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

Modeling conduction delays in the corpus callosum using MRI-measured g-ratio

Conduction of action potentials along myelinated axons is affected by their structural features, such as the axonal g-ratio, the ratio between the inner and outer diameters of the myelin sheath surrounding the axon. The effect of g-ratio variance on conduction properties has been quantitatively evaluated using single-axon models. It has recently become possible to estimate a g-ratio weighted measurement in vivo using quantitative MRI. Nevertheless, it is still unclear whether the variance in the g-ratio in the healthy human brain leads to significant differences in conduction velocity. In this work we tested whether the g-ratio MRI measurement can be used to predict conduction delays in the corpus callosum. We present a comprehensive framework in which the structural properties of fibers (i.e. length and g-ratio, measured using MRI), are incorporated in a biophysical model of axon conduction, to model conduction delays of long-range white matter fibers. We applied this framework to the corpus callosum, and found conduction delay estimates that are compatible with previously estimated values of conduction delays. We account for the variance in the velocity given the axon diameter distribution in the splenium, mid-body and genu, to further compare the fibers within the corpus callosum. Conduction delays have been suggested to increase with age. Therefore, we investigated whether there are differences in the g-ratio and the fiber length between young and old adults, and whether this leads to a difference in conduction speed and delays. We found very small differences between the predicted delays of the two groups in the motor fibers of the corpus callosum. We also found that the motor fibers of the corpus callosum have the fastest conduction estimates. Using the axon diameter distributions, we found that the occipital fibers have the slowest estimations, while the frontal and motor fiber tracts have similar estimates. Our study provides a framework for predicting conduction latencies in vivo. The framework could have major implications for future studies of white matter diseases and large range network computations. Our results highlight the need for improving additional in vivo measurements of white matter microstructure.

Effects of nongaussian diffusion on "isotropic diffusion" measurements: An ex-vivo microimaging and simulation study

Designing novel diffusion-weighted pulse sequences to probe tissue microstructure beyond the conventional Stejskal-Tanner family is currently of broad interest. One such technique, multidimensional diffusion MRI, has been recently proposed to afford model-free decomposition of diffusion signal kurtosis into terms originating from either ensemble variance of isotropic diffusivity or microscopic diffusion anisotropy. This ability rests on the assumption that diffusion can be described as a sum of multiple Gaussian compartments, but this is often not strictly fulfilled. The effects of nongaussian diffusion on single shot isotropic diffusion sequences were first considered in detail by de Swiet and Mitra in 1996. They showed theoretically that anisotropic compartments lead to anisotropic time dependence of the diffusion tensors, which causes the measured isotropic diffusivity to depend on gradient frame orientation. Here we show how such deviations from the multiple Gaussian compartments assumption conflates orientation dispersion with ensemble variance in isotropic diffusivity. Second, we consider additional contributions to the apparent variance in isotropic diffusivity arising due to intracompartmental kurtosis. These will likewise depend on gradient frame orientation. We illustrate the potential importance of these confounds with analytical expressions, numerical simulations in simple model geometries, and microimaging experiments in fixed spinal cord using isotropic diffusion encoding waveforms with 7.5 ms duration and 3000 mT/m maximum amplitude.

Towards microstructure fingerprinting: Estimation of tissue properties from a dictionary of Monte Carlo diffusion MRI simulations

Many closed-form analytical models have been proposed to relate the diffusion-weighted magnetic resonance imaging (DW-MRI) signal to microstructural features of white matter tissues. These models generally make assumptions about the tissue and the diffusion processes which often depart from the biophysical reality, limiting their reliability and interpretability in practice. Monte Carlo simulations of the random walk of water molecules are widely recognized to provide near groundtruth for DW-MRI signals. However, they have mostly been limited to the validation of simpler models rather than used for the estimation of microstructural properties. This work proposes a general framework which leverages Monte Carlo simulations for the estimation of physically interpretable microstructural parameters, both in single and in crossing fascicles of axons. Monte Carlo simulations of DW-MRI signals, or fingerprints, are pre-computed for a large collection of microstructural configurations. At every voxel, the microstructural parameters are estimated by optimizing a sparse combination of these fingerprints. Extensive synthetic experiments showed that our approach achieves accurate and robust estimates in the presence of noise and uncertainties over fixed or input parameters. In an in vivo rat model of spinal cord injury, our approach provided microstructural parameters that showed better correspondence with histology than five closed-form models of the diffusion signal: MMWMD, NODDI, DIAMOND, WMTI and MAPL. On whole-brain in vivo data from the human connectome project (HCP), our method exhibited spatial distributions of apparent axonal radius and axonal density indices in keeping with ex vivo studies. This work paves the way for microstructure fingerprinting with Monte Carlo simulations used directly at the modeling stage and not only as a validation tool.

Two-dimensional magnetization-transfer - CPMG MRI reveals tract-specific signatures in fixed rat spinal cord

Multiexponential T₂ (MET₂) Relaxometry and Magnetization Transfer (MT) are among the most promising MRI-derived techniques for white matter (WM) characterization. Both techniques are shown to have histologically correlated sensitivity to myelin, but these correlations are not fully understood. Furthermore, MET₂ and MT report on different WM features, thus they can be considered specific to different (patho)physiological states. Two-dimensional studies potentially resolving interactions, such as those commonly used in NMR, have been rarely performed in this context. Here, we investigated how off-resonance irradiation affects different MET₂ components in fixed rat spinal cord white matter at 16.4 T. These 2D MT-MET₂ experiments reveal that MT affects both short and long T₂ components in a tract-specific fashion. The spatially distinct signal modulations enhanced contrast between microstructurally-distinct spinal cord tracts. Two hypotheses to explain these findings were proposed: either selective elimination of a short T₂ component through pre-saturation combines with intercompartmental water exchange effects occurring on the irradiation timescale; or, other macromolecular species that exist within the tissue - other than myelin - such as neurofilaments, may be involved in the apparent microstructural segregation of the spinal cord (SC) from MET₂. Though further investigation is required to elucidate the underlying mechanism, this phenomenon adds a new dimension for WM characterization.

What dominates the time dependence of diffusion transverse to axons: Intra- or extra-axonal water?

Brownian motion of water molecules provides an essential length scale, the diffusion length, commensurate with cell dimensions in biological tissues. Measuring the diffusion coefficient as a function of diffusion time makes in vivo diffusion MRI uniquely sensitive to the cellular features about three orders of magnitude below imaging resolution. However, there is a longstanding debate, regarding which contribution - intra- or extra-cellular - is more relevant in the overall time-dependence of the MRI-derived diffusion metrics. Here we resolve this debate in the human brain white matter. By varying not just the diffusion time, but also the gradient pulse duration of a standard diffusion MRI sequence, we identify a functional form of the measured time-dependent diffusion coefficient transverse to white matter tracts in 10 healthy volunteers. This specific functional form is shown to originate from the extra-axonal space, and provides estimates of the fiber packing correlation length for axons in a bundle. Our results offer a metric for the outer axonal diameter, a promising candidate marker for demyelination in neurodegenerative diseases. From the methodological perspective, our analysis demonstrates how competing models, which describe different physics yet interpolate standard measurements equally well, can be distinguished based on their prediction for an independent "orthogonal" measurement.

Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI

The key component of a microstructural diffusion MRI 'super-scanner' is a dedicated high-strength gradient system that enables stronger diffusion weightings per unit time compared to conventional gradient designs. This can, in turn, drastically shorten the time needed for diffusion encoding, increase the signal-to-noise ratio, and facilitate measurements at shorter diffusion times. This review, written from the perspective of the UK National Facility for In Vivo MR Imaging of Human Tissue Microstructure, an initiative to establish a shared 300 mT/m-gradient facility amongst the microstructural imaging community, describes ten advantages of ultra-strong gradients for microstructural imaging. Specifically, we will discuss how the increase of the accessible measurement space compared to a lower-gradient systems (in terms of Δ, b-value, and TE) can accelerate developments in the areas of 1) axon diameter distribution mapping; 2) microstructural parameter estimation; 3) mapping micro-vs macroscopic anisotropy features with gradient waveforms beyond a single pair of pulsed-gradients; 4) multi-contrast experiments, e.g. diffusion-relaxometry; 5) tractography and high-resolution imaging in vivo and 6) post mortem; 7) diffusion-weighted spectroscopy of metabolites other than water; 8) tumour characterisation; 9) functional diffusion MRI; and 10) quality enhancement of images acquired on lower-gradient systems. We finally discuss practical barriers in the use of ultra-strong gradients, and provide an outlook on the next generation of 'super-scanners'.

Linking spherical mean diffusion weighted signal with intra-axonal volume fraction

Diffusion MRI has been widely used to assess brain tissue microstructure. However, the conventional diffusion tensor imaging (DTI) is inadequate for characterizing fiber direction or fiber density in voxels with crossing fibers in brain white matter. The constrained spherical deconvolution (CSD) technique has been proposed to measure the complex fiber orientation distribution (FOD) using a single high b-value (b ≥ 3000 s/mm²) to derive the intra-axonal volume fraction (V_in) from the calculated FOD. Recently, the spherical mean technique (SMT) was developed to fit V_in directly from a multi-compartment model with multi-shell b-values. Although different numbers of b-values are needed in the two techniques, both methods have been suggested to be related to the spherical mean diffusion weighted signal (S¯). The current study compared the two techniques on the same high-quality Human Connectome Project diffusion data and investigated the relation between S¯ and V_in systematically. At high b-values (b ≥ 3000 s/mm²), S¯ is linearly related to V_in, and S¯ provides similar contrast with V_in in white matter. At low b-values (b ~ 1000 s/mm²), the linear relation between S¯ and V_in is sensitive to the variations of intrinsic diffusivity. These results demonstrate that S¯ measured with the typical b-value of 1000 s/mm² is not an indicator of V_in, and previous DTI studies acquired with b = 1000 s/mm² cannot be re-analyzed to provide V_in-weighted contrast.

Diffusion tensor imaging shows mechanism-specific differences in injury pattern and progression in rat models of acute spinal cord injury

We investigate the ability of diffusion tensor imaging (DTI) to distinguish between three experimental rat models of spinal cord injury mechanism - contusion, dislocation, and distraction. Ex vivo DTI scans were performed on cord specimens that were preserved at different time points of the acute injury (3 hr, 24 hr, and 7 days post-injury) across all three injury mechanisms. White matter was classified as abnormal if their DTI metric was substantially different from regional values measured from a set of uninjured controls, thus allowing generation of binary "white matter damage maps" which categorizes each pixel in the DTI image as "normal" or "damaged". Damage classification was most robust using thresholds in the longitudinal diffusivity, which supports previous studies that show that longitudinal diffusivity is the most robust DTI metric in depicting damage in SCI. Furthermore, the spatial damage patterns from all subjects in the same group were consolidated into a "damage occurrence ratio map", which illustrates an average damage shape that characterizes the injury mechanism. Our analysis has yielded a dataset which highlights the differences in injury pattern due to the initial mode of mechanical injury. For example, contusion produced an initial injury that emanated radially outward from the central canal, with subsequent damage along the caudal corticospinal tract and rostral gracile fasciculus; dislocation injuries showed a high level of involvement in the lateral and ventral white matter which became less apparent by 7 days post-injury, and distraction injuries were found to be less focal and more distributed rostrocaudally. This work represents a first step in adopting the use of the primary injury mechanism as a clinical prognostic factor in SCI, which may help to inform the trialing of existing neuroprotective treatment candidates, the development of new therapies as well as personalize the management of SCI for the individual patient.

Minimal number of gradient directions for robust measurement of spherical mean diffusion weighted signal

PURPOSE

Determination of the minimum number of gradient directions (N_min) for robust measurement of spherical mean diffusion weighted signal (S¯).

METHODS

Computer simulations were employed to characterize the relative standard deviation (RSD) of the measured spherical mean signal as a function of the number of gradient directions (N). The effects of diffusion weighting b-value and signal-to-noise ratio (SNR) were investigated. Multi-shell high angular resolution Human Connectome Project diffusion data were analyzed to support the simulation results.

RESULTS

RSD decreases with increasing N, and the minimum number of N needed for RSD ≤ 5% is referred to as N_min. At high SNRs, N_min increases with increasing b-value to achieve sufficient sampling. Simulations showed that N_min is linearly dependent on the b-value. At low SNRs, N_min increases with increasing b-value to reduce the noise. RSD can be estimated as σS¯N, where σ = 1/SNR is the noise level. The experimental results were in good agreement with the simulation results. The spherical mean signal can be measured accurately with a subset of gradient directions.

CONCLUSION

As N_min is affected by b-value and SNR, we recommend using 10 × b / b₁ (b₁ = 1 ms/μm²) uniformly distributed gradient directions for typical human diffusion studies with SNR ~ 20 for robust spherical mean signal measurement.

Inferring diameters of spheres and cylinders using interstitial water

OBJECT

Most early methods to infer axon diameter distributions using magnetic resonance imaging (MRI) used single diffusion encoding sequences such as pulsed gradient spin echo (SE) and are thus sensitive to axons of diameters > 5 μm. We previously simulated oscillating gradient (OG) SE sequences for diffusion spectroscopy to study smaller axons including the majority constituting cortical connections. That study suggested the model of constant extra-axonal diffusion breaks down at OG accessible frequencies. In this study we present data from phantoms to test a time-varying interstitial apparent diffusion coefficient.

MATERIALS AND METHODS

Diffusion spectra were measured in four samples from water packed around beads of diameters 3, 6 and 10 μm; and 151 μm diameter tubes. Surface-to-volume ratios, and diameters were inferred.

RESULTS

The bead pore radii estimates were 0.60±0.08 μm, 0.54±0.06 μm and 1.0±0.1 μm corresponding to bead diameters ranging from 2.9±0.4 μm to 5.3±0.7 μm, 2.6±0.3 μm to 4.8±0.6 μm, and 4.9±0.7 μm to 9±1 μm. The tube surface-to-volume ratio estimate was 0.06±0.02 μm^-1 corresponding to a tube diameter of 180±70 μm.

CONCLUSION

Interstitial models with OG inferred 3-10 μm bead diameters from 0.54±0.06 μm to 1.0±0.1 μm pore radii and 151 μm tube diameters from 0.06±0.02 μm^-1 surface-to-volume ratios.

On modeling

Mapping tissue microstructure with MRI holds great promise as a noninvasive window into tissue organization at the cellular level. Having originated within the realm of diffusion NMR in the late 1970s, this field is experiencing an exponential growth in the number of publications. At the same time, model-based approaches are also increasingly incorporated into advanced MRI acquisition and reconstruction techniques. However, after about two decades of intellectual and financial investment, microstructural mapping has yet to find a single commonly accepted clinical application. Here, we suggest that slow progress in clinical translation may signify unresolved fundamental problems. We outline such problems and related practical pitfalls, as well as review strategies for developing and validating tissue microstructure models, to provoke a discussion on how to bridge the gap between our scientific aspirations and the clinical reality. We argue for recalibrating the efforts of our community toward a more systematic focus on fundamental research aimed at identifying relevant degrees of freedom affecting the measured MR signal. Such a focus is essential for realizing the truly revolutionary potential of noninvasive three-dimensional in vivo microstructural mapping.

