BACKGROUND:Flow diversion has revolutionized the management of intracranial aneurysms. This study aimed to evaluate the preliminary safety and efficacy profile of the novel Lattice flow diverter (LFD) in clinical applications. METHODS:We retrospectively analyzed consecutive patients with intracranial aneurysms who were treated with the LFD between June 2023 and May 2024. Based on the medical records and imaging data, we collected demographic characteristics, aneurysm features, procedural details, perioperative complications, clinical outcomes, and imaging results. RESULTS:This study comprised 105 patients (mean age, 55.4±9.04 years; 72.4% female) with 117 aneurysms, including 104 (88.9%) anterior circulation aneurysms. Procedural success was achieved in all patients (109 devices deployed). Adjunctive techniques included coiling in 39 aneurysms (33.3%) and balloon-assisted wall apposition in three cases (2.6%). The overall perioperative complication rate was 5.8%, with neurological complications (all ischemic events) occurring in 2.9% of cases. Clinical follow-up (mean 10.0±1.4 months) demonstrated preserved functional independence (modified Rankin Scale (mRS) score 0-2) in 98.0% of patients. Imaging follow-up (mean 6.6±1.6 months) revealed complete occlusion in 71.9% of aneurysms and adequate occlusion (Raymond-Roy class I/II) in 88.6%. CONCLUSION:The LFD demonstrated favorable safety and efficacy characteristics for intracranial aneurysm treatment during short-term follow-up. Long-term outcomes require validation in multicenter prospective cohort studies.

BACKGROUND AND PURPOSE:The Pipeline Embolization Device (PED) revolutionized endovascular treatment of intracranial aneurysms (IAs), especially complex wide-neck lesions, but incomplete occlusion remains common. This study aimed to develop an ensemble model integrating clinical, morphological, and hemodynamic features for predicting post-PED occlusion outcomes. MATERIALS AND METHODS:This retrospective study included 306 patients with IAs treated with PED from January 2016 to June 2023. Clinical, morphological, and hemodynamic features were extracted from clinical records, three-dimensional rotational angiography, and digital subtraction angiography (DSA) to develop a weighted soft-voting ensemble model for predicting aneurysm occlusion at ≥6-month follow-up. The final prediction was generated by combining the weighted predicted probabilities from five individual algorithms rather than by a simple majority vote. Performance used area under the receiver operating characteristic curve (AUC) and confusion-matrix metrics; feature importance used SHapley Additive exPlanations (SHAP). RESULTS:Among 306 patients (mean age 52.9±10.9 years; 192 women), pre- and post-PED hemodynamic features were extracted; 31 features (13 clinical/morphological, 18 post-PED hemodynamic-9 each from aneurysm and parent-artery regions of interest) were modeled. Complete occlusion was observed in 202/243 aneurysms (83.1%) in the internal dataset and 49/63 (77.8%) in the external test set. In the external test set, the ensemble achieved an AUC of 0.902 (95% CI, 0.82-0.98), an accuracy of 88.9% (95% CI, 78.5-95.2%), a sensitivity of 93.9% (95% CI, 82.8-98.7%), and a specificity of 71.4% (95% CI, 45.0-88.3%). Independent predictors of incomplete occlusion were branch involvement, daughter sacs, and older age. Post-PED changes (time-to-peak, mean-transit-time, cerebral-blood-volume) correlated with outcomes; complete occlusion associated with higher aneurysmal maximum intensity projection and parent-artery cerebral blood flow. CONCLUSIONS:DSA-derived quantitative hemodynamic and morphological features are valuable biomarkers for PED efficacy. The ensemble showed robust performance (AUC 0.902; 95% CI 0.82-0.98) and may aid risk stratification and personalized IA treatment planning.

Hemodynamic status concerning restenosis of chronic internal carotid artery occlusion (CICAO) after successful endovascular recanalization are scarce. This study is aim to identify post-procedural hemodynamics that may be associated with restenosis. This study retrospectively enrolled 202 patients who successfully underwent endovascular recanalization for CICAO. Quantitative digital subtraction angiography (QDSA) was employed to assess immediate post-procedural hemodynamic parameters of the internal carotid artery. A hierarchical modeling strategy was implemented to construct predictive models and determine the incremental predictive value of hemodynamic parameters. Internal validation of the models was performed using bootstrap resampling with 1000 repetitions. 48 patients (23.8

