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

NCT ID: NCT07126821

Last Updated: 2025-08-17

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

100000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-05-15

Study Completion Date

2030-12-31

Brief Summary

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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.

Detailed Description

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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.

Conditions

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

Study Design

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Observational Model Type

CASE_ONLY

Study Time Perspective

RETROSPECTIVE

Interventions

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No Interventions

No Interventions

Intervention Type OTHER

Eligibility Criteria

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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.
Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Xiangya Hospital of Central South University

OTHER

Sponsor Role lead

Responsible Party

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Xuan Gong

Associate Consultant

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Xiangya Hospital of Central South University

Changsha, Hunan, China

Site Status RECRUITING

Countries

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China

Central Contacts

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Xuan Gong, PhD.

Role: CONTACT

0086-731-8975-3037

Zhou Chen, PhD.

Role: CONTACT

0086-13687397913

Facility Contacts

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Xuan Gong, PhD.

Role: primary

0086-731-8975-3037

Zhou Chen, PhD.

Role: backup

0086-13687397913

Other Identifiers

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2025030464

Identifier Type: -

Identifier Source: org_study_id

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