their combined assessment, for short-term outcomes following interventional treatment. The dashed line represents the 3D-TOF MRA score, the thin solid line represents the CTA score, and the bold solid line represents the combined assessment. The diagonal line indicates the reference line (AUC = 0.5). The area under the curve (AUC) values were 0.877 for 3D-TOF MRA, 0.892 for CTA, and 0.926 for the combined model, indicating good discriminative ability of all three approaches, with the combined model performing best. Discussion This study investigated the factors influencing short-term functional outcomes following endovascular treatment in patients with ischemic stroke associated with carotid web (CaW). The findings indicate that advanced age, comorbid hypertension and hyperlipidemia, moderate-to-severe stroke severity, and larger infarct volume were independent risk factors for poor prognosis. These observations are consistent with previous reports. With advancing age, vascular elasticity declines, intimal thickening and lipid deposition increase, all of which exacerbate vascular stenosis and atherosclerosis, thereby elevating the risk of stroke onset and recurrence[ 15 ].Hypertension and hyperlipidemia are well-established risk factors for cerebrovascular disease and often act synergistically to trigger or exacerbate vascular wall injury and hemodynamic disturbances, which may compromise reperfusion efficacy and hinder functional recovery[ 16 ].Additionally, a larger infarct area implies more extensive brain tissue damage, which naturally correlates with poorer outcomes. Therefore, in patients with these risk factors, postoperative management should emphasize blood pressure and lipid control, as well as appropriate use of antiplatelet and lipid-lowering therapies, to facilitate better long-term recovery. This study also evaluated the prognostic value of 3D-TOF MRA and CTA imaging in the early postoperative period. Results demonstrated that both 3D-TOF MRA and CTA scores were significantly lower in the poor outcome group than in the favorable outcome group, and both were identified as independent predictors of short-term prognosis. 3D-TOF MRA, a noninvasive vascular imaging technique based on the principle of "flow-related enhancement," effectively captures high-velocity blood flow signals and is suitable for assessing perfusion in larger vessels. However, its sensitivity for detecting small-caliber or slow-flow collateral vessels is limited[ 17 , 18 ].CTA, through intravenous contrast administration and rapid multi-planar image acquisition, offers superior spatial resolution and a more comprehensive assessment of collateral circulation, making it particularly suitable for acute stroke evaluation[ 19 ].Both imaging scores reflect the extent of postoperative flow restoration and collateral perfusion, suggesting that higher scores are associated with better cerebral perfusion and improved neurological recovery. Currently, a wide range of methods are available for predicting prognosis in ischemic stroke, including clinical scoring systems (e.g., NIHSS, mRS), laboratory markers (e.g., inflammatory cytokines, D-dimer), neurophysiological techniques (e.g., electroencephalography), and imaging-based assessments. However, scales such as the NIHSS may have limited prognostic value in certain subtypes of ischemic stroke, such as small artery occlusion (SAO) or strokes involving penetrating artery lesions[ 20 ].In terms of imaging, beyond 3D-TOF MRA and CTA, modalities such as CT perfusion (CTP), diffusion-weighted imaging (DWI), and perfusion-weighted imaging (PWI) are also widely used to evaluate ischemic penumbra and collateral circulation, offering guidance for predicting outcomes after reperfusion therapy[ 21 – 23 ].Nevertheless, CTP requires more advanced equipment and technical expertise and carries a higher risk of radiation exposure. While DWI and PWI have clear advantages in localizing ischemic lesions, they remain limited in assessing hemodynamic changes and collateral compensation.In this study, ROC curve analysis demonstrated that both 3D-TOF MRA and CTA scores showed strong discriminatory ability in predicting short-term outcomes following endovascular treatment in patients with CaW-related ischemic stroke. Their combined use further improved predictive accuracy, with an AUC of 0.926—higher than values reported in previous studies using combined CTA and CTP assessments[ 24 , 25 ].These findings suggest that multimodal imaging provides superior clinical utility and sensitivity, and can serve as a valuable tool for postoperative prognostication.Moreover, 3D-TOF MRA and CTA offer advantages such as short acquisition times, stable data acquisition, and relatively intuitive interpretation. These features are particularly beneficial in patients with significant anatomical variations such as CaW, where the two modalities can clearly depict alterations in local blood flow pathways and assess the establishment of intracranial collateral circulation. This provides direct guidance in determining whether effective compensatory blood flow channels have been formed after intervention. Therefore, this study supports the integration of combined 3D-TOF MRA and CTA into the postoperative follow-up protocol for patients with CaW-related stroke. As a repeatable, noninvasive imaging strategy with high clinical value, this approach may provide a reliable basis for developing precise, individualized rehabilitation and secondary prevention plans following endovascular treatment. However, several limitations should be acknowledged. This was a single-center study with a relatively small sample size, which may limit the generalizability of the findings. Future studies with larger, multicenter cohorts are needed to validate and strengthen the conclusions. In addition, the diagnosis of carotid web in this study was based solely on imaging features without histopathological confirmation. Although previous studies have demonstrated a high concordance between imaging findings and pathological results, the absence of tissue validation introduces a degree of diagnostic uncertainty. Future research should incorporate pathological evidence to further verify the imaging-based diagnostic criteria for carotid web. Declarations Ethics approval and consent to participate The study was submitted to, and approved by the Ethics Committee of No. 905 Hospital of PLA Navy（No. 2023LW07）.All methods were performed in accordance with the Declaration of Helsinki.Informed consent to participate was obtained from all of the participants in the study. Consent for publication Not applicable. Availability of data and materials All relevant data are presented in the text and the tables. Competing interests The authors declare that they have no competing interests. Funding There was no source of funding. Authors’ contributions GL and YZ conceived and designed the study. BW and NJ wrote the paper. TW contributed to data collection. BW ,NJ and TW contributed equal to this paper .All authors read and approved the final manuscript. Acknowledgements Not applicable. References Patel SD, Otite FO, Topiwala K, Saber H, Kaneko N, Sussman E, Mehta TV, Tummala R, Hinman J, Nogueira R et al : Interventional compared with medical management of symptomatic carotid web: A systematic review . Journal of Stroke and Cerebrovascular Diseases 2022, 31 (10):106682. Zhang AJ, Dhruv P, Choi P, Bakker C, Koffel J, Anderson D, Kim J, Jagadeesan B, Menon BK, Streib C: A Systematic Literature Review of Patients With Carotid Web and Acute Ischemic Stroke . STROKE 2018, 49 (12):2872-2876. Boujan T, Neuberger U, Pfaff J, Nagel S, Herweh C, Bendszus M, Möhlenbruch MA: Value of Contrast-Enhanced MRA versus Time-of-Flight MRA in Acute Ischemic Stroke