Changes in sensorimotor-related thalamic diffusion properties and cerebrospinal fluid hydrodynamics predict gait responses to tap test in idiopathic normal-pressure hydrocephalus

OBJECTIVES

To compare diffusion tensor (DT)-derived indices from the thalamic nuclei and cerebrospinal fluid (CSF) hydrodynamic parameters for the prediction of gait responsiveness to the CSF tap test in early iNPH patients.

METHODS

In this study, 22 patients with iNPH and 16 normal controls were enrolled with the approval of an institutional review board. DT imaging and phase-contrast magnetic resonance imaging were performed in patients and controls to determine DT-related indices of the sensorimotor-related thalamic nuclei and CSF hydrodynamics. Gait performance was assessed in patients using gait scale before and after the tap test. The Mann-Whitney U test and receiver operating characteristic (ROC) curve analysis were applied to compare group differences between patients and controls and assess the predictive performance of gait responsiveness to the tap test in the patients.

RESULTS

Fractional anisotropy (FA) and axial diffusivity showed significant increases in the ventrolateral (VL) and ventroposterolateral (VPL) nuclei of the iNPH group compared with those of the control group (p < 0.05). The predictions of gait responsiveness of ventral thalamic FA alone (area under the ROC curve [AUC] < 0.8) significantly outperformed those of CSF hydrodynamics alone (AUC < 0.6). The AUC curve was elevated to 0.812 when the CSF peak systolic velocity and FA value were combined for the VPL nucleus, yielding the highest sensitivity (0.769) and specificity (0.778) to predict gait responses.

CONCLUSIONS

Combined measurements of sensorimotor-related thalamic FA and CSF hydrodynamics can provide potential biomarkers for gait response to the CSF tap test in patients with iNPH.

KEY POINTS

• Ventrolateral and ventroposterolateral thalamic FA may predict gait responsiveness to tap test. • Thalamic neuroplasticity can be assessed through DTI in idiopathic normal-pressure hydrocephalus. • Changes in the CST associated with gait control could trigger thalamic neuroplasticity. • Activities of sensorimotor-related circuits could alter in patients with gait disturbance. • Management of patients with iNPH could be more appropriate.

Diffusion tensor imaging of human Achilles tendon by stimulated echo readout-segmented EPI (ste-RS-EPI)

PURPOSE

Healing, regeneration, and remodeling of the injured Achilles tendon are associated with notable changes in tendon architecture. However, assessing Achilles microstructural properties with conventional diffusion tension imaging (DTI) remains a challenge because of very short T₂ / <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>T</mml:mi> <mml:mn>2</mml:mn> <mml:mo>*</mml:mo></mml:msubsup> </mml:mrow> </mml:math> values of the tendon. Hence, the objective of this study was to develop a novel Achilles tendon DTI protocol for a non-invasive investigation of the changes of microstructural integrity in tendinopathy.

METHODS

A novel stimulated echo readout-segmented EPI (ste-RS-EPI) DTI sequence was proposed to achieve a TE of ∼14-20 ms for typical b-values of 400-800 s/mm² on clinical 3T MRI scanners. To further boost tendon MR signal, the Achilles was positioned at the magic angle (∼55 °) with respect to the scanner B₀ field. The sensitivity of the developed protocol was evaluated in 19 healthy participants and 6 patients with clinically confirmed tendinopathy.

RESULTS

Compared to spin echo RS-EPI DTI protocol, ste-RS-EPI provided an ∼100-200% increase in Achilles MR signal. Tendinopathic Achilles demonstrated a high degree of microstructural disruption based on DTI tractography analysis, with significantly lower (P < 0.05) axial diffusivity (1.20 ± 0.19 vs. 1.39 ± 0.10 × 10^-3 mm² /s), radial diffusivity (0.72 ± 0.11 vs. 0.81 ± 0.08 × 10^-3 mm² /s), and mean diffusivity (0.87 ± 0.14 vs. 1.00 ± 0.07 × 10^-3 mm² /s), but no significant difference in fractional anisotropy (0.38 ± 0.04 vs. 0.38 ± 0.05; P = 0.86).

CONCLUSION

Achilles tendon ste-RS-EPI DTI can non-invasively detect the tendinopathy-induced changes to microstructural integrity, consistent with the disruption of collagen arrangement and increased cellularity. This study demonstrated the robustness and sensitivity of the proposed protocol in Achilles tendinopathy.

Microstructural imaging in the spinal cord and validation strategies

In vivo histology using magnetic resonance imaging (MRI) is a newly emerging research field that aims to non-invasively characterize tissue microstructure. The implications of in vivo histology are many, from discovering novel biomarkers to studying human development, to providing tools for disease diagnosis and monitoring the effects of novel treatments on tissue. This review focuses on quantitative MRI (qMRI) techniques that are used to map spinal cord microstructure. Opening with a rationale for non-invasive imaging of the spinal cord, this article continues with a brief overview of the existing MRI techniques for axon and myelin imaging, followed by the specific challenges and potential solutions for acquiring and processing such data. The final part of this review focuses on histological validation, with suggested tissue preparation, acquisition and processing protocols for large-scale microscopy.

Multi-compartmental diffusion characterization of the human cervical spinal cord in vivo using the spherical mean technique

The purpose of this work was to evaluate the feasibility and reproducibility of the spherical mean technique (SMT), a multi-compartmental diffusion model, in the spinal cord of healthy controls, and to assess its ability to improve spinal cord characterization in multiple sclerosis (MS) patients at 3 T. SMT was applied in the cervical spinal cord of eight controls and six relapsing-remitting MS patients. SMT provides an elegant framework to model the apparent axonal volume fraction vax , intrinsic diffusivity Dax , and extra-axonal transverse diffusivity Dex_perp (which is estimated as a function of vax and Dax ) without confounds related to complex fiber orientation distribution that reside in diffusion MRI modeling. SMT's reproducibility was assessed with two different scans within a month, and SMT-derived indices in healthy and MS cohorts were compared. The influence of acquisition scheme on SMT was also evaluated. SMT's vax , Dax , and Dex_perp measurements all showed high reproducibility. A decrease in vax was observed at the site of lesions and normal appearing white matter (p < 0.05), and trends towards a decreased Dax and increased Dex_perp were seen. Importantly, a twofold reduction in acquisition yielded similarly high accuracy with SMT. SMT provides a fast, reproducible, and accurate method to improve characterization of the cervical spinal cord, and may have clinical potential for MS patients.

Validation of diffusion MRI estimates of compartment size and volume fraction in a biomimetic brain phantom using a human MRI scanner with 300 mT/m maximum gradient strength

Diffusion microstructural imaging techniques have attracted great interest in the last decade due to their ability to quantify axon diameter and volume fraction in healthy and diseased human white matter. The estimates of compartment size and volume fraction continue to be debated, in part due to the lack of a gold standard for validation and quality control. In this work, we validate diffusion MRI estimates of compartment size and volume fraction using a novel textile axon ("taxon") phantom constructed from hollow polypropylene yarns with distinct intra- and extra-taxonal compartments to mimic white matter in the brain. We acquired a comprehensive set of diffusion MRI measurements in the phantom using multiple gradient directions, diffusion times and gradient strengths on a human MRI scanner equipped with maximum gradient strength (G_max) of 300 mT/m. We obtained estimates of compartment size and restricted volume fraction through a straightforward extension of the AxCaliber/ActiveAx frameworks that enables estimation of mean compartment size in fiber bundles of arbitrary orientation. The voxel-wise taxon diameter estimates of 12.2 ± 0.9 μm were close to the manufactured inner diameter of 11.8 ± 1.2 μm with G_max = 300 mT/m. The estimated restricted volume fraction demonstrated an expected decrease along the length of the fiber bundles in accordance with the known construction of the phantom. When G_max was restricted to 80 mT/m, the taxon diameter was overestimated, and the estimates for taxon diameter and packing density showed greater uncertainty compared to data with G_max = 300 mT/m. In conclusion, the compartment size and volume fraction estimates resulting from diffusion measurements on a human scanner were validated against ground truth in a phantom mimicking human white matter, providing confidence that this method can yield accurate estimates of parameters in simplified but realistic microstructural environments. Our work also demonstrates the importance of a biologically analogous phantom that can be applied to validate a variety of diffusion microstructural imaging methods in human scanners and be used for standardization of diffusion MRI protocols for neuroimaging research.

