Water diffusion in rat brain in vivo as detected at very large b values is multicompartmental

Metabolic activity diffusion imaging (MADI): II. Noninvasive, high-resolution human brain mapping of sodium pump flux and cell metrics

We introduce a new ¹ H₂ O magnetic resonance approach: metabolic activity diffusion imaging (MADI). Numerical diffusion-weighted imaging decay simulations characterized by the mean cellular water efflux (unidirectional) rate constant (k_io ), mean cell volume (V), and cell number density (ρ) are produced from Monte Carlo random walks in virtual stochastically sized/shaped cell ensembles. Because of active steady-state trans-membrane water cycling (AWC), k_io reflects the cytolemmal Na⁺ , K⁺ ATPase (NKA) homeostatic cellular metabolic rate (^c MR_NKA ). A digital 3D "library" contains thousands of simulated single diffusion-encoded (SDE) decays. Library entries match well with disparate, animal, and human experimental SDE decays. The V and ρ values are consistent with estimates from pertinent in vitro cytometric and ex vivo histopathological literature: in vivo V and ρ values were previously unavailable. The library allows noniterative pixel-by-pixel experimental SDE decay library matchings that can be used to advantage. They yield proof-of-concept MADI parametric mappings of the awake, resting human brain. These reflect the tissue morphology seen in conventional MRI. While V is larger in gray matter (GM) than in white matter (WM), the reverse is true for ρ. Many brain structures have k_io values too large for current, invasive methods. For example, the median WM k_io is 22s^-1 ; likely reflecting mostly exchange within myelin. The k_io •V product map displays brain tissue ^c MR_NKA variation. The GM activity correlates, quantitatively and qualitatively, with the analogous resting-state brain ¹⁸ FDG-PET tissue glucose consumption rate (^t MR_glucose ) map; but noninvasively, with higher spatial resolution, and no pharmacokinetic requirement. The cortex, thalamus, putamen, and caudate exhibit elevated metabolic activity. MADI accuracy and precision are assessed. The results are contextualized with literature overall homeostatic brain glucose consumption and ATP production/consumption measures. The MADI/PET results suggest different GM and WM metabolic pathways. Preliminary human prostate results are also presented.

Metabolic activity diffusion imaging (MADI): I. Metabolic, cytometric modeling and simulations

Evidence mounts that the steady-state cellular water efflux (unidirectional) first-order rate constant (k_io [s^-1 ]) magnitude reflects the ongoing, cellular metabolic rate of the cytolemmal Na⁺ , K⁺ -ATPase (NKA), ^c MR_NKA (pmol [ATP consumed by NKA]/s/cell), perhaps biology's most vital enzyme. Optimal ¹ H₂ O MR k_io determinations require paramagnetic contrast agents (CAs) in model systems. However, results suggest that the homeostatic metabolic k_io biomarker magnitude in vivo is often too large to be reached with allowable or possible CA living tissue distributions. Thus, we seek a noninvasive (CA-free) method to determine k_io in vivo. Because membrane water permeability has long been considered important in tissue water diffusion, we turn to the well-known diffusion-weighted MRI (DWI) modality. To analyze the diffusion tensor magnitude, we use a parsimoniously primitive model featuring Monte Carlo simulations of water diffusion in virtual ensembles comprising water-filled and -immersed randomly sized/shaped contracted Voronoi cells. We find this requires two additional, cytometric properties: the mean cell volume (V [pL]) and the cell number density (ρ [cells/μL]), important biomarkers in their own right. We call this approach metabolic activity diffusion imaging (MADI). We simulate water molecule displacements and transverse MR signal decays covering the entirety of b-space from pure water (ρ = V = 0; k_io undefined; diffusion coefficient, D₀ ) to zero diffusion. The MADI model confirms that, in compartmented spaces with semipermeable boundaries, diffusion cannot be described as Gaussian: the nanoscopic D (D_n ) is diffusion time-dependent, a manifestation of the "diffusion dispersion". When the "well-mixed" (steady-state) condition is reached, diffusion becomes limited, mainly by the probabilities of (1) encountering (ρ, V), and (2) permeating (k_io ) cytoplasmic membranes, and less so by D_n magnitudes. Importantly, for spaces with large area/volume (A/V; claustrophobia) ratios, this can happen in less than a millisecond. The model matches literature experimental data well, with implications for DWI interpretations.

