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.