AI-based Medical Device Validation for Early Melanoma Detection

Sponsor
AI Labs Group S.L
Study ID
NCT06221397
Status
Completed

Conditions

Eligibility Criteria

Sex
ALL
Age
18 Years - N/A
Healthy Volunteers
Not accepted

Interventions

  • AI-based Computer-Aided Diagnosis (CAD) Software for Skin Lesion Analysis. — DEVICE
    The intervention is a software-only medical device that utilizes artificial intelligence and machine vision algorithms to analyze digital images of the skin. Unlike traditional diagnostic tools, this system is designed to provide quantitative data on visible clinical signs and an interpretative distribution of possible disease categories (ICD codes). Key Distinguishing Features Non-Invasive Diagnostic Support: It acts as a clinical decision-support tool to help practitioners prioritize patients based on malignancy risk, rather than providing a standalone or confirmatory diagnosis. Broad ICD Recognition: While many tools focus only on melanoma, this system is capable of recognizing a variety of ICD categories, including basal cell carcinoma, nevi, and dermatofibroma Advanced Image Preprocessing: The system includes a Dermatology Image Quality Assessment (DIQA) algorithm to ensure images have sufficient visual quality before analysis.

Study Details

The goal of this observational study is to learn if a computer-aided diagnosis (CAD) system can help identify skin cancer (cutaneous melanoma). The research focuses on adults who have skin spots that a doctor thinks might be cancerous. The main questions the study aims to answer are: Can the artificial intelligence (AI) tool accurately identify melanoma in skin images? How does the tool's accuracy compare to the clinical judgment of expert skin doctors (dermatologists)? Researchers will compare the results from the AI tool to the final diagnosis made by doctors or through a skin biopsy. A biopsy is a medical test where a small piece of skin is removed and checked in a lab. Participants will: Have their skin spots photographed using a special camera attached to a smartphone. Allow researchers to use their clinical data and biopsy results for the study. The study does not change the medical care participants receive. Doctors will continue to treat participants as they normally would. By testing this tool, researchers hope to find a way to detect skin cancer earlier and more accurately

Key Dates

Start date
Sep 17, 2020
Status verified
Feb 2026
Primary completion
Nov 13, 2023
Completion
Nov 13, 2023

Study Design

Enrollment
105 participants (actual)

Arms

  • Arm: Patients with suspected cutaneous malignancy
    Group/Cohort Description The study group consists of adult patients (over 18 years old) who presented at the Dermatology Departments of Hospital Universitario Cruces and Hospital Universitario Basurto with skin lesions suspected of being malignant. As this is an observational study, participants were not assigned to any new medical interventions, drugs, or treatments as part of the research protocol.

Primary Outcome Measure

Area Under the ROC Curve (AUC) for Melanoma Detection [ Time Frame: At the time of the single clinical visit (Baseline). ]

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