Automated Aortic Stenosis Grading
Us2.ai measures Vmax, mean gradient, and AVA on every scan and reports a guideline-based severity grade for the clinician to confirm. Published correlations with expert sonographers: r = 0.97, 0.94, and 0.88.
The Most Common Valvular Heart Disease
Aortic stenosis affects over 12% of people aged 75 and older. As populations age and TAVR referrals surge, the demand for accurate AS grading is outpacing the specialist workforce.
Aortic stenosis is the most common valvular heart disease in the elderly. Prevalence increases steeply with age, making it a growing public health challenge.
Severe aortic stenosis carries a 2-year mortality of 25.6% when managed conservatively. Timely identification and intervention are critical to survival.
Up to 50% of AS cases show discordance between Vmax, mean gradient, and AVA grading criteria, making consistent severity classification a persistent clinical challenge.
TAVR has transformed AS management, creating unprecedented demand for echocardiographic assessment: pre-procedural screening and post-procedural surveillance. Every TAVR candidate requires precise AS grading, and every TAVR patient needs serial follow-up. Automating this assessment is essential to keep pace.
Automated AS Measurement & Severity Grading
Us2.ai grades aortic stenosis end to end, from view identification through Doppler tracing to a guideline-based severity grade, measuring every guideline parameter on each scan for the clinician to confirm.
Peak Aortic Velocity (Vmax)
The primary hemodynamic parameter for AS grading. Us2.ai automatically identifies continuous-wave Doppler of the aortic valve, traces the velocity envelope, and reports Vmax with r = 0.97 correlation to expert measurements.
Mean Pressure Gradient
Derived from the full CW Doppler envelope. Us2.ai computes mean gradient automatically. Alongside Vmax, it defines mild, moderate, and severe AS. Published correlation: r = 0.94.
Aortic Valve Area (AVA)
Calculated via the continuity equation using LVOT diameter, LVOT VTI, and AV VTI, all measured automatically. AVA is critical for identifying low-flow, low-gradient severe AS. Published correlation: r = 0.88.
LV Function & Flow Assessment
LVEF and stroke volume index are essential to distinguish classical severe AS from paradoxical low-flow states. Us2.ai reports both automatically, enabling complete hemodynamic context for every patient.
Beyond individual measurements, Us2.ai integrates Vmax, mean gradient, AVA, and LVEF to output a final AS severity grade: mild, moderate, or severe. This automated grading workflow is patented (US 12,322,100 B2).
Validated in a Peer-Reviewed Study
Us2.ai's AS assessment has been validated in a multi-center study published in the Journal of the American Society of Echocardiography, the field's leading journal.
First Fully Automated System
Us2.ai is the first published AI system to perform end-to-end automated AS assessment requiring zero human input, from raw DICOM images to severity classification, with no manual measurements or corrections needed.
Expert-Level Accuracy
Across all key parameters, Us2.ai achieved correlations of r = 0.76–0.97 against expert sonographer measurements. For the primary AS marker (Vmax), the correlation of r = 0.97 matches inter-expert variability.
Scalable Without Specialists
The growing TAVR population demands exponentially more echo assessments. Fully automated AS grading enables high-volume screening and surveillance without requiring additional specialist sonographers for every study.
Us2.ai Accuracy: AI vs. Expert Measurements
Frequently Asked Questions
Common questions about aortic stenosis and AI echocardiography.
How common is aortic stenosis?
Aortic stenosis is the most common valvular heart disease, affecting over 12% of people aged 75 and older. Its prevalence increases steeply with age, and it is a growing public health challenge as populations age worldwide.
Can AI accurately grade aortic stenosis severity?
Yes. Us2.ai has published peer-reviewed evidence in the Journal of the American Society of Echocardiography demonstrating fully automated AS grading with correlations of r=0.97 for peak velocity, r=0.94 for mean gradient, and r=0.88 for aortic valve area. The system achieved 97.6% accuracy for detecting moderate-or-greater AS.
What parameters does Us2.ai measure for aortic stenosis?
Us2.ai automatically measures all key AS parameters: peak aortic velocity (Vmax), mean pressure gradient, aortic valve area via the continuity equation (including LVOT diameter and VTI), and left ventricular ejection fraction. It then integrates these into a final severity classification.
What makes Us2.ai's AS assessment different from other AI tools?
Us2.ai is the first published AI system to perform fully automated end-to-end aortic stenosis assessment requiring zero human input. From raw DICOM images to final severity classification, the entire process, including view identification, Doppler tracing, and continuity equation calculation, is performed without manual interaction.
Peer-reviewed. Expert-level accuracy.
Automated AS Grading, Every Echo
Us2.ai measures Vmax, mean gradient, and AVA on every scan and reports a guideline-based severity grade, with published correlations to expert sonographers of r = 0.97, 0.94, and 0.88.