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

Area of Science:

• Medical Imaging
• Plastic Surgery
• Oncology

Background:

• Preoperative breast volume prediction is crucial for breast reconstruction, patient education, and risk stratification.
• Few studies have validated the accuracy of preoperative 3D surface imaging for predicting breast volume.

Purpose of the Study:

• To evaluate the accuracy of VECTRA XT three-dimensional imaging, specifically VECTRA Analysis Module (VAM) and VECTRA Body Sculptor (VBS), in predicting mastectomy breast volume.
• To compare the predictive accuracy of VAM and VBS against intraoperative mastectomy specimen weights.

Main Methods:

• A retrospective review of 179 patients (266 breasts) who underwent mastectomy with preoperative VECTRA XT 3D imaging from 2020-2021.
• Volumetric analysis performed using VECTRA Analysis Module (VAM) and VECTRA Body Sculptor (VBS) based on standard anatomical breast borders.
• Predictive accuracy defined as estimates within ±10% or ±100 g of the intraoperative mastectomy specimen weight.

Main Results:

• No significant difference was found between mean mastectomy weight (620.8 ± 360.3 g) and mean VAM estimate (609.5 ± 361.9 g).
• Mean VBS estimate (498.9 ± 337.6 g) significantly differed from mean mastectomy weight (P < 0.001).
• Predictive accuracy within ±100 g was achieved by 58.7% of VAM estimates and 44.4% of VBS estimates. Body mass index, body surface area, and ptosis grade impacted prediction accuracy.

Conclusions:

• VECTRA Analysis Module (VAM) demonstrates higher accuracy in predicting mastectomy weight compared to VECTRA Body Sculptor (VBS).
• Discrepancies may arise from differences between surgical mastectomy borders and the breast borders used in volumetric analysis.
• Surgeons should integrate patient physical characteristics with 3D imaging data for improved preoperative breast volume prediction.