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Yaghjyan L, Wang Z, Warner ET, Rosner B, Heine J, Tamimi RM. Reproductive Factors Related to Childbearing and a Novel Automated Mammographic Measure, V. Cancer Epidemiol Biomarkers Prev 2024; 33:804-811. [PMID: 38497795 PMCID: PMC11147729 DOI: 10.1158/1055-9965.epi-23-1318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 02/06/2024] [Accepted: 03/13/2024] [Indexed: 03/19/2024] Open
Abstract
BACKGROUND We investigated the associations between several reproductive factors related to childbearing and the variation (V) measure (a novel, objective, single summary measure of breast image intensity) by menopausal status. METHODS Our study included 3,814 cancer-free women within the Nurses' Health Study (NHS) and NHSII cohorts. The data on reproductive variables and covariates were obtained from biennial questionnaires closest to the mammogram date. V-measures were obtained from mammographic images using a previously developed algorithm capturing the standard deviation of pixel values. We used multivariate linear regression to examine the associations of parity, age at first birth, time between menarche and first birth, time since last pregnancy, and lifetime breastfeeding duration with V-measure, adjusting for breast cancer risk factors, including the percentage of mammographic density (PMD). We further examined whether these associations were statistically accounted for (mediated) by PMD. RESULTS Among premenopausal women, none of the reproductive factors were associated with V. Among postmenopausal women, inverse associations of parity and positive associations of age at first birth with V were mediated by PMD (percent mediated: nulliparity: 66.7%, P < 0.0001; parity: 50.5%, P < 0.01; age at first birth 76.1%, P < 0.001) and were no longer significant in PMD-adjusted models. Lifetime duration of breastfeeding was positively associated with V [>36 vs. 0 ≤1 months β = 0.29; 95% confidence interval (CI) 0.07; 0.52, Ptrend < 0.01], independent of PMD. CONCLUSIONS Parity, age at first birth, and breastfeeding were associated with postmenopausal V. IMPACT This study highlights associations of reproductive factors with mammographic image intensity.
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Affiliation(s)
- Lusine Yaghjyan
- Department of Epidemiology, University of Florida, College of Public Health and Health Professions and College of Medicine, Gainesville, Florida
| | - Zifan Wang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Erica T Warner
- Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Bernard Rosner
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - John Heine
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida
| | - Rulla M Tamimi
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York
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Barnard ME, DuPré NC, Heine JJ, Fowler EE, Murthy DJ, Nelleke RL, Chan A, Warner ET, Tamimi RM. Reproductive risk factors for breast cancer and association with novel breast density measurements among Hispanic, Black, and White women. Breast Cancer Res Treat 2024; 204:309-325. [PMID: 38095811 PMCID: PMC10948301 DOI: 10.1007/s10549-023-07174-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 11/02/2023] [Indexed: 12/21/2023]
Abstract
PURPOSE There are differences in the distributions of breast cancer incidence and risk factors by race and ethnicity. Given the strong association between breast density and breast cancer, it is of interest describe racial and ethnic variation in the determinants of breast density. METHODS We characterized racial and ethnic variation in reproductive history and several measures of breast density for Hispanic (n = 286), non-Hispanic Black (n = 255), and non-Hispanic White (n = 1694) women imaged at a single hospital. We quantified associations between reproductive factors and percent volumetric density (PVD), dense volume (DV), non-dense volume (NDV), and a novel measure of pixel intensity variation (V) using multivariable-adjusted linear regression, and tested for statistical heterogeneity by race and ethnicity. RESULTS Reproductive factors most strongly associated with breast density were age at menarche, parity, and oral contraceptive use. Variation by race and ethnicity was most evident for the associations between reproductive factors and NDV (minimum p-heterogeneity:0.008) and V (minimum p-heterogeneity:0.004) and least evident for PVD (minimum p-heterogeneity:0.042) and DV (minimum p-heterogeneity:0.041). CONCLUSION Reproductive choices, particularly those related to childbearing and oral contraceptive use, may contribute to racial and ethnic variation in breast density.
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Affiliation(s)
- Mollie E Barnard
- Slone Epidemiology Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02118, USA.