Can increased spatial resolution solve the crossing fiber problem for diffusion MRI?

It is now widely recognized that voxels with crossing fibers or complex geometrical configurations present a challenge for diffusion MRI (dMRI) reconstruction and fiber tracking, as well as microstructural modeling of brain tissues. This "crossing fiber" problem has been estimated to affect anywhere from 30% to as many as 90% of white matter voxels, and it is often assumed that increasing spatial resolution will decrease the prevalence of voxels containing multiple fiber populations. The aim of this study is to estimate the extent of the crossing fiber problem as we progressively increase the spatial resolution, with the goal of determining whether it is possible to mitigate this problem with higher resolution spatial sampling. This is accomplished using ex vivo MRI data of the macaque brain, followed by histological analysis of the same specimen to validate these measurements, as well as to extend this analysis to resolutions not yet achievable in practice with MRI. In both dMRI and histology, we find unexpected results: the prevalence of crossing fibers increases as we increase spatial resolution. The problem of crossing fibers appears to be a fundamental limitation of dMRI associated with the complexity of brain tissue, rather than a technical problem that can be overcome with advances such as higher fields and stronger gradients.

Promise and pitfalls of g-ratio estimation with MRI

The fiber g-ratio is the ratio of the inner to the outer diameter of the myelin sheath of a myelinated axon. It has a limited dynamic range in healthy white matter, as it is optimized for speed of signal conduction, cellular energetics, and spatial constraints. In vivo imaging of the g-ratio in health and disease would greatly increase our knowledge of the nervous system and our ability to diagnose, monitor, and treat disease. MRI based g-ratio imaging was first conceived in 2011, and expanded to be feasible in full brain white matter with preliminary results in 2013. This manuscript reviews the growing g-ratio imaging literature and speculates on future applications. It details the methodology for imaging the g-ratio with MRI, and describes the known pitfalls and challenges in doing so.

In vivo imaging of cancer cell size and cellularity using temporal diffusion spectroscopy

PURPOSE

A temporal diffusion MRI spectroscopy based approach has been developed to quantify cancer cell size and density in vivo.

METHODS

A novel imaging microstructural parameters using limited spectrally edited diffusion (IMPULSED) method selects a specific limited diffusion spectral window for an accurate quantification of cell sizes ranging from 10 to 20 μm in common solid tumors. In practice, it is achieved by a combination of a single long diffusion time pulsed gradient spin echo (PGSE) and three low-frequency oscillating gradient spin echo (OGSE) acquisitions. To validate our approach, hematoxylin and eosin staining and immunostaining of cell membranes, in concert with whole slide imaging, were used to visualize nuclei and cell boundaries, and hence, enabled accurate estimates of cell size and cellularity.

RESULTS

Based on a two compartment model (incorporating intra- and extracellular spaces), accurate estimates of cell sizes were obtained in vivo for three types of human colon cancers. The IMPULSED-derived apparent cellularities showed a stronger correlation (r = 0.81; P < 0.0001) with histology-derived cellularities than conventional ADCs (r = -0.69; P < 0.03).

CONCLUSION

The IMPULSED approach samples a specific region of temporal diffusion spectra with enhanced sensitivity to length scales of 10-20 μm, and enables measurements of cell sizes and cellularities in solid tumors in vivo. Magn Reson Med 78:156-164, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Resolution limit of cylinder diameter estimation by diffusion MRI: The impact of gradient waveform and orientation dispersion

Diffusion MRI has been proposed as a non-invasive technique for axonal diameter mapping. However, accurate estimation of small diameters requires strong gradients, which is a challenge for the transition of the technique from preclinical to clinical MRI scanners, since these have weaker gradients. In this work, we develop a framework to estimate the lower bound for accurate diameter estimation, which we refer to as the resolution limit. We analyse only the contribution from the intra-axonal space and assume that axons can be represented by impermeable cylinders. To address the growing interest in using techniques for diffusion encoding that go beyond the conventional single diffusion encoding (SDE) sequence, we present a generalised analysis capable of predicting the resolution limit regardless of the gradient waveform. Using this framework, waveforms were optimised to minimise the resolution limit. The results show that, for parallel cylinders, the SDE experiment is optimal in terms of yielding the lowest possible resolution limit. In the presence of orientation dispersion, diffusion encoding sequences with square-wave oscillating gradients were optimal. The resolution limit for standard clinical MRI scanners (maximum gradient strength 60-80 mT/m) was found to be between 4 and 8 μm, depending on the noise levels and the level of orientation dispersion. For scanners with a maximum gradient strength of 300 mT/m, the limit was reduced to between 2 and 5 μm.

Impact of transcytolemmal water exchange on estimates of tissue microstructural properties derived from diffusion MRI

PURPOSE

To investigate the influence of transcytolemmal water exchange on estimates of tissue microstructural parameters derived from diffusion MRI using conventional PGSE and IMPULSED methods.

METHODS

Computer simulations were performed to incorporate a broad range of intracellular water life times τin (50-∞ ms), cell diameters d (5-15 μm), and intrinsic diffusion coefficient Din (0.6-2 μm2 /ms) for different values of signal-to-noise ratio (SNR) (10 to 50). For experiments, murine erythroleukemia (MEL) cancer cells were cultured and treated with saponin to selectively change cell membrane permeability. All fitted microstructural parameters from simulations and experiments in vitro were compared with ground-truth values.

RESULTS

Simulations showed that, for both PGSE and IMPULSED methods, cell diameter d can be reliably fit with sufficient SNR (≥ 50), whereas intracellular volume fraction fin is intrinsically underestimated due to transcytolemmal water exchange. Din can be reliably fit only with sufficient SNR and using the IMPULSED method with short diffusion times. These results were confirmed with those obtained in the cell culture experiments in vitro.

CONCLUSION

For the sequences and models considered in this study, transcytolemmal water exchange has minor effects on the fittings of d and Din with physiologically relevant membrane permeabilities if the SNR is sufficient (> 50), but fin is intrinsically underestimated. Magn Reson Med 77:2239-2249, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Application and evaluation of NODDI in the cervical spinal cord of multiple sclerosis patients

INTRODUCTION

There is a need to develop imaging methods sensitive to axonal injury in multiple sclerosis (MS), given the prominent impact of axonal pathology on disability and outcome. Advanced multi-compartmental diffusion models offer novel indices sensitive to white matter microstructure. One such model, neurite orientation dispersion and density imaging (NODDI), is sensitive to neurite morphology, providing indices of apparent volume fractions of axons (vin), isotropic water (viso) and the dispersion of fibers about a central axis (orientation dispersion index, ODI). NODDI has yet to be studied for its sensitivity to spinal cord pathology. Here, we investigate the feasibility and utility of NODDI in the cervical spinal cord of MS patients.

METHODS

NODDI was applied in the cervical spinal cord in a cohort of 8 controls and 6 MS patients. Statistical analyses were performed to test the sensitivity of NODDI-derived indices to pathology in MS (both lesion and normal appearing white matter NAWM). Diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) analysis were also performed to compare with NODDI.

