title: Breast fat volume measurement using wide-bore 3 T MRI: comparison of traditional mammographic density evaluation with MRI density measurements using automatic segmentation.
abstract: OBJECTIVE
  To compare magnetic resonance imaging (MRI)-derived breast density measurements using automatic segmentation algorithms with radiologist estimations using the Breast Imaging Reporting and Data Systems (BI-RADS) density classification.
  
  
  METHODS
  Forty women undergoing mammography and dynamic breast MRI as part of their clinical management were recruited. Fat-water separated MRI images derived from a two-point Dixon technique, phase-sensitive reconstruction, and atlas-based segmentation were obtained before and after intravenous contrast medium administration. Breast density was assessed using software from Advanced MR Analytics (AMRA), Linköping, Sweden, with results compared to the widely used four-quartile quantitative BI-RADS scale.
  
  
  RESULTS
  The proportion of glandular tissue in the breast on MRI was derived from the AMRA sequence. The mean unenhanced breast density was 0.31±0.22 (mean±SD; left) and 0.29±0.21 (right). Mean breast density on post-contrast images was 0.32±0.19 (left) and 0.32±0.2 (right). There was "almost perfect" correlation between pre- and post-contrast breast density quantification: Spearman's correlation rho=0.98 (95% confidence intervals [CI]: 0.97-0.99; left) and rho=0.99 (95% CI: 0.98-0.99; right). The 95% limits of agreement were -0.11-0.08 (left) and -0.08-0.03 (right). Interobserver reliability for BI-RADS was "substantial": weighted Kappa k=0.8 (95% CI: 0.74-0.87). The Spearman correlation coefficient between BI-RADS and MRI breast density was rho=0.73 (95% CI: 0.60-0.82; left) and rho=0.75 (95% CI: 0.63-0.83; right) which was also "substantial".
  
  
  CONCLUSIONS
  The AMRA sequence provides a fully automated, reproducible, objective assessment of fibroglandular breast tissue proportion that correlates well with mammographic assessment of breast density with the added advantage of avoidance of ionising radiation.
authors.affiliation: Department of Radiology, Norfolk and Norwich University Hospital, UK.
authors.forename: E
authors.initials: E
authors.lastname: Petridou
authors.affiliation: Department of Radiology, Norfolk and Norwich University Hospital, UK.
authors.forename: M
authors.initials: M
authors.lastname: Kibiro
authors.affiliation: Department of Radiology, Norfolk and Norwich University Hospital, UK.
authors.forename: C
authors.initials: C
authors.lastname: Gladwell
authors.affiliation: Department of Radiology, Norfolk and Norwich University Hospital, UK. Electronic address: paul.malcolm@nnuh.nhs.uk.
authors.forename: P
authors.initials: P
authors.lastname: Malcolm
authors.affiliation: Department of Radiology, Norfolk and Norwich University Hospital, UK.
authors.forename: A
authors.initials: A
authors.lastname: Toms
authors.affiliation: Department of Radiology, Norfolk and Norwich University Hospital, UK.
authors.forename: A
authors.initials: A
authors.lastname: Juette
authors.affiliation: Centre for Medical Image Science and Visualisation, Linköping University, Sweden; Department of Biomedical Engineering, Linköping University, Sweden; Advanced MR Analytics AB, Teknikringen 7, Linköping, Sweden.
authors.forename: M
authors.initials: M
authors.lastname: Borga
authors.affiliation: Centre for Medical Image Science and Visualisation, Linköping University, Sweden; Department of Medical and Health Sciences, Linköping University, Sweden; Advanced MR Analytics AB, Teknikringen 7, Linköping, Sweden.
authors.forename: O
authors.initials: O
authors.lastname: Dahlqvist Leinhard
authors.affiliation: Centre for Medical Image Science and Visualisation, Linköping University, Sweden; Department of Biomedical Engineering, Linköping University, Sweden.
authors.forename: T
authors.initials: T
authors.lastname: Romu
authors.affiliation: Department of Radiology, Norfolk and Norwich University Hospital, UK.
authors.forename: B
authors.initials: B
authors.lastname: Kasmai
authors.affiliation: Department of Radiology, Norfolk and Norwich University Hospital, UK.
authors.forename: E
authors.initials: E
authors.lastname: Denton
mesh_terms: D000273:Adipose Tissue / Q000033:anatomy & histology* / Q000000981:diagnostic imaging*; D001940:Breast / Q000033:anatomy & histology* / Q000000981:diagnostic imaging*; D000071060:Breast Density; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods; D008327:Mammography; D009929:Organ Size; D011446:Prospective Studies