Using Big Data to Assess Legitimacy of Plastic Surgery Information on Social Media

Background The proliferation of social media in plastic surgery poses significant difficulties for the public in determining legitimacy of information. This work proposes a system based on social network analysis (SNA) to assess the legitimacy of information contributors within a plastic surgery community. Objectives The aim of this study was to quantify the centrality of individual or group accounts on plastic surgery social media by means of a model based on academic plastic surgery and a single social media outlet. Methods To develop the model, a high-fidelity, active, and legitimate source account in academic plastic surgery (@psrc1955, Plastic Surgery Research Council) appearing only on Instagram (Facebook, Menlo Park, CA) was chosen. All follower-followed relationships were then recorded, and Gephi (https://gephi.org/) was used to compute 5 different centrality metrics for each contributor within the network. Results In total, 64,737 unique users and 116,439 unique follower-followed relationships were identified within the academic plastic surgery community. Among the metrics assessed, the in-degree centrality metric is the gold standard for SNA, hence this metric was designated as the centrality factor. Stratification of 1000 accounts by centrality factor demonstrated that all of the top 40 accounts were affiliated with a plastic surgery residency program, a board-certified academic plastic surgeon, a professional society, or a peer-reviewed journal. None of the accounts in the top decile belonged to a non–plastic surgeon or non-physician; however, this increased significantly beyond the 50th percentile. Conclusions A data-driven approach was able to identify and successfully vet a core group of interconnected accounts within a single plastic surgery subcommunity for the purposes of determining legitimate sources of information

Craniofacial Measurements of Donors and Recipients Correlate with Aesthetic Outcome in Virtual Face Transplantation

Background: Face transplantation is an increasingly feasible option for patients with severe disfigurement. Donors and recipients are currently matched based on immune compatibility, skin characteristics, age, and gender. Aesthetic outcomes of the match are not always optimal and not possible to study in actual cases due to ethical and logistical challenges. We have used a reproducible and inexpensive three-dimensional virtual face transplantation (VFT) model to study this issue. Methods: Sixty-one VFTs were performed using reconstructed high-resolution computed tomography angiographs of male and female subjects aged 20–69 years. Twenty independent reviewers evaluated the level of disfigurement of the posttransplant models. Absolute differences in 9 soft-tissue measurements and 16 bony cephalometric measurements from each of the VFT donor and recipient pretransplant model pairs were correlated to the reviewers’ evaluation of disfigurement after VFT through a multivariate logistic regression model. Results: Five soft-tissue measurements and 3 bony measurements were predictive of the rating of disfigurement after VFT (odds ratio; 95% confidence interval): trichion-to-nasion facial height (1.106; 1.066–1.148), endocanthal width (1.096; 1.051–1.142), exocanthal width (1.067; 1.036–1.099), mouth/chelion width (1.064; 1.019–1.110), subnasale-to-menton facial height (1.029; 1.003–1.056), inner orbit width (1.039; 1.009–1.069), palatal plane/occlusal plane angle (1.148; 1.047–1.258), and sella-nasion/mandibular plane angle (1.079; 1.013–1.150). Conclusions: This study provides early evidence for the importance of soft-tissue and bony measurements in planning of facial transplantation. With future improvements to immunosuppressive regimens and increased donor availability, these measurements may be used as an additional criterion to optimize posttransplant outcomes