A novel total body digital photography smartphone application designed to detect and monitor skin lesions: a pilot study

Abstract

<p class="Body">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. </p>

Algorithm based smartphone apps to assess risk of skin cancer in adults: systematic review of diagnostic accuracy studies

“…The current CE marking assessment processes are inadequate for protecting the public against the risks created by using smartphone diagnostic or risk stratification apps. 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,4748 or when used for store and forward teledermatology 4950. However, healthcare professionals who work in primary and secondary care need to be aware of the limitations of algorithm based apps to reliably identify melanomas, and should inform potential smartphone app users about these limitations.…”

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

“…A notable feature of this study was the use of sequential images from patients that were taken as part of an image and nevus biobanking protocol at our institution. 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., 2019 ). The use of artificial nevi and/or digital changes to nevi may not reflect a real-world situation and may introduce artifacts and/or bias owing to assumptions made when creating or modifying the lesions.…”

Partnering with a senior living community to optimise teledermatology via full body skin screening during the COVID‐19 pandemic: A pilot programme

“…Guido et al previously showed that SkinIO had 92% sensitivity in detecting new or changing lesions. 17 Future studies can explore the role mobile applications may play in remote diagnosis.…”

“…SkinIO was used as a tool for image collection, with a streamlined interface enabling the physician to quickly browse through organised collections of full body and dermoscopic photos (Figure 2 ). 17 , 18 The application uses a deep neural network‐based outlier detection model that analyzes all photos from a patient's total body photography session, compares each lesion, and highlights lesions most different from the average. The neural network aspect was only used in triage for photography, but not for diagnosis.…”