Diffusion MRI with pulsed and free gradient waveforms: Effects of restricted diffusion and exchange

Monitoring time dependence with diffusion MRI yields observables sensitive to compartment sizes (restricted diffusion) and membrane permeability (water exchange). However, restricted diffusion and exchange have opposite effects on the diffusion-weighted signal, which can lead to errors in parameter estimates. In this work, we propose a signal representation that incorporates the effects of both restricted diffusion and exchange up to second order in b-value and is compatible with gradient waveforms of arbitrary shape. The representation features mappings from a gradient waveform to two scalars that separately control the sensitivity to restriction and exchange. We demonstrate that these scalars span a two-dimensional space that can be used to choose waveforms that selectively probe restricted diffusion or exchange, eliminating the correlation between the two phenomena. We found that waveforms with specific but unconventional shapes provide an advantage over conventional pulsed and oscillating gradient acquisitions. We also show that parametrization of waveforms into a two-dimensional space can be used to understand protocols from other approaches that probe restricted diffusion and exchange. For example, we found that the variation of mixing time in filter-exchange imaging corresponds to variation of our exchange-weighting scalar at a fixed value of the restriction-weighting scalar. The proposed signal representation was evaluated using Monte Carlo simulations in identical parallel cylinders with hexagonal and random packing as well as parallel cylinders with gamma-distributed radii. Results showed that the approach is sensitive to sizes in the interval 4-12 μm and exchange rates in the simulated range of 0 to 20 s - 1 , but also that there is a sensitivity to the extracellular geometry. The presented theory constitutes a simple and intuitive description of how restricted diffusion and exchange influence the signal as well as a guide to protocol design capable of separating the two effects.

Disentangling the effects of restriction and exchange with diffusion exchange spectroscopy

Diffusion exchange spectroscopy (DEXSY) is a multidimensional NMR technique that can reveal how water molecules exchange between compartments within heterogeneous media, such as biological tissue. Data from DEXSY experiments is typically processed using numerical inverse Laplace transforms (ILTs) to produce a diffusion-diffusion spectrum. A tacit assumption of this ILT approach is that the signal behavior is Gaussian - i.e., the spin echo intensity decays exponentially with the degree of diffusion weighting. The assumptions that underlie Gaussian signal behavior may be violated, however, depending on the gradient strength applied and the sample under study. We argue that non-Gaussian signal behavior due to restrictions is to be expected in the study of biological tissue using diffusion NMR. Further, we argue that this signal behavior can produce confounding features in the diffusion-diffusion spectra obtained from numerical ILTs of DEXSY data - entangling the effects of restriction and exchange. Specifically, restricted signal behavior can result in broadening of peaks and in the appearance of illusory exchanging compartments with distributed diffusivities, which pearl into multiple peaks if not highly regularized. We demonstrate these effects on simulated data. That said, we suggest the use of features in the signal acquisition domain that can be used to rapidly probe exchange without employing an ILT. We also propose a means to characterize the non-Gaussian signal behavior due to restrictions within a sample using DEXSY measurements with a near zero mixing time or storage interval. We propose a combined acquisition scheme to independently characterize restriction and exchange with various DEXSY measurements, which we term Restriction and Exchange from Equally-weighted Double and Single Diffusion Encodings (REEDS-DE). We test this method on ex vivo neonatal mouse spinal cord - a sample consisting primarily of gray matter - using a low-field, static gradient NMR system. In sum, we highlight critical shortcomings of prevailing DEXSY analysis methods that conflate the effects of restriction and exchange, and suggest a viable experimental approach to disentangle them.

Attempts at the Characterization of In-Cell Biophysical Processes Non-Invasively-Quantitative NMR Diffusometry of a Model Cellular System

In the literature, diffusion studies of cell systems are usually limited to two water pools that are associated with the extracellular space and the entire interior of the cell. Therefore, the time-dependent diffusion coefficient contains information about the geometry of these two water regions and the water exchange through their boundary. This approach is due to the fact that most of these studies use pulse techniques and relatively low gradients, which prevents the achievement of high b-values. As a consequence, it is not possible to register the signal coming from proton populations with a very low bulk or apparent self-diffusion coefficient, such as cell organelles. The purpose of this work was to obtain information on the geometry and dynamics of water at a level lower than the cell size, i.e., in cellular structures, using the time-dependent diffusion coefficient method. The model of the cell system was made of baker’s yeast (Saccharomyces cerevisiae) since that is commonly available and well-characterized. We measured characteristic fresh yeast properties with the application of a compact Nuclear Magnetic Resonance (NMR)-Magritek Mobile Universal Surface Explorer (MoUSE) device with a very high, constant gradient (~24 T/m), which enabled us to obtain a sufficient stimulated echo attenuation even for very short diffusion times (0.2–40 ms) and to apply very short diffusion encoding times. In this work, due to a very large diffusion weighting (b-values), splitting the signal into three components was possible, among which one was associated only with cellular structures. Time-dependent diffusion coefficient analysis allowed us to determine the self-diffusion coefficients of extracellular fluid, cytoplasm and cellular organelles, as well as compartment sizes. Cellular organelles contributing to each compartment were identified based on the random walk simulations and approximate volumes of water pools calculated using theoretical sizes or molar fractions. Information about different cell structures is contained in different compartments depending on the diffusion regime, which is inherent in studies applying extremely high gradients.