- University of Utah Intermountain Healthcare Department of Population Health Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.
| | - Natalie C DuPré
- Department of Epidemiology and Population Health, School of Public Health and Information Sciences, University of Louisville, Louisville, KY, USA
| | - John J Heine
- Division of Population Sciences, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA
| | - Erin E Fowler
- Division of Population Sciences, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA
| | - Divya J Murthy
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Rebecca L Nelleke
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Ariane Chan
- Volpara Health Technologies Ltd., Wellington, New Zealand
| | - Erica T Warner
- Clinical Translational Epidemiology Unit, Department of Medicine, Mongan Institute, Massachusetts General Hospital, Boston, MA, USA
| | - Rulla M Tamimi
- Department of Population Health Sciences, Weill Cornell Medical, New York, NY, USA
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Heine J, Fowler EEE, Weinfurtner RJ, Hume E, Tworoger SS. Breast density analysis of digital breast tomosynthesis. Sci Rep 2023; 13:18760. [PMID: 37907569 PMCID: PMC10618274 DOI: 10.1038/s41598-023-45402-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 10/19/2023] [Indexed: 11/02/2023] Open
Abstract
Mammography shifted to digital breast tomosynthesis (DBT) in the US. An automated percentage of breast density (PD) technique designed for two-dimensional (2D) applications was evaluated with DBT using several breast cancer risk prediction measures: normalized-volumetric; dense volume; applied to the volume slices and averaged (slice-mean); and applied to synthetic 2D images. Volumetric measures were derived theoretically. PD was modeled as a function of compressed breast thickness (CBT). The mean and standard deviation of the pixel values were investigated. A matched case-control (CC) study (n = 426 pairs) was evaluated. Odd ratios (ORs) were estimated with 95% confidence intervals. ORs were significant for PD: identical for volumetric and slice-mean measures [OR = 1.43 (1.18, 1.72)] and [OR = 1.44 (1.18, 1.75)] for synthetic images. A 2nd degree polynomial (concave-down) was used to model PD as a function of CBT: location of the maximum PD value was similar across CCs, occurring at 0.41 × CBT, and PD was significant [OR = 1.47 (1.21, 1.78)]. The means from the volume and synthetic images were also significant [ORs ~ 1.31 (1.09, 1.57)]. An alternative standardized 2D synthetic image was constructed, where each pixel value represents the percentage of breast density above its location. Several measures were significant and an alternative method for constructing a standardized 2D synthetic image was produced.
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Affiliation(s)
- John Heine
- Cancer Epidemiology Department, Moffitt Cancer Center and Research Institute, 12902 Bruce B. Downs Blvd, Tampa, FL, 33612, USA.
| | - Erin E E Fowler
- Cancer Epidemiology Department, Moffitt Cancer Center and Research Institute, 12902 Bruce B. Downs Blvd, Tampa, FL, 33612, USA
| | - R Jared Weinfurtner
- Diagnostic Imaging and Interventional Radiology, Moffitt Cancer Center and Research Institute, 12902 Bruce B. Downs Blvd, Tampa, FL, 33612, USA
| | - Emma Hume
- Cancer Epidemiology Department, Moffitt Cancer Center and Research Institute, 12902 Bruce B. Downs Blvd, Tampa, FL, 33612, USA
| | - Shelley S Tworoger
- Cancer Epidemiology Department, Moffitt Cancer Center and Research Institute, 12902 Bruce B. Downs Blvd, Tampa, FL, 33612, USA
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Monticciolo DL, Newell MS, Moy L, Lee CS, Destounis SV. Breast Cancer Screening for Women at Higher-Than-Average Risk: Updated Recommendations From the ACR. J Am Coll Radiol 2023; 20:902-914. [PMID: 37150275 DOI: 10.1016/j.jacr.2023.04.002] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Revised: 03/26/2023] [Accepted: 04/06/2023] [Indexed: 05/09/2023]
Abstract
Early detection decreases breast cancer death. The ACR recommends annual screening beginning at age 40 for women of average risk and earlier and/or more intensive screening for women at higher-than-average risk. For most women at higher-than-average risk, the supplemental screening method of choice is breast MRI. Women with genetics-based increased risk, those with a calculated lifetime risk of 20% or more, and those exposed to chest radiation at young ages are recommended to undergo MRI surveillance starting at ages 25 to 30 and annual mammography (with a variable starting age between 25 and 40, depending on the type of risk). Mutation carriers can delay mammographic screening until age 40 if annual screening breast MRI is performed as recommended. Women diagnosed with breast cancer before age 50 or with personal histories of breast cancer and dense breasts should undergo annual supplemental breast MRI. Others with personal histories, and those with atypia at biopsy, should strongly consider MRI screening, especially if other risk factors are present. For women with dense breasts who desire supplemental screening, breast MRI is recommended. For those who qualify for but cannot undergo breast MRI, contrast-enhanced mammography or ultrasound could be considered. All women should undergo risk assessment by age 25, especially Black women and women of Ashkenazi Jewish heritage, so that those at higher-than-average risk can be identified and appropriate screening initiated.
