Background:It remains unclear whether non-optimum temperatures are associated with hospital admissions for subtypes of cardiovascular events, and how PM2.5 and black carbon (BC) modify these associations. Methods:Hospital admission data of major cardiovascular events were obtained from two major national health insurance systems across 270 cities of prefecture-level or above in China during 2013-2017. A two-stage time-series study was conducted using a generalized additive model with a quasi-Poisson family, combined with a distributed lag nonlinear regression model, to explore the exposure-response associations of non-optimum temperatures with hospital admissions. Effect modification was investigated by stratifying ambient particulate air pollution levels into quartile groups. Findings:In a total of 24,564,921 hospital admission records for major cardiovascular events, compared with the minimum morbidity temperature (18.3 °C), the relative risks (RRs) of hospital admissions for total major cardiovascular events associated with extreme cold temperature (-3.1 °C, 2.5th percentile) and extreme hot temperature (27.9 °C, 97.5th percentile) were 1.69 [95% confidence interval (CI): 1.46-1.96] and 1.27 (95% CI: 1.15-1.41), respectively. Such temperature-hospital admission associations were amplified at high BC levels, especially under extreme hot temperature, with RR increased from 1.14 (95% CI: 1.02-1.28) in the first quartile to 1.53 (95% CI: 1.31-1.78) in the fourth quartile group of BC levels. Interpretation:Our study suggests that both extreme cold and hot temperatures contribute to elevated hospital admission risks for major cardiovascular events, with high BC levels further exacerbating the risks associated with extreme hot temperature. Funding:National Science Fund for Distinguished Young Scholars of China (grant number 82525058), National Natural Science Foundation of China (grant number 82203991), and Youth Top Talent Program of Xi'an Jiaotong University.

Ischemic stroke is a leading cause of mortality and morbidity globally. Prompt intervention is essential for arresting disease progression and minimizing central nervous system damage. Although imaging studies play a significant role in diagnosing ischemic stroke, their high costs and limited sensitivity often result in diagnostic and treatment delays. Blood biomarkers have shown considerable promise in the diagnosis and prognosis of ischemic stroke. Serum markers, closely associated with stroke pathophysiology, aid in diagnosis, subtype identification, prediction of disease progression, early neurological deterioration, and recurrence. Their advantages are particularly pronounced due to their low cost and rapid results. Despite the identification of numerous candidate blood biomarkers, their clinical application requires rigorous research and thorough validation. This review focuses on various blood biomarkers related to ischemic stroke, including coagulation and fibrinolysis-related factors, endothelial dysfunction markers, inflammatory biomarkers, neuronal and axonal injury markers, exosomes with their circular RNAs and other relevant molecules. It also summarizes the latest methods and techniques for stroke biomarker detection, aiming to provide critical references for the clinical application of key stroke biomarkers.

ABSTRACT Objectives Cerebral small vascular disease (CSVD) is not rare in neurologically asymptomatic individuals. Glucose control and insulin resistance (IR) may be its risk factors. We aimed to explore the relationship between CSVD markers, glucose control, and IR in neurologically asymptomatic, nondiabetic individuals. Methods A total of 412 participants from the annual physical examinations population in our hospital who underwent brain magnetic resonance imaging from May 2019 to June 2021 were enrolled. We collected clinical data and blood test indices and calculated the triglyceride‐glucose (TyG) index. CSVD markers were assessed, including lacunes, white matter hyperintensities (WMH), enlarged perivascular spaces (EPVS), cerebral microbleeds (CMBs), and the total CSVD score. Correlations between CSVD markers, clinical variables, and blood test parameters were analyzed. Results The median age of our group was 70.32 ± 10.27 years (45–103 years). The prevalence of asymptomatic CSVD was 43.7%. Lacunes were present in 8.3%, periventricular WMH (PVWMH) in 65.3%, deep WMH (DWMH) in 64.1%, EPVS in 87.4%, and CMBs in 31.3% of individuals. Glycated hemoglobin A1c (HbA1c) varied between PVWMH subgroups (p = 0.043). Fasting blood glucose (FBG) was higher in individuals with deep CMBs than in those without deep CMBs (p = 0.012). FBG was an independent risk factor for deep CMBs after controlling for multiple variables. However, the TyG index was not associated with CSVD markers. Conclusions The prevalence of neurologically asymptomatic CSVD is common in the nondiabetic population. It may be beneficial for middle‐aged and elderly people to pay attention to their blood glucose levels.

