Relevant bibliographies by topics / Volumetric mammographic breast density

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Volumetric mammographic breast density'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Volumetric mammographic breast density"

1

Wanders, Johanna O. P., Gils Carla H. van, Nico Karssemeijer, et al. "The combined effect of mammographic texture and density on breast cancer risk: a cohort study." Breast Cancer Research 20, no. 1 (2018): 36. https://doi.org/10.1186/s13058-018-0961-7.

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<strong>Background: </strong>Texture patterns have been shown to improve breast cancer risk segregation in addition to area-based mammographic density. The additional value of texture pattern scores on top of volumetric mammographic density measures in a large screening cohort has never been studied.<strong>Methods: </strong>Volumetric mammographic density and texture pattern scores were assessed automatically for the first available digital mammography (DM) screening examination of 51,400 women (50–75 years of age) participating in the Dutch biennial breast cancer screening program between 20
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Moshina, Nataliia, Marta Roman, Sofie Sebuødegård, Gunvor G. Waade, Giske Ursin, and Solveig Hofvind. "Comparison of subjective and fully automated methods for measuring mammographic density." Acta Radiologica 59, no. 2 (2017): 154–60. http://dx.doi.org/10.1177/0284185117712540.

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Background Breast radiologists of the Norwegian Breast Cancer Screening Program subjectively classified mammographic density using a three-point scale between 1996 and 2012 and changed into the fourth edition of the BI-RADS classification since 2013. In 2015, an automated volumetric breast density assessment software was installed at two screening units. Purpose To compare volumetric breast density measurements from the automated method with two subjective methods: the three-point scale and the BI-RADS density classification. Material and Methods Information on subjective and automated density
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Sak, Mark, Peter Littrup, Rachel Brem, and Neb Duric. "Whole Breast Sound Speed Measurement from US Tomography Correlates Strongly with Volumetric Breast Density from Mammography." Journal of Breast Imaging 2, no. 5 (2020): 443–51. http://dx.doi.org/10.1093/jbi/wbaa052.

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Abstract Objective To assess the feasibility of using tissue sound speed as a quantitative marker of breast density. Methods This study was carried out under an Institutional Review Board–approved protocol (written consent required). Imaging data were selected retrospectively based on the availability of US tomography (UST) exams, screening mammograms with volumetric breast density data, patient age of 18 to 80 years, and weight less than 300 lbs. Sound speed images from the UST exams were used to measure the volume of dense tissue, the volume averaged sound speed (VASS), and the percent of hi
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Ko, Su Yeon, and Min Jung Kim. "Associations of age, body mass index, and breast size with mammographic breast density in Korean women." Journal of Medicine and Life Science 20, no. 1 (2023): 21–31. http://dx.doi.org/10.22730/jmls.2023.20.1.21.

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We aimed (a) to investigate the associations between age, body mass index (BMI), and breast size with mammographic density based on the breast imaging reporting and data system (BI-RADS) and volumetric breast density measurement (VBDM) with Volpara, (b) to evaluate the associations of age, BMI, and breast size with fibroglandular tissue volume (FGV), and (c) to demonstrate the association of mammographic density grade with FGV. From April 2012 to May 2012, 1,203 women consecutively underwent mammography, and their breast density was calculated using the density grade and volume determined by V
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Ko, Su Yeon, Eun-Kyung Kim, Min Jung Kim, and Hee Jung Moon. "Mammographic Density Estimation with Automated Volumetric Breast Density Measurement." Korean Journal of Radiology 15, no. 3 (2014): 313. http://dx.doi.org/10.3348/kjr.2014.15.3.313.

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Rahbar, Kareem, Albert Gubern-Merida, James T. Patrie, and Jennifer A. Harvey. "Automated Volumetric Mammographic Breast Density Measurements May Underestimate Percent Breast Density for High-density Breasts." Academic Radiology 24, no. 12 (2017): 1561–69. http://dx.doi.org/10.1016/j.acra.2017.06.002.