RESULTS

A decrease in NODDI-derived vin was observed at the site of the lesion (p < 0.01), whereas a global increase in ODI was seen throughout white matter (p < 0.001). DKI-derived mean kurtosis (MK) and radial kurtosis (RK) and DTI-derived fractional anisotropy (FA) and radial diffusivity (RD) were all significantly different in MS patients (p < 0.02), however NODDI provided higher contrast between NAWM and lesion in all MS patients.

CONCLUSION

NODDI provides unique contrast that is not available with DKI or DTI, enabling improved characterization of the spinal cord in MS.

Early Detection of Treatment-Induced Mitotic Arrest Using Temporal Diffusion Magnetic Resonance Spectroscopy

PURPOSE: A novel quantitative magnetic resonance imaging (MRI) method, namely, temporal diffusion spectroscopy (TDS), was used to detect the response of tumor cells (notably, mitotic arrest) to a specific antimitotic treatment (Nab-paclitaxel) in culture and human ovarian xenografts and evaluated as an early imaging biomarker of tumor responsiveness. METHODS: TDS measures a series of apparent diffusion coefficients (ADCs) of tissue water over a range of effective diffusion times, which may correspond to diffusion distances ranging from subcellular to cellular levels (~ 3-20 μm). By fitting the measured ADC data to a tissue model, parameters reflecting structural properties such as restriction size in solid tumors can be extracted. Two types of human ovarian cell lines (OVCAR-8 as a responder to Nab-paclitaxel and NCI/ADR-RES as a resistant type) were treated with either vehicle (PBS) or Nab-paclitaxel, and treatment responses of both in vitro and in vivo cases were investigated using TDS. RESULTS: Acute cell size increases induced by Nab-paclitaxel in responding tumors were confirmed by flow cytometry and light microscopy in cell culture. Nab-paclitaxel–induced mitotic arrest in treated tumors/cells was quantified histologically by measuring the mitotic index in vivo using a mitosis-specific marker (anti-phosphohistone H3). Changes in the fitted restriction size, one of the parameters obtained from TDS, were able to detect and quantify increases in tumor cell sizes. All the MR results had a high degree of consistency with other flow, microscopy, and histological data. Moreover, with an appropriate analysis, the Nab-paclitaxel–responsive tumors in vivo could be easily distinguished from all the other vehicle-treated and Nab-paclitaxel–resistant tumors. CONCLUSION: TDS detects increases in cell sizes associated with antimitotic-therapy–induced mitotic arrest in solid tumors in vivo which occur before changes in tissue cellularity or conventional diffusion MRI metrics. By quantifying changes in cell size, TDS has the potential to improve the specificity of MRI methods in the evaluation of therapeutic response and enable a mechanistic understanding of therapy-induced changes in tumors.

Validation of surface-to-volume ratio measurements derived from oscillating gradient spin echo on a clinical scanner using anisotropic fiber phantoms

A diffusion measurement in the short-time surface-to-volume ratio (S/V) limit (Mitra et al., Phys Rev Lett. 1992;68:3555) can disentangle the free diffusion coefficient from geometric restrictions to diffusion. Biophysical parameters, such as the S/V of tissue membranes, can be used to estimate microscopic length scales non-invasively. However, due to gradient strength limitations on clinical MRI scanners, pulsed gradient spin echo (PGSE) measurements are impractical for probing the S/V limit. To achieve this limit on clinical systems, an oscillating gradient spin echo (OGSE) sequence was developed. Two phantoms containing 10 fiber bundles, each consisting of impermeable aligned fibers with different packing densities, were constructed to achieve a range of S/V values. The frequency-dependent diffusion coefficient, D(ω), was measured in each fiber bundle using OGSE with different gradient waveforms (cosine, stretched cosine, and trapezoidal), while D(t) was measured from PGSE and stimulated-echo measurements. The S/V values derived from the universal high-frequency behavior of D(ω) were compared against those derived from quantitative proton density measurements using single spin echo (SE) with varying echo times, and from magnetic resonance fingerprinting (MRF). S/V estimates derived from different OGSE waveforms were similar and demonstrated excellent correlation with both SE- and MRF-derived S/V measures (ρ  ≥  0.99). Furthermore, there was a smoother transition between OGSE frequency f and PGSE diffusion time when using teffS/V=9/64f, rather than the commonly used t_eff  = 1/(4f), validating the specific frequency/diffusion time conversion for this regime. Our well-characterized fiber phantom can be used for the calibration of OGSE and diffusion modeling techniques, as the S/V ratio can be measured independently using other MR modalities. Moreover, our calibration experiment offers an exciting perspective of mapping tissue S/V on clinical systems.

Mapping axonal density and average diameter using non-monotonic time-dependent gradient-echo MRI

White Matter (WM) microstructures, such as axonal density and average diameter, are crucial to the normal function of the Central Nervous System (CNS) as they are closely related with axonal conduction velocities. Conversely, disruptions of these microstructural features may result in severe neurological deficits, suggesting that their noninvasive mapping could be an important step towards diagnosing and following pathophysiology. Whereas diffusion based MRI methods have been proposed to map these features, they typically entail the application of powerful gradients, which are rarely available in the clinic, or extremely long acquisition schemes to extract information from parameter-intensive models. In this study, we suggest that simple and time-efficient multi-gradient-echo (MGE) MRI can be used to extract the axon density from susceptibility-driven non-monotonic decay in the time-dependent signal. We show, both theoretically and with simulations, that a non-monotonic signal decay will occur for multi-compartmental microstructures - such as axons and extra-axonal spaces, which were here used as a simple model for the microstructure - and that, for axons parallel to the main magnetic field, the axonal density can be extracted. We then experimentally demonstrate in ex-vivo rat spinal cords that its different tracts - characterized by different microstructures - can be clearly contrasted using the MGE-derived maps. When the quantitative results are compared against ground-truth histology, they reflect the axonal fraction (though with a bias, as evident from Bland-Altman analysis). As well, the extra-axonal fraction can be estimated. The results suggest that our model is oversimplified, yet at the same time evidencing a potential and usefulness of the approach to map underlying microstructures using a simple and time-efficient MRI sequence. We further show that a simple general-linear-model can predict the average axonal diameters from the four model parameters, and map these average axonal diameters in the spinal cords. While clearly further modelling and theoretical developments are necessary, we conclude that salient WM microstructural features can be extracted from simple, SNR-efficient multi-gradient echo MRI, and that this paves the way towards easier estimation of WM microstructure in vivo.

Diffusion MRI of the spinal cord: from structural studies to pathology

Diffusion MRI is extensively used to study brain microarchitecture and pathologies, and water diffusion appears highly anisotropic in the white matter (WM) of the spinal cord (SC). Despite these facts, the use of diffusion MRI to study the SC, which has increased in recent years, is much less common than that in the brain. In the present review, after a brief outline of early studies of diffusion MRI (DWI) and diffusion tensor MRI (DTI) of the SC, we provide a short survey on DTI and on diffusion MRI methods beyond the tensor that have been used to study SC microstructure and pathologies. After introducing the porous view of WM and describing the q-space approach and q-space diffusion MRI (QSI), we describe other methodologies that can be applied to study the SC. Selected applications of the use of DTI, QSI, and other more advanced diffusion MRI methods to study SC microstructure and pathologies are presented, with some emphasis on the use of less conventional diffusion methodologies. Because of length constraints, we concentrate on structural studies and on a few selected pathologies. Examples of the use of diffusion MRI to study dysmyelination, demyelination as in experimental autoimmune encephalomyelitis and multiple sclerosis, amyotrophic lateral sclerosis, and traumatic SC injury are presented. We conclude with a brief summary and a discussion of challenges and future directions for diffusion MRI of the SC. Copyright © 2016 John Wiley & Sons, Ltd.

