Central Nervous System DiseaseMRICTAI (Artificial Intelligence)Radiology
Investigational drug(s) / intervention(s)
AI-assisted diagnostic systems
AI-assisted diagnostic systems: Diagnosing neurological diseases on CT/MRI with and without AI-assisted tools
Study 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.
Eligibility
Sex
ALL
Min age
—
Max age
—
Healthy volunteers
Accepted
Inclusion Criteria:
* 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.
Exclusion Criteria:
* 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.
Primary outcome measure(s)
AI tools vs Radiologists from Clinical silence trial — 6 months 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.
AI-assisted diagnostic tool collaborates with Radiologists in clinical workflow — 6 months 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.
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
We use cookies to analyse site traffic and improve your experience. With your consent, we may also use cookies for advertising. You can change your choice at any time on our Cookie Policy page. See also our Privacy Policy.