Compartmental study of T(1) and T(2) in rat brain and trigeminal nerve in vivo

In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI

Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency,ω $$ \omega $$ , in addition to the diffusion tensor,D $$ \mathbf{D} $$ , and relaxation,R 1 $$ {R}_1 $$ ,R 2 $$ {R}_2 $$ , correlations. AD ω - R 1 - R 2 $$ \mathbf{D}\left(\omega \right)-{R}_1-{R}_2 $$ clinical imaging protocol was then introduced, with limited brain coverage and 3 mm3 voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm3 voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on theirD ω - R 1 - R 2 $$ \mathbf{D}\left(\omega \right)-{R}_1-{R}_2 $$ distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.

Empirical relationship between TEM-derived myelin volume fraction and MRI-R2 values in aging ex vivo rat corpus callosum

Ex vivo ratiometric measurements of short- and long-T2 components using the multiple spin echo sequence of MRI are often employed to evaluate alterations in myelin content in the white matter (WM) of the brain. However, the relationship between absolute MRI-T2 values (long-T2 component) and myelin volumetric information in aged ex vivo rodent WM appears to be influenced by factors such as animal species, field strength, and fixation durations/washing. Here, multiple spin echo sequence-based MRI-R2 (the reciprocal of T2) values were measured in the corpus callosum (CC) region in the post-mortem rat brains (n = 9) of different age groups with common fixation techniques without washing at 7 T. Transmission electron microscopy (TEM)-based quantification of myelin volume fraction (MVF) and corresponding Monte-Carlo simulation to estimate relaxation rates (R2,IE) due to diffusion in the presence of inhomogeneous magnetic field perturbation in intra- and extra-cellular (IE) spaces were respectively performed. To determine whether the short-T2 components originating from myelin water were mixed with long-T2 components from IE water or were undetectable, the MVF values obtained from TEM results were respectively compared with MRI-R2 and R2,IE values. A significant correlation (Pearson's correlation coefficient r = 0.8763; p < 0.01) of average MRI-R2 and MVF values was observed. Estimated R2,IE values from Monte-Carlo simulations in IE water signals were also positively correlated (r = 0.8281; p < 0.01) with MVF values. However, the magnitudes of R2,IE values were much smaller than those observed for MRI-R2 values, indicating that changes in R2 related MVF are likely dominated by myelin water components. Such comparisons between independent parameters from MRI, TEM, and simulations support the suggestion that myelin water signals were indistinguishably mixed to exhibit mono-exponential T2 relaxation, and multiple spin echo sequence-based MRI-R2 values in aging ex vivo rat CC without prolonged washing still reflect the volumetric information of myelin, likely due to enhanced water exchange across the myelin.

In Vivo Myelin Water Quantification Using Diffusion-Relaxation Correlation MRI: A Comparison of 1D and 2D Methods

Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion-relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. Whilst 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion.

Diffuse axonal injury has a characteristic multidimensional MRI signature in the human brain

Axonal injury is a major contributor to the clinical symptomatology in patients with traumatic brain injury. Conventional neuroradiological tools, such as CT and MRI, are insensitive to diffuse axonal injury (DAI) caused by trauma. Diffusion tensor MRI parameters may change in DAI lesions; however, the nature of these changes is inconsistent. Multidimensional MRI is an emerging approach that combines T1, T2, and diffusion, and replaces voxel-averaged values with distributions, which allows selective isolation of specific potential abnormal components. By performing a combined post-mortem multidimensional MRI and histopathology study, we aimed to investigate T1-T2-diffusion changes linked to DAI and to define their histopathological correlates. Corpora callosa derived from eight subjects who had sustained traumatic brain injury, and three control brain donors underwent post-mortem ex vivo MRI at 7 T. Multidimensional, diffusion tensor, and quantitative T1 and T2 MRI data were acquired and processed. Following MRI acquisition, slices from the same tissue were tested for amyloid precursor protein (APP) immunoreactivity to define DAI severity. A robust image co-registration method was applied to accurately match MRI-derived parameters and histopathology, after which 12 regions of interest per tissue block were selected based on APP density, but blind to MRI. We identified abnormal multidimensional T1-T2, diffusion-T2, and diffusion-T1 components that are strongly associated with DAI and used them to generate axonal injury images. We found that compared to control white matter, mild and severe DAI lesions contained significantly larger abnormal T1-T2 component (P = 0.005 and P < 0.001, respectively), and significantly larger abnormal diffusion-T2 component (P = 0.005 and P < 0.001, respectively). Furthermore, within patients with traumatic brain injury the multidimensional MRI biomarkers differentiated normal-appearing white matter from mild and severe DAI lesions, with significantly larger abnormal T1-T2 and diffusion-T2 components (P = 0.003 and P < 0.001, respectively, for T1-T2; P = 0.022 and P < 0.001, respectively, for diffusion-T2). Conversely, none of the conventional quantitative MRI parameters were able to differentiate lesions and normal-appearing white matter. Lastly, we found that the abnormal T1-T2, diffusion-T1, and diffusion-T2 components and their axonal damage images were strongly correlated with quantitative APP staining (r = 0.876, P < 0.001; r = 0.727, P < 0.001; and r = 0.743, P < 0.001, respectively), while producing negligible intensities in grey matter and in normal-appearing white matter. These results suggest that multidimensional MRI may provide non-invasive biomarkers for detection of DAI, which is the pathological substrate for neurological disorders ranging from concussion to severe traumatic brain injury.