Futile recanalization is a recognized challenge in acute ischemic stroke (AIS) patients after endovascular treatment (EVT). Our purpose was to develop and validate a predictive model for futile recanalization after EVT by integrating arterial-venous collateral assessment with clinical parameters. This study included 392 AIS patients with acute anterior circulation large vessel occlusion who underwent EVT (March 2016-June 2024). Patients were stratified into training (n = 160), internal validation (n = 69), and completely independent external validation (n = 163) cohorts collected from a separate medical center. Predictors were identified using Boruta algorithm and LASSO regression. Multiple machine learning models were evaluated through discrimination, calibration, and decision curve analyses, with SHAP analysis for feature importance. Three independent predictors were identified: age (OR: 1.06, 95% CI: 1.02-1.11), whole-brain arterial collateral status (OR: 0.30, 95% CI: 0.18-0.50), and whole-brain venous collateral status (OR: 0.78, 95% CI: 0.67-0.90). The model demonstrated excellent discrimination in the training cohort (AUC: 0.914, 95% CI: 0.866-0.963), internal validation cohort (AUC: 0.918, 95% CI: 0.844-0.991), and notably maintained robust performance in the completely independent external validation cohort (AUC: 0.755, 95% CI: 0.678-0.832). Calibration plots showed good agreement between predicted and observed outcomes. SHAP analysis further confirmed the importance of arterial and venous collateral status assessments. The integration of whole-brain arterial-venous collateral assessment with clinical parameters shows potential value in predicting futile recanalization after EVT. This model, validated across multiple cohorts, may provide additional information to support clinical decision-making.

Background: The evidence for the interactive effects of long-term exposure to ambient fine particulate matter (PM2.5) and ozone (O-3) with typical coagulation parameters which are widely used in clinical practices is limited. Methods: Data on basic information and typical coagulation parameters from 40,338 ischemic heart disease (IHD) patients with their first admission records between January 1, 2018 and May 31, 2019 were obtained from Anzhen Hospital, Beijing. Multivariate linear regression model and stratified analysis were used to evaluate separate and interactive effects of annual PM2.5 and maximum daily 8-h average (MDA8) O-3 exposures on typical coagulation parameters. Results: We found that both long-term PM2.5 and MDA8 O-3 exposures were associated with increases in prothrombin time and international normalized ratio (INR), and decreases in prothrombin activity (PTA), activated partial thromboplastin time (APTT), and D-Dimer. The effect estimates of both PM2.5 and MDA8 O-3 on PTA, INR, and APTT were generally stronger at higher percentiles of co-pollutant strata (all P-difference<0.05). For example, the percent changes in PTA associated with per 10 mu g/m(3) increase in PM2.5 were -0.68 % (95 %CI: -0.97 %, -0.38 %), -1.04 % (95 %CI: -1.30 %, -0.78 %) and -1.36 % (95 %CI: -1.80 %, -0.91 %) in the low (<= 25 %), medium (25 %-75 %) and high (>75 %) MDA8 O-3 strata, respectively; and the percent changes in PTA associated with per 10 mu g/m(3) increase in MDA8 O-3 were -1.63 % (95 %CI: -1.96 %, -1.30 %), -1.67 % (95 %CI: -2.03 %, -1.30 %) and -2.30 % (95 %CI: -2.78 %, -1.82 %) in the low, medium and high PM2.5 strata, respectively. Conclusions: Our study provides novel evidence that long-term PM2.5 and O-3 exposures synergistically impair the function of coagulation, which may lead to the adverse prognosis in IHD patients, highlighting the advantage of implementing integrated management approaches for both air pollutants.

Maternal placental growth factor (PLGF) is essential for fetal growth, and emerging evidence links PM2.5 exposure to adverse pregnancy outcomes (APOs). However, the effects of specific PM2.5 constituents on maternal PLGF levels and their underlying mechanism remain unclear. We recruited 11,677 mother-child pairs between 2017 and 2023 in Tianjin, China. Individual exposure was assessed using the Tracking Air Pollution in China dataset. Cox proportional hazards models and quantile-based g-computation models were utilized to assess the individual and joint effects of exposure to PM2.5 and its constituents on APOs. Causal mediation analysis was used to estimate the mediation effects of maternal PLGF levels on these association. Maternal exposure to PM2.5 and its constituents was associated with an increased risk of premature rupture of membrane, preterm birth (PTB), and low birth weight (LBW) during entire pregnancy. Among the constituents, organic matter (OM) demonstrated the greatest adverse effect. Causal mediation analysis indicated that decrease in maternal PLGF levels mediate by 30.4 % and 34.3 % of the associations between PM2.5 and PTB, LBW, respectively. Our findings highlighted the potential mechanism between PM2.5 and its constituents exposure and APOs by maternal PLGF as clinical biomarker reflecting placental function.

