Mapping mean axon diameter and intra-axonal volume fraction may have significant clinical potential because nerve conduction velocity is directly dependent on axon diameter, and several neurodegenerative diseases affect axons of specific sizes and alter axon counts. Diffusion-weighted MRI methods based on the pulsed gradient spin echo (PGSE) sequence have been reported to be able to assess axon diameter and volume fraction non-invasively. However, due to the relatively long diffusion times used, e.g. > 20 ms, the sensitivity to small axons (diameter < 2 µm) is low, and the derived mean axon diameter has been reported to be overestimated. In the current study, oscillating gradient spin echo (OGSE) diffusion sequences with variable frequency gradients were used to assess rat spinal white matter tracts with relatively short effective diffusion times (1 – 5 ms). In contrast to previous PGSE-based methods, the extra-axonal diffusion cannot be modeled as hindered (Gaussian) diffusion when short diffusion times are used. Appropriate frequency-dependent rates are therefore incorporated into our analysis and validated by histology-based computer simulation of water diffusion. OGSE data were analyzed to derive mean axon diameters and intra-axonal volume fractions of rat spinal white matter tracts (mean axon diameter ~ 1.27 – 5.54 µm). The estimated values were in good agreement with histology, including the small axon diameters (< 2.5 µm). This study establishes a framework for quantification of nerve morphology using the OGSE method with high sensitivity to small axons.

The myelin water fraction (MWF) has been used as a quantitative measure of the amount of myelin present in tissue. However, recent work has suggested that inter-compartmental exchange of water between myelin and non-myelin compartments may cause the MWF to underestimate the true myelin content of tissue. In this work, multi-exponential T2 experiments were performed in-vivo within the rat spinal cord, and a wide variation of the MWF (10–35%) was measured within four rat spinal cord tracts with similar myelin content. A numerical simulation based upon segmented histology images was used to quantitatively account for T2 variations between tracts. The model predicts that a difference in exchange between the four spinal cord tracts, mediated by a difference in the average axon radius and myelin thickness, is sufficient to account for the variation in MWF measured in-vivo.

Purpose To implement and validate a previously proposed ultra-short echo time (UTE) method for measuring collagen-bound and pore water concentrations in bone based on their T2 differences. Methods Clinically compatible UTE image sequences for quantitative T2-based bound and pore water imaging in bone were implemented and validated on a 3T human scanner and a 4.7T small bore system. Bound and pore water images were generating using T2-selective adiabatic pulses. In both cases, the magnetization preparation was integrated into a 3D UTE acquisition, with 16 radial spokes acquired per preparation. Images were acquired from human cadaveric femoral mid-shafts, from which isolated bone samples were subsequently extracted for non-imaging analysis using T2 spectroscopic measurements. Results A strong correlation was found between imaging-derived concentrations of bound and pore water and those determined from the isolated bone samples. Conclusion These studies demonstrate the translation of previously developed approaches for distinguishing bound and pore water from human cortical bone using practical human MRI constraints of gradient performance and RF power deposition.

Purpose Several studies have shown strong correlations between myelin content and T1 within the brain, and have even suggested that T1 can be used to estimate myelin content. However, other micro-anatomical features such as compartment size are known to affect longitudinal relaxation rates, similar to compartment size effects in porous media. Methods T1 measurements were compared with measured or otherwise published axon size measurements in white matter tracts of the rat spinal cord, rat brain, and human brain. Results In both ex vivo and in vivo studies, correlations were present between the relaxation rate 1/T1 and axon size across regions of rat spinal cord with nearly equal myelin content. Conclusions While myelination is likely the dominant determinant of T1 in white matter, variations in white matter microstructure, independent of myelin volume fraction, may also be reflected in T1 differences between regions or subjects.