Magnetic resonance measurements of cellular and sub-cellular membrane structures in live and fixed neural tissue

We develop magnetic resonance (MR) methods for real-time measurement of tissue microstructure and membrane permeability of live and fixed excised neonatal mouse spinal cords. Diffusion and exchange MR measurements are performed using the strong static gradient produced by a single-sided permanent magnet. Using tissue delipidation methods, we show that water diffusion is restricted solely by lipid membranes. Most of the diffusion signal can be assigned to water in tissue which is far from membranes. The remaining 25% can be assigned to water restricted on length scales of roughly a micron or less, near or within membrane structures at the cellular, organelle, and vesicle levels. Diffusion exchange spectroscopy measures water exchanging between membrane structures and free environments at 100 s^-1.

Glutamate diffusion in the rat brain in vivo under light and deep anesthesia conditions

PURPOSE

Glutamate (Glu) is the most abundant neurotransmitter in the human central nervous system and glutamatergic neurotransmission has been implicated in many common and severe neuropsychiatric disorders. In vivo MRS techniques have been developed to measure brain Glu concentration to investigate the pathophysiology of various brain disorders. However, it is difficult to interpret Glu signal changes because Glu plays multiple roles in the brain and is found in multiple microenvironments including cytosolic, vesicular, and extracellular.

METHODS

In vivo diffusion-weighted MRS (DW-MRS) with low to very high b-values was performed on the rat prefrontal cortex at 9.4T under both light and deep anesthetic conditions to examine Glu diffusion properties.

RESULTS

Significant alterations in Glu diffusion as well as reduced Glu concentration were observed under deep anesthesia compared with superficial anesthesia in the absence of similar changes in NAA or creatine.

CONCLUSION

The modifications in Glu diffusion under deep anesthesia might reflect changes in Glu microenvironment. The present work shows that Glu DW-MRS could be an important tool to explore Glu physiology with changing levels of neuronal activity and synaptic function.

Water mobility spectral imaging of the spinal cord: Parametrization of model-free Laplace MRI

Diffusion magnetic resonance imaging (dMRI) of biological systems most often results in non-monoexponential signal, due to their complexity and heterogeneity. One approach to interpreting dMRI data without imposing tissue microstructural models is to fit the signal to a multiexponential function, which is sometimes referred to as an inverse Laplace transformation, and to display the coefficients as a distribution of the diffusivities, or water mobility spectra. Until recently, this method has not been used in a voxelwise manner, mainly because of heavy data requirements. With recent advancements in processing and experimental design, voxelwise Laplace MRI approaches are becoming feasible and attractive. The rich spectral information, combined with a three-dimensional image, presents a challenge because it tremendously increases the dimensionality of the data and requires a robust method for interpretation and analysis. In this work, we suggest parameterizing the empirically measured water mobility spectra using a bimodal lognormal function. This approach allows for a compact representation of the spectrum, and it also resolves overlapping spectral peaks, which allows for a robust extraction of their signal fraction. We apply the method on a fixed spinal cord sample and use it to generate robust intensity images of slow- and fast-diffusion components. Using the parametric variables, we create novel image contrasts, among them the information entropy of the water mobility spectrum, which pack unique features of the individual diffusion regimes in the investigated system.

Efficient experimental designs for isotropic generalized diffusion tensor MRI (IGDTI)

PURPOSE

We propose a new generalized diffusion tensor imaging (GDTI) experimental design and analysis framework for efficiently measuring orientationally averaged diffusion-weighted images (DWIs), which remove bulk signal modulations attributed to diffusion anisotropy and quantify isotropic higher-order diffusion tensors (HOT). We illustrate how this framework accelerates the clinical measurement of rotation-invariant tissue microstructural parameters derived from HOT, such as the HOT-Trace and the mean t-kurtosis.

THEORY AND METHODS

For a large range of b-values, we compare orientationally averaged DWIs measured with high angular resolution diffusion imaging to those obtained with the proposed isotropic GDTI (IGDTI) experimental design. We compare rotation-invariant microstructural parameters measured with IGDTI to those derived from HOTs measured explicitly with GDTI.

RESULTS

In both fixed-brain microimaging and in vivo clinical experiments, IGDTI accurately quantifies mean apparent diffusion coefficient (mADC)-weighted DWIs over a wide range of b-values and allows efficient computation of HOT-derived scalar tissue parameters from a small number of DWIs.

CONCLUSIONS

IGDTI provides direct and accurate estimates of orientationally averaged tissue water mobilities over a wide range of b-values. This efficient method may enable new, sensitive, and quantitative assessments for clinical applications in which changes in mADC can be observe,d such as detecting and characterizing stroke, cancers, and neurodegenerative diseases. Magn Reson Med 79:180-194, 2018. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

On a fractional order calculus model in diffusion weighted breast imaging to differentiate between malignant and benign breast lesions detected on X-ray screening mammography

OBJECTIVE

To evaluate a fractional order calculus (FROC) model in diffusion weighted imaging to differentiate between malignant and benign breast lesions in breast cancer screening work-up using recently introduced parameters (βFROC, DFROC and μFROC).

