The application and optimization of super-resolution reconstruction for isotropic out-of-plane MRI to study the musculoskeletal system

ABSTRACT

In this paper we optimised and adapted a post-processing super-resolution reconstruction (SRR) algorithm for its use in the semi-automated isotropic reconstruction of non-isotropically acquired musculoskeletal magnetic resonance image (MRI) data. The ability to produce isotropic MRI data facilitated the (1) enhanced out-of-plane image visualisation; (2) semi-automated image registration with CT data of the same anatomical site; and (3) improved image segmentation. The effectiveness of the SRR algorithm was demonstrated on several musculoskeletal scans including ex vivo tibial plateaus, in vivo knees and hands with varying levels of structural complexity and potential for motion artefact.

KEYWORDS:

• Super-resolution reconstruction
• musculoskeletal
• isotropic voxels
• MRI
• image registration

Acknowledgments

The authors acknowledge Dr. Jason Werle (for providing the tibial plateaus) and Scott Brunet (hand imaging data). Justin J. Tse holds a T. Chen Fong Postdoctoral Fellowship and Luke Garland is funded through the Alberta Innovates Summer Studentship. This project was funded by the McCaig Institute, Arthritis Society Stars Early Career Investigator Award and the Natural Science and Engineering Research Council of Canada (NSERC #RGPIN-2018-03908).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Arthritis Society [Arthritis Society Stars Early Career Investigator]; Natural Sciences and Engineering Research Council of Canada [NSERC #RGPIN-2018-03908].

Notes on contributors

Justin J. Tse

Justin Tse is a postdoctoral fellow in the Department of Radiology at the University of Calgary, Canada. He obtained his B.Sc in Microbiology and Immunology and M.Sc in Environmental Toxicology from the University of Saskatchewan. He continued his education to obtain a Ph.D in Medical Biophysics from the University of Western Ontario. He is currently interested in the application of a multi-modal imaging approach (i.e. ultrasound, magnetic resonance imaging, and computed tomography) to better understand the effects of inflammation on bone changes as they pertain to rheumatoid arthritis.

Luke Garland

Luke Garland is currently an undergraduate student at the Schulich School of Engineering, University of Calgary, Canada. He is pursuing a BSc. in Electrical Engineering with a Minor in Computer Engineering. In 2019, he was a summer student in the Manske Lab at the University of Calgary, supported by the Alberta Innovates Summer Research Studentship.

Michael T. Kuczynski

Michael Kuczynski is a PhD student in the department of Biomedical Engineering at the University of Calgary, Alberta, Canada. He obtained his BSc in Electrical Engineering at the University of Calgary in 2018. The topic of his PhD thesis is the use of dynamic computed tomography to better understand the structure-function relationship in joints affected by osteoarthritis. His research interests include image processing, joint biomechanics, and joint diseases.

Peter Salat

Peter Salat MD, FRCPC is a practicing radiologist with fellowship training in musculoskeletal and interventional radiology and is clinical assistant professor at the University of Calgary Department of Radiology. He is the current medical director of the Centre for Mobility and Joint Health at the University of Calgary and medical director of the diagnostic imaging department at the Rockyview Hospital in Calgary. Peter has diverse interests in msk imaging research.

Yves Pauchard

Yves Pauchard, PhD, is currently an Instructor in the Department of Electrical and Computer Engineering at the University of Calgary teaching programming and machine learning courses. Prior to returning to Calgary in 2016, Dr Pauchard held an Assistant Professor position at the University of Applied Sciences Winterthur, Switzerland, where he taught in the undergraduate computer science program. He is a trained electrical engineer with graduate and post-graduate training in medical imaging and analysis studying bone and musculoskeletal tissues. His research interests include imaging, image and data analysis, and computational modelling.

Sarah L. Manske

Sarah Manske, PhD, is an Assistant Professor in the Department of Radiology and McCaig Institute for Bone and Joint Health at the University of Calgary, Calgary, Canada. Her research focuses on the mechanisms that underpin bone’s response to anabolic and catabolic stimuli. Her group use multiple imaging modalities (e.g., HR-pQCT and MRI) and image processing techniques to extract highly sensitive, quantitative changes occurring in the bone, applied to diseases such as osteoarthritis and rheumatoid arthritis.