Modeling white matter microstructure with fiber ball imaging

McKinnon, Emilie T.; Helpern, Joseph A.; Jensen, Jens Højgaard

doi:10.1016/j.neuroimage.2018.04.025

Cited by 47 publications

(95 citation statements)

References 49 publications

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“…to monopolar data with b‐values of 0 s/mm 2 and 6000 s/mm 2 and TE ranging from 90 ms to 150 ms. The assumed values for D a were 1.0, 1.5, 2.0, and 2.5 µm 2 /ms, which are representative of estimates obtained from microstructural modeling …”

Section: Methodsmentioning

confidence: 85%

Measuring intra‐axonal T₂ in white matter with direction‐averaged diffusion MRI

McKinnon

Jensen

2018

Magnetic Resonance in Med

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Purpose To demonstrate how the T2 relaxation time of intra‐axonal water (T2a) in white matter can be measured with direction‐averaged diffusion MRI. Methods For b‐values larger than about 4000 s/mm2, the direction‐averaged diffusion MRI signal from white matter is dominated by the contribution from water within axons, which enables T2a to be estimated by acquiring data for multiple TE values and fitting a mono‐exponential decay curve. If given a value of the intra‐axonal diffusivity, an extension of the method allows the extra‐axonal relaxation time (T2e) to be calculated also. This approach was applied to estimate T2a in white matter for 3 healthy subjects at 3 T, as well as T2e for a selected set of assumed intra‐axonal diffusivities. Results The estimated T2a values ranged from about 50 ms to 110 ms, with considerable variation among white matter regions. For white matter tracts with primarily collinear fibers, T2a was found to depend on the angle of the tract relative to the main magnetic field, which is consistent with T2a being affected by magnetic field inhomogeneities arising from spatial differences in magnetic susceptibility. The T2e values were significantly smaller than the T2a values across white matter regions for several plausible choices of the intra‐axonal diffusivity. Conclusion The relaxation time for intra‐axonal water in white matter can be determined in a straightforward manner by measuring the direction‐averaged diffusion MRI signal with a large b‐value for multiple TEs. In healthy brain, T2a is greater than T2e and varies considerably with anatomical region.

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Section: Methodsmentioning

confidence: 85%

Measuring intra‐axonal T₂ in white matter with direction‐averaged diffusion MRI

McKinnon

Jensen

2018

Magnetic Resonance in Med

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“…The direction‐averaged TDE data (i.e.,

{\bar{S}}_{2}

) are utilized in Equation , along with direction‐averaged data acquired with identical imaging parameters other than

b_{⊥}

being set to 0 (i.e.,

{\bar{S}}_{1}

), to estimate the intra‐axonal diffusivity. An advantage of our method, in contrast to alternative SDE techniques, is the simplicity with which the intra‐axonal diffusivity is obtained. In fact, with the TDE approach, D a is the easiest parameter to determine rather than, as other studies have found, one of the most difficult .…”

Section: Discussionmentioning

confidence: 99%

“…To find the intra‐axonal diffusion tensor, D a , we use the fact that a standard FBI analysis of the same multidirection data obtained using the TDE sequence with

b_{⊥} = 0

is sufficient to estimate D a / D a . Given that D a is known, the full D a follows immediately.…”

Section: Discussionmentioning

confidence: 99%

“…Only spherical harmonic coefficients of even degree were needed because of the antipodal symmetry of the dMRI signal . The diffusion tensor for the intra‐axonal space, D a , was then obtained from Equation :

{boldD}_{a} = \frac{D_{a}}{c_{0}^{0} \sqrt{30}} (\begin{matrix} \frac{\sqrt{30}}{3} c_{0}^{0} - \frac{\sqrt{6}}{3} c_{2}^{0} + c_{2}^{2} + c_{2}^{- 2} & i c_{2}^{2} - i c_{2}^{- 2} & - c_{2}^{1} + c_{2}^{- 1} \\ i c_{2}^{2} - i c_{2}^{- 2} & \frac{\sqrt{30}}{3} c_{0}^{0} - \frac{\sqrt{6}}{3} c_{2}^{0} - c_{2}^{2} - c_{2}^{- 2} & - i c_{2}^{1} - i c_{2}^{- 1} \\ - c_{2}^{1} + c_{2}^{- 1} & - i c_{2}^{1} - i c_{2}^{- 1} & \frac{\sqrt{30}}{3} c_{0}^{0} + \frac{2 \sqrt{6}}{3} c_{2}^{0} \end{matrix}) .

