Narrative review demonstrates that AI-enhanced ultrasound improves safety and outcomes in Brazilian butt lift surgeries, suggesting a shift toward better practices.
Background: The Brazilian butt lift (BBL) is increasingly guided by ultrasound to avoid deep or intramuscular fat placement, which has been associated with fatal pulmonary fat embolism. Real-time visualization of the superficial and deep gluteal fasciae improves safety, but consistent plane identification can remain challenging. Artificial intelligence (AI) may augment ultrasound by assisting with tissue-layer recognition, cannula tracking, and standardized interpretation. Methods: A narrative review of gluteal anatomy, historical safety guidelines, and contemporary evidence on ultrasound-guided BBL was performed. We additionally outlined an AI-assisted ultrasound workflow and described a detailed surgical technique using mobile, handheld ultrasound with integrated AI-based optimization features. A preliminary retrospective clinical experience using this method was evaluated to assess feasibility and early safety signals. Results: Ultrasound reliably enables identification of the gluteal fascial layers and supports subcutaneous-only fat placement. AI-assisted visualization further enhances anatomical consistency, facilitates plane confirmation during injection, and may reduce operator-dependent variability. In our early clinical experience, the workflow was feasible, with no major complications observed and satisfactory short-term outcomes. Conclusions: Ultrasound guidance has significantly improved the safety profile of BBL by allowing continuous confirmation of subcutaneous fat placement. The integration of AI offers a promising adjunct that may enhance precision, standardize technique, and expand accessibility for surgeons with varying levels of experience. Preliminary findings support the practicality of AI-assisted ultrasound; however, larger datasets are needed to validate its impact on outcomes and long-term safety.
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Kazzi et al. (2026) studied this question.
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