A practical evaluation of measures derived from compressed sensing diffusion spectrum imaging

Hamsanandini Radhakrishnan, Chenying Zhao, Valerie J. Sydnor, Erica B. Baller, Philip A. Cook, Damien A. Fair, Barry Giesbrecht, Bart Larsen, Kristin Murtha, David R. Roalf, Sage Rush-Goebel, Russell T. Shinohara, Haochang Shou, M. Dylan Tisdall, Jean M. Vettel, Scott T. Grafton, Matthew Cieslak, Theodore D. Satterthwaite

Research output: Contribution to journalArticlepeer-review


Diffusion Spectrum Imaging (DSI) using dense Cartesian sampling of q-space has been shown to provide important advantages for modeling complex white matter architecture. However, its adoption has been limited by the lengthy acquisition time required. Sparser sampling of q-space combined with compressed sensing (CS) reconstruction techniques has been proposed as a way to reduce the scan time of DSI acquisitions. However prior studies have mainly evaluated CS-DSI in post-mortem or non-human data. At present, the capacity for CS-DSI to provide accurate and reliable measures of white matter anatomy and microstructure in the living human brain remains unclear. We evaluated the accuracy and inter-scan reliability of 6 different CS-DSI schemes that provided up to 80% reductions in scan time compared to a full DSI scheme. We capitalized on a dataset of 26 participants who were scanned over eight independent sessions using a full DSI scheme. From this full DSI scheme, we subsampled images to create a range of CS-DSI images. This allowed us to compare the accuracy and inter-scan reliability of derived measures of white matter structure (bundle segmentation, voxel-wise scalar maps) produced by the CS-DSI and the full DSI schemes. We found that CS-DSI estimates of both bundle segmentations and voxel-wise scalars were nearly as accurate and reliable as those generated by the full DSI scheme. Moreover, we found that the accuracy and reliability of CS-DSI was higher in white matter bundles that were more reliably segmented by the full DSI scheme. As a final step, we replicated the accuracy of CS-DSI in a prospectively acquired dataset (n = 20, scanned once). Together, these results illustrate the utility of CS-DSI for reliably delineating in vivo white matter architecture in a fraction of the scan time, underscoring its promise for both clinical and research applications.

Original languageEnglish (US)
Article numbere26580
JournalHuman Brain Mapping
Issue number5
StatePublished - Apr 2024

Bibliographical note

Publisher Copyright:
© 2024 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.


  • MRI acquisition
  • compressed sensing
  • diffusion-weighted imaging
  • white matter

PubMed: MeSH publication types

  • Journal Article


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