Nipple or skin-sparing mastectomy flap: can preoperative breast-MRI predict post-operative complications?

Authors

L I Sgaramella, A Pasculli, F P Prete, F Cofone, M Moschetta, M Maruccia, R Elia, M Telegrafo, V De Ruvo, M Bisceglie, M M Miccoli, F Palma, C Testini, G Giudice, M Testini, A Gurrado, BCUPoliBa Working Group

Published in

Updates in surgery. Oct 13, 2026. Epub Oct 13, 2026.

Abstract

This study aimed to evaluate the role of skin flap thickness (SFT), measured by preoperative breast magnetic resonance imaging (MRI), in predicting postoperative complications after nipple-sparing or skin-sparing mastectomy, and to assess its value in guiding reconstructive strategy selection.
We conducted a retrospective single-center study including patients who underwent preoperative breast MRI and nipple-sparing or skin-sparing mastectomy for breast cancer or BRCA1/2 mutations between January 2019 and August 2025. Demographic, clinical, and perioperative data were collected. Patients were stratified into two groups based on mean preoperative SFT: >8 mm (Group A) and <8 mm (Group B). Postoperative complications were recorded and analyzed using univariate and multivariate models.
Sixty patients (mean age 47.5 ± 9.1 years) and 80 breasts (40 unilateral, 20 bilateral procedures) were included. Group A comprised 54 breasts (67.5%), while Group B included 26 (32.5%). Postoperative hospital stays and incision type differed significantly between groups (p < 0.05). Overall postoperative morbidity was 16.25%. Partial nipple-areola complex necrosis (11.5%) and hematoma (7.7%) occurred significantly more often in Group B compared to Group A (both p < 0.05). Multivariate analysis confirmed preoperative SFT <8 mm as an independent predictor of these complications (odds ratio 13.40, p = 0.012).
Preoperative magnetic resonance imaging assessment of skin flap thickness reliably identifies patients at increased risk of postoperative complications. Integrating this parameter into surgical planning may support personalized reconstructive decision-making and improve clinical outcomes.

PMID:
42870219
Bibliographic data and abstract were imported from PubMed on 14 Oct 2026.

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