Clinical Trial Details
— Status: Active, not recruiting
Administrative data
| NCT number |
NCT05843994 |
| Other study ID # |
2023-5810 |
| Secondary ID |
|
| Status |
Active, not recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
February 13, 2023 |
| Est. completion date |
June 30, 2024 |
Study information
| Verified date |
March 2024 |
| Source |
Northwestern University |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
In this study, an artificial intelligence model to detect squamous cell carcinomas (SCC) on
photos of recessive dystrophic epidermolysis bullosa (RDEB) skin is developed. The ultimate
goal is to integrate this model into an app for patients and physicians, to help detect SCCs
in RDEB early.
SCCs which rapidly metastasize are the main cause of death in adults with RDEB. The earlier
an SCC is recognized, the easier it can be removed and the better the outcome. AI leverages
computer science to perform tasks that typically require human intelligence and has recently
been used to identify skin cancers based on images. We are currently developing an AI
approach for early detection of SCC and distinction of malignancy from chronic wounds and
other RDEB skin findings. The aim is to create a web application for patients with RDEB to
upload images of their skin and get an output as to SCC present/ no SCC. This will be
especially valuable for patients with difficult access to medical expertise and those who are
hesitant to allow full skin examination at each visit, often because of fear of biopsies.
Thus, this project will directly benefit patients by allowing early recognition of SCCs and
will empower patients and their families by providing a home use tool.
So far, the study team has mainly used professional images (photographs taken in hospital
settings by physicians, nurses, and clinical photographers) of both SCCs in RDEB and images
of RDEB skin without SCC to develop and train the AI model. The images that are expected in a
real-life setting will mostly be pictures taken by patients or family members with their
phones or digital cameras. These images have different properties regarding resolution,
focus, lighting, and backgrounds. Incorporating such images will be crucial in the upcoming
phases of model development-testing and validation-for the web application be a success for
patients.
Description:
This project will enroll adolescents and adults with RDEB and history of at least one SCC.
The survey and consents will be provided in English, Spanish, German, French, Arabic,
Chinese, and Russian. The study team is inviting people with RDEB around the world to
participate and are hoping that approximately 100 people will provide images.
Participants will be asked to complete the survey and upload photographs of SCC(s) using the
links below. Depending on the number of SCCs they have had and the number of photos they want
to provide, the survey will take approximately 15-20 minutes to complete.
To participate in this study, please follow this link:
https://redcap.nubic.northwestern.edu/redcap/surveys/?s=JH9LHR4CC4R4H3HN
