A stepwedge-based method for measuring breast density: observer variability and comparison with human reading

Diffey, Jenny; Berks, Michael; Hufton, Alan; Chung, Camilla; Verow, Rosanne; Morrison, Joanna; Wilson, Mary; Boggis, Caroline; Morris, Julie; Maxwell, Anthony; Astley, Susan M.

doi:10.1117/12.844265

Cited by 3 publications

(3 citation statements)

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“…Additionally, the dependence of the software on user expertise reduces its reproducibility. 54,55 Removing the human from the evaluation completely would obviously be the solution to the issue of subjective variability; therefore, automated methods of breast density evaluation have been developed.…”

Section: Semi-automated Methodsmentioning

confidence: 99%

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

Ekpo¹,

McEntee²

2014

BJR

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Digital breast tomosynthesis (DBT) has gained acceptance as an adjunct to digital mammography in screening. Now that breast density reporting is mandated in several states in the USA, it is increasingly important that the methods of breast density measurement be robust, reliable and consistent. Breast density assessment with DBT needs some consideration since quantitative methods are modelled for two-dimensional (2D) mammography. A review of methods used for breast density assessment with DBT was performed. Existing evidence shows Cumulus has better reproducibility than that of the breast imaging reporting and data system (BI-RADS®) but still suffers from subjective variability; MedDensity is limited by image noise, whilst Volpara and Quantra are robust and consistent. The reported BI-RADs inter-reader breast density agreement (k) ranged from 0.65 to 0.91, with inter-reader correlation (r) ranging from 0.70 to 0.93. The correlation (r) between BI-RADS and Cumulus ranged from 0.54-0.94, whilst that of BI-RADs and MedDensity ranged from 0.48-0.78. The reported agreement (k) between BI-RADs and Volpara is 0.953. Breast density correlation between DBT and 2D mammography ranged from 0.73 to 0.97, with agreement (k) ranging from 0.56 to 0.96. To avoid variability and provide more reliable breast density information for clinicians, automated volumetric methods are preferred.Breast cancer accounts for approximately 23% of all cancers in females and is the most frequent cause of cancer deaths in females worldwide.

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Section: Semi-automated Methodsmentioning

confidence: 99%

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

Ekpo¹,

McEntee²

2014

BJR

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“…18,19 Semi-automated methods require user input and also suffer from subjective variability and add labour-intensive software into the already complex radiological reporting ecosystem. 20 There are also concerns that measurement of MBD as percentage area breast density by area-based semiautomated and automated methods is affected by breast size and treatment of the breast as a two-dimensional structure and therefore may not be representative of the quantity of the dense tissue in the breast. 21 To avoid variability and provide a more consistent measure of the quantity of the dense tissue in the breast, automated volumetric tools such as Quantra have been developed.…”

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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“…3,[111][112][113][114] Furthermore, area-based techniques measure percentage dense area and treat the breast as a two-dimensional structure, ignoring the three-dimensional features of the breast. 115 There are doubts that area measurement of breast density as percentage mammographic density (PMD) may not accurately reflect the quantity of dense tissue in the breast.…”

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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A stepwedge-based method for measuring breast density: observer variability and comparison with human reading

Cited by 3 publications

References 0 publications

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

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

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

Breast composition: Measurement and clinical use

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