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Brentnall, Adam R., Wendy F. Cohn, William A. Knaus, Martin J. Yaffe, Jack Cuzick, and Jennifer A. Harvey. "A Case-Control Study to Add Volumetric or Clinical Mammographic Density into the Tyrer-Cuzick Breast Cancer Risk Model." Journal of Breast Imaging 1, no. 2 (2019): 99–106. http://dx.doi.org/10.1093/jbi/wbz006.

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Abstract Background Accurate breast cancer risk assessment for women attending routine screening is needed to guide screening and preventive interventions. We evaluated the accuracy of risk predictions from both visual and volumetric mammographic density combined with the Tyrer-Cuzick breast cancer risk model. Methods A case-control study (474 patient participants and 2243 healthy control participants) of women aged 40–79 years was performed using self-reported classical risk factors. Breast density was measured by using automated volumetric software and Breast Imaging and Reporting Data Syste
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Wanders, Johanna O. P., Katharina Holland, Nico Karssemeijer, et al. "The effect of volumetric breast density on the risk of screen-detected and interval breast cancers: a cohort study." Breast Cancer Research 19, no. 1 (2017): 67. https://doi.org/10.1186/s13058-017-0859-9.

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<strong>Background: </strong>In the light of the breast density legislation in the USA, it is important to know a woman's breast cancer risk, but particularly her risk of a tumor that is not detected through mammographic screening (interval cancer). Therefore, we examined the associations of automatically measured volumetric breast density with screen-detected and interval cancer risk, separately.<strong>Methods: </strong>Volumetric breast measures were assessed automatically using Volpara version 1.5.0 (Matakina, New Zealand) for the first available digital mammography (DM) examination of 52,
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Lundberg, Frida E., Anna L. V. Johansson, Kenny Rodriguez-Wallberg, et al. "Association of infertility and fertility treatment with mammographic density in a large screening-based cohort of women: a cross-sectional study." Breast Cancer Research 18, no. 1 (2016): 36. https://doi.org/10.1186/s13058-016-0693-5.

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<strong>Background: </strong>Ovarian stimulation drugs, in particular hormonal agents used for controlled ovarian stimulation (COS) required to perform in vitro fertilization, increase estrogen and progesterone levels and have therefore been suspected to influence breast cancer risk. This study aims to investigate whether infertility and hormonal fertility treatment influences mammographic density, a strong hormone-responsive risk factor for breast cancer.<strong>Methods: </strong>Cross-sectional study including 43,313 women recruited to the Karolinska Mammography Project between 2010 and 2013
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Chang, Tien-Yu, Jay Wu, Pei-Yuan Liu, Yan-Lin Liu, Dmytro Luzhbin, and Hsien-Chou Lin. "Using Breast Tissue Information and Subject-Specific Finite-Element Models to Optimize Breast Compression Parameters for Digital Mammography." Electronics 11, no. 11 (2022): 1784. http://dx.doi.org/10.3390/electronics11111784.

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Digital mammography has become a first-line diagnostic tool for clinical breast cancer screening due to its high sensitivity and specificity. Mammographic compression force is closely associated with image quality and patient comfort. Therefore, optimizing breast compression parameters is essential. Subjects were recruited for digital mammography and breast magnetic resonance imaging (MRI) within a month. Breast MRI images were used to calculate breast volume and volumetric breast density (VBD) and construct finite element models. Finite element analysis was performed to simulate breast compre
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Dissertations / Theses on the topic "Volumetric mammographic breast density"

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Assi, Valentina. "Clinical and epidemiological issues and applications of mammographic density." Thesis, Queen Mary, University of London, 2014. http://qmro.qmul.ac.uk/xmlui/handle/123456789/7855.

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Mammographic density, the amount of radiodense tissue on a mammogram, is a strong risk factor for breast cancer, with properties that could be an asset in screening and prevention programmes. Its use in risk prediction contexts is currently limited, however, mainly due to di culties in measuring and interpreting density. This research investigates rstly, the properties of density as an independent marker of breast cancer risk and secondly, how density should be measured. The rst question was addressed by analysing data from a chemoprevention trial, a trial of hormonal treatment, and a cohort s
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Lundström, Eva. "Mammographic breast density and postmenopausal hormone therapy /." Stockholm, 2005. http://diss.kib.ki.se/2005/91-7140-581-X/.

