Boonipat, Thanapoom

Summary: Social interactions are largely dependent on the interpretation of information conveyed through facial expressions. Although facial reanimation seeks restoration of the facial expression of emotion, outcome measures have not addressed this directly. This study evaluates the use of a machine learning technology to directly measure facial expression before and after facial reanimation surgery. Fifteen study subjects with facial palsy were evaluated both before and after undergoing cross-facial nerve grafting and free gracilis muscle transfer. Eight healthy volunteers were assessed for control comparison. Video footage of subjects with their face in repose and with a posed, closed-lip smile was obtained. The video data were then analyzed using the Noldus FaceReader software application to measure the relative proportions of seven cardinal facial expressions detected within each clip. The facial expression recognition application detected a far greater happy signal in postoperative (42 percent) versus preoperative (13 percent) smile videos (p < 0.0001), compared to 53 percent in videos of control faces smiling. This increase in postoperative happy signal was achieved in exchange for a reduction in the sad signal (15 percent to 9 percent; p = 0.092) and the neutral signal (57 percent to 37 percent; p = 0.0012). For video clips of patients in repose, no significant difference in happy emotion was detected between preoperative (3.1 percent) and postoperative (1.4 percent) states (p = 0.5). This study provides the first proof of concept for the use of a machine learning software application to objectively quantify facial expression before and after surgical reanimation. CLINICAL QUESTION/LEVEL OF EVIDENCE: Diagnostic, IV.

Abstract Background The use of eye-tracking technology in plastic surgery has gained popularity over the past decade due to its ability to assess observers’ visual preferences in an objective manner. Objectives The goal of this study was to provide a comprehensive review of eye-tracking studies in plastic and reconstructive surgery, which can aid in the design and conduct of high-quality eye-tracking studies. Methods Through application of Preferred Reporting Items for Systematic review and Meta-Analysis (PRISMA) guidelines, a comprehensive search of articles published on eye-tracking across several databases was conducted from January 1946 to January 2019. Inclusion criteria included studies evaluating the use of eye-tracking technology in the field of plastic and reconstructive surgery. The resulting publications were screened by 2 independent reviewers. Results A total of 595 articles were identified, 23 of which met our inclusion criteria. The most common application of eye-tracking was to assess individuals with cleft lip/palate (9 studies). All 19 studies that evaluated fixation patterns among conditions vs controls reported significant differences between the 2 groups. Five out of 7 studies assessing visual data between preoperative and postoperative patients identified significant differences between the preoperative and postoperative groups, whereas 2 studies did not. Nine studies examined the relation between severity indices, attractiveness scores, or personality ratings and gaze patterns. Correlation was found in 7 out of the 9 studies. Conclusions This systematic review demonstrates the utility of eye-tracking technology as a quantifiable objective assessment and emerging research tool for evaluating outcomes in several domains of plastic and reconstructive surgery.

We provide a case report of reconstruction of a massive chest wall defect after recurrent phyllodes tumour resections. The reconstruction used a bipedicled groin and latissimus dorsi flap, with composite rib autologous reconstruction. The patient successfully recovered from the operation. Our case illustrates the applicability of this flap in the armamentarium of anterior chest wall reconstructive options.