A novel AI model developed by Mayo Clinic and Ultromics demonstrated high accuracy in screening for cardiac amyloidosis in a clinical trial involving over 2,600 patients. Published in European Heart Journal, the AI achieved 85% sensitivity and 93% specificity, outperforming traditional clinical scores.
The model uses a single echocardiography videoclip to identify all major amyloidosis types, distinguishing them from similar cardiac conditions. Cardiac amyloidosis causes heart stiffening due to abnormal amyloid protein deposits, often leading to heart failure and frequently missed due to symptom overlap with other diseases.
Early diagnosis is critical as emerging drug therapies can slow disease progression but not reverse existing damage. The AI integrates with echo PACS systems, facilitating widespread use in echo labs.
Dr. Patricia Pellikka of Mayo Clinic, a key investigator, highlighted the model’s robust performance across amyloid phenotypes (AL, wtATTR, hATTR). This work follows their FDA-cleared AI model for detecting heart failure with preserved ejection fraction.
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