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Use of a smartphone for imaging, modelling, and evaluation of keloids.

Authors
  • Jiang, WeiQian1
  • Guo, LingLi2
  • Wu, Huan3
  • Ying, Jun3
  • Yang, Zheng4
  • Wei, BaoHua4
  • Pan, Feng4
  • Han, Yan5
  • 1 Department of Plastic Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China. Electronic address: [email protected] , (China)
  • 2 Department of Plastic Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China. Electronic address: [email protected] , (China)
  • 3 Center of medical big data, Chinese PLA General Hospital, Beijing, China. , (China)
  • 4 Department of Plastic Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China. , (China)
  • 5 Department of Plastic Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China. Electronic address: [email protected] , (China)
Type
Published Article
Journal
Burns : journal of the International Society for Burn Injuries
Publication Date
Dec 01, 2020
Volume
46
Issue
8
Pages
1896–1902
Identifiers
DOI: 10.1016/j.burns.2020.05.026
PMID: 32646548
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

We used a smartphone to construct three-dimensional (3D) models of keloids, then quantitatively simulate and evaluate these tissues. We uploaded smartphone photographs of 33 keloids on the chest, shoulder, neck, limbs, or abdomen of 28 patients. We used the parallel computing power of a graphics processing unit to calculate the spatial co-ordinates of each pixel in the cloud, then generated 3D models. We obtained the longest diameter, thickness, and volume of each keloid, then compared these data to findings obtained by traditional methods. Measurement repeatability was excellent: intraclass correlation coefficients were 0.998 for longest diameter, 0.978 for thickness, and 0.993 for volume. When measuring the longest diameter and volume, the results agreed with Vernier caliper measurements and with measurements obtained after the injection of water into the cavity. When measuring thickness, the findings were similar to those obtained by ultrasound. Bland-Altman analyses showed that the ratios of 95% confidence interval extremes were 3.03% for longest diameter, 3.03% for volume, and 6.06% for thickness. Smartphones were used to acquire data that was then employed to construct 3D models of keloids; these models yielded quantitative data with excellent reliability and validity. The smartphone can serve as an additional tool for keloid diagnosis and research, and will facilitate medical treatment over the internet. Copyright © 2020 Elsevier Ltd and ISBI. All rights reserved.

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