Literature DB >> 9016235

Fatty and fibroglandular tissue volumes in the breasts of women 20-83 years old: comparison of X-ray mammography and computer-assisted MR imaging.

N A Lee1, H Rusinek, J Weinreb, R Chandra, H Toth, C Singer, G Newstead.   

Abstract

OBJECTIVE: A method for segmenting MR images of the breast was applied to determine fatty and fibroglandular tissue volumes in breasts of women in different age groups. The results were compared with subjective assessments of breast density from X-ray mammograms in the same patients.
MATERIALS AND METHODS: Two experienced mammographers assessed the percentage of fat in the breasts of 40 women who were 20-83 years old. MR images were obtained on a 1.0-T scanner equipped with a bilateral receive-only breast coil. Images were acquired using a three-dimensional T1-weighted gradient-echo sequence with a 1.25 x 1.4 x 2.5 mm resolution. On average, breast parenchyma appeared in 30 images in each breast. Image segmentation was based on a semiautomated, two-compartmental (fatty and fibroglandular tissue) model that accounts for partial volume effects. To validate the accuracy of the MR imaging segmentation technique, we performed a phantom study using an identical imaging sequence.
RESULTS: The accuracy of the MR imaging segmentation of the phantom was of the order of 2%. In our subjects, fat content was 42.5% +/- 30.3% (mean +/- SD) on mammography versus 66.5% +/- 18% on MR images. Although we found a significant correlation (r = .63) between the two techniques, mammography poorly differentiated breasts containing less than 45% fat. When our analysis included only dense breasts (i.e., those containing less than 75% fat on MR images), the correlation coefficient decreased to .34. The largest discrepancies between mammography and MR imaging occurred in breasts that had 60-80% fat as measured on MR imaging.
CONCLUSION: Fatty and fibroglandular tissue can be differentiated on MR images of the breast with high precision and accuracy, therefore allowing assessment of breast density. The conclusions of researchers who used mammographic density patterns should be reassessed.

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Year:  1997        PMID: 9016235     DOI: 10.2214/ajr.168.2.9016235

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  54 in total

1.  Comparison of breast density measured on MR images acquired using fat-suppressed versus nonfat-suppressed sequences.

Authors:  Daniel H-E Chang; Jeon-Hor Chen; Muqing Lin; Shadfar Bahri; Hon J Yu; Rita S Mehta; Ke Nie; David J B Hsiang; Orhan Nalcioglu; Min-Ying Su
Journal:  Med Phys       Date:  2011-11       Impact factor: 4.071

2.  Automated Breast Density Measurements From Chest Computed Tomography Scans.

Authors:  Touseef A Qureshi; Harini Veeraraghavan; Janice S Sung; Jennifer B Kaplan; Jessica Flynn; Emily S Tonorezos; Suzanne L Wolden; Elizabeth A Morris; Kevin C Oeffinger; Malcolm C Pike; Chaya S Moskowitz
Journal:  J Med Syst       Date:  2019-06-22       Impact factor: 4.460

3.  Classification of breast computed tomography data.

Authors:  Thomas R Nelson; Laura I Cerviño; John M Boone; Karen K Lindfors
Journal:  Med Phys       Date:  2008-03       Impact factor: 4.071

4.  Template-based automatic breast segmentation on MRI by excluding the chest region.

Authors:  Muqing Lin; Jeon-Hor Chen; Xiaoyong Wang; Siwa Chan; Siping Chen; Min-Ying Su
Journal:  Med Phys       Date:  2013-12       Impact factor: 4.071

5.  Mammographic density, MRI background parenchymal enhancement and breast cancer risk.

Authors:  M C Pike; C L Pearce
Journal:  Ann Oncol       Date:  2013-11       Impact factor: 32.976

6.  Differences in breast density assessment using mammography, tomosynthesis and MRI and their implications for practice.

Authors:  A Tagliafico; G Tagliafico; N Houssami
Journal:  Br J Radiol       Date:  2013-10-28       Impact factor: 3.039

7.  Consistency of breast density measured from the same women in four different MR scanners.

Authors:  Jeon-Hor Chen; Siwa Chan; Yi-Jui Liu; Dah-Cherng Yeh; Chih-Kai Chang; Li-Kuang Chen; Wei-Fan Pan; Chih-Chen Kuo; Muqing Lin; Daniel H E Chang; Peter T Fwu; Min-Ying Su
Journal:  Med Phys       Date:  2012-08       Impact factor: 4.071

8.  Development of a quantitative method for analysis of breast density based on three-dimensional breast MRI.

Authors:  Ke Nie; Jeon-Hor Chen; Siwa Chan; Man-Kwun I Chau; Hon J Yu; Shadfar Bahri; Tiffany Tseng; Orhan Nalcioglu; Min-Ying Su
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

9.  3D multi-parametric breast MRI segmentation using hierarchical support vector machine with coil sensitivity correction.

Authors:  Yi Wang; Glen Morrell; Marta E Heibrun; Allison Payne; Dennis L Parker
Journal:  Acad Radiol       Date:  2012-10-23       Impact factor: 3.173

10.  Comparison of diffuse optical tomography of human breast with whole-body and breast-only positron emission tomography.

Authors:  Soren D Konecky; Regine Choe; Alper Corlu; Kijoon Lee; Rony Wiener; Shyam M Srinivas; Janet R Saffer; Richard Freifelder; Joel S Karp; Nassim Hajjioui; Fred Azar; Arjun G Yodh
Journal:  Med Phys       Date:  2008-02       Impact factor: 4.071

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