MRI . AM J NEURORADIOL 2018, 39 (9):1710-1716. Campbell D, Butler E, Campbell RB, Ho J, Barber PA: General Anesthesia Compared With Non-GA in Endovascular Thrombectomy for Ischemic Stroke . NEUROLOGY 2023, 100 (16). Busto G, Casetta I, Morotti A, Barra A, Maccaglia MG, Bianchi A, Moretti M, Capasso F, Toffali M, Arba F: Multi-phase CT-Angiography outperforms angiographic careggi collateral score and predicts functional outcome in acute ischemic stroke . NEUROL SCI 2025, 46 (1):249-256. Chiara C, Umberto S, Daniele M, Valentina C, Nicola C, Valeria L, Giuseppina S, Andrea S, Pietro F, Ivan G: Correction to: Association of the Careggi Collateral Score with 3-month modified Rankin Scale score after thrombectomy for stroke with occlusion of the middle cerebral artery . J NEUROL 2022(269-2). Shi Z, Zhao X, Zhu S, Miao X, Zhang Y, Han S, Wang B, Zhang B, Ye X, Dai Y et al : Time-of-Flight Intracranial MRA at 3 T versus 5 T versus 7 T: Visualization of Distal Small Cerebral Arteries . RADIOLOGY 2023, 306 (1):207-217. Mair G, White P, Bath PM, Muir K, Martin C, Dye D, Chappell F, Kummer R, Macleod M, Sprigg N et al : Accuracy of artificial intelligence software for CT angiography in stroke . ANN CLIN TRANSL NEUR 2023, 10 (7):1072-1082. Wang T, Li C, Li S, Tang P, Guo Q, Fang L: High-resolution magnetic resonance imaging features of time-of-flight magnetic resonance angiography signal loss and its relevance to ischemic stroke . QUANT IMAG MED SURG 2024, 14 (9):6820-6829. Regenhardt RW, González RG, He J, Lev MH, Singhal AB: Symmetric CTA Collaterals Identify Patients with Slow-progressing Stroke Likely to Benefit from Late Thrombectomy . RADIOLOGY 2022, 302 (2):400-407. Chen H, Colasurdo M, Costa M, Nossek E, Kan P: Carotid webs: a review of pathophysiology, diagnostic findings, and treatment options . J NEUROINTERV SURG 2024, 16 (12):1294-1299. Chinese SON, Chinese SS: Chinese guidelines for diagnosis and treatment of acute ischemic stroke 2023 . Chinese Journal of Neurology 2024, 57 (06):523-559. LIU R, WANG H, CHEN Y, LI Y, BAI P: CTA and CTP in evaluating collateral circulation status of acute ischemic stroke and relationship with prognosis . Chinese Journal of Practical Nervous Diseases 2024, 27 (4):442-447. Wang Y, Wang C, Liu L, Zang W, Wang K: Relationship between adipokines and short-term outcome in elderly acute ischemic stroke patients after intravascular intervention . Chin J Ceriatr Heart Brain Vessel Dis 2020, 22 (3):296-299. Goyal M, Menon BK, van Zwam WH, Dippel DWJ, Mitchell PJ, Demchuk AM, Dávalos A, Majoie CBLM, van der Lugt A, de Miquel MA et al : Endovascular thrombectomy after large-vessel ischaemic stroke: a meta-analysis of individual patient data from five randomised trials . The Lancet 2016, 387 (10029):1723-1731. Tu W, Wang L, Yan F, Peng B, Hua Y, Liu M, Ji X, Ma L, Shan C, Wang Y et al : China stroke surveillance report 2021 . MILITARY MED RES 2023, 10 (1):33. Balodis A, Kalējs VR, Migunova K: Bilateral Low-Flow Type-D Dural Carotid-Cavernous Fistula: Diagnosis and Treatment with 3D Time-of-Flight Magnetic Resonance Angiography . AM J CASE REP 2024, 25 . LI Y, SHI H, ZHANG K, WANG W, YANG S, QIAN T: Ｒ ole of 3D-Slicer in Evaluating Trigeminal Nerve Atrophy . JOURNAL OF CLINICAL RADIOLOGY 2023, 42 (3):378-383. Tao R, Song L, Tian-hao Y, Tian C: The value of color-coded multiphase CT angiography in assessing clinical outcome of acute ischemic stroke . Radiol Practice 2024, 39 (10):1311-1318. YUAN L, ZHANG JX, WANG SJ, CHEN FF, HE XH, CHEN LL: Predictive value of National Institutes of Health Stroke Scale combined with serum high ⁃ sensitivity C ⁃ reactive protein at admission to ischemic stroke . Chin J Contemp Neurol Neurosurg 2022, 22 (7). Shehjar F, Maktabi B, Rahman ZA, Bahader GA, James AW, Naqvi A, Mahajan R, Shah ZA: Stroke: Molecular mechanisms and therapies: Update on recent developments . NEUROCHEM INT 2023, 162 :105458. Westendorp WF, Dames C, Nederkoorn PJ, Meisel A: Immunodepression, Infections, and Functional Outcome in Ischemic Stroke . STROKE 2022, 53 (5):1438-1448. Bowren M, Bruss J, Manzel K, Edwards D, Liu C, Corbetta M, Tranel D, Boes AD: Post-stroke outcomes predicted from multivariate lesion-behaviour and lesion network mapping . BRAIN 2022, 145 (4):1338-1353. FANG Y, CUI B, ZHOU S: Evaluation Value of Multi-phase CTA Combined with CTP on Cerebral Blood Perfusion Status and Prognosis of Patients with Acute Ischemic Stroke . JOURNAL OF BEIHUA UNIVERSITY(Natural Science) 2022, 23 (1):84-88. Lu S, Zhang X, Xu X, Cao Y, Zhao LB, Liu Q, Wu F, Liu S, Shi H: Comparison of CT angiography collaterals for predicting target perfusion profile and clinical outcome in patients with acute ischemic stroke . EUR RADIOL 2019, 29 (9):4922-4929. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7388366","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":513544793,"identity":"362d8138-fb96-45ef-9ab5-b7e42218f61b","order_by":0,"name":"Bo Wang","email":"","orcid":"","institution":"905 Hospital of PLA Navy","correspondingAuthor":false,"prefix":"","firstName":"Bo","middleName":"","lastName":"Wang","suffix":""},{"id":513544794,"identity":"f6455714-d815-4bce-b86e-2854727c3880","order_by":1,"name":"Nan Jin","email":"","orcid":"","institution":"905 Hospital of PLA Navy","correspondingAuthor":false,"prefix":"","firstName":"Nan","middleName":"","lastName":"Jin","suffix":""},{"id":513544795,"identity":"39cc8871-9bea-4a14-97bf-8f972f6f433e","order_by":2,"name":"Tingting Wang","email":"","orcid":"","institution":"905 Hospital of PLA Navy","correspondingAuthor":false,"prefix":"","firstName":"Tingting","middleName":"","lastName":"Wang","suffix":""},{"id":513544796,"identity":"79412ac2-8af8-4bc1-bf96-2a50754b0531","order_by":3,"name":"Yanfei Zhang","email":"","orcid":"","institution":"Second Affiliated Hospital of Naval Medical University，Shanghai","correspondingAuthor":false,"prefix":"","firstName":"Yanfei","middleName":"","lastName":"Zhang","suffix":""},{"id":513544797,"identity":"7f2ae463-f41f-4ae7-adad-055a4ec324a6","order_by":4,"name":"Guorui Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYHACxgMJDDZQNhuReoBa0kjVwsBwmAQt5vxnDA48bDtvrzvtjAHDh7LDDPyzG/BrsZyRY3Agse124rbbOQaMM84dZpC4cwC/FoMbPGAtCWZALcy8bYcZDCQSCGg5fwak5Zw9WMtforQcADvsACPIYcyMxGixnJFWcCDhXDLQL2kFB3vOpfNI3CCgxZz/8MaHP8rsgA5L3vjgR5m1HP8MQg5j4DCAcw4AMQ9+9WAt7A8IKhoFo2AUjIIRDgCDD0jWp83W9gAAAABJRU5ErkJggg==","orcid":"","institution":"905 Hospital of PLA Navy","correspondingAuthor":true,"prefix":"","firstName":"Guorui","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-08-16 15:23:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7388366/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7388366/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91510538,"identity":"c98039c9-9261-4414-b3ce-c1dd754f5b05","added_by":"auto","created_at":"2025-09-17 08:44:40","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":170078,"visible":true,"origin":"","legend":"\u003cp\u003e3D-TOF MRA image showing cerebral infarction in the right middle cerebral artery territory (male, 59 years old)\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7388366/v1/b6f65616401e7bad13a77392.jpeg"},{"id":91507915,"identity":"459a9121-5364-4c64-8d7e-b6a0ecdb3cdf","added_by":"auto","created_at":"2025-09-17 08:36:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":384180,"visible":true,"origin":"","legend":"\u003cp\u003eCTA imaging of ischemic stroke with carotid web (CaW) (male, 42 years old).\u003cbr\u003e\nA: A punctate low-density shadow is seen on the posterior wall of the right internal carotid artery origin; sagittal and volume-rendered reconstructions show a punctate intraluminal filling defect protruding into the vessel lumen.B: A linear low-density shadow is observed on the posterior wall of the left internal carotid artery origin; sagittal and volume-rendered reconstructions reveal a linear intraluminal filling defect projecting into the vessel lumen.