Deep-Learning Image Reconstruction in CCTA

Not Applicable

Completed

• Conditions: Coronary Artery Disease

• Registration Number: NCT03980470
• Lead Sponsor: University of Zurich

Brief Summary

Cardiac CT allows the assessment of the heart and of the coronary arteries by use of ionising radiation. Although radiation exposure was significantly reduced in recent years, further decrease in radiation exposure is limited by increased image noise and deterioration in image quality. Recent evidence suggests that further technological refinements with artificial intelligence allows improved post-processing of images with reduction of image noise.

The present study aims at assessing the potential of a deep-learning image reconstruction algorithm in a clinical setting. Specifically, after a standard clinical scan, patients are scanned with lower radiation exposure and reconstructed with the DLIR algorithm. This interventional scan is then compared to the standard clinical scan.

Detailed Description

Not available

Study Timeline

• Study Start: 2019-05-08
• Study First Submitted: 2019-05-24
• Study First Submitted QC: 2019-06-06
• Study First Posted: 2019-06-10
• Primary Completion: 2019-06-20
• Study Completion: 2019-06-20
• Results First Submitted: 2021-09-28
• Status Verified: 2021-10
• Results First Submitted QC: 2021-10-26
• Last Update Submitted: 2021-10-26
• Results First Posted: 2021-11-24
• Last Update Posted: 2021-11-24

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 50

Inclusion Criteria

• Patients referred for cardiac CT angiography
• Age ≥ 18 years
• Written informed consent

Exclusion Criteria

• Pregnancy or breast-feeding
• Enrollment of the investigator, his/her family members, employees and other dependent persons
• Renal insufficiency (GFR below 35 mL/min/1.73 m²)

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: SINGLE_GROUP

Primary Outcome Measures

Name	Time	Method
Subjective Image Quality	Day 1	Subjective image quality as measured by Likert scale from 1 (non-evaluable) to 5 (excellent)

Secondary Outcome Measures

Name	Time	Method
Signal-to-noise Ratio	Day 1	Signal-to-noise ratio
Signal Intensity	Day 1	Signal intensity as average hounsfield units within a region of interest in the aortic root, change from experimental interventional to the control intervention
Dose-length Products	Day 1	Comparison of dose-length products
Image Noise	Day 1	Image noise as standard deviation of hounsfield units within a region of interest in the aortic root, change from experimental interventional to the control intervention
Plaque Volumes	Day 1	Quantitative analysis of coronary artery plaque volumes

Trial Locations

Locations (1)

University Hospital; 🇨🇭 Zurich, Switzerland