关键词:

短暂性脑缺血发作, 脑梗死, CT灌注成像, Nomogram模型, 预测

Abstract:

Objective　To develop a risk prediction model combining whole-brain CT perfusion parameters and clinical characteristics for transient ischemic attack (TIA)-related ischemic stroke, and to evaluate its predictive performance and clinical applicability. Methods　This retrospective study collected the data of 304 patients with TIA treated at No.215 Hospital of Shaanxi Nuclear Industry between January 2019 and January 2024. There were 172 males and 132 females. They were (55.26±11.96) years old. According to whether they had cerebral infarction, the patients were divided into an infarction group (51 cases) and a non-infarction group (253 cases). The whole-brain CT perfusion parameters [cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), and time to peak (TTP)] were obtained using the Philips Brilliance iCT (256-slice) system. The multivariate logistic regression analysis was performed to construct a Nomogram prediction model based on the CT perfusion parameters and clinical characteristics (ABCD2 score, history of hypertension and hyperlipidemia, etc.). Statistical comparisons were conducted using t-test, rank sum tests, χ² test, and Spearman correlation analysis. The predictive performance of the model was evaluated using the receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA). Results　The multivariate logistic regression analysis showed that frequency of ischemic episodes, ABCD2 score, CBF, CBV, MTT, history of hypertension and hyperlipidemia, atrial fibrillation, and carotid artery stenosis were the independent risk factors (all P<0.05). The area under the curve of the Nomogram model was 0.962 (95%CI 0.941-0.984); the C-index was 0.900 (95%CI 0.854-0.945). The calibration curve demonstrated good agreement between the predicted and actual outcomes, and the DCA showed clinical benefit across a risk threshold range of (0-97)%, with a maximum net benefit of 83.22%. Conclusion　The Nomogram model, combining whole-brain CT perfusion parameters and clinical characteristics, can accurately predict the risk of ischemic stroke secondary to TIA, has high predictive performance and clinical utility, and can provide scientific references for early intervention strategies.

Key words:

Transient ischemic attack, Cerebral infarction, CT perfusion imaging, Nomogram model, Prediction