Molecular imaging biomarkers for breast cancer risk and personalized screening

Recently, Hruska and colleagues (1) published an interesting paper in Breast Cancer Research on a crucial topic to understanding breast cancer risk factors. In 2016, they assessed BPU with molecular breast imaging (MBI) as a risk factor through a case-control study nested in a cohort study (2); in their recent study they showed that a semi-automated system can be used for a quantitative measurement of BPU (1). The study, though conducted retrospectively, has all the strengths of purely prospective cohort studies, since the authors had the opportunity to construct a cohort of asymptomatic women screened for breast cancer with MBI and included in their case-control study all the cases occurring in the cohort. Furthermore, the cohort had a sufficiently long follow up (3.5 y average) to include both incident cases and prevalent cases missed by the screening tests. Assessment of Tc-99m sestamibi BPU was conducted retrospectively. In the study published in 2016, two radiologists, blinded to the outcome, interpreted the uptake with a subjective four-point qualitative scale, while in the present study two non-radiologist readers, blinded to the outcome, performed a quantitative semi-automated measurement: on MBI images analyzed with the corresponding digital mammograms, they defined two regions-of-interest (ROI), one of purely fat tissue and one of fibroglandular tissue. Quantitative BPU was defined as a unitless ratio of the average pixel intensity (counts/pixel) within the fibroglandular tissue versus the average pixel intensity in fat