Optimization of data acquisition and analysis for fiber ball imaging

Moss, Hunter G.; McKinnon, Emilie T.; Glenn, G. Russell; Helpern, Joseph A.; Jensen, Jens Højgaard

doi:10.1016/j.neuroimage.2019.07.005

Cited by 21 publications

(64 citation statements)

References 54 publications

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“…It is plausible that the water exchange time for unmyelinated axons is substantially shorter than for myelinated axons to an extent that water within unmyelinated axons is in rapid exchange with extra‐axonal water and thus effectively merged with this compartment as far as diffusion properties are concerned. Although the observed scaling behavior of the direction‐averaged dMRI signal with b ‐value does strongly support our basic picture of it being dominated by contributions from intra‐axonal water for the large axial b ‐value used in our experiments, possible contributions from other WM components, such as glial cells, also cannot be definitively excluded, and further investigations exploring the direction‐averaged dMRI signal’s specificity to intra‐axonal water would be of value. Finally, an important caveat is that earlier work supporting the required assumptions for the TDE method has mainly been performed in healthy adult human brain at a field level of 3T.…”

Section: Discussionsupporting

confidence: 67%

“…Assumption 2 is valid provided the T 2 of myelin water, which is approximately 10 to 20 ms, is short in comparison to the echo time for the sequence, as is usually true for dMRI sequences implemented on clinical MRI systems. Assumption 3 is strongly supported by recent work on the scaling of the dMRI signal for b ‐values >~4000 s/mm 2 . There is also substantial evidence that assumption 4 holds to a reasonable approximation, at least in healthy adults, for b ‐values >4000 s/mm 2 .…”

Section: Introductionmentioning

confidence: 65%

“…The method requires the axial b ‐value, b || , to be sufficiently strong to suppress the dMRI signal from the extra‐axonal water pool. Specifically, previous studies indicate that the condition b || ≥ 4000 s/mm 2 should be satisfied . For this reason, we choose b || = 4000 s/mm 2 in our experiments because this was considered to be the smallest feasible axial diffusion weighting.…”

Section: Discussionmentioning

confidence: 99%

“…The TDE data must be acquired in a sufficiently large number of diffusion encoding directions to allow for an accurate estimate of the direction‐averaged dMRI signal. Here, we used 64 diffusion encoding directions, which was motivated by results obtained for the closely related FBI imaging technique . The diffusion encoding direction is defined, for our TDE sequence, as being aligned with the axial gradients.…”

Section: Discussionmentioning

confidence: 99%

“…The fiber orientation density function (fODF) for each WM voxel was estimated from the dMRI data with b || = 4000 s/mm 2 and

b_{⊥}

= 0 s/mm 2 by applying the FBI method . Specifically, the spherical harmonic expansion coefficients,

a_{2 l}^{m}

, of the dMRI data were used to estimate the spherical harmonic expansion coefficients,

c_{2 l}^{m}

, of the fODF from the formula (Equation ):

c_{2 l}^{m} = \frac{a_{2 l}^{m}}{2 π P_{2 l} false(0 false) g_{2 l} false(b_{false| false|} D_{a} false)} \cdot \sqrt{\frac{b_{false| false|} D_{a}}{π}},

where P 2 l ( x ) is the Legendre polynomial of degree 2 l , and (Equation ):

g_{2 l} (b_{| |} D_{a}) \equiv \frac{l! {(b_{| |} D_{a})}^{l + \frac{1}{2}}}{Γ (2 l + \frac{3}{2})}_{1} F_{1} (l + \frac{1}{2}; 2 l + \frac{3}{2}; - b_{| |} D_{a})

with 1 F 1 ( a ; b ; z ) indicating the confluent hypergeometric function of the first kind and Γ( x ) indicating the gamma function.…”

Section: Methodsmentioning

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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Section: Discussionsupporting

confidence: 67%

Section: Introductionmentioning

confidence: 65%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

“…The fiber orientation density function (fODF) for each WM voxel was estimated from the dMRI data with b || = 4000 s/mm 2 and

b_{⊥}

= 0 s/mm 2 by applying the FBI method . Specifically, the spherical harmonic expansion coefficients,

a_{2 l}^{m}

, of the dMRI data were used to estimate the spherical harmonic expansion coefficients,

c_{2 l}^{m}

, of the fODF from the formula (Equation ):

