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Breast Tissue Composition and Susceptibility to Breast Cancer

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TLDR
An overview of selected areas of current knowledge about the relationship between breast density and susceptibility to breast cancer is provided, and the uses of breast density in risk prediction and breast cancer prevention are reviewed.
Abstract
Breast density, as assessed by mammography, reflects breast tissue composition. Breast epithelium and stroma attenuate x-rays more than fat and thus appear light on mammograms while fat appears dark. In this review, we provide an overview of selected areas of current knowledge about the relationship between breast density and susceptibility to breast cancer. We review the evidence that breast density is a risk factor for breast cancer, the histological and other risk factors that are associated with variations in breast density, and the biological plausibility of the associations with risk of breast cancer. We also discuss the potential for improved risk prediction that might be achieved by using alternative breast imaging methods, such as magnetic resonance or ultrasound. After adjustment for other risk factors, breast density is consistently associated with breast cancer risk, more strongly than most other risk factors for this disease, and extensive breast density may account for a substantial fraction of breast cancer. Breast density is associated with risk of all of the proliferative lesions that are thought to be precursors of breast cancer. Studies of twins have shown that breast density is a highly heritable quantitative trait. Associations between breast density and variations in breast histology, risk of proliferative breast lesions, and risk of breast cancer may be the result of exposures of breast tissue to both mitogens and mutagens. Characterization of breast density by mammography has several limitations, and the uses of breast density in risk prediction and breast cancer prevention may be improved by other methods of imaging, such as magnetic resonance or ultrasound tomography.

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Journal ArticleDOI

Mammographic density and breast cancer risk: current understanding and future prospects

TL;DR: It is likely that measurement ofPMD will be improved in the near future and that understanding of the genetics and biological basis of the association of PMD with breast cancer risk will also improve, according to work now in progress.
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Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring

TL;DR: The state-of-the-art results show that the learned breast density scores have a very strong positive relationship with manual ones, and that the learning texture scores are predictive of breast cancer.
Journal ArticleDOI

Deep learning in mammography and breast histology, an overview and future trends.

TL;DR: A computer based breast cancer modelling approach is proposed: the Mammography–Histology–Phenotype–Linking–Model, which develops a mapping of features/phenotypes between mammographic abnormalities and their histopathological representation.
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Automated quantification of aligned collagen for human breast carcinoma prognosis.

TL;DR: The utility of a supervised learning protocol for streamlining the analysis of collagen alignment with respect to tumor stromal boundaries is demonstrated and TACS positive fibers are more well-aligned with each other, are of generally lower density, and terminate within or near groups of epithelial cells at larger angles of interaction.
References
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Journal ArticleDOI

Projecting Individualized Probabilities of Developing Breast Cancer for White Females Who Are Being Examined Annually

TL;DR: To assist in medical counseling, a method to estimate the chance that a woman with given age and risk factors will develop breast cancer over a specified interval is presented and individualized breast cancer probabilities are calculated.
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Explaining the Decrease in U.S. Deaths from Coronary Disease, 1980–2000

TL;DR: In this paper, the authors applied a previously validated statistical model, Impact, to data on the use and effectiveness of specific cardiac treatments and on changes in risk factors between 1980 and 2000 among U.S. adults 25 to 84 years old.
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Stromal fibroblasts in cancer initiation and progression

TL;DR: It is revealed that fibroblasts have a more profound influence on the development and progression of carcinomas than was previously appreciated and this has important therapeutic implications.
Journal ArticleDOI

Breast imaging reporting and data system (BI-RADS).

TL;DR: The Breast Imaging Reporting and Data System (BI-RADS) lexicon was developed by the American College of Radiology to standardize mammographic reporting and is clinically useful and facilitates communication and research.
Journal ArticleDOI

Simple proton spectroscopic imaging.

W T Dixon
- 01 Oct 1984 - 
TL;DR: Simple modification of a spin echo imaging pulse sequence generates useful spectroscopic information at 0.35 T and provides new parameters for tissue characterization and improved contrast between some organs.
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