Refined imaging features of culprit plaques improve the prediction of recurrence in intracranial atherosclerotic stroke within the middle cerebral artery territory

Abstract

Recurrence is a significant adverse outcome of ischemic stroke (IS), particularly in cases of intracranial arteriosclerosis (ICAS). In this study, we investigated the impact of imaging features of culprit plaque using high-resolution magnetic resonance vessel wall imaging (HR-MR-VWI) on the prediction of IS recurrence. A total of 86 patients diagnosed with ICAS-related IS within the middle cerebral artery (MCA) territory were included, of which 23.25% experienced recurrent IS within one year. Our findings revealed significant differences between the recurrence and non-recurrence groups in terms of age (p = 0.007), diabetes mellitus (p = 0.031), hyperhomocysteinemia (p = 0.021), artery-artery embolism (AAE) infarction (p = 0.019), prominent enhancement (p = 0.013), and surface irregularity of the culprit plaque (p = 0.009). Age (HR = 1.063, p = 0.005), AAE infarction (HR = 5.708, p = 0.008), and prominent enhancement of the culprit plaque (HR = 4.105, p = 0.025) were identified as independent risk factors for stroke recurrence. The areas under the receiver operating characteristic curve (AUCs) for predicting IS recurrence using clinical factors, conventional imaging findings, HR-MR-VWI plaque features, and a combination of clinical and conventional imaging models were 0.728, 0.645, 0.705, and 0.814, respectively. Notably, the combination model demonstrated superior predictive performance with an AUC of 0.870. Similarly, AUC of combination model for predicting IS recurrence in validation cohort which enrolled another 37 patients was 0.865. In conclusion, the presence of obvious enhancement in culprit plaque on HR-MR-VWI is a valuable factor in predicting IS recurrence in ICAS-related strokes within the MCA territory. Furthermore, our combination model, incorporating plaque features, exhibited improved prediction accuracy.