Quantitative Perfusion MRI

Techniques, Applications and Practical Considerations

1st Edition, Volume 11 - August 22, 2023
Editors: Hai-Ling Margaret Cheng, ‪Gustav J. Strijkers‬
Language: English
Paperback ISBN:
9 7 8 - 0 - 3 2 3 - 9 5 2 0 9 - 5
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 9 5 2 1 0 - 1

Quantitative Perfusion MRI: Techniques, Applications, and Practical Considerations, Volume 11 clearly and carefully explains the basic theory and MRI techniques for quantifyi… Read more

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Quantitative Perfusion MRI: Techniques, Applications, and Practical Considerations, Volume 11 clearly and carefully explains the basic theory and MRI techniques for quantifying perfusion non-invasively in deep tissue, covering all aspects of perfusion imaging, from acquisition requirements to selection of contrast agents and appropriate pharmacokinetic models and for reliable quantification in different diseases and tissue types. Specifically, this book enables the reader to understand what microvascular functional parameters can be measured with perfusion MRI, learn the basic techniques to measure perfusion in different organs, apply the appropriate perfusion MRI technique to the organ of interest, and much more.

This complete reference on quantitative perfusion MRI is highly suitable for both early and experienced researchers, graduate students and clinicians wishing to understand how quantitative perfusion MRI can apply to their application area of interest.

Cover
Title page
Table of Contents
Series Page
Copyright
List of contributors
Preface
Section 1: Basic principles
Chapter 1: Basic principles for imaging blood flow
Abstract
1.1: Introduction
1.2: Theory
1.3: MRI versus other modalities for imaging perfusion
1.4: Clinical relevance
1.5: Summary
References
Chapter 2: Dynamic contrast-enhanced MRI
Abstract
2.1: Introduction
2.2: Image acquisition
2.3: Quantitative DCE analysis
2.4: Summary
References
Chapter 3: Dynamic susceptibility contrast MRI
Abstract
3.1: Introduction
3.2: Theory
3.3: Acquisition of DSC-MRI data
3.4: Perfusion parameters
3.5: DSC-MRI data postprocessing possibilities
3.6: Advanced biomarkers in DSC-MRI
3.7: Applications
3.8: Summary
References
Further reading
Chapter 4: Arterial spin labeling MRI
Abstract
4.1: Introduction
4.2: Acquisition
4.3: Analysis
4.4: Clinical applications
4.5: Advanced techniques and future directions
4.6: Conclusion
References
Recommended further reading
Chapter 5: Vasoreactivity MRI
Abstract
5.1: Introduction
5.2: Theory
5.3: Applications
5.4: Future directions
5.5: Summary
References
Further reading
Section 2: Technical considerations
Chapter 6: MR contrast agents for perfusion imaging
Abstract
6.1: Introduction
6.2: Classification of MR contrast agents for perfusion imaging
6.3: Clinical applications
6.4: Safety issues
6.5: Learning and knowledge outcomes
Disclaimer
References
Chapter 7: Protocol requirements for quantitation accuracy
Abstract
7.1: Introduction
7.2: Dynamic acquisition: The ideal sequence
7.3: Dynamic acquisition: Practical solutions
7.4: Additional considerations for accurate quantification
7.5: Future directions
7.6: Summary
References
Chapter 8: Arterial input function: A friend or a foe?
Abstract
8.1: Introduction
8.2: Pitfalls and possibilities
8.3: Summary
References
Chapter 9: Motion compensation strategies
Abstract
9.1: Introduction
9.2: Acquisition strategies
9.3: Types of motion and related artifacts
9.4: Potential strategies to mitigate motion-related artifacts
9.5: New approaches and future directions
9.6: Summary
References
Chapter 10: Practical considerations for water exchange modeling in DCE-MRI
Abstract
10.1: Introduction
10.2: Modeling water exchange in DCE-MRI
10.3: Signal modeling in the presence of water exchange
10.4: Simulation of water exchange effects in DCE-MRI
10.5: Model parameter estimation
10.6: Methods of enhancing sensitivity to water exchange
10.7: Conclusions
References
Chapter 11: Acceleration methods for perfusion imaging
Abstract
11.1: Introduction
11.2: General MRI acquisition and reconstruction
11.3: Accelerated MRI through reconstruction of undersampled data
11.4: Accelerated MRI through simultaneous multi-slice imaging
11.5: Accelerated MRI through reduced signal averages
11.6: Selection of acceleration methods for perfusion MRI
11.7: Conclusion
Acknowledgment
References
Further reading
Chapter 12: Artificial intelligence: The next frontier of perfusion imaging?
Abstract
12.1: Introduction
12.2: Background
12.3: AI in perfusion MRI
12.4: Summary
References
Section 3: Applications
Chapter 13: Perfusion MRI in the brain: Insights from sickle cell disease and the healthy brain
Abstract
13.1: Overview
13.2: Sickle cell disease
13.3: Case reports
13.4: Challenges and solutions
13.5: Learning and knowledge outcomes
References
Chapter 14: Perfusion MRI in the heart: Arterial spin labeling
Abstract
14.1: Overview
14.2: Imaging protocol
14.3: Data analysis protocol
14.4: Applications
14.5: Safety considerations
14.6: Challenges and solutions
14.7: Learning and knowledge outcomes
References
Chapter 15: Perfusion MRI in the heart: First-pass perfusion
Abstract
15.1: Overview
15.2: Imaging protocol
15.3: Data analysis protocol
15.4: Applications
15.5: Safety considerations
15.6: Challenges and solutions
15.7: Learning and knowledge outcomes
Declarations
References
Chapter 16: Perfusion MRI of the lungs
Abstract
16.1: Overview
16.2: Technical advances in lung MRI
16.3: Exogenous contrast-enhanced approaches
16.4: Endogenous contrast approaches
16.5: Other approaches
16.6: Clinical applications
16.7: Challenges and solutions
16.8: Learning and knowledge outcomes
Acknowledgments
References
Chapter 17: Applications of quantitative perfusion MRI in the liver
Abstract
17.1: Overview
17.2: Imaging protocol
17.3: Data analysis protocol
17.4: Challenges and solutions
17.5: Case studies of applications
17.6: Learning and knowledge outcomes
References
Chapter 18: Perfusion MRI in the kidneys: Arterial spin labeling
Abstract
18.1: Overview
18.2: Imaging protocol
18.3: Data analysis protocol
18.4: Case studies of applications
18.5: Safety considerations
18.6: Challenges and solutions
18.7: Learning and knowledge outcomes
References
Chapter 19: DCE-MRI in the kidneys
Abstract
19.1: Overview
19.2: Imaging protocol
19.3: Data analysis protocol
19.4: Case studies of applications
19.5: Safety considerations
19.6: Challenges and solutions
19.7: Learning and knowledge outcomes
References
Chapter 20: MRI of skeletal muscle perfusion
Abstract
20.1: Overview
20.2: Imaging protocol
20.3: Data analysis protocol
20.4: Case studies of applications
20.5: Safety considerations
20.6: Challenges and solutions
20.7: Learning and knowledge outcomes
Acknowledgments
References
Index

