3D Photography to Quantify the Severity of Metopic Craniosynostosis
Madeleine K. Bruce, BA; Wenzheng Tao; Justin Beiriger, BSE; Cameron Christensen; Miles J. Pfaff, MD; Ross Whitaker, PhD; Jesse A. Goldstein, MD
Department of Plastic Surgery, UPMC Children's Hospital of Pittsburgh
Presenter: Madeleine Bruce, BA
Director Name: Vu Nguyen
Author Category: Medical Student
Presentation Category: Clinical
Abstract Category: Craniomaxillofacial
This study aims to determine the utility of 3D photography for evaluating the severity of metopic craniosynostosis (MCS) using a validated machine learning (ML) algorithm. Objective measurement of head shape in patients with MCS is critical to understanding the spectrum of severity and patient outcomes after surgery. Furthermore, the use of 3D photography will aid in the reduction of unnecessary radiation exposure in this patient population.
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 were included. 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.
Author Contact Information:
Department of Plastic Surgery
4401 Penn Avenue