Innovative TRANSFORM Trial to Assess CT Imaging, Combined with AI, to Detect and Stratify Early Risk of Heart Events

A paradigm shift in the detection and prevention of cardiovascular disease, analogous to the system in place for decades in the field of cancer, looms on the horizon with the start of a nationwide clinical trial known as TRANSFORM. The randomized controlled study will assess whether pairing coronary CT angiography (CCTA) with an investigational AI-enabled algorithm to classify into stages the build-up of atherosclerotic plaque in the arteries of patients well before they have suffered a heart attack is superior to the standard of care.

“Currently, there is no effective way to determine if someone who is healthy but at risk because of diabetes or metabolic syndrome, for example, could experience a major cardiovascular event,” says study chair Deepak L. Bhatt, MD, MPH, MBA, Director of the Mount Sinai Fuster Heart Hospital and the Dr. Valentin Fuster Professor of Cardiovascular Medicine at the Icahn School of Medicine at Mount Sinai. “TRANSFORM is designed to perform early diagnosis and risk assessment for the severity of plaque using an AI algorithm, then titrate advanced medical therapy to prevent disease progression in those individuals found to be at greatest risk in an effort to reduce heart attack events.”

TRANSFORM in early 2024 will begin enrolling 7,500 patients with no symptoms or history of heart disease at 100 to 200 sites across the United States. All participants will undergo CCTA, then be randomized by researchers to either standard-of-care treatment based on atherosclerotic cardiovascular disease (ASCVD) risk factors, or to a care strategy driven by a personalized plaque staging system developed by Cleerly, a digital health care company that is sponsoring the trial. 

The goal of study organizers is to provide scientific evidence for a new model of primary care prevention in cardiovascular care, similar to what oncology uses to stage cancers on a scale of I to IV, depending on how much the tumors have grown and spread. Similarly, a four-tier CAD staging system based on a comprehensive assessment of the morphology and composition of coronary atherosclerotic plaque—representing low, mild, moderate, and high risk for future adverse events—may enable tailoring of medical therapy based on underlying event risk.

“The AI-enabled algorithm we will be using takes information from a noninvasive CT angiogram to look not only at the amount of plaque in the arteries of the heart, but also at its distribution and composition to see if there are resultant changes in blood flow due to the plaque,” explains Dr. Bhatt. “Through these characteristics, we hope to be able to predict the likelihood of a plaque rupture, as well as determine if the volume of plaque is sufficient to restrict the flow of blood within particular arteries. A standard angiogram can do some of that, but it cannot tell you what a patient’s chances are of having a heart attack over, say, the next five years.”

Just as important as risk stratification is the medical therapy that the highest risk patients in the TRANSFORM trial will receive. The objective, according to Dr. Bhatt, is to create a personalized care plan around the patient that surpasses current clinical guidelines. This approach might include intense cholesterol reduction through bempedoic acid, injectable PCSK9 inhibitors, SGLT1/SGLT2 inhibitors, colchicine, and antithrombotic medications—in effect, a full-court press targeting cholesterol, inflammation, and thrombosis designed to significantly modify risk and reduce the chance of future myocardial infarction or other serious cardiovascular events.

Monitoring is also a vital trial component of the study. Patients assigned to the coronary artery disease plaque staging arm will undergo a repeat CCTA scan at 24 months to check for disease progression. A plaque staging report comparing baseline to two-year results will be given to the patient’s care team, providing actionable, vessel-by-vessel insights for further planning and, potentially, intensification of therapy if improvements are not observed.

“We are hopeful this study will truly be transformative for the practice of cardiovascular medicine,” Dr. Bhatt says. “What we find may allow for a much more refined estimate of patient risk, based on the enormous power of AI in combination with coronary CT angiography, to see if we can measurably improve patient outcomes.”