NCT06206187

Blinded Randomized Controlled Trial of Artificial Intelligence Guided Detection of Intracardiac Thrombus

ICE Detector-RCT: Blinded, Randomized Controlled Trial of Electrophysiologist vs. Artificial Intelligence Detection of Intracardiac Thrombus

• Status: Unknown
• Phase: N/A
• Study type: Interventional
• Enrollment: 1,500 (estimated)
• Sponsor: Shanghai Chest Hospital · Academic / Other
• Sex: All
• Age: 18 Years – 90 Years
• Healthy volunteers: Accepted

Summary

To determine whether an integrated AI decision support can save time and improve the accuracy of detection of intracardiac thrombus, the investigators are conducting a blinded, randomized controlled study of AI-guided detection of intracardiac thrombus to electrophysiologist judgment in preliminary readings of echocardiograms.

Conditions

• Atrial Fibrillation

Interventions

Type	Name	Description
OTHER	Automated detection of the intracardiac thrombus through deep learning	A deep learning model will identify the intracardiac thrombus. The AI model will produce an assessment of intracardiac thrombus using video based features.
OTHER	Electrophysiologist judgment of the intracardiac thrombus	Cardiac electrophysiologists use their own experience to determine whether there is intracardiac thrombus

Timeline

• Start date: 2024-01-05
• Primary completion: 2025-07-31
• Completion: 2025-12-31
• First posted: 2024-01-16
• Last updated: 2024-01-16

Locations

1 site across 1 country: China