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用于促进色素沉着性皮肤病变变化评估的计算机视觉方法的开发与狭义验证

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

作者信息

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

机构信息

Division of Hematology/Oncology, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.

UPMC Hillman Cancer Center, Pittsburgh, Pennsylvania, USA.

出版信息

JID Innov. 2023 Jan 9;3(2):100181. doi: 10.1016/j.xjidi.2023.100181. eCollection 2023 Mar.

Abstract

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.

摘要

记录色素沉着性皮肤病变的数量和外观随时间的变化对于皮肤癌的早期检测至关重要,并且可能为黑色素瘤早期治疗性预防试验的疗效提供初步信号。尽管在黑色素瘤的计算机辅助诊断方面取得了重大进展,但评估病变演变的自动化方法相对不发达。本报告描述了数学算法的开发和狭义验证,该算法用于在大面积皮肤的连续数码照片之间配准痣,并对齐图像以改进变化的检测和量化。来自现有数据库的系列后躯干照片由该软件进行处理和分析,结果由一组临床医生使用单独的基于可扩展标记语言的应用程序进行评估。该软件对小至2毫米的皮肤病变检测具有高灵敏度。该软件能准确地配准病变,在图像边缘偶尔会出现错误。在一项针对17名患者的初步研究中,与未配准的图像相比,使用该软件使临床医生能够在另外3至11名患者中识别出新的和/或增大的病变。大小变化的自动量化与人工评分者的表现相似。这些结果支持了该技术的进一步开发和更广泛的验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda9/10030255/9fb6b7354314/gr1.jpg

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