Murphy Michael P, Killen Cameron J, Ralles Steven J, Brown Nicholas M, Song Albert J, Wu Karen
Loyola University Medical Center, Department of Orthopaedic Surgery and Rehabilitation, 2160 S. First Avenue,Maguire Suite 1700, Maywood, IL 60153, USA.
Loyola University Medical Center, Department of Radiology, 2160 S. First Avenue,Maguire Suite 1700, Maywood, IL 60153, USA.
J Clin Orthop Trauma. 2021 Apr 14;18:61-65. doi: 10.1016/j.jcot.2021.04.002. eCollection 2021 Jul.
Several radiological methods of measuring anteversion of the acetabular component after total hip arthroplasty have been described, all time-consuming and with varying reproducibility. This study aimed to compare the recently proposed Area method to true cup anteversion as determined by an accelerometer. This study further applied this method programmatically to autonomously determine radiographic cup orientation using two computer programs, then compared these results to hand and accelerometer measurements. 160 anteroposterior pelvis radiographs were taken of a standard Sawbones® pelvis fitted with a total hip arthroplasty system. The acetabular cup was re-oriented between each radiograph, with anteversion ranging from 0° to 90°. An accelerometer was mounted to the cup to measure true cup anteversion. Radiographic anteversion was independently measured via three methods: by hand, linear image processing, and machine learning. Measurements were compared to triaxial accelerometer recordings. Coefficient of determination (R2) was found to be 0.997, 0.991, and 0.989 for hand measurements, the machine learning, and linear image processing, respectively. The machine learning program and hand measurements overestimated anteversion by 0.70° and 0.02° respectively. The program using linear techniques underestimated anteversion by 5.02°. Average runtime was 0.03 and 0.59 s for the machine learning and linear image processing program, respectively. The machine learning program averaged within 1° of cup orientation given a true cup anteversion less than 51°, and within 2° given an anteversion less than 85°. The Area method showed great accuracy and reliability with hand measurements compared to true anteversion. The results of this study support the use of machine learning for accurate, timely, autonomous assessment of cup orientation.
已经描述了几种测量全髋关节置换术后髋臼组件前倾角的放射学方法，这些方法都耗时且重复性各异。本研究旨在将最近提出的面积法与通过加速度计确定的髋臼杯真实前倾角进行比较。本研究进一步以编程方式应用此方法，通过两个计算机程序自主确定放射照片上髋臼杯的方向，然后将这些结果与手工测量和加速度计测量结果进行比较。对安装有全髋关节置换系统的标准Sawbones®骨盆拍摄了160张前后位骨盆X线片。在每张X线片之间重新调整髋臼杯的方向，前倾角范围为0°至90°。在髋臼杯上安装一个加速度计以测量髋臼杯的真实前倾角。通过三种方法独立测量放射学前倾角：手工测量、线性图像处理和机器学习。将测量结果与三轴加速度计记录进行比较。手工测量、机器学习和线性图像处理的决定系数（R²）分别为0.997、0.991和0.989。机器学习程序和手工测量分别将前倾角高估了0.70°和0.02°。使用线性技术的程序将前倾角低估了 5.02°。机器学习程序和线性图像处理程序的平均运行时间分别为0.03秒和0.59秒。当真实髋臼杯前倾角小于51°时，机器学习程序的平均结果在髋臼杯方向的1°范围内；当前倾角小于85°时，平均结果在2°范围内。与真实前倾角相比，面积法在手工测量中显示出很高的准确性和可靠性。本研究结果支持使用机器学习对髋臼杯方向进行准确、及时的自主评估。
