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Improved accuracy of breast volume calculation from 3D surface imaging data using statistical shape models.

Michael W Göpper1, Jakob Neubauer2, Ziad Kalash1

  • 1Faculty of Medicine, Department of Plastic and Hand Surgery, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany.

Plos One
|November 24, 2020
PubMed
Summary
This summary is machine-generated.

A new statistical shape model (SSM) method improves breast volume accuracy by calculating the posterior breast border, outperforming traditional interpolation techniques. This novel approach offers a more reliable measurement for 3D scanning applications.

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Area of Science:

  • Medical imaging
  • Biomedical engineering
  • Computational anatomy

Background:

  • Three-dimensional (3D) scanning is used for breast volume estimation but lacks precision due to un-imaged thoracic walls.
  • Current methods interpolate the posterior breast border, leading to inaccuracies.
  • A novel method is presented to enhance measurement accuracy by calculating the posterior border.

Purpose of the Study:

  • To develop and validate a novel method for accurate breast volume estimation using 3D scanning.
  • To improve the calculation of the posterior breast border, a critical factor in volume accuracy.
  • To compare the performance of the novel method against traditional interpolation techniques.

Main Methods:

  • A statistical shape model (SSM) of the thoracic wall was created using principal component analysis on computed tomography (CT) images.
  • The SSM was fitted to 3D scan data to interpolate the missing thoracic wall curvature for indirect volumetry.
  • An SSM of the breast was also developed for direct volumetry, validated with magnetic resonance imaging (MRI) and 3D scans.

Main Results:

  • SSM-based volumetry showed a significantly higher determination coefficient (R2 = 0.737) compared to the interpolation method (R2 = 0.404).
  • The SSM and interpolation methods were found to be significantly different (p = 0.75).
  • MRI volumetry demonstrated a strong correlation with 3D volumetry (R2 = 0.978).

Conclusions:

  • The SSM-based method for posterior breast border calculation is reliable and superior to current interpolation methods.
  • This SSM approach provides a foundation for software applications designed to calculate breast volume from 3D surface scan data.
  • The findings suggest a significant improvement in the accuracy of breast volume measurements using advanced modeling techniques.