Superb Microvascular Imaging-based nomogram for acute stroke risk prediction in carotid plaque: integrating ultrasonic neovascularization and clinical biomarkers

Abstract

Aims: This study aimed to develop and validate an effective nomogram combining clinical biomarkers and carotid plaque’s superb microvascular imaging (SMI) features for predicting acute ischemic stroke.

Material and methods: In this study, 326 patients with carotid plaque were enrolled, and all patients were divided into two datasets for training and validation. We constructed an integrated nomogram combining clinical and ultrasound characteristics of carotid plaque using LASSO regression and multivariable logistic regression to predict acute ischemic stroke.

Results: LASSO regression combined with multivariate logistic regression indicated that smoking index, stroke duration, diabetes duration, monocytes/lymphocyte ratio, the surface condition and SMI neovascularization level of plaque were independently related to acute ischemic stroke. The area under the curve for the nomogram to predict AIS was 0.839 (95% CI,0.789-0.888) in the training cohort, 0.785 (95% CI, 0.669-0.901) in the validation cohort.

Conclusions: Our proposed acute ischemic stroke nomogram shows favorable predictive value to patients with carotid artery plaques and has positive clinical significance in individualized scientific management.