Hai-Ling Margaret Cheng

Prof. H.-L.M. Cheng is Full Professor at the University of Toronto in the Institute of Biomedical Engineering and the Edward S. Rogers Sr. Department of Electrical & Computer Engineering. She earned her B.Sc. and M.Sc. in Electrical & Computer Engineering at the University of Calgary and worked in industry on real-time synthetic aperture radar surveillance before completing her Ph.D. in Medical Biophysics at the University of Toronto on her thesis “MRI monitoring of focused ultrasound thermal ablation”. Her research in quantitative MRI methodologies expanded over the next decade at the Hospital for Sick Children, where she developed protocols for clinical research in parallel to forging the first MRI applications in tissue engineering and designing novel MRI contrast agents. In 2014, she joined the Faculty of Engineering at the University of Toronto and the Ted Rogers Centre for Heart Research. Her current research is focused on new contrast agent design and rapid, quantitative MRI methodologies for physiological, cellular, and molecular imaging, with an emphasis on early detection of heart failure and MRI-guided tissue regenerative therapies.

Affiliations and expertise

Full Professor, Dean’s Spark Professor, Institute of Biomedical Engineering, The Edward S. Rogers Sr. Department of Electrical & Computer Engineering, University of Toronto, Toronto, Ontario, Canada.

‪S

‪Gustav J. Strijkers‬

Prof. dr. G.J. (Gustav) Strijkers is Full Professor (Preclinical and Translational MRI) at the University of Amsterdam (UvA) and Adjunct Professor at Mount Sinai, New York. He earned his PhD at the Eindhoven University of Technology (TUE) with the title Magnetic Nanostructures and was a post-doctoral fellow at John Hopkins University, Baltimore. He served as assistant professor and associate professor at TUE and at UvA. He was a reviewer for several international journals and funding agencies and a member of scientific associations. Currently, his group uses a translational approach for the development of novel MRI sequences for improved diagnostics of disease and therapy monitoring. Novel preclinical protocols for high field MRI are initially developed in mouse and rat models. The most promising protocols are then translated for human clinical MRI. He established research programs on the development of comprehensive accelerated MRI protocols which provide valuable readouts in preclinical studies on the development and treatment of cardiovascular diseases, the application of traditional and novel nano particulate contrast agents, the improvement of imaging speed in MRI by the use of parallel imaging and novel mathematical imaging acceleration techniques, the use of multi-contrast MRI for the comprehensive and real-time evaluation of cancer therapy, and the development of diffusion-MRI to assess heart and skeletal muscle architecture and structural integrity in health and disease.

Affiliations and expertise

Full Professor (Preclinical and Translational MRI), University of Amsterdam (UvA) and Adjunct Professor, Mount Sinai, NY, USA

Life Sciences

Physical Sciences & Engineering

Social Sciences & Humanities

Health