Deep-Learning Image Reconstruction in CCTA
- Conditions
- Coronary Artery Disease
- Interventions
- Device: TrueFidelity
- 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
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 50
- Patients referred for cardiac CT angiography
- Age ≥ 18 years
- Written informed consent
- 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
- Arm && Interventions
Group Intervention Description Normal-dose versus Low-dose TrueFidelity The standard intervention consists of the routinely performed cardiac CT datasets reconstructed with a standard iterative reconstruction algorithm (ASIR-V). Median radiation dose is about 0.5 mSv, range between about 0.2 and 1.2 mSv; median contrast agent administration about 45 mL, range between 35 and 55 mL. The experimental intervention is an additional CT scan with a lower dose (about 20 to 50% decrease) and a similar contrast agent administration that is reconstructed with a deep-learning image reconstruction immediately after the clinical CT scan. The additional time required is about 5 minutes.
- 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