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Ironside, Alastair J. "Molecular mediators of mammographic density." Thesis, Queen Mary, University of London, 2017. http://qmro.qmul.ac.uk/xmlui/handle/123456789/25898.

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Mammographic density (MD), created predominantly by increased stromal tissue, is a major breast cancer risk factor, though little is known about the biological mechanisms mediating it. Tamoxifen prevents breast cancer in a subset of high risk women via mechanisms that appear dependent on reduction of MD. Animal models suggest tamoxifen remodels the mammary stroma to a tumour-inhibitory phenotype. This study aims to analyse the effect of tamoxifen on human breast fibroblast function and identify pro-tumourigenic pathways contributing to density-associated risk. Methods Primary human breast fibr
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Björklund, Tomas. "Automatic evaluation of breast density in mammographic images." Thesis, KTH, Skolan för teknik och hälsa (STH), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-103788.

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The goal of this master thesis is to develop a computerized method for automatic estimation of the mammographic density of mammographic images from 5 different types of mammography units.   Mammographic density is a measurement of the amount of fibroglandular tissue in a breast. This is the single most attributable risk factor for breast cancer; an accurate measurement of the mammographic density can increase the accuracy of cancer prediction in mammography. Today it is commonly estimated through visual inspection by a radiologist, which is subjective and results in inter-reader variation.   T
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Li, Tong. "Characteristics of Mammographic Density for Women in China." Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/17368.

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Objectives: The purpose of this study is to understand the characteristics of mammographic density for women in China. Methods: The potential factors of density were examined using two approaches - one qualitative (i.e. BIRADS classification) and one quantitative measurement (i.e. AutoDensity algorithm). The BIRADS study (with 4867 women) used Spearman tests and Mann-Whitney/Kruskal-Wallis tests to examine the associations between density and variables. Logistic regression was then performed to produce odds ratio. The AutoDensity study recruited 1071 (84 with and 987 without breast cancer) w
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Yaghjyan, Lusine. "Determinants of Mammographic Breast Density in Different Subsets of Women." University of Cincinnati / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1250096767.

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Wegrzyn, Lani. "Circadian Disruption, Mammographic Density and Risk of Breast Cancer." Thesis, Harvard University, 2016. http://nrs.harvard.edu/urn-3:HUL.InstRepos:25757888.

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Humans are synchronized to the 24-hour day by the light-dark cycle of the environment. Through alteration of the suprachiasmatic nucleus (SCN), the brain’s circadian pacemaker, exposure to light at night (LAN) influences the functions in the body that operate with circadian regularity, including the endocrine, immune and digestive systems. The SCN also signals to the pineal gland to modulate production of melatonin, a hormone that has established antimitotic and antiproliferative properties, and has been shown to regulate estrogen and other hormones important in breast cancer etiology. Peopl
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Varghese, Jajini Susan. "Genetic and life-style determinants of mammographic density." Thesis, University of Cambridge, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.610197.

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Pawluczyk, Olga. "Volumetric estimation of breast density for breast cancer risk prediction." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ58694.pdf.

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Li, Yanpeng. "Mammographic Density Assessment: Inter-Reader Variability And Novel Phantom Quantification." Thesis, The University of Sydney, 2015. http://hdl.handle.net/2123/13820.

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Aims: This thesis aims to investigate the level of consistency in radiologists’ mammographic density (MD) reporting and to investigate the reasons that lead to reporting variability, and then to develop novel, affordable phantom images to validate imaging parameters linked with MD assessment. Methods: Project one: 17 radiologists were asked to report the BI-RADS density category and to manually segment the areas they regarded as MD for 40 clinical images. The consistency in the BI-RADS density reporting was quantified, and the impact of MD segmentation was investigated. For radiologists’ MD s
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Books on the topic "Volumetric mammographic breast density"

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Pawluczyk, Olga. Volumetric estimation of breast density for breast cancer risk prediction. National Library of Canada, 2001.

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Simick, Michelle K. Near infrared transillumination spectroscopy of breast tissue for correlation with mammographic density. National Library of Canada, 2002.

