Transverse relaxation in rat optic nerve

Beyond the diffusion standard model in fixed rat spinal cord with combined linear and planar encoding

Information about tissue on the microscopic and mesoscopic scales can be accessed by modelling diffusion MRI signals, with the aim of extracting microstructure-specific biomarkers. The standard model (SM) of diffusion, currently the most broadly adopted microstructural model, describes diffusion in white matter (WM) tissues by two Gaussian components, one of which has zero radial diffusivity, to represent diffusion in intra- and extra-axonal water, respectively. Here, we reappraise these SM assumptions by collecting comprehensive double diffusion encoded (DDE) MRI data with both linear and planar encodings, which was recently shown to substantially enhance the ability to estimate SM parameters. We find however, that the SM is unable to account for data recorded in fixed rat spinal cord at an ultrahigh field of 16.4 T, suggesting that its underlying assumptions are violated in our experimental data. We offer three model extensions to mitigate this problem: first, we generalize the SM to accommodate finite radii (axons) by releasing the constraint of zero radial diffusivity in the intra-axonal compartment. Second, we include intracompartmental kurtosis to account for non-Gaussian behaviour. Third, we introduce an additional (third) compartment. The ability of these models to account for our experimental data are compared based on parameter feasibility and Bayesian information criterion. Our analysis identifies the three-compartment description as the optimal model. The third compartment exhibits slow diffusion with a minor but non-negligible signal fraction (∼12%). We demonstrate how failure to take the presence of such a compartment into account severely misguides inferences about WM microstructure. Our findings bear significance for microstructural modelling at large and can impact the interpretation of biomarkers extracted from the standard model of diffusion.

Non-negative least squares computation for in vivo myelin mapping using simulated multi-echo spin-echo T2 decay data

Multi-compartment T₂ mapping has gained particular relevance for the study of myelin water in the brain. As a facilitator of rapid saltatory axonal signal transmission, myelin is a cornerstone indicator of white matter development and function. Regularized non-negative least squares fitting of multi-echo T₂ data has been widely employed for the computation of the myelin water fraction (MWF), and the obtained MWF maps have been histopathologically validated. MWF measurements depend upon the quality of the data acquisition, B₁⁺ homogeneity and a range of fitting parameters. In this special issue article, we discuss the relevance of these factors for the accurate computation of multi-compartment T₂ and MWF maps. We generated multi-echo spin-echo T₂ decay curves following the Carr-Purcell-Meiboom-Gill approach for various myelin concentrations and myelin T₂ scenarios by simulating the evolution of the magnetization vector between echoes based on the Bloch equations. We demonstrated that noise and imperfect refocusing flip angles yield systematic underestimations in MWF and intra-/extracellular water geometric mean T₂ (gmT₂ ). MWF estimates were more stable than myelin water gmT₂ time across different settings of the T₂ analysis. We observed that the lower limit of the T₂ distribution grid should be slightly shorter than TE₁ . Both TE₁ and the acquisition echo spacing also have to be sufficiently short to capture the rapidly decaying myelin water T₂ signal. Among all parameters of interest, the estimated MWF and intra-/extracellular water gmT₂ differed by approximately 0.13-4 percentage points and 3-4 ms, respectively, from the true values, with larger deviations observed in the presence of greater B₁⁺ inhomogeneities and at lower signal-to-noise ratio. Tailoring acquisition strategies may allow us to better characterize the T₂ distribution, including the myelin water, in vivo.

Towards unconstrained compartment modeling in white matter using diffusion-relaxation MRI with tensor-valued diffusion encoding

PURPOSE

To optimize diffusion-relaxation MRI with tensor-valued diffusion encoding for precise estimation of compartment-specific fractions, diffusivities, and T₂ values within a two-compartment model of white matter, and to explore the approach in vivo.

METHODS

Sampling protocols featuring different b-values (b), b-tensor shapes (b_Δ ), and echo times (TE) were optimized using Cramér-Rao lower bounds (CRLB). Whole-brain data were acquired in children, adults, and elderly with white matter lesions. Compartment fractions, diffusivities, and T₂ values were estimated in a model featuring two microstructural compartments represented by a "stick" and a "zeppelin."

RESULTS

Precise parameter estimates were enabled by sampling protocols featuring seven or more "shells" with unique b/b_Δ /TE-combinations. Acquisition times were approximately 15 minutes. In white matter of adults, the "stick" compartment had a fraction of approximately 0.5 and, compared with the "zeppelin" compartment, featured lower isotropic diffusivities (0.6 vs. 1.3 μm² /ms) but higher T₂ values (85 vs. 65 ms). Children featured lower "stick" fractions (0.4). White matter lesions exhibited high "zeppelin" isotropic diffusivities (1.7 μm² /ms) and T₂ values (150 ms).

