Clinical trial · Interventional
Development of an Aid to Melanoma Detection Using Artificial Intelligence Algorithms Based on Images From the VECTRA 3D System.
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.
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Naevi | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Scanner of the whole body using the VECTRA 3D | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- type
- EXPERIMENTAL
- label
- Scanner of the whole body sing the VECTRA 3D
- description
- Whole body image acquisition using the VECTRA 3D Whole Body 360 Imaging System to detect potential melanoma
- interventionNames
- Other: Scanner of the whole body using the VECTRA 3D
Primary outcomes (1)
- measure
- development and validation of algorithms to identify lesions clinically suspected of being melanoma by a dermatologist (potentially malignant and/or ugly duckling).
- timeFrame
- from enrollement to until 6 month
- description
- 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 (3)
- measure
- concordance rate for malignant annotations
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
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.
References
Publications (0)
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