Estimation of Mastectomy Volume Using Preoperative Mastectomy Simulation Images Acquired by the Vectra H2 System

Author:

Kim Jiwoo1,Matsumine Hajime1,Niimi Yosuke1,Osada Atsuyoshi1,Sakurai Hiroyuki1

Affiliation:

1. From the Department of Plastic and Reconstructive Surgery, School of Medicine, Tokyo Women’s Medical University, Tokyo, Japan.

Abstract

Background: Preoperative prediction of breast volume is very important in planning breast reconstruction. In this study, we assessed the usefulness of a novel method for preoperative estimation of mastectomy volume by comparing the weight of actual mastectomy specimens with the values predicted by the developed method using the Vectra H2. Methods: All patients underwent skin-sparing mastectomy and immediate autologous breast reconstruction. Preoperatively, the patient’s breast was scanned using the Vectra H2 and a postmastectomy simulation image was constructed on a personal computer. The estimated mastectomy volume was calculated by comparing the preoperative and postmastectomy three-dimensional simulation images. Correlation coefficients with the estimated mastectomy volume were calculated for the actual mastectomy weight and the transplanted flap weight. Results: Forty-five breasts of 42 patients were prospectively analyzed. The correlations with the estimated mastectomy volume were r = 0.95 (P < 0.0001) for actual mastectomy weight and r = 0.84 (P < 0.0001) for transplanted free-flap weight. The mastectomy weight estimation formula obtained by linear regression analysis using the estimated mastectomy volume was 0.98 × estimated mastectomy volume + 5.4 (coefficient of determination R2 = 0.90, P < 0.0001). The root-mean-square error for the mastectomy weight estimation formula was 38 g. Conclusions: We used the Vectra H2 system to predict mastectomy volume. The predictions provided by this method were highly accurate. Three-dimensional imaging is a noncontact, noninvasive measurement method that is both accurate and simple to perform. Use of this effective tool for volume prediction is expected to increase in the future.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Surgery,General Medicine

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