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•Simultaneously high b-value and frequency OGSE diffusion encoding are achieved.•The frequency dependences of diffusivity and kurtosis are studied for human brains.•The effects of gradient nonlinearity on frequency-dependent DKI measures are studied.•A trend of decreasing kurtosis over frequency is captured for in vivo human brains. Measuring the time/frequency dependence of diffusion MRI is a promising approach to distinguish between the effects of different tissue microenvironments, such as membrane restriction, tissue heterogeneity, and compartmental water exchange. In this study, we measure the frequency dependence of diffusivity (D) and kurtosis (K) with oscillating gradient diffusion encoding waveforms and a diffusion kurtosis imaging (DKI) model in human brains using a high-performance, head-only MAGNUS gradient system, with a combination of b-values, oscillating frequencies (f), and echo time that has not been achieved in human studies before. Frequency dependence of diffusivity and kurtosis are observed in both global and local white matter (WM) and gray matter (GM) regions and characterized with a power-law model ∼Λ*fθ. The frequency dependences of diffusivity and kurtosis (including changes between fmin and fmax, Λ, and θ) vary over different WM and GM regions, indicating potential microstructural differences between regions. A trend of decreasing kurtosis over frequency in the short-time limit is successfully captured for in vivo human brains. The effects of gradient nonlinearity (GNL) on frequency-dependent diffusivity and kurtosis measurements are investigated and corrected. Our results show that the GNL has prominent scaling effects on the measured diffusivity values (3.5∼5.5% difference in the global WM and 6∼8% difference in the global cortex) and subsequently affects the corresponding power-law parameters (Λ, θ) while having a marginal influence on the measured kurtosis values (<0.05% difference) and power-law parameters (Λ, θ). This study expands previous OGSE studies and further demonstrates the translatability of frequency-dependent diffusivity and kurtosis measurements to human brains, which may provide new opportunities to probe human brain microstructure in health and disease.

Mapping axon diameters within the central and peripheral nervous system could play an important role in our understanding of nerve pathways, and help diagnose and monitor an array of neurological disorders. Numerous diffusion MRI methods have been proposed for imaging axon diameters, most of which use conventional single diffusion encoding (SDE) spin echo sequences. However, a growing number of studies show that oscillating gradient spin echo (OGSE) sequences can provide additional advantages over conventional SDE sequences. Recent theoretical results suggest that this is especially the case in realistic scenarios, such as when fibres have unknown or dispersed orientation. In the present study, we adopt the ActiveAx approach to experimentally investigate the extent of these advantages by comparing the performances of SDE and trapezoidal OGSE in viable nerve tissue. We optimise SDE and OGSE ActiveAx protocols for a rat peripheral nerve tissue and test their performance using Monte Carlo simulations and a 800 mT/m gradient strength pre-clinical imaging experiment. The imaging experiment uses excised sciatic nerve from a rat's leg placed in a MRI compatible viable isolated tissue (VIT) maintenance chamber, which keeps the tissue in a viable physiological state that preserves the structural complexity of the nerve and enables lengthy scan times. We compare model estimates to histology, which we perform on the nerve post scanning. Optimisation produces a three-shell SDE and OGSE ActiveAx protocol, with the OGSE protocol consisting of one SDE sequence and two low-frequency oscillating gradient waveform sequences. Both simulation and imaging results show that the OGSE ActiveAx estimates of the axon diameter index have a higher accuracy and a higher precision compared to those from SDE. Histology estimates of the axon diameter index in our nerve tissue samples are 4–5.8 μm and these are excellently matched with the OGSE estimates 4.2–6.5 μm, while SDE overestimates at 5.2–8 μm for the same sample. We found OGSE estimates to be more precise with on average a 0.5 μm standard deviation compared to the SDE estimates which have a 2 μm standard deviation. When testing the robustness of the estimates when the number of the diffusion gradient directions reduces, we found that both OGSE and SDE estimates are affected, however OGSE is more robust to these changes than the SDE. Overall, these results suggest, quantitatively and in in vivo conditions, that low-frequency OGSE sequences may provide improved accuracy of axon diameter mapping compared to standard SDE sequences. •Performance of SDE and OGSE ActiveAx are compared for axon diameter imaging.•A viable rat sciatic nerve and Monte Carlo simulations are used as samples.•OGSE outperforms SDE in accuracy, precision and robustness of diameter estimates.•Optimal OGSE has low frequency with results matching histology at 800 mT/m.

Time‐dependent diffusion MRI (td‐dMRI) has potential in characterizing microstructural features; however, its value in imaging endometrioid endometrial adenocarcinoma (EEA) remains uncertain. Patients surgically confirmed with EEA were finally enrolled in our study. The td‐dMRI data were acquired using pulsed gradient spin echo sequence and oscillating gradient spin echo sequences. The microstructural markers, including cell diameter, intracellular volume fraction (Vin), cellularity, and extracellular diffusivity (Dex), were fitted with the imaging microstructural parameters using a limited spectrally edited diffusion (IMPULSED) model. The parameters were compared between low‐ and high‐risk groups and between low‐ and high‐proliferation groups. The diagnostic performance was evaluated using receiver‐operating characteristic curve and logistic regression analysis. Diameter, Dex, ADCPGSE, ADCN1, and ADCN2 were significantly low, whereas cellularity, ΔADC1 and ΔADC2 were significantly high in the high‐risk and high‐proliferation groups. Cellularity, ΔADC1, and ΔADC2 demonstrated excellent diagnostic efficacy in predicting both risk stratification and proliferation status. Cellularity was the only independent predictor for risk stratification, which exhibited a satisfactory positive correlation with cell density in histopathologic examination. The diagnostic potential of td‐dMRI‐based microstructural mapping was demonstrated to noninvasively probe the pathologic characteristics of patients with EEA in a clinical setting, which provided a valuable contribution to surgical guidance. This work, demonstrating the diagnostic potential of td‐dMRI‐based microstructural mapping in noninvasively probing the pathologic characteristics of patients with EEA in a clinical setting and providing a valuable contribution to surgical guidance, would be of interest to a broad readership in the fields of oncology, preoperative evaluation, and cancer treatment strategies.