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7388366/v1/66d9d46883b97b7394a26149.png"},{"id":91507912,"identity":"af01bce7-96d9-44e6-bf5b-dc7450369acc","added_by":"auto","created_at":"2025-09-17 08:36:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":19215,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReceiver Operating Characteristic (ROC) Curves of 3D-TOF MRA and CTA Scores for Predicting Short-Term Prognosis After Interventional Therapy in Ischemic Stroke Patients With Carotid Web (CaW)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ROC curves illustrate the predictive performance of 3D time-of-flight magnetic resonance angiography (3D-TOF MRA) and computed tomography angiography (CTA) scores, as well as their combined assessment, for short-term outcomes following interventional treatment. The dashed line represents the 3D-TOF MRA score, the thin solid line represents the CTA score, and the bold solid line represents the combined assessment. The diagonal line indicates the reference line (AUC = 0.5). The area under the curve (AUC) values were 0.877 for 3D-TOF MRA, 0.892 for CTA, and 0.926 for the combined model, indicating good discriminative ability of all three approaches, with the combined model performing best.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7388366/v1/8a64c2d08fa06283b62d69b1.png"},{"id":93485538,"identity":"39f147e9-e8e3-4234-b788-633a3932ae77","added_by":"auto","created_at":"2025-10-14 11:02:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2792269,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7388366/v1/f7eaadfa-44e7-4689-9138-c835d5fc9ad7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical Utility of 3D-TOF MRA and CTA in Predicting Short-Term Prognosis After Endovascular Treatment for Carotid Web–Related Ischemic Stroke","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cstrong\u003eCarotid web (CaW)\u003c/strong\u003e is a rare structural abnormality of the carotid artery intima, characterized by a shelf-like fibrous membrane protruding into the arterial lumen, significantly altering local hemodynamics[1]. Recent studies have identified CaW as an important cause of cryptogenic ischemic stroke. In affected patients, CaW can induce local blood flow stasis and turbulence, predisposing to in situ thrombus formation at the web and subsequent distal cerebral infarction via an artery-to-artery embolic mechanism. However, its exact pathophysiological mechanisms remain incompletely understood[2].Although endovascular therapies, such as mechanical thrombectomy, are now standard treatments for ischemic stroke and have been shown to effectively recanalize occluded vessels and improve cerebral perfusion[3, 4],neurological recovery after intervention varies considerably among patients with CaW. This suggests that factors beyond successful recanalization\u0026mdash;such as collateral circulation capacity\u0026mdash;may play a critical role in clinical outcomes[5].\u003c/p\u003e\n\u003cp\u003eCurrently, digital subtraction angiography (DSA) is regarded as the gold standard for evaluating collateral circulation due to its high spatial and temporal resolution. However, its clinical utility is limited by its invasive nature, the risk of contrast-induced nephrotoxicity, and radiation exposure[6].Noninvasive imaging modalities such as three-dimensional time-of-flight magnetic resonance angiography (3D-TOF MRA) and computed tomography angiography (CTA) have been widely used in cerebrovascular assessment. Nonetheless, the sensitivity and specificity of these techniques for visualizing collateral circulation in patients with carotid web (CaW) remain a subject of debate. For example, 3D-TOF MRA can clearly visualize the circle of Willis without the need for contrast agents, but it has limited capability in detecting slow-flow collaterals[7].In contrast, CTA enables rapid assessment of vascular occlusion severity but lacks the ability to quantify microcirculatory perfusion[8].The combination of 3D-TOF MRA and CTA offers complementary advantages, providing a more comprehensive evaluation of cerebral vasculature. This combined approach enhances the accuracy of assessing CaW-related occlusions and stenoses, and improves collateral circulation assessment by integrating information across multiple angles and time points. Such multimodal imaging can compensate for the limitations of single-modality techniques in identifying slow flow, visualizing small-caliber vessels, and evaluating hemodynamic status, thereby offering more reliable imaging evidence to support clinical decision-making[9, 10].\u003c/p\u003e\n\u003cp\u003eMoreover, most existing studies have focused on the association between a single imaging modality and stroke prognosis, while systematic investigations on the combined application of 3D-TOF MRA and CTA in the evaluation of CaW-related stroke remain lacking\u0026nbsp;[11].To address this gap, the present study aimed to explore the relationship between combined imaging features from 3D-TOF MRA and CTA and short-term functional outcomes after endovascular treatment in patients with ischemic stroke associated with CaW.By retrospectively analyzing imaging data from patients who underwent endovascular therapy, we compared imaging parameters across different prognostic groups and assessed their predictive value.This study seeks to establish a prognosis prediction model based on multimodal imaging, providing a reference for individualized clinical management and offering new insights into the underlying mechanisms of CaW-related ischemic stroke.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy population\u003c/p\u003e\u003cp\u003eFrom January 2023 to March 2025, a total of 98 patients with ischemic stroke and confirmed carotid web (CaW) who underwent endovascular treatment at No. 905 Hospital of PLA Navy (China) were consecutively enrolled.Inclusion criteria were as follows: (1) diagnosis of ischemic stroke according to established criteria[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], with imaging confirmation of CaW; (2) age between 18 and 80 years; (3) symptom onset to hospital presentation within 48 hours; (4) first-ever ischemic stroke; (5) provision of written informed consent.\u003c/p\u003e\u003cp\u003eExclusion criteria included: (1) preexisting neurological deficits; (2) coagulopathy or abnormal coagulation profile; (3) ischemic stroke secondary to hematologic disorders, cardioembolic sources, or granulomatous diseases; (4) severe dysfunction of vital organs (heart, lungs, liver, kidneys); (5) presence of malignancy; (6) impaired consciousness or psychiatric disorders interfering with cooperation.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMeasurement\u003c/b\u003es\u003c/p\u003e\u003cp\u003e\u003cb\u003eParticipant Characteristics\u003c/b\u003e:Demographic and clinical data were collected, including sex, age, body mass index (BMI), smoking history, alcohol consumption, hypertension, diabetes mellitus, coronary artery disease, hyperlipidemia, stroke severity, intravenous thrombolysis, ICU admission, infarct volume, arterial occlusion site, lesion location, Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification, neutrophil count, platelet count, and serum creatinine levels. All data were obtained from the hospital\u0026rsquo;s electronic medical record system..