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

Lee, N A; Rusinek, Henry; Weinreb, J C; Chandra, Ramesh; Toth, Hildegard K.; Singer, Christian F.; Newstead, G

doi:10.2214/ajr.168.2.9016235

Cited by 152 publications

(112 citation statements)

References 5 publications

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“…Even so there have been attempts to estimate breast tissue composition by analysis of mammograms 30-37 and MRI data. [5][6][7][8]38 Breast CT is capable of producing high-resolution volumetric images of pendant breasts. 10 Breast CT images are subjectively of higher quality than the images from projection mammography.…”

Section: Ib Breast Tissue Compositionmentioning

confidence: 99%

Classification of breast computed tomography data

et al. 2008

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Differences in breast tissue composition are important determinants in assessing risk, identifying disease in images and following changes over time. This paper presents an algorithm for tissue classification that separates breast tissue into its three primary constituents of skin, fat and glandular tissue. We have designed and built a dedicated breast CT scanner. Fifty-five normal volunteers and patients with mammographically identified breast lesions were scanned. Breast CT voxel data were filtered using a 5 pt median filter and the image histogram was computed. A two compartment Gaussian fit of histogram data was used to provide an initial estimate of tissue compartments. After histogram analysis, data were input to region-growing algorithms and classified as to belonging to skin, fat or gland based on their value and architectural features. Once tissues were classified, a more detailed analysis of glandular tissue patterns and a more quantitative analysis of breast composition was made. Algorithm performance assessment demonstrated very good or excellent agreement between algorithm and radiologist observers in 97.7% of the segmented data. We observed that even in dense breasts the fraction of glandular tissue seldom exceeded 50%. For most individuals the composition is better characterized as being a 70% (fat)−30% (gland) composition than a 50% (fat) −50% (gland) composition.

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Section: Ib Breast Tissue Compositionmentioning

confidence: 99%

Classification of breast computed tomography data

et al. 2008

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“…With menopause, there is a progressive atrophy of glandular tissue; mitotic activity slows down; and vascular requirements decrease. Some of these changes have been monitored qualitatively by mammography and MRI (3,(18)(19)(20). Involution of breast glandular tissue can be impeded by the use of exogenous hormones, such as estrogen and progesterone (21).…”

mentioning

confidence: 99%

Noninvasive functional optical spectroscopy of human breast tissue

Shah

Cerussi

Eker

et al. 2001

Proc. Natl. Acad. Sci. U.S.A.

278

187

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Near infrared diffuse optical spectroscopy and diffuse optical imaging are promising methods that eventually may enhance or replace existing technologies for breast cancer screening and diagnosis. These techniques are based on highly sensitive, quantitative measurements of optical and functional contrast between healthy and diseased tissue. In this study, we examine whether changes in breast physiology caused by exogenous hormones, aging, and fluctuations during the menstrual cycle result in significant alterations in breast tissue optical contrast. A noninvasive quantitative diffuse optical spectroscopy technique, frequencydomain photon migration, was used. Measurements were performed on 14 volunteer subjects by using a hand-held probe. Intrinsic tissue absorption and reduced scattering parameters were calculated from frequency-domain photon migration data. Wavelength-dependent absorption (at 674, 803, 849, and 956 nm) was used to determine tissue concentration of oxyhemoglobin, deoxyhemoglobin, total hemoglobin, tissue hemoglobin oxygen saturation, and bulk water content. Results show significant and dramatic differences in optical properties between menopausal states. Average premenopausal intrinsic tissue absorption and reduced scattering values at each wavelength are 2.5-to 3-fold higher and 16 -28% greater, respectively, than absorption and scattering for postmenopausal subjects. Absorption and scattering properties for women using hormone replacement therapy are intermediate between premenopausal and postmenopausal populations. Physiological properties show differences in mean total hemoglobin (7.0 M, 11.8 M, and 19.2 M) and water concentration relative to pure water (10.9%, 15.3%, and 27.3%) for postmenopausal, hormone replacement therapy, and premenopausal subjects, respectively. Because of their unique, quantitative information content, diffuse optical methods may play an important role in breast diagnostics and improving our understanding of breast disease.

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“…Several attempts have been made to apply computer methods to measurements of density, with Boyd and Yaffe's interactive threshold program being the most well known [9]. Analyses comparing the actual volume of fibroglandular and fatty tissue measured by magnetic resonance imaging (MRI) to the percentage area of density estimated from mammograms demonstrated that the 2D measurements did not truly represent the dense area and tend to overestimate the amount of density [10]. Recent developments in this field explored automated methods that measure density volumetrically.…”

Section: Methods For Assessing Mammographic Densitymentioning

confidence: 99%

Update on the importance of parenchymal patterns and breast cancer risk

Ding

Warren

2004

Breast Cancer Online

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Mammographic density is a well-documented independent risk factor for breast cancer. Measurements of density come in various forms, ranging from qualitative descriptions to quantitative assessments or a combination of both. The different means of examining density lead to variations in density-risk relationship. Currently there is no consensus on which method is preferable. The interrelation of mammographic density with other risk factors is crucial to density-risk assessments, since each of these risk factors can influence density on its own. Mammographic density can be modified through hormonal and chemical means, which can have important implications on mammographic sensitivity, accuracy in cancer diagnosis and cancer prevention.

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

Cited by 152 publications

References 5 publications

Classification of breast computed tomography data

Classification of breast computed tomography data

Noninvasive functional optical spectroscopy of human breast tissue

Update on the importance of parenchymal patterns and breast cancer risk

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