Magnetic Resonance Imaging-Based Volumetric Analysis and Its Relationship to Actual Breast Weight

 

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Background Preoperative volume assessment is useful in breast reconstruction. Magnetic resonance imaging (MRI) and mammography are commonly available to reconstructive surgeons in the care of a patient with breast cancer. This study aimed to verify the accuracy of breast volume measured by MRI, and to identify any factor affecting the relationship between measured breast volume and actual breast weight to derive a new model for accurate breast volume estimation.

Methods From January 2012 to January 2013, a retrospective review was performed on a total of 101 breasts from 99 patients who had undergone total mastectomy. The mastectomy specimen weight was obtained for each breast. Mammographic and MRI data were used to estimate the volume and density. A standard statistical analysis was performed.

Results The mean mastectomy specimen weight was 340.8 g (range, 95 to 795 g). The mean MRI-estimated volume was 322.2 mL³. When divided into three groups by the "difference percentage value", the underestimated group showed a significantly higher fibroglandular volume, higher percent density, and included significantly more Breast Imaging, Reporting and Data System mammographic density grade 4 breasts than the other groups. We derived a new model considering both fibroglandular tissue volume and fat tissue volume for accurate breast volume estimation.

Conclusions MRI-based breast volume assessment showed a significant correlation with actual breast weight; however, in the case of dense breasts, the reconstructive surgeon should note that the mastectomy specimen weight tends to overestimate the volume. We suggested a new model for accurate breast volume assessment considering fibroglandular and fat tissue volume.

Publication History

Received: 14 February 2013

Accepted: 16 April 2013

Article published online:
01 May 2022

© 2013. The Korean Society of Plastic and Reconstructive Surgeons. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonCommercial License, permitting unrestricted noncommercial use, distribution, and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes. (https://creativecommons.org/licenses/by-nc/4.0/)

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