Us2.ca

Us2.ca is an AI-powered image analysis software that processes transthoracic cardiac ultrasound images to help qualified cardiologists, sonographers, and healthcare practitioners diagnose cardiac amyloidosis. It is intended for adult patients with increased left ventricular wall thickness (interventricular septal thickness or left ventricular posterior wall thickness ≥12mm) and serves as a clinical decision-support tool, not a standalone diagnostic device.

Both Us2.ca and the predicate device (EchoGo Cardiac Amyloidosis 1.0) are Class II adjunctive cardiovascular status indicators using machine learning algorithms to analyze DICOM-formatted echocardiographic images. Both devices are software-as-a-medical-device (SaMD) hosted on third-party cloud infrastructure. Key differences include Us2.ca's expanded intended population (all adults, not just those ≥65 years) and broader user base (sonographers and licensed practitioners, not only interpreting clinicians).

The submission references AAMI/ANSI HE75 standards for human factors and usability engineering assessment. FDA guidance documents on cybersecurity management, software changes, and 510(k) decision-making are cited. Internal verification and validation testing, regression testing, and design control processes are described, but specific ISO, IEC, or ASTM consensus standards are not explicitly identified in this summary.

Both devices target cardiac amyloidosis detection using machine learning on echocardiographic data and share the same regulatory classification and product code. Us2.ca's differences in intended population age range and user types do not create new safety or effectiveness questions because the device operates on the same technological principle, uses comparable performance metrics (sensitivity 86.9%, specificity 87.4%), and demonstrates substantial equivalence through extensive external validation across multiple clinical sites and ultrasound vendors with results meeting established benchmarks and subgroup consistency across demographics and systems.