High-resolution diffusion kurtosis imaging at 3T enabled by advanced post-processing

Mohammadi, Siawoosh; Tabelow, Karsten; Ruthotto, Lars; Feiweier, Thorsten; Polzehl, Jörg; Weiskopf, Nikolaus

doi:10.3389/fnins.2014.00427

Cited by 22 publications

(50 citation statements)

References 71 publications

(120 reference statements)

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“…(2) The first b = 0 image of each DWI dataset with reversed phase encoding was coregistered using the blip‐up data as target and the b = 0 image of the blip‐down data as source, the resulting transformation was applied to all blip‐down data. (3) DWIs were subjected to motion correction using a multitarget registration approach similar to [Mohammadi et al, ]. Note that we refrained from eddy current distortion correction, because the employed acquisition protocol included parallel imaging and the twice‐refocused spin echo scheme making these distortions negligible.…”

Section: Methodsmentioning

confidence: 99%

Four in vivo g‐ratio‐weighted imaging methods: Comparability and repeatability at the group level

Ellerbrock

Mohammadi

2017

Human Brain Mapping

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A recent method, denoted in vivo g-ratio-weighted imaging, has related the microscopic gratio, only accessible by ex vivo histology, to noninvasive MRI markers for the fiber volume fraction (FVF) and myelin volume fraction (MVF). Different MRI markers have been proposed for g-ratio weighted imaging, leaving open the question which combination of imaging markers is optimal. To address this question, the repeatability and comparability of four g-ratio methods based on different combinations of, respectively, two imaging markers for FVF (tract-fiber density, TFD, and neurite orientation dispersion and density imaging, NODDI) and two imaging markers for MVF (magnetization transfer saturation rate, MT, and, from proton density maps, macromolecular tissue volume, MTV) were tested in a scan-rescan experiment in two groups. Moreover, it was tested how the repeatability and comparability were affected by two key processing steps, namely the masking of unreliable voxels (e.g., due to partial volume effects) at the group level and the calibration value used to link MRI markers to MVF (and FVF). Our data showed that repeatability and comparability depend largely on the marker for the FVF (NODDI outperformed TFD), and that they were improved by masking. Overall, the g-ratio method based on NODDI and MT showed the highest repeatability (90%) and lowest variability between groups (3.5%). Finally, our results indicate that the calibration procedure is crucial, for example, calibration to a lower g-ratio value (g 5 0.6) than the commonly used one (g 5 0.7) can change not only repeatability and comparability but also the reported dependency on the FVF imaging marker. Hum Brain Mapp 39:24-41, 2018.V C 2017 Wiley Periodicals, Inc.

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Section: Methodsmentioning

confidence: 99%

Four in vivo g‐ratio‐weighted imaging methods: Comparability and repeatability at the group level

Ellerbrock

Mohammadi

2017

Human Brain Mapping

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“…Eq. (5), derived in Appendix B, pragmatically assumes that: only the first higher moment, diffusional kurtosis [39], contributes; the square of the apparent diffusion coefficient is uncorrelated with the apparent diffusional kurtosis; the mean diffusional kurtosis can be taken to be unity (approximately true over much healthy human brain WM [39,40,41]); and the effect of diffusional kurtosis on each individual eigenvalue is negligible. Figure 1 shows much closer agreement between the prediction of Eq.…”

Section: Theorymentioning

confidence: 99%

“…In all cases (subjects 1-3) subject motion, eddy currents, and susceptibility distortions were corrected for using the ACID toolbox [45]; for details see References [46,40,47,48]. Additionally for the multiband data (subjects 1 and 2), after the above corrections were applied, the corrected data from the two phase encoding directions were summed for use in subsequent analysis.…”

Section: Data Collection and Preprocessingmentioning

confidence: 99%

“…(6) and (3), respectively, from these DT parameters; we refer to these as the 'NODDI-DTI method' results. For subjects 1 and 2, the ACID toolbox was also used to simultaneously estimate the diffusion and kurtosis tensors [40], giving silver standard mean diffusivity estimates (MD DKI ) less biased by the effects of diffusional kurtosis [38] allowing evaluation of the validity of Eq. 5.…”

Section: Parameter Estimation and Comparisonmentioning

confidence: 99%

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NODDI-DTI: extracting neurite orientation and dispersion parameters from a diffusion tensor