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Lai, Joe Heng. A polymorphic locus in the promoter region of the IGFBP3 gene is associated with mammographic breast density. National Library of Canada, 2003.

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Martin, Lisa Jane. Menopause and breast cancer risk: The influence of dietary fat reduction and breast cancer risk factors on timing of menopause and change in mammographic density. 2005.

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Hong, Chi-Chen. Influence of genetic polymorphisms in P450 C17[alpha](T27C), catechol-O-methyltransferase (VAL158MET), and activity level of cytochrome P450 1A2 on mammographic density levels and other risk factors for breast cancer. 2004.

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Book chapters on the topic "Volumetric mammographic breast density"

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Heang-Ping, Chan, Lubomir M. Hadjiiski, Marilyn A. Roubidoux, et al. "Breast Density Estimation: Correlation of Mammographic Density and MR Volumetric Density." In Digital Mammography. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-59327-7_67.

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Tromans, Christopher, and Michael Brady. "An Alternative Approach to Measuring Volumetric Mammographic Breast Density." In Digital Mammography. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11783237_4.

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Nutine, Leila, Jamie C. Sergeant, Julie Morris, et al. "Volumetric and Area-Based Measures of Mammographic Density in Women with and without Cancer." In Breast Imaging. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31271-7_76.

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Tromans, Christopher, and Michael Brady. "A Scatter Model for Use in Measuring Volumetric Mammographic Breast Density." In Digital Mammography. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11783237_35.

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Rico, D., J. Yang, B. Augustine, G. E. Mawdsley, and M. J. Yaffe. "Peripheral Thickness Correction for Volumetric Breast Density Estimation." In Digital Mammography. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-59327-7_44.

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Fieselmann, Andreas, Anna K. Jerebko, and Thomas Mertelmeier. "Volumetric Breast Density Combined with Masking Risk: Enhanced Characterization of Breast Density from Mammography Images." In Breast Imaging. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41546-8_61.

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Johansson, Henrik, Miriam von Tiedemann, and Björn Cederström. "Breast Density Classification Based on Volumetric Glandularity Measured by Spectral Mammography." In Breast Imaging. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07887-8_35.

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Diffey, Jennifer, Joanna Morrison, Michael Berks, et al. "Volumetric Breast Density and Breast Cancer Risk Factors in a Screening Population." In Digital Mammography. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13666-5_52.

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Tromans, Christopher E., Ralph Highnam, Oliver Morrish, et al. "Patient Specific Dose Calculation Using Volumetric Breast Density for Mammography and Tomosynthesis." In Breast Imaging. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07887-8_23.

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Augustine, Bindu J., Gordon E. Mawdsley, Norman F. Boyd, and Martin J. Yaffe. "Volumetric Breast Density Estimation on Mammograms Using Breast Tissue Equivalent Phantoms – An Update." In Digital Mammography. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11783237_3.

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Conference papers on the topic "Volumetric mammographic breast density"

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Harris, Chelsea, Uchenna Okorie, and Sokratis Makrogiannis. "Mammographic Breast Density Classification by Integration of Deep Dictionaries and Multi-Model Sparse Approximations." In 2024 IEEE International Symposium on Biomedical Imaging (ISBI). IEEE, 2024. http://dx.doi.org/10.1109/isbi56570.2024.10635360.

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Jing, H., B. Keller, Jae Young Choi, et al. "Dependence of radiation dose on area and volumetric mammographic breast density estimation." In SPIE Medical Imaging, edited by Robert M. Nishikawa and Bruce R. Whiting. SPIE, 2013. http://dx.doi.org/10.1117/12.2007989.

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Holland, Katharina, Carla H. van Gils, Johanna OP Wanders, Ritse M. Mann, and Nico Karssemeijer. "Quantification of mammographic masking risk with volumetric breast density maps: how to select women for supplemental screening." In SPIE Medical Imaging, edited by Georgia D. Tourassi and Samuel G. Armato. SPIE, 2016. http://dx.doi.org/10.1117/12.2216810.

