Deep-Learning Image Reconstruction in CCTA
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|ClinicalTrials.gov Identifier: NCT03980470|
Recruitment Status : Recruiting
First Posted : June 10, 2019
Last Update Posted : June 10, 2019
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.
|Condition or disease||Intervention/treatment||Phase|
|Coronary Artery Disease||Device: TrueFidelity||Not Applicable|
|Study Type :||Interventional (Clinical Trial)|
|Estimated Enrollment :||50 participants|
|Intervention Model:||Single Group Assignment|
|Masking:||Single (Outcomes Assessor)|
|Official Title:||Usefulness of Deep-Learning Image Reconstruction for Cardiac Computed Tomography Angiography - a Prospective, Non-randomized Observational Trial|
|Actual Study Start Date :||May 3, 2019|
|Estimated Primary Completion Date :||June 30, 2019|
|Estimated Study Completion Date :||September 30, 2019|
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.
TrueFidelity (Deep Learning Image Reconstruction, DLIR) software by GE Healthcare.
The medical device in question is a novel reconstruction algorithm for raw CT data which is based on artificial intelligence approaches, namely deep-learning iterative reconstruction (DLIR). This DLIR algorithm will be installed on the console of the CT Revolution scanning device, which is in routine clinical use for cardiac CT scans at the Department of Nuclear Medicine at the University Hospital Zurich. Purpose of this installation is the assessment of the performance of the DLIR algorithm during a limited time span of six weeks.
The algorithm will be CE-marked at the time of installation and use (statement by GE Healthcare provided separately). Its intended use is the reconstruction of CT datasets.
Of note, the novel DLIR algorithm will not substitute any clinical routine procedures currently in use. That is, diagnosis will still be made using the standard reconstruction algorithms.
No Intervention: Normal-dose
The control 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.
- Subjective image quality as measured by Likert scale from 1 to 5, change from experimental interventional to the control intervention [ Time Frame: 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 [ Time Frame: 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 [ Time Frame: Day 1 ]
- Signal-to-noise ratio and contrast-to-noise ratio, change from experimental interventional to the control intervention [ Time Frame: Day 1 ]
- Comparison of dose-length products and radiation exposure in mSv [ Time Frame: Day 1 ]
- Subjective analysis of plaque composition (calcified plaque, non-calcified plaque, mixed plaque) and lesion severity (below 50%, 50-70%, over 70%) [ Time Frame: Day 1 ]
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03980470
|Contact: Valerie Treyer, PhDemail@example.com|
|Principal Investigator:||Ronny R Buechel, MD||Director of Cardiac Imaging|