Evidence map›Paper›PMID 42004773›Full record

ArticlePlastic and reconstructive surgery. Global open2026

Enhancing Safety and Outcomes in Brazilian Butt Lift: Mobile Ultrasound With Artificial Intelligence.

Tony Kazzi, Joanne El Turk, Rawad Baroud

Abstract read
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Tony KazziFrom the Division of Plastic and Reconstructive Surgery, University of Balamand, Beirut, Lebanon.
Joanne El TurkFaculty of Medicine, American University of Beirut, Beirut, Lebanon.
Rawad BaroudProfessor Farid Hakme Alumni Association, Hospital da Plástica, Rio de Janeiro, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Identifiers

PMID42004773
PMCPMC13090055

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.