Melanoma (Skin Cancer)AI-MELNCT06621810
Artificial Intelligence Based Melanoma Early Diagnosis and Risk Prediction in Children, Adolescents and Young Adults
An observational study of Melanoma (Skin Cancer) and Artificial Intelligence (AI), run by German Cancer Research Center at 3 sites in 3 countries.
Trial summary
The goal of this study is to develop supportive diagnostic artificial intelligence algorithms to distinguish melanoma from nevi or other benign pigmented skin lesions, especially in younger patients (below the age of 30). Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Melanoma (Skin Cancer), Artificial Intelligence (AI), Pediatric Cancer
- How many people
- 3,000 participants
- Where
- 3 sitesin 3 countries
- Study dates
- 1 Dec 2022to 30 Nov 2026
- Phase
- Observational
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Study population: Mainly children (up to and including 15 years of age), adolescents (16-20) and young adults (from 21 to 30 years of age)
Who may be able to join
- -
Who cannot join
- Patients without a melanoma or nevus diagnosis
- images with insufficient image quality
Trial locations and contacts
3 sites in 3 countries. Contact the study team or a site near you to ask about taking part.
3 sites in 3 countries
Spain1 site, 1 recruiting
- Recruiting
Hospital Clínic de Barcelona
Barcelona, 08036
Susana Puig, spuig@clinic.cat
About this study
Official title: AI-MEL: Image Analysis and Machine Learning for Early Diagnosis and Risk Prediction in Children, Adolescents and Young Adults
The goal of this study is to develop supportive diagnostic artificial intelligence algorithms to distinguish melanoma from nevi or other benign pigmented skin lesions, especially in younger patients (below the age of 30). The main goals it aims to achieve are:
- development of an algorithm based on dermatoscopic images, targeting skin cancer screening in vulnerable populations
- development of another algorithm based on histological images, intended to be used by pathologists on lesions that are still suspicious of melanoma after dermatologic assessment
- implementation of explainability methods to enable the user to better comprehend the systems' decisions, avoid biases and increase trust in these applications
There is no additional time commitment for the study participants for this study, as the data used in this project will be collected in routine clinical practice anyway.
- Keywords
- melanoma, AI, pediatric, image analysis, Children Adolescence Young Adults (CAYA)
- Medical subject headings
- Melanoma, Neoplasms
What is being measured
The primary outcome is the main question the study is designed to answer.
Area Under the Receiver Operator Curve (AUROC)
The AUROC is used to measure and compare the diagnostic accuracy of different classifiers. Thereby, a higher value means better diagnostic performance, with an AUROC of 1 being a perfect score.
Measured: First Assessment: Upon completion of the first training and testing cycle (approx. within 1.5 years from the start of the study). Reevaluations: at 6 and 12 months post-initial training for model improvement.
Secondary outcomes (1)
Balanced accuracy
The balanced accuracy is used to measure and compare the diagnostic accuracy between classifier and physician. Thereby, a higher value means better diagnostic performance, with a balanced accuracy of 1 signifying perfect diagnostic capabilities.
Measured: First Assessment: Upon completion of the first training and testing cycle (approx. within 1.5 years from the start of the study). Reevaluations: at 6 and 12 months post-initial training for model improvement.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted1 Oct 2024
- Study start1 Dec 2022
- Primary completion30 Nov 2026 (estimated)
- Study completion30 Nov 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Melanoma (Skin Cancer)Studies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case only
- Time perspective
- Other
- Enrolment
- 3,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- German Cancer Research Center
- Sponsor type
- University, hospital or other
- Collaborators
- Universität Tübingen, University of Florence, Fundacio Clinic Barcelona, Hospital Clinic of Barcelona
- Responsible party
- Sponsor
- Investigators
- Titus J Brinker, PD Dr. med, Principal investigator, German Cancer Research Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06621810
- Sponsor's protocol ID
- MELCAYA-AI-MEL
- Acronym
- AI-MEL
- Status last verified
- Sep 2024
- First submitted
- 24 Sep 2024
- Last updated
- 1 Oct 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No