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Journal articles on the topic 'Volumetric mammographic breast density'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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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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2

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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3

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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4

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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5

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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6

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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7

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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8

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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9

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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11

Wang, Jeff, Ania Azziz, Bo Fan, et al. "Agreement of Mammographic Measures of Volumetric Breast Density to MRI." PLoS ONE 8, no. 12 (2013): e81653. http://dx.doi.org/10.1371/journal.pone.0081653.

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12

Masala, Giovanna, Melania Assedi, Benedetta Bendinelli, et al. "The FEDRA Longitudinal Study: Repeated Volumetric Breast Density Measures and Breast Cancer Risk." Cancers 15, no. 6 (2023): 1810. http://dx.doi.org/10.3390/cancers15061810.

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Mammographic breast density (MBD) is a strong independent risk factor for breast cancer (BC). We investigated the association between volumetric MBD measures, their changes over time, and BC risk in a cohort of women participating in the FEDRA (Florence-EPIC Digital mammographic density and breast cancer Risk Assessment) study. The study was carried out among 6148 women with repeated MBD measures from full-field digital mammograms and repeated information on lifestyle habits, reproductive history, and anthropometry. The association between MBD measures (modeled as time-dependent covariates), t

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13

Destounis, Stamatia, Lisa Johnston, Ralph Highnam, Andrea Arieno, Renee Morgan, and Ariane Chan. "Using Volumetric Breast Density to Quantify the Potential Masking Risk of Mammographic Density." American Journal of Roentgenology 208, no. 1 (2017): 222–27. http://dx.doi.org/10.2214/ajr.16.16489.

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14

Brand, J. S., K. Humphreys, D. J. Thompson, et al. "Volumetric Mammographic Density: Heritability and Association With Breast Cancer Susceptibility Loci." JNCI Journal of the National Cancer Institute 106, no. 12 (2014): dju334. http://dx.doi.org/10.1093/jnci/dju334.

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15

Klifa, C., S. Sand, L. Vora, et al. "Magnetic Resonance Imaging quantification of breast density in BRCA carriers following gonadotropin releasing hormone agonist (GnRHA)-based hormonal chemoprevention." Journal of Clinical Oncology 27, no. 15_suppl (2009): 1506. http://dx.doi.org/10.1200/jco.2009.27.15_suppl.1506.

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1506 Background: Breast tissue density limits the usefulness of mammography as a surveillance tool in young women. Breast Magnetic Resonance Imaging (MRI) provides high tissue contrast and three-dimensional structural information not impaired by high breast density. We developed a volumetric “MR density” measure of breast structural composition that may be complementary to mammographic breast density. We tested this MR density measure in unaffected women with known high risk of breast cancer due to a BRCA gene mutation (or empiric risk > 30% lifetime), who were recruited in a phase II trial

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16

Gennaro, Gisella, Melissa L. Hill, Elisabetta Bezzon, and Francesca Caumo. "Quantitative Breast Density in Contrast-Enhanced Mammography." Journal of Clinical Medicine 10, no. 15 (2021): 3309. http://dx.doi.org/10.3390/jcm10153309.

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Contrast-enhanced mammography (CEM) demonstrates a potential role in personalized screening models, in particular for women at increased risk and women with dense breasts. In this study, volumetric breast density (VBD) measured in CEM images was compared with VBD obtained from digital mammography (DM) or tomosynthesis (DBT) images. A total of 150 women who underwent CEM between March 2019 and December 2020, having at least a DM/DBT study performed before/after CEM, were included. Low-energy CEM (LE-CEM) and DM/DBT images were processed with automatic software to obtain the VBD. VBDs from the p

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17

Perry, Nick, Sue Moss, Steve Dixon, et al. "Mammographic Breast Density and Urbanization: Interactions with BMI, Environmental, Lifestyle, and Other Patient Factors." Diagnostics 10, no. 6 (2020): 418. http://dx.doi.org/10.3390/diagnostics10060418.

