Prediction of Resection Weight in Reduction Mammaplasty Based on Anthropometric Measurements

Abstract

Background: The aim of this study was to develop a simple, clinically useful method to accurately predict resection weight in women undergoing reduction mammaplasty. Patients and Methods: 39 women undergoing breast reduction participated in the study. Sternal notch to nipple distance, nipple to inframammary fold distance (NIMF), medial end point to nipple distance (MN), lateral endpoint to nipple distance (LN), superior border of the breast to nipple distance (SN), breast circumference (BC), and chest circumference (CC) were measured. 5 other predicting variables were also derived; horizontal breast measurement (H) by adding MN to LN, vertical breast measurement (V) by adding NIMF to SN, the product of H and V (H*V), the product of H and NIMF (H*NIMF), and the difference between BC and CC (D). Regression analysis was used to compose a formula for predicting resection weight. Results: Among the predicting variables, H*NIMF measurements had the highest correlation coefficient value (Pearson correlation = 0.809) with the resection weight. The following formula was obtained with regression analysis: Predicted resection weight = (1.45 × H*NIMF) + (31.5 × D) - 576. Conclusion: Breast resection weights can be accurately predicted by the presented method based on anthropomorphic measurements.