Temporal Diffusion Ratio (TDR) for imaging restricted diffusion: Optimisation and pre-clinical demonstration
•Temporal Diffusion Ratio (TDR) maps areas of restricted diffusion using two different gradient waveforms.•The two optimised gradient waveforms have: long δ + low G and short δ + high G.•If data is noisy, calculating TDR using HARDI acqisition subsets increases accuracy.•First demonstration of TDR i...
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Published in | NeuroImage (Orlando, Fla.) Vol. 269; p. 119930 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
01.04.2023
Elsevier Limited Elsevier |
Subjects | |
Online Access | Get full text |
ISSN | 1053-8119 1095-9572 1095-9572 |
DOI | 10.1016/j.neuroimage.2023.119930 |
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Summary: | •Temporal Diffusion Ratio (TDR) maps areas of restricted diffusion using two different gradient waveforms.•The two optimised gradient waveforms have: long δ + low G and short δ + high G.•If data is noisy, calculating TDR using HARDI acqisition subsets increases accuracy.•First demonstration of TDR in pre-clinical imaging.•TDR values are strongly correlated with axon diameter in rat spinal cord.
Temporal Diffusion Ratio (TDR) is a recently proposed dMRI technique (Dell'Acqua et al., proc. ISMRM 2019) which provides contrast between areas with restricted diffusion and areas either without restricted diffusion or with length scales too small for characterisation. Hence, it has a potential for informing on pore sizes, in particular the presence of large axon diameters or other cellular structures. TDR employs the signal from two dMRI acquisitions obtained with the same, large, b-value but with different diffusion gradient waveforms. TDR is advantageous as it employs standard acquisition sequences, does not make any assumptions on the underlying tissue structure and does not require any model fitting, avoiding issues related to model degeneracy. This work for the first time introduces and optimises the TDR method in simulation for a range of different tissues and scanner constraints and validates it in a pre-clinical demonstration. We consider both substrates containing cylinders and spherical structures, representing cell soma in tissue. Our results show that contrasting an acquisition with short gradient duration, short diffusion time and high gradient strength with an acquisition with long gradient duration, long diffusion time and low gradient strength, maximises the TDR contrast for a wide range of pore configurations. Additionally, in the presence of Rician noise, computing TDR from a subset (50% or fewer) of the acquired diffusion gradients rather than the entire shell as proposed originally further improves the contrast. In the last part of the work the results are demonstrated experimentally on rat spinal cord. In line with simulations, the experimental data shows that optimised TDR improves the contrast compared to non-optimised TDR. Furthermore, we find a strong correlation between TDR and histology measurements of axon diameter. In conclusion, we find that TDR has great potential and is a very promising alternative (or potentially complement) to model-based approaches for informing on pore sizes and restricted diffusion in general. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Shared first author. Shared senior author. |
ISSN: | 1053-8119 1095-9572 1095-9572 |
DOI: | 10.1016/j.neuroimage.2023.119930 |