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Purpose <p>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.</p> Methods <p>Facial surface models (SMs) were generated for 30 volunteers (15 men, 15 women) using the Vectra M5 (<i>Canfield Scientific, USA</i>), the TrueDepth camera of the iPhone 14 Pro (<i>Apple Inc., USA</i>), 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.</p> Results <p>Photogrammetry-based SMs exhibited an overall landmark-to-landmark deviation of M = 0.8&#xa0;mm (SD =  ± 0.58&#xa0;mm, n = 450), while TrueDepth-based SMs displayed a deviation of M = 1.1&#xa0;mm (SD =  ± 0.72&#xa0;mm, n = 450). The mean volumetric difference for photogrammetry-based SMs was M = 1.8&#xa0;cc (SD =  ± 2.12&#xa0;cc, n = 90), and M = 3.1&#xa0;cc (SD =  ± 2.64&#xa0;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&#xa0;mm. Volumetric measurements revealed LoA &gt; 2&#xa0;cc. Photogrammetry-based measurements demonstrated higher inter-observer reliability for overall landmark-to-landmark deviation.</p> Conclusion <p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年1月10日

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  • Robin Hartmann,
  • Maximilian Weiherer,
  • Felix Nieberle,
  • Christoph Palm,
  • Vanessa Brébant,
  • Lukas Prantl,
  • Philipp Lamby,
  • Torsten E. Reichert,
  • Jürgen Taxis,
  • Tobias Ettl

摘要

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.