T1 Mapping for Microstructural Assessment of the Cervical Spinal Cord in the Evaluation of Patients with Degenerative Cervical Myelopathy

BACKGROUND AND PURPOSE

Although current radiologic evaluation of degenerative cervical myelopathy by conventional MR imaging accurately demonstrates spondylosis or degenerative disc disease causing spinal cord dysfunction, conventional MR imaging still fails to provide satisfactory anatomic and clinical correlations. In this context, we assessed the potential value of quantitative cervical spinal cord T1 mapping regarding the evaluation of patients with degenerative cervical myelopathy.

MATERIALS AND METHODS

Twenty patients diagnosed with mild and moderate-to-severe degenerative cervical myelopathy and 10 healthy subjects were enrolled in a multiparametric MR imaging protocol. Cervical spinal cord T1 mapping was performed with the MP2RAGE sequence procedure. Retrieved data were processed and analyzed regarding the global spinal cord and white and anterior gray matter on the basis of the clinical severity and the spinal canal stenosis grading.

RESULTS

Noncompressed levels in healthy controls demonstrated significantly lower T1 values than noncompressed, mild, moderate, and severe stenotic levels in patients. Concerning the entire spinal cord T1 mapping, patients with moderate-to-severe degenerative cervical myelopathy had higher T1 values compared with healthy controls. Regarding the specific levels, patients with moderate-to-severe degenerative cervical myelopathy demonstrated a T1 value increase at C1, C7, and the level of maximal compression compared with healthy controls. Patients with mild degenerative cervical myelopathy had lower T1 values than those with moderate-to-severe degenerative cervical myelopathy at the level of maximal compression. Analyses of white and anterior gray matter confirmed similar results. Strong negative correlations between individual modified Japanese Orthopaedic Association scores and T1 values were also observed.

CONCLUSIONS

In this preliminary study, 3D-MP2RAGE T1 mapping demonstrated increased T1 values in the pathology tissue samples, with diffuse medullary alterations in all patients with degenerative cervical myelopathy, especially relevant at C1 (nonstenotic level) and at the maximal compression level. Encouraging correlations observed with the modified Japanese Orthopaedic Association score make this novel approach a potential quantitative biomarker related to clinical severity in degenerative cervical myelopathy. Nevertheless, patients with mild degenerative cervical myelopathy demonstrated nonsignificant results compared with healthy controls and should now be studied in multicenter studies with larger patient populations.

Whole-Brain Imaging of Subvoxel T1-Diffusion Correlation Spectra in Human Subjects