\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e3D-TOF MRA Assessment\u003c/strong\u003e\u003cp\u003eAll patients underwent magnetic resonance imaging using a 3.0 Tesla MRI scanner (Siemens, Germany), including routine T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI) in axial planes. The acquired 3D-TOF MRA raw images were transferred to a dedicated 3D post-processing software for image reconstruction and analysis. Visualization and interpretation were performed using volume rendering (VR), multiplanar reconstruction (MPR), and maximum intensity projection (MIP) techniques (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCTA Assessment\u003c/strong\u003e\u003cp\u003eMultiphase CTA imaging was performed using a multi-detector CT scanner (GE, USA). Nonionic iodinated contrast agent (iopamidol) was injected via the median cubital vein using a dual-barrel high-pressure injector at a rate of 5 mL/s, with a total volume of approximately 70\u0026ndash;80 mL. An automatic bolus-tracking technique was employed, with the trigger threshold set at 120 Hounsfield units (HU) in the aortic arch. The arterial phase scan was initiated immediately upon reaching the threshold, followed by venous and delayed phase scans at fixed time delays (e.g., 5 seconds and 10 seconds), completing a three-phase imaging protocol. All imaging data were transferred to a workstation for post-processing using volume rendering (VR), maximum intensity projection (MIP), and multiplanar reconstruction (MPR) techniques. These images were used to evaluate the degree of vascular occlusion and the dynamic perfusion status of collateral circulation (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eImaging Feature Scoring\u003c/b\u003e: Both raw and reconstructed images were independently reviewed by two experienced radiologists. In cases of disagreement, the two reviewers discussed the findings and reached a consensus. A 5-point collateral circulation grading system was used, defined as follows:0 points: 0 points(No collateral perfusion) ;1 point(Persistent perfusion defect);2 points(Partial perfusion defect);3 points:(Slow collateral flow to the ischemic area);4 points(Rapid collateral flow to the ischemic area)[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].Both 3D-TOF MRA and multiphase CTA findings were scored accordingly. For CTA, collateral grading was performed separately for each imaging phase, and the highest score among the three phases was recorded as the final collateral score.The diagnosis of carotid web was primarily based on CTA imaging. Diagnostic criteria included a thin, shelf-like intraluminal filling defect located on the posterior or posterolateral wall of the carotid bulb, without evidence of calcified plaques or atherosclerotic stenosis. In selected cases, MRA findings were used to support the diagnosis.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eOutcome Assessment\u003c/strong\u003e\u003cp\u003ePatients were followed up for 3 months via outpatient visits. All 157 patients completed follow-up. Functional outcomes were assessed using the modified Rankin Scale (mRS) \u003csup\u003e[9]\u003c/sup\u003e, which scores disability severity from 0 to 5. A score of \u0026gt;\u0026thinsp;2 or death was defined as a poor outcome, whereas a score of \u0026le;\u0026thinsp;2 was considered a favorable outcome [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Based on these criteria, patients were divided into a favorable outcome group (n\u0026thinsp;=\u0026thinsp;102) and a poor outcome group (n\u0026thinsp;=\u0026thinsp;55).\u003c/p\u003e\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eAll statistical analyses were performed using SPSS version 26.0 (IBM, Armonk, NY, USA). Continuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (x̄ \u0026plusmn; s), and categorical variables were presented as counts and percentages (%). Comparisons between groups were conducted using the \u003cem\u003et\u003c/em\u003e-test for continuous variables and the chi-square test for categorical variables. Multivariate logistic regression analysis was performed to identify factors independently associated with short-term outcomes. The predictive value of the scoring methods was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). A two-sided \u003cem\u003eP\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, significant differences were observed between the poor outcome group and the good outcome group in terms of age, presence of hypertension, presence of hyperlipidemia, stroke severity, ICU admission, infarct volume, proportion of large-artery atherosclerosis, 3D-TOF MRA scores, and CTA scores (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\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\u003eComparison of Short-Term Prognosis After Interventional Therapy in Ischemic Stroke Patients with Carotid Web (CaW)\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=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePoor Prognosis Group (n\u0026thinsp;=\u0026thinsp;55)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGood Prognosis Group (n\u0026thinsp;=\u0026thinsp;102)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eχ\u0026sup2;/t\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.499\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.480\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35(63.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e59(57.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20(36.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43(42.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e68.98\u0026thinsp;\u0026plusmn;\u0026thinsp;12.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e61.44\u0026thinsp;\u0026plusmn;\u0026thinsp;12.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.419\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBMI (kg/m\u0026sup2;)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e23.44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23.06\u0026thinsp;\u0026plusmn;\u0026thinsp;2.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.726\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.470\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSmoking history\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.310\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.578\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3 (15.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16 (20.51%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17 (85.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e62 (79.49%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAlcohol consumption history\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.975\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2 (10.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8 (10.26%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18 (90.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e70 (89.74%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHypertension\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.045\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14 (70.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e35 (44.87%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6 (30.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43 (55.13%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDiabetes\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.312\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.576\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8 (40.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26 (33.33%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12 (60.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e52 (66.67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCoronary heart disease\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.307\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8 (40.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22 (28.21%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12 (60.