RATIONALE AND OBJECTIVES:To evaluate the predictive value of combined computed tomography perfusion (CTP) and quantitative digital subtraction angiography (QDSA) for cerebral hyperperfusion syndrome (CHS) after surgical revascularization in moyamoya disease (MMD). METHODS:This retrospective study included 340 patients (396 hemispheres) with MMD who underwent direct or combined bypass surgery. Preoperative CTP and QDSA assessments were performed to assess cerebral perfusion and analyze hemodynamic parameters. Logistic regression with generalized estimating equations (GEE), accounting for within-patient clustering, and receiver operating characteristic (ROC) analyses were used to identify risk factors and evaluate predictive performance. RESULTS:Postoperative CHS occurred in 29.04% (115/396) of hemispheres. Independent risk factors included CTP stages 3-4 (OR 7.40, 95% CI 4.27-12.84, p<0.001), shortened TTP of superficial temporal artery (OR 0.66, 95% CI 0.55-0.79, p<0.001), older age (OR 1.03, 95% CI 1.00-1.06, p=0.030), and hypertension (OR 4.74, 95% CI 2.74-8.19, p<0.001). The multivariate integrated model demonstrated good predictive performance (AUC 0.815, 95% CI 0.771-0.858). CONCLUSION:Combined CTP and QDSA assessment effectively predicts CHS risk after MMD revascularization, with CTP stages 3-4, shortened TTP of STA, older age, and hypertension as independent risk factors. This dual-modality approach aids in preoperative risk stratification and surgical planning.

Introduction: Venous thromboembolism (VTE) is an important complication after spontaneous intracerebral hemorrhage (ICH). However, it remains a clinical challenge to identify individuals at high risk for VTE in a population with ICH. This study aimed to develop a model integrating cardiac biomarkers with clinical-radiological factors for predicting VTE risk in patients with spontaneous ICH. Methods: ICH patients were retrospectively enrolled between October 2019 and December 2022. Baseline clinical characteristics, laboratory data, and radiological features were collected. Patients with pulmonary embolism (PE) and deep vein thrombosis were classified into the VTE group. Cox regression analysis was used to identify independent predictors of in-hospital VTE. A nomogram was developed based on the multivariate model, and its performance was evaluated using the concordance index (C-index), decision curve analysis, and net reclassification improvement. Results: A total of 170 patients (mean age: 54.66 ± 13.6 years, 125 [73.5%] males) with ICH were included in the analysis. Thirty-six (21.2%) patients were assigned to the VTE group. Multivariate Cox analysis identified age (HR = 1.032, 95% CI: 1.002–1.062, p = 0.033), baseline edema volume (HR = 1.034, 95% CI: 1.012–1.056, p = 0.002), intraventricular hemorrhage (HR = 3.268, 95% CI: 1.635–6.530, p < 0.001), myoglobin (Myo; HR = 1.002, 95% CI: 1.000–1.003, p = 0.010), and B-type natriuretic peptide (BNP; HR = 1.003, 95% CI: 1.001–1.006, p = 0.007) as independent predictors. The combined model showed better predictive performance than the clinical-radiological model alone (C-index: 0.791 vs. 0.749). The nomogram demonstrated good calibration and clinical utility across a wide risk threshold range. Conclusion: Myo and BNP provide incremental predictive value for VTE risk stratification in ICH patients beyond traditional factors. The developed nomogram offers a practical tool for individualized risk assessment, potentially guiding optimized VTE prophylaxis strategies.

Flow diverters (FDs) are an established treatment method for dissecting aneurysms.1-3 However, device shortening post-deployment and subsequent migration into the aneurysm may pose significant risks.4,5 In this technical video (Video 1), we present a case of Pipeline Flex Shield deployment for a dissecting aneurysm in the M1 segment of the left middle cerebral artery, where proximal segment shortening with subsequent device migration into the aneurysm sac was observed during the 9-month follow-up evaluation. In this procedure, we successfully advanced a microwire-guided microcatheter through the proximal portion of the compromised stent. Utilizing an exchange technique, the original delivery catheter was replaced to facilitate deployment of a Lattice flow diverter. Final angiography confirmed adequate overlap between the two stents with re-established luminal patency in the parent artery. n analogous clinical scenarios, telescoping stent deployment within the shortened endoprosthesis may constitute a viable salvage strategy.

