Resolving degeneracy in diffusion MRI biophysical model parameter estimation using double diffusion encoding

Coelho, Santiago; Pozo, José M.; Jespersen, Sune Nørhøj; Jones, Derek K.; Frangi, Alejandro F.

doi:10.1002/mrm.27714

Cited by 56 publications

(53 citation statements)

References 58 publications

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“…We note that more advanced DW-MRI acquisition schemes such as B-tensor encoding (64) parcellation of the brain cyto-architecture (Figure 9 and 10). As shown in Figure 10 (18,19), while recent works using DDE showed that this acquisition scheme can help disentangling different sources of DW-MRI signal that can be linked to different features of the underpinning tissue microstructure (69)(70)(71)(72). Future works will focus on harnessing the orthogonal information offered by these advanced acquisition schemes in order to maximize the sensitivity and specificity of the measured DW-MRI signal to the soma contribution.…”

Section: Discussionmentioning

confidence: 99%

SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI

et al. 2020

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This work introduces a compartment-based model for apparent cell body (namely soma) and neurite density imaging (SANDI) using non-invasive diffusion-weighted MRI (DW-MRI). The existing conjecture in brain microstructure imaging trough DW-MRI presents water diffusion in white (WM) and grey (GM) matter as restricted diffusion in neurites, modelled by infinite cylinders of null radius embedded in the hindered extra-neurite water. The extra-neurite pool in WM corresponds to water in the extra-axonal space, but in GM it combines water in the extra-cellular space with water in soma. While several studies showed that this microstructure model successfully describe DW-MRI data in WM and GM at b3 ms/m 2 , it has been also shown to fail in GM at high b values (b>>3 ms/m 2 ). Here we hypothesize that the unmodelled soma compartment may be responsible for this failure and propose SANDI as a new model of brain microstructure where soma is explicitly included. We assess the effects of size and density of soma on the direction-averaged DW-MRI signal at high b values and the regime of validity of the model using numerical simulations and comparison with experimental data from mouse (bmax = 40 ms/m 2 ) and human (bmax = 10 ms/m 2 ) brain. We show that SANDI defines new contrasts representing new complementary information on the brain cyto-and myelo-architecture. Indeed, we show for the first-time maps from 25 healthy human subjects of MR soma and neurite signal fractions, that remarkably mirror contrasts of histological images of brain cyto-and myelo-architecture. Although still under validation, SANDI might provide new insight into tissue architecture by introducing a new set of biomarkers of potential great value for biomedical applications and pure neuroscience.

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Section: Discussionmentioning

confidence: 99%

SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI

et al. 2020

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“…The fact that in the present study, DDE MRI seems to provide more detailed information than the SDE MRI experiment may originate from the relatively high q‐values used in both experiments ( q larger than 2500 cm −1 ). Note that very recently it was demonstrated that not very high q‐values are required to show that DDE MRI can reduce some of the bias of SDE MRI . Since the diffusion weighting in both MRI experiments are very similar (practically identical) it is less likely to be the origin of the observed subtle differences between the SDE and DDE MRI results.…”

Section: Discussionmentioning

confidence: 99%

“…However, the diameter distributions extracted from these experiments show different profiles for each ROI, allowing a differentiation between them. Note that very recently, Grussu et al showed by simulations that most of the diffusivity variations take place in diffusion times below 20–25 ms in both low and high axonal density regions. For diffusion times of above these values the diffusivities appear to change relatively little.…”

Section: Discussionmentioning

confidence: 99%

“…Note that very recently it was demonstrated that not very high q-values are required to show that DDE MRI can reduce some of the bias of SDE MRI. 86 Since the diffusion weighting in both MRI experiments are very similar (practically identical) it is less likely to be the origin of the observed subtle differences between the SDE and DDE MRI results.…”

