Current Advances in Artificial Intelligence in the Field of Aesthetic Surgery and Breast Augmentation: Short Review

Abstract

Study design: This review is structured as a systematic analysis of the literature to evaluate the impacts of artificial intelligence (AI) on the field of plastic surgery, with a focus on breast augmentation and aesthetic surgical procedures. Key areas of exploration include advancements in machine-learning techniques relevant to plastic surgery, the integration of AI into preoperative planning processes, and the historical evolution of AI in aesthetic surgery. The review also systematically assesses current AI tools specifically developed for breast augmentation, such as 3D imaging and predictive analytics, to understand their efficacy and role in clinical practice. Objective: This article explores the current state and future prospects of AI in plastic surgery, with a focus on breast augmentation and aesthetic procedures. Emphasis is placed on the benefits, challenges, and the imperative for collaborative efforts in the integration of AI technologies. Methods: Advancements in machine-learning algorithms and AI technologies are examined for their potential in automating the assessment and enhancement of surgical skills. The role of AI in facilitating objective evaluations in aesthetic surgery is discussed, addressing challenges such as the lack of standardized training datasets and integration issues. The importance of mitigating potential biases introduced by AI to ensure objectivity in patient assessments is highlighted. Results: The article discusses the historical evolution of AI, from Alan Turing’s conceptualization to contemporary applications in aesthetic surgery. Artificial intelligence’s ability to analyze vast patient datasets is explored, showcasing its potential for offering personalized treatment recommendations and improving accuracy over time. Specific AI tools for breast augmentation, including Canfield Mirror, QuantifiCare LifeViz Infinity Pro, Crisalix, BreastGAN, Arbrea Breast Software (ABS), and Deep Surface AI, are examined in detail, emphasizing their advantages and drawbacks. Conclusions: Evaluation of clinical photography techniques, relying on specific hardware, is presented, with consideration given to the potential of AI-based illumination systems to enhance consistency in preoperative images. The review concludes by envisioning the transformative future of AI in aesthetic surgery, considering its untapped potential in diagnostic imaging, personalized treatment plans, and enhanced surgical precision through integration with virtual and augmented reality. Despite challenges, the promises of AI in personalized treatments, precise patient care, and improved surgical assistance suggest a transformative future for plastic surgery, contingent on addressing current concerns. Collaborative efforts are deemed essential for the successful implementation of AI technologies in the field.