Rationale and Objectives: A significant complication of endovascular treatment (EVT) is hemorrhagic transformation (HT), which can worsen the outcomes of patients with acute ischemic stroke (AIS). This study aimed to evaluate the predictive value of venous collateral circulation on HT in patients with AIS undergoing EVT. Materials and Methods: We retrospectively analyzed 126 patients with AIS who received EVT. The four-dimensional computed tomography angiography-based venous collateral score (4D-VCS) and arterial collateral circulation score (4D-ACS) were used to assess venous and arterial collaterals, respectively. Significant variables were identified using the least absolute shrinkage and selection operator algorithm. Logistic regression analysis, receiver operating characteristic (ROC) analysis, and DeLong's test were conducted. Results: HT occurred in 41.3% (52/126) of patients. Higher clot burden score (CBS; odds ratio [OR]: 0.82, 95% confidence interval [CI]: 0.71-0.95, p = 0.009), better arterial collateral circulation (OR: 0.59, 95% CI: 0.42-0.83, p = 0.003), and better venous collateral circulation (OR: 0.85, 95% CI: 0.73-0.97, p = 0.020) were significantly associated with reduced HT risk. The area under the curve (AUC) values for CBS, 4D-ACS, and 4D-VCS were 0.730, 0.772, and 0.795, respectively. Model 1 (4D-VCS+CBS) achieved AUC of 0.820, significantly improving over CBS alone ( p = 0.0133). Model 2 (4D-VCS+4D-ACS) had an AUC of 0.829, significantly higher than 4D-ACS alone ( p = 0.0271). Model 3 (4D-ACS+CBS) had an AUC of 0.790. Model 4 (4D-VCS+4D-ACS+CBS) showed highest AUC of 0.851. Significant correlations were found between 4D-VCS and ischemic core volume ( r = -0.684, p < 0.001) and between 4D-VCS and mismatch ratio ( r = 0.558, p < 0.001). Conclusion: Evaluating venous collateral circulation using 4D-VCS could improve HT risk prediction in patients with AIS after EVT. When combined with other predictors, 4D-VCS may potentially enhance diagnostic performance, which suggests the potential role of venous collateral circulation in predicting HT risk.

OBJECTIVE:To develop logistic regression nomogram and machine learning (ML)-based models to predict 3-month unfavorable functional outcome for acute ischemic stroke (AIS) patients undergoing reperfusion therapy.METHODS:Patients undergoing reperfusion therapy (intravenous thrombolysis and/or endovascular treatment) were prospectively recruited. Unfavorable outcome was defined as 3-month modified Rankin Scale (mRS) score 3-6. The independent risk factors associated with unfavorable outcome were obtained by regression analysis and included in the prediction model. The performance of nomogram was assessed by the area under the curve (AUC), calibration curve, and decision curve analysis (DCA). ML models were compared with nomogram using AUC; the generalizability of all models was ascertained in an external cohort.RESULTS:A total of 505 patients were enrolled, with 256 in the model construction, and 249 in the external validation. Five variables were identified as prognostic factors: baseline NIHSS, D-dimer level, random blood glucose (RBG), blood urea nitrogen (BUN), and systolic blood pressure (SBP) before reperfusion. The AUC values of nomogram were 0.865, 0.818, and 0.779 in the training set, test set, and external validation, respectively. The calibration curve and DCA indicated appreciable reliability and good net benefits. The best three ML models were extra trees (ET), CatBoost, and random forest (RF) models; all of them showed favorable discrimination in the training cohort, and confirmed in the test and external sets.CONCLUSION:Baseline NIHSS, D-dimer, RBG, BUN, and SBP before reperfusion were independent predictors for 3-month unfavorable outcome after reperfusion therapy in AIS patients. Both nomogram and ML models showed good discrimination and generalizability.

