Multidimensional diffusion MRI with spectrally modulated gradients reveals unprecedented microstructural detail

Research output: Contribution to journalArticle

Abstract

Characterization of porous media is essential in a wide range of biomedical and industrial applications. Microstructural features can be probed non-invasively by diffusion magnetic resonance imaging (dMRI). However, diffusion encoding in conventional dMRI may yield similar signatures for very different microstructures, which represents a significant limitation for disentangling individual microstructural features in heterogeneous materials. To solve this problem, we propose an augmented multidimensional diffusion encoding (MDE) framework, which unlocks a novel encoding dimension to assess time-dependent diffusion specific to structures with different microscopic anisotropies. Our approach relies on spectral analysis of complex but experimentally efficient MDE waveforms. Two independent contrasts to differentiate features such as cell shape and size can be generated directly by signal subtraction from only three types of measurements. Analytical calculations and simulations support our experimental observations. Proof-of-concept experiments were applied on samples with known and distinctly different microstructures. We further demonstrate substantially different contrasts in different tissue types of a post mortem brain. Our simultaneous assessment of restriction size and shape may be instrumental in studies of a wide range of porous materials, enable new insights into the microstructure of biological tissues or be of great value in diagnostics.

Details

Authors
Organisations
External organisations
  • Hvidovre Hospital
  • Technical University of Denmark
  • University of Manchester
  • Bioxydyn Ltd
  • Random Walk Imaging AB
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Radiology, Nuclear Medicine and Medical Imaging
Original languageEnglish
Article number9026
JournalScientific Reports
Volume9
Issue number1
Publication statusPublished - 2019 Jun 21
Publication categoryResearch
Peer-reviewedYes