FDA Clears AI Software to Enhance CCTA Detection of Coronary Artery Disease
Through AI-powered assessment of coronary computed tomography angiography (CCTA) scans, the CaRi-Plaque software may provide improved clarity on the development of coronary plaques and luminal stenosis.
Offering the promise of improved insights into coronary plaques and luminal stenosis, the artificial intelligence (AI)-enabled CaRi-Plaque software has garnered 510(k) clearance from the Food and Drug Administration (FDA).
Through evaluation of coronary computed tomography angiography (CCTA) scans, reports generated with the CaRi-Plaque software provide actionable insights on plaque burden, total plaque volume, maximum stenosis, calcified plaque volume and other quantitative measures for coronary vessels, according to Caristo Diagnostics, the developer of CaRi-Plaque.
Offering quantitative insights into the extent and severity of coronary plaque and luminal stenosis based on AI assessment of coronary computed tomography angiography (CCTA) scans, the CaRi-Plaque software has garnered 510(k) clearance from the Food and Drug Administration (FDA). (Image courtesy of Caristo Diagnostics.)
By ascertaining the extent and severity of coronary plaque and luminal stenosis, Caristo Diagnostics said the CaRi-Plaque software may facilitate earlier detection of coronary artery disease (CAD) in high-risk patients.
"We stand on the brink of revolution in the prevention and treatment of coronary disease, thanks to Caristo's ability to analyze plaque and inflammation on coronary CT scans," said Stephen A. Bloom, M.D., a cardiologist and director of advance imaging at Midwest Heart & Vascular Specialists in Kansas City. "This advancement enables us to diagnose early stages of coronary disease, even before a coronary CT calcium score becomes positive, allowing for earlier intervention and treatment.”
Study: AI-Generated ADC Maps from MRI More Than Double Specificity in Prostate Cancer Detection
June 5th 2025Emerging research showed that AI-generated ADC mapping from MRI led to significant increases in accuracy, PPV and specificity in comparison to conventional ADC mapping while achieving a 93 percent sensitivity for PCa.
Can AI Assessment of PET Imaging Predict Treatment Outcomes for Patients with Lymphoma?
June 2nd 2025The use of adjunctive AI software with pre-treatment PET imaging demonstrated over a fourfold higher likelihood of predicting progression-free survival (PFS) in patients being treated for lymphoma, according to a new meta-analysis.
Lunit Unveils Enhanced AI-Powered CXR Software Update
May 28th 2025The Lunit Insight CXR4 update reportedly offers new features such as current-prior comparison of chest X-rays (CXRs), acute bone fracture detection and a 99.5 percent negative predictive value (NPV) for identifying normal CXRs.
