Development and Narrow Validation of Computer Vision Approach to Facilitate Assessment of Change in Pigmented Cutaneous Lesions

© 2023 The Authors..

The documentation of the change in the number and appearance of pigmented cutaneous lesions over time is critical to the early detection of skin cancers and may provide preliminary signals of efficacy in early-phase therapeutic prevention trials for melanoma. Despite substantial progress in computer-aided diagnosis of melanoma, automated methods to assess the evolution of lesions are relatively undeveloped. This report describes the development and narrow validation of mathematical algorithms to register nevi between sequential digital photographs of large areas of skin and to align images for improved detection and quantification of changes. Serial posterior truncal photographs from a pre-existing database were processed and analyzed by the software, and the results were evaluated by a panel of clinicians using a separate Extensible Markup Language‒based application. The software had a high sensitivity for the detection of cutaneous lesions as small as 2 mm. The software registered lesions accurately, with occasional errors at the edges of the images. In one pilot study with 17 patients, the use of the software enabled clinicians to identify new and/or enlarged lesions in 3‒11 additional patients versus the unregistered images. Automated quantification of size change performed similarly to that of human raters. These results support the further development and broader validation of this technique.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:3

Enthalten in:

JID innovations : skin science from molecules to population health - 3(2023), 2 vom: 15. März, Seite 100181

Sprache:

Englisch

Beteiligte Personen:

Maguire, William F [VerfasserIn]
Haley, Paul H [VerfasserIn]
Dietz, Catherine M [VerfasserIn]
Hoffelder, Mike [VerfasserIn]
Brandt, Clara S [VerfasserIn]
Joyce, Robin [VerfasserIn]
Fitzgerald, Georgia [VerfasserIn]
Minnier, Christopher [VerfasserIn]
Sander, Cindy [VerfasserIn]
Ferris, Laura K [VerfasserIn]
Paragh, Gyorgy [VerfasserIn]
Arbesman, Joshua [VerfasserIn]
Wang, Hong [VerfasserIn]
Mitchell, Kevin J [VerfasserIn]
Hughes, Ellen K [VerfasserIn]
Kirkwood, John M [VerfasserIn]

Links:

Volltext

Themen:

CI, confidence interval
Journal Article

Anmerkungen:

Date Revised 25.03.2023

published: Electronic-eCollection

Citation Status PubMed-not-MEDLINE

doi:

10.1016/j.xjidi.2023.100181

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM354654721