Evaluation and comparison of diffusion MR methods for measuring apparent transcytolemmal water exchange rate constant

Two diffusion-based approaches, CG (constant gradient) and FEXI (filtered exchange imaging) methods, have been previously proposed for measuring transcytolemmal water exchange rate constant k_in, but their accuracy and feasibility have not been comprehensively evaluated and compared. In this work, both computer simulations and cell experiments in vitro were performed to evaluate these two methods. Simulations were done with different cell diameters (5, 10, 20μm), a broad range of k_in values (0.02-30s^-1) and different SNR's, and simulated k_in's were directly compared with the ground truth values. Human leukemia K562 cells were cultured and treated with saponin to selectively change cell transmembrane permeability. The agreement between measured k_in's of both methods was also evaluated. The results suggest that, without noise, the CG method provides reasonably accurate estimation of k_in especially when it is smaller than 10s^-1, which is in the typical physiological range of many biological tissues. However, although the FEXI method overestimates k_in even with corrections for the effects of extracellular water fraction, it provides reasonable estimates with practical SNR's and more importantly, the fitted apparent exchange rate AXR showed approximately linear dependence on the ground truth k_in. In conclusion, either CG or FEXI method provides a sensitive means to characterize the variations in transcytolemmal water exchange rate constant k_in, although the accuracy and specificity is usually compromised. The non-imaging CG method provides more accurate estimation of k_in, but limited to large volume-of-interest. Although the accuracy of FEXI is compromised with extracellular volume fraction, it is capable of spatially mapping k_in in practice.

Probing metabolite diffusion at ultra-short time scales in the mouse brain using optimized oscillating gradients and "short"-echo-time diffusion-weighted MRS

Measuring diffusion at ultra-short time scales may yield information about short-range intracellular structure and cytosol viscosity. However, reaching such time scales usually requires oscillating gradients, which in turn imply long echo times T_E . Here we propose a new kind of stretched oscillating gradient that allows us to increase diffusion-weighting b while preserving spectral and temporal properties of the gradient modulation. We used these optimized gradients to measure metabolite diffusion in the mouse brain down to effective diffusion times of 1 ms while keeping T_E relatively short (60 ms). At such T_E , a significant macromolecule signal could still be observed and used as an internal reference of approximately null diffusivity, which proved critical to discard datasets corrupted by some motion artifact. The methods introduced here may be useful to improve the accuracy and precision of metabolite apparent diffusion coefficient measurements with oscillating gradients.

A comparative assessment of preclinical chemotherapeutic response of tumors using quantitative non-Gaussian diffusion MRI

BACKGROUND

Diffusion-weighted MRI (DWI) signal attenuation is often not mono-exponential (i.e. non-Gaussian diffusion) with stronger diffusion weighting. Several non-Gaussian diffusion models have been developed and may provide new information or higher sensitivity compared with the conventional apparent diffusion coefficient (ADC) method. However the relative merits of these models to detect tumor therapeutic response is not fully clear.

METHODS

Conventional ADC, and three widely-used non-Gaussian models, (bi-exponential, stretched exponential, and statistical model), were implemented and compared for assessing SW620 human colon cancer xenografts responding to barasertib, an agent known to induce apoptosis via polyploidy. Bayesian Information Criterion (BIC) was used for model selection among all three non-Gaussian models.

RESULTS

All of tumor volume, histology, conventional ADC, and three non-Gaussian DWI models could show significant differences between control and treatment groups after four days of treatment. However, only the non-Gaussian models detected significant changes after two days of treatment. For any treatment or control group, over 65.7% of tumor voxels indicate the bi-exponential model is strongly or very strongly preferred.

CONCLUSION

Non-Gaussian DWI model-derived biomarkers are capable of detecting tumor earlier chemotherapeutic response of tumors compared with conventional ADC and tumor volume. The bi-exponential model provides better fitting compared with statistical and stretched exponential models for the tumor and treatment models used in the current work.

Pulsed and oscillating gradient MRI for assessment of cell size and extracellular space (POMACE) in mouse gliomas

Solid tumor microstructure is related to the aggressiveness of the tumor, interstitial pressure and drug delivery pathways, which are closely associated with treatment response, metastatic spread and prognosis. In this study, we introduce a novel diffusion MRI data analysis framework, pulsed and oscillating gradient MRI for assessment of cell size and extracellular space (POMACE), and demonstrate its feasibility in a mouse tumor model. In vivo and ex vivo POMACE experiments were performed on mice bearing the GL261 murine glioma model (n = 8). Since the complete diffusion time dependence is in general non-analytical, the tumor microstructure was modeled in an appropriate time/frequency regime by impermeable spheres (radius Rcell , intracellular diffusivity Dics ) surrounded by extracellular space (ECS) (approximated by constant apparent diffusivity Decs in volume fraction ECS). POMACE parametric maps (ECS, Rcell , Dics , Decs ) were compared with conventional diffusion-weighted imaging metrics, electron microscopy (EM), alternative ECS determination based on effective medium theory (EMT), and optical microscopy performed on the same samples. It was shown that Decs can be approximated by its long time tortuosity limit in the range [1/(88 Hz)-31 ms]. ECS estimations (44 ± 7% in vivo and 54 ± 11% ex vivo) were in agreement with EMT-based ECS and literature on brain gliomas. Ex vivo, ECS maps correlated well with optical microscopy. Cell sizes (Rcell  = 4.8 ± 1.3 in vivo and 4.3 ± 1.4 µm ex vivo) were consistent with EM measurements (4.7 ± 1.8 µm). In conclusion, Rcell and ECS can be quantified and mapped in vivo and ex vivo in brain tumors using the proposed POMACE method. Our experimental results support the view that POMACE provides a way to interpret the frequency or time dependence of the diffusion coefficient in tumors in terms of objective biophysical parameters of neuronal tissue, which can be used for non-invasive monitoring of preclinical cancer studies and treatment efficacy. Copyright © 2016 John Wiley & Sons, Ltd.

New insights about time-varying diffusivity and its estimation from diffusion MRI

PURPOSE

Characterizing the relation between the applied gradient sequences and the measured diffusion MRI signal is important for estimating the time-dependent diffusivity, which provides important information about the microscopic tissue structure.

THEORY AND METHODS

In this article, we extend the classical theory of Stepišnik for measuring time-dependent diffusivity under the Gaussian phase approximation. In particular, we derive three novel expressions which represent the diffusion MRI signal in terms of the mean-squared displacement, the instantaneous diffusivity, and the velocity autocorrelation function. We present the explicit signal expressions for the case of single diffusion encoding and oscillating gradient spin-echo sequences. Additionally, we also propose three different models to represent time-varying diffusivity and test them using Monte-Carlo simulations and in vivo human brain data.

RESULTS

The time-varying diffusivities are able to distinguish the synthetic structures in the Monte-Carlo simulations. There is also strong statistical evidence about time-varying diffusivity from the in vivo human data set.

CONCLUSION

The proposed theory provides new insights into our understanding of the time-varying diffusivity using different gradient sequences. The proposed models for representing time-varying diffusivity can be utilized to study time-varying diffusivity using in vivo human brain diffusion MRI data. Magn Reson Med 78:763-774, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Double oscillating diffusion encoding and sensitivity to microscopic anisotropy

Purpose

To introduce a novel diffusion pulse sequence, namely double oscillating diffusion encoding (DODE), and to investigate whether it adds sensitivity to microscopic diffusion anisotropy (µA) compared to the well‐established double diffusion encoding (DDE) methodology.