Weiskopf

et al. 2016

Preprint

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NODDI-DTI is a simplification of the NODDI model that, when its underlying assumptions are met, allows extraction of biophysical parameters from standard single-shell DTI data, permitting biophysical analysis of DTI datasets.In contrast to the NODDI signal model, the NODDI-DTI signal model contains no CSF compartment, restricting its application to voxels with very low CSF partial-volume contamination. This simplification allowed derivation of simple analytical relations between parameters representing axon density, ν, and dispersion, τ , and DTI invariants (MD and FA) through moment expansion of the NODDI-DTI signal model. These relations formally allow extraction of biophysical parameters from DTI data. It should be emphasised that the NODDI-DTI model inherits the strong assumptions of the NODDI model, and so is nominally restricted to analysis of healthy brains.NODDI-DTI parameter estimates were computed by applying the proposed analytical relations to DTI parameters extracted from the first shell of data, and compared to parameters extracted by fitting the NODDI-DTI model to (i) both shells (recommended) and (ii) the first shell (as for DTI) of data in the white matter of three different in vivo diffusion datasets. NODDI-DTI parameters estimated from DTI and NODDI-DTI parameters estimated by fitting the model to the first shell of data gave similar errors compared to two-shell NODDI-DTI estimates. The NODDI-DTI method gave unphysical parameter estimates in a small percentage of voxels, reflecting voxelwise DTI estimation error or NODDI-DTI model invalidity. In the course of evaluating the NODDI-DTI model it was found that diffusional kurtosis strongly biased DTI-based MD values, and so a novel heuristic correction requiring only DTI data was derived and used to account for this bias.Our results demonstrate that NODDI-DTI is a promising model and technique to interpret restricted datasets acquired for DTI analysis with greater biophysical specificity, though its limitations must be borne in mind.

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“…Novel quantitative MRI protocols of the spinal cord and brain have the potential to measure neural changes at the microstructural level. This is because the degree of myelination, iron content and neuronal microstructure are reflected in MR relaxation times, magnetization transfer and diffusion-weighted images which can be measured at high resolution [14][15][16]. These novel quantitative MR methods include multiparametric mapping [17][18][19][20][21] and diffusion tensor imaging [22] next to volumetric measures (i.e.…”

Section: Human Spinal Cord Injury: Noninvasive Tracking Of Trauma-indmentioning

confidence: 99%

Tracking trauma-induced structural and functional changes above the level of spinal cord injury

Huber

Curt

Freund

2015

Current Opinion in Neurology

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PURPOSE OF REVIEW: This review will highlight the latest findings from neuroimaging studies that track structural and functional changes within the central nervous system at both the brain and spinal cord levels following acute human spinal cord injury (SCI). The putative, underlying biological mechanisms of structural change (e.g. degradation of neural tissue) rostral to the lesion site will be discussed in relation to animal models of SCI and their potential value in clinical studies of human SCI. RECENT FINDINGS: Recent prospective studies in human acute SCI have begun to reveal the timecourse, spatial distribution and extent of structural changes following an acute SCI and their relation to functional outcome. Adaptive changes in sensory and motor pathways above the level of the lesion have prognostic value and complement clinical readouts. SUMMARY: The introduction of sensitive neuroimaging biomarkers will be an essential step forward in the implementation of interventional trials in which proof-of-concept is currently limited to clinical readouts, but more responsive measures are required to improve the sensitivity of clinical trials. Purpose of review This review will highlight the latest findings from neuroimaging studies that track structural and functional changes within the central nervous system at both the brain and spinal cord levels following acute human spinal cord injury (SCI). The putative, underlying biological mechanisms of structural change (e.g. degradation of neural tissue) rostral to the lesion site will be discussed in relation to animal models of SCI and their potential value in clinical studies of human SCI. Recent findingsRecent prospective studies in human acute SCI have begun to reveal the time-course, spatial distribution and extent of structural changes following an acute SCI and their relation to functional outcome. Adaptive changes in sensory and motor pathways above the level of the lesion have prognostic value and complement clinical readouts. SummaryThe introduction of sensitive neuroimaging biomarkers will be an essential step forward in the implementation of interventional trials in which proof-of-concept is currently limited to clinical readouts, but more responsive measures are required to improve the sensitivity of clinical trials.

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High-resolution diffusion kurtosis imaging at 3T enabled by advanced post-processing

Cited by 22 publications

References 71 publications

Four in vivo g‐ratio‐weighted imaging methods: Comparability and repeatability at the group level

Four in vivo g‐ratio‐weighted imaging methods: Comparability and repeatability at the group level

NODDI-DTI: extracting neurite orientation and dispersion parameters from a diffusion tensor

Tracking trauma-induced structural and functional changes above the level of spinal cord injury

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