An Alternative Approach to Measuring Volumetric Mammographic Breast Density

2006 ◽  
pp. 26-33 ◽  
Author(s):  
Christopher Tromans ◽  
Michael Brady
Keyword(s):  
Breast Density ◽  
Mammographic Breast Density ◽  
Alternative Approach

scholarly journals Relationship of mammographic densities to breast cancer risk

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Engy A. Ali ◽  
Mariam Raafat
Keyword(s):  
Breast Cancer ◽  
Breast Density ◽  
Statistical Significance ◽  
Significant Risk ◽  
Close Relation ◽  
Mammographic Screening ◽  
Mammographic Breast Density ◽  
Study Results ◽  
Relationship Of ◽  
Mammographic Densities

Abstract Background Our goal was to find out the relation between mammographic densities and cancer of the breast according to the recent ACR classification. From the medical records of Kasereliny Hospital, 49,409 women were subjected to digital mammography for screening, of which 1500 breast cancer cases were collected. The mammographic categories of breast density were ACR-A, B, C, and D, which were detected by two senior radiologists. All radiological classifications were made using both standard mammographic views bilaterally. Two-sided tests of statistical significance were represented by all the P values. Results From 2014 to 2019, 49,409 women came for digital mammographic screening, their age ranges between 40 and 65, and all of them are included in the study. One thousand cases of breast cancer cases were radiologically and pathologically diagnosed. Different densities were arranged in descending pattern depending on the frequency of positive cases: D (13.7%), C (3.3%), B (2.7%), A (2.2%). There is positive significant risk ratio among every higher mammographic density in comparison to the lower density. Conclusion Our study results show that the risk of breast cancer is in close relation to the mammographic breast density.

scholarly journals Subjective Versus Quantitative Methods of Assessing Breast Density

Diagnostics ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 331 ◽  
Author(s):  
Wijdan Alomaim ◽  
Desiree O’Leary ◽  
John Ryan ◽  
Louise Rainford ◽  
Michael Evanoff ◽  
...  
Keyword(s):  
Breast Density ◽  
Quantitative Methods ◽  
Weighted Kappa ◽  
Subjective Assessment ◽  
Evidence Base ◽  
Assessment Methods ◽  
Digital Data ◽  
Mammographic Breast Density ◽  
National Breast ◽  
Busy Clinical Setting

In order to find a consistent, simple and time-efficient method of assessing mammographic breast density (MBD), different methods of assessing density comparing subjective, quantitative, semi-subjective and semi-quantitative methods were investigated. Subjective MBD of anonymized mammographic cases (n = 250) from a national breast-screening programme was rated by 49 radiologists from two countries (UK and USA) who were voluntarily recruited. Quantitatively, three measurement methods, namely VOLPARA, Hand Delineation (HD) and ImageJ (IJ) were used to calculate breast density using the same set of cases, however, for VOLPARA only mammographic cases (n = 122) with full raw digital data were included. The agreement level between methods was analysed using weighted kappa test. Agreement between UK and USA radiologists and VOLPARA varied from moderate (κw = 0.589) to substantial (κw = 0.639), respectively. The levels of agreement between USA, UK radiologists, VOLPARA with IJ were substantial (κw = 0.752, 0.768, 0.603), and with HD the levels of agreement varied from moderate to substantial (κw = 0.632, 0.680, 0.597), respectively. This study found that there is variability between subjective and objective MBD assessment methods, internationally. These results will add to the evidence base, emphasising the need for consistent, simple and time-efficient MBD assessment methods. Additionally, the quickest method to assess density is the subjective assessment, followed by VOLPARA, which is compatible with a busy clinical setting. Moreover, the use of a more limited two-scale system improves agreement levels and could help minimise any potential country bias.

How Mammographic Breast Density Affects Radiologists' Visual Search Patterns

2014 ◽  
Vol 21 (11) ◽  
pp. 1386-1393 ◽  
Author(s):  
Dana S. AL Mousa ◽  
Patrick C. Brennan ◽  
Elaine A. Ryan ◽  
Warwick B. Lee ◽  
Jennifer Tan ◽  
...  
Keyword(s):  
Visual Search ◽  
Breast Density ◽  
Mammographic Breast Density ◽  
Search Patterns

scholarly journals Interactions of alcohol and postmenopausal hormone use in regards to mammographic breast density

2018 ◽  
Vol 29 (8) ◽  
pp. 751-758
Author(s):  
Lusine Yaghjyan ◽  
Graham Colditz ◽  
Heather Eliassen ◽  
Bernard Rosner ◽  
Aleksandra Gasparova ◽  
...  
Keyword(s):  
Breast Density ◽  
Mammographic Breast Density ◽  
Postmenopausal Hormone ◽  
Hormone Use

scholarly journals Tumour Size at Detection According to Different Measures of Mammographic Breast Density

2009 ◽  
Vol 16 (3) ◽  
pp. 140-146 ◽  
Author(s):  
Carolyn Nickson ◽  
Anne M Kavanagh
Keyword(s):  
Breast Cancer ◽  
Breast Density ◽  
Tumour Size ◽  
Mammographic Screening ◽  
Cancer Prognosis ◽  
Mammographic Breast Density ◽  
Interval Cancers ◽  
Dense Area ◽  
Screening Strategies ◽  
Continuous Measures

Objectives Breast cancer prognosis is better for smaller tumours. Women with high breast density are at higher risk of breast cancer and have larger screen-detected and interval cancers in mammographic screening programmes. We assess which continuous measures of breast density are the strongest predictors of breast tumour size at detection and therefore the best measures to identify women who might benefit from more intensive mammographic screening or alternative screening strategies. Setting and methods We compared the association between breast density and tumour size for 1007 screen-detected and 341 interval cancers diagnosed in an Australian mammographic screening programme between 1994 and 1996, for three semi-automated continuous measures of breast density: per cent density, dense area and dense area adjusted for non-dense area. Results After adjustment for age, hormone therapy use, family history of breast cancer and mode of detection (screen-detected or interval cancers), all measures of breast density shared a similar positive and significant association with tumour size. For example, tumours increased in size with dense area from an estimated mean 2.2 mm larger in the second quintile (β = 2.2; 95% Cl 0.4–3.9, P < 0.001) to mean 6.6 mm larger in the highest decile of dense area (β = 6.6; 95% Cl 4.4–8.9, P < 0.001), when compared with first quintile of breast density. Conclusions Of the breast density measures assessed, either dense area or per cent density are suitable measures for identifying women who might benefit from more intensive mammographic screening or alternative screening strategies.

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