Methods

We simulate measurements from DODE and DDE sequences for different types of microstructures exhibiting restricted diffusion. First, we compare the effect of varying pulse sequence parameters on the DODE and DDE signal. Then, we analyse the sensitivity of the two sequences to the microstructural parameters (pore diameter and length) which determine µA. Finally, we investigate specificity of measurements to particular substrate configurations.

Results

Simulations show that DODE sequences exhibit similar signal dependence on the relative angle between the two gradients as DDE sequences, however, the effect of varying the mixing time is less pronounced. The sensitivity analysis shows that in substrates with elongated pores and various orientations, DODE sequences increase the sensitivity to pore diameter, while DDE sequences are more sensitive to pore length. Moreover, DDE and DODE sequence parameters can be tailored to enhance/suppress the signal from a particular range of substrates.

Conclusions

A combination of DODE and DDE sequences maximize sensitivity to µA, compared to using just the DDE method. Magn Reson Med 78:550–564, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Assessing the accuracy of using oscillating gradient spin echo sequences with AxCaliber to infer micron-sized axon diameters

OBJECTIVE

Current magnetic resonance imaging (MRI) axon diameter measurements rely on the pulsed gradient spin-echo sequence, which is unable to provide diffusion times short enough to measure small axon diameters. This study combines the AxCaliber axon diameter fitting method with data generated from Monte Carlo simulations of oscillating gradient spin-echo sequences (OGSE) to infer micron-sized axon diameters, in order to determine the feasibility of using MRI to infer smaller axon diameters in brain tissue.

MATERIALS AND METHODS

Monte Carlo computer simulation data were synthesized from tissue geometries of cylinders of different diameters using a range of gradient frequencies in the cosine OGSE sequence . Data were fitted to the AxCaliber method modified to allow the new pulse sequence. Intra- and extra-axonal water were studied separately and together.

RESULTS

The simulations revealed the extra-axonal model to be problematic. Rather than change the model, we found that restricting the range of gradient frequencies such that the measured apparent diffusion coefficient was constant over that range resulted in more accurate fitted diameters. Thus a careful selection of frequency ranges is needed for the AxCaliber method to correctly model extra-axonal water, or adaptations to the method are needed. This restriction helped reduce the necessary gradient strengths for measurements that could be performed with parameters feasible for a Bruker BG6 gradient set. For these experiments, the simulations inferred diameters as small as 0.5 μm on square-packed and randomly packed cylinders. The accuracy of the inferred diameters was found to be dependent on the signal-to-noise ratio (SNR), with smaller diameters more affected by noise, although all diameter distributions were distinguishable from one another for all SNRs tested.

CONCLUSION

The results of this study indicate the feasibility of using MRI with OGSE on preclinical scanners to infer small axon diameters.

Early Idiopathic Normal Pressure Hydrocephalus Patients With Neuropsychological Impairment Are Associated With Increased Fractional Anisotropy in the Anterior Thalamic Nucleus

In this study, we aimed to investigate the reactive changes in diffusion tensor imaging (DTI)-derived diffusion metrics of the anterior thalamic nucleus (AN), a relaying center for the Papez circuit, in early idiopathic normal pressure hydrocephalus (iNPH) patients with memory impairment, as well as its correlation with the patients' neuropsychological performances. In total, 28 probable iNPH patients with symptom onset within 1 year and 17 control subjects were prospectively recruited between 2010 and 2013 for this institutional review board-approved study. Imaging studies including DTI and a neuropsychological assessment battery were performed in all subjects. Diffusion metrics were measured from the region of the AN using tract-deterministic seeding method by reconstructing the mammillo-thalamo-cingulate connections within the Papez circuit. Differences in diffusion metrics and memory assessment scores between the patient and control group were examined via the Mann-Whitney U test. Spearman correlation analyses were performed to examine associations between diffusion metrics of AN and neuropsychological tests within the patient group. We discovered that early iNPH patients exhibited marked elevations in fractional anisotropy, pure diffusion anisotropy, and axial diffusivity (all P < 0.01), as well as lower neuropsychological test scores including verbal and nonverbal memory (all P < 0.05) compared with normal control. Spearman rank correlation analyses did not disclose significant correlations between AN diffusion metrics and neuropsychological test scores in the patient group, whereas ranked scatter plots clearly demonstrated a dichotic sample distribution between patient and control samples. In summary, our study highlighted the potential compensatory role of the AN by increasing thalamocortical connectivity within the Papez circuit because memory function declines in early iNPH when early shunt treatment may potentially reverse the memory deficits.

White matter microstructure from nonparametric axon diameter distribution mapping

We report the development of a double diffusion encoding (DDE) MRI method to estimate and map the axon diameter distribution (ADD) within an imaging volume. A variety of biological processes, ranging from development to disease and trauma, may lead to changes in the ADD in the central and peripheral nervous systems. Unlike previously proposed methods, this ADD experimental design and estimation framework employs a more general, nonparametric approach, without a priori assumptions about the underlying form of the ADD, making it suitable to analyze abnormal tissue. In the current study, this framework was used on an ex vivo ferret spinal cord, while emphasizing the way in which the ADD can be weighted by either the number or the volume of the axons. The different weightings, which result in different spatial contrasts, were considered throughout this work. DDE data were analyzed to derive spatially resolved maps of average axon diameter, ADD variance, and extra-axonal volume fraction, along with a novel sub-micron restricted structures map. The morphological information contained in these maps was then used to segment white matter into distinct domains by using a proposed k-means clustering algorithm with spatial contiguity and left-right symmetry constraints, resulting in identifiable white matter tracks. The method was validated by comparing histological measures to the estimated ADDs using a quantitative similarity metric, resulting in good agreement. With further acquisition acceleration and experimental parameters adjustments, this ADD estimation framework could be first used preclinically, and eventually clinically, enabling a wide range of neuroimaging applications for improved understanding of neurodegenerative pathologies and assessing microstructural changes resulting from trauma.

The Effect of Microcirculatory Flow on Oscillating Gradient Diffusion MRI and Diffusion Encoding with Dual-Frequency Orthogonal Gradients (DEFOG)

PURPOSE

We investigated the effect of microcirculatory flow on oscillating gradient spin echo (OGSE) diffusion MRI at low b-values and developed a diffusion preparation method called diffusion encoding with dual-frequency orthogonal gradients (DEFOG) to suppress the effect.

METHODS

Compared to conventional OGSE sequences, DEFOG adds a pulsed gradient that is orthogonal to the oscillating gradient and has a moderate diffusion weighting (e.g., 300 s/mm² ). In vivo MRI data were acquired from adult mouse brains (n = 5) on an 11.7 Tesla scanner, with diffusion times from 23.2 to 0.83 ms and b-values from 50 to 700 s/mm² .

RESULTS

Apparent diffusion coefficients (ADCs) measured using a conventional OGSE sequence at low b-values (< 200 mm² /s) were significantly higher than those measured at moderate b-values (> 300 mm² /s), potentially due to contributions from microcirculatory flow. In comparison, OGSE ADCs measured using the DEFOG method at low b-values were comparable to those measured at moderate b-values. The effect of microcirculatory flow on diffusion signals was diffusion time-dependent, and this dependency may reflect the capillary geometry and blood flow velocity in the mouse cortex.

