Aesthetic surgery journal · 2021
Facelift Surgery Turns Back the Clock: Artificial Intelligence and Patient Satisfaction Quantitate Value of Procedure Type and Specific Techniques.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Gibstein Alexander R, Chen Kevin, Nakfoor Bruce, Lu Stephen M, Cheng Roger, Thorne Charles H, Bradley James P
Аннотация
BACKGROUND: Patients desire facelifting procedures to look younger, refreshed, and attractive. Unfortunately, there are few objective studies assessing the success of types of facelift procedures and ancillary techniques.
OBJECTIVES: The authors sought to utilize convolutional neural network algorithms alongside patient-reported FACE-Q outcomes to evaluate perceived age reduction and patient satisfaction following various facelift techniques.
METHODS: Standardized preoperative and postoperative (1-year) images of patients who underwent facelift procedures were analyzed by 4 neural networks to estimate age reduction after surgery (n = 105). FACE-Q surveys were employed to measure patient-reported facial aesthetic outcome. We compared (1) facelift procedure type: skin-only vs superficial musculoaponeurotic system (SMAS)-plication, vs SMAS-ectomy; and (2) ancillary techniques: fat grafting (malar) vs no fat grafting. Outcomes were based on complications, estimated age-reduction, and patient satisfaction.
RESULTS: The neural network preoperative age accuracy score demonstrated that all neural networks were accurate in identifying our patients' ages (mean score = 100.4). SMAS-ectomy and SMAS-plication had significantly greater age-reduction (5.85 and 5.35 years, respectively) compared with skin-only (2.95 years, P < 0.05). Fat grafting compared to no fat grafting demonstrated 2.1 more years of age reduction. Facelift procedure type did not affect FACE-Q scores; however, patients who underwent fat grafting had a higher satisfaction with outcome (78.1 ± 8 vs 69 ± 6, P < 0.05) and decision to have the procedure (83.0 ± 6 vs 72 ± 9, P < 0.05).
CONCLUSIONS: Artificial intelligence algorithms can reliably estimate the reduction in apparent age after facelift surgery. Facelift technique, like SMAS-ectomy or SMAS-plication, and specific technique, like fat grafting, were found to enhance facelifting outcomes and patient satisfaction.
OBJECTIVES: The authors sought to utilize convolutional neural network algorithms alongside patient-reported FACE-Q outcomes to evaluate perceived age reduction and patient satisfaction following various facelift techniques.
METHODS: Standardized preoperative and postoperative (1-year) images of patients who underwent facelift procedures were analyzed by 4 neural networks to estimate age reduction after surgery (n = 105). FACE-Q surveys were employed to measure patient-reported facial aesthetic outcome. We compared (1) facelift procedure type: skin-only vs superficial musculoaponeurotic system (SMAS)-plication, vs SMAS-ectomy; and (2) ancillary techniques: fat grafting (malar) vs no fat grafting. Outcomes were based on complications, estimated age-reduction, and patient satisfaction.
RESULTS: The neural network preoperative age accuracy score demonstrated that all neural networks were accurate in identifying our patients' ages (mean score = 100.4). SMAS-ectomy and SMAS-plication had significantly greater age-reduction (5.85 and 5.35 years, respectively) compared with skin-only (2.95 years, P < 0.05). Fat grafting compared to no fat grafting demonstrated 2.1 more years of age reduction. Facelift procedure type did not affect FACE-Q scores; however, patients who underwent fat grafting had a higher satisfaction with outcome (78.1 ± 8 vs 69 ± 6, P < 0.05) and decision to have the procedure (83.0 ± 6 vs 72 ± 9, P < 0.05).
CONCLUSIONS: Artificial intelligence algorithms can reliably estimate the reduction in apparent age after facelift surgery. Facelift technique, like SMAS-ectomy or SMAS-plication, and specific technique, like fat grafting, were found to enhance facelifting outcomes and patient satisfaction.