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, and Tony Stöcker
In: Frontiers in Neuroscience (2018), 12(650)
 

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.

Images

Bibtex

@ARTICLE{Tobisch:FN2018,
    author = {Tobisch, Alexandra and Stirnberg, R{\"u}diger and Harms, Robbert L. and Schultz, Thomas and Roebroeck,
              Alard and Breteler, Monique M. B. and St{\"o}cker, Tony},
     pages = {650},
     title = {Compressed Sensing Diffusion Spectrum Imaging for Accelerated Diffusion Microstructure MRI in
              Long-Term Population Imaging},
   journal = {Frontiers in Neuroscience},
    volume = {12},
      year = {2018},
  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.}
}