Quantitative assessment of microcalcification cluster image quality in digital breast tomosynthesis, 2-dimensional and synthetic mammography

Med Biol Eng Comput. 2020 Jan;58(1):187-209. doi: 10.1007/s11517-019-02072-0. Epub 2019 Dec 7.

Abstract

Quantitative assessment of microcalcification (MC) cluster image quality is presented, in terms of cluster signal-difference-to-noise ratio (SDNR) intercomparison among digital breast tomosynthesis (DBT) and 2-dimensional (2D) and synthetic-2-dimensional (s2D) mammography. A phantom that provides realistic appearance of MC clusters located in uniform and nonuniform background was imaged in 2D and DBT, considering various scattering conditions. MC cluster SDNR differentiation is investigated with respect to MC particle size (uniform background) and surrounding parenchyma density (nonuniform background). An accurate MC cluster segmentation method was used to delineate individual MC particles and estimate MC cluster SDNR. Analysis of the uniform part of the phantom indicated higher performance of DBT and 2D over s2D for the smallest cluster size (106-177 μm), no difference among mammographic modes for the largest MC cluster (224-354 μm), and enhanced role of 2D for decreasing cluster size and increasing scattering. Analysis of the nonuniform part of the phantom indicated DBT performed better than 2D and s2D in case of dense parenchyma pattern, while 2D and s2D did not differ across parenchyma density patterns and scattering conditions. The presented MC cluster SDNR analysis was capable of revealing subtle differences among mammographic modes and suggests a methodology for clinical image quality assessment. Graphical abstract.

Keywords: Digital breast tomosynthesis; Digital mammography; Microcalcification cluster; Signal-difference-to-noise ratio; Synthetic 2D images.

MeSH terms

  • Breast / diagnostic imaging*
  • Breast / pathology*
  • Calcinosis / diagnostic imaging*
  • Female
  • Humans
  • Image Processing, Computer-Assisted*
  • Mammography*
  • Particle Size
  • Phantoms, Imaging
  • Reproducibility of Results
  • Signal-To-Noise Ratio