Computed Tomography

Cardiac computed tomography (CT) has become a primary cardiovascular imaging modality in the past 20 years, and was recommended as a 1A recommendation in the 2021 chest pain assessment guidelines. CT calcium scoring has became a primary risk assessment for coronary artery disease and whether patients should be on statins. Coronary CT angiography (CCTA) is used to for anatomical assessment of the arteries for plaque burden and to identify areas of blockage that may cause ischemia and heart attacks. Additional use of contrast CT perfusion or fractional flow reserve CT (FFR-CT) can offer physiological information on the function of the heart. CT plays a primary role in structural heart assessments for heart valves, repair of congenital defects and left atrial appendage occlusion (LAAO) for both pre-procedure planning and procedural guidance. Find more news on general radiology CT use.

HeartFlow Plaque Analysis

AI-powered coronary plaque assessments show ‘strong agreement’ with IVUS

HeartFlow's noninvasive Plaque Analysis technology, which uses AI to evaluate CCTA images, delivered assessments that mostly lined up with IVUS results. 

AI-based CAD assessments dramatically improve vascular surgery outcomes

PAD patients evaluated with HeartFlow's noninvasive FFRCT Analysis technology prior to surgery experienced much better outcomes, including a 63% lower risk of all-cause mortality after five years. 

Cardiology ranked No. 2 among all specialties with 122 FDA-cleared AI models

Only radiology is associated with more FDA-cleared AI algorithms than cardiology, according to new federal data. 

Interview with Nehal Mehta, MD, Penn Medicine, who explains how coronary inflammation can be seen using AI on cardiac CT scans to better risk stratify patients and begin preventive drug therapy.

AI helps cardiologists track new drug's effect on inflammation

The combination of AI and CT helped Nehal Mehta, MD, and colleagues track the performance of a new drug designed to target coronary inflammation. 

Sarah Jane Rinehart, MD, director of cardiac imaging, Charleston Area Medical Center, Charleston West Virginia, as been using the FDA-cleared RoadMap artificial intelligence algorithm from HeartFlow in studies and in clinical used since it was cleared and said it helps cardiologists in several ways. #ACC #ACC24 #ACC2024 #Heartflow #AIhealth

AI improves CT assessments, boosts care for real-world heart patients

Automated AI-generated measurements combined with annotated CT images can improve treatment planning and help referring physicians and patients better understand their disease, explained Sarah Jane Rinehart, MD, director of cardiac imaging with Charleston Area Medical Center.

Advanced artificial intelligence (AI) models can evaluate cardiovascular risk in routine chest CT scans without contrast, according to new research published in Nature Communications.[1] In fact, the authors noted, the AI approach may be more effective at identifying issues than relying on guidance from radiologists.

AI predicts cardiovascular risk during CT scans—no invasive tests or contrast required

Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans. 

New cardiac imaging strategy could reduce ICA, PCI rates

Radiologists with Massachusetts General Hospital found that the selective use of cardiac CT and AI-based CAD evaluations could make a significant impact on patient care. 

PHOTO GALLERY: Highlights from ACC.24 in Atlanta

ACC.24, the American College of Cardiology's annual meeting in Atlanta, featured the latest in cardiovascular research and technologies. Representatives from Cardiovascular Business were there in person to take in the excitement. 

Around the web

Several key trends were evident at the Radiological Society of North America 2024 meeting, including new CT and MR technology and evolving adoption of artificial intelligence.

Ron Blankstein, MD, professor of radiology, Harvard Medical School, explains the use of artificial intelligence to detect heart disease in non-cardiac CT exams.