Three-Dimensional Surface Analysis for Preoperative Prediction of Breast Volume: A Validation Study

Abstract

Background: Few studies have examined whether preoperative three-dimensional surface imaging can accurately predict breast volume. Reliably predicting breast volume preoperatively can assist with breast reconstruction planning, patient education, and perioperative risk stratification. Methods: The authors conducted a review of patients who underwent mastectomy from 2020 to 2021 and included all patients who had preoperative VECTRA XT three-dimensional imaging. VECTRA Analysis Module (VAM) and VECTRA Body Sculptor (VBS) were used for volumetric analysis using standard anatomical breast borders. Breast weights were obtained intraoperatively. Predictive accuracy was defined as VAM estimates ±10% of mastectomy specimen weight or ±100 g of mastectomy weight. Results: The study included 179 patients (266 breasts). There was no significant difference (P = 0.22) between mean mastectomy weight of 620.8 ± 360.3 g and mean VAM estimate of 609.5 ± 361.9 g. Mean VBS estimate was 498.9 ± 337.6 g, which differed from mean mastectomy weight (P < 0.001). When defining predictive accuracy as ±100 g, 58.7% of VAM and 44.4% of VBS estimates were accurate. Body mass index, body surface area, and ptosis grade significantly affected VAM and VBS breast volume predictions. Conclusions: VAM is more accurate at predicting mastectomy weight than VBS, likely because of VAM’s analysis of surface topography rather than discrete surface landmarks. Discrepancies between VECTRA estimates and mastectomy weight were likely attributable to differences between surgical mastectomy borders and breast borders used in volumetric analysis. Surgeons should consider the physical characteristics of patients when using three-dimensional imaging. CLINICAL QUESTION/LEVEL OF EVIDENCE: Diagnostic, I.