Automated Fat-tissue Extraction for Preoperative Estimation of Profunda Artery Perforator Flap Weight in Breast Reconstruction: A Three-dimensional Computed Tomography–Based Analysis

Summary: This study aims to establish an objective and reproducible method for estimating profunda artery perforator (PAP) flap weight by incorporating automated fat-tissue extraction using computed tomography (CT) attenuation thresholds. Thirty-two women who underwent breast reconstruction using PAP flaps were retrospectively analyzed. Preoperative CT data were processed using the Synapse Vincent system to generate 3-dimensional models. Adipose tissue in the flap region was automatically segmented using predefined Hounsfield unit thresholds (–150 to –50 HU). Predicted flap weight was calculated by assuming a fat density of 0.9 g/cm 3 and compared with the intraoperative weight using Pearson correlation and linear regression analyses. The mean predicted and actual flap weights were 294.9 ± 73.1 and 272.4 ± 69.8 g, respectively, and demonstrated a strong correlation ( r = 0.9149, P < 0.0001). The flap weight estimation formula obtained by linear regression was as follows: actual weight = 0.8628 × predicted weight + 30.39. The coefficient of determination (R 2 = 0.837) and root–mean-square percentage error (10.33%) indicated high predictive accuracy. Bland–Altman analysis showed a bias of −6.99 g (limits, −62.34 to 48.36 g). Automated fat-tissue extraction using 3-dimensional CT modeling is a rapid and noninvasive technique for reliable estimation of PAP flap weight and may improve preoperative planning for perforator flap breast reconstruction.