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Affiliation(s)
- Debra L Monticciolo
- Division Chief, Breast Imaging, Massachusetts General Hospital, Boston, Massachusetts.
| | - Mary S Newell
- Interim Division Chief, Breast Imaging, Emory University, Atlanta, Georgia
| | - Linda Moy
- Associate Chair for Faculty Mentoring, New York University Grossman School of Medicine, New York, New York; Editor-in-Chief, Radiology
| | - Cindy S Lee
- New York University Grossman School of Medicine, New York, New York
| | - Stamatia V Destounis
- Elizabeth Wende Breast Care, Rochester, New York; Chair, ACR Commission on Breast Imaging
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Heine J, Fowler EE, Weinfurtner RJ, Hume E, Tworoger SS. Breast Density Analysis Using Digital Breast Tomosynthesis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.10.527911. [PMID: 36824710 PMCID: PMC9948963 DOI: 10.1101/2023.02.10.527911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
We evaluated an automated percentage of breast density (BD) technique (PDa) with digital breast tomosynthesis (DBT) data. The approach is based on the wavelet expansion followed by analyzing signal dependent noise. Several measures were investigated as risk factors: normalized volumetric; total dense volume; average of the DBT slices (slice-mean); a two-dimensional (2D) metric applied to the synthetic images; and the mean and standard deviations of the pixel values. Volumetric measures were derived theoretically, and PDa was modeled as a function of compressed breast thickness. An alternative method for constructing synthetic 2D mammograms was investigated using the volume results. A matched case-control study (n = 426 pairs) was analyzed. Conditional logistic regression modeling, controlling body mass index and ethnicity, was used to estimate odds ratios (ORs) for each measure with 95% confidence intervals provided parenthetically. There were several significant findings: volumetric measure [OR = 1.43 (1.18, 1.72)], which produced an identical OR as the slice-mean measure as predicted; [OR =1.44 (1.18, 1.75)] when applied to the synthetic images; and mean of the pixel values (volume or 2D synthetic) [ORs ~ 1.31 (1.09, 1.57)]. PDa was modeled as 2nd degree polynomial (concave-down): its maximum value occurred at 0.41×(compressed breast thickness), which was similar across case-control groups, and was significant from this position [OR = 1.47 (1.21, 1.78)]. A standardized 2D synthetic image was produced, where each pixel value represents the percentage of BD above its location. The significant findings indicate the validity of the technique. Derivations supported by empirical analyses produced a new synthetic 2D standardized image technique. Ancillary to the objectives, the results provide evidence for understanding the percentage of BD measure applied to 2D mammograms. Notwithstanding the findings, the study design provides a template for investigating other measures such as texture.
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Anandarajah A, Chen Y, Colditz GA, Hardi A, Stoll C, Jiang S. Studies of parenchymal texture added to mammographic breast density and risk of breast cancer: a systematic review of the methods used in the literature. Breast Cancer Res 2022; 24:101. [PMID: 36585732 PMCID: PMC9805242 DOI: 10.1186/s13058-022-01600-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Accepted: 12/21/2022] [Indexed: 12/31/2022] Open
Abstract
This systematic review aimed to assess the methods used to classify mammographic breast parenchymal features in relation to the prediction of future breast cancer. The databases including Medline (Ovid) 1946-, Embase.com 1947-, CINAHL Plus 1937-, Scopus 1823-, Cochrane Library (including CENTRAL), and Clinicaltrials.gov were searched through October 2021 to extract published articles in English describing the relationship of parenchymal texture features with the risk of breast cancer. Twenty-eight articles published since 2016 were included in the final review. The identification of parenchymal texture features varied from using a predefined list to machine-driven identification. A reduction in the number of features chosen for subsequent analysis in relation to cancer incidence then varied across statistical approaches and machine learning methods. The variation in approach and number of features identified for inclusion in analysis precluded generating a quantitative summary or meta-analysis of the value of these features to improve predicting risk of future breast cancers. This updated overview of the state of the art revealed research gaps; based on these, we provide recommendations for future studies using parenchymal features for mammogram images to make use of accumulating image data, and external validation of prediction models that extend to 5 and 10 years to guide clinical risk management. Following these recommendations could enhance the applicability of models, helping improve risk classification and risk prediction for women to tailor screening and prevention strategies to the level of risk.