T1 relaxation and water mobility generate eloquent MRI tissue contrasts with great diagnostic value in many neuroradiological applications. However, conventional methods do not adequately quantify the microscopic heterogeneity of these important biophysical properties within a voxel, and therefore have limited biological specificity. We describe a new correlation spectroscopic (CS) MRI method for measuring how T1 and mean diffusivity (MD) co-vary in microscopic tissue environments. We develop a clinical pulse sequence that combines inversion recovery (IR) with single-shot isotropic diffusion encoding (IDE) to efficiently acquire whole-brain MRIs with a wide range of joint T1-MD weightings. Unlike conventional diffusion encoding, the IDE preparation ensures that all subvoxel water pools are weighted by their MDs regardless of the sizes, shapes, and orientations of their corresponding microscopic diffusion tensors. Accordingly, IR-IDE measurements are well-suited for model-free, quantitative spectroscopic analysis of microscopic water pools. Using numerical simulations, phantom experiments, and data from healthy volunteers we demonstrate how IR-IDE MRIs can be processed to reconstruct maps of two-dimensional joint probability density functions, i.e., correlation spectra, of subvoxel T1-MD values. In vivo T1-MD spectra show distinct cerebrospinal fluid and parenchymal tissue components specific to white matter, cortical gray matter, basal ganglia, and myelinated fiber pathways, suggesting the potential for improved biological specificity. The one-dimensional marginal distributions derived from the T1-MD correlation spectra agree well with results from other relaxation spectroscopic and quantitative MRI studies, validating the T1-MD contrast encoding and the spectral reconstruction. Mapping subvoxel T1-diffusion correlations in patient populations may provide a more nuanced, comprehensive, sensitive, and specific neuroradiological assessment of the non-specific changes seen on fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted MRIs (DWIs) in cancer, ischemic stroke, or brain injury.

Fast multicomponent 3D-T1ρ relaxometry

NMR relaxometry can provide information about the relaxation of the magnetization in different tissues, increasing our understanding of molecular dynamics and biochemical composition in biological systems. In general, tissues have complex and heterogeneous structures composed of multiple pools. As a result, bulk magnetization returns to its original state with different relaxation times, in a multicomponent relaxation. Recovering the distribution of relaxation times in each voxel is a difficult inverse problem; it is usually unstable and requires long acquisition time, especially on clinical scanners. MRI can also be viewed as an inverse problem, especially when compressed sensing (CS) is used. The solution of these two inverse problems, CS and relaxometry, can be obtained very efficiently in a synergistically combined manner, leading to a more stable multicomponent relaxometry obtained with short scan times. In this paper, we will discuss the details of this technique from the viewpoint of inverse problems.

Multidimensional correlation MRI

Multidimensional correlation spectroscopy is emerging as a novel MRI modality that is well suited for microstructure and microdynamic imaging studies, especially of biological specimens. Conventional MRI methods only provide voxel-averaged and mostly macroscopically averaged information; these methods cannot disentangle intra-voxel heterogeneity on the basis of both water mobility and local chemical interactions. By correlating multiple MR contrast mechanisms and processing the data in an integrated manner, correlation spectroscopy is able to resolve the distribution of water populations according to their chemical and physical interactions with the environment. The use of a non-parametric, phenomenological representation of the multidimensional MR signal makes no assumptions about tissue structure, thereby allowing the study of microscopic structure and composition of complex heterogeneous biological systems. However, until recently, vast data requirements have confined these types of measurement to non-localized NMR applications and prevented them from being widely and successfully used in conjunction with imaging. Recent groundbreaking advancements have allowed this powerful NMR methodology to be migrated to MRI, initiating its emergence as a promising imaging approach. This review is not intended to cover the entire field of multidimensional MR; instead, it focuses on pioneering imaging applications and the challenges involved. In addition, the background and motivation that have led to multidimensional correlation MR development are discussed, along with the basic underlying mathematical concepts. The goal of the present work is to provide the reader with a fundamental understanding of the techniques developed and their potential benefits, and to provide guidance to help refine future applications of this technology.

Multidimensional correlation spectroscopic imaging of exponential decays: From theoretical principles to in vivo human applications

Multiexponential modeling of relaxation or diffusion MR signal decays is a popular approach for estimating and spatially mapping different microstructural tissue compartments. While this approach can be quite powerful, it is also limited by the fact that one-dimensional multiexponential modeling is an ill-posed inverse problem with substantial ambiguities. In this article, we present an overview of a recent multidimensional correlation spectroscopic imaging approach to this problem. This approach helps to alleviate ill-posedness by making advantageous use of multidimensional contrast encoding (e.g., 2D diffusion-relaxation encoding or 2D relaxation-relaxation encoding) combined with a regularized spatial-spectral estimation procedure. Theoretical calculations, simulations, and experimental results are used to illustrate the benefits of this approach relative to classical methods. In addition, we demonstrate an initial proof-of-principle application of this kind of approach to in vivo human MRI experiments.