Objective:To analyze risk factors for unfavorable outcomes after recanalization of large vessel occlusion (LVO) in patients with acute ischemic stroke (AIS).Methods:Patients with AIS-LVO who underwent recanalization treatment (including intravenous thrombolysis and endovascular intervention) at the Stroke Unit of Beijing Hospital from August 2018 to January 2022 were consecutively enrolled. According to the modified Rankin Scale (mRS) at 90-day follow-up after recanalization treatment, participants were classified as unfavorable outcomes (mRS>2) and favorable outcomes (mRS≤2). Baseline clinical data of enrolled patients was collected, and step-wise multivariate logistic regression analysis was used to identify independent risk factors for unfavorable outcomes after recanalization in AIS-LVO patients.Results:A total of 212 AIS-LVO patients were enrolled, including 86 females (41.35%), with an average age of 72.9 years. There were 75 patients in the favorable outcome group and 137 patients in the unfavorable outcome group. Compared with the favorable outcome group, the unfavorable outcome group had a higher average age, a higher proportion of females and patients with atrial fibrillation, higher baseline NIHSS, higher systolic blood pressure, and higher blood creatinine and D-dimer levels (all P<0.05). After adjusting for age and atrial fibrillation as confounding factors, multivariate logistic regression analysis showed that female ( OR=2.859, 95% CI: 1.202-6.799, P=0.018), higher baseline NIHSS ( OR=14.417, 95% CI: 6.269-33.158, P<0.001), higher pre-treatment systolic blood pressure ( OR=1.034, 95% CI: 1.015-1.054, P=0.001), higher emergency blood creatinine level ( OR=1.378, 95% CI: 1.105-1.719, P=0.005), and higher D-dimer level ( OR=3.594, 95% CI: 1.290-10.014, P=0.014) were independent risk factors for unfavorable outcomes after recanalization treatment in patients with AIS-LVO. Conclusion:Female, higher NIHSS, higher systolic blood pressure, higher blood creatinine level and D-dimer level are independent risk factors for unfavorable functional outcomes at 90 days after recanalization treatment of large vessel occlusion in patients with acute ischemic stroke.

Objectives: People with arteriosclerotic cardiovascular diseases (ASCVD) frequently use antithrombotic agents and statins. The objective of the study was to explore the prevalence and risk factors of cerebral microbleeds (CMBs) in elderly (>= 65 years old) Chinese people with ASCVD. Materials and methods: We prospectively included 755 eligible participants with complete MRI data, and CMBs were discerned on the SWI sequence. Multivariate logistic regression was performed to analyze risk factors associated with CMBs. Results: The average age was 74.9 +/- 9.5 years, and the prevalence of CMBs was 37.9% (286/755). Of those with CMBs, 65.0% (186/286) had strictly lobar CMBs, 35.0% (100/286) had deep or infratentorial CMBs with or without lobar CMBs. We divided CMBs into two groups according to their locations, lobar CMBs group (strictly lobar CMBs) and deep CMBs group (with or without lobar CMBs). Age per 10 years (odds ratio (OR) 1.42, 95% confidence interval (CI) 1.17-1.72, p < 0.001), statin use (OR 1.54, 95% CI 1.05-2.26, p = 0.03), and lacunes (OR 1.70, 95% CI 1.09-2.68, p = 0.02) were associated with any CMBs. Age per 10 years (OR 1.33, 95% CI 1.10-1.63, p < 0.001), statin use (OR 1.67, 95% CI 1.12-2.50, p = 0.01), and white matter hyperintensities (OR 1.71, 95% CI 1.17-2.51, p < 0.01) were associated with lobar CMBs. Only lacunes were associated with deep CMBs (OR 3.29, 95% CI 1.85-5.87, p < 0.001). Conclusions: In elderly people with risk factors of ASCVD, antithrombotic drug use was not associated with any CMBs, lobar CMBs, or deep CMBs. Statin use was correlated with lobar CMBs but not deep CMBs.