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Mammographic breast density (MBD) is an important imaging biomarker of breast cancer risk, but it has been suggested that increased MBD is not a genuine finding once corrected for age and body mass index (BMI). This study examined the association of various factors, including both residing in and working in the urban setting, with MBD. Questionnaires were completed by 1144 women attending for mammography at the London Breast Institute in 2012–2013. Breast density was assessed with an automated volumetric breast density measurement system (Volpara) and compared with subjective radiologist asses

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18

Getz, Kayla R., Myung S. Jeon, Chongliang Luo, Jingqin Luo, and Adetunji T. Toriola. "Abstract 4173: Lipidome of mammographic breast density in premenopausal women." Cancer Research 83, no. 7_Supplement (2023): 4173. http://dx.doi.org/10.1158/1538-7445.am2023-4173.

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Abstract Introduction: High mammographic breast density (MBD) is a strong risk factor for breast cancer, but the biological mechanisms underlying high MBD are not well understood. We, therefore, comprehensively investigated for the first time the associations of lipid species with volumetric measures of MBD to elucidate potential biological mechanisms of high MBD in premenopausal women. Methods: We performed lipidomic profiling on 705 premenopausal women recruited during their annual screening mammogram at Washington University School of Medicine, St. Louis, MO. Lipidomic profiling for 982 lip

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Holen, Åsne S., Marthe Larsen, Nataliia Moshina, et al. "Visualization of the Nipple in Profile: Does It Really Affect Selected Outcomes in Organized Mammographic Screening?" Journal of Breast Imaging 3, no. 4 (2021): 427–37. http://dx.doi.org/10.1093/jbi/wbab042.

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Abstract Objective To investigate whether having the nipple imaged in profile was associated with breast characteristics or compression parameters, and whether it affected selected outcomes in screening with standard digital mammography or digital breast tomosynthesis. Methods In this IRB-approved retrospective study, results from 87 450 examinations (174 900 breasts) performed as part of BreastScreen Norway, 2016–2019, were compared by nipple in profile status and screening technique using descriptive statistics and generalized estimating equations. Unadjusted and adjusted odds ratios with 95

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20

Youn, Inyoung, SeonHyeong Choi, Shin Ho Kook, and Yoon Jung Choi. "Mammographic Breast Density Evaluation in Korean Women Using Fully Automated Volumetric Assessment." Journal of Korean Medical Science 31, no. 3 (2016): 457. http://dx.doi.org/10.3346/jkms.2016.31.3.457.

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21

Odama, Adashi Margaret, Valerie Otti, Shuai Xu, Olamide Adebayo, and Adetunji T. Toriola. "Coffee, Tea, and Mammographic Breast Density in Premenopausal Women." Nutrients 13, no. 11 (2021): 3852. http://dx.doi.org/10.3390/nu13113852.

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Studies have investigated the associations of coffee and tea with mammographic breast density (MBD) in premenopausal women with inconsistent results. We analyzed data from 375 premenopausal women who attended a screening mammogram at Washington University School of Medicine, St. Louis, MO in 2016, and stratified the analyses by race (non-Hispanic White (NHW) vs. Black/African American). Participants self-reported the number of servings of coffee, caffeinated tea, and decaffeinated tea they consumed. Volpara software was used to determine volumetric percent density (VPD), dense volume (DV), and

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22

Wei, Jun, Heang-Ping Chan, Mark A. Helvie, et al. "Correlation between mammographic density and volumetric fibroglandular tissue estimated on breast MR images." Medical Physics 31, no. 4 (2004): 933–42. http://dx.doi.org/10.1118/1.1668512.

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23

Cohen, Eric A., Omid Haji Maghsoudi, Raymond Acciavatti, et al. "Abstract P070: Volumetric parenchymal pattern analysis for breast cancer risk estimation." Cancer Prevention Research 16, no. 1_Supplement (2023): P070. http://dx.doi.org/10.1158/1940-6215.precprev22-p070.