CONCLUSIONS

Diffusion-relaxation MRI with tensor-valued diffusion encoding expands the set of microstructure parameters that can be precisely estimated and therefore increases their specificity to biological quantities.

Diffusion time dependence of microstructural parameters in fixed spinal cord

Biophysical modelling of diffusion MRI is necessary to provide specific microstructural tissue properties. However, estimating model parameters from data with limited diffusion gradient strength, such as clinical scanners, has proven unreliable due to a shallow optimization landscape. On the other hand, estimation of diffusion kurtosis (DKI) parameters is more robust, and its parameters may be connected to microstructural parameters, given an appropriate biophysical model. However, it was previously shown that this procedure still does not provide sufficient information to uniquely determine all model parameters. In particular, a parameter degeneracy related to the relative magnitude of intra-axonal and extra-axonal diffusivities remains. Here we develop a model of diffusion in white matter including axonal dispersion and demonstrate stable estimation of all model parameters from DKI in fixed pig spinal cord. By employing the recently developed fast axisymmetric DKI, we use stimulated echo acquisition mode to collect data over a two orders of magnitude diffusion time range with very narrow diffusion gradient pulses, enabling finely resolved measurements of diffusion time dependence of both net diffusion and kurtosis metrics, as well as model intra- and extra-axonal diffusivities, and axonal dispersion. Our results demonstrate substantial time dependence of all parameters except volume fractions, and the additional time dimension provides support for intra-axonal diffusivity to be larger than extra-axonal diffusivity in spinal cord white matter, although not unambiguously. We compare our findings for the time-dependent compartmental diffusivities to predictions from effective medium theory with reasonable agreement.

TE dependent Diffusion Imaging (TEdDI) distinguishes between compartmental T2 relaxation times

Biophysical modeling of macroscopic diffusion-weighted MRI signal in terms of microscopic cellular parameters holds the promise of quantifying the integrity of white matter. Unfortunately, even fairly simple multi-compartment models of proton diffusion in the white matter do not provide a unique, biophysically plausible solution. Here we report a nontrivial diffusion MRI signal dependence on echo time (TE) in human white matter in vivo. We demonstrate that such TE dependence originates from compartment-specific T2 values and that it is a promising "orthogonal measure" able to break the degeneracy in parameter estimation, and to yield important relaxation metrics robustly. We thereby enable the precise estimation of the intra- and extra-axonal water T2 relaxation times, which is precluded by a limited signal-to-noise ratio when using multi-echo relaxometry alone.

Diffusional kurtosis imaging and white matter microstructure modeling in a clinical study of major depressive disorder

Major depressive disorder (MDD) is a globally prevalent psychiatric disorder that results from disruption of multiple neural circuits involved in emotional regulation. Although previous studies using diffusion tensor imaging (DTI) found smaller values of fractional anisotropy (FA) in the white matter, predominantly in the frontal lobe, of patients with MDD, studies using diffusion kurtosis imaging (DKI) are scarce. Here, we used DKI whole-brain analysis with tract-based spatial statistics (TBSS) to investigate the brain microstructural abnormalities in MDD. Twenty-six patients with MDD and 42 age- and sex-matched control subjects were enrolled. To investigate the microstructural pathology underlying the observations in DKI, a compartment model analysis was conducted focusing on the corpus callosum. In TBSS, the patients with MDD showed significantly smaller values of FA in the genu and frontal portion of the body of the corpus callosum. The patients also had smaller values of mean kurtosis (MK) and radial kurtosis (RK), but MK and RK abnormalities were distributed more widely compared with FA, predominantly in the frontal lobe but also in the parietal, occipital, and temporal lobes. Within the callosum, the regions with smaller MK and RK were located more posteriorly than the region with smaller FA. Model analysis suggested significantly smaller values of intra-neurite signal fraction in the body of the callosum and greater fiber dispersion in the genu, which were compatible with the existing literature of white matter pathology in MDD. Our results show that DKI is capable of demonstrating microstructural alterations in the brains of patients with MDD that cannot be fully depicted by conventional DTI. Though the issues of model validation and parameter estimation still remain, it is suggested that diffusion MRI combined with a biophysical model is a promising approach for investigation of the pathophysiology of MDD.

