Small Bowel Deep Learning Algorithm Project (NCT03706664) | Clinical Trial Compass
Active — Not RecruitingNot Applicable
Small Bowel Deep Learning Algorithm Project
United Kingdom226 participantsStarted 2019-03-01
Plain-language summary
Crohn's disease affects 200,000 people in the UK (\~1 in 500), most are young (diagnosed \< 35 years) with costs of direct medical care exceeding £500 million.
Crohn's disease is caused by an auto-immune response and affects any part of the digestive tract, most commonly the last segment of the small bowel (the terminal ileum).
Magnetic resonance imaging (MRI) plays a role in 3 areas: Crohn's disease diagnosis , monitoring treatment response \& assessing development of complications.
To evaluate the small bowel using MRI, Radiologists visually examine the scan slice-by-slice. The interpretation is time consuming and error-prone because of disease presentation variability and differentiation of diseased segments from collapsed segments.
Deep learning for image analysis is based on a computer algorithm "learning" from human (Radiologist) generated training data.
This method has been successfully applied to medical imaging, for example computer detection of lung cancer on chest X-rays.
This pilot study investigates if a deep learning algorithm can identify and score segments of inflamed terminal ileum affected by Crohn's disease.
To our knowledge this is the first project attempting to develop such an algorithm.The study will retrospectively review MR images obtained as part of standard care from patients being investigated for, Crohn's or being followed up with Crohn's disease. 226 patients' images will be used for the study.
On fully anonymised images two Radiologists working at Northwick Park Hospital will score and outline normal and abnormal loops of terminal ileum. Imperial College computer science department will then develop a deep learning algorithm from imaging features of normal and abnormal loops.
The study end-point is algorithm performance vs. images labelled by Radiologists.
The eventual aim is to develop an algorithm that assists Radiologists in the accurate diagnosis and follow-up of patients with Crohn's disease.
Who can participate
Age range
16 Years
Sex
ALL
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Inclusion Criteria for all cases:
* Patient's age \>16 years of age, (this age cut off has been used in the recent METRIC trial investigating imaging in Crohn's disease)
* MRI sequences obtained include axial T2 weighted images; coronal T2 weighted images and axial post contrast MRI images.
Inclusion criteria for normal MR Enterography cases:
• Normal MR Enterography studies reviewed in consensus by two Radiologists (UP \& PL). Normal is defined as no sites of small or large bowel Crohn's disease.
Inclusion criteria for terminal ileal Crohn's cases:
* MR Enterography studies reviewed in consensus by two Radiologists shows terminal ileal Crohn's disease. Patients with more than one segment of small bowel Crohn's disease including terminal ileum are eligible. Patients with terminal ileal Crohn's disease continuous with large bowel are eligible.
* Diagnosis of Crohn's disease of terminal ileum based on endoscopic, histological and radiological findings. (This criteria has been used in the recent METRIC trial investigating imaging in Crohn's disease).
Exclusion Criteria for all cases:
* Poor quality MRI images as judged by consensus Radiologist opinion.
* No more than 3 MRI scans will come from the same patient.
Exclusion criteria for terminal ileal Crohn's cases:
* MR Enterography shows any bowel abnormality not due to Crohn's.
* Patient has undergone previous small or large bowel resection (this will distort anatomy and is beyond the scope of the present project). Pati…
Questions worth asking your doctor
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
1Based on my diagnosis and history, is this trial worth exploring for me — or is there a standard treatment we should try first?
2What does this trial's phase tell us about how much is already known about its safety and benefit?
3What would taking part actually involve for me — visits, tests, time, and travel?
4What are the known and possible risks or side effects I should weigh, and how would they be monitored?
5If this trial isn't the right fit, what other options or trials would you suggest I look into?
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
Questions for the trial coordinator
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
1What does taking part actually involve week to week — how many visits, where, and how long does each one take?
2What costs are covered by the study, and what might I have to pay for myself, including travel, parking, or time off work?
3What happens during screening, and what happens if the study team confirms I don't meet the criteria after those tests?
4Who pays for the scans, blood work, and other tests the trial requires — the study, my insurance, or me?
5How will being in the trial affect my regular care, and will my own doctor stay informed and involved?
6Can I leave the trial at any point if I change my mind, and what would happen to my care if I do?
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
What they're measuring
1
Machine learning algorithm's ability to accurately localize the terminal ileum.