AI learns to spot Crohn's on MRI in new pilot study
NCT ID NCT03706664
First seen Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 1 time
Summary
This pilot study is testing whether a deep learning algorithm can identify and score inflamed segments of the terminal ileum in MRI scans of people with Crohn's disease. Researchers will use 226 anonymized MRI scans, with radiologists first marking normal and abnormal areas. The algorithm's performance will be compared to the radiologists' labels. If it works, the algorithm could eventually help speed up and improve the accuracy of Crohn's diagnosis and monitoring.
What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
Active substance
machine learning algorithm
What this could lead to
If successful, this could lead to a tool that helps radiologists diagnose and monitor Crohn's disease more quickly and accurately.
What could go wrong
This is an early pilot study with only 226 patients. The algorithm may not work as well in real-world settings or on different types of MRI machines.
Disclaimer
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Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
This is a summary of the original study . Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
Contacts and locations
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Locations
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St Mark's Hospital
London, Harrow, HA13UJ, United Kingdom