University of Groningen
Quantitative cardiac dual source CT; from morphology to function
Assen, van, Marly
DOI:
10.33612/diss.93012859
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Publication date: 2019
Link to publication in University of Groningen/UMCG research database
Citation for published version (APA):
Assen, van, M. (2019). Quantitative cardiac dual source CT; from morphology to function. Rijksuniversiteit Groningen. https://doi.org/10.33612/diss.93012859
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Quantitative Cardiac Dual Source CT;
from Morphology to Function
Quantitative Cardiac Dual Source CT; from Morphology to Function
PhD thesis with a summary in Dutch, University of Groningen, The Netherlands ISBN 978-94-034-1814-8
ISBN (ebook) 978-94-034-1815-5
Printed by Ipskamp Printing, Enschede Lay out Douwe Oppewal
Cover Image courtesy of M. Eid and M.H. Albrecht © M. van Assen 2019
The copyright of the articles that have been published or accepted for publication has been transferred to the publishers of the respective journals. This copy of the thesis has been supplied on condition that anyone who consults it is understood to recognize that no part of this thesis and no information derived from it may be published, reproduced, or transmitted in any form by any means without the author’s prior consent, or when appropriate, from the aforementioned publishers.
Financial support by the Dutch Heart Foundation for the publication of this thesis is gratefully acknowledged. Additional financial support for the publication of this thesis was generously provided by:
Quantitative Cardiac Dual Source CT;
from Morphology to Function
PhD thesis
to obtain the degree of PhD at the University of Groningen
on the authority of the
Rector Magnificus Prof. dr. C. Wijmenga and in accordance with
the decision by the College of Deans. This thesis will be defended in public on Wednesday 4 September 2019 at 11.00 hours
by
Marly van Assen born on 18 October 1989
Supervisors
Prof. M. Oudkerk Prof. R. Vliegenthart
Co-supervisor
Prof. U.J. Schoepf
Assessment Committee
Prof. G.J. Verkerke Prof. H.J. Lamb Prof. T. Leiner
6
TABLE OF CONTENTS
1. Introduction 8
Part I Coronary plaque and vessel wall analysis 20
2. Machine Learning in Cardiac CT: 22
Basic Concepts and Contemporary Data
3. Deep Learning-based Automated CT Coronary 50 Artery Calcium Scoring
4. Automated Plaque Analysis for the Prognostication 64 of Major Adverse Cardiac Events
Part II Coronary flow analysis 92
5. CT-FFR profiles in patients without coronary artery disease; 94 the effect of location and luminal area
6. Relationship between coronary CT angiography-derived 110 fractional flow reserve and dynamic CT myocardial
perfusion imaging in patients with coronary artery disease
7. Prognostic Value of CT Myocardial Perfusion Imaging and 128 CT-derived Fractional Flow Reserve for Major Adverse
Cardiac Events in Patients with Coronary Artery Disease
Part III Myocardial perfusion analysis 150
8. Dynamic Myocardial CT Perfusion Imaging 152 9. Low CT temporal sampling rates result in a substantial 184
7 10. Intermodel Disagreement of Myocardial Blood Flow 202
Estimation from Dynamic CT Perfusion Imaging
11. The Feasibility, Tolerability, Safety, and Accuracy of 220 Low-Radiation Dynamic CT Myocardial Perfusion Imaging with Regadenoson Compared to Single-Photon Emission CT
Part IV Functional Myocardial fibrosis analysis 242
12. Iodine Quantification Based on Rest / Stress Perfusion 244 Dual Energy CT to Differentiate Ischemic, Infarcted
and Normal Myocardium
13. Feasibility of Extracellular Volume Quantification using 264 Dual-energy CT
Part V General discussion and summary 278
14. General discussion 280 English summary 298 Nederlandse samenvatting 304 Part VI Appendices 312 Acknowledgements 314 Author Affiliations 320 Publications 330 Curriculum Vitae 340