MATERIALS AND METHODS

This retrospective analysis within a prospective IRB-approved study included 51 participants (mean 58.4 years) after written informed consent. All patients had suspicious screening mammograms and indication for biopsy. Prior to biopsy, full diagnostic contrast-enhanced MRI examination was acquired including diffusion-weighted-imaging (DWI, b = 0,100,750,1500 s/mm2). Conventional apparent diffusion coefficient Dapp and FROC parameters (βFROC, DFROC and μFROC) as suggested further indicators of diffusivity components were measured in benign and malignant lesions. Receiver operating characteristics (ROC) were calculated to evaluate the diagnostic performance of the parameters.

RESULTS

29/51 patients histopathologically revealed malignant lesions. The analysis revealed an AUC for Dapp of 0.89 (95% CI 0.80-0.98). For FROC derived parameters, AUC was 0.75 (0.60-0.89) for DFROC, 0.59 (0.43-0.75) for βFROC and 0.59 (0.42-0.77) for μFROC. Comparison of the AUC curves revealed a significantly higher AUC of Dapp compared to the FROC parameters DFROC (p = 0.009), βFROC (p = 0.003) and μFROC (p = 0.001).

CONCLUSION

In contrast to recent description in brain tumors, the apparent diffusion coefficient Dapp showed a significantly higher AUC than the recently proposed FROC parameters βFROC, DFROC and μFROC for differentiating between malignant and benign breast lesions. This might be related to the intrinsic high heterogeneity within breast tissue or to the lower maximal b-value used in our study.

Early Changes in Glutamate Metabolism and Perfusion in Basal Ganglia following Hypoxia-Ischemia in Neonatal Piglets: A Multi-Sequence 3.0T MR Study

The excitotoxicity of glutamate metabolism as well as hemodynamic disorders of the brain are both risk factors for neonatal hypoxic–ischemic brain damage (HIBD). In the present study, changes in glutamate metabolism in the basal ganglia were detected by proton magnetic resonance spectroscopy (¹H-MRS) at 0–6, 8–12, 24–30, and 48–60 h after the induction of hypoxia-ischemia (HI) in newborn piglets. Meanwhile, correlation analysis was performed by combining the microcirculatory perfusion informations acquired by intravoxel incoherent motion (IVIM) scan to explore their possible interaction mechanism. The results suggested that Glu level in the basal ganglia underwent a “two-phase” change after HI; perfusion fraction f, an IVIM-derived perfusion parameter, was clearly decreased in the early stage after HI, then demonstrated a transient and slight recovery process, and thereafter continued to decrease. The changes in f and Glu level were in a significant negative correlation (r = −0.643, P = 0.001). Our study results revealed that Glu level is closely associated with the microcirculatory perfusion changes in the acute stage of HIBD.

In vivo mapping of human spinal cord microstructure at 300mT/m

The ability to characterize white matter microstructure non-invasively has important applications for the diagnosis and follow-up of several neurological diseases. There exists a family of diffusion MRI techniques, such as AxCaliber, that provide indices of axon microstructure, such as axon diameter and density. However, to obtain accurate measurements of axons with small diameters (<5μm), these techniques require strong gradients, i.e. an order of magnitude higher than the 40-80mT/m currently available in clinical systems. In this study we acquired AxCaliber diffusion data at a variety of different q-values and diffusion times in the spinal cord of five healthy subjects using a 300mT/m whole body gradient system. Acquisition and processing were optimized using state-of-the-art methods (e.g., 64-channel coil, template-based analysis). Results consistently show an average axon diameter of 4.5+/-1.1μm in the spinal cord white matter. Diameters ranged from 3.0μm (gracilis) to 5.9μm (spinocerebellar tracts). Values were similar across laterality (left-right), but statistically different across spinal cord pathways (p<10(-5)). The observed trends are similar to those observed in animal histology. This study shows, for the first time, in vivo mapping of axon diameter in the spinal cord at 300mT/m, thus creating opportunities for applications in spinal cord diseases.

Accuracies and Contrasts of Models of the Diffusion-Weighted-Dependent Attenuation of the MRI Signal at Intermediate b-values

The diffusion-weighted-dependent attenuation of the MRI signal E(b) is extremely sensitive to microstructural features. The aim of this study was to determine which mathematical model of the E(b) signal most accurately describes it in the brain. The models compared were the monoexponential model, the stretched exponential model, the truncated cumulant expansion (TCE) model, the biexponential model, and the triexponential model. Acquisition was performed with nine b-values up to 2500 s/mm² in 12 healthy volunteers. The goodness-of-fit was studied with F-tests and with the Akaike information criterion. Tissue contrasts were differentiated with a multiple comparison corrected nonparametric analysis of variance. F-test showed that the TCE model was better than the biexponential model in gray and white matter. Corrected Akaike information criterion showed that the TCE model has the best accuracy and produced the most reliable contrasts in white matter among all models studied. In conclusion, the TCE model was found to be the best model to infer the microstructural properties of brain tissue.