Inferring brain tissue composition and microstructure via MR relaxometry

MRI relaxometry is sensitive to a variety of tissue characteristics in a complex manner, which makes it both attractive and challenging for characterizing tissue. This article reviews the most common water proton relaxometry measures, T₁, T₂, and T₂^*, and reports on their development and current potential to probe the composition and microstructure of brain tissue. The development of these relaxometry measures is challenged by the need for suitably accurate tissue models, as well as robust acquisition and analysis methodologies. MRI relaxometry has been established as a tool for characterizing neural tissue, particular with respect to myelination, and the potential for further development exists.

Lysophosphatidyl Choline Induced Demyelination in Rat Probed by Relaxation along a Fictitious Field in High Rank Rotating Frame

In this work a new MRI modality entitled Relaxation Along a Fictitious Field in the rotating frame of rank 4 (RAFF4) was evaluated in its ability to detect lower myelin content in lysophosphatidyl choline (LPC)-induced demyelinating lesions. The lesions were induced in two areas of the rat brain with either uniform or complex fiber orientations, i.e., in the corpus callosum (cc) and dorsal tegmental tract (dtg), respectively. RAFF4 showed excellent ability to detect demyelinated lesions and good correlation with myelin content in both brain areas. In comparison, diffusion tensor imaging metrices, fractional anisotropy, mean diffusivity and axonal and radial diffusivity, and magnetization transfer (MT) metrices, longitudinal relaxation during off-resonance irradiation and MT ratio, either failed to detect demyelination in dtg or showed lower correlation with myelin density quantified from gold chloride stained histological sections. Good specifity of RAFF4 to myelin was confirmed by its low correlation with cell density assesed from Nissl stained sections as well as its lack of sensitivity to pH changes in the physiological range as tested in heat denaturated bovine serum albumin phantoms. The excellent ability of RAFF4 to detect myelin content and its insensitivity to fiber orientation distribution, gliosis and pH, together with low specific absorption rate, demonstrates the promise of rotating frame of rank n (RAFFn) as a valuable MRI technique for non-invasive imaging of demyelinating lesions.

MRI relaxation in the presence of fictitious fields correlates with myelin content in normal rat brain

PURPOSE

Brain myelin plays an important role in normal brain function. Demyelination is involved in many degenerative brain diseases, thus quantitative imaging of myelin has been under active investigation. In previous work, we demonstrated the capability of the method known as Relaxation Along a Fictitious Field (RAFF) in the rotating frame of rank n (RAFFn) to provide image contrast between white and gray matter in human and rat brains. Here, we provide evidence pointing to myelin being the major source of this contrast.

METHODS

RAFFn relaxation time constant (TRAFFn) was mapped in rat brain ex vivo. TRAFFn was quantified in 12 different brain areas. TRAFFn values were compared with multiple other MRI metrics (T1, T2 , continuous wave T1ρ, adiabatic T1ρ and T2ρ, magnetization transfer ratio), and with histologic measurements of cell density, myelin and iron content.

RESULTS

Highest contrast between white and grey matter was obtained with TRAFFn in the rotating frames of ranks n = 4 and 5. TRAFFn values correlated strongly with myelin content, whereas no associations between TRAFFn and iron content or cell density were found.

CONCLUSION

TRAFFn with n = 4 or 5 provides a high sensitivity for selective myelin mapping in the rat brain.

Temporal phase correction of multiple echo T2 magnetic resonance images

Typically, magnetic resonance imaging (MRI) analysis is performed on magnitude data, and multiple echo T2 data consist of numerous images of the same slice taken with different echo spacing, giving voxel-wise temporal sampling of the noise as the signals decay according to T2 relaxation. Magnitude T2 decay data has Rician distributed noise which is characterized by a change in the noise distribution from Gaussian, through a transitional region, to Rayleigh as the signal to noise ratio decreases with increasing echo time. Non-Gaussian noise distributions may produce errors in the commonly applied non-negative least squares (NNLS) algorithm that is used to assess multiple echo decays for compartmentalized water environments through the creation of T2 distributions. Typically, Gaussian noise is sought by performing spatial-based phase correction on the MRI data however, these methods cannot capitalize on the temporal information available from multiple echo T2 acquisitions. Here we describe a temporal phase correction (TPC) algorithm that utilizes the temporal noise information available in multiple echo T2 acquisitions to put the relevant decay information in the Real portion of the decay data and leave only noise in the Imaginary portion. We apply this TPC algorithm to create real-valued multiple echo T2 data from human subjects measured at 1.5 T. We show that applying TPC causes changes in the T2 distribution estimates; notably the possible resolution of separate extracellular and intracellular water environments, and the disappearance of the commonly labeled cerebrospinal fluid peak, which might be an artefact observed in many previously published multiple echo T2 analyses.

