A routine osteoporosis screening bone density test can also detect increased risk for a heart attack because of the presence of calcium in the aorta. But reading these images requires expertise and can be time-consuming.
Now, research from a multi-institution collaboration, including Harvard Medical School and Hebrew SeniorLife, reports that this calcification test score can be calculated quickly by using machine learning, without the need for a person to grade the scans.
This finding is published in the journal eBiomedicine.
“This development paves the way for use in routine clinical settings with little or no time to generate the useful calcification score that predicts heart attacks,” said Douglas Kiel, HMS professor of medicine and director of the Musculoskeletal Research Center at Hebrew SeniorLife and an author on the paper.