Predicting breast cancer: How MRI can help high-risk patients

MRI can offer information about a patient’s future risk of developing breast cancer, which in turn could help doctors personalize screening and prevention measures for high-risk women, according to results of a study published online May 12 in Radiology.

It is estimated that approximately 40,000 women in the U.S. are killed by breast cancer annually, a fact that drives the ongoing need for early detection, especially in women who are at an increased risk of developing breast cancer in the future. But population-based risk-assessment tools have proved unsuccessful at determining individual risk, according to lead author Brian Dontchos, MD, and his colleagues at the University of Washington School of Medicine. “Several studies have examined the value of adding mammographic density to current risk prediction tools; however, these models provide only moderate discriminative ability,” wrote Dontchos et al. “MR imaging has shown high correlation to mammographic breast density assessment and may provide superior accuracy in the determination of breast cancer risk.”

Dontchos and his team set out to investigate the effectiveness of qualitative MRI in predicting future cancers in women at heightened risk of developing breast cancer. To do so, they conducted a retrospective study of all MR breast cancer screening images performed on high-risk patients from January 2006 to December 2011 at their medical facility. Amount of background parenchymal enhancement (BPE), BPE patterning (periperharl versus central) and amount of fibroglandular tissue (FGT) were assessed for two groups: patients who eventually developed breast cancer, and those who did not.

Their results showed that women with mild, moderate or high levels of BPE were nine times more likely to have developed cancer during the interval between their initial exams and the time of the study than those with minimal BPE. Alternately, BPE pattern, FGT levels and general mammographic breast density showed no statistical significance in determining future cancer risk.

“Our results suggest that this breast MR imaging feature has the potential to improve upon standard clinical models to more accurately determine a woman’s individual breast cancer risk,” wrote Dontchos and colleagues. “We found no differences in mammographic density or the amount of FGT on MR images between the cancer and control cohorts.”

Dontchos and his colleagues believe their finding can aid doctors in developing better screening strategies to catch developing breast cancers early and reduce mortality rates. “If this biomarker is verified in larger multicenter cohorts,” the authors concluded, “the integration of BPE into clinical risk assessment tools could enable screening and chemoprevention strategies to be better tailored to each individual’s true risk.”