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Early Identification and Diagnosis of BAD-related Stroke

NCT07693816 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 1602

Last updated 2026-07-09

No results posted yet for this study

Summary

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.

Conditions

  • Branch Atheromatous Disease
  • Acute Ischemic Stroke
  • Cerebral Infarction

Interventions

DIAGNOSTIC_TEST

Multisource clinical-imaging artificial intelligence diagnostic assessment

The diagnostic assessment consists of artificial intelligence-assisted analysis of routinely collected clinical, laboratory, cardiovascular, and multimodal neuroimaging data to estimate the probability of BAD-related stroke. The model output will be compared with an independent central clinical-imaging reference diagnosis. The model will not determine treatment assignment in this observational study.

Sponsors & Collaborators

  • Institute of Automation, Chinese Academy of Sciences

    collaborator OTHER

  • Beijing Zhongke Ruiyi Information Technology Co., Ltd.

    collaborator UNKNOWN

  • Peking Union Medical College Hospital

    lead OTHER

Principal Investigators

  • Jun Ni, MD · Peking Union Medical College Hospital

Eligibility

Min Age
18 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-07-15
Primary Completion
2028-01-31
Completion
2028-12-31

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07693816 on ClinicalTrials.gov