NCT07308704

A Study Of Deep Learning For Echo Analysis, Tracking, And Evaluation

DELINEATE-Deploy: Deep Learning for Echo Analysis, Tracking, and Evaluation - Prospective Deployment Platform IRB

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 10,040,000 (estimated)
• Sponsor: Mayo Clinic · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

The purpose of this study is to deploy and evaluate informational AI-Echo algorithms that assist echo clinicians in interpreting core echocardiographic parameters (e.g., LV/RV size and function, valvular disease severity) and stratifying disease progression risk. The primary outcome is clinician usability, interpretive consistency, and workflow integration. Second, we will conduct a pragmatic, stepped-wedge clinical trial with multiple arms evaluating diagnostic AI-Echo algorithms designed to identify specific cardiovascular diseases- such as genetic cardiomyopathy, ischemic heart disease, and cardiac amyloidosis-and assess whether AI deployment increases diagnostic testing and shortens time to diagnosis. Trials will be conducted using EHR-based notification systems with cluster-level randomization.

Conditions

• Cardiomyopathy
• Ischemic Heart Disease
• Cardiac Amyloidosis

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	Transthoracic Echocardiography (TTE)	AI analysis of transthoracic echocardiography to improve disease detection.

Timeline

• Start date: 2026-02-26
• Primary completion: 2028-02-01
• Completion: 2028-02-01
• First posted: 2025-12-30
• Last updated: 2026-04-16

Locations

1 site across 1 country: United States