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| ID | Type | Description | Link |
|---|---|---|---|
| 2026-2-4014 | Other Grant/Funding Number | Capital's Funds for Health Improvement and Research |
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| Name | Class |
|---|---|
| Institute of Automation, Chinese Academy of Sciences | OTHER |
| Beijing Zhongke Ruiyi Information Technology Co., Ltd. | UNKNOWN |
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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| BAD-related stroke cohort | Adults with acute ischemic stroke who meet predefined clinical-imaging diagnostic criteria for branch atheromatous disease-related stroke after central adjudication. |
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| Non-BAD stroke cohort | Adults with acute ischemic stroke who do not meet diagnostic criteria for BAD-related stroke and are included as the comparator cohort for model development and/or external validation. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Multisource clinical-imaging artificial intelligence diagnostic assessment | Diagnostic Test | 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. |
| Measure | Description | Time Frame |
|---|---|---|
| Overall diagnostic accuracy of the AI-assisted model for identifying BAD-related stroke | Overall diagnostic accuracy will be calculated as the proportion of participants correctly classified as BAD-related stroke or non-BAD acute ischemic stroke by the AI-assisted diagnostic model, using the independent central clinical-imaging adjudication as the reference standard. | Baseline acute phase, after completion of required clinical and neuroimaging assessments, within 7 days after symptom onset or last known well |
| Measure | Description | Time Frame |
|---|---|---|
| Overall accuracy of the early screening model for identifying possible BAD-related stroke | Overall accuracy will be calculated as the proportion of participants correctly classified as possible BAD-related stroke or non-BAD acute ischemic stroke by the early screening model at a prespecified decision threshold. The model will use only prespecified non-imaging clinical data available at enrollment or within 24 hours after admission. The reference standard will be independent central clinical-imaging adjudication according to predefined diagnostic criteria. |
| Measure | Description | Time Frame |
|---|---|---|
| Occurrence of early neurological deterioration | Early neurological deterioration was defined as an increase of more than 4 point in NIHSS score or more than 1 point in NIHSS motor score. | Within 7 days after enrollment |
| Modified Rankin Scale score at 90 days |
Inclusion Criteria:
Participants will be classified into the BAD-related stroke cohort if they meet all predefined BAD-related stroke diagnostic criteria, including:
Participants with acute ischemic stroke who do not meet BAD-related stroke criteria will be classified into the non-BAD acute ischemic stroke cohort.
Exclusion Criteria:
General exclusion criteria for all participants:
Additional criteria that preclude classification as BAD-related stroke:
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The study population will include adults aged 18 to 80 years with acute ischemic stroke who present within 1 week after symptom onset or last known well time at participating stroke centers. Participants will be classified as BAD-related stroke or non-BAD acute ischemic stroke according to predefined diagnostic criteria and independent central clinical-imaging adjudication.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Shengde Li, MD | Contact | 010-69156371 | lishengde.medicine@qq.com |
| Name | Affiliation | Role |
|---|---|---|
| Jun Ni, MD | Peking Union Medical College Hospital | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Beijing Fangshan District Liangxiang Hospital | Recruiting | Beijing | China |
Individual participant data will not be shared because the study involves sensitive multicenter clinical and multimodal neuroimaging data from patients with acute ischemic stroke, with residual re-identification risks even after de-identification. Data sharing is restricted by informed consent, ethics approvals, multicenter data-use agreements, institutional policies, and applicable privacy and cybersecurity regulations. Aggregate study results or study-specific questions may be directed to the corresponding author, but participant-level data access is not included in the current IPD sharing plan.
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| ID | Term |
|---|---|
| D000083242 | Ischemic Stroke |
| D002544 | Cerebral Infarction |
| ID | Term |
|---|---|
| D020521 | Stroke |
| D002561 | Cerebrovascular Disorders |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
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| At enrollment, using non-imaging clinical data available within 24 hours after admission |
Functional outcome will be assessed using the modified Rankin Scale at 90 days. The distribution of scores and prespecified dichotomized outcomes may be summarized.
| 90 days after stroke onset |
| Beijing Haidian Hospital | Recruiting | Beijing | China |
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| Beijing Huaxin Hospital (The First Hospital of Tsinghua University) | Recruiting | Beijing | China |
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| Beijing Jingmei Group General Hospital | Recruiting | Beijing | China |
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| Beijing Longfu Hospital | Recruiting | Beijing | China |
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| Beijing Puren Hospital | Recruiting | Beijing | China |
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| Beijing Shijingshan Hospital | Recruiting | Beijing | China |
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| Beijing Shijitan Hospital, Capital Medical University | Recruiting | Beijing | China |
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| Beijing Sixth Hospital | Recruiting | Beijing | China |
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| Beijing Yanqing District Hospital | Recruiting | Beijing | China |
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| Peking Union Medical College Hospital | Recruiting | Beijing | China |
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| D009422 |
| Nervous System Diseases |
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |
| D020520 | Brain Infarction |
| D002545 | Brain Ischemia |
| D007238 | Infarction |
| D007511 | Ischemia |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D009336 | Necrosis |