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e56 (71.79%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHyperlipidemia\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.071\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.044\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11 (55.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25 (32.05%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9 (45.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e53 (67.95%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSeverity of illness\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.235\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMild\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2 (10.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e31 (39.74%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5 (25.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23 (29.49%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSevere\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13 (65.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24 (30.77%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIV thrombolysis\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.095\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.758\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10 (50.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e36 (46.15%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10 (50.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e42 (53.85%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eICU admission\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13 (65.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29 (37.18%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7 (35.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e49 (62.82%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCerebral infarct area (mm\u0026sup2;)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e59.46\u0026thinsp;\u0026plusmn;\u0026thinsp;8.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45.29\u0026thinsp;\u0026plusmn;\u0026thinsp;6.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.877\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eArterial occlusion site\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.788\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.594\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInternal carotid artery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5 (25.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25 (32.05%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM1 segment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7 (35.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33 (42.31%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eICA and M1 segment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6 (30.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12 (15.38%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBasilar artery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1 (5.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6 (7.69%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVertebral artery (V4 segment)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1 (5.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2 (2.56%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLesion location\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.359\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.549\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnterior circulation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17 (85.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e70 (89.74%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePosterior circulation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3 (15.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8 (10.26%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTOAST classification\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.054\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.048\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLarge artery atherosclerosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6 (30.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e40 (51.28%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCardioembolism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7 (35.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e28 (35.90%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7 (35.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10 (12.82%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNeutrophil count (\u0026times;10⁹/L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7.23\u0026thinsp;\u0026plusmn;\u0026thinsp;2.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.233\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.221\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePlatelet count (\u0026times;10⁹/L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e241.25\u0026thinsp;\u0026plusmn;\u0026thinsp;23.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e235.58\u0026thinsp;\u0026plusmn;\u0026thinsp;26.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.880\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.381\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSerum creatinine (\u0026micro;mol/L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e80.27\u0026thinsp;\u0026plusmn;\u0026thinsp;12.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e82.10\u0026thinsp;\u0026plusmn;\u0026thinsp;13.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.558\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.578\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e3D-TOF MRA score\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.707\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCTA score\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.418\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAs presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, multivariate analysis identified age, presence of hypertension, hyperlipidemia, stroke severity, infarct volume, 3D-TOF MRA score, and CTA score as independent predictors of short-term functional outcome after endovascular treatment in patients with ischemic stroke associated with CaW (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\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\u003eMultivariate Logistic Regression Analysis of Factors Influencing Short-Term Prognosis After Interventional Therapy in Ischemic Stroke Patients with Carotid Web (CaW)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" 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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWald\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eOR Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e95% Confidence Interval\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.321\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.196\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.021\u0026ndash;3.594\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension (No\u0026thinsp;=\u0026thinsp;1, Yes\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.797\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.397\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.451\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.207\u0026ndash;0.981\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHyperlipidemia (No\u0026thinsp;=\u0026thinsp;1, Yes\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.333\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.229\u0026ndash;0.846\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSeverity of illness (Mild\u0026thinsp;=\u0026thinsp;1, Moderate\u0026thinsp;=\u0026thinsp;2, Severe\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.996\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.445\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.369\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.154\u0026ndash;0.884\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCerebral infarct area\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.194\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11.302\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e55.368\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.332\u0026ndash;574.923\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3D-TOF MRA score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-2.793\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.444\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.061\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.006\u0026ndash;0.640\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCTA score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-4.