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Abstract Introduction: Mammographic breast density is among the strongest risk factors for breast cancer. However, breast density is typically assessed subjectively by the radiologist according to the Breast Imaging Reporting and Data System (BI-RADS) based on 2 dimensional (2D) digital mammography (DM) images. Digital breast tomosynthesis (DBT) is quickly replacing DM and allows more detailed volumetric imaging of the breast. Advances in radiomics, the high-throughput extraction of radiologic features, has enabled characterization of breast parenchymal complexity beyond breast density alone.

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24

Richard-Davis, Gloria, Brianna Whittemore, Anthony Disher, et al. "Evaluation of Quantra Hologic Volumetric Computerized Breast Density Software in Comparison With Manual Interpretation in a Diverse Population." Breast Cancer: Basic and Clinical Research 12 (January 1, 2018): 117822341875929. http://dx.doi.org/10.1177/1178223418759296.

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Objective: Increased mammographic breast density is a well-established risk factor for breast cancer development, regardless of age or ethnic background. The current gold standard for categorizing breast density consists of a radiologist estimation of percent density according to the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) criteria. This study compares paired qualitative interpretations of breast density on digital mammograms with quantitative measurement of density using Hologic’s Food and Drug Administration–approved R2 Quantra volumetric breast

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25

Colditz, Graham A., and Shu Jiang. "Abstract PD12-06: PD12-06 Longitudinal analysis of breast density change assessed by digital mammogram is associated with breast cancer." Cancer Research 83, no. 5_Supplement (2023): PD12–06—PD12–06. http://dx.doi.org/10.1158/1538-7445.sabcs22-pd12-06.

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Abstract Mammographic breast density is a well-established and strong risk factor for breast cancer. Widespread use of digital mammography has opened new potential for assessment of density changes over time. The underlying premise is that changes in breast tissue due to evolving structures that support cancer development should translate to quantifiable differences between the two breasts over time. To address this hypothesis, we draw on extensive digital mammography data and bring repeated measures over up to 10 years to evaluate the association between change in mammographic breast density

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26

Giuliano, Vincenzo, and Concetta Giuliano. "Volumetric Breast Ultrasound as a Screening Modality in Mammographically Dense Breasts." ISRN Radiology 2013 (October 23, 2013): 1–7. http://dx.doi.org/10.5402/2013/235270.

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This investigation is part of an ongoing large scale study using volumetric breast ultrasound (VBUS) as a screening modality in mammographically dense breasts, offering a substantial benefit to MR imaging of the breast in terms of cost and efficiency. The addition of VBUS to mammography in women with greater than 50% breast density resulted in the detection of 12.3 per 1,000 breast cancers, compared to 4.6 per 1,000 by mammography alone with an overall attributable risk of breast cancer of 19.92 (95% confidence level, 16.75–23.61) in our screened population. These preliminary results may justi

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27

Brand, Judith S., Kamila Czene, John A. Shepherd, et al. "Automated Measurement of Volumetric Mammographic Density: A Tool for Widespread Breast Cancer Risk Assessment." Cancer Epidemiology Biomarkers & Prevention 23, no. 9 (2014): 1764–72. http://dx.doi.org/10.1158/1055-9965.epi-13-1219.

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28

Park, In Hae, Kyungran Ko, Ji Soo Choi, et al. "Higher volumetric breast density to predict risk for aggressive breast cancer subtype in postmenopausal Korean women." Journal of Clinical Oncology 31, no. 15_suppl (2013): e11584-e11584. http://dx.doi.org/10.1200/jco.2013.31.15_suppl.e11584.

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e11584 Background: In Asian population, the peak incidence of breast cancer is women in their late forties. We investigated the association between volumetric breast density and breast cancer risk according to menstruation status and breast cancer subtypes in Korean women. Methods: We prospectively enrolled 509 newly diagnosed breast cancer patients and 1336 healthy control subjects who performed mammography at the National Cancer Center in Korea between Sep 2011 and Nov 2012. Breast density was estimated using volumetric breast composition measurement (VolparaTM). We collected clinical data i

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Hjerkind, Kirsti Vik, Merete Ellingjord-Dale, Anna L. V. Johansson, et al. "Volumetric Mammographic Density, Age-Related Decline, and Breast Cancer Risk Factors in a National Breast Cancer Screening Program." Cancer Epidemiology Biomarkers & Prevention 27, no. 9 (2018): 1065–74. http://dx.doi.org/10.1158/1055-9965.epi-18-0151.