Early metabolic changes following ischemia onset in rats: an in vivo diffusion-weighted imaging and 1H-magnetic resonance spectroscopy study at 7.0 T

Despite improvements in imaging techniques, it remains challenging to quantitatively assess the time of ischemic onset of an acute ischemic stroke. It is crucial to evaluate the early signs of infarction, which are predictive of responses to recombinant tissue plasminogen activator within a treatment window of 4.5 h after stroke induction. The aim of the present study was to assess and quantify the onset time for hyperacute middle cerebral artery occlusion (MCAO) ischemic stroke by measuring the apparent diffusion coefficient (ADC) of diffusion‑weighted imaging (DWI) and 1H‑magnetic resonance spectroscopy (MRS) at 7.0 T. DWI, conventional T2‑weighted imaging (T2WI) and subsequent focal ADCs were employed to evaluate ischemic brain lesions in a rat model of MCAO (n=20) at different time‑points following a stroke. A quantitation of local changes in metabolite concentrations within the lesions was performed using MRS. Proton metabolites were quantified automatically using LCModel software. At 30 min after MCAO, intense signals were observed in the DWI spectra of all animals. No abnormal signal was observed within 3 h by T2WI. ADC images of the central area, peripheral striping and on the fringes of the infarction demonstrated a lower signal than that of the normal side. The ADC decreased significantly within 30 min after infarction, followed by a gradual elevation in volatility levels and then becoming relatively stable at a lower level 3 h later. MRS exhibited a consistent elevation of lactate and reduced N‑acetyl aspartic acid. Glutamate and taurine reached a maximum 2 h after MCAO and began to decrease 1 h later. In conclusion, the present study demonstrated that hyperacute ischemic stroke can be quantitatively detected with the application of ADC, DWI and MRS. These methods may also be used to quantitatively assess the ischemic onset time of a hyperacute stroke.

The role of tissue microstructure and water exchange in biophysical modelling of diffusion in white matter

Biophysical models that describe the outcome of white matter diffusion MRI experiments have various degrees of complexity. While the simplest models assume equal-sized and parallel axons, more elaborate ones may include distributions of axon diameters and axonal orientation dispersions. These microstructural features can be inferred from diffusion-weighted signal attenuation curves by solving an inverse problem, validated in several Monte Carlo simulation studies. Model development has been paralleled by microscopy studies of the microstructure of excised and fixed nerves, confirming that axon diameter estimates from diffusion measurements agree with those from microscopy. However, results obtained in vivo are less conclusive. For example, the amount of slowly diffusing water is lower than expected, and the diffusion-encoded signal is apparently insensitive to diffusion time variations, contrary to what may be expected. Recent understandings of the resolution limit in diffusion MRI, the rate of water exchange, and the presence of microscopic axonal undulation and axonal orientation dispersions may, however, explain such apparent contradictions. Knowledge of the effects of biophysical mechanisms on water diffusion in tissue can be used to predict the outcome of diffusion tensor imaging (DTI) and of diffusion kurtosis imaging (DKI) studies. Alterations of DTI or DKI parameters found in studies of pathologies such as ischemic stroke can thus be compared with those predicted by modelling. Observations in agreement with the predictions strengthen the credibility of biophysical models; those in disagreement could provide clues of how to improve them. DKI is particularly suited for this purpose; it is performed using higher b-values than DTI, and thus carries more information about the tissue microstructure. The purpose of this review is to provide an update on the current understanding of how various properties of the tissue microstructure and the rate of water exchange between microenvironments are reflected in diffusion MRI measurements. We focus on the use of biophysical models for extracting tissue-specific parameters from data obtained with single PGSE sequences on clinical MRI scanners, but results obtained with animal MRI scanners are also considered. While modelling of white matter is the central theme, experiments on model systems that highlight important aspects of the biophysical models are also reviewed.

Anomalous diffusion measured by a twice-refocused spin echo pulse sequence: analysis using fractional order calculus

PURPOSE

To theoretically develop and experimentally validate a formulism based on a fractional order calculus (FC) diffusion model to characterize anomalous diffusion in brain tissues measured with a twice-refocused spin-echo (TRSE) pulse sequence.

MATERIALS AND METHODS

The FC diffusion model is the fractional order generalization of the Bloch-Torrey equation. Using this model, an analytical expression was derived to describe the diffusion-induced signal attenuation in a TRSE pulse sequence. To experimentally validate this expression, a set of diffusion-weighted (DW) images was acquired at 3 Tesla from healthy human brains using a TRSE sequence with twelve b-values ranging from 0 to 2600 s/mm(2). For comparison, DW images were also acquired using a Stejskal-Tanner diffusion gradient in a single-shot spin-echo echo planar sequence. For both datasets, a Levenberg-Marquardt fitting algorithm was used to extract three parameters: diffusion coefficient D, fractional order derivative in space β, and a spatial parameter μ (in units of μm). Using adjusted R-squared values and standard deviations, D, β, and μ values and the goodness-of-fit in three specific regions of interest (ROIs) in white matter, gray matter, and cerebrospinal fluid, respectively, were evaluated for each of the two datasets. In addition, spatially resolved parametric maps were assessed qualitatively.

