Huddleston Hailey P, Credille Kevin, Alzein Mohamad M, Cregar William M, Hevesi Mario, Inoue Nozomu, Yanke Adam B
Hospital for Special Surgery, New York, New York, U.S.A.
Houston Methodist Hospital, Houston, Texas, U.S.A.
Arthrosc Sports Med Rehabil. 2024 Apr 10;6(4):100936. doi: 10.1016/j.asmr.2024.100936. eCollection 2024 Aug.
To investigate the feasibility and accuracy of 3-dimensional (3D) iPhone scans using commercially available applications compared with computed tomography (CT) for mapping chondral surface topography of the knee.
Ten cadaveric dysplastic trochleae, 16 patellae, and 24 distal femoral condyles (DFCs) underwent CT scans and 3D scans using 3 separate optical scanning applications on an iPhone X. The 3D surface models were compared by measuring surface-to-surface least distance distribution of overlapped models using a validated 3D-3D registration volume merge method. The absolute least mean square distances for the iPhone-generated models from each scanning application were calculated in comparison to CT models using a point-to-surface distance algorithm allowing regional "inside/outside" measurement of the absolute distance between models.
Only 1 of the 3 scanning applications created models usable for quantitative analysis. Overall, there was a median absolute least mean square distance between the usable model and CT-generated models of 0.18 mm. The trochlea group had a significantly lower median absolute least mean square distance compared with the DFC group (0.14 mm [interquartile range, 0.13-0.17] vs 0.19 mm [0.17-0.25], = .002). iPhone models were smaller compared with CT models (negative signed distances) for all trochleae, 83% of DFCs, and 69% of patellae.
In this study, we found minimal differences between a 3D iPhone scanning application and conventional CT scanning when analyzing surface topography.
Emerging 3D iPhone scanning technology can create accurate, inexpensive, real-time 3D models of the intended target. Surface topography evaluation may be useful in graft selection during surgical procedures such as osteochondral allograft transplantation.
与计算机断层扫描(CT)相比,研究使用市售应用程序进行三维(3D)iPhone扫描来绘制膝关节软骨表面地形的可行性和准确性。
对10个尸体发育不良的滑车、16个髌骨和24个股骨远端髁(DFC)进行CT扫描,并使用iPhone X上的3种独立光学扫描应用程序进行3D扫描。通过使用经过验证的3D-3D配准体积合并方法测量重叠模型的表面到表面最小距离分布,对3D表面模型进行比较。使用点到表面距离算法计算每个扫描应用程序生成的iPhone模型与CT模型相比的绝对最小均方距离,从而允许对模型之间的绝对距离进行区域“内部/外部”测量。
3种扫描应用程序中只有1种创建了可用于定量分析的模型。总体而言,可用模型与CT生成模型之间的绝对最小均方距离中位数为0.18毫米。滑车组的绝对最小均方距离中位数明显低于DFC组(0.14毫米[四分位间距,0.13 - 0.17]对0.19毫米[0.17 - 0.25],P = 0.002)。对于所有滑车、83%的DFC和69%的髌骨,iPhone模型与CT模型相比更小(负符号距离)。
在本研究中,我们发现在分析表面地形时,3D iPhone扫描应用程序与传统CT扫描之间的差异极小。
新兴的3D iPhone扫描技术可以创建准确、廉价、实时的预期目标3D模型。表面地形评估在诸如骨软骨异体移植等手术过程中的移植物选择中可能有用。