Automated breast-density evaluation was just as accurate in predicting women’s risk of breast cancer, found and not found by mammography, as subjective evaluation done by radiologists, in a study led by researchers at UC San Francisco and Mayo Clinic.
Both assessment methods were equally accurate in predicting both the risk of cancer detected through mammography screening and the risk of interval invasive cancer – that is, cancer diagnosed within a year of a negative mammography result. Both methods predicted interval cancer more strongly than screen-detected cancer. The study was published May 1, 2018, in the Annals of Internal Medicine.
Breast density can increase tumor aggressiveness, as well as mask the presence of tumors in mammograms, explained UCSF Professor of Medicine Karla Kerlikowske, MD, who led the study with Mayo Clinic Professor of Epidemiology Celine Vachon, PhD. “This means that women with dense breasts are more likely to be diagnosed with advanced-stage breast cancers, especially those that are interval cancers, because their cancers are more likely to remain undetected for longer,” said Kerlikowske.
“These findings demonstrate that breast-density evaluation can be done with equal accuracy by either a radiologist or an automated system,” she said. “They also show the potential
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