The BREAST-V: a unifying predictive formula for volume assessment in small, medium, and large breasts.

Abstract

BACKGROUND 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. METHODS 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. RESULTS 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. CONCLUSIONS 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.

DOI: 10.1097/PRS.0b013e318290f6bd
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@article{Longo2013TheBA, title={The BREAST-V: a unifying predictive formula for volume assessment in small, medium, and large breasts.}, author={Benedetto Longo and Alessio Farcomeni and Germano Ferri and Antonella Campanale and Micheal Sorotos and Fabio Santanelli}, journal={Plastic and reconstructive surgery}, year={2013}, volume={132 1}, pages={1e-7e} }