Characterizing inter-compartmental water exchange in myelinated tissue using relaxation exchange spectroscopy

PURPOSE

To investigate inter-compartmental water exchange in two model myelinated tissues ex vivo using relaxation exchange spectroscopy.

METHODS

Building upon a previously developed theoretical framework, a three-compartment (myelin, intra-axonal, and extra-axonal water) model of the inversion-recovery prepared relaxation exchange spectroscopy signal was applied in excised rat optic nerve and frog sciatic nerve samples to estimate the water residence time constants in myelin (τmyelin ).

RESULTS

In the rat optic nerve samples, τmyelin = 138 ± 15 ms (mean ± standard deviation) was estimated. In sciatic nerve, which possesses thicker myelin sheaths than optic nerve, a much longer τmyelin = 2046 ± 140 ms was observed.

CONCLUSION

Consistent with previous studies in rat spinal cord, the extrapolation of exchange rates in optic nerve to in vivo conditions indicates that τmyelin < 100 ms. This suggests that there is a significant effect of inter-compartmental water exchange on the transverse relaxation of water protons in white matter. The much longer τmyelin values in sciatic nerve supports the postulate that the inter-compartmental water exchange rate is mediated by myelin thickness. Together, these findings point to the potential for MRI methods to probe variations in myelin thickness in white matter.

Origins of the ultrashort-T2 1H NMR signals in myelinated nerve: a direct measure of myelin content?

Recently developed MRI techniques have enabled clinical imaging of short-lived (1)H NMR signals with T(2) < 1 ms. Using these techniques, novel signal enhancement has been observed in myelinated tissues, although the source of this enhancement has not been identified. Herein, we report studies of the nature and origins of ultrashort T(2) (uT(2)) signals (50 μs < T(2) < 1 ms) from amphibian and mammalian myelinated nerves. NMR measurements and comparisons with myelin phantoms and expected myelin components indicate that these uT(2) signals arise predominantly from methylene (1)H on/in the myelin membranes, which suggests that direct measurement of uT(2) signals can be used as a new means for quantitative myelin mapping.

Compartment-specific enhancement of white matter and nerve ex vivo using chromium

Chromium--Cr(VI) in the form of potassium dichromate--has been shown to specifically enhance white matter signal. The proposed mechanism for this enhancement is reduction of diamagnetic Cr(VI) to paramagnetic chromium species by oxidizable myelin lipids. The purpose of the study herein was to better understand the microanatomical basis of this enhancement (i.e., the relative enhancement of myelin, intra-axonal, and extra-axonal water). Toward this end, integrated T(1)-T(2) measurements were performed in potassium dichromate loaded (hereafter referred to as chromated) rat brains, rat optic nerve samples, and frog sciatic nerve samples ex vivo. In control optic nerve and white matter, two T(1)-T(2) components were resolved, representing myelin and nonmyelin water (intra- and extra-axonal water). Following chromation, three T(1)-T(2) components were resolved in these same tissues. Results from similar measurements in sciatic nerve-all three components are resolvable in control and chromated samples-and quantitative histologic analysis suggest that this additional T(1)-T(2) component is due to a splitting of the nonmyelin water component into intra- and extra-axonal water components. This compartment-specific enhancement may provide unique contrast for MR histology, as well as allow one to probe the compartmental basis of various contrast mechanisms in neural tissue.

Multiexponential T2 and magnetization transfer MRI of demyelination and remyelination in murine spinal cord

Identification of remyelination is important in the evaluation of potential treatments of demyelinating diseases such as multiple sclerosis. Local injection of lysolecithin into the brain or spinal cord provides a murine model of demyelination with spontaneous remyelination. The aim of this study was to determine if quantitative, multicomponent T(2) (qT(2)) analysis and magnetization transfer ratio (MTR), both indicative of myelin content, could detect changes in myelination, particularly remyelination, of the cervical spinal cord in mice treated with lysolecithin. We found that the myelin water fraction and geometric mean T(2) value of the intra/extracellular water significantly decreased at 14 days then returned to control levels by 28 days after injury, corresponding to clearance of myelin debris and remyelination which was shown by eriochrome cyanine and oil red O staining of histological sections. The MTR was significantly decreased 14 days after lysolecithin injection, and remained low over the time course studied. Evidence of demyelination shown by both qT(2) and MTR lagged behind the histological evidence of demyelination. Myelin water fraction increased with remyelination, however MTR remained lower after 28 days. The difference between qT(2) and MTR may identify early remyelination.