Rome, Italy From the Plastic Surgery Unit, Sant'Andrea Hospital, School of Medicine and Psycology, and the Department of Infectious Diseases and Public Health, School of Medicine and Dentistry, "Sapienza" University of Rome.
Plast Reconstr Surg. 2013 Jul;132(1):1e-7e. doi: 10.1097/PRS.0b013e318290f6bd.
Breast volume assessment enhances preoperative planning of both aesthetic and reconstructive procedures, helping the surgeon in the decision-making process of shaping the breast. Numerous methods of breast size determination are currently reported but are limited by methodologic flaws and variable estimations. The authors aimed to develop a unifying predictive formula for volume assessment in small to large breasts based on anthropomorphic values.
Ten anthropomorphic breast measurements and direct volumes of 108 mastectomy specimens from 88 women were collected prospectively. The authors performed a multivariate regression to build the optimal model for development of the predictive formula. The final model was then internally validated. A previously published formula was used as a reference.
Mean (±SD) breast weight was 527.9 ± 227.6 g (range, 150 to 1250 g). After model selection, sternal notch-to-nipple, inframammary fold-to-nipple, and inframammary fold-to-fold projection distances emerged as the most important predictors. The resulting formula (the BREAST-V) showed an adjusted R of 0.73. The estimated expected absolute error on new breasts is 89.7 g (95 percent CI, 62.4 to 119.1 g) and the expected relative error is 18.4 percent (95 percent CI, 12.9 to 24.3 percent). Application of reference formula on the sample yielded worse predictions than those derived by the formula, showing an R of 0.55.
The BREAST-V is a reliable tool for predicting small to large breast volumes accurately for use as a complementary device in surgeon evaluation. An app entitled BREAST-V for both iOS and Android devices is currently available for free download in the Apple App Store and Google Play Store.
CLINICAL QUESTION/LEVEL OF EVIDENCE: Diagnostic, II.
乳房体积评估可增强美容和重建手术的术前规划，帮助外科医生在塑造乳房的决策过程中。目前报道了许多乳房大小确定方法，但这些方法受到方法学缺陷和可变估计的限制。作者旨在基于人体测量值为小至大乳房的体积评估开发统一的预测公式。
前瞻性收集了 88 名女性的 108 例乳房切除术标本的 10 个人体测量值和直接体积。作者进行了多元回归分析，以建立预测公式的最佳模型。然后对最终模型进行内部验证。使用先前发表的公式作为参考。
乳房平均（±SD）重量为 527.9 ± 227.6g（范围为 150 至 1250g）。在模型选择后，胸骨切迹至乳头、乳晕下皱襞至乳头和乳晕下皱襞至皱襞投影距离成为最重要的预测因子。得出的公式（BREAST-V）显示调整后的 R 为 0.73。新乳房的预计绝对误差为 89.7g（95%CI，62.4 至 119.1g），预计相对误差为 18.4%（95%CI，12.9 至 24.3%）。在样本上应用参考公式的预测结果不如公式本身的预测结果准确，显示 R 为 0.55。
BREAST-V 是一种可靠的工具，可准确预测小至大乳房的体积，可作为外科医生评估的补充设备。目前，可在 Apple App Store 和 Google Play Store 免费下载适用于 iOS 和 Android 设备的 BREAST-V 应用程序。
临床问题/证据水平：诊断，II。
