Can a Point-of-Care 3D Printing Workflow Produce Accurate and Successful Results for Craniomaxillofacial Trauma?

Abstract

Computer-aided design and manufacturing (CAD/CAM) is having a profound impact on craniomaxillofacial surgery, and point-of-care (POC) solutions for repairing facial trauma are starting to emerge. The purpose of this study was to demonstrate the success and accuracy of a POC 3D printing workflow for craniomaxillofacial trauma. A retrospective cohort study was undertaken to analyze subjects presenting to a level 1 trauma center after sustaining facial trauma and were then treated using the POC 3D printing workflow. Subjects were excluded if they were not treated with the POC 3D printing workflow, were lost to follow-up, or if clinical data were incomplete. Predictor variables included the cause of trauma (mechanism), location of the mandibular fracture, type of fracture, mandibular severity score, and repair error (ie, root mean square error (RMSE) value for planned vs actual outcome). The primary outcome variables were case success and case error. Success was defined as clinical and radiographic evidence of bony stability at 3months. Case accuracy was calculated overlaying preoperative plan data to postoperative data generating a numerical value (RMSE value, mm). Covariates included age (years), gender (male/female), surgery time (mins), and CAD/CAM time (preoperative). Descriptive statistics were calculated for each variable. Dependence between rates or counts was established using the Wilcoxon rank sum or Fisher's exact test. Linear regression model was computed to discern how predictor variables influence RMSE. A P value<.05 was considered statistically significant. The sample included 27 subjects (19 male/8 female). The average age of all subjects was 46.4±18.0years. Common mechanisms of injury were assault (33%) and self-inflicted gunshots (SIGSW; 30%), and the average severity score for mandible injury was (13.5±3.3). Ninety-three percent of cases were deemed successful. The average repair accuracy (RMSE value) was 3.4±1.8mm. A linear regression model indicated those injured by a fall (β-coefficient 1.99; P=.010), motor vehicle collision (β-coefficient 1.49; P=.043), or SIGSW (β-coefficient 2.82; P<.001) correlated with RMSE. In-house CAD/CAM technologies can be utilized at the POC to repair complex facial trauma accurately and successfully.