Detecting hidden brain diseases using artificial intelligence
Official title: Covert Cerebrovascular Disease Detected by Artificial Intelligence (C2D2AI): Pragmatic Neuroimaging Biomarkers for Future Stroke and Dementia Risk
Funded at Tufts Medical Center · NIH-11035080 · Data updated 2026-11-12
This study is looking to find hidden brain problems that can lead to strokes and memory issues by using advanced imaging and smart computer technology, so we can help people catch these risks early and stay healthier longer.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Tufts Medical Center NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | February 15, 2024 |
| Project end | January 31, 2028 |
| Funding year | 2025 |
| Award (this year) | $713,385 |
| NIH project number | 5R01NS134859-02 |
| Project ID | NIH-11035080 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals who have undergone neuroimaging scans and may have undetected covert cerebrovascular disease.
✕Less likely to help
Patients who do not have access to neuroimaging or those without risk factors for cerebrovascular disease may not benefit from this research.
What this research studies
This research focuses on identifying covert cerebrovascular disease (CCD), which includes covert brain infarction and white matter disease, through advanced neuroimaging techniques and artificial intelligence. By analyzing routine clinical scans, the study aims to uncover these hidden conditions that are often missed but can significantly increase the risk of future strokes and dementia. The approach involves using AI algorithms to improve the detection and understanding of these diseases, ultimately helping to identify individuals at high risk before they experience severe cognitive decline.
Why it matters
Potential benefit: If successful, this research could lead to earlier detection and intervention for patients at risk of stroke and dementia, potentially improving their long-term health outcomes.
How similar studies have gone: Previous studies have shown promise in using AI for medical imaging, suggesting that this approach could be effective in detecting covert cerebrovascular diseases.
Where this research is happening
-
Tufts Medical Center
Boston, United States Active
Researchers
- Principal investigator: Kent, David M — Tufts Medical Center
- Study coordinator: Kent, David M
Related research
Other NIH-funded projects on the same topics.
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Finding hidden small strokes and white matter damage on routine brain scans with AI
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AI detects hidden brain blood-vessel damage linked to stroke and dementia
This project uses AI to find hidden small strokes and white-matter changes on routine brain scans in older adults to help prevent future stroke and dementia.
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Using artificial intelligence to find hidden brain diseases that could lead to strokes and dementia
This study is looking to find hidden brain problems that could lead to stroke or dementia by using smart computer techniques to analyze brain scans and reports, helping doctors catch these issues early and improve treatment for patients.
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BBB Dysfunction after Stroke and Risk for Dementia
A study at Stanford will look at whether inflammation after a stroke leads to leaky blood vessels and later dementia, by following stroke survivors and comparing them with people without stroke.
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DNMT3a and oligodendrocyte renewal after stroke
A patient-focused study will explore how a specific gene, DNMT3a, might help repair brain white matter after a stroke to reduce dementia risk.
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BBB Dysfunction after Stroke and Dementia Risk
This NIH grant aims to understand why some people develop dementia years after a stroke by looking at brain inflammation and blood vessel leakage.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.