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Deep-Learning Image Reconstruction in CCTA

Not Applicable
Completed
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
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
Arm && Interventions
GroupInterventionDescription
Normal-dose versus Low-doseTrueFidelityThe 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
NameTimeMethod
Subjective Image QualityDay 1

Subjective image quality as measured by Likert scale from 1 (non-evaluable) to 5 (excellent)

Secondary Outcome Measures
NameTimeMethod
Signal-to-noise RatioDay 1

Signal-to-noise ratio

Signal IntensityDay 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 ProductsDay 1

Comparison of dose-length products

Image NoiseDay 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 VolumesDay 1

Quantitative analysis of coronary artery plaque volumes

Trial Locations

Locations (1)

University Hospital

🇨🇭

Zurich, Switzerland

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