Clinical trial NCT04185493: Coronary Artery Geometry and the Severity of Coronary Atherosclerosis
Official title: Assessment of Coronary Artery Geometry With Coronary CT Angiography: Evaluation of Atherosclerotic Plaque Burden and Composition
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Coronary Artery Disease
Atherosclerosis
Atherosclerotic Plaque
Stable Angina
Keywords: Geometry
Bifurcation Angle
Cardiac Computed Tomography Angiography
Coronary Artery Disease
Vulnerable Coronary Plaque
Indexed Coronary Volume
Risk Assessment
Lead sponsor: Aristotle University Of Thessaloniki
Sponsor class: OTHER
First posted: 2019-12-04
Enrollment: 100
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Consecutive patients older than 18 years old at entry, of both genders, who referred for coronary CT angiography

Brief summary: The purpose of this study is to investigate the potential association of coronary artery geometry, based on coronary CT angiography (CCTA), with the complexity and the severity of coronary atherosclerosis.

Detailed description: The angulation of the side branch take-off has been reported to influence the severity of atherosclerosis in coronary bifurcations, as larger angles have been associated with increased plaque burden. Data from computational fluid dynamics studies have confirmed this finding by demonstrating that even in the absence of alterations in the amount of branch flow, a wide angle between the side branches intensifies flow perturbations, increases the spatial endothelial shear stress (ESS) variations in the bifurcation region and the low ESS in the lateral walls, thereby augmenting the atherosclerosis-prone environment. The magnitude of reversed flow, the extension of the recirculation zone and the duration of flow separation during the pulse cycle comprise other haemodynamic parameters which are important in atherogenesis and are amplified by an increased bifurcation angle.

Eligibility criteria: Inclusion Criteria:

* Patients referred for cardiac CT angiography
* Patients without previous history of Coronary Artery Disease (CAD)
* Age ≥ 18 years
* Patients giving voluntary written consent to participate in the study

Exclusion Criteria:

* Pregnancy or breast-feeding
* Patients with serious concurrent disease and life expectancy of \< 1 year
* Patients with a previous history of CAD
* Patients who refuse to give written consent for participation in the study

Primary outcomes:
measure: Left Main Coronary Artery (LMCA) angle of take-off from the aortic root
timeFrame: 30 days
measure: Right Coronary Artery (RCA) angle of take-off from the aortic root
timeFrame: 30 days
measure: Left Anterior Descending (LAD) / Left Circumflex (LCx) bifurcation angle
timeFrame: 30 days
measure: Indexed Coronary Volume
timeFrame: 30 days
Secondary outcomes:
measure: Extent of Coronary Atherosclerosis
timeFrame: 30 days
measure: Severity of Coronary Atherosclerosis assessed by using Leiden CTA risk score
timeFrame: 30 days
measure: Severity of Coronary Atherosclerosis assessed by using Gensini score
timeFrame: 30 days
measure: Complexity of Coronary Artery Disease [CT-SYNTAX score]
timeFrame: 30 days
measure: Frequency of occurrence of high-risk plaques
timeFrame: 30 days
measure: Plaque burden assessment [Modified Duke CAD Index for coronary CTA]
timeFrame: 30 days
Other outcomes:
Locations:
city: Thessaloníki
country: Greece
facility: AHEPA University Hospital, Department of Cardiology
Study officials:
affiliation: AHEPA-Department of Cardiology
name: Haralambos Karvounis, MD, PhD
role: STUDY_CHAIR
affiliation: AHEPA-Department of Radiology
name: Konstantinos Kouskouras, MD, PhD
role: PRINCIPAL_INVESTIGATOR
affiliation: AHEPA-Department of Cardiology
name: Georgios Rampidis, MD, MSc
role: PRINCIPAL_INVESTIGATOR
affiliation: AHEPA-Department of Radiology
name: Vasileios Rafailidis, MD, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Antoniadis AP, Giannopoulos AA, Wentzel JJ, Joner M, Giannoglou GD, Virmani R, Chatzizisis YS. Impact of local flow haemodynamics on atherosclerosis in coronary artery bifurcations. EuroIntervention. 2015;11 Suppl V:V18-22. doi: 10.4244/EIJV11SVA4.
citation: Rampidis GP, Benetos G, Benz DC, Giannopoulos AA, Buechel RR. A guide for Gensini Score calculation. Atherosclerosis. 2019 Aug;287:181-183. doi: 10.1016/j.atherosclerosis.2019.05.012. Epub 2019 May 10. No abstract available.
citation: Ferencik M. About the twists and turns: Relationship of coronary artery geometry and atherosclerosis. J Cardiovasc Comput Tomogr. 2018 May-Jun;12(3):261-262. doi: 10.1016/j.jcct.2018.04.004. Epub 2018 Apr 24. No abstract available.
citation: Toutouzas K, Benetos G, Karanasos A, Chatzizisis YS, Giannopoulos AA, Tousoulis D. Vulnerable plaque imaging: updates on new pathobiological mechanisms. Eur Heart J. 2015 Dec 1;36(45):3147-54. doi: 10.1093/eurheartj/ehv508. Epub 2015 Sep 28.
citation: Giannopoulos AA, Benz DC, Grani C, Buechel RR. Imaging the event-prone coronary artery plaque. J Nucl Cardiol. 2019 Feb;26(1):141-153. doi: 10.1007/s12350-017-0982-0. Epub 2017 Jul 6.
citation: Kolossvary M, Szilveszter B, Merkely B, Maurovich-Horvat P. Plaque imaging with CT-a comprehensive review on coronary CT angiography based risk assessment. Cardiovasc Diagn Ther. 2017 Oct;7(5):489-506. doi: 10.21037/cdt.2016.11.06.
citation: Pflederer T, Ludwig J, Ropers D, Daniel WG, Achenbach S. Measurement of coronary artery bifurcation angles by multidetector computed tomography. Invest Radiol. 2006 Nov;41(11):793-8. doi: 10.1097/01.rli.0000239318.88270.9f.
citation: Benetos G, Buechel RR, Goncalves M, Benz DC, von Felten E, Rampidis GP, Clerc OF, Messerli M, Giannopoulos AA, Gebhard C, Fuchs TA, Pazhenkottil AP, Kaufmann PA, Grani C. Coronary artery volume index: a novel CCTA-derived predictor for cardiovascular events. Int J Cardiovasc Imaging. 2020 Apr;36(4):713-722. doi: 10.1007/s10554-019-01750-2. Epub 2020 Jan 1.
citation: Benz DC, Benetos G, Rampidis G, von Felten E, Bakula A, Sustar A, Kudura K, Messerli M, Fuchs TA, Gebhard C, Pazhenkottil AP, Kaufmann PA, Buechel RR. Validation of deep-learning image reconstruction for coronary computed tomography angiography: Impact on noise, image quality and diagnostic accuracy. J Cardiovasc Comput Tomogr. 2020 Sep-Oct;14(5):444-451. doi: 10.1016/j.jcct.2020.01.002. Epub 2020 Jan 13.