Vision-language AI to diagnose brain diseases from imaging and clinical data
Official title: A Vision-Language Foundation Model for Brain Disease Diagnosis From Multimodal Data
Run by Xiangya Hospital of Central South University · NCT07126821 · Data updated 2026-11-12
This project will test a new AI that reads scans, pathology, genomics, and clinical records to help diagnose a wide range of brain diseases for patients with tumors, vascular problems, or neurodegeneration.
Quick facts
| Study type | Observational |
|---|---|
| Sex | All |
| Enrollment | 100000 (estimated) |
| Sponsor | Xiangya Hospital of Central South University Academic / other |
| Locations | 1 site (Changsha, Hunan) |
| Status | Recruiting |
| Started | May 15, 2025 |
| Main results expected | December 31, 2030 |
| Study ends | December 31, 2030 |
| Registry record updated | August 17, 2025 |
| Trial ID | NCT07126821 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are patients with accurately diagnosed brain diseases and complete clinical and imaging records, as well as control patients who have complete brain MRIs and no history of brain disease.
✕Probably not a fit
Patients with incomplete or heavily artifacted imaging, missing key clinical data, or cases outside the represented disease spectrum are unlikely to benefit and may be excluded.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational project will compile patient demographics, multimodal medical imaging (MRI, CT, PET), histopathology, genomic data when available, and other laboratory tests to train a vision-language foundation model. The model is being built to be explainable, provide uncertainty estimates, and automatically generate diagnostic-style reports to support clinicians. The dataset will include pathologically confirmed brain tumor cases, clinically confirmed other brain diseases, and non-brain-disease controls with complete imaging. An exploratory aim is to validate model performance using large-scale MRI cohorts for generalizability.
Why it matters
Potential benefit: If successful, the AI could help clinicians make faster, more consistent, and more transparent diagnoses across many brain diseases and produce draft reports to streamline care.
How similar studies have gone: AI tools have shown promising results for specific imaging tasks such as tumor segmentation and stroke detection, but a broad vision-language foundation model covering all brain diseases is largely novel and unproven.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: Patients with brain diseases: * Patients with brain tumors were pathologically diagnosed. * Patients with other brain diseases were correctly diagnosed. * The clinical case data of all patients were complete. Non-brain disease population: * All patients have complete clinical case data, complete brain MRI, no history brain diseases, no brain surgery or other brain diseases that affect the diagnosis and observation of MR imaging. Exclusion Criteria: * Cases in which MRI were incomplete or with significant noise and artifacts.
Where it's running
-
Xiangya Hospital of Central South University
Changsha, Hunan, China Recruiting
Study contacts
- Study coordinator: Xuan Gong, PhD.
- Email: gong.xuan@csu.edu.cn
- Phone: 0086-731-8975-3037
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.