Diffusivity-limited q-space trajectory imaging

Deneb Boito*, Magnus Herberthson, Tom Dela Haije, Ida Blystad, Evren Özarslan

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Q-space trajectory imaging (QTI) allows non-invasive estimation of microstructural features of heterogeneous porous media via diffusion magnetic resonance imaging performed with generalised gradient waveforms. A recently proposed constrained estimation framework, called QTI+, improved QTI's resilience to noise and data sparsity, thus increasing the reliability of the method by enforcing relevant positivity constraints. In this work we consider expanding the set of constraints to be applied during the fitting of the QTI model. We show that the additional conditions, which introduce an upper bound on the diffusivity values, further improve the retrieved parameters on a publicly available human brain dataset as well as on data acquired from healthy volunteers using a scanner-ready protocol.

Original languageEnglish
JournalMagnetic Resonance Letters
Volume3
Issue number2
Pages (from-to)187-196
ISSN2097-0048
DOIs
Publication statusPublished - 2023

Bibliographical note

Publisher Copyright:
© 2023 The Authors

Keywords

  • Constrained
  • Diffusion
  • Diffusion MRI
  • Microscopic anisotropy
  • Microstructure
  • q-space trajectory imaging
  • QTI
  • QTI+

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