An Explainable Neuroradiologist Artificial Intelligence Assistance System for Brain CT and MRI

NCT07167043 | Enrolling By Invitation DMC

• 1 other identifier: 2025-A09
• Study Type: observational
• Target: 30,000
• Locations: 1 country
• Sites: 1

Brief Summary

This clinic trial aims to validate the working performance of radiologists with or without artificial intelligence (AI) diagnostic tool at neurological diseases diagnosis on brain CT/MRI. Routine diagnosis workflow in real clinical scenario including imaging reading, feature interpretation, differential diagnosis, writing initial report and optimizing revised version. And the gold standards of diagnosis are the histopathology references for brain tumors and the discharge diagnosis integrating all the examination results for the other neurological diseases. The performance of AI-assisted tools on diagnosing should be examined in a clinical process with multiple aspects identical to human radiologists' work before being transformed and putted to use. This study hypothesizes that AI models, trained with over 100,000 patient scans, are non-inferior to radiologists in neurological disease diagnosis on brain CT and MRI. For the secondary end-points, we investigate the performance of AI-radiologist collaboration of reasoning-enhanced AI-assisted systems. We hypothesize that, by visualizing the process of imaging interpretation and diagnosis, reasoning-enhanced AI can not only improve working performance of radiologists but also boost their trust in AI tools.

Conditions

Central Nervous System Disease; MRI; CT; AI (Artificial Intelligence); Radiology

Outcome Measures

Primary Outcomes (2)

• AI tools vs Radiologists from Clinical silence trial

  Diagnostic performance of AI models and over 50 radiologists from the Clinical silence trial study, at neurological diseases on brain CT/MRI, with respect to histopathology and discharge diagnosis as reference, to assess the working performance of neuroimaging AI diagnostic tools.

  6 months

• AI-assisted diagnostic tool collaborates with Radiologists in clinical workflow

  Working efficiency (time taking) and diagnostic confidence and accuracy of radiologists from AI-radiologist collaboration study, at neurological diseases on brain CT/MRI, to assess the clinical viability of AI-assisted diagnostic tool.

  6 months

Secondary Outcomes (2)

• Present AI vs the other AI tools uploaded from Clinical silence trial

  6 months

• Reasoning-enhanced AI model collaborates with Radiologists in clinical workflow

  6 months

Interventions

AI-assisted diagnostic systems DIAGNOSTIC_TEST

Diagnosing neurological diseases on CT/MRI with and without AI-assisted tools

Eligibility Criteria

• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

All patient exams are of men suspected of harboring brain tumors or the other neurological diseases, with or without neurological symptoms, and without a history of prior brain surgery. Patients underwent brain CT and MRI, and were primarily examined at Beijing Tiantan hospital, between 2012-2026.

You may qualify if:

• For MRI: patients suspected of harboring brain tumors or detected with brain occupancy at initiating or other institution, who subsequently underwent brain MRI.
• For CT: patients with or without neurological symptoms, suspected of harboring ischemic, hemorrhagic, space-occupiing, degenerative brain disease, or traumatic brain injury, who subsequently underwent brain CT.

You may not qualify if:

• Patients who opted-out or did not give permission to reuse clinical data.
• Patients with a history of prior brain surgery.
• Patients whose brain CT or MRI exhibit severe artifacts (e.g. heavy warping due to air, metal artifacts, heavy motion artifacts), thereby impeding the usage of the data.

Sponsors & Collaborators

• Yaou Liu: lead

Study Sites (1)

Beijing Tiantan Hospital

Beijing, China

Location

Biospecimen

Retention: SAMPLES WITH DNA

Biospecimen is not stored beyond the timeframe of this study, for the purpose of this study. However, biospecimen is stored beyond the timeframe of this study, for the purpose of regular clinical care. In this case, biospecimen refers to histopathology tissue acquired from confirmatory brain biopsies. Within the scope of clinical routine, storing such specimen can facilitate reassessments through the future, e.g. for comparisons if the patient presents new findings or metastasis of their initial findings, for comparisons against histopathology findings of the original patient's offspring, or even for legal purposes in the case of misdiagnosis.

MeSH Terms

Conditions

Central Nervous System Diseases

Condition Hierarchy (Ancestors)

Nervous System Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: OTHER
• Target Duration: 5 Years
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Director of the Radiology Department

Study Record Dates

• First Submitted: September 3, 2025
• First Posted: September 11, 2025
• Study Start: May 1, 2025
• Primary Completion (Estimated): October 1, 2030
• Study Completion (Estimated): December 1, 2030
• Last Updated: September 11, 2025

Record last verified: 2025-09

Locations

CN (1)