RESULTS

The analytical expression for the TRSE sequence, derived from the FC diffusion model, accurately characterized the diffusion-induced signal loss in brain tissues at high b-values. In the selected ROIs, the goodness-of-fit and standard deviations for the TRSE dataset were comparable with the results obtained from the Stejskal-Tanner dataset, demonstrating the robustness of the FC model across multiple data acquisition strategies. Qualitatively, the D, β, and μ maps from the TRSE dataset exhibited fewer artifacts, reflecting the improved immunity to eddy currents.

CONCLUSION

The diffusion-induced signal attenuation in a TRSE pulse sequence can be described by an FC diffusion model at high b-values. This model performs equally well for data acquired from the human brain tissues with a TRSE pulse sequence or a conventional Stejskal-Tanner sequence.

Preliminary observations of increased diffusional kurtosis in human brain following recent cerebral infarction

By application of the MRI method of diffusional kurtosis imaging, a substantially increased diffusional kurtosis was observed within the cerebral ischemic lesions of three stroke subjects, 13-26 h following the onset of symptoms. This increase is interpreted as probably reflecting a higher degree of diffusional heterogeneity in the lesions when compared with normal-appearing contralateral tissue. In addition, for two of the subjects with white matter infarcts, the increase had a strong fiber tract orientational dependence. It is proposed that this effect is consistent with a large drop in the intra-axonal diffusivity, possibly related to either axonal varicosities or alterations associated with the endoplasmic reticulum.

Apparent exchange rate mapping with diffusion MRI

Water exchange through the cell membranes is an important feature of cells and tissues. The rate of exchange is determined by factors such as membrane lipid composition and organization, as well as the type and activity of aquaporins. A method for noninvasively estimating the rate of water exchange would be useful for characterizing pathological conditions, e.g., tumors, multiple sclerosis, and ischemic stroke, expected to be associated with a change of the membrane barrier properties. This study describes the filter exchange imaging method for determining the rate of water exchange between sites having different apparent diffusion coefficients. The method is based on the filter-exchange pulsed gradient spin-echo NMR spectroscopy experiment, which is here modified to be compatible with the constraints of clinical MR scanners. The data is analyzed using a model-free approach yielding maps of the apparent exchange rate, here being introduced in analogy with the concept of the apparent diffusion coefficient. Proof-of-principle experiments are performed on microimaging and whole-body clinical scanners using yeast suspension phantoms. The limitations and appropriate experimental conditions are examined. The results demonstrate that filter exchange imaging is a fast and reliable method for characterizing exchange, and that it has the potential to become a powerful diagnostic tool.

Effect of diffusion-sensitizing gradient timings on the exponential, biexponential and diffusional kurtosis model parameters: in-vivo measurements in the rat thalamus

OBJECT

To investigate whether spacing (Delta) and duration (delta) of the diffusion-sensitizing gradient pulses differentially affect exponential (D'), biexponential (D (slow), D (fast) and f (slow)) and diffusional kurtosis (D and K) model parameters.

METHODS

Measurements were performed in the rat thalamus for b = 200-3,200 s mm(-2), sweeping Delta between 20 and 100 ms at delta = 15 ms, and delta between 15 and 50 ms at Delta = 60 ms. Linear regressions were performed for each model parameter vs. Delta or delta.

RESULTS

Increasing Delta from 20 to 100 ms increases D' (from 0.64 to 0.70 x 10(-3) mm(2)s(-1)) and D (slow) (from 0.26 to 0.33 x 10(-3) mm(2)s(-1)), reduces K (from 0.57 to 0.53), and has no effects on D (fast), f (slow) or D. Increasing delta from 15 to 50 ms increases D (from 0.80 to 0.88 x 10(-3) mm(2)s(-1)), and has no effects on the other parameters.

CONCLUSION

The parameters of the biexponential and diffusional kurtosis models are more sensitive than the exponential model to Delta and delta; however, observed effects are too small to account for the discrepancies found in literature.

On high b diffusion imaging in the human brain: ruminations and experimental insights

Interest in the manner in which brain tissue signal decays with b factor in diffusion imaging schemes has grown in recent years following the observation that the decay curves depart from purely monoexponential decay behavior. Regardless of the model or fitting function proposed for characterizing sufficiently sampled decay curves (vide infra), the departure from monoexponentiality spells increased tissue characterization potential. The degree to which this potential can be harnessed to improve specificity, sensitivity and spatial localization of diseases in brain, and other tissues, largely remains to be explored. Furthermore, the degree to which currently popular diffusion tensor imaging methods, including visually impressive white matter fiber "tractography" results, have almost completely ignored the nonmonoexponential nature of the basic signal decay with b factor is worthy of communal introspection. Here we limit our attention to a review of the basic experimental features associated with brain water signal diffusion decay curves as measured over extended b-factor ranges, the simple few parameter fitting functions that have been proposed to characterize these decays and the more involved models, e.g.,"ruminations," which have been proposed to account for the nonmonoexponentiality to date.

