(1) Background: Follow-up infarct volume (FIV) may have implications for prognostication in acute ischemic stroke patients. Factors predicting the discrepancy between FIV and 90-day outcomes are poorly understood. We aimed to develop a comprehensive predictive model of FIV and explore factors associated with the discrepancy. (2) Methods: Patients with acute anterior circulation large vessel occlusion were included. Baseline clinical and CT features were extracted and analyzed, including the CTP-based hypoperfusion index (HI) and the NCCT-based e-ASPECT, measured by automated software. FIV was assessed on follow-up NCCT at 3–7 days. Multiple linear regression was used to construct the predictive model. Subgroup analysis was performed to explore factors associated with poor outcomes (90-mRS scores 3–6) in small FIV (<70 mL). (3) Results: There were 170 patients included. Baseline e-ASPECT, infarct core volume, hypoperfusion volume, HI, baseline international normalized ratio, and successful recanalization were associated with FIV and included in constructing the predictive model. Baseline NIHSS, baseline hypertension, stroke history, and current tobacco use were associated with poor outcomes in small FIV. (4) Conclusions: A comprehensive predictive model (including HI) of FIV was constructed. We also emphasized the importance of hypertension and smoking status at baseline for the functional outcomes in patients with a small FIV.

PURPOSE:To investigate the association of tortuosity of the main cerebral arteries with intracranial aneurysm (IA) occurrence and rupture. To investigate the relationship between arterial tortuosity and aneurysm morphology as well as conventional risk factors of vascular diseases. METHODS:Three subject groups were analyzed in this study: Patients with ruptured IAs, patients with unruptured IAs, and healthy subjects. The groups were matched by sex and age using tendency score matching. Their intracranial magnetic resonance angiography (MRA) images were collected retrospectively. The intracranial arterial structures were segmented from the MRA images. Arterial tortuosity was measured and statistically compared between the different subject groups and different vessels. Correlation analysis was conducted between arterial tortuosity and clinical risk factors as well as aneurysm morphology. RESULTS:120 patients were included in the study (average age: 67.5 years; 60% female), 40 for each group after matching. The tortuosity of the aneurysm-bearing artery was significantly greater than that of the contralateral artery in both the ruptured and unruptured IA groups (p < 0.001). There was no significant association between clinical risk factors (history of hypertension, hyperlipidemia, diabetes, smoking, and alcohol use) and arterial tortuosity. There were significant negative correlations between aneurysm-bearing artery tortuosity and aneurysm morphological features such as maximal diameter (p = 0.0011), neck diameter (p < 0.0001), maximum height (p = 0.0024), and size ratio (p = 0.0269). CONCLUSION:The occurrence of cerebral aneurysms correlates to increased unilateral arterial tortuosity, but the risk of aneurysm enlargement/rupturing decreases with greater arterial tortuosity. Abnormal tortuosity may be congenital as tortuosity has no clear connection with acquired common risk factors of vascular diseases.

专家引言：脑血管疾病如脑梗死、脑动脉瘤是全球范围内困扰人类健康、带来社会医疗负担的重要议题。近年来，四川省人民医院放射科王玉婷教授团队围绕脑血管影像学开展了一系列的研究，一方面在缺血性疾病如脑梗死领域，探索急性和慢性期不同的影像学任务；另一方面在出血性疾病如脑动脉瘤领域，开展人群研究和新型标志物的探索和验证。基于较长期的系统性研究，开发验证了一系列较关键的影像标志物，可应用于脑梗死、脑动脉瘤等血管疾病的临床管理全流程的多个场景（病因诊断、预后预测、破裂出血风险评估、复发风险评估、药物疗效监测等），为辅助脑血管疾病的诊疗提供了影像学依据。北京天坛医院刘亚欧教授指出，脑血管病作为全球范围内导致成人死亡和残疾的重要原因，如何减少其发病、改善预后并减少复发是目前的重要研究方向。王玉婷教授团队从西南人群入手，着眼于脑血管病领域的临床关键问题，从临床需求出发进行研究设计，进行了一系列临床影像研究，并与国内外研究团队深入合作，将影像学新技术应用于脑卒中病因探索、临床预后预测、疾病复发风险评估、药物疗效监测等方面，使影像研究结果能够应用于临床实践。

