🫀 Modest attenuation in AF or reduced LVEF subgroups
🫀 Modest attenuation in AF or reduced LVEF subgroups
In a multicenter study developing an explainable, flow-aware AI pipeline to jointly grade mitral and tricuspid regurgitation from routine transthoracic echo DICOMs, discrimination for clinically significant (≥moderate) MR/TR was excellent in internal testing (AUROC >0.980; NPV >0.970) but showed modest attenuation in patients with atrial fibrillation or reduced LVEF.
Why It Matters To Your Practice
MR and TR commonly coexist and are assessed from overlapping echo views, making consistent grading time-intensive and variable across readers and settings.
An explainable, physiology-aware model with strong rule-out performance could support automated triage—especially where expert echo interpretation is constrained.
Subgroup attenuation in AF or reduced LVEF highlights where clinician oversight may be most needed before acting on AI outputs.
Clinical Implications
High NPV suggests a potential role as a screening/rule-out layer to deprioritize studies unlikely to have ≥moderate MR/TR, while escalating likely positives for expedited review.
Expect slightly lower performance when rhythm irregularity (AF) or reduced systolic function complicates Doppler and hemodynamic interpretation; consider tighter human-in-the-loop thresholds in these strata.
External validation across two additional institutions supports portability, but modest AUROC drops—especially for severe regurgitation—argue for local calibration and ongoing QA.
Insights
The pipeline is designed for real-world workflow: automated view selection from routine DICOMs, leaflet pose estimation for morphology, and systolic-phase awareness for Doppler interpretation.
Joint MR/TR grading may better reflect how clinicians interpret overlapping views and shared hemodynamic context than single-valve models.
Explainability and physiologic constraints are positioned as adoption enablers, addressing a common barrier to deploying “black-box” echo AI.
The Bottom Line
This explainable echo AI system maintained excellent internal performance and strong rule-out capability, with modest attenuation in AF or reduced LVEF—exactly the patients where you should plan for closer clinician verification.