Digital mammographic density and breast cancer risk: a case–control study of six alternative density assessment methods

Eng, Amanda; Gallant, Zoe; Shepherd, John; McCormack, Valerie; Li, Jingmei; Dowsett, Mitch; Vinnicombe, Sarah; Allen, Steve; dos‐Santos‐Silva, Isabel

doi:10.1186/s13058-014-0439-1

Cited by 181 publications

(178 citation statements)

References 31 publications

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“…15 All approaches have shown that breast density is a significant risk factor for breast cancer. 16,17 However, for breast density information to be used consistently for assessing risk and tailoring screening pathways, it is essential that methods of assessment are reliable and reproducible, as inaccurate calculation could adversely affect the patient outcome and clinical management. The BI-RADS approach commonly used in the clinical practice is subjective and inconsistent.…”

Section: Introductionmentioning

confidence: 99%

Quantra™ should be considered a tool for two-grade scale mammographic breast density classification

Ekpo

McEntee

Rickard

et al. 2016

BJR

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Objective: To assess the agreement between Quantra™ (Hologic Inc., Bedford, MA) and Breast Imaging Reporting and Data Systems (BI-RADS®) and the performance of Quantra at reproducing BI-RADS mammographic breast density (MBD) assessment. Methods: MBD assessment was performed using Quantra and BI-RADS. BI-RADS assessment was performed in two phases (1314 and 292 cases, respectively). Kappa was used to assess the interreader agreement and the agreement between Quantra and BI-RADS, and receiver-operating characteristics analysis was used to assess the performance of Quantra at reproducing BI-RADS rating. In Phase 1, Quantra demonstrated 93.2% sensitivity and 86.1% specificity for BI-RADS on a two-grade scale (1-2 vs 3-4). In Phase 2, it demonstrated 91.3% sensitivity and 83.6% specificity on a two-grade scale. Conclusion: Quantra is limited in reproducing BI-RADS rating on a four-grade scale; however, it highly reproduces BI-RADS assessment on a two-grade scale. Advances in knowledge: Quantra (v. 2.0) is a poor predictor of BI-RADS assessment on a four-grade scale, but well reproduces BI-RADS rating on a two-grade scale. Therefore, it should be considered a tool for two-grade scale MBD classification. INTRODUCTIONBreast density is associated with breast cancer risk, interval breast cancer and mammographic sensitivity. 1,2 It has been shown that 30% reduction in breast cancer mortality is partly attributable to improved knowledge of its risk factors and advances in early detection and treatment strategies. 3,4 Breast density refers to the proportion of the breast that is composed of fibroglandular tissue 5 and is related to established breast cancer risk factors such as genetics, hormonal agents and lifestyle characteristics. 6,7 Most importantly, breast density reduction has been shown to be a prognostic marker of response to adjuvant tamoxifen therapy in post-menopausal females. 8,9 Therefore, adding breast density information to existing breast cancer riskprediction models may improve the stratification of breast cancer risk, 10 which may lead to earlier adoption of prevention and control measures. Breast density information can also be used for tailoring clinical decisions such as screening intervals for females who are asymptomatic and the selection of more appropriate imaging pathways such

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Section: Introductionmentioning

confidence: 99%

Quantra™ should be considered a tool for two-grade scale mammographic breast density classification

Ekpo

McEntee

Rickard

et al. 2016

BJR

View full text Add to dashboard Cite

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“…Quantra has been shown to be an reliable 117,118 and reproducible 119,120 for mammographic breast density assessment, and a strong predictor of breast cancer risk from breast density. 28 Quantra has also been shown to accurately reproduce radiologists' BIRADS assessment on a two-category scale. 121,122 Volpara TM (Matakina Technology Limited) is also based on relative physics principles, and measures mammographic breast density by finding a reference point of entirely fat (P FAT ) in each image and then estimating X-ray attenuation relative to that point for all other points in the image.…”

Section: Categorisation Of Breast Composition Using "Quantitative Arementioning

confidence: 93%

“…87 For example, it encourages users to inform patients that small lesions may be missed in BIRADS C and that mammography sensitivity is lower in category D. 89 Previous editions of BIRADS have demonstrated consistent association between breast density and cancer risk particularly in postmenopausal women. 28,82 However, BIRADS suffers from reduced reproducibility and has shown wide inter-reader agreement (κ) ranging from 0.37 -0.91. [90][91][92] Therefore, an assessment of the extent of inter-reader agreement with the 5 th edition is increasingly relevant.…”

Section: The History Of Qualitative Breast Density Classificationmentioning

confidence: 99%

“…[103][104][105][106] Image J has demonstrated strong correlation with Cumulus and BIRADS 107 and positive association between breast density and cancer risk. 28,108 However, quantum and anatomical noise reduce the reliability of AutoDensity and MedDensity. 24,109 Image quality may limit accurate outlining of the dense area with semi-automated methods.…”