c_{2 l}^{m} = \frac{a_{2 l}^{m}}{2 π P_{2 l} false(0 false) g_{2 l} false(b_{false| false|} D_{a} false)} \cdot \sqrt{\frac{b_{false| false|} D_{a}}{π}},

where P 2 l ( x ) is the Legendre polynomial of degree 2 l , and (Equation ):

g_{2 l} (b_{| |} D_{a}) \equiv \frac{l! {(b_{| |} D_{a})}^{l + \frac{1}{2}}}{Γ (2 l + \frac{3}{2})}_{1} F_{1} (l + \frac{1}{2}; 2 l + \frac{3}{2}; - b_{| |} D_{a})

with 1 F 1 ( a ; b ; z ) indicating the confluent hypergeometric function of the first kind and Γ( x ) indicating the gamma function.…”

Section: Methodsmentioning

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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Impact of b‐value on estimates of apparent fibre density

Genc

Tax

Raven

et al. 2020

Human Brain Mapping

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Recent advances in diffusion magnetic resonance imaging (dMRI) analysis techniques have improved our understanding of fibre‐specific variations in white matter microstructure. Increasingly, studies are adopting multi‐shell dMRI acquisitions to improve the robustness of dMRI‐based inferences. However, the impact of b‐value choice on the estimation of dMRI measures such as apparent fibre density (AFD) derived from spherical deconvolution is not known. Here, we investigate the impact of b‐value sampling scheme on estimates of AFD. First, we performed simulations to assess the correspondence between AFD and simulated intra‐axonal signal fraction across multiple b‐value sampling schemes. We then studied the impact of sampling scheme on the relationship between AFD and age in a developmental population (n = 78) aged 8–18 (mean = 12.4, SD = 2.9 years) using hierarchical clustering and whole brain fixel‐based analyses. Multi‐shell dMRI data were collected at 3.0T using ultra‐strong gradients (300 mT/m), using 6 diffusion‐weighted shells ranging from b = 0 to 6,000 s/mm2. Simulations revealed that the correspondence between estimated AFD and simulated intra‐axonal signal fraction was improved with high b‐value shells due to increased suppression of the extra‐axonal signal. These results were supported by in vivo data, as sensitivity to developmental age‐relationships was improved with increasing b‐value (b = 6,000 s/mm2, median R2 = .34; b = 4,000 s/mm2, median R2 = .29; b = 2,400 s/mm2, median R2 = .21; b = 1,200 s/mm2, median R2 = .17) in a tract‐specific fashion. Overall, estimates of AFD and age‐related microstructural development were better characterised at high diffusion‐weightings due to improved correspondence with intra‐axonal properties.

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Fiber ball white matter modeling in focal epilepsy

Bryant

McKinnon

Taylor

et al. 2021

Human Brain Mapping

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Multicompartment diffusion magnetic resonance imaging (MRI) approaches are increasingly being applied to estimate intra-axonal and extra-axonal diffusion characteristics in the human brain. Fiber ball imaging (FBI) and its extension fiber ball white matter modeling (FBWM) are such recently described multicompartment approaches.However, these particular approaches have yet to be applied in clinical cohorts. The modeling of several diffusion parameters with interpretable biological meaning may offer the development of new, noninvasive biomarkers of pharmacoresistance in epilepsy. In the present study, we used FBI and FBWM to evaluate intra-axonal and extra-axonal diffusion properties of white matter tracts in patients with longstanding focal epilepsy. FBI/FBWM diffusion parameters were calculated along the length of 50 white matter tract bundles and statistically compared between patients with refractory epilepsy, nonrefractory epilepsy and controls. We report that patients with chronic epilepsy had a widespread distribution of extra-axonal diffusivity relative to controls, particularly in circumscribed regions along white matter tracts projecting to cerebral cortex from thalamic, striatal, brainstem, and peduncular regions. Patients with refractory epilepsy had significantly greater markers of extra-axonal diffusivity compared to those with nonrefractory epilepsy. The extra-axonal diffusivity alterations in patients with epilepsy observed in the present study could be markers of neuroinflammatory processes or a reflection of reduced axonal density, both of which have been histologically demonstrated in focal epilepsy. FBI is a clinically feasible MRI approach that provides the basis for more interpretive conclusions about the microstructural environment of the brain and may represent a unique biomarker of pharmacoresistance in epilepsy.

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Optimization of data acquisition and analysis for fiber ball imaging

Cited by 21 publications

References 54 publications

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

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

Impact of b‐value on estimates of apparent fibre density

Fiber ball white matter modeling in focal epilepsy

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