Early Identification and Diagnosis of BAD-related Stroke

Overview

Branch atheromatous disease (BAD)-related stroke is an important subtype of acute ischemic stroke involving penetrating arteries and is associated with early neurological deterioration. Early recognition and standardized diagnosis remain challenging in routine clinical practice because clinical symptoms are often non-specific and the diagnosis requires integrated clinical and imaging assessment. This multicenter prospective observational study will collect demographic, clinical, laboratory, electrocardiographic, ultrasound, and multimodal neuroimaging data from adults with acute ischemic stroke within 1 week of symptom onset. Participants will receive routine clinical care determined by their treating physicians; no treatment or management strategy will be assigned by the study protocol. An independent central clinical-imaging adjudication committee will classify participants as BAD-related stroke or non-BAD acute ischemic stroke according to predefined diagnostic criteria. The study aims to develop and externally validate artificial intelligence-assisted screening and diagnostic models for BAD-related stroke and to evaluate their discrimination, calibration, and potential clinical utility.

Branch atheromatous disease (BAD)-related stroke has been increasingly recognized as a clinically meaningful subtype of acute ischemic stroke. It typically presents as a single subcortical infarction in the territory of penetrating arteries, especially the lenticulostriate arteries and paramedian pontine arteries. Because BAD-related stroke is not well captured by conventional etiologic classification systems and because its early diagnosis requires standardized interpretation of clinical and neuroimaging features, delayed or inconsistent recognition may limit subsequent precision-management research. This study is designed as a multicenter, prospective, observational cohort study. Eligible adults with acute ischemic stroke will be enrolled within 1 week after symptom onset or last known well time. Multisource data will be collected, including demographics, vascular risk factors, baseline neurological assessments, laboratory tests, electrocardiography, carotid/cardiac ultrasound, routine brain MRI, intracranial vascular imaging by MRA/CTA/DSA when available, high-resolution vessel wall MRI when available, ASL perfusion imaging when available, acute-phase treatment information, early neurological deterioration, and 90-day functional outcomes. The study will include two predefined diagnostic cohorts: participants with BAD-related stroke and participants with non-BAD acute ischemic stroke. BAD-related stroke will be adjudicated by an independent central clinical-imaging committee according to predefined imaging and etiologic criteria. The reference diagnosis will be based on baseline and follow-up clinical information, neuroimaging, vascular imaging, cardiac evaluation, and 90-day follow-up information when applicable. Artificial intelligence-assisted models will be developed and validated to support early screening and diagnostic classification of BAD-related stroke. The early screening model will use non-imaging or routinely available acute-phase clinical information, whereas the diagnostic model will integrate multisource clinical and imaging information. Model performance will be evaluated in an external validation cohort using discrimination, sensitivity, specificity, accuracy, calibration, and decision curve analysis. The study protocol does not assign any therapeutic intervention, diagnostic procedure beyond routine or protocol-specified observational assessments, or clinical management strategy. All treatments will be determined by the treating physicians according to local practice and applicable guidelines.