Background Managing patient expectations is important to ensuring patient satisfaction in aesthetic medicine. To this end, computer technology developed to photograph, digitize, and manipulate three-dimensional (3D) objects has been applied to the female breast. However, the systems remain complex, physically cumbersome, and extremely expensive. Objectives The authors of the current study wish to introduce the plastic surgery community to BreastGAN, a portable, artificial intelligence-equipped tool trained on real clinical images to simulate breast augmentation outcomes. Methods Charts of all patients who underwent bilateral breast augmentation performed by the senior author were retrieved and analyzed. Frontal before and after images were collected from each patient’s chart, cropped in a standardized fashion, and used to train a neural network designed to manipulate before images to simulate a surgical result. AI-generated frontal after images were then compared to the real surgical results. Results Standardizing the evaluation of surgical results is a timeless challenge which persists in the context of AI-synthesized after images. In this study, AI-generated images were comparable to real surgical results. Conclusions This study features a portable, cost-effective neural network trained on real clinical images and designed to simulate surgical results following bilateral breast augmentation. Tools trained on a larger dataset of standardized surgical image pairs will be the subject of future studies.

Background: Positional plagiocephaly has garnered increased research interest since the introduction of the Back to Sleep campaign in the 1990s, and the subsequent increase in infants with cranial deformity. Research has focused on treatment outcomes and developing new modalities to address asymmetric heads. Little attention has been given to the cost of treatment and diagnosis. This study aimed to summarize the literature and provide an overview of the costs associated with a diagnosis of positional plagiocephaly. Methods: A literature review was performed by searching PubMed and Ovid Embase to identify studies pertaining to the “cost” of plagiocephaly diagnosis or treatment through direct financial factors, disturbance to daily routines (ie, through treatment prolongation), or related stress. Results: Twenty-nine peer-reviewed studies were included. Treatment options for plagiocephaly are stratified by severity and age of diagnosis, with different pathways available to treat different stages of asymmetry. The common factor across all treatment modalities is that earlier diagnosis unequivocally leads to better aesthetic outcomes and shorter treatment times. This leads to lower costs for treatment, a lower stress burden for parents, and lower costs for the healthcare system in the future through reduction of long-term effects. Our theoretical cost model suggests that early diagnosis at 4 months can lead to a treatment cost of $1495, when compared with $5195 for detection of deformity at or after 6 months. Conclusion: The dramatic cost disparity between early and late diagnosis highlights the need for reliable methods to accurately detect cranial deformity early in an infant’s life.

This article summarizes the current state of diagnostic modalities for infant craniofacial deformities and highlights capable diagnostic tools available currently to pediatricians.

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