Brain (Nervous System) CancersNCT07126821
A Vision-Language Foundation Model for Brain Disease Diagnosis From Multimodal Data
An observational study of Brain (Nervous System) Cancers and Brain Arterial Disease, run by Xiangya Hospital of Central South University at 1 site in China.
Trial summary
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. Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Brain (Nervous System) Cancers, Brain Arterial Disease, Neuro-Degenerative Disease
- How many people
- 100,000 participants
- Where
- 1 siteChina
- Study dates
- 15 May 2025to 31 Dec 2030
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Study population: Patients with brain disease or Non-disease condition
Who may be able to join
- 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.
Who cannot join
- Cases in which MRI were incomplete or with significant noise and artifacts.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
Xiangya Hospital of Central South University
Changsha, Hunan, 410008
Xuan Gong, PhD., 0086-731-8975-3037, gong.xuan@csu.edu.cn
Zhou Chen, PhD., 0086-13687397913, czad0412@163.com
About this study
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.
Read the detailed 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.
- Conditions
- Brain (Nervous System) Cancers, Brain Arterial Disease, Neuro-Degenerative Disease, Brain Tumors, Brain Diseases, Neurological di
- Being tested
- No Interventions
- Keywords
- brain tumors, brain cancers, brain diseases, foundation model, diagnosis, prediction, neurological diseases
- Medical subject headings
- Neurologic Manifestations, Neoplasms, Intracranial Arterial Diseases, Brain Neoplasms, Brain Diseases, Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
No InterventionsOther
No Interventions
What is being measured
The primary outcome is the main question the study is designed to answer.
Brain Disease Diagnostic performance
This study will evaluate how accurately the AI model can identify and differentiate between: 1. Brain tumors including gliomas, glioneuronal tumors, and neuronal tumor, meningioma, germ cell tumors, embryonal tumors, tumors of the sellar region, pineal region tumors, mesenchymal, non-meningothelial tumors, choroid plexus tumors, hematolymphoid tumors, cranial and paraspinal nerve tumors, melanocytic tumors and brain metastases based on WHO CNS 5 classification; 2. Brain diseases apart from brain tumors such as brain arterial disease, neurodegenerative disorders, etc.; 3. Normal brain findings; The model's performance will be assessed using sensitivity, specificity, F1-score AUC-ROC. Diagnostic ability of AI model will be compared against with pathological diagnosis(if possible), final clinical diagnoses by neurologists or radiologists.
Measured: Perioperative
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 Aug 2025
- Study start15 May 2025
- Primary completion31 Dec 2030 (estimated)
- Study completion31 Dec 2030 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Brain (Nervous System) CancersStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case only
- Time perspective
- Retrospective
- Enrolment
- 100,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Xiangya Hospital of Central South University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Xuan Gong, Xiangya Hospital of Central South University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07126821
- Sponsor's protocol ID
- 2025030464
- Status last verified
- Aug 2025
- First submitted
- 31 Jul 2025
- Last updated
- 17 Aug 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 17 Aug 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Vision-Language Foundation Model for Brain Disease Diagnosis From Multimodal Data
- ClinicalTrials.gov ID
- NCT07126821
- Acronym / sponsor ID
- 2025030464
- Conditions
- Brain (Nervous System) Cancers, Brain Arterial Disease, Neuro-Degenerative Disease, Brain Tumors, Brain Diseases, Neurological di
- Keywords
- brain tumors, brain cancers, brain diseases, foundation model, diagnosis, prediction, neurological diseases
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 100,000 participants (estimated)
- Lead sponsor
- Xiangya Hospital of Central South UniversityUniversity, hospital or other
- Study start
- 15 May 2025 (actual)
- Primary completion
- 31 Dec 2030 (estimated)
- Study completion
- 31 Dec 2030 (estimated)
- First posted
- 17 Aug 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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
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.
Study design
- Observational model
- Case only
- Time perspective
- Retrospective
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Patients with brain disease or Non-disease condition
Key inclusion criteria (6 listed)
- Patients with brain tumors were pathologically diagnosed.
- Patients with other brain diseases were correctly diagnosed.
- The clinical case data of all patients were complete.
- 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.
Key exclusion criteria (1 listed)
- Cases in which MRI were incomplete or with significant noise and artifacts.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| No InterventionsNo Interventions | Other | – |
Primary outcome
Brain Disease Diagnostic performance
Time frame: Perioperative
This study will evaluate how accurately the AI model can identify and differentiate between: 1. Brain tumors including gliomas, glioneuronal tumors, and neuronal tumor, meningioma, germ cell tumors, embryonal tumors, tumors of the sellar region, pineal region tumors, mesenchymal, non-meningothelial tumors, choroid plexus tumors, hematolymphoid tumors, cranial and paraspinal nerve tumors, melanocytic tumors and brain metastases based on WHO CNS 5 classification; 2. Brain diseases apart from brain tumors such as brain arterial disease, neurodegenerative disorders, etc.; 3. Normal brain findings; The model's performance will be assessed using sensitivity, specificity, F1-score AUC-ROC. Diagnostic ability of AI model will be compared against with pathological diagnosis(if possible), final clinical diagnoses by neurologists or radiologists.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 Aug 2025.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Brain (Nervous System) Cancers and Brain Arterial Disease, run by Xiangya Hospital of Central South University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 17 Aug 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Xuan Gong, PhD. (0086-731-8975-3037, gong.xuan@csu.edu.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Brain Disease Diagnostic performance (time frame: Perioperative). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 17 Aug 2025.