iPhone-Based Cartilage Topography Scanning Yields Similar Results to Computed Tomography Scanning

Abstract

Purpose: 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. Methods: 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. Results: 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], P = .002). iPhone models were smaller compared with CT models (negative signed distances) for all trochleae, 83% of DFCs, and 69% of patellae. Conclusions: In this study, we found minimal differences between a 3D iPhone scanning application and conventional CT scanning when analyzing surface topography. Clinical Relevance: 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.