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.245\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.687\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.001\u0026ndash;0.196\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-7.419\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.232\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e36.263\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eReceiver operating characteristic (ROC) curve analysis demonstrated that 3D-TOF MRA score, CTA score, and the combined imaging assessment all had good predictive value for short-term outcomes in patients with CaW-related ischemic stroke following endovascular treatment. The area under the curve (AUC) values were 0.877, 0.892, and 0.926, respectively (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).See Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e for details.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eROC Curve Results for 3D-TOF MRA and CTA Scores in Predicting Short-Term Prognosis After Interventional Therapy in Ischemic Stroke Patients with Carotid Web (CaW)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" 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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAUC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSensitivity\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSpecificity\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eOptimal Cut-off\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3D-TOF MRA Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.877\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.805\u0026ndash;0.948\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.885\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.750\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.830\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCTA Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.892\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.821\u0026ndash;0.963\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.885\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.750\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.995\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCombined Assessment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.867\u0026ndash;0.986\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.897\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.800\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe ROC curves illustrate the predictive performance of 3D time-of-flight magnetic resonance angiography (3D-TOF MRA) and computed tomography angiography (CTA) scores, as well as their combined assessment, for short-term outcomes following interventional treatment. The dashed line represents the 3D-TOF MRA score, the thin solid line represents the CTA score, and the bold solid line represents the combined assessment. The diagonal line indicates the reference line (AUC\u0026thinsp;=\u0026thinsp;0.5). The area under the curve (AUC) values were 0.877 for 3D-TOF MRA, 0.892 for CTA, and 0.926 for the combined model, indicating good discriminative ability of all three approaches, with the combined model performing best.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study investigated the factors influencing short-term functional outcomes following endovascular treatment in patients with ischemic stroke associated with carotid web (CaW). The findings indicate that advanced age, comorbid hypertension and hyperlipidemia, moderate-to-severe stroke severity, and larger infarct volume were independent risk factors for poor prognosis. These observations are consistent with previous reports. With advancing age, vascular elasticity declines, intimal thickening and lipid deposition increase, all of which exacerbate vascular stenosis and atherosclerosis, thereby elevating the risk of stroke onset and recurrence[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].Hypertension and hyperlipidemia are well-established risk factors for cerebrovascular disease and often act synergistically to trigger or exacerbate vascular wall injury and hemodynamic disturbances, which may compromise reperfusion efficacy and hinder functional recovery[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].Additionally, a larger infarct area implies more extensive brain tissue damage, which naturally correlates with poorer outcomes. Therefore, in patients with these risk factors, postoperative management should emphasize blood pressure and lipid control, as well as appropriate use of antiplatelet and lipid-lowering therapies, to facilitate better long-term recovery.\u003c/p\u003e\u003cp\u003eThis study also evaluated the prognostic value of 3D-TOF MRA and CTA imaging in the early postoperative period. Results demonstrated that both 3D-TOF MRA and CTA scores were significantly lower in the poor outcome group than in the favorable outcome group, and both were identified as independent predictors of short-term prognosis. 3D-TOF MRA, a noninvasive vascular imaging technique based on the principle of \"flow-related enhancement,\" effectively captures high-velocity blood flow signals and is suitable for assessing perfusion in larger vessels. However, its sensitivity for detecting small-caliber or slow-flow collateral vessels is limited[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].CTA, through intravenous contrast administration and rapid multi-planar image acquisition, offers superior spatial resolution and a more comprehensive assessment of collateral circulation, making it particularly suitable for acute stroke evaluation[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].Both imaging scores reflect the extent of postoperative flow restoration and collateral perfusion, suggesting that higher scores are associated with better cerebral perfusion and improved neurological recovery.