PurposeThe purpose of this study was to investigate whether the changes in apparent diffusion coefficients (ADCs) due to differences in diffusion time reflect tissue properties in actual measurements of phantoms.Materials and methodsVarious n-alkane phantoms and sucrose/collagen phantoms with various collagen densities were set up with and without polyvinyl alcohol (PVA) foam with an average pore diameter of 300 μm. Thus, n-alkanes or sucrose/collagen represented substrate viscosity and the presence of PVA foam represented tissue structure with septum. Diffusion-weighted images with various diffusion times (7.71–60 ms) were acquired using pulsed-gradient spin-echo (PGSE) and oscillating-gradient spin-echo (OGSE) sequences. The ADCs of the phantoms with and without PVA foam were calculated.ResultsThe ADCs of some of the phantoms without PVA decreased with diffusion times decreased. In the n-alkane phantoms, only C8H18 showed significantly different ADCs depending on the use of PVA foam in the OGSE sequence. On the other hand, sucrose/collagen phantoms showed significant differences according to diffusion time. The ADCs of the phantoms decreased as the molecular size of the n-alkanes or collagen density of the sucrose/collagen phantom increased. Compared to phantoms without PVA foam, the ADC of the phantoms with PVA foam decreased as the diffusion time increased.ConclusionChanges in ADCs due to differences in diffusion time reflect tissue properties in actual measurements of phantoms. These changes in ADCs can be used for tissue characterization in vivo.

As the oscillating gradient spin-echo sequence has shown promise as a means to probe tissue microstructure, it was applied here to diffusion-tensor imaging of in vivo rat brain. The apparent diffusion tensor (ADT) was estimated for motion-probing gradient (MPG) frequencies in the range 33.3–133.3Hz, and regions-of-interest (ROIs) in the corpus callosum (CC), visual cortex (VC), cerebellar white matter (CBWM) and cerebellar grey matter (CBGM) were selected for detailed analysis. There were substantial, approximately linear changes to the ADT with increasing MPG frequency for all four ROIs. All ROIs showed clear increases in mean diffusivity. CBWM had a substantial decrease in fractional anisotropy, whereas the CC and VC had minor increases of the same parameter. All eigenvalues of the ADT tended to increase with frequency for the CBWM, CBGM and VC, but only the principal eigenvalue increased strongly for the CC. On the other hand, there was no evidence that the orientation of the principal eigenvector varied systematically with MPG frequency for any of the ROIs. The relationship between the behaviour of the eigenvalues and the behaviours of the mean diffusivity and fractional anisotropy is investigated in detail. Pixelwise linear fits to the MD from individual animals found elevated changes across the cerebellum. The data acquired for this work encompassed a range of effective diffusion-times from 7.5ms down to 1.875ms, and some ideas on how the results might be used to extract quantitative information about brain tissue microstructure are discussed. ► Clear frequency-dependent changes were measured over the range 33.3–133.3Hz. ► All selected regions showed clear increases in mean diffusivity. ► Fractional anisotropy may either increase or decrease depending on tissue type. ► Orientation of principal eigenvector is independent of frequency for all ROIs. ► Frequency range covers effective diffusion-times from 7.5ms down to 1.875ms.

PurposeCompared with the conventional pulsed gradient spin-echo (PGSE) sequence, diffusion-weighted imaging (DWI) with the oscillating gradient spin-echo (OGSE) sequence can shorten the diffusion time by changing the frequency. The purpose was to investigate whether n-alkanes are suitable as isotropic phantoms for estimating the diffusion coefficient with the OGSE sequence.Materials and methodsWe investigated changes in the apparent diffusion coefficient (ADC) due to differences in the viscosities of nine n-alkane phantoms with different numbers of carbon atoms from C8H18 to C16H34 using OGSE and PGSE sequences at 21 °C. Effective diffusion times of 4.3, 5.1, 6.5, 9.3, 20, 40, and 60 ms were used. The T2 relaxation times of each n-alkane phantom were measured using quantitative synthetic magnetic resonance imaging (MRI). Circular regions of interest were placed manually within the alkane phantoms on ADC and T2 maps.ResultsIn each alkane phantom, changes in mean ADC values were almost constant with changes in diffusion times. Viscosities and ADC values showed inverse proportionality, as expected theoretically.ConclusionThe ADC values of alkanes do not depend on diffusion times. The n-alkanes can be useful phantoms for assessing the accuracy of clinical protocols of DWI with the OGSE sequence.