3D Total Body Photography as a Promising Innovation for Early Skin Cancer Detection: Scoping Review
Notice bibliographique
Résumé
BACKGROUND: Skin cancer is a global health concern due to its high and still increasing incidence and associated healthcare cost. Belgium is no exception as one in five people are diagnosed with skin cancer before the age of 75. A promising innovation, the VECTRA WB360, a three-dimensional total body photography system allows clinicians to objectively compare the totality of the skin on a macroscopic level on further appointments. The integrated lesion visualisation software allows automated detection, counts and assessment of skin lesions. And detailed comparison of individual lesions is possible through the attached digital dermatoscope. OBJECTIVE: This study aims to review available literature on the use of the Vectra in research and clinical settings, and to summarise the clinical utility, advantages and limitations reported for this system. METHODS: An electronic literature search was conducted on PubMed from December 2023 - March 2024 using a combination of following search terms: 3D imaging, VECTRA WB360, melanoma, non-melanoma skin cancer, their synonyms and associated entry terms. Publications that used a device other than the Vectra WB360 were excluded, as were articles reporting on new technology without further research or without added cases. After thorough screening of the articles and removal of duplicates, 11 articles remained. RESULTS: Our literature search yielded 11 relevant papers, which included 2 case studies, 6 prospective and 3 retrospective studies. According to multiple studies, the VECTRA WB360 images were of a high enough quality to allow on-screen diagnosis of some melanoma and nonmelanoma skin cancers by dermatologists. Sensitivity compared to face to face examination for melanoma is unknown. The integrated lesion visualisation software is capable of detecting and counting naevi and distinguishing melanoma from other skin lesions with high accuracy, with convolutional neural network (CNN) integration further enhancing its sensitivity and specificity. However, it is important to note that no comparison to the usual standard of care was made. Also, dermatologists achieved greater specificity and thus remained superior to machine and artificial intelligence. CONCLUSIONS: While the VECTRA 3D TBP holds substantial promise for the early detection and monitoring of skin cancer, its application cannot yet replace the expertise of trained clinicians. Although the lesion visualizer and DEXI score offer potential enhancements, they also pose risks, including a significant increase in unnecessary excisions due to lower specificity. Despite these promising results, expert overview is still recommended and superior, since there is not enough evidence yet that 3D TBP and/or AI is reliable on its own or beneficial as a support tool Given the small samples and lack of blinded trials, further studies are needed to explore and improve the diagnostic capacities of 3D TBP and the possible integration of CNN's or other AI extensions. It will also be important to examine the Vectra 360WB compared to the usual standard of care.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».