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大面积烧伤的自动计算机辅助表面积估计:斐济是否正在接管烧伤护理?

Automated computer-assisted surface area estimation in large surface burns: Is Fiji taking over burn care?

作者信息

Bucher Florian, Dastagir Nadjib, Tamulevicius Martynas, Obed Doha, Dieck Thorben, Vogt Peter M, Dastagir Khaled

机构信息

Department of Plastic, Aesthetic, Hand and Reconstructive Surgery, Hannover Medical School, Hannover, Germany.

出版信息

JPRAS Open. 2025 Apr 28;45:20-32. doi: 10.1016/j.jpra.2025.04.010. eCollection 2025 Sep.

Abstract

AIMS

Although several methods exist for estimating the extent of large surface burns, common approaches often tend toward overestimation and have notable limitations. This study was performed to assess the accuracy of Fiji software for manual and automated computer-assisted estimation of large surface burns.

METHODS

A retrospective analysis of the burn registry of a European Burns Association certified burn center was performed from January 1, 2019 to October 1, 2024. Fiji was used for manual and computer-assisted total body surface area (TBSA) estimation from admission photographs of patients with large surface burns. The results were compared with TBSA estimations made using a smartphone application, the referring emergency doctor, and a consultant plastic surgeon.

RESULTS

In total, 37 patients were included. Excellent intra-examiner agreement was found between the estimations made by the consultant plastic surgeon and automated Fiji estimations (0.968), followed by manual Fiji estimations (0.958). Similar results were obtained between automated and manual computer-assisted TBSA estimations using Fiji (0.991), with a mean deviation of 0.729%. The mean deviation between automated computer-assisted TBSA estimations using Fiji and the consultant plastic surgeon was -4.189%.

CONCLUSIONS

Manual and automated computer-assisted TBSA estimations using Fiji provided highly accurate results via pixel-by-pixel analysis, demonstrating that automated methods can match the precision of manual approaches. These findings highlight the expanding role of computer-assisted image analysis in improving burn care practices.

摘要

目的

尽管存在多种估计大面积烧伤范围的方法,但常用方法往往倾向于高估,且有明显局限性。本研究旨在评估斐济软件在手动和自动计算机辅助估计大面积烧伤方面的准确性。

方法

对一家获得欧洲烧伤协会认证的烧伤中心2019年1月1日至2024年10月1日的烧伤登记册进行回顾性分析。使用斐济软件从大面积烧伤患者的入院照片中手动和计算机辅助估计全身表面积(TBSA)。将结果与使用智能手机应用程序、转诊急诊医生和整形外科顾问医生进行的TBSA估计进行比较。

结果

共纳入了37例患者。整形外科顾问医生的估计与斐济软件自动估计之间的检查者内一致性极佳(0.968),其次是斐济软件手动估计(0.958)。使用斐济软件进行的自动和手动计算机辅助TBSA估计之间也获得了类似结果(0.991),平均偏差为0.729%。使用斐济软件进行的自动计算机辅助TBSA估计与整形外科顾问医生之间的平均偏差为-4.189%。

结论

使用斐济软件进行手动和自动计算机辅助TBSA估计通过逐像素分析提供了高度准确的结果,表明自动方法可以与手动方法的精度相匹配。这些发现凸显了计算机辅助图像分析在改善烧伤护理实践中日益扩大的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c87/12149551/12ad43ca5b84/gr1.jpg

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