CorVista's AI Aims to Unmask a Hidden Heart Condition

BETHESDA, MD – March 24, 2026 – A significant gap in cardiovascular diagnostics, one that leaves millions of patients—predominantly women—with debilitating symptoms but no clear answers, may soon be addressed by artificial intelligence. CorVista Health, a Maryland-based medical technology company, is poised to present groundbreaking data on a non-invasive, machine-learning-powered test designed to detect Ischemia with Non-Obstructive Coronary Arteries (INOCA), a frustratingly elusive condition.

The announcement of the new data, scheduled for a poster presentation at the prestigious American College of Cardiology’s Annual Scientific Session (ACC.26) in New Orleans next week, signals a potential paradigm shift in how clinicians approach patients with chest pain and other cardiac symptoms who show no signs of blocked major arteries.

The Diagnostic Dilemma of INOCA

For decades, the primary focus of cardiac diagnostics has been on identifying obstructive coronary artery disease (CAD)—significant blockages in the heart's main arteries. The standard tool, coronary angiography, is highly effective at visualizing these blockages. But what happens when the angiogram comes back "clear," yet the patient continues to suffer from angina, shortness of breath, and fatigue?

This is the clinical reality for the estimated 3 to 4 million Americans, and many more worldwide, living with INOCA. The condition is characterized by evidence of ischemia (a lack of oxygen-rich blood flow to the heart muscle) without the presence of flow-limiting blockages. The problem often lies in the heart's smaller vessels, the microvasculature, which traditional tests are not designed to assess.

This diagnostic blind spot has profound consequences, particularly for women, who constitute between 50% and 70% of the INOCA patient population. Often dismissed as having non-cardiac pain or anxiety, these patients can endure years of symptoms, repeated hospital visits, and unnecessary invasive tests, all while their condition goes unrecognized. Contrary to earlier beliefs that INOCA was a benign syndrome, recent research has confirmed it is associated with an elevated risk of major adverse cardiovascular events (MACE), including heart attack, stroke, and heart failure, significantly impacting both quality of life and long-term prognosis.

A New Paradigm at the Point of Care

CorVista Health aims to replace this uncertainty with a definitive, point-of-care solution. The company's CorVista System is an FDA-cleared platform that uses a unique combination of sensors and machine-learned algorithms to analyze cardiac and hemodynamic signals. The test itself is remarkably simple for the patient: a brief, non-invasive procedure that requires no radiation, contrast agents, fasting, or exercise. Within minutes, the system's AI provides clinicians with actionable diagnostic insights.

The upcoming presentation at ACC.26, titled "Noninvasive Ischemia Detection in Symptomatic Patients: A Physiologic Feature Machine-Learned Model," will unveil the latest data specifically for INOCA detection. The research will be presented by the company’s Chief Scientific Officer, Dr. Charles Bridges, and Data Scientist, Tim Burton, highlighting the development of a model based on physiological features.

The company has already established a track record of regulatory and clinical success. Its CorVista System has received FDA 510(k) clearance for two other modules: one for assessing the likelihood of significant CAD, which demonstrated a 99% negative predictive value in ruling out the disease, and another for indicating the likelihood of pulmonary hypertension (PH), which received a Breakthrough Device designation from the FDA. This history of successful validation lends significant weight to its new venture into the challenging INOCA space.

Reshaping the Cardiovascular Market

The introduction of an effective, non-invasive test for INOCA could be a disruptive force in the multi-billion dollar cardiovascular diagnostics market. This market, valued at over $11 billion in 2024 and projected to more than double by 2034, is increasingly driven by a demand for safer, faster, and more patient-friendly diagnostic modalities.

CorVista's competitive advantage lies not only in its technology but also in its business model. By offering its platform as a "MedTech-as-a-Service," the company lowers the barrier to entry for clinics and hospitals that may lack the capital for expensive imaging equipment like PET or cardiac MRI scanners. This model has the potential to democratize access to advanced cardiac diagnostics, extending its reach into rural and underserved communities where specialized care is often limited.

For a healthcare system grappling with rising costs and the need for greater efficiency, a tool that can quickly and accurately triage patients in an outpatient or emergency setting is highly attractive. By providing a clear diagnosis for INOCA, the CorVista System could reduce the number of costly and invasive angiograms performed on patients who will not benefit from them, while directing those who do have the condition toward appropriate, targeted therapies.

The Science Behind the Signal

At the heart of the CorVista System is the power of machine learning to decipher complex biological data. The system synchronously captures a rich dataset of physiological signals during each test. These signals, which reflect the intricate mechanics and blood flow of the cardiovascular system, contain subtle patterns that are invisible to the human eye or conventional diagnostic tools.

The "physiologic feature machine-learned model" to be presented at ACC.26 was likely trained on extensive datasets, comparing the signals of patients with confirmed INOCA against those without. By learning these distinct digital signatures, the algorithm can predict the likelihood of the condition in new patients. This approach represents a significant leap from traditional diagnostics, which often rely on single, indirect biomarkers of disease.

The scientific rigor behind this effort is spearheaded by Dr. Charles Bridges, a figure of immense standing in both medicine and engineering. A former cardiac surgeon, Johnson & Johnson executive, and an elected member of the National Academy of Engineering, Dr. Bridges' leadership underscores the deep scientific foundation of CorVista's technology. The company's approach, validated through its IDENTIFY clinical studies for CAD and PH, involves rigorous, blinded clinical trials to prove the algorithm's performance before bringing it to market. The cardiology community will be watching the ACC.26 presentation closely for data that meets this high standard, potentially paving the way for a new standard of care for a long-neglected patient population.