BACKGROUND:Endovascular recanalization for chronic internal carotid artery occlusion (CICAO) remains technically challenging, with variable success rates and a lack of reliable predictive tools for patient selection. We aim to analyze risk factors associated with failed recanalization in CICAO patients and develop a decision tree model to quantify individualized recanalization potential. METHODS:We retrospectively analyzed 321 patients with symptomatic CICAO who underwent endovascular recanalization. Univariate and multivariate analyses were used to identify risk factors for recanalization failure. A decision tree model and logistic model were constructed. Models' performance was evaluated using AUC analysis and decision curve analysis (DCA). RESULTS:The overall recanalization success rate was 61.7 %. Our study identified three independent risk factors for failed recanalization: occlusion length > 10 cm, type III stump morphology, and contralateral internal carotid artery stenosis. The decision-tree model demonstrated good performance (AUC 0.839 in training, 0.834 in validation) and provided clinical interpretability compared to logistic regression. DCA confirmed clinical utility across probability thresholds. CONCLUSIONS:We developed and validated a decision tree model that effectively predicts endovascular recanalization success in CICAO patients, which may serve as a valuable tool to support clinical decision-making for patients with CICAO.

Little is known about the association between periprocedural hemodynamics and in-stent restenosis (ISR) following stent implantation in patients with symptomatic intracranial atherosclerotic stenosis (ICAS). This study aims to identify periprocedural hemodynamics that may be associated with ISR. Subjects were selected from the NOVA trial (The First-in-man Trial Evaluating the Safety and Efficacy of the NOVA Intracranial Stent Trial). ISR was defined as greater than 50

The pipeline embolization device (PED) has been established as an effective treatment option for aneurysms within its designated indications. Recently, its off-label applications, including treating middle cerebral artery (MCA) aneurysms, have increased. This study augmented the current literature by examining the outcomes of PED utilization for MCA aneurysms. We collected data from consecutive patients with MCA aneurysms treated with PED between June 2016 and December 2021. Particularly, we collected data on patient demographics, aneurysm characteristics, procedural details, perioperative complications, and clinical and angiographic follow-up results. A total of 69 patients (mean age 47.4 years; 42.0

BACKGROUND:Current evidence regarding restenosis after successful endovascular recanalization for chronic internal carotid artery occlusion (CICAO) remains limited. This study aimed to investigate the incidence and risk factors of restenosis following technically successful revascularization for CICAO, and to develop a novel risk score for risk stratification. METHODS:This retrospective cohort study included 204 patients with CICAO who underwent successful endovascular recanalization. The incidence of restenosis was assessed, risk factors were identified through multivariable regression analysis, and a predictive model for restenosis was developed using multivariable regression analysis. RESULTS:During a mean imaging follow-up duration of 16.1 ± 8.5 months, 47 patients (23.5 %) developed internal carotid artery restenosis or reocclusion. A multivariable logistic regression model constructed using backward stepwise regression demonstrated an area under the curve values of 0.758 in the training set and 0.757 in the test set. The model identified three independent risk factors: internal carotid artery tortuosity, non-tapered stump morphology, and residual stenosis > 30 %. CONCLUSION:This study demonstrated a restenosis rate of 23.5 % following successful endovascular recanalization for CICAO. Internal carotid artery tortuosity, non-tapered stump morphology, and residual stenosis > 30 % were identified as independent predictors of restenosis.

Background Cerebral arteriovenous malformation (AVM) is a cerebrovascular disorder posing a risk for intracranial hemorrhage. However, there are few reliable quantitative indices to predict hemorrhage risk accurately. This study aimed to identify potential biomarkers for hemorrhage risk by quantitatively analyzing the hemodynamic and morphological features within the AVM nidus.Methods This study included three datasets comprising consecutive patients with untreated AVMs between January 2008 to December 2023. Training and test datasets were used to train and evaluate the model. An independent validation dataset of patients receiving conservative treatment was used to evaluate the model performance in predicting subsequent hemorrhage during follow-up. Hemodynamic and morphological features were quantitatively extracted based on digital subtraction angiography (DSA). Individual models using various machine learning algorithms and an ensemble model were constructed on the training dataset. Model performance was assessed using the confusion matrix-related metrics.Results This study included 844 patients with AVMs, distributed across the training (n=597), test (n=149), and validation (n=98) datasets. Five hemodynamic and 14 morphological features were quantitatively extracted for each patient. The ensemble model, constructed based on five individual machine-learning models, achieved an area under the curve of 0.880 (0.824-0.937) on the test dataset and 0.864 (0.769-0.959) on the independent validation dataset.Conclusion Quantitative hemodynamic and morphological features extracted from DSA data serve as potential indicators for assessing the rupture risk of AVM. The ensemble model effectively integrated multidimensional features, demonstrating favorable performance in predicting subsequent rupture of AVM.

