Akamine Nozomu, Matsumine Hajime, Sakurai Hiroyuki
From the Department of Plastic and Reconstructive Surgery, School of Medicine, Tokyo Women's Medical University, Tokyo, Japan.
Plast Reconstr Surg Glob Open. 2025 Aug 20;13(8):e7064. doi: 10.1097/GOX.0000000000007064. eCollection 2025 Aug.
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 ( = 0.938, < 0.0001). The regression formula was as follows: actual weight = 0.9391 × predicted weight + 68.98. The coefficient of determination (²) 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.
对于使用腹壁下深动脉穿支（DIEP）皮瓣进行成功的乳房重建而言，术前准确估计皮瓣重量至关重要。然而，目前依靠体格检查或经验的方法往往具有主观性。我们开发了一种简单的客观方法，使用广泛可用的三维图像分析软件程序Synapse Vincent来预测DIEP皮瓣重量。这项前瞻性研究纳入了2020年1月至2023年9月期间接受DIEP皮瓣自体乳房重建的40例患者。使用Synapse Vincent从术前计算机断层扫描图像构建腹部皮下组织的半圆柱形三维模型。通过假设脂肪密度为1.0 g/cm³，将模型体积转换为预测的皮瓣重量。使用Pearson相关性分析和线性回归分析比较预测的和实际术中皮瓣重量。预测皮瓣重量的平均值为732 ± 306 g，实际皮瓣重量的平均值为754 ± 310 g。观察到预测重量与实际重量之间存在强相关性（ = 0.938， < 0.0001）。回归公式如下：实际重量 = 0.9391 × 预测重量 + 68.98。决定系数（²）为0.88，均方根百分比误差为17%，表明预测准确性高。我们使用Synapse Vincent的方法能够准确且实用地术前估计DIEP皮瓣重量。其易于使用、广泛可用以及与标准计算机断层扫描成像的兼容性使其成为自体乳房重建手术规划的有价值工具。
