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Volumetric breast density estimation from full-field digital mammograms: a validation study.

Albert Gubern-Mérida1, Michiel Kallenberg2, Bram Platel2

  • 1Department of Computer Architecture and Technology, University of Girona, Girona, Spain ; Department of Radiology, Radboud University Medical Center, Nijmegen, The Netherlands.

Plos One
|January 28, 2014
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Summary

Automatic volumetric breast density assessment using Full-Field Digital Mammograms (FFDM) shows high correlation with Magnetic Resonance Imaging (MRI) data. This method is accurate and can aid in breast cancer risk assessment and personalized screening.

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Area of Science:

  • Radiology
  • Medical Imaging
  • Breast Cancer Research

Background:

  • Accurate breast density assessment is crucial for breast cancer risk stratification.
  • Traditional methods for breast density assessment can be subjective.
  • Volumetric assessment offers a more objective approach.

Purpose of the Study:

  • To objectively evaluate an automated volumetric breast density assessment tool for Full-Field Digital Mammograms (FFDM).
  • To compare FFDM-derived volumetric measurements against Magnetic Resonance Imaging (MRI) as a reference standard.

Main Methods:

  • A commercial FFDM-based volumetric breast density estimation method was assessed.
  • Volume estimates from 186 FFDM exams (MLO and CC views) were compared to MRI measurements.
  • Pearson's correlation coefficients were calculated to determine the agreement between FFDM and MRI.

Main Results:

  • High correlation was observed between FFDM volumetric measurements and MRI data.
  • Pearson's correlation coefficients were 0.93 for volumetric breast density, 0.97 for breast volume, and 0.85 for fibroglandular tissue volume.
  • These findings indicate strong agreement between the two imaging modalities.

Conclusions:

  • Accurate volumetric breast density assessment is feasible using FFDM.
  • This automated method has the potential for integration into objective breast cancer risk models.
  • The findings support the use of FFDM-based volumetric density for personalized breast cancer screening strategies.