Mapping mean axon diameter and axonal volume fraction by MRI using temporal diffusion spectroscopy

Xu, Junzhong; Li, Hua; Harkins, Kevin D.; Jiang, Xiaoyu; Xie, Jingping; Kang, Hakmook; Does, Mark D.; Gore, John C.

doi:10.1016/j.neuroimage.2014.09.006

Cited by 113 publications

(145 citation statements)

References 72 publications

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“…Oscillating Diffusion Encoding (ODE) experiments [14,54,55] have been widely used in SDE to enhance contrast in neural tissue, likely since they access shorter diffusion time than could be reached using pulsed-gradient-spin-echo methods [56]. Additionally, ODE has been shown to be highly beneficial for mapping axonal sizes in rat spinal cord [57,58] as well as for contrasting malignancy in tissues [59,60]. More recently, the DDE framework was extended toward accommodation of oscillating gradients, termed Double Oscillating Diffusion Encoding (DODE, Figure 1A), first in theory [61], and more recently, in experiment [62].…”

Section: Introductionmentioning

confidence: 99%

Axon Diameters and Myelin Content Modulate Microscopic Fractional Anisotropy at Short Diffusion Times in Fixed Rat Spinal Cord

Shemesh

2018

Front. Phys.

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Mapping tissue microstructure accurately and noninvasively is one of the frontiers of biomedical imaging. Diffusion Magnetic Resonance Imaging (MRI) is at the forefront of such efforts, as it is capable of reporting on microscopic structures orders of magnitude smaller than the voxel size by probing restricted diffusion. Double Diffusion Encoding (DDE) and Double Oscillating Diffusion Encoding (DODE) in particular, are highly promising for their ability to report on microscopic fractional anisotropy (µFA), a measure of the pore anisotropy in its own eigenframe, irrespective of orientation distribution. However, the underlying correlates of µFA have insofar not been studied. Here, we extract µFA from DDE and DODE measurements at ultrahigh magnetic field of 16.4T with the goal of probing fixed rat spinal cord microstructure. We further endeavor to correlate µFA with Myelin Water Fraction (MWF) derived from multiexponential T 2 relaxometry, as well as with literature-based spatially varying axon diameter. In addition, a simple new method is presented for extracting unbiased µFA from three measurements at different b-values. Our findings reveal strong anticorrelations between µFA (derived from DODE) and axon diameter in the distinct spinal cord tracts; a moderate correlation was also observed between µFA derived from DODE and MWF. These findings suggest that axonal membranes strongly modulate µFA, which-owing to its robustness toward orientation dispersion effects-reflects axon diameter much better than its typical FA counterpart. µFA varied when measured via oscillating or blocked gradients, suggesting selective probing of different parallel path lengths and providing insight into how those modulate µFA metrics. Our findings thus shed light into the underlying microstructural correlates of µFA and are promising for future interpretations of this metric in health and disease.

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Section: Introductionmentioning

confidence: 99%

Axon Diameters and Myelin Content Modulate Microscopic Fractional Anisotropy at Short Diffusion Times in Fixed Rat Spinal Cord

Shemesh

2018

Front. Phys.

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“…The complete list of TDD studies and models used to characterize tissue structure based on this geometry are detailed in another section of the manuscript. In addition to the unrealistic case of infinite impermeable membranes already described by Tanner and Stejskal [41], similar expressions were derived for diffusion inside spherical shells [42] and infinite cylinders [43]. The former, in order to represent cellular nuclei and cytoplasm, adds two extra degrees of freedom to a problem already prone to overfitting [15].…”

Section: Diffusion Inside Impermeable Spheresmentioning

confidence: 89%

“…This model assumes that the ECS diffusion varies linearly with frequency f OGSE in the range 50-150 Hz. This assumption was motivated by (i) the empirical linear behavior of the overall ADC (intra-and extracellular) measured in the healthy mouse brain [34] and (ii) simulations in extra-axonal space derived from histology samples [43]. Unfortunately, this would only be valid of a twodimensional problem (d = 2 in Equation 3) and the correct formula for the ECS diffusion around spheres at long times is given by Equation (5) instead.…”

Section: The Impulsed Modelmentioning

confidence: 99%

Time-Dependent Diffusion MRI in Cancer: Tissue Modeling and Applications

Reynaud

2017

Front. Phys.