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Affiliation(s)
- Akila Anandarajah
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, 660 S Euclid Ave MSC 8100-0094-2200, Saint Louis, MO, 63110, USA
| | - Yongzhen Chen
- Saint Louis University School of Medicine, Saint Louis, MO, USA
| | - Graham A Colditz
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, 660 S Euclid Ave MSC 8100-0094-2200, Saint Louis, MO, 63110, USA
| | - Angela Hardi
- Bernard Becker Medical Library, Washington University School of Medicine, MSC 8132-12-01, 660 S Euclid Ave, Saint Louis, MO, 63110, USA
| | - Carolyn Stoll
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, 660 S Euclid Ave MSC 8100-0094-2200, Saint Louis, MO, 63110, USA
| | - Shu Jiang
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, 660 S Euclid Ave MSC 8100-0094-2200, Saint Louis, MO, 63110, USA.
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Personalized Screening and Prevention Based on Genetic Risk of Breast Cancer. CURRENT BREAST CANCER REPORTS 2022. [DOI: 10.1007/s12609-022-00443-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Yaghjyan L, Smotherman C, Heine J, Colditz GA, Rosner B, Tamimi RM. Associations of Oral Contraceptives with Mammographic Breast Density in Premenopausal Women. Cancer Epidemiol Biomarkers Prev 2021; 31:436-442. [PMID: 34862209 DOI: 10.1158/1055-9965.epi-21-0853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 09/15/2021] [Accepted: 11/30/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND We investigated the associations of oral contraceptives (OC) with percent breast density (PD), absolute dense area (DA), nondense area (NDA), and a novel image intensity variation (V) measure in premenopausal women. METHODS This study included 1,233 controls from a nested case-control study within Nurses' Health Study II cohort. Information on OCs was collected in 1989 and updated biennially. OC use was defined from the questionnaire closest to the mammogram date. PD, DA, and NDA were measured from digitized film mammograms using a computer-assisted thresholding technique; the V measure was obtained with a previously developed algorithm measuring the SD of pixel values in the eroded breast region. Generalized linear regression was used to assess associations between OCs and density measures (square root-transformed PD, DA, and NDA, and -untransformed V). RESULTS OC use was not associated with PD [current vs. never: β = -0.06; 95% confidence interval (CI), -0.37-0.24; past vs. never: β = 0.10; 95% CI, -0.09-0.29], DA (current vs. never: β = -0.20; 95% CI -0.59-0.18; past vs. never: β = 0.13; 95% CI, -0.12-0.39), and NDA (current vs. never: β = -0.19; 95% CI, -0.56-0.18; past vs. never: β = -0.01; 95% CI, -0.28-0.25). Women with younger age at initiation had significantly greater V-measure (<20 years vs. never: β = 26.88; 95% CI, 3.18-50.58; 20-24 years vs. never: β = 20.23; 95% CI, -4.24-44.71; 25-29 years vs. never: β = 2.61; 95% CI -29.00-34.23; ≥30 years vs. never: β = 0.28; 95% CI, -34.16-34.72, P trend = 0.03). CONCLUSIONS Our findings suggest that an earlier age at first OC use was associated with significantly greater V. IMPACT These findings could guide decisions about the age for OC initiation.
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Affiliation(s)
- Lusine Yaghjyan
- Department of Epidemiology, University of Florida, College of Public Health and Health Professions and College of Medicine, Gainesville, Florida.
| | - Carmen Smotherman
- Department of Epidemiology, University of Florida, College of Public Health and Health Professions and College of Medicine, Gainesville, Florida
| | - John Heine
- Cancer Epidemiology Department, Moffitt Cancer Center & Research Institute, Tampa, Florida
| | - Graham A Colditz
- Department of Surgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri.,Institute for Public Health, Washington University in St. Louis, St. Louis, Missouri
| | - Bernard Rosner
- Channing Division of Network Medicine, Department of Medicine Research, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Rulla M Tamimi
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York
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