Section: Sde and Angular Dde Mri In The Spinal Cordmentioning

confidence: 95%

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Single‐ and double‐Diffusion encoding MRI for studying ex vivo apparent axon diameter distribution in spinal cord white matter

et al. 2019

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Mapping average axon diameter (AAD) and axon diameter distribution (ADD) in neuronal tissues non‐invasively is a challenging task that may have a tremendous effect on our understanding of the normal and diseased central nervous system (CNS). Water diffusion is used to probe microstructure in neuronal tissues, however, the different water populations and barriers that are present in these tissues turn this into a complex task. Therefore, it is not surprising that recently we have witnessed a burst in the development of new approaches and models that attempt to obtain, non‐invasively, detailed microstructural information in the CNS. In this work, we aim at challenging and comparing the microstructural information obtained from single diffusion encoding (SDE) with double diffusion encoding (DDE) MRI. We first applied SDE and DDE MR spectroscopy (MRS) on microcapillary phantoms and then applied SDE and DDE MRI on an ex vivo porcine spinal cord (SC), using similar experimental conditions. The obtained diffusion MRI data were fitted by the same theoretical model, assuming that the signal in every voxel can be approximated as the superposition of a Gaussian‐diffusing component and a series of restricted components having infinite cylindrical geometries. The diffusion MRI results were then compared with histological findings. We found a good agreement between the fittings and the experimental data in white matter (WM) voxels of the SC in both diffusion MRI methods. The microstructural information and apparent AADs extracted from SDE MRI were found to be similar or somewhat larger than those extracted from DDE MRI especially when the diffusion time was set to 40 ms. The apparent ADDs extracted from SDE and DDE MRI show reasonable agreement but somewhat weaker correspondence was observed between the diffusion MRI results and histology. The apparent subtle differences between the microstructural information obtained from SDE and DDE MRI are briefly discussed.

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“…There is still a lack of direct diffusion metric comparisons with the same biophysical meaning (Jelescu et al, 2015), (Jelescu et al, 2016), (Coelho et al, 2019) using large subject cohorts. The intraaxonal water fraction which can be treated as an indirect axon density, has a unique representation of the WM organisation and, consequently, might play an important role as a powerful biomarker for further brain studies based on UKB: brain age gap evaluation (Smith et al, 2019), (Kaufmann et al, 2019), genome-wide association studies (Elliott et al, 2018), understanding of mental health disorders (Neilson et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Feasibility of axon density metrics for brain asymmetry evaluation in the UK Biobank subsample

Maximov

Westlye

2020

Preprint

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Standard diffusion MRI model with intra-and extra-axonal water pools offers a set of microstructural parameters describing brain white matter architecture. However, a non-linearity of the general model and diffusion data contamination by noise and imaging artefacts make estimation of diffusion metrics challenging. In order to develop reproducible and reliable diffusion approaches and to avoid computational model degeneracy, one needs to devise additional theoretical assumptions allowing a stable numerical implementation. As a result, it is possible to estimate intra-axonal water fraction (AWF) representing one of the important structural parameters. AWF can be treated as an indirect measure of axon density and has a strong potential as useful clinical biomarker. A few diffusion approaches such as white matter tract integrity, neurite orientation dispersion and density imaging, and spherical mean technique, allow one to evaluate AWF in the frame of their theoretical assumptions. In the present study, we considered the compatibility of axon density metrics obtained from different diffusion models and the influence of the diffusion metric on a brain asymmetry estimation in UK Biobank sample consisting of 182 subjects. We found AWF derived from a spherical mean technique is the most statistically representative measure. As a result, we revealed that brain asymmetry indecies derived from intra-axonal water fraction weakly decrease along the lifespan, reducing the left-right hemisphere difference within increased age.

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Resolving degeneracy in diffusion MRI biophysical model parameter estimation using double diffusion encoding

Cited by 56 publications

References 58 publications

SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI

SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI

Single‐ and double‐Diffusion encoding MRI for studying ex vivo apparent axon diameter distribution in spinal cord white matter

Feasibility of axon density metrics for brain asymmetry evaluation in the UK Biobank subsample

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