SEOUL-- October 27, 2021 -- Coreline Soft, the developer of the AI Coronary Artery Calcium (CAC) solution named AVIEW CAC, announced that its AI CAC solution showed 99.2% accuracy from a population study conducted by the Institute for Diagnostic Accuracy (iDNA), the NELSON trial team in Europe.

The study verified the performance of the AI-based Coronary Artery Calcium scoring solution compared to an experienced reader from a well-defined screening population.

The prospective data acquired from the ROBINSCA screening trial in the Netherlands was used and the study found that ‘the deep learning-based software for automatic CAC scoring performed excellently in a population-based screening setting to determine risk categorization in asymptomatic participants.’ The research team concluded that the diagnostic accuracy of the company’s AI system was 99.2 percent for initiation of treatment from the low dose computed tomography.

Matthijs Oudkerk, Professor of Radiology at the University Medical Center Groningen and Principal Investigator for Radiology of the NELSON Lung Cancer Detection Study, concluded that “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.”

"Early detection and treatment are very important to reduce coronary heart disease, the second leading cause of death globally,” said Jinkook Kim, CEO of Coreline. “The automatic AI solution is becoming the very key tool for early detection of coronary anomalies, contributing to heart health.”

The study and its results are in the article of the JACC (Journal of the American College of Cardiology) and published online in August 2021.