NCT04116983

DERM NMSC Validation Study

Effectiveness of an Image Analysing Algorithm (DERM) to Diagnose Non-melanoma Skin Cancer (NMSC) and Benign Skin Lesions Compared to Gold Standard Clinical and Histological Diagnosis

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 572 (actual)
• Sponsor: Skin Analytics Limited · Industry
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

This study aims to establish the effectiveness of an Artificial Intelligence (AI) algorithm (DERM) to determine the presence of Basal Cell Carcinoma (BCC) and Squamous Cell Carcinoma (SCC) and frequently observed benign conditions, when used to analyse images of skin lesions taken by commonly available smart phone cameras.

Detailed description

DERM, an Artificial Intelligence (AI)-based diagnosis support tool, has been shown to be able to accurately identify Non-melanoma skin cancers (NMSC) and other conditions from historical images of suspicious skin lesions (moles). This study aims to establish how well DERM determines the presence of these conditions in images of skin lesions collected in a clinical setting. Suspicious skin lesions that are due to be assessed by a dermatologist and a patch of healthy skin will be photographed using three commonly available smart phone cameras with a specific lens attachment. The images will be analysed by DERM, and the results compared to the clinician's diagnosis (all lesions) and histologically-conformed diagnosis (any lesion that is biopsied).

Conditions

• Non-melanoma Skin Cancer

Interventions

Type	Name	Description
DEVICE	Deep Ensemble for the Recognition of Malignancy (DERM)	An AI-based diagnosis support tool

Timeline

• Start date: 2020-06-26
• Primary completion: 2022-02-28
• Completion: 2022-03-16
• First posted: 2019-10-07
• Last updated: 2022-05-18

Locations

3 sites across 1 country: United Kingdom