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

Objective: We used a smartphone to construct three-dimensional (3D) models of keloids, then quantitatively simulate and evaluate these tissues.Methods: We uploaded smartphone photographs of 33 keloids on the chest, shoulder, neck, limbs, or abdomen of 28 patients. We used the parallel computing powe...

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Detalles Bibliográficos
Publicado en:Burns (03054179) Vol. 46; no. 8; pp. 1896 - 1903
Autores principales: Jiang, WeiQian, Guo, LingLi, Wu, Huan, Ying, Jun, Yang, Zheng, Wei, BaoHua, Pan, Feng, Han, Yan
Formato: research Journal Article
Publicado: Elsevier B.V. Dec2020
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Dec2020
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      pub: Elsevier B.V.
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        10.1016/j.burns.2020.05.026
        NLM32646548
        147680309
      ppf: 1896
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        atl: Use of a smartphone for imaging, modelling, and evaluation of keloids.
      aug:
        au:
          Jiang, WeiQian
          Guo, LingLi
          Wu, Huan
          Ying, Jun
          Yang, Zheng
          Wei, BaoHua
          Pan, Feng
          Han, Yan
        affil: Department of Plastic Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China
      sug:
        subj:
          Imaging, Three-Dimensional Standards
          Keloid
          Human
          Reproducibility of Results
          China
          Burns Complications
          Imaging, Three-Dimensional Statistics and Numerical Data
          Burns
          Middle Age
          Male
          Adult
          Imaging, Three-Dimensional Methods
          Female
          Comparative Studies
          Multicenter Studies
          Evaluation Research
          Validation Studies
          Middle Aged: 45-64 years
          Adult: 19-44 years
          Male
          Female
      ab: Objective: We used a smartphone to construct three-dimensional (3D) models of keloids, then quantitatively simulate and evaluate these tissues.Methods: 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.Results: 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.Conclusion: 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.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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