About this trial
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.
Eligibility criteria
Qualifiers
Age 18 to 80 years.
Diagnosis of acute ischemic stroke.
Time from symptom onset to enrollment ≤ 1 week; if the onset time is unknown, time from last known well to enrollment ≤ 1 week.
Availability of required baseline clinical and neuroimaging assessments according to the study protocol.
Disqualifiers
Intracranial hemorrhage, vascular malformation, aneurysm, brain abscess, malignant intracranial mass, or other non-ischemic intracranial lesion on baseline CT, MRI, MRA, CTA, or DSA.
Pre-stroke modified Rankin Scale score ≥2.
Life expectancy ≤6 months.
Unable to tolerate MRI examination.
Trial design
Treatments tested in this trial
- Multisource clinical-imaging artificial intelligence diagnostic assessment
Treatment groups
Sponsors and collaborators
Peking Union Medical College Hospital
Lead sponsor
Institute of Automation, Chinese Academy of Sciences
Collaborator
Beijing Zhongke Ruiyi Information Technology Co., Ltd.
Collaborator