Background and purposePostinterventional rupture of intracranial aneurysms (IAs) remains a severe complication after flow diverter treatment. However, potential hemodynamic mechanisms underlying independent predictors for postinterventional rupture of IAs remain unclear. In this study, we employed arteriography-derived radiomic features to predict this complication.MethodsWe included 64 patients who underwent pipeline flow diversion for intracranial aneurysms, distinguishing between 16 patients who experienced postinterventional rupture and 48 who did not. We performed propensity score matching based on clinical and morphological factors to match these patients with 48 patients with postinterventional unruptured IAs at a 1:3 ratio. Postinterventional digital subtraction angiography were used to create five arteriography-derived perfusion parameter maps and then radiomics features were obtained from each map. Informative features were selected through the least absolute shrinkage and selection operator method with five-fold cross-validation. Subsequently, radiomics scores were formulated to predict the occurrence of postinterventional IA ruptures. Prediction performance was evaluated with the training and test datasets using area under the curve (AUC) and confusion matrix-derived metrics.ResultsOverall, 1,459 radiomics features were obtained, and six were selected. The resulting radiomics scores had high efficacy in distinguishing the postinterventional rupture group. The AUC and Youden index were 0.912 (95% confidence interval: 0.767–1.000) and 0.847 for the training dataset, respectively, and 0.938 (95% confidence interval, 0.806–1.000) and 0.800 for the testing dataset, respectively.ConclusionRadiomics scores generated using arteriography-derived radiomic features effectively predicted postinterventional IA ruptures and may aid in differentiating IAs at high risk of postinterventional rupture.

BACKGROUND: Evaluating rupture risk in cerebral arteriovenous malformations currently lacks quantitative hemodynamic and angioarchitectural features necessary for predicting subsequent hemorrhage. We aimed to derive rupture-related hemodynamic and angioarchitectural features of arteriovenous malformations and construct an ensemble model for predicting subsequent hemorrhage. METHODS: This retrospective study included 3 data sets, as follows: training and test data sets comprising consecutive patients with untreated cerebral arteriovenous malformations who were admitted from January 2015 to June 2022 and a validation data set comprising patients with unruptured arteriovenous malformations who received conservative treatment between January 2009 and December 2014. We extracted rupture-related features and developed logistic regression (clinical features), decision tree (hemodynamic features), and support vector machine (angioarchitectural features) models. These 3 models were combined into an ensemble model using a weighted soft-voting strategy. The performance of the models in discriminating ruptured arteriovenous malformations and predicting subsequent hemorrhage was evaluated with confusion matrix-related metrics in the test and validation data sets. RESULTS: A total of 896 patients (mean±SD age, 28±14 years; 404 women) were evaluated, with 632, 158, and 106 patients in the training, test, and validation data sets, respectively. From the training set, 9 clinical, 10 hemodynamic, and 2912 pixel-based angioarchitectural features were extracted. A logistic regression model was built using 4 selected clinical features (age, nidus size, location, and venous aneurysm), whereas a decision-tree model was constructed from 4 hemodynamic features (outflow time, stasis index, cerebral blood flow, and outflow volume ratio). A support vector machine model was designed using 5 pixel-based angioarchitectural features. In the validation data set, the accuracy, sensitivity, specificity, and area under the curve of the ensemble model for predicting subsequent hemorrhages were 0.840, 0.889, 0.823, and 0.911, respectively. CONCLUSIONS: The ensemble model incorporating clinical, hemodynamic, and angioarchitectural features showed favorable performance in predicting subsequent hemorrhage of cerebral arteriovenous malformations.

