Artificial intelligence-enabled simulation of gluteal augmentation: A helpful tool in preoperative outcome simulation?

Leonard Knoedler; Jan Odenthal; Lukas Prantl; Berkin Oezdemir; Andreas Kehrer; Martin Kauke-Navarro; Dany Y Matar; Doha Obed; Adriana C Panayi; P Niclas Broer; Christian Chartier; Samuel Knoedler

doi:10.1016/j.bjps.2023.01.039

Artificial intelligence-enabled simulation of gluteal augmentation: A helpful tool in preoperative outcome simulation?

J Plast Reconstr Aesthet Surg. 2023 May:80:94-101. doi: 10.1016/j.bjps.2023.01.039. Epub 2023 Feb 9.

Authors

Affiliations

¹ Department of Plastic, Hand and Reconstructive Surgery, University Hospital Regensburg, Regensburg, Germany.
² Department of General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany.
³ Department of Surgery, Division of Plastic and Reconstructive Surgery, Yale New Haven Hospital, Yale School of Medicine, New Haven, CT, USA.
⁴ Department of Surgery, Division of Plastic Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
⁵ Department of Surgery, Division of Plastic Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Plastic, Aesthetic, Hand and Reconstructive Surgery, Hannover Medical School, Hannover, Germany.
⁶ Department of Plastic, Reconstructive, Hand and Burn Surgery, Bogenhausen Academic Teaching Hospital Munich, Munich, Germany.
⁷ McGill University Faculty of Medicine, Montreal, Canada.
⁸ Department of Surgery, Division of Plastic Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Plastic Surgery and Hand Surgery, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany. Electronic address: samuel.knoedler@tum.de.

PMID: 37001299
DOI: 10.1016/j.bjps.2023.01.039

Abstract

Background: While the buttock region is considered an esthetic hallmark, the Brazilian butt lift (BBL) remains controversially discussed in the plastic surgery community. This is due to its contentious safety profile. Thus, informed consent and patient education play a key role in preoperative planning. To this end, we aimed to program an easy-to-use, widely accessible, and low-budget algorithm that produces reliable outcome simulations.

Methods: The conditional generative adversarial network (GAN) was trained using pre- and postoperative images from 1628 BBL patients. To validate outcome simulation, 25 GAN-generated images were assessed deploying 67 Amazon Mechanical Turk Workers (Mturks).

Results: Mturks could not differentiate between GAN-generated and real patient images in approximately 49.4% of all trials.

Conclusion: This study presents a free-to-use, widely accessible, and reliable algorithm to visualize potential surgical outcomes that could potentially be applied in other fields of plastic surgery.

Keywords: Artificial intelligence; Autologous fat grafting; Brazilian butt lifting; Gluteal augmentation.

MeSH terms

Algorithms
Artificial Intelligence*
Buttocks / surgery
Humans
Plastic Surgery Procedures*
Surgical Flaps / surgery