Purpose: The aim of this study was to verify the value of collateral circulation and B-type natriuretic peptide (BNP) in predicting clinical outcomes of patients with acute ischemic stroke (AIS) and their biomarker value for stroke subtypes before endovascular treatment (EVT). Patients and Methods: In this retrospective study, 182 patients who underwent EVT for unilateral anterior circulation large-vessel occlusion between March 2016 and January 2022 were analyzed. The modified collateral circulation scoring system on four-dimensional computed tomography angiography (4D CTA-CS) was used to assess collateral status, and stroke subtypes were determined according to the TOAST classification criteria. Patients were divided into good (mRS ≤ 2) and poor outcome (mRS > 2) groups based on their modified Rankin Scale (mRS) score at 3 months. Results: 4D CTA-CS was an independent predictor of the clinical outcome for all AIS patients (odds ratio = 0.253; 95% CI, 0.147–0.437; p < 0.001), CE stroke patients (odds ratio = 0.513; 95% CI, 0.280–0.939; p = 0.030), and LAA stroke patients (odds ratio = 0.148; 95% CI, 0.049–0.447; p = 0.001). The BNP was a biomarker for clinical outcome prediction in CE (odds ratio = 1.004; 95% CI, 1.001–1.008; p = 0.005) but not in LAA patients. Combined with BNP, 4D CTA-CS improved predictive values for clinical outcomes (p < 0.05). Conclusion: Collateral status and BNP could be used as independent predictors of clinical outcomes in AIS patients and could determine stroke subtypes (CE stroke or LAA stroke). In addition, the model of 4D CTA-CS combined with BNP was the most effective in predicting clinical outcomes compared with collateral status or BNP alone.

Previous studies have shown that exposure to black carbon (BC, a tracer of traffic-related air pollution) and psychosocial stress are both associated with adverse cardiac effects, but whether psychosocial stress could modify the cardiac effects of BC is unclear. To investigate the potential modifying effect of psychosocial stress on the associations between acute exposure to BC and typical cardiac health variables, real-time personal 24 h measurements were conducted in a repeated-measure study among adults with elevated blood pressure (high-risk group) and a panel study among normal adults (low-risk group) in China. Measured cardiac health variables included ST-segment depression events, heart rate, and heart rate variability (HRV) variables. Perceived Stress Scale, State Anxiety Inventory and Self-rating Depression Scale were used to assess the recent psychosocial stress status of the participants, and a composite stress index was established based on these scales. Generalized linear mixed-effects model was used to analyze the associations between BC exposure and cardiac health variables and potential effect modification by psychosocial stress. A total of 97 24 h measurements among 97 participants in the repeated-measure study and 202 24 h measurements among 87 participants in the panel study were included in the final analysis. Acute BC exposure was significantly associated with increased ST-segment depression events and heart rate and decreases in HRV in both studies. The marginal effects of acute BC exposure on most cardiac health variables generally tended to be amplified under higher vs low levels of psychosocial stress in both studies, with the composite stress index apparently modifying the associations of BC exposure with most ST-segment depression events and HRV variables. These findings suggest that psychosocial stress may increase the participants' cardiac susceptibility to BC exposure, which could be helpful for the identification of susceptible individuals in the context of traffic-related air pollution.

目的 对比分析基底动脉闭塞(basilar artery occlusion,BAO)所致急性缺血性卒中(acute ischemic stroke,AIS)患者接受血管再通治疗的有效性和安全性.方法 前瞻性收集于2018年8月至2021年1月在北京医院卒中单元就诊并接受血管再通治疗的颅内大动脉闭塞的AIS患者的病例资料.根据梗死部位和责任血管分为 BAO 组(BAO-AIS 患者)和前循环颅内动脉闭塞(anterior circulation intracranial artery occlusion,ACO)组(ACO-AIS患者).采用治疗后90 d改良Rankin评分(modified Rankin Scale,mRS)评估血管再通治疗后的功能预后,以评估再通治疗的有效性,采用血管再通治疗后出血转化和脑实质出血发生率评估再通治疗的安全性.对比分析两组队列间患者血管再通有效性和安全性指标的差异.结果 BAO组患者比ACO组患者合并心房颤动的比例更低(35.71％比59.21％,X2=4.558,P=0.033).两组间患者血管再通治疗后90 d mRS评分预后不良差异无显统计学意义(60.71％比65.57％,x2=0.211,P=0.646);BAO组梗死后出血转化率(21.43％比47.76％,x2=5.705,P=0.017)及脑实质出血率(3.57％比14.93％,P=0.031)比例均显著低于ACO组.结论 与ACO-AIS患者相比,BAO-AIS患者行血管再通治疗同样有效,且在出血转化方面安全性更好.

