The Effect of Microcirculatory Flow on Oscillating Gradient Diffusion MRI and Diffusion Encoding with Dual-Frequency Orthogonal Gradients (DEFOG).
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ABSTRACT:
SUBMITTER: Wu D
PROVIDER: S-EPMC5568088 | biostudies-other | 2017 Apr
REPOSITORIES: biostudies-other
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Project description:We investigated whether oscillating gradient diffusion MRI (dMRI) can provide information on brain microstructural changes after formaldehyde fixation and after hypoxic-ischemic (HI) injury beyond that provided by conventional dMRI.Pulsed gradient spin echo (PGSE) and oscillating gradient spin echo (OGSE) dMRI of the adult mouse brain was performed in vivo (50-200 Hz, b?=?600 mm(2)/s), and a similar protocol was applied to neonatal mouse brains at 24 h after unilateral hypoxia-ischemia. Animals were perfusion fixed with 4% paraformaldehyde for ex vivo dMRI and histology.Apparent diffusion coefficients (ADCs) measured in the live adult mouse brain presented tissue-dependent frequency-dependence. In vivo OGSE-ADC maps at high oscillating frequencies (>100 Hz) showed clear contrast between the molecular layer and granule cell layer in the adult mouse cerebellum. Formaldehyde fixation significantly altered the temporal diffusion spectra in several brain regions. In neonatal mouse brains with HI injury, in vivo ADC measurements from edema regions showed diminished edema contrasts at 200 Hz compared with the PGSE results. Histology showed severe tissue swelling and necrosis in the edema regions.The results demonstrate the unique ability of OGSE-dMRI in delineating tissue microstructures at different spatial scales.
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Project description:Background and purposeMicrostructure imaging with advanced diffusion MRI (dMRI) techniques have shown increased sensitivity and specificity to microstructural changes in various disease and injury models. Oscillating gradient spin echo (OGSE) dMRI, implemented by varying the oscillating gradient frequency, and microscopic anisotropy (μA) dMRI, implemented via tensor valued diffusion encoding, may provide additional insight by increasing sensitivity to smaller spatial scales and disentangling fiber orientation dispersion from true microstructural changes, respectively. The aims of this study were to characterize the test-retest reproducibility of in vivo OGSE and μA dMRI metrics in the mouse brain at 9.4 Tesla and provide estimates of required sample sizes for future investigations.MethodsTwelve adult C57Bl/6 mice were scanned twice (5 days apart). Each imaging session consisted of multifrequency OGSE and μA dMRI protocols. Metrics investigated included μA, linear diffusion kurtosis, isotropic diffusion kurtosis, and the diffusion dispersion rate (Λ), which explores the power-law frequency dependence of mean diffusivity. The dMRI metric maps were analyzed with mean region-of-interest (ROI) and whole brain voxel-wise analysis. Bland-Altman plots and coefficients of variation (CV) were used to assess the reproducibility of OGSE and μA metrics. Furthermore, we estimated sample sizes required to detect a variety of effect sizes.ResultsBland-Altman plots showed negligible biases between test and retest sessions. ROI-based CVs revealed high reproducibility for most metrics (CVs < 15%). Voxel-wise CV maps revealed high reproducibility for μA (CVs ~ 10%), but low reproducibility for OGSE metrics (CVs ~ 50%).ConclusionMost of the μA dMRI metrics are reproducible in both ROI-based and voxel-wise analysis, while the OGSE dMRI metrics are only reproducible in ROI-based analysis. Given feasible sample sizes (10-15), μA metrics and OGSE metrics may provide sensitivity to subtle microstructural changes (4-8%) and moderate changes (> 6%), respectively.
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Project description:Objects making up complex porous systems in Nature usually span a range of sizes. These size distributions play fundamental roles in defining the physicochemical, biophysical and physiological properties of a wide variety of systems - ranging from advanced catalytic materials to Central Nervous System diseases. Accurate and noninvasive measurements of size distributions in opaque, three-dimensional objects, have thus remained long-standing and important challenges. Herein we describe how a recently introduced diffusion-based magnetic resonance methodology, Non-Uniform-Oscillating-Gradient-Spin-Echo (NOGSE), can determine such distributions noninvasively. The method relies on its ability to probe confining lengths with a (length)6 parametric sensitivity, in a constant-time, constant-number-of-gradients fashion; combined, these attributes provide sufficient sensitivity for characterizing the underlying distributions in ?m-scaled cellular systems. Theoretical derivations and simulations are presented to verify NOGSE's ability to faithfully reconstruct size distributions through suitable modeling of their distribution parameters. Experiments in yeast cell suspensions - where the ground truth can be determined from ancillary microscopy - corroborate these trends experimentally. Finally, by appending to the NOGSE protocol an imaging acquisition, novel MRI maps of cellular size distributions were collected from a mouse brain. The ensuing micro-architectural contrasts successfully delineated distinctive hallmark anatomical sub-structures, in both white matter and gray matter tissues, in a non-invasive manner. Such findings highlight NOGSE's potential for characterizing aberrations in cellular size distributions upon disease, or during normal processes such as development.
