Ultromics, a leader in AI-powered cardiology solutions, has unveiled new findings from its latest study on artificial intelligence in echocardiography, shared during the American Society of Echocardiography’s (ASE) 2025 Scientific Sessions in Nashville, Tennessee. The research, published as an abstract in the Journal of the American Society of Echocardiography (JASE), highlights the expanding role of AI in identifying cardiac amyloidosis earlier and with greater accuracy than traditional methods.
Cardiac amyloidosis, once often diagnosed only after years of unexplained heart failure, has rapidly moved into the spotlight of cardiology. With new therapies making headlines and specialists spotlighting the disease at major conferences, early detection is becoming critical. Ultromics’ AI solution, EchoGo® Amyloidosis, demonstrates its ability to find subtle disease markers during routine echocardiograms, allowing physicians to intervene at earlier stages when treatment has the greatest impact.
The study evaluated 4,815 patient cases drawn from 17 hospitals across the United States and United Kingdom, modeling how EchoGo® Amyloidosis could improve clinical referral decisions in real-world environments. The AI system consistently detected cases that standard approaches overlooked while reducing the burden of unnecessary testing. Across both low- and high-prevalence scenarios, the tool improved detection rates and enhanced efficiency, demonstrating broad potential for everyday clinical practice.
Cardiac amyloidosis is now understood to be a significant driver of heart failure, but up to two-thirds of cases remain undiagnosed. While therapies such as tafamidis and acoramidis are proven to slow disease progression and improve survival, they are most effective when treatment begins early. Dr. Ashley Akerman, Director of Clinical Sciences at Ultromics and lead author of the study, emphasized that patients too often endure years of symptoms before receiving a diagnosis. According to Dr. Akerman, integrating EchoGo® Amyloidosis into routine heart scans could help physicians identify more patients at risk, minimize unnecessary referrals, and expedite access to confirmatory testing and treatment.
EchoGo® Amyloidosis analyzes echocardiograms at the pixel level to reveal patterns invisible to the human eye. Trained on data from more than 7,100 patients across 15 international sites and validated in over 2,700 patients from 18 additional centers, the model demonstrated strong accuracy (AUC 0.93) across diverse, multi-ethnic populations. Its automated assessments provide consistency and reliability, helping clinicians bridge the diagnostic gap and connect more patients to life-extending therapies.
This study adds to the expanding clinical evidence base for Ultromics’ EchoGo® platform, the first FDA-cleared and Medicare-reimbursed AI solution for echocardiography. Already adopted by leading U.S. hospitals including UChicago Medicine, Northwestern, and City of Hope, EchoGo® is helping clinicians achieve earlier disease detection and more precise patient care, reinforcing AI’s transformative role in modern cardiology.
