Walters Sam, Metcalfe Benjamin, Twiste Martin, Seminati Elena, Bailey Nicola Y
Department of Mechanical Engineering, University of Bath, Bath, Somerset, United Kingdom.
Bath Institute for the Augmented Human, University of Bath, Bath, Somerset, United Kingdom.
PLoS One. 2024 Dec 2;19(12):e0313542. doi: 10.1371/journal.pone.0313542. eCollection 2024.
Monitoring the volume and shape of residual limbs post-amputation is necessary to achieve optimal socket fit and determine overall limb health, yet contemporary clinical measurement techniques show high variance between measures. Three-dimensional scanning presents an opportunity for improved accuracy and reliability of residual limb measurements, however, three-dimensional scanners remain prohibitively expensive. A cost-effective alternative is the use of software that can utilise the photographs of modern smartphone cameras to create geometrically accurate scans. Whilst several studies have investigated the potential of privately developed photogrammetry algorithms for capturing residual limbs with clinical accuracy, none to the authors knowledge have explored commercially available software to do the same. Three applications were tested, namely Polycam, Luma, and Meshroom, to determine if they could produce clinically acceptable results. Scans of ten residual limbs were created using both smartphone technology and a reference structured-light scanner (Artec EVA), against which the validity and reliability of the resulting limb models were assessed using the Bland-Altman method and Intraclass Correlation Coefficient, respectively. Polycam and Luma achieved both Pearson Coefficients and Intraclass Correlation Coefficients of 0.999, and Coefficients of Variation of 1.1% and 1.4%, respectively. Volume reliability coefficients were 58.3 ml and 70.0 ml respectively for Polycam and Luma, whereas Meshroom failed to meet any of the criteria for clinical suitability, with a repeatability coefficient of 790.3 ml. Both Polycam and Luma exhibit sufficient accuracy and reliability to be considered for clinical volume measurements.
截肢后监测残肢的体积和形状对于实现最佳的假肢适配以及确定整体肢体健康状况至关重要,然而当代临床测量技术显示测量结果之间存在很大差异。三维扫描为提高残肢测量的准确性和可靠性提供了契机,但是三维扫描仪仍然价格昂贵得令人望而却步。一种经济高效的替代方法是使用能够利用现代智能手机摄像头拍摄的照片来创建几何精确扫描的软件。虽然有几项研究调查了私人开发的摄影测量算法在临床精度下捕捉残肢的潜力,但据作者所知,尚未有研究探索使用商业可用软件来做同样的事情。测试了三款应用程序,即Polycam、Luma和Meshroom,以确定它们是否能产生临床可接受的结果。使用智能手机技术和参考结构光扫描仪(Artec EVA)对十个残肢进行了扫描,并分别使用布兰德-奥特曼方法和组内相关系数评估了所得肢体模型的有效性和可靠性。Polycam和Luma的皮尔逊系数和组内相关系数均达到0.999,变异系数分别为1.1%和1.4%。Polycam和Luma的体积可靠性系数分别为58.3毫升和70.0毫升,而Meshroom未能满足任何临床适用性标准,其重复性系数为790.3毫升。Polycam和Luma都表现出足够的准确性和可靠性,可用于临床体积测量。