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Skarping, Ida, Judith Brand, Per Hall, and Signe Borgquist. "Abstract P3-07-04: Effects of statin use on volumetric mammographic density: Results from the Karolinska mammography project for risk prediction of breast cancer (KARMA) study." In Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium; December 9-13, 2014; San Antonio, TX. American Association for Cancer Research, 2015. http://dx.doi.org/10.1158/1538-7445.sabcs14-p3-07-04.

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Sak, Mark A., Neb Duric, and Peter Littrup. "Volumetric breast density comparisons between waveform UST sound speed imaging and mammography (Conference Presentation)." In Ultrasonic Imaging and Tomography, edited by Neb Duric and Brett C. Byram. SPIE, 2018. http://dx.doi.org/10.1117/12.2296649.

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Birrell, SN, and ND Birrell. "Abstract P4-16-02: An open labelled longitudinal evaluation of a subcutaneous combination of testosterone and anastrozole in pre-menopausal women with high volumetric mammographic breast density." In Abstracts: 2016 San Antonio Breast Cancer Symposium; December 6-10, 2016; San Antonio, Texas. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7445.sabcs16-p4-16-02.

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Birrell, SN, D. Dougherty, SB Good, NJ Birrell, and P. Rolan. "Abstract P2-06-01: The effect of a subcutaneous combination of testosterone (T) and anastrozole (Ai) (HAVAHT+Ai™) on volumetric mammographic breast density (MBD); an open labelled cohort study." In Abstracts: 2018 San Antonio Breast Cancer Symposium; December 4-8, 2018; San Antonio, Texas. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.sabcs18-p2-06-01.

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Kontos, Despina, Ye Xing, Predrag R. Bakic, Emily F. Conant, and Andrew D. A. Maidment. "A comparative study of volumetric breast density estimation in digital mammography and magnetic resonance imaging: results from a high-risk population." In SPIE Medical Imaging, edited by Nico Karssemeijer and Ronald M. Summers. SPIE, 2010. http://dx.doi.org/10.1117/12.845568.

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McEntee, Mark F., and Christine N. Damases. "Mammographic density measurement: a comparison of automated volumetric density measurement to BIRADS." In SPIE Medical Imaging, edited by Claudia R. Mello-Thoms and Matthew A. Kupinski. SPIE, 2014. http://dx.doi.org/10.1117/12.2042966.

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Chakraborty, Debapriya, Sarbani Palit, and Ujjwal Bhattacharya. "Deep Classification of Mammographic Breast Density: DCBARNet." In 2023 38th International Conference on Image and Vision Computing New Zealand (IVCNZ). IEEE, 2023. http://dx.doi.org/10.1109/ivcnz61134.2023.10344251.

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Reports on the topic "Volumetric mammographic breast density"

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Sellers, Thomas A. Genetic Epidemiology of Mammographic Breast Density. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada393931.

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Sellers, Thomas. Genetic Epidemiology of Mammographic Breast Density. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada383349.

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Sanderson, Maureen. Mammographic Breast Density in a Cohort of Medically Underserved Women. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada612751.

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Sanderson, Maureen. Mammographic Breast Density in a Cohort of Medically Underserved Women. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada592664.

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Harvey, Jennifer A. Increasing Mammographic Breast Density in Response to Hormone Placement Therapy and Breast Cancer Risk. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada431736.

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Harvey, Jennifer A., Richard J. Santen, Gina R. Petroni, Viktor E. Bovberg, and Mark B. Williams. Increasing Mammographic Breast Density in Response to Hormone Replacement Therapy and Breast Cancer Risk. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada412142.

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Harvey, Jennifer A. Increasing Mammographic Breast Density in Response to Hormone Replacement Therapy and Breast Cancer Risk. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada424557.

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Chan, Heang-Ping. Automated Method for Analysis of Mammographic Breast Density - A Technique for Breast Cancer Risk Estimation. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada438212.

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Chan, Heang-Ping. Automated Method for Analysis of Mammographic Breast Density - A Technique for Breast Cancer Risk Estimation. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada428513.

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Chan, Heang P. Automated Method for Analysis of Mammographic Breast Density - A Technique for Breast Cancer Risk Estimation. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada418148.

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