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Mahmoud, Mattia A., Anne Marie McCarthy, Despina Kontos, et al. "Abstract P022: Quantitative measures of breast density and breast cancer risk prediction among black women in a screening population." Cancer Prevention Research 16, no. 1_Supplement (2023): P022. http://dx.doi.org/10.1158/1940-6215.precprev22-p022.

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Abstract Background: Although mammographic density (MD) is a strong predictor of invasive breast cancer, it has been shown to increase the discriminatory ability of existing risk prediction models only slightly. Breast density is assessed visually by radiologists according to the Breast Imaging Reporting and Data System (BI-RADS) criteria, which has been shown to lack reproducibility. Additionally, the racial diversity of women included in the previous studies was limited. Quantitative measures of breast density have been developed that automatically measure density directly from images. Our p

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31

Wanders, Johanna O. P., Katharina Holland, Wouter B. Veldhuis, et al. "Volumetric breast density affects performance of digital screening mammography." Breast Cancer Research and Treatment 162, no. 1 (2016): 95–103. http://dx.doi.org/10.1007/s10549-016-4090-7.

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32

Wang, Zhentian, Nik Hauser, Rahel A. Kubik-Huch, Fabio D’Isidoro, and Marco Stampanoni. "Quantitative volumetric breast density estimation using phase contrast mammography." Physics in Medicine and Biology 60, no. 10 (2015): 4123–35. http://dx.doi.org/10.1088/0031-9155/60/10/4123.

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33

Matthew, Kayode A., Girish K. Vanapali, Kayla R. Getz, et al. "Abstract 4431: Steroid hormone metabolites and mammographic breast density in premenopausal women." Cancer Research 84, no. 6_Supplement (2024): 4431. http://dx.doi.org/10.1158/1538-7445.am2024-4431.

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Abstract Background: Steroid hormones influence breast tissue development and play a role in breast carcinogenesis. Their associations with mammographic breast density (MBD), an established risk factor for breast cancer, are less clear. We, therefore, investigated the associations of steroid hormone metabolites with MBD in premenopausal women. Methods: Our study population consists of 705 premenopausal women recruited during their annual screening mammogram at the Washington University School of Medicine, St. Louis, MO. We assessed volumetric percent density (VPD), dense volume (DV), and non-d

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Hayashi, Saori, Takafumi Morisaki, Yoshiki Otsubo, et al. "Abstract P3-04-12: Quantitative evaluation and assessment using the automated volumetric breast density measurement software Volpara Density in Japanese women." Clinical Cancer Research 31, no. 12_Supplement (2025): P3–04–12—P3–04–12. https://doi.org/10.1158/1557-3265.sabcs24-p3-04-12.

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Abstract Background: Breast cancer screening is being conducted to reduce death from breast cancer, and only mammography screening has been proven to reduce breast cancer mortality. One of the most common causes that reduce the efficacy of mammography screening is a dense breast. The problems with a dense breast are the lower ability to detect breast cancer and the higher incidence of breast cancer. Therefore, evaluating the breast components with objectivity and reproducibility is important. However, in Japan, the composition of the breast is still assessed visually, and this assessment has i

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Wysoczanski, Artur, Elsa D. Angelini, Sachin S. Jambawalikar, Andrew F. Laine, and Mary M. Salvatore. "Abstract P2-06-29: Automated Breast Density Assessment on Chest CT with a Deep-Learned 3D Ordinal Regression Model." Clinical Cancer Research 31, no. 12_Supplement (2025): P2–06–29—P2–06–29. https://doi.org/10.1158/1557-3265.sabcs24-p2-06-29.