Objective: Idiopathic intracranial hypertension (IIH) is a condition of unknown etiology associated with venous sinus stenosis. This study aimed to develop a magnetic resonance venography (MRV)-based radiomics model for predicting a high trans-stenotic pressure gradient (TPG) in IIH patients diagnosed with venous sinus stenosis. Materials and Methods: This retrospective study included 105 IIH patients (median age [interquartile range], 35 years [27- 42 years]; female:male, 82:23) who underwent MRV and catheter venography complemented by venous manometry. Contrast enhanced-MRV was conducted under 1.5 Tesla system, and the images were reconstructed using a standard algorithm. Shape features were derived from MRV images via the PyRadiomics package and selected by utilizing the least absolute shrinkage and selection operator (LASSO) method. A radiomics score for predicting high TPG (>= 8 mmHg) in IIH patients was formulated using multivariable logistic regression; its discrimination performance was assessed using the area under the receiver operating characteristic curve (AUROC). A nomogram was constructed by incorporating the radiomics scores and clinical features. Results: Data from 105 patients were randomly divided into two distinct datasets for model training (n = 73; 50 and 23 with and without high TPG, respectively) and testing (n = 32; 22 and 10 with and without high TPG, respectively). Three informative shape features were identified in the training datasets: least axis length, sphericity, and maximum three-dimensional diameter. The radiomics score for predicting high TPG in IIH patients demonstrated an AUROC of 0.906 (95% confidence interval, 0.836- 0.976) in the training dataset and 0.877 (95% confidence interval, 0.755-0.999) in the test dataset. The nomogram showed good calibration. Conclusion: Our study presents the feasibility of a novel model for predicting high TPG in IIH patients using radiomics analysis of noninvasive MRV-based shape features. This information may aid clinicians in identifying patients who may benefit from stenting.

BackgroundPatients with sub-acute cerebral venous sinus thrombosis experience (SA.CVST) severe symptoms compared to two other venous sinus-related diseases, including chronic cerebral venous sinus thrombosis (C.CVST) and idiopathic intracranial hypertension (IIH).ObjectiveThis study aimed to determine whether the different immune reactions in different venous sinuses are related.MethodsStagnant blood in the cerebral venous sinuses was extracted by passing a microcatheter and CD14-positive cells were sorted by magnetic beads and subjected to RNA-seq sequencing.ResultsCompared to patients with IIH, 128 genes were significantly down-regulated and 373 genes were significantly up-regulated in the sub-acute CVST samples. The functions of these genes were mainly focused on “immune response”, “T cell activation” and “plasma membrane”. Gene Set Enrichment Analysis (GSEA) showed T cell survival and activation-related function significantly unregulated in sub-acute CVST. On the other hand, there were 366 genes down-regulated in chronic CVST and 75 genes up-regulated in chronic CVST. In functional annotation, these differently expressed genes were enriched in the “extracellular region”, “chemokine-mediated signaling pathway” and “immune response”. GSEA analysis confirmed that chemokine-related functions were all up-regulated in sub-acute CVST and monocyte-macrophage adhesion functions were also significantly up-regulated.ConclusionThis study suggested the CD14-positive created an activated immune response in sub-acute CVST.

PURPOSE:To explore imaging biomarkers predictive of intratumoral haemorrhage for lesions intended for elective stereotactic biopsy. METHOD:This study included a retrospective cohort of 143 patients with 175 intracranial lesions intended for stereotactic biopsy. All the lesions were randomly split into a training dataset ( n =121) and a test dataset ( n =54) at a ratio of 7:3. Thirty-four lesions were defined as "hemorrhage-prone tumors" as haemorrhage occurred between initial diagnostic MRI acquisition and the scheduled biopsy procedure. Radiomics features were extracted from the contrast-enhanced T1 Weighted Imaging and T2 Weighted Imaging images. Features informative of haemorrhage were then selected by the LASSO algorithm, and an Support Vector Machine model was built with selected features. The Support Vector Machine model was further simplified by discarding features with low importance and calculating them using a "permutation importance" method. The model's performance was evaluated with confusion matrix-derived metrics and area under curve (AUC) values on the independent test dataset. RESULTS:Nine radiomics features were selected as haemorrhage-related features of intracranial tumours by the LASSO algorithm. The simplified model's sensitivity, specificity, accuracy, and AUC reached 0.909, 0.930, 0.926, and 0.949 (95% CI: 0.865-1.000) on the test dataset in the discrimination of "hemorrhage-prone tumors". The permutation method rated feature "T2_gradient_firstorder_10Percentile" as the most important, the absence of which decreased the model's accuracy by 10.9%. CONCLUSION:Radiomics features extracted on contrast-enhanced T1 Weighted Imaging and T2 Weighted Imaging sequences were predictive of future haemorrhage of intracranial tumours with favourable accuracy. This model may assist in the arrangement of biopsy procedures and the selection of target lesions in patients with multiple lesions.