Background and Aims Identifying unruptured intracranial aneurysm instability is crucial for therapeutic decision-making. This study aims to evaluate the role of Radiomics and traditional morphological features in identifying aneurysm instability by constructing and comparing multiple models. Materials and Methods A total of 227 patients with 254 intracranial aneurysms evaluated by CTA were included. Aneurysms were divided into unstable and stable groups using comprehensive criteria: the unstable group was defined as aneurysms with near-term rupture, growth during follow-up, or caused compressive symptoms; those without the aforementioned conditions were grouped as stable aneurysms. Aneurysms were randomly divided into training and test sets at a 1:1 ratio. Radiomics and traditional morphological features (maximum diameter, irregular shape, aspect ratio, size ratio, location, etc.) were extracted. Three basic models and two integrated models were constructed after corresponding statistical analysis. Model A used traditional morphological parameters. Model B used Radiomics features. Model C used the Radiomics features related to aneurysm morphology. Furthermore, integrated models of traditional and Radiomics features were built (model A+B, model A+C). The area under curves (AUC) of each model was calculated and compared. Results There were 31 (13.7%) patients harboring 36 (14.2%) unstable aneurysms, 15 of which ruptured post-imaging, 16 with growth on serial imaging, and 5 with compressive symptoms, respectively. Four traditional morphological features, six Radiomics features, and three Radiomics-derived morphological features were identified. The classification of aneurysm stability was as follows: the AUC of the training set and test set in models A, B, and C are 0.888 (95% CI 0.808–0.967) and 0.818 (95% CI 0.705–0.932), 0.865 (95% CI 0.777–0.952) and 0.739 (95% CI 0.636–0.841), 0.605(95% CI 0.470–0.740) and 0.552 (95% CI 0.401–0.703), respectively. The AUC of integrated Model A+B was numerically slightly higher than any single model, whereas Model A+C was not. Conclusions A radiomics and traditional morphology integrated model seems to be an effective tool for identifying intracranial aneurysm instability, whereas the use of Radiomics-derived morphological features alone is not recommended. Radiomics-based models were not superior to the traditional morphological features model.

Background and Aims: Statin therapy is an essential component of cardiovascular preventive care. In recent years, various vessel wall MRI (VW-MRI) techniques have been used to monitor atherosclerosis progression or regression in patients with extracranial or intracranial large-artery atherosclerosis. We aimed to perform a systematic review and meta-analysis on the effects of statin therapy on plaque evolution as assessed by VW-MRI. Materials and Methods: Prospective studies investigating carotid and intracranial atherosclerotic plaques in patients on statin therapy monitored by serial VW-MRI were systematically identified in the literature. The plaque burden and lipid-rich necrotic core (LRNC) volume of carotid plaque and the imaging features of intracranial plaques were extracted and summarized. For studies investigating carotid artery wall volume and LRNC volume, combined estimates were derived by meta-analysis. Results: The study identified 21 studies of carotid plaque and two studies of intracranial plaque. While 16 studies investigating carotid plaques that included 780 patients by High-resolution VW-MRI were included in the meta-analysis. There was no significant change in carotid wall volume from baseline to 12 months. A significant change in LRNC volume was observed at > 12 months compared with baseline (Effect = -10.69, 95% CI = -19.11, -2.28, P < 0.01), while no significant change in LRNC volume at 3-6 months or 7-12 months after statin therapy initiation in 6 studies. Increases in fibrous tissue and calcium and reduction in neovascularization density of the plaque were seen in 2/3 studies (including 48/59 patients), 1/3 studies (including 17/54 patients), and 2/2 studies (including 71 patients) after statin therapy, respectively. Two studies with 257 patients in intracranial atherosclerosis showed that statins could effectively decrease wall volume and plaque enhancement volume. Conclusions: Collective data indicated that statins could potentially stabilize carotid plaques by significantly reducing LRNC with 1 year of therapy as shown on serial carotid VW-MRI. There was no significant decrease in wall volume, which nonetheless indicated that plaque composition changes might be more sensitive to response monitoring than wall volume. It is likely that more sensitive, clinically relevant, and preferably quantitative indicators of therapeutic effects on intracranial vessel plaque morphology will be developed in the future.