The National Heart, Lung and Blood Institute https://www.nhlbi.nih.gov, within NIH, is funding a $7 million award at the Smidt Heart Institute at Cedars-Sinai.
The goal is to establish a new program to develop data tools that will help predict which patients could experience heart attacks, heart failure, and other cardiac conditions.
Coronary Artery Disease (CAD) remains a major public health concern with a high prevalence in the U.S. Functional, molecular, and structural imaging offers a unique opportunity to understand the pathophysiology of CAD, especially in high risk groups such as patients with obesity, diabetes, and chronic kidney disease.
However, physicians are not yet able to use the data optimally to identify patients at highest risk of adverse events due to the technical complexity of using advance multivariable data, and the lack of automation and integrative tools.
“Advanced imaging data could help predict patients’ risk of serious cardiac events but is so complex that clinicians aren’t always able to use it,” said Piotr Slomka, PhD, Director, Innovation in Imaging and Professor of Cardiology and Medicine in the Division of Artificial Intelligence (AI) in Medicine at Cedars-Sinai.
Dr. Slomka plans to create tools that can combine data from positron emission and tomography and CT scans to give a clearer picture of patients’ cardiac risk. He also plans to develop a large multicenter PET and CT imaging registry and use AI tools to develop decision support tools to thoroughly test these tools, automate analysis and quality control, and identify who can benefit from treatment using aggressive therapies.
According to Sumeet Chugh MD, Director, Division of AI in Medicine at Cedars-Sinai, Director of the Center for Cardiac Arrest Prevention, Smidt Heart Institute, “Our clinicians, have developed clinical tools that are now used worldwide. Now they have the skills to translate innovation into something they can place in clinicians’ hands, that will directly benefit patients everywhere.”
The grant, Outstanding Investigator Award (R-35) (R35HL161195) is titled “Patient-Specific Outcome Prediction from Cardiovascular Multimodality Imaging by Artificial Intelligence”.
Go to the Smidt Heart Institute at https://www.cedar.sinai.org/programs/heart.html for more information.