Real-time, in vivo skin cancer triage by laser-induced plasma spectroscopy combined with a deep learning-based diagnostic algorithm.
J Am Acad Dermatol
; 89(1): 99-105, 2023 Jul.
Article
en En
| MEDLINE
| ID: mdl-35752277
ABSTRACT
BACKGROUND:
Although various skin cancer detection devices have been proposed, most of them are not used owing to their insufficient diagnostic accuracies. Laser-induced plasma spectroscopy (LIPS) can noninvasively extract biochemical information of skin lesions using an ultrashort pulsed laser.OBJECTIVE:
To investigate the diagnostic accuracy and safety of real-time noninvasive in vivo skin cancer diagnostics utilizing nondiscrete molecular LIPS combined with a deep neural network (DNN)-based diagnostic algorithm.METHODS:
In vivo LIPS spectra were acquired from 296 skin cancers (186 basal cell carcinomas, 96 squamous cell carcinomas, and 14 melanomas) and 316 benign lesions in a multisite clinical study. The diagnostic performance was validated using 10-fold cross-validations.RESULTS:
The sensitivity and specificity for differentiating skin cancers from benign lesions using LIPS and the DNN-based algorithm were 94.6% (95% CI 92.0%-97.2%) and 88.9% (95% CI 85.5%-92.4%), respectively. No adverse events, including macroscopic or microscopic visible marks or pigmentation due to laser irradiation, were observed.LIMITATIONS:
The diagnostic performance was evaluated using a limited data set. More extensive clinical studies are needed to validate these results.CONCLUSIONS:
This LIPS system with a DNN-based diagnostic algorithm is a promising tool to distinguish skin cancers from benign lesions with high diagnostic accuracy in real clinical settings.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Neoplasias Cutáneas
/
Carcinoma Basocelular
/
Aprendizaje Profundo
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
J Am Acad Dermatol
Año:
2023
Tipo del documento:
Article