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NCT Number: NCT06999499

Development of an Aid to Melanoma Detection Using Artificial Intelligence Algorithms Based on Images From the VECTRA 3D System.

The background to this research is that frequent medical screening of the general population for melanoma is not feasible. The real challenge of this project is to develop an automatic process for detecting any potential melanoma. To this end, the project aims to design an algorithm to build a novel diagnostic aid that makes use of the similarity and disparity of pigmented lesions in the same patient. To achieve this, we need to obtain and structure a large database of images grouping all pigmented lesions per patient according to their similarities as perceived by dermatologists.

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Key information

Conditions

Naevi Neoplasms Neoplasms by Histologic Type Nevi and Melanomas Nevus

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Male or female aged 18 and over
  • Patient with more than 15 nevi (moles) of various phototypes (I to III)
  • Patient who has received information about the study and has not expressed any opposition
  • Patient who is a beneficiary or entitled person under a social security scheme

Exclusion criteria

  • Patients with phototype V
  • Patients with chronic inflammatory skin diseases
  • Claustrophobic patients
  • Patients who are bedridden or handicapped
  • Patients who are excluded from another research protocol at the time of collection of the non-objection.
  • Patients covered by articles L1121-5 to 1121-8 of the French Public Health Code (minors, adults under guardianship or trusteeship, patients deprived of their liberty, pregnant or breast-feeding women),
  • Any other reason which, in the investigator's opinion, could interfere with the evaluation of the research objectives.

Treatment and study plan

Scanner of the whole body using the VECTRA 3D

Other

Whole body image acquisition using the VECTRA 3D Whole Body 360 Imaging System to detect potential melanoma

Primary outcomes

  1. development and validation of algorithms to identify lesions clinically suspected of being melanoma by a dermatologist (potentially malignant and/or ugly duckling).

    Time frame: from enrollement to until 6 month

    Comparison of the results given by the analysis of the images by 3 dermatologists or by the software. Estimation of sensitivity and specificity thresholds of at least 93% (accuracy level 5%).

Secondary outcomes

  1. concordance rate for malignant annotations

    Time frame: From enrollement to 6 month after

    concordance between the malignant yes-no annotations of each of the three dermatologists (2 to 2) will be tested.

  2. concordance rate for ugly duckling

    Time frame: From enrollement to 6 month after

    concordance between the ugly duckling yes-no annotations of each of the three dermatologists (2 to 2) will be tested.

  3. calculation of the proportion of melanomas confirmed by anatomopathology

    Time frame: From enrollement to 6 month after

    For each lesion identified as malignant or ugly duckling by the gold standard and removed for histological analysis: calculation of the proportion of melanomas confirmed by pathology.

Study contacts

Contact information is provided by the study sponsor or research team.

Jilliana MONNIER Dr

CONTACT

[email protected]

0491435817 ext. +33

Sponsors and collaborators

Lead sponsor

Assistance Publique Hopitaux De Marseille

Other

Registry information

Official study title

Development of Artificial Intelligence Algorithms to Help Detect Potential Melanomas, Using Images From the VECTRA 3D Whole Body 360 Imaging System, a 3D Whole-body Skin Scanner.

Acronym: SELF DETECT

Important dates

Study start
2026
Primary completion
2028
Study completion
2028
First posted
May 31, 2025
Registry last updated
Nov 18, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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