The apparent diffusion coefficient (ADC), as measured by diffusion-weighted MRI, has proven useful in the diagnosis and evaluation of ischemic stroke. The ADC of tissue water is reduced by 30-50% following ischemia and provides excellent contrast between normal and affected tissue. Despite its clinical utility, there is no consensus on the biophysical mechanism underlying the reduction in ADC. In this work, a numerical simulation of water diffusion is used to predict the effects of cellular tissue properties on experimentally measured ADC. The model indicates that the biophysical mechanisms responsible for changes in ADC postischemia depend upon the time over which diffusion is measured. At short diffusion times, the ADC is dependent upon the intrinsic intracellular diffusivity, while at longer, clinically relevant diffusion times, the ADC is highly dependent upon the cell volume fraction. The model also predicts that at clinically relevant diffusion times, the 30-50% drop in ADC after ischemia can be accounted for by cell swelling alone when intracellular T 2 is allowed to be shorter than extracellular The idea to use NMR to measure diffusion was introduced by Torrey in 1956 (1). The clinical utility of diffusionweighted MRI (DWMRI) was realized in the early 1990s in the evaluation of ischemic stroke. Within minutes of onset, DWMRI exhibits hyperintensity in regions of the brain affected by acute stroke, while T 2 -weighted images remain unaffected. The apparent diffusion coefficient (ADC), a quantitative measure of the diffusion of water in tissue, decreases 30 -50% in ischemic regions of the brain (2,3). While these results have had significant clinical utility, there remains no consensus on the biophysical mechanisms causing the drop in ADC. Several mechanisms have been proposed, including increases in the intracellular volume fraction (IVF) (3), increased tortuosity of extracellular spaces (4), decreased membrane permeability (P mem ) (4), and decreases in the diffusion of water in the intracellular space (5,6). Because a large number of tissue parameters have been hypothesized to affect the ADC, mathematical models of water diffusion are useful to assess the role of each parameter on the ADC.In free diffusion, the signal from DWMRI decays exponentially with increasing b-value, and is characterized by the intrinsic diffusion coefficient, D. However, the diffusion of water in tissue is not free: water interacts with lipid membranes, macromolecules, and other cellular and extracellular constituents, causing the signal decay to deviate from the monoexponential decay observed in free diffusion (7,8). The ADC lumps all of these interactions into a single "apparent" diffusion coefficient, which is calculated by fitting the DWMRI signal to an exponential decay over a specific range of b-values, typically between 0 and 1000 sec/mm 2 . Therefore, the ADC provides little indication of the specific biophysical mechanisms contributing the DWMRI signal decay. Other analyses of diffusion fit the non-monoexponential signa...

Purpose Multi‐exponential relaxometry is a powerful tool for characterizing tissue, but generally requires high image signal‐to‐noise ratio (SNR). This work evaluates the use of principal‐component‐analysis (PCA) denoising to mitigate these SNR demands and improve the precision of relaxometry measures. MethodsPCA denoising was evaluated using both simulated and experimental MRI data. Bi‐exponential transverse relaxation signals were simulated for a wide range of acquisition and sample parameters, and experimental data were acquired from three excised and fixed mouse brains. In both cases, standard relaxometry analysis was performed on both original and denoised image data, and resulting estimated signal parameters were compared. ResultsDenoising reduced the root‐mean‐square‐error of parameters estimated from multi‐exponential relaxometry by factors of ≈3×, for typical acquisition and sample parameters. Denoised images and subsequent parameter maps showed little or no signs of spatial artifact or loss of resolution. Conclusion Experimental studies and simulations demonstrate that PCA denoising of MRI relaxometry data is an effective method of improving parameter precision without sacrificing image resolution. This simple yet important processing step thus paves the way for broader applicability of multi‐exponential MRI relaxometry.

Purpose To investigate inter-compartmental water exchange in two model myelinated tissues ex vivo using relaxation exchange spectroscopy (REXSY). Methods Building upon a previously developed theoretical framework, a three-compartment (myelin, intra-axonal, and extra-axonal water) model of the inversion-recovery prepared REXSY signal was applied in excised rat optic nerve and frog sciatic nerve samples to estimate the water residence time constants in myelin (τmyelin). Results In the rat optic nerve samples, τmyelin = 138 ± 15 ms (mean ± standard deviation) was estimated. In sciatic nerve, which possesses thicker myelin sheaths than optic nerve, a much longer τmyelin = 2046 ± 140 ms was observed. Conclusions Consistent with previous studies in rat spinal cord, the extrapolation of exchange rates in optic nerve to in vivo conditions indicates that τmyelin < 100 ms. This suggests that there is a significant effect of inter-compartmental water exchange on the transverse relaxation of water protons in white matter. The much longer τmyelin values in sciatic nerve supports the postulate that the inter-compartmental water exchange rate is mediated by myelin thickness. Together, these findings point to the potential for MRI methods to probe variations in myelin thickness in white matter.

While myelinated axons present an important barrier to water diffusion, many models used to interpret DWI signal neglect other potential influences of myelin. In this work, Monte Carlo simulations were used to test the sensitivity of DWI results to the diffusive properties of water within myelin. Within these simulations, the apparent diffusion coefficient (Dapp) varied slowly over several orders of magnitude of the coefficient of myelin water diffusion (Dm), but exhibited important differences compared to Dapp values simulated that neglect Dm (=0). Compared to Dapp, the apparent diffusion kurtosis (Kapp) was generally more sensitive to Dm. Simulations also tested the sensitivity of Dapp and Kapp to the amount of myelin present. Unique variations in Dapp and Kapp caused by differences in the myelin volume fraction were diminished when myelin water diffusion was included. Also, expected trends in Dapp and Kapp with experimental echo time were reduced or inverted when accounting for myelin water diffusion, and these reduced/inverted trends were seen experimentally in ex vivo rat brain DWI experiments. In general, myelin water has the potential to subtly influence DWI results and bias models of DWI that neglect these components of white matter.