title: Impact of skin removal on quantitative measurement of breast density using MRI.
abstract: OBJECTIVE
  In breast MRI, skin and fibroglandular tissue commonly possess similar signal intensities, and as such, the inclusion of skin as dense tissue leads to an overestimation in the measured density. This study investigated the impact of skin to the quantitative measurement of breast density using MRI.
  
  
  METHODS
  The analysis was performed on the normal breasts of 50 women using nonfat-saturated (nonfat-sat) T1 weighted MR images. The skin was segmented by using a dynamic searching algorithm, which was based on the change in signal intensities from the background air (dark), to the skin (moderate), and then to the fatty tissue (bright). Tissue with moderate intensities that fell between the two boundaries determined based on the intensity gradients (from air to skin, and from skin to fat) was categorized as skin. The percent breast density measured with and without skin exclusion was compared. Also the relationship between the skin volume and the breast volume was investigated. Then, this relationship was used to estimate the skin volume from the breast volume for skin correction.
  
  
  RESULTS
  The percentage of the skin volume normalized to the breast volume ranged from 5.0% to 15.2% (median 8.6%, mean +/- STD 8.8 +/- 2.6%) among 50 women. The percent breast densities measured with skin (y) and without skin (x) were highly correlated, y = 1.23x+7% (r = 0.94, p < 0.001). The relationship between the skin volume and the breast volume was analyzed based on transformed data (the square root of the skin volume vs the cube root of breast volume) using the linear regression, and yielded r = 0.87, p < 0.001. When this model was used to estimate the skin volume for correction in the density analysis, it provided a better fit to the measured density with skin exclusion (with adjusted R2 = 0.98, and root mean square error = 1.6) compared to the correction done by using a fixed cutoff value of 8% (adjusted R2 = 0.83, root mean square error = 4.7).
  
  
  CONCLUSIONS
  The authors have shown that the skin volume is related to the breast volume, and this relationship may be used to correct for the skin effect in the MRI-based density measurement. A reliable quantitative density analysis method will aid in clinical investigation to evaluate the role of breast density for cancer risk assessment or for prediction of the efficacy of risk-modifying drugs using hormonal therapy.
authors.affiliation: Tu and Yuen Center for Functional Onco-Imaging, University of California, Irvine, California 92697, USA.
authors.forename: Ke
authors.initials: K
authors.lastname: Nie
authors.forename: Daniel
authors.initials: D
authors.lastname: Chang
authors.forename: Jeon-Hor
authors.initials: JH
authors.lastname: Chen
authors.forename: Tzu-Ching
authors.initials: TC
authors.lastname: Shih
authors.forename: Chieh-Chih
authors.initials: CC
authors.lastname: Hsu
authors.forename: Orhan
authors.initials: O
authors.lastname: Nalcioglu
authors.forename: Min-Ying
authors.initials: MY
authors.lastname: Su
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000473:pathology* / Q000503:physiopathology*; D003720:Densitometry / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012867:Skin / Q000473:pathology* / Q000503:physiopathology*; D013382:Subtraction Technique