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Abstract Introduction: Breast cancer is the most common malignancy and the second-leading cause of cancer mortality in women. Breast density, defined as the extent of fibroglandular tissue within the breast, is assessed semi-quantitatively on a four-grade scale, from mostly fatty (grade 1) to extremely dense (grade 4), with a severalfold increase in prospective cancer risk between the lowest and highest grades. Millions of chest CT studies are performed annually in patients eligible for routine mammographic screening, representing a significant opportunity for incidental density reporting and

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Damases, Christine N., Patrick C. Brennan, Claudia Mello-Thoms, and Mark F. McEntee. "Mammographic Breast Density Assessment Using Automated Volumetric Software and Breast Imaging Reporting and Data System (BIRADS) Categorization by Expert Radiologists." Academic Radiology 23, no. 1 (2016): 70–77. http://dx.doi.org/10.1016/j.acra.2015.09.011.

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Ghammraoui, Bahaa, Andreu Badal, and Stephen J. Glick. "Feasibility of estimating volumetric breast density from mammographic x-ray spectra using a cadmium telluride photon-counting detector." Medical Physics 45, no. 8 (2018): 3604–13. http://dx.doi.org/10.1002/mp.13031.

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38

Geeraert, N., R. Klausz, L. Cockmartin, S. Muller, H. Bosmans, and I. Bloch. "Comparison of volumetric breast density estimations from mammography and thorax CT." Physics in Medicine and Biology 59, no. 15 (2014): 4391–409. http://dx.doi.org/10.1088/0031-9155/59/15/4391.

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39

Holland, Katharina, Carla H. van Gils, Ritse M. Mann, and Nico Karssemeijer. "Quantification of masking risk in screening mammography with volumetric breast density maps." Breast Cancer Research and Treatment 162, no. 3 (2017): 541–48. http://dx.doi.org/10.1007/s10549-017-4137-4.

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Mainprize, James G., Albert H. Tyson, and Martin J. Yaffe. "The relationship between anatomic noise and volumetric breast density for digital mammography." Medical Physics 39, no. 8 (2012): 4660–68. http://dx.doi.org/10.1118/1.4736422.

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41

McCarthy, Anne Marie, Stacey Winham, Christopher Scott, et al. "Abstract PS16-07: Quantitative breast density measures and radiomic parenchymal phenotypes improve breast cancer risk prediction among Black and White women undergoing mammography screening." Clinical Cancer Research 31, no. 12_Supplement (2025): PS16–07—PS16–07. https://doi.org/10.1158/1557-3265.sabcs24-ps16-07.

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Abstract Breast parenchymal patterns identified on mammograms are associated with breast cancer risk. Breast density, which is clinically and visually assessed based on the BI-RADS lexicon, is a well-recognized risk factor for breast cancer that has modest reproducibility. Black women have, on average, lower BI-RADS categorized density than White women, despite having higher volumes of dense breast tissue when density is measured quantitatively. Beyond breast density, we recently identified and validated six parenchymal phenotypes, based on 390 radiomic texture features extracted from 2-D full

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Puri, Akshjot, Zheng Yin, Sergio Granados-Principal, et al. "Abstract P2-07-01: Hydroxytyrosol, a Component of Olive Oil for Breast Cancer Prevention in Women at High Risk." Cancer Research 83, no. 5_Supplement (2023): P2–07–01—P2–07–01. http://dx.doi.org/10.1158/1538-7445.sabcs22-p2-07-01.

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Abstract Background Breast cancer is the most frequently diagnosed cancer in women in developed countries with increased incidence in women at high risk such as those with strong family history, BRCA mutations, atypical hyperplasia etc. Chemoprevention with drugs like tamoxifen and aromatase inhibitors come with challenges of intolerance and limited efficacy in estrogen receptor negative breast cancers. The purpose of our study was to evaluate the effects of hydroxytyrosol (HT), a component of olive oil on mammographic breast density reduction, which is a validated surrogate biomarker for brea

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Ko, Eun Sook, Rock Bum Kim, and Boo-Kyung Han. "Reproducibility of automated volumetric breast density assessment in short-term digital mammography reimaging." Clinical Imaging 39, no. 4 (2015): 582–86. http://dx.doi.org/10.1016/j.clinimag.2015.02.011.

