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6 th <strong>International</strong> <strong>Workshop</strong> on Breast Densitometry and Breast Cancer Risk Assessment COMPARISON OF ALTERNATIVE METHODS FOR ESTIMATING BREAST DENSITY Isabel dos Santos Silva 1 , Steve Allen 2 , Amanda Eng 1 , Zoe Garland 1 , Sarah Vinnicombe 3 , Valerie McCormack 4 , JA Shepherd 5 , Mitch Dowsett 2 1 London School of Hygiene and Tropical Medicine, London, England; 2 Royal Marsden Hospital, UK; 3 University of Dundee, UK; 4 <strong>International</strong> Agency for Research on Cancer, France; 5 University of California ABSTRACTS FOR SPEAKERS Mammographic density (MD), a trait which closely reflects the amount of radio-dense (non-fatty) tissue of the breast, is one of the strongest known risk factors for breast cancer and a major determinant of sensitivity of mammographic screening. In many US states it is now mandatory for doctors to inform women if their breasts are dense (BI-RADS: 3 or 4), albeit it is unclear whether they will benefit from more intensive screening (e.g. shorter screening intervals, combination of mammography with ultrasound or MRI). Currently, there are several approaches to measuring MD in screen-film mammography. Qualitative assessments, such as BI-RADS, classify density into categories based on the subjective analysis of patterns observed on the mammogram while quantitative measurements determine the proportion of the projected breast area that is composed of radio-dense tissue on a digitised screen-film. The quantitative semi-automatic threshold method, as implemented by the Cumulus software, is regarded as the “gold standard” for screen-film mammography. However, this method has limitations: it is subjective (i.e. observer-dependent); its area-based nature may be less efficient than a volume-based approach; and it is a rather time-consuming and labour-intensive method. The latter, in particular, have precluded its incorporation into routine clinical/screening practice. Fully automated methods have been developed which attempt to use volumetric approaches to quantify more precisely breast density on digitised screenfilms. But despite their alleged higher precision, such volumetric methods do not appear to predict breast cancer risk more accurately than the area-based approaches. As screen-film mammography is being replaced by full-field digital mammography (FFDM), new fullyautomated volumetric methods have recently been developed for assessment of density from digital images. Evaluation of the performance of these methods have been mainly limited to establishing the correlations of their measurements with those from more established methods (e.g. BIRADS or Cumulus) and/or evaluating the extent to which their measurements are associated with known breast cancer risk factors. Ultimately, the best method for measuring breast density from digital images is the one that yields the strongest association with breast cancer risk. The development of a valid universal standard tool for measuring MD is vital for accurate risk prediction (on a population and individual level) and to tailor preventive measures, including breast screening, according to a woman’s risk. In this talk, I will present data from our on-going work on the evaluation of alternative methods of measuring breast density on digital images. These include three area-based methods: (i) visual qualitative assessment using the BI-RADS classification; (ii) a semi-automated assessment using a thresholding technique (Cumulus); and (iii) an automated ImageJ-based approach which mimics Cumulus (the latter two optimised for FFDM). In addition, we have evaluated three automated volumetric approaches: (iv) single X-ray absorptiometry (SXA) with calibration phantoms; (v) Volpara TM ; and (vi) Quantra TM . Overall, the findings showed that the density estimates yielded by the automated volumetric methods were at least as strongly associated with breast cancer risk as those produced by the area-based approaches. Thus, these results support the use of volumetric-based approaches in screening/clinical settings and in large-scale studies. 12
6 th <strong>International</strong> <strong>Workshop</strong> on Breast Densitometry and Breast Cancer Risk Assessment BREAST CANCER RISK: IS IT JUST ABOUT BREAST DENSITY Elizabeth Morris MD FACR Chief, Breast Imaging Service, Department of Radiology, Memorial Sloan-Kettering Cancer Center Breast parenchyma depicted on mammography has been shown to provide valuable information about breast cancer risk. Breast tissue consists primarily of fibroglandular tissue and fat. Fibroglandular tissue is responsible for the density seen on mammography. The risk of breast cancer and women with mammographically dense breasts has been shown in multiple studies to be higher than in women with predominantly mammographically fatty breasts. Breast MRI is a standard part of the imaging workup in high risk women and in patients with known breast cancer. On breast MRI examinations, the amount of fibroglandular tissue can be seen and this likely corresponds to breast density seen on mammography. MRI however demonstrates additional information about the underlying fibroglandular tissue. As intravenous contrast material is injected routinely for breast MRI examinations, it is been observed that native fibroglandular tissue will demonstrate variable enhancement patterns and levels of enhancement. The enhancement of the existing underlying fibroglandular tissue has been termed background parenchymal enhancement. As background parenchymal enhancement is related to vascular flow, it has been proposed that this may represent an imaging biomarker of the underlying proliferation of fibroglandular tissue. Investigations have shown that there is an extremely strong association between BPE and risk of breast cancer, at least a strong as the association between mammographic density and breast cancer. There has been observed that background parenchymal enhancement is also affected by treatment changes and hormonal manipulation. For example, tamoxifen therapy and aromatase inhibitors may decrease the intrinsic background parenchymal enhancement, demonstrating an imaging treatment response. It has been shown that background parenchymal enhancement may fluctuate during the menstrual cycle and that hormone replacement therapy can cause an increase in background parenchymal enhancement. Radiation therapy to the breast causes marked reduction in background parenchymal enhancement. As with breast density and distribution of breast parenchyma on mammography, it appears that the background parenchymal enhancement of breast MRI is also extremely variable and women have different patterns and intensity of background parenchymal enhancement. In fact, it has been observed that not all mammographically dense breasts demonstrate increased background parenchymal enhancement. Therefore, it is possible that MRI can further stratify women at high risk for developing breast cancer on the basis of background parenchymal enhancement. 1. King V, Brooks JD, Bernstein JL, Reiner AS, Pike MC, Morris EA. Background parenchymal enhancement at breast MR imaging and breast cancer risk. Radiology 2011; 260(1):50-60. PMID: 21493794 2. King V, Goldfarb S, Brooks J, Sung JS, Pike MC, Nulsen B, Jozefara J, Dickler M, Morris EA. Effect of aromatase inhibitors on background parenchymal enhancement and amount of fibroglandular tissue on Breast MRI. Radiology. 2012 Sep; 264(3):670-8. PMID: 22771878. 3. King V, Kaplan J, Pike MC, Liberman L, Dershaw DD, Lee CH, Brooks JD, Morris EA. Impact of tamoxifen on amount of fibroglandular tissue, background parenchymal enhancement, and cysts on breast magnetic resonance imaging. Breast J. 2012 Nov; 18(6):527-34. PMID: 23002953. 4. King V, Gu Y, Kaplan JB, Brooks JD, Pike MC, Morris EA. Impact of menopausal status on background parenchymal enhancement and fibroglandular tissue on breast MRI. European Radiology. 2012 Dec; 22(12):2641-7. PMID: 22752463. ABSTRACTS FOR SPEAKERS 13
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