A Vision-Language Foundation Model for Brain Disease Diagnosis From Multimodal Data

Central South University

Status: Enrolling

Conditions: Neurological di; Neuro-Degenerative Disease; Brain (Nervous System) Cancers; Brain Tumors; Brain Arterial Disease; Brain Diseases

Treatments: Other: No Interventions

Study type: Observational

Funder types: Other

Identifiers

NCT07126821

2025030464

Details and patient eligibility

About

The goal of this observational study is to develop an innovative, comprehensive, and explainable AI vision-language foundation model (VLM) to advance the diagnosis and interpretation of brain diseases using multi-modal data. We will include patient demographics, medical imaging data (such as MRI, CT, and PET scans), histopathological data, genomic data when available, and other necessary laboratory examinations and tests to establish a screening and diagnostic model for brain diseases.

Full description

Secondary Objective: To establish a comprehensive diagnostic model with uncertainty quantification and automated report generation that covers all brain diseases based on clinical indicators.

Exploratory Objective: To include MRI scans from large-scale populations for model validation.

Enrollment: 100,000 estimated patients

Sex: All

Volunteers: Accepts Healthy Volunteers

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.