Background and aimsSecondary embolization (SE) during mechanical thrombectomy (MT) for cerebral large vessel occlusion (LVO) could reduce the anterior blood flow and worsen clinical outcomes. The current SE prediction tools have limited accuracy. In this study, we aimed to develop a nomogram to predict SE following MT for LVO based on clinical features and radiomics extracted from computed tomography (CT) images.Materials and methodsA total of 61 patients with LVO stroke treated by MT at Beijing Hospital were included in this retrospective study, of whom 27 developed SE during the MT procedure. The patients were randomly divided (7:3) into training (n = 42) and testing (n = 19) cohorts. The thrombus radiomics features were extracted from the pre-interventional thin-slice CT images, and the conventional clinical and radiological indicators associated with SE were recorded. A support vector machine (SVM) learning model with 5-fold cross-verification was used to obtain the radiomics and clinical signatures. For both signatures, a prediction nomogram for SE was constructed. The signatures were then combined using the logistic regression analysis to construct a combined clinical radiomics nomogram.ResultsIn the training cohort, the area under the receiver operating characteristic curve (AUC) of the nomograms was 0.963 for the combined model, 0.911 for the radiomics, and 0.891 for the clinical model. Following validation, the AUCs were 0.762 for the combined model, 0.714 for the radiomics model, and 0.637 for the clinical model. The combined clinical and radiomics nomogram had the best prediction accuracy in both the training and test cohort.ConclusionThis nomogram could be used to optimize the surgical MT procedure for LVO based on the risk of developing SE.

Objectives To evaluate the application of black-blood CT (BBCT) in carotid artery wall imaging and its accuracy in disclosing stenosis rate and plaque burden of carotid artery. Methods A total of 110 patients underwent contrast-enhanced CT scan with two phases, and BBCT images were obtained using contrast-enhancement (CE)-boost technology. Two radiologists independently scored subjective image quality on black-blood computerized tomography (BBCT) images using a 4-point scale and then further analyzed plaque types. The artery stenosis rate on BBCT was measured and compared with CTA. The plaque burden on BBCT was compared with that on high-resolution intracranial vessel wall MR imaging (VW-MR imaging). The kappa value and intraclass correlation coefficient (ICC) were used for consistency analysis. The diagnostic accuracy of BBCT for stenosis rate and plaque burden greater than 50% was evaluated by AUC. Results The subjective image quality scores of BBCT had good consistency between the two readers (ICC = 0.836, p < 0.001). BBCT and CTA had a good consistency in the identification of stenosis rate ( p < 0.001). There was good consistency between BBCT and VW-MR in diagnosis of plaque burden ( p < 0.001). As for plaque burden over 50%, BBCT had good sensitivity (93.10%) and specificity (73.33%), with an AUC of 0.950 (95%CI 0.838–0.993). Compared with CTA, BBCT had higher consistency with VW-MR in disclosing low-density plaques and mixed plaques (ICC = 0.931 vs 0.858, p < 0.001). Conclusions BBCT can not only display the carotid artery wall clearly but also accurately diagnose the stenosis rate and plaque burden of carotid artery. Clinical relevance statement Black-blood CT, as a novel imaging technology, can assist clinicians and radiologists in better visualizing the structure of the vessel wall and plaques, especially for patients with contraindication to MRI. Key Points • Black-blood CT can clearly visualize the carotid artery wall and plaque burden. • Black-blood CT is superior to conventional CTA with more accurate diagnosis of the carotid stenosis rate and plaque burden features.

Objective:To explore the significance of four-dimensional CT angiography(4D CTA) and CT perfusion (CTP) imaging in evaluating collateral circulation grades in patients with moyamoya disease and moyamoya syndrome and their relationship with cerebral hemodynamics.Methods:The clinical and imaging data of 32 patients with moyamoya disease and moyamoya syndrome in Beijing Hospital from January 2017 to January 2022 were retrospectively analyzed. All patients underwent 4D CTA-CTP imaging. Collateral circulation was scored on CTA images by using Alberta stroke program early CT score system, and on digital subtraction angiography (DSA) images by using American society of interventional and therapeutic neuroradiology/Society of interventional radiology score system, respectively. The patients were divided into Ⅰ-Ⅲ circulation compensation grades based on collateral circulation score. Regions of interest were delineated at basal ganglia on perfusion maps and the perfusion parameters were obtained including cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT), mean transit time (TTP) and delay time (DLY). The Kruskal-Wallis test was used to compare the perfusion parameters in different collateral circulation grades, and pairwise comparison was performed with Bonferroni correction. Kappa and Spearman tests were used to analyze the consistency and correlation of 4D CTA and DSA in the classification of collateral circulation.Results:4D CTA and DSA had a moderate consistency (Kappa=0.693, P<0.001) and a strong correlation ( r=0.805, P<0.001) in evaluating collateral grades. There were statistically significant differences in CBF, MTT and TTP among collateral compensation grade Ⅰ, grade Ⅱ and grade Ⅲ ( H values were 7.91, 11.69, 8.93; P values were 0.019, 0.003 and 0.012, respectively). Further pairwise comparison showed that the CBF of collateral compensation grade Ⅰ was lower than that of grade Ⅲ ( P=0.015), MTT of grade Ⅱ was higher than that of grade Ⅲ ( P=0.005), and TTP of grade Ⅰ was higher than that of grade Ⅲ ( P=0.015). There was no statistical significance of other indicators in pairwise comparison. There were no significant differences in CBV and DLY among collateral compensation grade Ⅰ, grade Ⅱ and grade Ⅲ ( P>0.05). Conclusions:4D CTA-CTP is equivalent to DSA in evaluating collateral circulation in patients with moyamoya disease and moyamoya syndrome. It can also evaluate the cerebral hemodynamics comprehensively, which has high clinical significance for disease monitoring.

