Evaluating smartphone-based 3D imaging techniques for clinical application in oral and maxillofacial surgery: A comparative study with the vectra M5: Three-dimensional Surface Imaging Utilizing Smartphones

Purpose This study aimed to clarify the applicability of smartphone-based three-dimensional (3D) surface imaging for clinical use in oral and maxillofacial surgery, comparing two smartphone-based approaches to the gold standard. Methods Facial surface models (SMs) were generated for 30 volunteers (15 men, 15 women) using the Vectra M5 ( Canfield Scientific, USA ), the TrueDepth camera of the iPhone 14 Pro ( Apple Inc., USA ), and the iPhone 14 Pro with photogrammetry. Smartphone-based SMs were superimposed onto Vectra-based SMs. Linear measurements and volumetric evaluations were performed to evaluate surface-to-surface deviation. To assess inter-observer reliability, all measurements were performed independently by a second observer. Statistical analyses included Bland–Altman analyses, the Wilcoxon signed-rank test for paired samples, and Intraclass correlation coefficients. Results Photogrammetry-based SMs exhibited an overall landmark-to-landmark deviation of M = 0.8 mm (SD = ± 0.58 mm, n = 450), while TrueDepth-based SMs displayed a deviation of M = 1.1 mm (SD = ± 0.72 mm, n = 450). The mean volumetric difference for photogrammetry-based SMs was M = 1.8 cc (SD = ± 2.12 cc, n = 90), and M = 3.1 cc (SD = ± 2.64 cc, n = 90) for TrueDepth-based SMs. When comparing the two approaches, most landmark-to-landmark measurements demonstrated 95% Bland–Altman limits of agreement (LoA) of ≤ 2 mm. Volumetric measurements revealed LoA > 2 cc. Photogrammetry-based measurements demonstrated higher inter-observer reliability for overall landmark-to-landmark deviation. Conclusion Both approaches for smartphone-based 3D surface imaging exhibit potential in capturing the face. Photogrammetry-based SMs demonstrated superior alignment and volumetric accuracy with Vectra-based SMs than TrueDepth-based SMs.