Branch Atheromatous Disease

Branch atheromatous disease (BAD) is a distinct subtype of ischemic stroke that is particularly prevalent among Chinese and other Asian populations. Patients with BAD are prone to early neurological deterioration and poor functional outcomes, and BAD is increasingly recognized as an independent disease entity. However, the association between BAD and cognitive impairment remains unclear. This nationwide, multicenter, prospective observational study will prospectively collect epidemiological, clinical, neuroimaging, functional, and cognitive outcome data from patients with BAD. The study aims to investigate the occurrence of cognitive impairment after BAD and identify the clinical and neuroimaging characteristics associated with cognitive impairment. In particular, the relationship between early neurological deterioration (END) and cognitive impairment will be investigated. As an exploratory objective, this study will further explore the potential brain network mechanisms underlying cognitive impairment associated with END events.

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.