\u003c/p\u003e\u003cp\u003eCurrently, a wide range of methods are available for predicting prognosis in ischemic stroke, including clinical scoring systems (e.g., NIHSS, mRS), laboratory markers (e.g., inflammatory cytokines, D-dimer), neurophysiological techniques (e.g., electroencephalography), and imaging-based assessments. However, scales such as the NIHSS may have limited prognostic value in certain subtypes of ischemic stroke, such as small artery occlusion (SAO) or strokes involving penetrating artery lesions[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].In terms of imaging, beyond 3D-TOF MRA and CTA, modalities such as CT perfusion (CTP), diffusion-weighted imaging (DWI), and perfusion-weighted imaging (PWI) are also widely used to evaluate ischemic penumbra and collateral circulation, offering guidance for predicting outcomes after reperfusion therapy[\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].Nevertheless, CTP requires more advanced equipment and technical expertise and carries a higher risk of radiation exposure. While DWI and PWI have clear advantages in localizing ischemic lesions, they remain limited in assessing hemodynamic changes and collateral compensation.In this study, ROC curve analysis demonstrated that both 3D-TOF MRA and CTA scores showed strong discriminatory ability in predicting short-term outcomes following endovascular treatment in patients with CaW-related ischemic stroke. Their combined use further improved predictive accuracy, with an AUC of 0.926\u0026mdash;higher than values reported in previous studies using combined CTA and CTP assessments[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].These findings suggest that multimodal imaging provides superior clinical utility and sensitivity, and can serve as a valuable tool for postoperative prognostication.Moreover, 3D-TOF MRA and CTA offer advantages such as short acquisition times, stable data acquisition, and relatively intuitive interpretation. These features are particularly beneficial in patients with significant anatomical variations such as CaW, where the two modalities can clearly depict alterations in local blood flow pathways and assess the establishment of intracranial collateral circulation. This provides direct guidance in determining whether effective compensatory blood flow channels have been formed after intervention.\u003c/p\u003e\u003cp\u003eTherefore, this study supports the integration of combined 3D-TOF MRA and CTA into the postoperative follow-up protocol for patients with CaW-related stroke. As a repeatable, noninvasive imaging strategy with high clinical value, this approach may provide a reliable basis for developing precise, individualized rehabilitation and secondary prevention plans following endovascular treatment.\u003c/p\u003e\u003cp\u003eHowever, several limitations should be acknowledged. This was a single-center study with a relatively small sample size, which may limit the generalizability of the findings. Future studies with larger, multicenter cohorts are needed to validate and strengthen the conclusions.\u003c/p\u003e\u003cp\u003eIn addition, the diagnosis of carotid web in this study was based solely on imaging features without histopathological confirmation. Although previous studies have demonstrated a high concordance between imaging findings and pathological results, the absence of tissue validation introduces a degree of diagnostic uncertainty. Future research should incorporate pathological evidence to further verify the imaging-based diagnostic criteria for carotid web.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was submitted to, and approved by the Ethics Committee of No. 905 Hospital of PLA Navy（No. 2023LW07）.All methods were performed in accordance with the Declaration of Helsinki.Informed consent to participate was obtained from all of the participants in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll relevant data are presented in the text and the tables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere was no source of funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGL and YZ conceived and designed the study. BW and NJ wrote the paper. TW contributed to data collection. BW ,NJ and TW contributed equal to this paper .All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePatel SD, Otite FO, Topiwala K, Saber H, Kaneko N, Sussman E, Mehta TV, Tummala R, Hinman J, Nogueira R\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eInterventional compared with medical management of symptomatic carotid web: A systematic review\u003c/strong\u003e. \u003cem\u003eJournal of Stroke and Cerebrovascular Diseases\u003c/em\u003e 2022, \u003cstrong\u003e31\u003c/strong\u003e(10):106682.\u003c/li\u003e\n\u003cli\u003eZhang AJ, Dhruv P, Choi P, Bakker C, Koffel J, Anderson D, Kim J, Jagadeesan B, Menon BK, Streib C: \u003cstrong\u003eA Systematic Literature Review of Patients With Carotid Web and Acute Ischemic Stroke\u003c/strong\u003e. \u003cem\u003eSTROKE\u003c/em\u003e 2018, \u003cstrong\u003e49\u003c/strong\u003e(12):2872-2876.\u003c/li\u003e\n\u003cli\u003eBoujan T, Neuberger U, Pfaff J, Nagel S, Herweh C, Bendszus M, M\u0026ouml;hlenbruch MA: \u003cstrong\u003eValue of Contrast-Enhanced MRA versus Time-of-Flight MRA in Acute Ischemic Stroke MRI\u003c/strong\u003e. \u003cem\u003eAM J NEURORADIOL\u003c/em\u003e 2018, \u003cstrong\u003e39\u003c/strong\u003e(9):1710-1716.\u003c/li\u003e\n\u003cli\u003eCampbell D, Butler E, Campbell RB, Ho J, Barber PA: \u003cstrong\u003eGeneral Anesthesia Compared With Non-GA in Endovascular Thrombectomy for Ischemic Stroke\u003c/strong\u003e. \u003cem\u003eNEUROLOGY\u003c/em\u003e 2023, \u003cstrong\u003e100\u003c/strong\u003e(16).\u003c/li\u003e\n\u003cli\u003eBusto G, Casetta I, Morotti A, Barra A, Maccaglia MG, Bianchi A, Moretti M, Capasso F, Toffali M, Arba F: \u003cstrong\u003eMulti-phase CT-Angiography outperforms angiographic careggi collateral score and predicts functional outcome in acute ischemic stroke\u003c/strong\u003e. \u003cem\u003eNEUROL SCI\u003c/em\u003e 2025, \u003cstrong\u003e46\u003c/strong\u003e(1):249-256.\u003c/li\u003e\n\u003cli\u003eChiara C, Umberto S, Daniele M, Valentina C, Nicola C, Valeria L, Giuseppina S, Andrea S, Pietro F, Ivan G: \u003cstrong\u003eCorrection to: Association of the Careggi Collateral Score with 3-month modified Rankin Scale score after thrombectomy for stroke with occlusion of the middle cerebral artery\u003c/strong\u003e. \u003cem\u003eJ NEUROL\u003c/em\u003e 2022(269-2).\u003c/li\u003e\n\u003cli\u003eShi Z, Zhao X, Zhu S, Miao X, Zhang Y, Han S, Wang B, Zhang B, Ye X, Dai Y\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eTime-of-Flight Intracranial MRA at 3 T versus 5 T versus 7 T: Visualization of Distal Small Cerebral Arteries\u003c/strong\u003e. \u003cem\u003eRADIOLOGY\u003c/em\u003e 2023, \u003cstrong\u003e306\u003c/strong\u003e(1):207-217.\u003c/li\u003e\n\u003cli\u003eMair G, White P, Bath PM, Muir K, Martin C, Dye D, Chappell F, Kummer R, Macleod M, Sprigg N\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eAccuracy of artificial intelligence software for CT angiography in stroke\u003c/strong\u003e. \u003cem\u003eANN CLIN TRANSL NEUR\u003c/em\u003e 2023, \u003cstrong\u003e10\u003c/strong\u003e(7):1072-1082.\u003c/li\u003e\n\u003cli\u003eWang T, Li C, Li S, Tang P, Guo Q, Fang L: \u003cstrong\u003eHigh-resolution magnetic resonance imaging features of time-of-flight magnetic resonance angiography signal loss and its relevance to ischemic stroke\u003c/strong\u003e. \u003cem\u003eQUANT IMAG MED SURG\u003c/em\u003e 2024, \u003cstrong\u003e14\u003c/strong\u003e(9):6820-6829.\u003c/li\u003e\n\u003cli\u003eRegenhardt RW, Gonz\u0026aacute;lez RG, He J, Lev MH, Singhal AB: \u003cstrong\u003eSymmetric CTA Collaterals Identify Patients with Slow-progressing Stroke Likely to Benefit from Late Thrombectomy\u003c/strong\u003e. \u003cem\u003eRADIOLOGY\u003c/em\u003e 2022, \u003cstrong\u003e302\u003c/strong\u003e(2):400-407.\u003c/li\u003e\n\u003cli\u003eChen H, Colasurdo M, Costa M, Nossek E, Kan P: \u003cstrong\u003eCarotid webs: a review of pathophysiology, diagnostic findings, and treatment options\u003c/strong\u003e. \u003cem\u003eJ NEUROINTERV SURG\u003c/em\u003e 2024, \u003cstrong\u003e16\u003c/strong\u003e(12):1294-1299.\u003c/li\u003e\n\u003cli\u003eChinese SON, Chinese SS: \u003cstrong\u003eChinese guidelines for diagnosis and treatment of acute ischemic stroke 2023\u003c/strong\u003e. \u003cem\u003eChinese Journal of Neurology\u003c/em\u003e 2024, \u003cstrong\u003e57\u003c/strong\u003e(06):523-559.