Artificial Intelligence Patient App for RDEB SCCs

Sponsor

Northwestern University (Other)

Overall Status

Recruiting

CT.gov ID

NCT05843994

Collaborator

Epidermolysis Bullosa Research Partnership (Other)

100

Enrollment

Location

16.5

Anticipated Duration (Months)

6.1

Patients Per Site Per Month

Study Details

Study Description

Brief 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.

Condition or Disease	Intervention/Treatment	Phase
Epidermolysis Bullosa Dystrophica	Other: online survey

Detailed 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

Study Design

Study Type:

Observational

Anticipated Enrollment :

100 participants

Observational Model:

Cohort

Time Perspective:

Prospective

Official Title:

Developing a Novel Artificial Intelligence Patient App to Recognize Squamous Cell Carcinoma (SCCs) in Recessive Dystrophic Epidermolysis Bullosa (RDEB): Image Collection

Actual Study Start Date :

Feb 13, 2023

Anticipated Primary Completion Date :

Dec 31, 2023

Anticipated Study Completion Date :

Jun 30, 2024

Outcome Measures

Primary Outcome Measures

Percent agreement of the presence or absence of squamous cell carcinoma (SCC) on the skin in photographs as detected by the App versus confirmed physician diagnosis [one day survey]