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In diffusion weighted imaging (DWI), the apparent diffusion coefficient (ADC) has been recognized as a useful and sensitive surrogate for cell density, paving the way for non-invasive tumor staging, and characterization of treatment efficacy in cancer. However, microstructural parameters, such as cell size, density and/or compartmental diffusivities affect diffusion in various fashions, making of conventional DWI a sensitive but non-specific probe into changes happening at cellular level. Alternatively, tissue complexity can be probed and quantified using the time dependence of diffusion metrics, sometimes also referred to as temporal diffusion spectroscopy when only using oscillating diffusion gradients. Time-dependent diffusion (TDD) is emerging as a strong candidate for specific and non-invasive tumor characterization. Despite the lack of a general analytical solution for all diffusion times/frequencies, TDD can be probed in various regimes where systems simplify in order to extract relevant information about tissue microstructure. The fundamentals of TDD are first reviewed (a) in the short time regime, disentangling structural and diffusive tissue properties, and (b) near the tortuosity limit, assuming weakly heterogeneous media near infinitely long diffusion times. Focusing on cell bodies (as opposed to neuronal tracts), a simple but realistic model for intracellular diffusion can offer precious insight on diffusion inside biological systems, at all times. Based on this approach, the main three geometrical models implemented so far (IMPULSED, POMACE, VERDICT) are reviewed. Their suitability to quantify cell size, intra-and extracellular spaces (ICS and ECS) and diffusivities are assessed. The proper modeling of tissue membrane permeability-hardly a newcomer in the field, but lacking applications-and its impact on microstructural estimates are also considered. After discussing general issues with tissue modeling and microstructural parameter estimation (i.e., fitting), potential solutions are detailed. The in vivo applications of this new, non-invasive, specific approach in cancer are reviewed, ranging from the characterization of gliomas in rodent brains and observation of time-dependence in breast tissue lesions and prostate cancer, to the recent preclinical evaluation of new treatments efficacy. It is expected that clinical applications of TDD will strongly benefit the community in terms of non-invasive cancer screening.

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“…Oscillating gradients and extensions [48][49][50][51] have been used in several research studies [27,28,32,35,38,[52][53][54][55][56][57][58][59][60][61][62][63][64][65], among them applications to human brains in vivo [66]. Comparing oscillating gradients to pulsed gradients, the advantage of the oscillating gradients is that the obtainable b-value is higher allowing the assessment of shorter times.…”

Section: Discussionmentioning

confidence: 99%

On the Vanishing of the t-term in the Short-Time Expansion of the Diffusion Coefficient for Oscillating Gradients in Diffusion NMR

et al. 2017

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Nuclear magnetic resonance (NMR) diffusion measurements can be used to probe porous structures or biological tissues by means of the random motion of water molecules. The short-time expansion of the diffusion coefficient in powers of t 1/2 , where t is the diffusion time related to the duration of the diffusion-weighting magnetic field gradient profile, is universally connected to structural parameters of the boundaries restricting the diffusive motion. The t 1/2 -term is proportional to the surface to volume ratio. The t-term is related to permeability and curvature. The short time expansion can be measured with two approaches in NMR-based diffusion experiments: First, by the use of diffusion encodings of short total duration and, second, by application of oscillating gradients of long total duration. For oscillating gradients, the inverse of the oscillation frequency becomes the relevant time scale. The purpose of this manuscript is to show that the oscillating gradient approach is blind to the t-term. On the one hand, this prevents fitting of permeability and curvature measures from this term. On the other hand, the t-term does not bias the determination of the t 1/2 -term in experiments.

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Mapping mean axon diameter and axonal volume fraction by MRI using temporal diffusion spectroscopy

Cited by 113 publications

References 72 publications

Axon Diameters and Myelin Content Modulate Microscopic Fractional Anisotropy at Short Diffusion Times in Fixed Rat Spinal Cord

Axon Diameters and Myelin Content Modulate Microscopic Fractional Anisotropy at Short Diffusion Times in Fixed Rat Spinal Cord

Time-Dependent Diffusion MRI in Cancer: Tissue Modeling and Applications

On the Vanishing of the t-term in the Short-Time Expansion of the Diffusion Coefficient for Oscillating Gradients in Diffusion NMR

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