Vulnerable carotid atherosclerotic plaque (CAP) significantly contributes to ischemic stroke. Neovascularization within plaques is an emerging biomarker linked to plaque vulnerability that can be detected using contrast-enhanced ultrasound (CEUS). Computed tomography angiography (CTA) is a common method used in clinical cerebrovascular assessments that can be employed to evaluate the vulnerability of CAPs. Radiomics is a technique that automatically extracts radiomic features from images. This study aimed to identify radiomic features associated with the neovascularization of CAP and construct a prediction model for CAP vulnerability based on radiomic features. CTA data and clinical data of patients with CAPs who underwent CTA and CEUS between January 2018 and December 2021 in Beijing Hospital were retrospectively collected. The data were divided into a training cohort and a testing cohort using a 7:3 split. According to the examination of CEUS, CAPs were dichotomized into vulnerable and stable groups. 3D Slicer software was used to delineate the region of interest in CTA images, and the Pyradiomics package was used to extract radiomic features in Python. Machine learning algorithms containing logistic regression (LR), support vector machine (SVM), random forest (RF), light gradient boosting machine (LGBM), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and multi-layer perception (MLP) were used to construct the models. The confusion matrix, receiver operating characteristic (ROC) curve, accuracy, precision, recall, and f-1 score were used to evaluate the performance of the models. A total of 74 patients with 110 CAPs were included. In all, 1,316 radiomic features were extracted, and 10 radiomic features were selected for machine-learning model construction. After evaluating several models on the testing cohorts, it was discovered that model_RF outperformed the others, achieving an AUC value of 0.93 (95% CI: 0.88-0.99). The accuracy, precision, recall, and f-1 score of model_RF in the testing cohort were 0.85, 0.87, 0.85, and 0.85, respectively. Radiomic features associated with the neovascularization of CAP were obtained. Our study highlights the potential of radiomics-based models for improving the accuracy and efficiency of diagnosing vulnerable CAP. In particular, the model_RF, utilizing radiomic features extracted from CTA, provides a noninvasive and efficient method for accurately predicting the vulnerability status of CAP. This model shows great potential for offering clinical guidance for early detection and improving patient outcomes.

目的 探讨全模型迭代(Forward Projected Model-Based Iterative Reconstruction Solution,FIRST)算法对腹部CT血管造影的图像质量改善情况.方法 回顾性分析于北京医院放射科行腹部CT血管造影检查的患者30例,分别对其图像进行不同算法的重建:滤波反投影算法(Filtered Back Projection,FBP)、混合迭代重建算法(Adaptive Iterative Dose Reduction 3D,AIDR 3D)和FIRST算法,并对3组图像进行最大密度投影后处理.采用单因素方差分析法对腹部主要血管及肌肉的CT值、噪声(Standard Deviation,SD)、信噪比(Signal to Noise Ratio,SNR)和对比噪声比(Contrast to Noise Ratio,CNR)进行对比,主要包括:第12胸椎水平的腹主动脉(Abdominal Aorta,AA)、腹腔干(Celiac Trunk,CT)、肠系膜上动脉(Superior Mesenteric,SMA)、肾动脉(Renal Artery,RA)、肝右动脉(Right Hepatic Artery,RHA)水平;在主观评价方面,由两名工作经验分别为7年及10年以上的放射科技师,通过双盲法按照5分标准进行评估,通过Kappa分析观察者间一致性,并采用Kruskal-Wallis检验分析3组图像之间的差异.结果 与FBP组和AIDR 3D组相比,FIRST组中腹腔干、肠系膜上动脉、肾动脉、背景(肌肉)的SNR、CNR值显著升高(P<0.001);3组腹腔干、肠系膜上动脉、肾动脉、肝右动脉、背景(肌肉)的CT值无统计学意义(P>0.05).在主观评分方面,FIRST组及AIDR 3D组均可满足诊断需要,主观评分均优于FBP组(P<0.05);此外,FIRST组的主观评分显著优于AIDR 3D组(P<0.05).结论 在腹部CT血管造影的重建算法中,与FBP和AIDR 3D相比,FIRST重建算法可以显著改善图像质量.

