In a population study involving 997 participants from the Robinsca CAC screening clinical trial in Europe, the company's AI-based Aview CAC software yielded 99.2% accuracy for categorizing risk compared with an experienced reader's interpretation of the low-dose CT exams, according to the researchers from the Institute for Diagnostic Accuracy (iDNA) at the University Medical Center Groningen in the Netherlands.
"The deep learning-based software for automatic CAC scoring can be used in a cardiovascular CT screening setting with high accuracy for cardiovascular risk categorization and initiation of preventive treatment," said senior author Dr. Matthijs Oudkerk, PhD, in a statement from Coreline.
Oudkerk was also principal investigator for radiology in the Dutch-Belgian Randomized Lung Cancer Screening (NELSON) study.
The CAC research was published online on August 18 in JACC: Cardiovascular Imaging.
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