Background Cognard type IIa+b dural arteriovenous fistulas (DAVFs) in the lateral sinuses are often complicated with venous sinus obstruction and accompanied by clinical symptoms and a risk of hemorrhage. The purpose of this study was to assess venous sinus stenting as a viable alternative treatment in complex lateral sinus DAVFs and examine its efficacy and safety. Methods We retrospectively examined patients diagnosed with type IIa+b DAVF in the transverse or sigmoid sinus with associated venous sinus occlusion who were treated via stent placement between April 2017 and June 2019. Results Six patients were included in this study. Three patients had DAVFs in both the transverse and sigmoid sinuses, two in the transverse sinus and confluence of sinuses, and one in the transverse sinus. The most common symptoms were headache, dizziness, and limb weakness. At the last follow-up, three patients had significant improvement, and three were asymptomatic. Angiograms performed immediately after the surgery showed restoration of the anterograde venous drainage in all patients. According to the follow-up angiography results, two DAVFs were completely obliterated, and four remained as stable type I DAVFs. Most patients had satisfactory venous sinus drainage, except one who had in-stent stenosis. Conclusions Stent placement can restore sinus patency, improve clinical symptoms, and decrease intracranial hemorrhage risk. This approach may be an effective option for treating type IIa+b lateral DAVFs complicated by sinus occlusion.

The Woven EndoBridge (WEB) device is a well established treatment for bifurcation aneurysms.1-6 However, failed detachment after deployment can present significant challenges. In this technical video (video 1), we report on a patient with a left middle cerebral artery (MCA) bifurcation aneurysm treated with the WEB device. Despite satisfactory deployment, multiple detachment attempts were unsuccessful. After repeated maneuvers, the WEB was finally detached but slightly protruded from the aneurysm sac, compromising blood flow in the superior branch of the MCA. Even after placing an Atlas stent, blood flow was not restored. Ultimately, using a microguidewire and microcatheter, we repositioned the protruded WEB device back into the aneurysm sac, successfully restoring blood flow. This case illustrates that the Atlas stent provides limited support for the WEB device. In similar situations, gently repositioning the protruded WEB back into the aneurysm sac may be a remedial measure. neurintsurg;jnis-2024-022430v1/V1F1V1Video 1Technical video demonstrating rescue techniques for managing intravascular mechanical obstruction following detachment of the WEB device.

The existing literature has reported cases of using Woven EndoBridge (WEB) device for recurrent aneurysm as well as situations where multiple WEB devices were deployed within a single aneurysm 1 -4 . However, the ef ficacy of a parallel placement strategy of WEB devices for treating wide-necked aneurysms, where a single WEB device proves insuf ficient for complete coverage of aneurysm neck, has yet to be reported. In this technical video (video 1), we report a case involving a patient in their 60 s who was diagnosed with an aneurysm during a routine physical examination. Digital subtraction angiography (DSA) revealed a wide-necked, lobulated aneurysm at the basilar tip. Independent measurements were taken of the main body and the saccular partitions of the aneurysm, and two WEB devices were sequentially deployed. Immediate postoperative DSA showed signi ficant stagnation within the aneurysm. The 11-month postoperative angiography showed that the aneurysm was adequately occluded. This case indicates that for wide-necked aneurysms where a single WEB device cannot fully cover the aneurysm neck, the parallel deployment of WEB devices can serve as an alternative treatment strategy.

Objectives Cerebral venous sinus thrombosis (CVST) can cause sinus obstruction and stenosis, with potentially fatal consequences. High-resolution magnetic resonance imaging (HRMRI) can diagnose CVST qualitatively, although quantitative screening methods are lacking for patients refractory to anticoagulation therapy and who may benefit from endovascular treatment (EVT). Thus, in this study, we used radiomic features (RFs) extracted from HRMRI to build machine learning models to predict response to drug therapy and determine the appropriateness of EVT. Materials and methods RFs were extracted from three-dimensional T1-weighted motion-sensitized driven equilibrium (MSDE), T2-weighted MSDE, T1-contrast, and T1-contrast MSDE sequences to build radiomic signatures and support vector machine (SVM) models for predicting the efficacy of standard drug therapy and the necessity of EVT. Results We retrospectively included 53 patients with CVST in a prospective cohort study, among whom 14 underwent EVT after standard drug therapy failed. Thirteen RFs were selected to construct the RF signature and CVST-SVM models. In the validation dataset, the sensitivity, specificity, and area under the curve performance for the RF signature model were 0.833, 0.937, and 0.977, respectively. The radiomic score was correlated with days from symptom onset, history of dyslipidemia, smoking, fibrin degradation product, and D-dimer levels. The sensitivity, specificity, and area under the curve for the CVST-SVM model in the validation set were 0.917, 0.969, and 0.992, respectively. Conclusions The CVST-SVM model trained with RFs extracted from HRMRI outperformed the RF signature model and could aid physicians in predicting patient responses to drug treatment and identifying those who may require EVT.