CONCLUSION

Microcirculatory flow affects OGSE diffusion MRI measurements at low b-values, and this effect can be suppressed using the DEFOG method. Magn Reson Med 77:1583-1592, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Fast and simplified mapping of mean axon diameter using temporal diffusion spectroscopy

Mapping axon diameter is of interest for the potential diagnosis and monitoring of various neuronal pathologies. Advanced diffusion-weighted MRI methods have been developed to measure mean axon diameters non-invasively, but suffer major drawbacks that prevent their direct translation into clinical practice, such as complex non-linear data fitting and, more importantly, long scanning times that are usually not tolerable for most human subjects. In the current study, temporal diffusion spectroscopy using oscillating diffusion gradients was used to measure mean axon diameters with high sensitivity to small axons in the central nervous system. Axon diameters have been found to be correlated with a novel metric, DDR⊥ (the rate of dispersion of the perpendicular diffusion coefficient with gradient frequency), which is a model-free quantity that does not require complex data analyses and can be obtained from two diffusion coefficient measurements in clinically relevant times with conventional MRI machines. A comprehensive investigation including computer simulations and animal experiments ex vivo showed that measurements of DDR⊥ agree closely with histological data. In humans in vivo, DDR⊥ was also found to correlate well with reported mean axon diameters in human corpus callosum, and the total scan time was only about 8 min. In conclusion, DDR⊥ may have potential to serve as a fast, simple and model-free approach to map the mean axon diameter of white matter in clinics for assessing axon diameter changes.

In vivo observation and biophysical interpretation of time-dependent diffusion in human white matter

The presence of micrometer-level restrictions leads to a decrease of diffusion coefficient with diffusion time. Here we investigate this effect in human white matter in vivo. We focus on a broad range of diffusion times, up to 600 ms, covering diffusion length scales up to about 30 μm. We perform stimulated echo diffusion tensor imaging on 5 healthy volunteers and observe a relatively weak time-dependence in diffusion transverse to major fiber tracts. Remarkably, we also find notable time-dependence in the longitudinal direction. Comparing models of diffusion in ordered, confined and disordered media, we argue that the time-dependence in both directions can arise due to structural disorder, such as axonal beads in the longitudinal direction, and the random packing geometry of fibers within a bundle in the transverse direction. These time-dependent effects extend beyond a simple picture of Gaussian compartments, and may lead to novel markers that are specific to neuronal fiber geometry at the micrometer scale.

Fiber Orientation and Compartment Parameter Estimation From Multi-Shell Diffusion Imaging

Diffusion MRI offers the unique opportunity of assessing the structural connections of human brains in vivo. With the advance of diffusion MRI technology, multi-shell imaging methods are becoming increasingly practical for large scale studies and clinical application. In this work, we propose a novel method for the analysis of multi-shell diffusion imaging data by incorporating compartment models into a spherical deconvolution framework for fiber orientation distribution (FOD) reconstruction. For numerical implementation, we develop an adaptively constrained energy minimization approach to efficiently compute the solution. On simulated and real data from Human Connectome Project (HCP), we show that our method not only reconstructs sharp and clean FODs for the modeling of fiber crossings, but also generates reliable estimation of compartment parameters with great potential for clinical research of neurological diseases. In comparisons with publicly available DSI-Studio and BEDPOSTX of FSL, we demonstrate that our method reconstructs sharper FODs with more precise estimation of fiber directions. By applying probabilistic tractography to the FODs computed by our method, we show that more complete reconstruction of the corpus callosum bundle can be achieved. On a clinical, two-shell diffusion imaging data, we also demonstrate the feasibility of our method in analyzing white matter lesions.

Structural information revealed by the dispersion of ADC with frequency

Diffusion MRI provides a non-invasive means to characterize tissue microstructure at varying length scales. Temporal diffusion spectra reveal how the apparent diffusion coefficient (ADC) varies with frequency. When measured using oscillating gradient spin echo sequences, the manner in which ADC disperses with gradient frequency (which is related to the reciprocal of diffusion time) provides information on the characteristic dimensions of restricting structures within the medium. For example, the dispersion of ADC with oscillating gradient frequency (ΔfADC) has been shown to correlate with axon sizes in white matter and provide novel tissue contrast in images of mouse hippocampus and cerebellum. However, despite increasing interest in applying frequency-dependent ADC to derive novel information on tissue, the interpretations of ADC spectra are not always clear. In this study, the relation between ADC spectra and restricting dimensions are further elucidated and used to derive novel image contrast related to the sizes of intrinsic microstructures.

Time-Dependent Influence of Cell Membrane Permeability on MR Diffusion Measurements

PURPOSE

To investigate the influence of cell membrane permeability on diffusion measurements over a broad range of diffusion times.

METHODS

Human myelogenous leukemia K562 cells were cultured and treated with saponin to selectively alter cell membrane permeability, resulting in a broad physiologically relevant range of 0.011-0.044 μm/ms. Apparent diffusion coefficient (ADC) values were acquired with the effective diffusion time (Δeff ) ranging from 0.42 to 3000 ms. Cosine-modulated oscillating gradient spin echo (OGSE) measurements were performed to achieve short Δeff from 0.42 to 5 ms, while stimulated echo acquisitions were used to achieve long Δeff from 11 to 2999 ms. Computer simulations were also performed to support the experimental results.

RESULTS

Both computer simulations and experiments in vitro showed that the influence of membrane permeability on diffusion MR measurements is highly dependent on the choice of diffusion time, and it is negligible only when the diffusion time is at least one order of magnitude smaller than the intracellular exchange lifetime.

CONCLUSION

The influence of cell membrane permeability on the measured ADCs is negligible in OGSE measurements at moderately high frequencies. By contrast, cell membrane permeability has a significant influence on ADC and quantitative diffusion measurements at low frequencies such as those sampled using conventional pulsed gradient methods.

The microstructural correlates of T1 in white matter

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.

CONCLUSION

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.

Quantification of cell size using temporal diffusion spectroscopy

PURPOSE

A new approach has been developed to quantify cell sizes and intracellular volume fractions using temporal diffusion spectroscopy with diffusion-weighted acquisitions.

METHODS

Temporal diffusion spectra may be used to characterize tissue microstructure by measuring the effects of restrictions over a range of diffusion times. Oscillating gradients have been used previously to probe variations on cellular and subcellular scales, but their ability to accurately measure cell sizes larger than 10 μm is limited. By combining measurements made using oscillating gradient spin echo (OGSE) and a conventional pulsed gradient spin echo (PGSE) acquisition with a single, relatively long diffusion time, we can accurately quantify cell sizes and intracellular volume fractions.

RESULTS

Based on a two compartment model (incorporating intra- and extracellular spaces), accurate estimates of cell sizes and intracellular volume fractions were obtained in vitro for (i) different cell types with sizes ranging from 10 to 20 μm, (ii) different cell densities, and (iii) before and after anticancer treatment.

CONCLUSION

Hybrid OGSE-PGSE acquisitions sample a larger region of temporal diffusion spectra and can accurately quantify cell sizes over a wide range. Moreover, the maximum gradient strength used was lower than 15 G/cm, suggesting that this approach is translatable to practical MR imaging.

Mesoscopic structure of neuronal tracts from time-dependent diffusion

Interpreting brain diffusion MRI measurements in terms of neuronal structure at a micrometer level is an exciting unresolved problem. Here we consider diffusion transverse to a bundle of fibers, and show theoretically, as well as using Monte Carlo simulations and measurements in a phantom made of parallel fibers mimicking axons, that the time dependent diffusion coefficient approaches its macroscopic limit slowly, in a (ln t)/t fashion. The logarithmic singularity arises due to short range disorder in the fiber packing. We identify short range disorder in axonal fibers based on histological data from the splenium, and argue that the time dependent contribution to the overall diffusion coefficient from the extra-axonal water dominates that of the intra-axonal water. This dominance may explain the bias in measuring axon diameters in clinical settings. The short range disorder is also reflected in the asymptotically linear frequency dependence of the diffusion coefficient measured with oscillating gradients, in agreement with recent experiments. Our results relate the measured diffusion to the mesoscopic structure of neuronal tissue, uncovering the sensitivity of diffusion metrics to axonal arrangement within a fiber tract, and providing an alternative interpretation of axonal diameter mapping techniques.