Study from AIM selected as best of RSNA

At the annual meeting of the RSNA, a study from AIM was selected as the best. The study investigates how AI can quantify coronary artery calcification (CAC) on low-dose chest CT. For this reason we developed a deep-learning algorithm that automatically quantifies coronary calcium on standard lung screening CT and evaluated prognostic value in 14,959 National Lung Screening Trial (NLST) participants.

We found significant associations between deep learning calcium score and all cause mortality as well as for cardiovascular mortality. Automated CAC corresponded closely to human readers in a large multicenter cohort of NLST participants having lung screening.