Stamford Health Deploys 2 FDA-Cleared AI Tools, Finding 11 Severe Aortic Valve Cases
Updated
Updated · dicardiology.com · Jun 17
Stamford Health Deploys 2 FDA-Cleared AI Tools, Finding 11 Severe Aortic Valve Cases
1 articles · Updated · dicardiology.com · Jun 17
Summary
Roughly 300 non-cardiac chest CT patients were screened with Stamford Health’s new aortic valve calcification algorithm, and 11 were later confirmed to have severe aortic stenosis on follow-up echocardiograms.
About one-third of that cohort had never previously received an echocardiogram despite visible aortic valve calcification, highlighting how standard exams can miss older patients already undergoing CT imaging for other reasons.
The FDA-cleared AVC and coronary artery calcification tools run in the background of non-contrast CT scans, quantify disease burden, and automatically alert ordering physicians to consider cardiology referral and further testing.
Stamford has used Bunkerhill Health’s CAC algorithm since 2024 to screen thousands of patients, and says another AI tool from Heartflow has already lifted coronary CT workflow volume by 10%.
Clinicians say the broader aim is to move AI from opportunistic detection into routine surveillance and, over time, potentially into formal cardiovascular screening guidelines.
Should hospitals use AI to re-analyze millions of past CT scans for missed signs of fatal heart disease?
As AI outpaces doctors in detection, who is liable for a missed diagnosis: the human or the algorithm?
Stamford Health’s 2026 AI-Driven Cardiovascular Screening: Early Detection of Aortic Valve and Coronary Artery Calcification at Scale
Overview
In June 2026, Stamford Health began using FDA-cleared AI tools to improve cardiovascular screening, focusing on detecting aortic valve and coronary artery calcification. This move follows the introduction of a new billing code and reimbursement system, making it easier for hospitals to adopt AI for chest CT scans. The main goal is to catch serious heart conditions, like aortic stenosis and coronary artery disease, earlier—problems that are often missed. By using AI, health systems can better identify at-risk patients and start treatments sooner, leading to improved care and clearer workflows for clinicians.