Compressed Sensing Diffusion Spectrum Imaging for Accelerated Diffusion Microstructure MRI in Long-Term Population Imaging

Alexandra Tobisch; Rüdiger Stirnberg; Robbert L Harms; Thomas Schultz; Alard Roebroeck; Monique M B Breteler; Tony Stöcker

doi:10.3389/fnins.2018.00650

Compressed Sensing Diffusion Spectrum Imaging for Accelerated Diffusion Microstructure MRI in Long-Term Population Imaging

Front Neurosci. 2018 Sep 24:12:650. doi: 10.3389/fnins.2018.00650. eCollection 2018.

Authors

Alexandra Tobisch^{1

2}, Rüdiger Stirnberg¹, Robbert L Harms³, Thomas Schultz^{2

4}, Alard Roebroeck³, Monique M B Breteler^{1

5}, Tony Stöcker^{1

6}

Affiliations

¹ German Center for Neurodegenerative Diseases, Bonn, Germany.
² Department of Computer Science, University of Bonn, Bonn, Germany.
³ Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.
⁴ Bonn-Aachen International Center for Information Technology, University of Bonn, Bonn, Germany.
⁵ Faculty of Medicine, Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn, Bonn, Germany.
⁶ Department of Physics and Astronomy, University of Bonn, Bonn, Germany.

Abstract

Mapping non-invasively the complex microstructural architecture of the living human brain, diffusion magnetic resonance imaging (dMRI) is one of the core imaging modalities in current population studies. For the application in longitudinal population imaging, the dMRI protocol should deliver reliable data with maximum potential for future analysis. With the recent introduction of novel MRI hardware, advanced dMRI acquisition strategies can be applied within reasonable scan time. In this work we conducted a pilot study based on the requirements for high resolution dMRI in a long-term and high throughput population study. The key question was: can diffusion spectrum imaging accelerated by compressed sensing theory (CS-DSI) be used as an advanced imaging protocol for microstructure dMRI in a long-term population imaging study? As a minimum requirement we expected a high level of agreement of several diffusion metrics derived from both CS-DSI and a 3-shell high angular resolution diffusion imaging (HARDI) acquisition, an established imaging strategy used in other population studies. A wide spectrum of state-of-the-art diffusion processing and analysis techniques was applied to the pilot study data including quantitative diffusion and microstructural parameter mapping, fiber orientation estimation and white matter fiber tracking. When considering diffusion weighted images up to the same maximum diffusion weighting for both protocols, group analysis across 20 subjects indicates that CS-DSI performs comparable to 3-shell HARDI in the estimation of diffusion and microstructural parameters. Further, both protocols provide similar results in the estimation of fiber orientations and for local fiber tracking. CS-DSI provides high radial resolution while maintaining high angular resolution and it is well-suited for analysis strategies that require high b-value acquisitions, such as CHARMED modeling and biomarkers from the diffusion propagator.

Keywords: compressed sensing; diffusion MRI; diffusion spectrum imaging; microstructure; multi-shell HARDI; population imaging.