Accuracy of three-dimensional photogrammetry and cone beam computed tomography based on linear measurements in patients with facial deformities

Comparison of methodologies for craniofacial soft-tissue cephalometrics: The value of virtual reality

BACKGROUND

Myriad options are available for plastic surgeons to perform soft-tissue analysis, which is vital to perioperative evaluation and research. Our objective is to compare the accuracy, precision, and efficiency of the available cephalometric modalities for conducting facial soft-tissue measurements.

METHODS

Twenty soft-tissue facial measurements were performed by 5 measurers with varying experiences on 5 adult subjects, using 6 methods-manual calipers, cone-beam CT, virtual reality (VR), 3D stereophotogrammetry, iPad-based 3D photogrammetry, and 2-dimensional photographs. Measurement sessions were timed and performed in triplicate, for a total of 9000 measurements. Intraclass correlation coefficient (ICC) was calculated for accuracy and one-way ANOVA was used for comparison. The coefficient of variation (CoV) was compared among groups to evaluate the precision of different methods by considering caliper measurements as the gold standard.

RESULTS

ICC among raters was 0.932, indicating excellent reliability. VR was significantly faster than other methods (137 s vs. 217 s for caliper, p < 0.001). CoV was the highest for 2D photographs and the lowest for VR (11.0 vs. 6.4, p < 0.001). The CoV of the caliper was similar to that of other methods, except for 2D photography, which was significantly higher. Measurements with the greatest absolute difference from caliper measurements, across modalities, were those around the eyes (left to right exocanthion), tragion to antitragion, and tragion to exocanthion.

CONCLUSION

2D photography is not an accurate method for cephalometric measurements. VR had the lowest variation between measurements, and was the fastest and equivalent to caliper measurements in accuracy. For studies involving a large number of cephalometrics, VR measurements may be a good option to improve study throughput.

3D Photography to Quantify the Severity of Metopic Craniosynostosis

This study aims to determine the utility of 3D photography for evaluating the severity of metopic craniosynostosis (MCS) using a validated, supervised machine learning (ML) algorithm.

This single-center retrospective cohort study included patients who were evaluated at our tertiary care center for MCS from 2016 to 2020 and underwent both head CT and 3D photography within a 2-month period.

The analysis method builds on our previously established ML algorithm for evaluating MCS severity using skull shape from CT scans. In this study, we regress the model to analyze 3D photographs and correlate the severity scores from both imaging modalities.

14 patients met inclusion criteria, 64.3% male (n = 9). The mean age in years at 3D photography and CT imaging was 0.97 and 0.94, respectively. Ten patient images were obtained preoperatively, and 4 patients did not require surgery. The severity prediction of the ML algorithm correlates closely when comparing the 3D photographs to CT bone data (Spearman correlation coefficient [SCC] r = 0.75; Pearson correlation coefficient [PCC] r = 0.82).

The results of this study show that 3D photography is a valid alternative to CT for evaluation of head shape in MCS. Its use will provide an objective, quantifiable means of assessing outcomes in a rigorous manner while decreasing radiation exposure in this patient population.

Facial Scanning Accuracy with Stereophotogrammetry and Smartphone Technology in Children: A Systematic Review

The aim of the study was to systematically review and compare the accuracy of smartphone scanners versus stereophotogrammetry technology for facial digitization in children. A systematic literature search strategy of articles published from 1 January 2010 to 30 August 2022 was adopted through a combination of Mesh terms and free text words pooled through boolean operators on the following databases: PubMed, Scopus, Web of Science, Cochrane Library, LILACS, and OpenGrey. Twenty-three articles met the inclusion criteria. Stationary stereophotogrammetry devices showed a mean accuracy that ranged from 0.087 to 0.860 mm, portable stereophotogrammetry scanners from 0.150 to 0.849 mm, and smartphones from 0.460 to 1.400 mm. Regarding the risk of bias assessment, fourteen papers showed an overall low risk, three articles had unclear risk and four articles had high risk. Although smartphones showed less performance on deep and irregular surfaces, all the analyzed devices were sufficiently accurate for clinical application. Internal depth-sensing cameras or external infrared structured-light depth-sensing cameras plugged into smartphones/tablets increased the accuracy. These devices are portable and inexpensive but require greater operator experience and patient compliance for the incremented time of acquisition. Stationary stereophotogrammetry is the gold standard for greater accuracy and shorter acquisition time, avoiding motion artifacts.