High b-value diffusion tensor imaging of the neonatal brain at 3T

BACKGROUND AND PURPOSE

Diffusion-weighted MR imaging studies of the adult brain have shown that contrast between lesions and normal tissue is increased at high b-values. We designed a prospective study to test the hypothesis that diffusion tensor imaging (DTI) obtained at high b-values increases image contrast and lesion conspicuity in the neonatal brain.

MATERIALS AND METHODS

We studied 17 neonates, median (range) age of 10 (2-96) days, who were undergoing MR imaging for clinical indications. DTI was performed on a Philips 3T Intera system with b-values of 350, 700, 1500, and 3000 s/mm(2). Image contrast and lesion conspicuity at each b-value were visually assessed. In addition, regions of interest were positioned in the central white matter at the level of the centrum semiovale, frontal and occipital white matter, splenium of the corpus callosum, posterior limb of the internal capsule, and the thalamus. Apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values for these regions were calculated.

RESULTS

Isotropic diffusion image contrast and lesion-to-normal-tissue contrast increased with increasing b-value. ADC values decreased with increasing b-value in all regions studied; however, there was no change in FA with increasing b-value.

CONCLUSIONS

Diffusion image contrast increased at high b-values may be useful in identifying lesions in the neonatal brain.

ADC measurements at low and high b values: insight into normal brain structure with clinical DWI

PURPOSE

To demonstrate drop in brain ADC measurements from low to high b values; to evaluate the structural information provided based on those changes; and to discuss the anatomical reasons for ADC differences.

METHODS

Four cerebral ROI (precuneus-PRC, hippocampus-HIP, and the genu-GCC and splenium-SCC of the corpus callosum-CC) were drawn for ADC measurements with low (1000) and high (3000) b-value DWI in 50 normal subjects. ANOVA and Bonferroni correction tested ADC differences between areas, between both hemispheres, between GCC and SCC, and between b-value related ADC drop within areas. Pearson test evaluated dependence of interhemispheric and intercallosum ADC measurements obtained with the same b-value, dependence between areas of intrazonal drop, and the interhemispheric and intercallosum dependence of intrazonal drop.

RESULTS

ADCs differed between areas (P<.0001). Interhemispheric ADC only differed in PRC with low b-value (P<.027). No HIP asymmetries occurred regardless the b-value. ADC drop within PRC and HIP was similar but differed (P<.0001) from ADC drop within both CC ROI. ADC drop was also different between GCC and SCC (P<.0001). In PRC and HIP, ADC showed a significant interhemispheric and intrazonal dependence (P<.0001). There was no GCC to SCC ADC dependence. Intrazonal dependence in the CC was only significant in the SCC (P<.001). Interhemispheric dependence of intrazonal drop was significant (PRC P=.007; HIP P<.0001) but failed to reach significance in the CC.

CONCLUSION

Low and high b-value measurements show different diffusion behaviours within different tissues, especially in a highly anisotropic structure as the corpus callosum. This fact can provide valuable information about brain structure and different diffusion compartments in clinical DWI.

Investigation of multicomponent diffusion in cat brain using a combined MTC–DWI approach

In this study, multiple-component water diffusion in the cat brain is investigated using an approach that combines diffusion-weighted images using multiple b values with magnetization transfer contrast (MTC). The MTC allows filter of signal originating from water molecules that rapidly exchange with binding sites on large macromolecular structures, and in brain white matter, it is assumed that a significant portion of the MTC is due to the interaction of water with the extraaxonal myelin sheath. Henceforth, multicomponent analysis of diffusion curves with and without MTC may shed light on the contribution of the extraaxonal water to the diffusion signal and on the relationship between diffusion components and tissue compartments in the brain. When a biexponential model was applied to the data, the volume fractions of the two diffusion components changed significantly in white matter with the application of the MTC. These changes are then discussed in the frame of tissue components and the possible interaction with the myelin sheath.

Analysis of the distribution of diffusion coefficients in cat brain at 9.4 T using the inverse Laplace transformation

In this work, the usefulness of the inverse Laplace transformation (ILT) in the characterization of diffusion processes in the brain has been investigated. The method has been implemented on both phantom and in vivo cat brain data acquired at high resolution at 9.4 T. The results were compared with monoexponential and biexponential analyses of the same data. It is shown that in the case of diffusion restricted by white matter axonal tracts, the resulting diffusograms are in good agreement with the biexponential model. In gray matter, however, the non-monoexponential decay does not lead to a bimodal distribution in the ILT, even though the data can be fitted to a biexponential. This finding suggests the possibility of a distribution of diffusion coefficients rather than a discrete biexponential behavior. It is shown that this distribution is sensitive, for example, to experimental parameters such as the diffusion time. Thus, the ILT offers the possibility of implementing a unique tool for the analysis of heterogeneous diffusion, that is, the analysis of the diffusion coefficient distribution, which has the yet unexplored potential of being a valuable parameter in the characterization of tissue structure.

