Cardiac MR

Cardiac MR: From Theory to Practice

Ismail, Tevfik F. (King’s College London; Guy's and St Thomas’ NHS Foundation Trust)
Strugnell, Wendy (Mater Hospital Brisbane)
Coletti, C. (TU Delft ImPhys/Medical Imaging)
Bozic, M. (TU Delft ImPhys/Medical Imaging; University Heidelberg)
Weingärtner, S.D. (TU Delft ImPhys/Computational Imaging; TU Delft ImPhys/Medical Imaging)
Hammernik, Kerstin (Technische Universität München; Imperial College London)
Correia, Teresa (King’s College London; Centre of Marine Sciences)
Küstner, Thomas (T€ubingen University Hospital)

2022

Cardiovascular disease (CVD) is the leading single cause of morbidity and mortality, causing over 17. 9 million deaths worldwide per year with associated costs of over $800 billion. Improving prevention, diagnosis, and treatment of CVD is therefore a global priority. Cardiovascular magnetic resonance (CMR) has emerged as a clinically important technique for the assessment of cardiovascular anatomy, function, perfusion, and viability. However, diversity and complexity of imaging, reconstruction and analysis methods pose some limitations to the widespread use of CMR. Especially in view of recent developments in the field of machine learning that provide novel solutions to address existing problems, it is necessary to bridge the gap between the clinical and scientific communities. This review covers five essential aspects of CMR to provide a comprehensive overview ranging from CVDs to CMR pulse sequence design, acquisition protocols, motion handling, image reconstruction and quantitative analysis of the obtained data. (1) The basic MR physics of CMR is introduced. Basic pulse sequence building blocks that are commonly used in CMR imaging are presented. Sequences containing these building blocks are formed for parametric mapping and functional imaging techniques. Commonly perceived artifacts and potential countermeasures are discussed for these methods. (2) CMR methods for identifying CVDs are illustrated. Basic anatomy and functional processes are described to understand the cardiac pathologies and how they can be captured by CMR imaging. (3) The planning and conduct of a complete CMR exam which is targeted for the respective pathology is shown. Building blocks are illustrated to create an efficient and patient-centered workflow. Further strategies to cope with challenging patients are discussed. (4) Imaging acceleration and reconstruction techniques are presented that enable acquisition of spatial, temporal, and parametric dynamics of the cardiac cycle. The handling of respiratory and cardiac motion strategies as well as their integration into the reconstruction processes is showcased. (5) Recent advances on deep learning-based reconstructions for this purpose are summarized. Furthermore, an overview of novel deep learning image segmentation and analysis methods is provided with a focus on automatic, fast and reliable extraction of biomarkers and parameters of clinical relevance.

cardiovascular MR
CMR protocol
deep learning
image processing
image reconstruction
imaging acceleration
quantitative imaging
sequence design

http://resolver.tudelft.nl/uuid:abee2cd5-7b8e-4662-841b-24a3132c4e9b

https://doi.org/10.3389/fcvm.2022.826283

2297-055X

Frontiers in Cardiovasculair Medicine, 9

Institutional Repository

review

© 2022 Tevfik F. Ismail, Wendy Strugnell, C. Coletti, M. Bozic, S.D. Weingärtner, Kerstin Hammernik, Teresa Correia, Thomas Küstner