Patterns in magnetic resonance images may predict if a patient has triple-negative breast cancer, slower-moving cancers or non-cancerous lesions with 95 percent accuracy, according to research published online in the journal Radiology.
The technique could enable doctors to use an MRI scan to diagnose more aggressive cancers earlier and fast track these patients for therapy.
“Literally, what we’re trying to do is squeeze out the information we’re not able to see just by looking at an image,” said senior author Anant Madabhushi, a professor of biomedical engineering at Case School of Engineering and director of the Center for Computational Imaging and Personalized Diagnostics.
Researchers analyzed images from 65 women and discovered that tumors from triple-negative cancer reflect different textures when images are enhanced with contrasting agents.
“Today, if a woman or her doctor finds a lump, she gets a mammogram and then a biopsy for molecular analysis, which can take two weeks or up to a month,” Madabhushi said. “If we can predict the cancer is triple-negative, we can fast track the patient for biopsy and treatment. Especially in cases with triple-negative cancer, two to four weeks saved can be crucial.”
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