Detection of intracellular lactate with localized diffusion {1H-13C}-spectroscopy in rat glioma in vivo

The aim of this study was to compare the diffusion characteristic of lactate and alanine in a brain tumor model to that of normal brain metabolites known to be mainly intracellular such as N-acetylaspartate or creatine. The diffusion of (13)C-labeled metabolites was measured in vivo with localized NMR spectroscopy at 9.4 T (400 MHz) using a previously described localization and editing pulse sequence known as ACED-STEAM ('adiabatic carbon editing and decoupling'). (13)C-labeled glucose was administered and the apparent diffusion coefficients of the glycolytic products, {(1)H-(13)C}-lactate and {(1)H-(13)C}-alanine, were determined in rat intracerebral 9L glioma. To obtain insights into {(1)H-(13)C}-lactate compartmentation (intra- versus extracellular), the pulse sequence used very large diffusion weighting (50 ms/microm(2)). Multi-exponential diffusion attenuation of the lactate metabolite signals was observed. The persistence of a lactate signal at very large diffusion weighting provided direct experimental evidence of significant intracellular lactate concentration. To investigate the spatial distribution of lactate and other metabolites, (1)H spectroscopic images were also acquired. Lactate and choline-containing compounds were consistently elevated in tumor tissue, but not in necrotic regions and surrounding normal-appearing brain. Overall, these findings suggest that lactate is mainly associated with tumor tissue and that within the time-frame of these experiments at least some of the glycolytic product ([(13)C] lactate) originates from an intracellular compartment.

Changes in extracellular space size and geometry in APP23 transgenic mice: a model of Alzheimer's disease

Diffusion parameters of the extracellular space (ECS) are changed in many brain pathologies, disturbing synaptic as well as extrasynaptic "volume" transmission, which is based on the diffusion of neuroactive substances in the ECS. Amyloid deposition, neuronal loss, and disturbed synaptic transmission are considered to be the main causes of Alzheimer's disease dementia. We studied diffusion parameters in the cerebral cortex of transgenic APP23 mice, which develop a pathology similar to Alzheimer's disease. The real-time tetramethylammonium (TMA) method and diffusion-weighted MRI were used to measure the ECS volume fraction (alpha = ECS volume/total tissue volume) and the apparent diffusion coefficients (ADCs) of TMA (ADC(TMA)), diffusing exclusively in the ECS and of water (ADC(W)). Measurements were performed in vivo in 6-, 8-, and 17- to 25-month-old hemizygous APP23 male and female mice and age-matched controls. In all 6- to 8-month-old APP23 mice, the mean ECS volume fraction, ADC(TMA), and ADC(W) were not significantly different from age-matched controls (alpha = 0.20 +/- 0.01; ADC(TMA), 580 +/- 16 microm(2).s(-1); ADC(W), 618 +/- 19 microm(2).s(-1)). Aging in 17- to 25-month-old controls was accompanied by a decrease in ECS volume fraction and ADC(W), significantly greater in females than in males, but no changes in ADC(TMA). ECS volume fraction increased (0.22 +/- 0.01) and ADC(TMA) decreased (560 +/- 7 microm(2).s(-1)) in aged APP23 mice. The impaired navigation observed in these animals in the Morris water maze correlated with their plaque load, which was twice as high in females (20%) as in males (10%) and may, together with changed ECS diffusion properties, account for the impaired extrasynaptic transmission and spatial cognition observed in old transgenic females.

Statistical model for diffusion attenuated MR signal

A general statistical model that can describe a rather large number of experimental results related to the structure of the diffusion-attenuated MR signal in biological systems is introduced. The theoretical framework relies on a phenomenological model that introduces a distribution function for tissue apparent diffusion coefficients (ADC). It is shown that at least two parameters--the position of distribution maxima (ADC) and the distribution width (sigma)--are needed to describe the MR signal in most regions of a human brain. A substantial distribution width, on the order of 36% of the ADC, was found for practically all brain regions examined. This method of modeling the MR diffusion measurement allows determination of an intrinsic tissue-specific ADC for a given diffusion time independent of the strength of diffusion sensitizing gradients. The model accounts for the previously found biexponential behavior of the diffusion-attenuated MR signal in CNS.

Biexponential apparent diffusion coefficient parametrization in adult vs newborn brain

The decay of brain water signal with b-factor in adult and newborn brains has been measured over an extended b-factor range. Measurements of the apparent diffusion coefficient (ADC) decay curves were made at 16 b-factors from 100 to 5000 s/mm(2) along three orthogonal directions using a line scan diffusion imaging (LSDI) sequence to acquire data from 0.09 ml voxels in a mid-brain axial slice. Regions-of-interest (ROIs) in cortical gray (CG) and white matter in the internal capsule (IC) were selected for ADC decay curve analyses using a biexponential fitting model over this extended b-factor range. Measures of the fast and slow ADC component amplitudes and the traces of the fast and slow diffusion coefficients were obtained from CG and IC ROIs in both adults and newborns. The ADC decay curves from the newborn brain regions were found to have a significantly higher fraction of the fast diffusion ADC component than corresponding regions in the adult brain. The results demonstrate that post-natal brain development has a profound affect on the biexponential parameters which characterize the decay of water signal over an extended b-factor range in both gray and white matter.