NCT03980470

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.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
50

participants targeted

Target at below P25 for not_applicable coronary-artery-disease

Timeline
Completed

Started May 2019

Shorter than P25 for not_applicable coronary-artery-disease

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

May 8, 2019

Completed
16 days until next milestone

First Submitted

Initial submission to the registry

May 24, 2019

Completed
17 days until next milestone

First Posted

Study publicly available on registry

June 10, 2019

Completed
10 days until next milestone

Primary Completion

Last participant's last visit for primary outcome

June 20, 2019

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

June 20, 2019

Completed
2.4 years until next milestone

Results Posted

Study results publicly available

November 24, 2021

Completed
Last Updated

November 24, 2021

Status Verified

October 1, 2021

Enrollment Period

1 month

First QC Date

May 24, 2019

Results QC Date

September 28, 2021

Last Update Submit

October 26, 2021

Conditions

Coronary Artery Disease

Outcome Measures

Primary Outcomes (1)

  • Subjective Image Quality

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

    Day 1

Secondary Outcomes (5)

  • Signal Intensity

    Day 1

  • Image Noise

    Day 1

  • Signal-to-noise Ratio

    Day 1

  • Dose-length Products

    Day 1

  • Plaque Volumes

    Day 1

Study Arms (1)

Normal-dose versus Low-dose

OTHER

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.

Device: TrueFidelity

Interventions

TrueFidelityDEVICE

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.

Normal-dose versus Low-dose

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

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

You may not qualify if:

  • 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)

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

University Hospital

Zurich, 8091, Switzerland

Location

Related Publications (5)

  • Benz DC, Grani C, Hirt Moch B, Mikulicic F, Vontobel J, Fuchs TA, Stehli J, Clerc OF, Possner M, Pazhenkottil AP, Gaemperli O, Buechel RR, Kaufmann PA. Minimized Radiation and Contrast Agent Exposure for Coronary Computed Tomography Angiography: First Clinical Experience on a Latest Generation 256-slice Scanner. Acad Radiol. 2016 Aug;23(8):1008-14. doi: 10.1016/j.acra.2016.03.015. Epub 2016 May 9.

    PMID: 27174030BACKGROUND

  • Benz DC, Fuchs TA, Grani C, Studer Bruengger AA, Clerc OF, Mikulicic F, Messerli M, Stehli J, Possner M, Pazhenkottil AP, Gaemperli O, Kaufmann PA, Buechel RR. Head-to-head comparison of adaptive statistical and model-based iterative reconstruction algorithms for submillisievert coronary CT angiography. Eur Heart J Cardiovasc Imaging. 2018 Feb 1;19(2):193-198. doi: 10.1093/ehjci/jex008.

    PMID: 28200212BACKGROUND

  • Sahiner B, Pezeshk A, Hadjiiski LM, Wang X, Drukker K, Cha KH, Summers RM, Giger ML. Deep learning in medical imaging and radiation therapy. Med Phys. 2019 Jan;46(1):e1-e36. doi: 10.1002/mp.13264. Epub 2018 Nov 20.

    PMID: 30367497BACKGROUND

  • Toprak O. Conflicting and new risk factors for contrast induced nephropathy. J Urol. 2007 Dec;178(6):2277-83. doi: 10.1016/j.juro.2007.08.054. Epub 2007 Oct 22.

    PMID: 17936812BACKGROUND

  • Benz DC, Grani C, Hirt Moch B, Mikulicic F, Vontobel J, Fuchs TA, Stehli J, Clerc OF, Possner M, Pazhenkottil AP, Gaemperli O, Buechel RR, Kaufmann PA. A low-dose and an ultra-low-dose contrast agent protocol for coronary CT angiography in a clinical setting: quantitative and qualitative comparison to a standard dose protocol. Br J Radiol. 2017 Jun;90(1074):20160933. doi: 10.1259/bjr.20160933. Epub 2017 May 25.

    PMID: 28406318BACKGROUND

MeSH Terms

Conditions

Coronary Artery Disease

Condition Hierarchy (Ancestors)

Coronary DiseaseMyocardial IschemiaHeart DiseasesCardiovascular DiseasesArteriosclerosisArterial Occlusive DiseasesVascular Diseases

Results Point of Contact

Title
Dr Ronny R. Buechel
Organization
University Hospital Zurich
ronny.buechel@usz.ch
+41442551059

Study Officials

  • Ronny R Buechel, MD

    Director of Cardiac Imaging

    PRINCIPAL INVESTIGATOR

Publication Agreements

PI is Sponsor Employee
Yes

Study Design

Study Type
interventional
Phase
not applicable
Allocation
NA
Masking
NONE
Purpose
DIAGNOSTIC
Intervention Model
SINGLE GROUP
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
PD Dr. med. Ronny R. Buechel

Study Record Dates

First Submitted

May 24, 2019

First Posted

June 10, 2019

Study Start

May 8, 2019

Primary Completion

June 20, 2019

Study Completion

June 20, 2019

Last Updated

November 24, 2021

Results First Posted

November 24, 2021

Record last verified: 2021-10

Data Sharing

IPD Sharing
Will not share

Locations

CH(1)