AI-enhanced "Two-thirds Guidelines" for Lipolifting: Addressing Multiple Hallmarks of Facial Aging

人工智能增强的“三分之二指导原则”在面部脂肪抽吸术中的应用:解决面部衰老的多种标志性特征

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Abstract

BACKGROUND: Facial aging involves complex changes such as volume loss, ligament weakening, and skin quality alterations. The "two-thirds guidelines" emerge as a novel strategy to combat these aging signs, drawing from an extensive analysis of 2800 facial fat grafting procedures conducted over two decades. METHODS: Guided by facial lipolifting data, including patient age, fat type (microfat and nanofat), and injection depth, this study devises a systematic framework for multilayer fat rejuvenation and ligament restoration. The two-thirds guidelines advocate injecting two-thirds of the patient's age for microfat and one-third for nanofat, with specific injection codes for lower, middle, and upper facial regions. RESULTS: A prospective study involving 400 patients confirms the efficacy of the two-thirds guidelines. However, applicability may vary for patients outside SD ranges, particularly concerning facial proportions and body mass index. Patients within the golden ratio range (1.4-1.9) report high satisfaction rates and a 50% fat graft uptake, with minimal complications. For patients outside this range, an artificial intelligence (AI) program was implemented. CONCLUSIONS: The two-thirds guidelines offer a comprehensive approach to facial rejuvenation, addressing volume loss, ligament weakening, and skin quality. They are applicable in early aging stages, promising enduring and natural outcomes while mitigating effects of weight fluctuations. These guidelines provide a safe, replicable, and adaptable approach to facial fat grafting, either standalone or in combination with facelift techniques, with minimized overfilling risks. A dataset obtained from 2800 patients serves as the foundation for developing an AI program tailored to aid doctors in diagnosing and treating similar cases.

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