Objective:To investigate the risk factors of infarct growth rate of elderly acute ischemic stroke(AIS)patients with endovascular treatment(EVT)and its influence on prognosis.Methods:Elderly AIS patients who underwent EVT at Beijing hospital from June 2016 to October 2020 were retrospectively included.Infarct growth rate(ml/h)=infarct core volume(ml)/time from stroke onset to CTP examination(h).Based on the rate of infarct growth and the patient's clinical severity, ROC curve was established, and the cut-off value of the ROC curve was obtained.By the cut-off value of the rate of infarct growth, the patients were divided into cerebral infarct slow-growth group and rapid-growth group.Predictors of rapid growth in infarct were analyzed by univariate and multivariate analysis.The patients were divided into good prognosis group(mRS score 0-2)and poor prognosis group(mRS score 3-6)according to the mRS score at the day 90 and the predictors of poor prognosis were analyzed separately.Results:A total of 67 elderly AIS patients were included with age ranging from 65-96 years and an average of(78.8±7.6)years.(1)The cut-off value of the optimal infarct growth rate for patients with good and poor prognosis was 8.89 ml/h.The patients were divided into fast-growth group(26 patients)and slow-growth group(41 patients)according the cut-off value.(2)Multivariate logistic regression showed that only poor collateral circulation was an independent predictor for fast infarct growth( OR=0.162, 95% CI: 0.053-0.489).(3)Faster infarct growth rate( OR=1.173, 95% CI: 1.044-1.318)and high NIHSS score( OR=1.146, 95% CI: 1.018-1.291)were predictors of poor prognosis. Conclusions:Collateral circulation status is a major influencing factor for the infarct growth rate, and a faster infarct growth rate is a predictor of poor prognosis for elderly AIS patients after endovascular treatment.

目的探讨基于多模态CT及LASSO-Logistic回归的急性缺血性卒中患者血管内治疗术后发生恶性大脑中动脉梗死(MMI)的预测价值,并构建Nomogram预测风险评分系统.资料与方法回顾性分析2016年3月—2021年6月于北京医院急诊行一站式多模态CT血管造影-CT灌注扫描并进行血管内治疗的120例前循环闭塞的急性缺血性卒中患者,根据是否发生MMI分为MMI组24例及非MMI组96例.对临床及影像学资料行LASSO-Logistic回归方法筛选变量,探讨相关因素在MMI中的预测价值,并建立Nomogram图预测模型.建立受试者工作特征曲线及校准曲线验证其效能.结果与非MMI组比较,MMI组患者基线美国国立卫生研究院卒中量表评分更高(Z=?4.071,P<0.001)、颈内动脉闭塞更多见(χ2=5.335,P=0.021)、再通不良占比更高(P<0.001)、梗死核心体积更大(Z=?6.672,P<0.001)、基线Alberta卒中项目早期CT评分更低(Z=?3.693,P<0.001)、4D CTA侧支循环评分更低(Z=?6.085,P<0.001)、血栓负荷评分更低(Z=?2.853,P=0.004).通过LASSO-Logistic回归筛选出MMI的独立预测因子为改良脑梗死溶栓分级(OR=22.098,95％CI 3.100～157.503,P=0.002)、梗死核心体积(OR=1.022,95％CI 1.008～1.037,P=0.002)及4D CTA侧支循环评分(OR=0.288,95％CI 0.128～0.647,P=0.003);基于三者构建的Nomogram模型的曲线下面积为0.965(95％CI 0.915～0.990,P<0.001).校准曲线及Hosmer-Lemeshow检验(P=0.878)显示该模型具有较好的预测符合度.结论未成功再通、较大梗死核心体积及低4D CTA侧支评分的急性缺血性卒中患者行血管内治疗后更易发生MMI,基于三者构建的Nomogram风险预测模型可以判断其MMI风险,指导医师的临床决策.