Prediction of the Ideal Implant Size Using 3-Dimensional Healthy Breast Volume in Unilateral Direct-to-Implant Breast Reconstruction

Author:

Kim Jeong-HoonORCID,Park Jin-Woo,Woo Kyong-Je

Abstract

Background and objectives: There is no consensus regarding accurate methods for assessing the size of the implant required for achieving symmetry in direct-to-implant (DTI) breast reconstruction. The purpose of this study was to determine whether the ideal implant size could be estimated using 3D breast volume or mastectomy specimen weight, and to compare prediction performances between the two variables. Materials and Methods: Patients who underwent immediate DTI breast reconstruction from August 2017 to April 2020 were included in this study. Breast volumes were measured using 3D surface imaging preoperatively and at postoperative three months. Ideal implant size was calculated by correcting the used implant volume by the observed postoperative asymmetry in 3D surface imaging. Prediction models using mastectomy weight or 3D volume were made to predict the ideal implant volume. The prediction performance was compared between the models. Results: A total of 56 patients were included in the analysis. In correlation analysis, the volume of the implant used was significantly correlated with the mastectomy specimen weight (R2 = 0.810) and the healthy breast volume (R2 = 0.880). The mean ideal implant volume was 278 ± 123 cc. The prediction model was developed using the healthy breast volume: Implant volume (cc) = healthy breast volume × 0.78 + 26 cc (R2 = 0.900). The prediction model for the ideal implant size using the 3D volume showed better prediction performance than that of using the mastectomy specimen weight (R2 = 0.900 vs 0.759, p < 0.001). Conclusions: The 3D volume of the healthy breast is a more reliable predictor than mastectomy specimen weight to estimate the ideal implant size. The estimation formula obtained in this study may assist in the selection of the ideal implant size in unilateral DTI breast reconstruction.

Publisher

MDPI AG

Subject

General Medicine

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