title: Anatomical complexity in breast parenchyma and its implications for optimal breast imaging strategies.
abstract: OBJECTIVE
  The purpose of this investigation was to assess the anatomical noise in breast images using a mathematically derived parameter β as a surrogate for detection performance, across the same patient cohort but in different imaging modalities including mammography, tomosynthesis, and breast CT.
  
  
  METHODS
  Women who were scheduled for breast biopsy were approached for participation in this IRB and HIPPA-compliant investigation. A total of 23 women had all views of each modality and represent the cohort studied in this investigation. Image data sets across all modalities were analyzed using 1000 regions of interest per image data set, and the anatomical noise power spectrum, NPS(a)(f), was computed and averaged for each breast image data set. After windowing the total noise power spectrum NPS(t)(f) to a specific frequency range corresponding to anatomical noise, the power-law slope (β) of the NPS(a)(f) was computed where NPS(a)(f) = α f(-) (β).
  
  
  RESULTS
  The value of β was determined for breast CT data sets, and they were 1.75 (0.424), 1.83 (0.352), and 1.79 (0.397), for the coronal, sagittal, and axial views, respectively. For tomosynthesis, β was 3.06 (0.361) and 3.10 (0.315) for the craniocaudal (CC) and medial lateral oblique (MLO) views, respectively. For mammography, these values were 3.17 (0.226) and 3.30 (0.236), for the CC and MLO views, respectively. The values of β for breast CT were significantly different than those for tomosynthesis and mammography (p < 0.001, all 12 comparisons).
  
  
  CONCLUSIONS
  Based on the parameter β which is thought to describe anatomical noise in breast images, breast CT was shown to have a statistically significant lower β than mammography or tomosynthesis. It has been suggested in the literature that a lower β may correspond to increased cancer detection performance; however, this has yet to be demonstrated unequivocally.
authors.affiliation: Biomedical Engineering Graduate Group, University of California, Sacramento, CA 95817, USA.
authors.forename: Lin
authors.initials: L
authors.lastname: Chen
authors.forename: Craig K
authors.initials: CK
authors.lastname: Abbey
authors.forename: Anita
authors.initials: A
authors.lastname: Nosratieh
authors.forename: Karen K
authors.initials: KK
authors.lastname: Lindfors
authors.forename: John M
authors.initials: JM
authors.lastname: Boone
mesh_terms: D001940:Breast / Q000033:anatomy & histology* / Q000166:cytology*; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D014054:Tomography / Q000379:methods*