Abstract
Accurate preoperative estimation of flap weight is essential for successful breast reconstruction using the deep inferior epigastric perforator (DIEP) flap. However, current methods relying on physical examination or experience are often subjective. We developed a simple objective method for predicting DIEP flap weight using Synapse Vincent, a widely available 3-dimensional image analysis software program. This prospective study included 40 patients who underwent autologous breast reconstruction using DIEP flaps between January 2020 and September 2023. A semicylindrical 3-dimensional model of the abdominal subcutaneous tissue was constructed from preoperative computed tomography images using Synapse Vincent. The volume of the model was converted to the predicted flap weight by assuming a fat density of 1.0 g/cm³. The predicted and actual intraoperative flap weights were compared using Pearson correlation and linear regression analyses. The mean predicted flap weight was 732 ± 306 g, and the mean actual flap weight was 754 ± 310 g. A strong correlation was observed between predicted and actual weights (r = 0.938, P < 0.0001). The regression formula was as follows: actual weight = 0.9391 × predicted weight + 68.98. The coefficient of determination (R²) was 0.88, and the root mean square percentage error was 17%, indicating high predictive accuracy. Our method using Synapse Vincent allows accurate and practical preoperative estimation of DIEP flap weights. Its ease of use, broad availability, and compatibility with standard computed tomography imaging make it a valuable tool for surgical planning in autologous breast reconstruction.