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Project description:To disentangle the free diffusivity (D0 ) and cellular membrane restrictions, by means of their surface-to-volume ratio (S/V), using the frequency-dependence of the diffusion coefficient D(?), measured in brain tumors in the short diffusion-time regime using oscillating gradients (OGSE).In vivo and ex vivo OGSE experiments were performed on mice bearing the GL261 murine glioma model (n?=?10) to identify the relevant time/frequency (t/?) domain where D(?) linearly decreases with ?(-1/2) . Parametric maps (S/V, D0 ) are compared with conventional DWI metrics. The impact of frequency range and temperature (20°C versus 37°C) on S/V and D0 is investigated ex vivo.The validity of the short diffusion-time regime is demonstrated in vivo and ex vivo. Ex vivo measurements confirm that the purely geometric restrictions embodied in S/V are independent from temperature and frequency range, while the temperature dependence of the free diffusivity D0 is similar to that of pure water.Our results suggest that D(?) in the short diffusion-time regime can be used to uncouple the purely geometric restriction effect, such as S/V, from the intrinsic medium diffusivity properties, and provides a nonempirical and objective way to interpret frequency/time-dependent diffusion changes in tumors in terms of objective biophysical tissue parameters. Magn Reson Med 76:237-247, 2016. © 2015 Wiley Periodicals, Inc.
| S-EPMC4724565 | biostudies-literature
Project description:PurposeWe investigate the importance of high gradient-amplitude and high slew-rate on oscillating gradient spin echo (OGSE) diffusion imaging for human brain imaging and evaluate human brain imaging with OGSE on the MAGNUS head-gradient insert (200 mT/m amplitude and 500 T/m/s slew rate).MethodsSimulations with cosine-modulated and trapezoidal-cosine OGSE at various gradient amplitudes and slew rates were performed. Six healthy subjects were imaged with the MAGNUS gradient at 3T with OGSE at frequencies up to 100 Hz and b = 450 s/mm2 . Comparisons were made against standard pulsed gradient spin echo (PGSE) diffusion in vivo and in an isotropic diffusion phantom.ResultsSimulations show that to achieve high frequency and b-value simultaneously for OGSE, high gradient amplitude, high slew rates, and high peripheral nerve stimulation limits are required. A strong linear trend for increased diffusivity (mean: 8-19%, radial: 9-27%, parallel: 8-15%) was observed in normal white matter with OGSE (20 Hz to 100 Hz) as compared to PGSE. Linear fitting to frequency provided excellent correlation, and using a short-range disorder model provided radial long-term diffusivities of D∞,MD = 911 ± 72 µm2 /s, D∞,PD = 1519 ± 164 µm2 /s, and D∞,RD = 640 ± 111 µm2 /s and correlation lengths of lc ,MD = 0.802 ± 0.156 µm, lc ,PD = 0.837 ± 0.172 µm, and lc ,RD = 0.780 ± 0.174 µm. Diffusivity changes with OGSE frequency were negligible in the phantom, as expected.ConclusionThe high gradient amplitude, high slew rate, and high peripheral nerve stimulation thresholds of the MAGNUS head-gradient enables OGSE acquisition for in vivo human brain imaging.
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Project description:Characterization of porous media is essential in a wide range of biomedical and industrial applications. Microstructural features can be probed non-invasively by diffusion magnetic resonance imaging (dMRI). However, diffusion encoding in conventional dMRI may yield similar signatures for very different microstructures, which represents a significant limitation for disentangling individual microstructural features in heterogeneous materials. To solve this problem, we propose an augmented multidimensional diffusion encoding (MDE) framework, which unlocks a novel encoding dimension to assess time-dependent diffusion specific to structures with different microscopic anisotropies. Our approach relies on spectral analysis of complex but experimentally efficient MDE waveforms. Two independent contrasts to differentiate features such as cell shape and size can be generated directly by signal subtraction from only three types of measurements. Analytical calculations and simulations support our experimental observations. Proof-of-concept experiments were applied on samples with known and distinctly different microstructures. We further demonstrate substantially different contrasts in different tissue types of a post mortem brain. Our simultaneous assessment of restriction size and shape may be instrumental in studies of a wide range of porous materials, enable new insights into the microstructure of biological tissues or be of great value in diagnostics.
| S-EPMC6588609 | biostudies-literature
Project description: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.