\u003c/li\u003e\n\u003cli\u003eLIU R, WANG H, CHEN Y, LI Y, BAI P: \u003cstrong\u003eCTA and CTP in evaluating collateral circulation status of acute ischemic stroke and \u003cstrong\u003erelationship with prognosis\u003c/strong\u003e\u003c/strong\u003e. \u003cem\u003eChinese Journal of Practical Nervous Diseases\u003c/em\u003e 2024, \u003cstrong\u003e27\u003c/strong\u003e(4):442-447.\u003c/li\u003e\n\u003cli\u003eWang Y, Wang C, Liu L, Zang W, Wang K: \u003cstrong\u003eRelationship between adipokines and short-term outcome in elderly acute ischemic stroke patients after intravascular intervention\u003c/strong\u003e. \u003cem\u003eChin J Ceriatr Heart Brain Vessel Dis\u003c/em\u003e 2020, \u003cstrong\u003e22\u003c/strong\u003e(3):296-299.\u003c/li\u003e\n\u003cli\u003eGoyal M, Menon BK, van Zwam WH, Dippel DWJ, Mitchell PJ, Demchuk AM, D\u0026aacute;valos A, Majoie CBLM, van der Lugt A, de Miquel MA\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eEndovascular thrombectomy after large-vessel ischaemic stroke: a meta-analysis of individual patient data from five randomised trials\u003c/strong\u003e. \u003cem\u003eThe Lancet\u003c/em\u003e 2016, \u003cstrong\u003e387\u003c/strong\u003e(10029):1723-1731.\u003c/li\u003e\n\u003cli\u003eTu W, Wang L, Yan F, Peng B, Hua Y, Liu M, Ji X, Ma L, Shan C, Wang Y\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eChina stroke surveillance report 2021\u003c/strong\u003e. \u003cem\u003eMILITARY MED RES\u003c/em\u003e 2023, \u003cstrong\u003e10\u003c/strong\u003e(1):33.\u003c/li\u003e\n\u003cli\u003eBalodis A, Kalējs VR, Migunova K: \u003cstrong\u003eBilateral Low-Flow Type-D Dural Carotid-Cavernous Fistula: Diagnosis and Treatment with 3D Time-of-Flight Magnetic Resonance Angiography\u003c/strong\u003e. \u003cem\u003eAM J CASE REP\u003c/em\u003e 2024, \u003cstrong\u003e25\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eLI Y, SHI H, ZHANG K, WANG W, YANG S, QIAN T: \u003cstrong\u003eＲ\u003c/strong\u003e\u003cstrong\u003eole of 3D-Slicer in Evaluating Trigeminal Nerve Atrophy\u003c/strong\u003e. \u003cem\u003eJOURNAL OF CLINICAL RADIOLOGY\u003c/em\u003e 2023, \u003cstrong\u003e42\u003c/strong\u003e(3):378-383.\u003c/li\u003e\n\u003cli\u003eTao R, Song L, Tian-hao Y, Tian C: \u003cstrong\u003eThe value of color-coded multiphase CT angiography in assessing clinical outcome of acute ischemic stroke\u003c/strong\u003e. \u003cem\u003eRadiol Practice\u003c/em\u003e 2024, \u003cstrong\u003e39\u003c/strong\u003e(10):1311-1318.\u003c/li\u003e\n\u003cli\u003eYUAN L, ZHANG JX, WANG SJ, CHEN FF, HE XH, CHEN LL: \u003cstrong\u003ePredictive value of National Institutes of Health Stroke Scale combined with serum \u003c/strong\u003e\u003cstrong\u003ehigh\u003c/strong\u003e\u003cstrong\u003e⁃\u003c/strong\u003e\u003cstrong\u003esensitivity C\u003c/strong\u003e\u003cstrong\u003e⁃\u003c/strong\u003e\u003cstrong\u003ereactive protein at admission to ischemic stroke\u003c/strong\u003e. \u003cem\u003eChin J Contemp Neurol Neurosurg\u003c/em\u003e 2022, \u003cstrong\u003e22\u003c/strong\u003e(7).\u003c/li\u003e\n\u003cli\u003eShehjar F, Maktabi B, Rahman ZA, Bahader GA, James AW, Naqvi A, Mahajan R, Shah ZA: \u003cstrong\u003eStroke: Molecular mechanisms and therapies: Update on recent developments\u003c/strong\u003e. \u003cem\u003eNEUROCHEM INT\u003c/em\u003e 2023, \u003cstrong\u003e162\u003c/strong\u003e:105458.\u003c/li\u003e\n\u003cli\u003eWestendorp WF, Dames C, Nederkoorn PJ, Meisel A: \u003cstrong\u003eImmunodepression, Infections, and Functional Outcome in Ischemic Stroke\u003c/strong\u003e. \u003cem\u003eSTROKE\u003c/em\u003e 2022, \u003cstrong\u003e53\u003c/strong\u003e(5):1438-1448.\u003c/li\u003e\n\u003cli\u003eBowren M, Bruss J, Manzel K, Edwards D, Liu C, Corbetta M, Tranel D, Boes AD: \u003cstrong\u003ePost-stroke outcomes predicted from multivariate lesion-behaviour and lesion network mapping\u003c/strong\u003e. \u003cem\u003eBRAIN\u003c/em\u003e 2022, \u003cstrong\u003e145\u003c/strong\u003e(4):1338-1353.\u003c/li\u003e\n\u003cli\u003eFANG Y, CUI B, ZHOU S: \u003cstrong\u003eEvaluation Value of Multi-phase CTA Combined with CTP on Cerebral Blood Perfusion Status and Prognosis of Patients with Acute Ischemic Stroke\u003c/strong\u003e. \u003cem\u003eJOURNAL OF BEIHUA UNIVERSITY(Natural Science)\u003c/em\u003e 2022, \u003cstrong\u003e23\u003c/strong\u003e(1):84-88.\u003c/li\u003e\n\u003cli\u003eLu S, Zhang X, Xu X, Cao Y, Zhao LB, Liu Q, Wu F, Liu S, Shi H: \u003cstrong\u003eComparison of CT angiography collaterals for predicting target perfusion profile and clinical outcome in patients with acute ischemic stroke\u003c/strong\u003e. \u003cem\u003eEUR RADIOL\u003c/em\u003e 2019, \u003cstrong\u003e29\u003c/strong\u003e(9):4922-4929.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"3D time-of-flight magnetic resonance angiography, computed tomography angiography, carotid web, ischemic stroke, short-term prognosis","lastPublishedDoi":"10.21203/rs.3.rs-7388366/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7388366/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eTo investigate the relationship between imaging characteristics derived from three-dimensional time-of-flight magnetic resonance angiography (3D-TOF MRA) and multiphase computed tomography angiography (CTA), and short-term outcomes following endovascular treatment in patients with ischemic stroke associated with carotid web (CaW).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis retrospective study analyzed clinical and imaging data of 157 ischemic stroke patients with confirmed CaW who underwent endovascular treatment. Based on the modified Rankin Scale (mRS) score at 3-month follow-up, patients were divided into a good outcome group (n\u0026thinsp;=\u0026thinsp;78) and a poor outcome group (n\u0026thinsp;=\u0026thinsp;20). Clinical and imaging parameters were compared between the two groups. Multivariate logistic regression analysis was performed to identify independent predictors of poor short-term outcomes. Receiver operating characteristic (ROC) curves were constructed to evaluate the predictive value of 3D-TOF MRA and CTA scores.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eMultivariate logistic regression identified age, hypertension, hyperlipidemia, stroke severity, ICU admission, infarct size, 3D-TOF MRA score, and CTA score as independent predictors of poor short-term outcome (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). ROC analysis demonstrated good predictive performance, with areas under the curve (AUC) of 0.877 for the 3D-TOF MRA score, 0.892 for the CTA score, and 0.926 for the combined model.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eImaging characteristics from 3D-TOF MRA and CTA are valuable predictors of short-term outcomes after endovascular treatment in ischemic stroke patients with CaW, and may serve as important references for clinical decision-making.\u003c/p\u003e","manuscriptTitle":"Clinical Utility of 3D-TOF MRA and CTA in Predicting Short-Term Prognosis After Endovascular Treatment for Carotid Web–Related Ischemic Stroke","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-17 08:36:35","doi":"10.21203/rs.3.rs-7388366/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8e4b4897-ae33-4dd1-a03a-cb6e303031c5","owner":[],"postedDate":"September 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-14T10:53:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-17 08:36:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7388366","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7388366","identity":"rs-7388366","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}