Section: Categorisation Of Breast Composition Using "Quantitative Arementioning

confidence: 99%

“…This will allow for shared decision-making between screened women and their physicians concerning strategies to reduce the associated risks and facilitate better decisions regarding screening. 17,19,27 National level breast density information will enable breast cancer risk stratification, 27,28 leading to selection of appropriate imaging pathways such as ultrasound, 29,30 digital breast tomosynthesis (DBT), 31 and magnetic resonance imaging (MRI) 30 to improve cancer detection in the dense breast.…”

Section: Introductionmentioning

confidence: 99%

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Breast composition: Measurement and clinical use

Ekpo¹,

Hogg²,

Highnam³

et al. 2015

Radiography

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Breast density is a measure of the extent of radiodense fibroglandular tissue in the breast. The risk of developing breast cancer and the risk of missing cancer at screening rise with higher breast density. In this paper, the historical background to breast density measurement is outlined and current evidence based practice is explained. The relevance of breast density knowledge to mammographic practice and image interpretation is considered in the light of clinical assessment and notification of mammographic breast density (MBD). The current work also discusses risk stratification for decisionmaking regarding screening frequency and better modalities for earlier detection of breast cancer in the dense breast. Automated volumetric approaches are explained while ultrasound, digital breast tomosynthesis, molecular breast imaging, and magnetic resonance imaging are introduced as valuable adjuncts to digital mammography for imaging the dense breast. The work concludes on the important note that screened women should be notified of their breast density, and such notification should be accompanied with clear and adequate information about breast density and cancer risk, strategies associated with lower MBD, as well as best screening intervals and pathways for women with dense breasts. Adoption of these strategies may be crucial to early detection and treatment of cancer and improving survival from the disease.

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Family History of Breast Cancer and Mammographic Breast Density in Premenopausal Women

et al. 2022

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IMPORTANCE Family history of breast cancer (FHBC) and mammographic breast density are independent risk factors for breast cancer, but the association of FHBC and mammographic breast density in premenopausal women is not well understood.OBJECTIVES To investigate the association of FHBC and mammographic breast density in premenopausal women using both quantitative and qualitative measurements. DESIGN, SETTING, AND PARTICIPANTSThis single-center cohort study examined 2 retrospective cohorts: a discovery set of 375 premenopausal women and a validation set of 14 040 premenopausal women. Data from women in the discovery set was collected between December 2015 and October 2016, whereas data from women in the validation set was collected between June 2010 and December 2015. Data analysis was performed between June 2018 and June 2020. EXPOSURES Family history of breast cancer (FHBC). MAIN OUTCOMES AND MEASURESThe primary outcomes were mammographic breast density measured quantitatively as volumetric percent density using Volpara (discovery set) and qualitatively using BI-RADS (Breast Imaging Reporting and Data System) breast density (validation set).Multivariable regressions were performed using a log-transformed normal distribution for the discovery set and a logistic distribution for the validation set. RESULTSOf 14 415 premenopausal women included in the study, the discovery set and validation set had similar characteristics (discovery set with FHBC: mean [SD] age, 47.1 [5.6] years; 15 [17.2%] were Black or African American women and 64 [73.6%] were non-Hispanic White women; discovery set with no FHBC: mean [SD] age, 47.7 [4.5] years; 87 [31.6%] were Black or African American women and 178 [64.7%] were non-Hispanic White women; validation set with FHBC: mean [SD] age, 46.8 [7.3] years; 720 [33.4%] were Black or African American women and 1378 [64.0%] were non-Hispanic White women]; validation set with no FHBC: mean [SD] age, 47.5 [6.1] years; 4572 [38.5%] were Black or African American women and 6632 [55.8%] were non-Hispanic White women]). In the discovery set, participants who had FHBC were more likely to have a higher mean volumetric percent density compared with participants with no FHBC (11.1% vs 9.0%). In the multivariable-adjusted model, volumetric percent density was 25% higher (odds ratio [OR], 1.25 ;95% CI, 1.12-1.41) in women with FHBC compared with women without FHBC; and 24% higher (OR, 1.24; 95% CI, 1.10-1.40) in women who had 1 affected relative, but not significantly higher in women who had at least 2 affected relatives (OR, 1.40; 95% CI, 0.95-2.07) compared with women with no relatives affected. In the validation set, women with a positive FHBC were more likely to have dense breasts (BI-RADS 3-4) compared with women with no FHBC (BI-RADS 3: 41.1% vs 38.8%; BI-RADS 4: 10.5% vs 7.7%). In the multivariable-adjusted model, the odds of having dense breasts (BI-RADS 3-4) were 30% higher (OR, 1.30; 95% CI, 1.17-1.45) in women with FHBC compared with women (continued) Key Points Question Is family history of b...

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Digital mammographic density and breast cancer risk: a case–control study of six alternative density assessment methods

Cited by 181 publications

References 31 publications

Quantra™ should be considered a tool for two-grade scale mammographic breast density classification

Quantra™ should be considered a tool for two-grade scale mammographic breast density classification

Breast composition: Measurement and clinical use

Family History of Breast Cancer and Mammographic Breast Density in Premenopausal Women

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