Alameddine, Khaled O.

Abstract Goals/Purpose The imperative for precision in aesthetic surgery necessitates a robust framework for evaluating the impact of facial interventions on perceived age. Our study introduces a cutting-edge AI model aimed at discerning an individual's perceived age from facial characteristics. This tool is designed to augment the assessment of various plastic surgery procedures, facilitating the tailoring of interventions to each patient's unique facial aging pattern. Methods/Technique We harnessed a deep convolutional neural network (DCNN), pre-trained on the extensive ImageNet dataset, and further refined using 523,051 pre-annotated facial images from the IMBD-WIKI database, normalized as per the Mathias et al. face detection paradigm. Faces were processed into a 299x299 pixel matrix, maintaining a 40% margin around the face for uniformity. The Xception architecture was employed for its advanced feature extraction capabilities. The model was refined and tested against a diverse set of 100 patient faces from the Mayo Clinic's database, categorized by demographic and procedural data. The AI model employed regression analysis and softmax probability for precise age estimation. Results/Complications The AI model exhibited a remarkable accuracy rate of 92.5% in age estimation for pre procedural patients, with a standard deviation of 3.2 years. It significantly outperformed traditional methods in identifying fine-grained age-related features. The AI model discerned an average perceived age reduction of 3.5 years across all patients post-procedure, with a notable variance among different types of surgeries. Certain procedures, such as rhytidectomy and blepharoplasty, showed a more pronounced age-reduction effect. Conclusion The AI model presents an accurate and objective method for quantifying perceived age, serving as a significant benchmark in facial aesthetic evaluation. By illustrating measurable age reduction following various procedures, with some surgeries yielding more substantial changes in perceived age, the model stands as a testament to the effectiveness of plastic surgery interventions. The precision of our model in predicting age pre- and post-procedure underscores its potential to assist surgeons in custom-tailoring surgeries to individual aging patterns. This innovation is poised to refine the decision-making process in aesthetic surgery, ensuring treatments are aligned with the desired outcomes for rejuvenation and patient-specific needs, ultimately advancing the frontier of personalized plastic surgery.

Abstract Goals/Purpose Patients with adjuvant radiotherapy are significantly more likely to have complications such as infections and wound dehiscence following breast surgery.1 Closed incision negative pressure wound therapy (cINPT) holds incision edges together, prevents external contamination and removes exudate, promoting tensile strength and increased collagen recruitment at the incision site compared to the standard of care dressings.2 cINPT is helpful in surgical closures on high-risk patients.3 We evaluated the complication rates following the use of cINPT in implant-based breast reconstruction. Methods/Technique A cohort was collected retrospectively from a single institution, from January 1, 2018 to October 31 2022. The complication rates were then compared between cINPT dressing and standard-of-care dressings on radiated patients following breast surgery. Results/Complications The data collected consist of a total of 83 radiated breasts that underwent implant based reconstruction. cINPT was used in 41 breasts and standard-of-care dressings were used in 42 breasts. Of the cINPT cohort, 2 patients developed seromas that required bedside aspirations (4.8%) and one patient developed an infection (2.4%) with none of the patients requiring re operations. Of the standard of care dressings cohort, 9 patients developed seromas (21.4%), and 3 patients developed infections (7.1%), of which 3 patients required reoperations (7.1%). Conclusion Patients with prior radiation who received cINPT had lower risk of developing complications compared to patients with prior radiation who received standard-of-care dressings.