Pushing the boundaries in autologous breast reconstruction: innovations from imaging to artificial intelligence - Scherrer, Isabell; Horch, Raymund E.; Promny, Dominik; Promny, Theresa; Eschenbacher, Elisabeth; Arkudas, Andreas (Frontiers in Surgery, 2025)
Breast cancer remains the most commonly diagnosed malignancy among women worldwide, with surgical intervention, ranging from breast-conserving procedures to total mastectomy, representing a cornerstone of curative treatment. In this context, breast reconstruction has become an essential component of comprehensive cancer treatment, addressing not only physical restoration but also playing a vital role in psychosocial rehabilitation and body image. Among the various reconstructive options, autologous tissue transfer has emerged as the preferred method for many patients, offering durable and natural-feeling results. In particular, abdominal-based free flaps such as the Deep Inferior Epigastric Perforator (DIEP) flap and the muscle-sparing Transverse Rectus Abdominis Myocutaneous (ms-TRAM) flap offer excellent results with reduced donor side morbidity. As the global number of breast cancer continues to rise, the demand for safe, individualized, and functionally superior reconstructive options rises as well. This article aims to provide a general overview of current surgical approaches and to highlight perspectives for future innovations in improving autologous breast reconstruction and patient satisfaction.
CRIS-Team Scopus Importer:2025-10-24
Keywords: 3D imaging; artificial intelligence; autologous breast reconstruction; breast cancer; breast reconstruction