磁共振成像2026，Vol.17Issue(9)：5-15,11.DOI:10.12015/issn.1674-8034.2026.09.002
基于胸部CT体成分分析联合酰胺质子转移加权成像预测急性缺血性卒中患者功能预后的价值
The value of chest CT-derived body composition analysis combined with amide proton transfer-weighted imaging in predicting functional outcomes in patients with acute ischemic stroke
摘要
Abstract
Objective:To explore the value of chest CT-derived body composition analysis combined with amide proton transfer-weighted(APTw)imaging in assessing the functional prognosis of patients with acute ischemic stroke(AIS).Materials and Methods:This prospective study enrolled 108 AIS patients(age 62.96±9.55 years).All patients underwent both head APTw imaging and chest CT scans.Functional outcomes were assessed using the 90-day modified Rankin scale(mRS)and patients were dichotomized into a favorable prognosis group(mRS≤2,n=58)and an unfavorable prognosis group(mRS>2,n=50).Body composition analysis based on non-contrast chest CT images included epicardial adipose tissue(EAT),visceral adipose tissue at the 12th thoracic vertebra level(VAT_T12),subcutaneous adipose tissue at the 12th thoracic vertebra level(SAT_T12),and skeletal muscle at the 12th thoracic vertebra level(SM_T12).Quantitative parameters derived from the APTw images[including the maximum values of APT(APTwmax_lesion and APTwmax_contralateral side),minimum values(APTwmin_lesion and APTwmin_contralateral side),average values(APTwmean_lesion and APTwmean_contralateral side),and the APTwmax-min value in the infarct core and contralateral normal white matter]were assessed.Differences in quantitative parameters between groups were evaluated using independent samples t-tests or the Mann-Whitney U test.Univariate and multivariate logistic regression analyses were performed to screen for independent predictors associated with AIS functional prognosis,and a nomogram model was constructed accordingly.The predictive performance of the model was assessed using the receiver operating characteristic(ROC)curve,calculating the area under the curve(AUC),accuracy,sensitivity,and specificity.Differences in AUC values between models were compared using DeLong's test.Calibration curves were used to evaluate the deviation between predicted and actual probabilities,and the Hosmer-Lemeshow test was employed to assess model goodness-of-fit(P>0.05 indicating good fit).The clinical utility of the model was evaluated using decision curve analysis(DCA).The importance of each feature within the nomogram model was interpreted using SHapley additive explanations(SHAP).Results:Based on 90-day mRS scores,patients were categorized into the favorable prognosis group(n=58,mRS:0-2)and the unfavorable prognosis group(n=50,mRS:3-6).Apart from admission mRS(t=3.782,P<0.001)and National Institutes of Health Stroke Scale(NIHSS)(t=2.743,P=0.006),other clinical characteristics showed no significant differences between groups.Body composition analysis revealed that patients in the unfavorable prognosis group had significantly higher epicardial adipose tissue volume(EATV)and visceral adipose tissue area at the 12th thoracic vertebra level(VAT_T12)(t=4.948,3.765,P<0.001),but lower attenuation values for EAT,VAT_T12,and SM_T12(t=-3.025,P=0.002;t=-2.434,P=0.015;t=-2.350,P=0.021,respectively)compared to the favorable prognosis group.Analysis of APTw-derived quantitative parameters showed significantly lower APTwmin_lesion(t=-3.036,P=0.002)and higher APTwmax-min_lesion(t=2.365,P=0.018)values in the unfavorable prognosis group.After screening for multicollinearity[variance inflation factor(VIF)<5],multivariate logistic regression identified admission mRS score[OR=2.726(95%CI:1.347 to 5.517),P=0.005],EATV[OR=1.019(95%CI:1.002 to 1.036),P=0.026],and APTwmin_lesion[OR=0.236(95%CI:0.084 to 0.662),P=0.006]as independent predictors of unfavorable prognosis.A nomogram model was subsequently constructed.The AUC values for predicting AIS functional prognosis were 0.704,0.777,0.670,and 0.873 for the individual independent predictors and the combined nomogram model,respectively.The calibration curve(Hosmer-Lemeshow test X-squared=10.533,P=0.230)and DeLong's test(P<0.05)confirmed that the nomogram model's predicted probabilities were highly consistent with the actual outcomes and that its performance was superior to that of individual predictors.The DCA curve demonstrated that the nomogram model provided the optimal net clinical benefit across all threshold probabilities.SHAP analysis revealed that the order of feature contribution to the nomogram model was EATV,followed by APTwmin_lesion,and then admission mRS score.Conclusions:The combination of chest CT-derived body composition analysis and APTw imaging provides a comprehensive assessment of AIS functional prognosis from dual perspectives:local brain injury characteristics and systemic metabolic reserve status.This approach offers a more reliable multi-dimensional imaging basis for the early and precise identification of patients at high risk for unfavorable outcomes,thereby providing a basis for risk stratification and health management in AIS patients.关键词
急性缺血性脑卒中/体质成分分析/定量计算机断层扫描/磁共振成像/酰胺质子转移加权成像/功能预后Key words
acute ischemic stroke/body composition analysis/quantitative computed tomography/magnetic resonance imaging/amide proton transfer-weighted imaging/functional outcome分类
医药卫生引用本文复制引用
马长军,王家正,张钦和,黄依萍,刘嘉慧,王秀林,李颖,丛丰裕,刘爱连,刘晶..基于胸部CT体成分分析联合酰胺质子转移加权成像预测急性缺血性卒中患者功能预后的价值[J].磁共振成像,2026,17(9):5-15,11.基金项目
辽宁省科技计划联合计划项目(编号:2025-MSLH-199) （编号:2025-MSLH-199）
大连市科技人才创新支持项目(编号:2023RY034)Joint Research Program of Liaoning Provincial Science and Technology Plan(No.2025-MSLH-199) （编号:2023RY034）
Dalian Science and Technology Talent Innovation Support Project(No.2023RY034). （No.2023RY034）
