Screening mammography beyond breast cancer: breast arterial calcifications as a sex-specific biomarker of cardiovascular risk. Issue 119 (October 2019) - Trimboli, Rubina Manuela; Codari, Marina; Guazzi, Marco; Sardanelli, Francesco
Graphical abstract: Highlights: Breast arterial calcifications are easily recognizable on mammography. Breast arterial calcifications are associated with cardiovascular risk factors. Breast arterial calcifications may serve as cardiovascular risk marker in women. A robust quantification is indispensable for an application in prevention. Abstract: Purpose: To highlight the importance of quantitative breast arterial calcifications (BAC) assessment for an effective stratification of cardiovascular (CV) risk in women, for whom current preventive strategies are inadequate. BAC, easily detectable on mammograms, are associated with CV disease and represent a potential imaging biomarker for CV disease prevention in women. Method: We summarized the available evidence on this topic. Results: Age, parity, diabetes, and hyperlipidemia were found to positively correlate with BAC. Women with BAC have a higher CV risk than those without BAC: the relative risk was reported to be 1.4 for transient ischemic attack/stroke, 1.5 for thrombosis, 1.8 for myocardial infarction; the reported hazard ratio was 1.32 for coronary artery disease (CAD), 1.52 for heart failure, 1.29 for CV death, 1.44 for death from CAD. However, BAC do not alarm radiologists; when reported, they are commonly mentioned as "present", not impacting on CV decision-making. Of 18 published studies, 9 reported only presence/absence of BAC, 4 used a semi-quantitative scale, and 5 a continuous scale (with manual, automatic or semiautomatic segmentation). Various appearance, topological complexity, and vessels overlap make BAC quantification difficult to standardize. Nevertheless, machine learning approaches showed promising results in BAC quantification on mammograms. Conclusions: There is a strong rationale for mammography to become a dual test for breast cancer screening and CV disease prevention. However, robust and automated quantification methods are needed for a deeper insight on the association between BAC and CV disease, to stratifying CV risk and define personalized preventive actions.