…”

Section: Methodsmentioning

confidence: 99%

“…In WM, one such parameter, intrinsic intra‐axonal diffusivity ( D a ), has proven especially challenging to measure . This is because D a estimates are sensitive to modeling assumptions and tend to be only loosely constrained by the data, although some recently proposed approaches seem to be more promising …”

Section: Introductionmentioning

confidence: 99%

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Triple diffusion encoding MRI predicts intra‐axonal and extra‐axonal diffusion tensors in white matter

Ramanna

Moss

McKinnon

et al. 2019

Magnetic Resonance in Med

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Purpose To demonstrate how triple diffusion encoding (TDE) MRI can be applied to separately estimate the intra‐axonal and extra‐axonal diffusion tensors in white matter (WM). Methods Using a TDE pulse sequence with an axially symmetric b‐matrix, diffusion MRI data were acquired at 3T for 3 healthy adults with an axial b‐value of 4000 s/mm2, a radial b‐value of 307 s/mm2, and 64 diffusion encoding directions. This acquisition was then repeated with the radial b‐value set to 0. A previously proposed theory was applied to these data in order to estimate the intra‐axonal diffusivity and axonal water fraction for each WM voxel. Conventional single diffusion encoding data were also obtained with b‐values of 1000 and 2000 s/mm2, which provided additional information sufficient for determining both the intra‐axonal and extra‐axonal diffusion tensors. Results From the TDE data, the average intra‐axonal diffusivity in WM was found to be 2.24 ± 0.18 µm2/ms, and the average axonal water fraction was found to be 0.60 ± 0.11. From the 2 diffusion tensors, average WM values were estimated for several compartment‐specific diffusion parameters. In particular, the extra‐axonal mean diffusivity was 1.09 ± 0.19 µm2/ms, the intra‐axonal fractional anisotropy was 0.50 ± 0.14, and the extra‐axonal fractional anisotropy was 0.23 ± 0.13. Conclusion By using a simple TDE pulse sequence with an axially symmetric b‐matrix, the diffusion tensors for the intra‐axonal and extra‐axonal spaces can be separately estimated in adult WM. This allows one to determine compartment‐specific diffusion properties for these 2 water pools.

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Greater Diffusion Restriction in White Matter in Preclinical Alzheimer Disease

Benitez

Jensen

Thorn

et al. 2022

Annals of Neurology

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Objective: The Alzheimer's continuum is biologically defined by beta-amyloid deposition, which at the earliest stages is superimposed upon white matter degeneration in aging. However, the extent to which these co-occurring changes is characterized is relatively underexplored. The goal of this study was to use diffusional kurtosis imaging (DKI) and biophysical modeling to detect and describe amyloid-related white matter changes in preclinical Alzheimer disease. Methods: Cognitively unimpaired participants ages 45 to 85 years completed brain magnetic resonance imaging, amyloid positron emission tomography (florbetapir), neuropsychological testing, and other clinical measures at baseline in a cohort study. We tested whether beta-amyloid-negative (ABÀ) and -positive (AB+) participants differed on DKIbased conventional (ie, fractional anisotropy [FA], mean diffusivity [MD], mean kurtosis) and modeling (ie, axonal water fraction [AWF], extra-axonal radial diffusivity [D e,⊥ ]) metrics, and whether these metrics were associated with other biomarkers. Results: We found significantly greater diffusion restriction (higher FA/AWF, lower MD/D e,⊥ ) in white matter in AB+ than ABÀ (partial η 2 =0.08-0.19), more notably in the extra-axonal space within primarily late myelinating tracts. Diffusion metrics predicted amyloid status incrementally over age (area under the curve = 0.84) with modest yet selective associations, where AWF (a marker of axonal density) correlated with speed/executive functions and neurodegeneration, whereas D e,⊥ (a marker of gliosis/myelin repair) correlated with amyloid deposition and white matter hyperintensity volume. Interpretation: These results support prior evidence of a nonmonotonic change in diffusion behavior, where an early increase in diffusion restriction is hypothesized to reflect inflammation and myelin repair prior to an ensuing decrease in diffusion restriction, indicating glial and neuronal degeneration.

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Modeling white matter microstructure with fiber ball imaging

Cited by 47 publications

References 49 publications

Measuring intra‐axonal T₂ in white matter with direction‐averaged diffusion MRI

Measuring intra‐axonal T₂ in white matter with direction‐averaged diffusion MRI

Triple diffusion encoding MRI predicts intra‐axonal and extra‐axonal diffusion tensors in white matter

Greater Diffusion Restriction in White Matter in Preclinical Alzheimer Disease

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Modeling white matter microstructure with fiber ball imaging

Cited by 47 publications

References 49 publications

Measuring intra‐axonal T2 in white matter with direction‐averaged diffusion MRI

Measuring intra‐axonal T2 in white matter with direction‐averaged diffusion MRI

Triple diffusion encoding MRI predicts intra‐axonal and extra‐axonal diffusion tensors in white matter

Greater Diffusion Restriction in White Matter in Preclinical Alzheimer Disease

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Measuring intra‐axonal T₂ in white matter with direction‐averaged diffusion MRI

Measuring intra‐axonal T₂ in white matter with direction‐averaged diffusion MRI