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Project description:The recently developed oscillating-gradient diffusion MRI (OG-dMRI) technique extends our ability to examine brain structures at different spatial scales. In this study, we investigated the sensitivity of OG-dMRI in detecting cellular and subcellular structural changes in a mouse model of neonatal hypoxia ischemia (HI). Neonatal mice received unilateral HI injury or sham injury at postnatal day 10, followed by in vivo T2-weighted and diffusion MRI of the brains at 3-6 h and 24 h after HI. Apparent diffusion coefficient (ADC) maps were acquired using conventional pulsed-gradient dMRI (PG-dMRI) and OG-dMRI with oscillating frequencies from 50 to 200 Hz. Pathology at cellular and subcellular levels was evaluated using neuronal, glial, and mitochondrial markers. We found significantly higher rates of ADC increase with oscillating frequencies (ΔfADC) in the ipsilateral edema region, compared to the contralateral side, starting as early as 3 h after HI. Even in injured regions that showed no apparent change in PG-ADC or pseudo-normalized PG-ADC measurements, ΔfADC remained significantly elevated. Histopathology showed swelling of sub-cellular structures in these regions with no apparent whole-cell level change. These results suggest that OG-dMRI is sensitive to subcellular structural changes in the brain after HI and is less susceptible to pseudo-normalization than PG-dMRI.
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Project description:PURPOSE:To improve velocity-to-noise ratio (VNR) and dynamic velocity range of 4D flow magnetic resonance imaging (MRI) by using dual-velocity encoding (dual-venc) with k-t generalized autocalibrating partially parallel acquisition (GRAPPA) acceleration. MATERIALS AND METHODS:A dual-venc 4D flow MRI sequence with k-t GRAPPA acceleration was developed using a shared reference scan followed by three-directional low- and high-venc scans (repetition time / echo time / flip angle?=?6.1 msec / 3.4 msec / 15°, temporal/spatial resolution?=?43.0 msec/1.2 × 1.2 × 1.2?mm3 ). The high-venc data were used to correct for aliasing in the low-venc data, resulting in a single dataset with the favorable VNR of the low-venc but without velocity aliasing. The sequence was validated with a 3T MRI scanner in phantom experiments and applied in 16 volunteers to investigate its feasibility for assessing intracranial hemodynamics (net flow and peak velocity) at the major intracranial vessels. In addition, image quality and image noise were assessed in the in vivo acquisitions. RESULTS:All 4D flow MRI scans were acquired successfully with an acquisition time of 20?±?4 minutes. The shared reference scan reduced the total acquisition time by 12.5% compared to two separate scans. Phantom experiments showed 51.4% reduced noise for dual-venc compared to high-venc and an excellent agreement of velocities (??=?0.8, P < 0.001). The volunteer data showed decreased noise in dual-venc data (54.6% lower) compared to high-venc, and improved image quality, as graded by two observers: fewer artifacts (P < 0.0001), improved vessel conspicuity (P < 0.0001), and reduced noise (P < 0.0001). CONCLUSION:Dual-venc 4D flow MRI exhibits the superior VNR of the low-venc acquisition and reliably incorporates low- and high-velocity fields simultaneously. In vitro and in vivo data demonstrate improved flow visualization, image quality, and image noise. LEVEL OF EVIDENCE:2 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:102-114.
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Project description:PurposeThe analysis of diffusion data obtained under large gradient nonlinearities necessitates corrections during data reconstruction and analysis. While two such preprocessing pipelines have been proposed, no comparative studies assessing their performance exist. Furthermore, both pipelines neglect the impact of subject motion during acquisition, which, in the presence of gradient nonlinearities, induces spatio-temporal B-matrix variations. Here, spatio-temporal B-matrix tracking (STB) is proposed and its performance compared to established pipelines.MethodsDiffusion tensor MRI (DT-MRI) was performed using a 300 mT/m gradient system. Data were acquired with volunteers positioned in regions with pronounced gradient nonlinearities, and used to compare the performance of six different processing pipelines, including STB.ResultsUp to 30% errors were observed in DT-MRI parameter estimates when neglecting gradient nonlinearities. Moreover, the order in which B0 inhomogeneity, eddy current and gradient nonlinearity corrections were performed was found to impact the consistency of parameter estimates significantly. Although, no pipeline emerged as a clear winner, the STB approach seemed to yield the most consistent parameter estimates under large gradient nonlinearities.ConclusionsUnder large gradient nonlinearities, the choice of preprocessing pipeline significantly impacts the estimated diffusion parameters. Motion-induced spatio-temporal B-matrix variations can lead to systematic bias in the parameter estimates, that can be ameliorated using the proposed STB framework.
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