Use of an elastic-scattering spectroscopy and artificial intelligence device in the assessment of lesions suggestive of skin cancer: A comparative effectiveness study.
| Autor: | Manolakos D; Gold Coast Dermatology Center, Delray Beach, Florida., Patrick G; Florida State University College of Medicine, Tallahassee, Florida., Geisse JK; Departments of Dermatology and Pathology, University of California San Francisco, San Francisco, California., Rabinovitz H; Skin and Cancer Associates, Plantation, Florida.; Department of Dermatology, University of Miami School of Medicine, Miami, Florida.; Medical College of Georgia, Augusta University, Augusta, Georgia., Buchanan K; Medical College of Georgia, Augusta University, Augusta, Georgia., Hoang P; DermaSensor, Inc., Miami, Florida., Rodriguez-Diaz E; Department of Biomedical Engineering, Boston University, Boston, Massachusetts., Bigio IJ; Department of Electrical & Computer Engineering, Boston University, Boston, Massachusetts., Cognetta AB; Florida State University College of Medicine, Tallahassee, Florida.; Dermatology Associates of Tallahassee, Tallahassee, Florida. |
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| Jazyk: | angličtina |
| Zdroj: | JAAD international [JAAD Int] 2023 Oct 11; Vol. 14, pp. 52-58. Date of Electronic Publication: 2023 Oct 11 (Print Publication: 2024). |
| DOI: | 10.1016/j.jdin.2023.08.019 |
| Abstrakt: | Background: Skin cancer is the most common form of cancer worldwide. As artificial intelligence (AI) expands its scope within dermatology, leveraging technology may aid skin cancer detection. Objective: To assess the safety and effectiveness of an elastic-scattering spectroscopy (ESS) device in evaluating lesions suggestive of skin cancer. Methods: This prospective, multicenter clinical validation study was conducted at 4 US investigational sites. Patients with skin lesions suggestive of melanoma and nonmelanoma skin cancers were clinically assessed by expert dermatologists and evaluated by a device using AI algorithms comparing current ESS lesion readings with training data sets. Statistical analyses included sensitivity, specificity, AUROC, negative predictive value (NPV), and positive predictive value (PPV). Results: Overall device sensitivity was 97.04%, with subgroup sensitivity of 96.67% for melanoma, 97.22% for basal cell carcinoma, and 97.01% for squamous cell carcinoma. No statistically significant difference was found between the device and dermatologist performance ( P = .8203). Overall specificity of the device was 26.22%. Overall NPV of the device was 89.58% and PPV was 57.54%. Conclusion: The ESS device demonstrated high sensitivity in detecting skin cancer. Use of this device may assist primary care clinicians in assessing suspicious lesions, potentially reducing skin cancer morbidity and mortality through expedited and enhanced detection and intervention. Competing Interests: Eladio Rodriguez-Diaz and Irving J. Bigio are coinventors, with fractional royalty rights, to the Boston University patents licensed to DermaSensor, Inc. Drs Bigio, Geisse and Rabinovitz are Scientific Advisory Board members for DermaSensor and are compensated by the company. Preston Hoang is a paid consultant for DermaSensor, Inc. Drs Armand Cognetta, Harold Rabinovitz, and Danielle Manolakos were paid principal investigators for this study. (© 2023 by the American Academy of Dermatology, Inc. Published by Elsevier Inc.) |
| Databáze: | MEDLINE |
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