Role of Simulation and Artificial Intelligence in Plastic Surgery Training

Abstract

Plastic surgery is an intricate field that requires cognitive proficiency, advanced technical skill, and sound surgical judgment. One challenge for plastic surgery residents is mastering these surgical skills while also respecting duty hours and providing high-quality patient care. In the face of these demands, resident surgical training must expand to meet the competency-based goals of the residency curriculum. Two potential methods of expansion are through the use of (1) simulation and (2) artificial intelligence as tools for both training and skill evaluation. In 2018, Thomson et al. identified 12 simulators currently implemented in plastic surgery.1 These simulators were divided into four modalities: computer-based (n = 5), synthetic (n = 2), animal (n = 2), and cadaver (n = 3). Combined, these simulators have present-day applications in reconstructive surgery, craniofacial surgery, and microsurgery; they evaluate a range of skills, from identifying anatomy to performing a procedure.1 Although computer-based simulators provide high-resolution and three-dimensional visualizations, they reinforce learning primarily through repetition. Although repetition is important for muscle memory, over time, it undermines active acquisition of new skill sets. Synthetic simulators provide anatomical representation but do not fully resemble actual tissue and require replacement after use. Animal simulators are used to practice sewing anastomoses in microvascular surgery and are great for developing microsurgical technical skills; however, ethical issues often limit the use of animal models in medicine. Cadavers have the highest fidelity and provide the most accurate anatomical accuracy and variation but are expensive and may act as reservoirs for communicable diseases. These simulator modalities have been shown to improve baseline skills, but additional studies are required to assess residents’ performance in the operating room. Plana et al. suggest that the lack of scientific evidence for improvement in trainee performance after simulation practice may explain skepticism by faculty members regarding its utility in training. In light of this hypothesis, they conducted a prospective, randomized, blind study and showed statistically significant improvement in trainees’ performance of cleft repair surgery using digital simulation versus textbook learning.2 Therefore, scientific studies that provide evidence for the utility and benefits of simulation in surgical training can help promote widespread integration of this novel technology into training programs. Artificial intelligence may have an even larger impact on surgical training if properly implemented. Artificial intelligence encompasses a number of subfields, including machine learning. Machine learning has the ability to analyze big data and learn to recognize patterns, predict outcomes, and increase accuracy with each iteration. In plastic surgery, machine learning already has multiple existing applications in burn, hand, microscopic, craniofacial, and aesthetic surgery.3 In aesthetics, for example, machine learning has been used to assess what people view as “beautiful” and their emotional response to cosmetic procedures.4,5 Knowledge of objective geometric parameters that elicit the best perceived aesthetic and emotional outcomes can drive surgical planning and improve patient counseling. Machine learning may also have powerful applications in enhancing plastic surgery training. When applied to video recordings of trainees, machine learning can assess both skills achieved and underdeveloped and can predict likely postoperative outcomes.3 A tool that identifies the quality of surgical techniques and predicts outcomes could be used to provide teaching points for trainees as they assess their own skills in the operating room. By using historical data, artificial intelligence offers trainees a safe space to learn from mistakes by positive or negative reinforcement of surgical techniques. Plastic surgeons are known for being adaptable and innovative, but simulation and artificial intelligence remain underused in plastic surgery. Although both have different sets of limitations to integration into surgical training, their potential is expansive. Overcoming these limitations will set the stage for the field of plastic surgery to move forward in the modern era of technology and medicine. DISCLOSURE The authors have no financial interests in this article and have received no external support related to this commentary.

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