A novel total body digital photography smartphone application designed to detect and monitor skin lesions: a pilot study
Open accessAbstract
Although some smartphone applications are designed for total body photography (TBP), few offer the specificity that enables self- as well as dermatologist-, detection of new lesions, or change in lesion color or in size as little as 1mm, on an ongoing basis. The aim of this study is to assess the sensitivity of a novel TBP application in the detection of changes to color and size of simulated skin lesions. Twenty-five subjects underwent one study visit. After baseline photography, new artificial markings were made or naturally occurring pigmented lesions located in any anatomical region were enhanced/enlarged, and a second matching set of photographs was then taken. From all 25 subjects, a total of 262 skin markings were evaluable. Of these, 241 (92%) were detected by the app, which resulted in an overall sensitivity of 92%. The high sensitivity establishes the app as capable of providing reliable self-TBP that allows detection and monitoring of new skin lesions or change in both size and color. This method greatly enhances the ability to accomplish ongoing self-monitoring and yet provides quality informing images to the dermatologist to assist in decision-making with the patient.
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Smartphones and dedicated skin cancer apps can have other roles; for example, assisting in skin self-examination, tracking the evolution of suspicious lesions in people more at risk of developing skin cancer, or when used for store and forward teledermatology.
“Smartphones and dedicated skin cancer apps can have other roles; for example, assisting in skin self-examination, tracking the evolution of suspicious lesions in people more at risk of developing skin cancer,47 48 or when used for store and forward teledermatology.49 50”
From Algorithm based smartphone apps to assess risk of skin cancer in adults: systematic review of diagnostic accuracy studies (2020) · cites this paper as [47]
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BackgroundInfluential
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“…V-VI (0.57) when compared to I-II (0.72) ROC-AUC was lower on DDI dataset when compared to original dataset for ModelDerm , DeepDerm , and HAM 10000 Guido et al. 23 2021 SkinIO FST IV: 16% of the participants; FST V: 0% of the participants; FST VI: 0% of the participants DeGrave et al. 24 2023…”
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“This differs from several other studies that used artificial means of generating changes in size and number of cutaneous lesions before analysis, either by drawing them on the skin (Guido et al., 2018) or by digitally modifying the original images to introduce the changes (Navarro et al.”
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Li, Z., Chen, K., Ji, Y., Wu, H., & Lu, Q. (2026) · Skin · doi:10.2738/skin.2026.0011
- Authors
- Guido, N., Hagstrom, E. L., Ibler, E., Carneiro, C., Orrell, K. A., Kelm, R. C., Rademaker, A. W., West, D. P., & Nardone, B.
- Affiliations
- Northwestern University (US)
- Venue
- Journal of Surgical Dermatology
- Publisher
- PiscoMed Publishing Pte Ltd
- Published
- 2018-07-03
- Volume
- 3
- Issue
- 2
- ISSN
- 2424-9084 (ISSN-L)
- 2424-9165
- OpenAlex
- W2884084085
- Cited by
- 5
- References
- 28
- Citations by year
- 2026: 1 · 2024: 1 · 2023: 1 · 2020: 1 · 2019: 1
- FWCI
- 0.19
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Journal of Surgical Dermatology (publishedVersion, cc-by-nc)
- Topics
- Health Sciences › Medicine › Oncology › Cutaneous Melanoma Detection and Management
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Digital Imaging in Medicine
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- total body photography, mobile application, skin lesion detection, lesion monitoring, self-monitoring, pigmented skin lesions, lesion size change, detection sensitivity, dermatology
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