Us2.ca is a clinical decision support tool that automatically analyzes echocardiogram images to assist cardiologists and healthcare professionals in identifying patients with potential cardiac amyloidosis. It improves clinical workflow by providing AI-derived measurements and report generation, helping clinicians focus on cases needing further follow-up, but it does not replace a formal diagnosis or current care standards.
Intended Use
Us2.ca processes acquired transthoracic cardiac ultrasound images to support qualified cardiologists, sonographers, or other licensed professional healthcare practitioners in their diagnosis of cardiac amyloidosis. Us2.ca is intended for use only in adult patients with increased left ventricular wall thickness, defined as an interventricular septal thickness (IVSd) or left ventricular posterior wall thickness (LVPWd) ≥ 12mm. Us2.ca is not intended to provide a diagnosis and does not replace current standards of care. The results from Us2.ca are not intended to exclude the need for further follow-up on cardiac amyloidosis.
Technology
Us2.ca is a software as a medical device (SaMD) that analyzes echocardiogram DICOM images via a video-based deep-learning AI model focusing on Apical 4-Chamber (A4C) ultrasound clips to detect cardiac amyloidosis. It automatically generates AI-derived measurements and functional disease indications aligned with cardiology guidelines. The software is hosted on a cloud platform and processes images post acquisition. It supports clinicians through automated report generation but leaves clinical decision-making to licensed professionals.
Performance
Us2.ca was developed and validated using a large multi-center retrospective dataset (over 4,000 patients for training and 1,647 for validation) acquired from GE, Philips, and Siemens ultrasound systems. The validation showed sensitivity of 86.9% and specificity of 87.4% for detecting cardiac amyloidosis among adult patients with increased left ventricular wall thickness. Subgroup analyses confirmed consistent performance across age, sex, race, ultrasound vendors, and clinical sites. Usability and cybersecurity testing were also performed to ensure safety and effectiveness.
Predicate Devices
No predicate devices specified
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