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Moshina, Nataliia, Sofie Sebuødegård, Christoph I. Lee, et al. "Automated Volumetric Analysis of Mammographic Density in a Screening Setting: Worse Outcomes for Women with Dense Breasts." Radiology 288, no. 2 (2018): 343–52. http://dx.doi.org/10.1148/radiol.2018172972.

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Engler, Camila, Laila Fernanda Moreira de Almeida, Elaine Rodrigues Leite, Fernando Leyton, and Maria Do Socorro Nogueira. "Comparison between average glandular dose (AGD) calculated by mammography equipment and VolparaDose software." Brazilian Journal of Radiation Sciences 12, no. 4A (Suppl.) (2025): e2635. https://doi.org/10.15392/2319-0612.2024.2635.

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In mammography equipment, the average glandular dose (AGD) is calculated from the incident air kerma (Ki) multiplied by conversion coefficients derived from Monte Carlo simulations, which consider breast thickness and density. However, calculating AGD using specific and true patient information results in a dose that is closer to the real dose. This study compares the AGD calculated by two different methods: the equipment, which uses conversion coefficients, and the VolparaDose software, which uses the patient-specific volumetric breast density (VBD). The study was conducted with a sample of 3

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Aitken, Zoe, Valerie A. McCormack, Ralph P. Highnam, et al. "Screen-Film Mammographic Density and Breast Cancer Risk: A Comparison of the Volumetric Standard Mammogram Form and the Interactive Threshold Measurement Methods." Cancer Epidemiology Biomarkers & Prevention 19, no. 2 (2010): 418–28. http://dx.doi.org/10.1158/1055-9965.epi-09-1059.

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Luo, Chongliang, Jingqin Luo, Kayla R. Getz, Myung Sik Jeon, and Adetunji T. Toriola. "Abstract 4271: A new methodological approach to discovering biomarkers of mammographic breast density using pathway-guided lipid amalgamation." Cancer Research 83, no. 7_Supplement (2023): 4271. http://dx.doi.org/10.1158/1538-7445.am2023-4271.

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Abstract Introduction: High mammographic breast density (MBD) is a risk factor for breast cancer. Studies are evaluating the associations of various multi-omic biomarkers, in well-defined pathways with MBD, but the existing methodological approaches have drawbacks. For example, multivariate association analysis adjusting for covariates may identify too many biomarkers and lacks proper biological interpretation. On the other hand, simple amalgams (e.g., combination or sum) of species within pathways may result in few associated pathways, as the species within a pathway could have different dire

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Taffe, Brianna D., Louise Henderson, Cherie Kuzmiak, Despina Kontos, and Sarah Nyante. "Abstract A119: Comparing the variability of two validated, quantitative breast density measures used in a community-based mammography registry across race and ethnicity." Cancer Epidemiology, Biomarkers & Prevention 32, no. 1_Supplement (2023): A119. http://dx.doi.org/10.1158/1538-7755.disp22-a119.

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Abstract Background: Breast density, an independent predictor of breast cancer risk, can be measured in multiple ways. Area-based measures quantify breast tissue in a 2-dimensional (2D) space, whereas volumetric, 3-dimensional (3D) measures incorporate information on the spatial relationship of dense and non-dense tissues that is not captured by 2D measures. Prior studies have shown that both types of measures vary by race/ethnicity. We compared the consistency of the relationship between validated 2D and 3D breast density measures across racial and ethnic groups. Methods: This study used data

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Oiwa, Mikinao, Tokiko Endo, Namiko Suda, et al. "Can quantitative evaluation of mammographic breast density, “volumetric measurement”, predict the masking risk with dense breast tissue? Investigation by comparison with subjective visual estimation by Japanese radiologists." Breast Cancer 26, no. 3 (2018): 349–58. http://dx.doi.org/10.1007/s12282-018-0930-0.

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Shi, L., S. Vedantham, K. Michaelsen, et al. "SU-E-I-54: Volumetric Breast Density: Comparison of Estimates From Tomosynthesis Reconstructions with Mammography." Medical Physics 41, no. 6Part5 (2014): 142. http://dx.doi.org/10.1118/1.4888004.

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