Measurement of breast density with digital breast tomosynthesis—a systematic review

Ekpo, Ernest U.; McEntee, Mark F.

doi:10.1259/bjr.20140460

Cited by 50 publications

(49 citation statements)

References 63 publications

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“…Variability in MBD assessment has been reported in the literature with interreader agreement (k) ranging from 0.19 to 0.91. 15,18,19 This interreader variability is also evident in Phase 2 of the present study ( Table 2). The high level of BI-RADS interreader agreement observed in the present study may be due to all readers working in the same practice.…”

Section: Discussionsupporting

confidence: 77%

“…5 Qualitative, semi-automated and fully automated approaches are available for acquiring MBD information from mammograms. 15 Qualitative approaches such as Breast Imaging Reporting and Data Systems (BI-RADS®) subjectively assign MBD grades based on the perceived relative proportions of fatty and dense tissue and ductal distribution. Semi-automated techniques involve the user outlining the dense area using computer assistance to calculate percentage MBD.…”

Section: Introductionmentioning

confidence: 99%

“…Fully automated area-based methods such as MedDensity and Autodensity measure percentage MBD, whilst others such as Quantra™ (Hologic Inc., Bedford, MA) and Volpara™ (Volpara Solutions, Mãkatina Company, Wellington, New Zealand) perform volumetric breast density measurement. 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.…”

Section: Introductionmentioning

confidence: 99%

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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: Discussionsupporting

confidence: 77%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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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“…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. [93][94][95][96] Consequently, the subjectivity of visual approaches and variation in image quality may cause inter-reader variability in mammographic breast density assessment.…”

Section: The History Of Qualitative Breast Density Classificationmentioning

confidence: 99%

“…92 Interactive thresholding methods use segmentation and thresholding techniques to select two grey levels for percentage mammographic density calculation. 99 The first of these separates the image of the breast from the background, and aggregation of the pixels over the intensity range gives the Cumulus has demonstrated good association between breast density and cancer risk in multiple global studies.…”

Section: Categorisation Of Breast Composition Using "Quantitative Arementioning

confidence: 99%

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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Quantitative evaluation of breast density using a dual‐energy technique on a digital breast tomosynthesis system

Lu¹,

Yeh

Cao

et al. 2019

J Applied Clin Med Phys

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Purpose Although breast density is considered a strong risk factor of breast cancer, its quantitative assessment is difficult. To investigate a quantitative method of measuring breast density using dual‐energy mammographic imaging with central digital breast tomosynthesis in physically uniform and nonuniform phantoms. Material and methods The dual‐energy imaging unit used a tungsten anode and silver filter with 30 kVp for high‐energy images and 20 kVp for low‐energy images. Uniform glandular‐equivalent phantoms were used to calibrate a dual‐energy based decomposition algorithm. The first study used uniform breast phantoms which ranged in thicknesses from 20 to 70 mm, in 10‐mm increments, and which provided 30%, 50%, and 70% of breast density. The second study used uniform phantoms ranging from 10% to 90% of breast density. The third study used non‐uniform phantoms (at an average density of 50%) with a thickness which ranged from 20 to 90 mm, in 10‐mm increments. Results The root mean square error of breast density measurements was 2.64–3.34% for the uniform, variable thickness phantoms, 4.17% for the uniform, variable density phantoms, and 4.49% for the nonuniform, variable thickness phantoms. Conclusion The dual‐energy technique could be used to measure breast density with a margin of error of < 10% using digital breast tomosynthesis.

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Measurement of breast density with digital breast tomosynthesis—a systematic review

Cited by 50 publications

References 63 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

Quantitative evaluation of breast density using a dual‐energy technique on a digital breast tomosynthesis system

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