AI CVD Detects What Humans Miss
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AI-CVD™ is an AI-powered cardiovascular disease detection technology that analyzes CT scans to identify hidden heart risks, enabling early intervention and personalized prevention strategies.
* Pending FDA Clearance for Patient Care.
* Available Only for Research Studies.
* Two AI-CVD™ components, AutoBMD™ and AutoChamber™ are FDA-cleared. The remaining components are pending approval.
* Click on the individual modules above to learn more
A Paradigm Shift in CVD Risk Assessment
AI-CVD™ is an advanced artificial intelligence technology that extracts opportunistic screening information available in a cardiac or lung CT scan. This innovative approach significantly enhances CVD risk stratification by integrating imaging disease measures. AI-CVD™ thus emerges as the most comprehensive tool that extends well beyond coronary artery calcium (CAC) score and coronary artery disease to predict heart failure, atrial fibrillation, stroke, total CVD, CVD death and all-cause mortality.
Key Components of AI-CVD™ Beyond the CAC Score
Developed by HeartLung
Thoracic vertebral bone density, measurable in routine CAC scans, provides an important marker for osteoporosis. Low BMD is independently associated with increased CVD risk and all-cause mortality, potentially mediated by shared inflammatory and metabolic pathways. Incorporating BMD into CVD risk assessments ensures early detection of both osteoporosis and its cardiovascular implications, enabling timely interventions.
TAC, an often-overlooked finding in CAC scans, predicts stroke and CVD mortality with greater precision when combined with traditional risk factors. As a marker of systemic atherosclerosis, TAC enhances risk stratification for cerebrovascular events, broadening the utility of CAC scans.
AVC, visible in CAC scans, predicts aortic stenosis and its associated cardiovascular outcomes. Early identification of AVC facilitates closer monitoring and timely surgical or medical interventions, reducing morbidity and mortality from valve-related complications.
AI-driven analysis of cardiac chamber volumes—including the left atrium (LA), left ventricle (LV), right atrium (RA), and right ventricle (RV) provides actionable insights into heart failure and atrial fibrillation risk. Enlarged LA volume strongly predicts AF and stroke, while LV hypertrophy correlates with HF and coronary artery disease. These measurements add critical dimensions to CAC scans, improving predictive accuracy.
Fatty liver, detected opportunistically in CAC scans, correlates with metabolic syndrome, diabetes, and heightened CVD risk. By quantifying liver fat, AI-CVD™ identifies individuals at risk for cardiometabolic events, offering opportunities for early lifestyle or pharmacological interventions.
Visceral fat—a major driver of systemic inflammation and insulin resistance—is measurable in CAC scans. Increased visceral fat volume is a powerful predictor of metabolic syndrome, type 2 diabetes, and CVD. AI-CVD™’s ability to quantify visceral fat improves risk stratification for these conditions.
Pulmonary emphysema, visible in chest CT scans, is linked to chronic obstructive pulmonary disease (COPD) and increased cardiovascular mortality. Including emphysema scoring in AI-CVD™ highlights the interplay between pulmonary and cardiovascular health, fostering integrated care approaches.
Myosteatosis, characterized by fat infiltration into skeletal muscle, is an emerging biomarker of systemic metabolic dysfunction. AI-driven measurement of thoracic skeletal muscle density from CAC scans has shown strong predictive value for HF, AF, CHD), and all-cause mortality. Recent studies demonstrate that combining myosteatosis with CAC scores amplifies risk prediction, particularly for males, making it a critical addition to AI-CVD™.
The value of a CAC score is well established. With this AI-CVD™ component we report not only the weighted Agatston CAC score but also the area, density, location, distribution and shape of each calcified plaque and will be able to monitor changes in each plaque over time while reporting new plaques in the same artery or another artery.
AI-CVD™: A Novel Imaging-Augmented CVD Risk Score
AI-CVD™ leverages advanced AI algorithms to enhance cardiovascular disease risk assessment by integrating comprehensive imaging data from CAC scans with traditional risk factors. This approach significantly improves the prediction of conditions like heart failure and atrial fibrillation, outperforming traditional risk scores. Validated through studies like MESA and FHS, AI-CVD™ aims to set a new standard in cardiology.
Contact us for a Research Trial.
The size of the aorta and pulmonary artery (PA) are key indicators of cardiovascular health. Changes in PA size can signal pulmonary hypertension or other vascular diseases. Accurate measurement through imaging helps in early detection and management. An enlarged aorta can indicate conditions like aneurysm or dissection. AI-CVD™ uses advanced algorithms to measure these sizes, enhancing risk assessment and timely intervention for cardiovascular and pulmonary conditions.
