Perfusion area versus volume of the DIEP flap: A multivariable analysis of perforator and flap characteristics for estimation of perfusion area and volume

Background: The extent of perfusion of a deep inferior epigastric artery perforator (DIEP) flap is a primary concern for surgeons. This study aimed to determine whether the flap area or volume can be estimated using perforator and flap characteristics. Methods: Intraoperative flap perfusion was assessed using indocyanine green angiography in patients who underwent DIEP flap breast reconstruction between November 2018 and February 2023. The area perfused by a single dominant perforator was delineated on the surface of the flap and measured using the ImageJ software. Multiple linear regression analysis was conducted to estimate the 'perfusion ratio,' defined as the perfused area divided by the total flap area. Potential predictor variables included flap size (cm(2)), flap thickness (mm), perforator diameter (mm), perforator rows (medial/lateral), vertical location of perforator (at or above/below the umbilicus), and perforator eccentricity (vertical distance from upper flap margin to perforator, cm). Results: In total, 101 patients were included in this analysis. The mean 'perfusion ratio' was 67.8% +/- 11.5%, predicted by perforator diameter (p = 0.022) and vertical location below umbilicus (p < 0.001) with positive correlations and negatively correlated with flap thickness (p = 0.003) in the multivariable analysis. Both perfusion area and weight were predicted by perforator diameter, vertical location of perforator, flap size, and flap thickness (p < 0.001). The coefficient of determination (adjusted R-2) for prediction of perfusion weight was higher than that for the perfusion area (75.5% vs. 69.4%). Conclusions: Flap volume, rather than area, is determined by a perforator of a given diameter and location. (c) 2024 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.