Retaining information from multidimensional correlation MRI using a spectral regions of interest generator

Multidimensional correlation magnetic resonance imaging (MRI) is an emerging imaging modality that is capable of disentangling highly heterogeneous and opaque systems according to chemical and physical interactions of water within them. Using this approach, the conventional three dimensional MR scalar images are replaced with spatially resolved multidimensional spectra. The ensuing abundance in microstructural and chemical information is a blessing that incorporates a real challenge: how does one distill and refine it into images while retaining its significant components? In this paper we introduce a general framework that preserves the spectral information from spatially resolved multidimensional data. Equal weight is given to significant spectral components at the single voxel level, resulting in a summarized image spectrum. This spectrum is then used to define spectral regions of interest that are utilized to reconstruct images of sub-voxel components. Using numerical simulations we first show that, contrary to the conventional approach, the proposed framework preserves spectral resolution, and in turn, sensitivity and specificity of the reconstructed images. The retained spectral resolution allows, for the first time, to observe an array of distinct [Formula: see text]-[Formula: see text]-[Formula: see text] components images of the human brain. The robustly generated images of sub-voxel components overcome the limited spatial resolution of MRI, thus advancing multidimensional correlation MRI to fulfilling its full potential.

Dipolar induced spin-lattice relaxation in the myelin sheath: A molecular dynamics study

Interactions between hydrogen protons of water molecules and macromolecules within the myelin sheath surrounding the axons are a major factor influencing the magnetic resonance (MR) contrast in white matter (WM) regions. In past decades, several studies have investigated the underlying effects and reported a wide range of R1 rates for the myelin associated compartments at different field strengths. However, it was also shown that the experimental quantification of the compartment-specific R1 rates is associated with large uncertainties. The current study therefore investigates the longitudinal relaxation rates within the myelin sheath using a molecular dynamic (MD) simulation. For this purpose, a realistic molecular model of the myelin sheath was employed to determine the dipole-dipole induced R1 relaxation rate of the hydrogen protons at clinically relevant field strengths. The results obtained clearly reflect the spatial heterogeneity of R1 with a increased relaxivity of myelin water due to a reduced molecular mobility near the membrane surface. Moreover, the calculated R1 rates for both myelin water and macromolecules are in excellent agreement with experimental findings from the literature at different field strengths.

Optimization of data acquisition and analysis for fiber ball imaging

The inverse Funk transform of high angular resolution diffusion imaging (HARDI) data provides an estimate for the fiber orientation density function (fODF) in white matter (WM). Since the inverse Funk transform is a straightforward linear transformation, this technique, referred to as fiber ball imaging (FBI), offers a practical means of calculating the fODF that avoids the need for a response function or nonlinear numerical fitting. Nevertheless, the accuracy of FBI depends on both the choice of b-value and the number of diffusion-encoding directions used to acquire the HARDI data. To inform the design of optimal scan protocols for its implementation, FBI predictions are investigated here with in vivo data from healthy adult volunteers acquired at 3 T for b-values spanning 1000 to 10,000 s/mm², for diffusion-encoding directions varying in number from 30 to 256 and for TE ranging from 90 to 120 ms. Our results suggest b-values above 4000 s/mm² with at least 64 diffusion-encoding directions are adequate to achieve reasonable accuracy with FBI for calculating axon-specific diffusion measures and for performing WM fiber tractography (WMFT).

Spatially-resolved 1H NMR relaxation-exchange measurements in heterogeneous media

In the last decades, the ¹H NMR T₂-T₂ relaxation-exchange (REXSY) technique has become an essential tool for the molecular investigation of simple and complex fluids in heterogeneous porous solids and soft matter, where the mixing-time-evolution of cross-correlated T₂-T₂ peaks enables a quantitative study of diffusive exchange kinetics in multi-component systems. Here, we present a spatially-resolved implementation of the T₂-T₂ correlation technique, named z-T₂-T₂, based on one-dimensional spatial mapping along z using a rapid frequency-encode imaging scheme. Compared to other phase-encoding methods, the adopted MRI technique has two distinct advantages: (i) is has the same experimental duration of a standard (bulk) T₂-T₂ measurement, and (ii) it provides a high spatial resolution. The proposed z-T₂-T₂ method is first validated against bulk T₂-T₂ measurements on homogeneous phantom consisting of cyclohexane uniformly imbibed in finely-sized α-Al₂O₃ particles at a spatial resolution of 0.47 mm; thereafter, its performance is demonstrated, on a layered bed of multi-sized α-Al₂O₃ particles, for revealing spatially-dependent molecular exchange kinetics properties of intra- and inter-particle cyclohexane as a function of particle size. It is found that localised z-T₂-T₂ spectra provide well resolved cross peaks whilst such resolution is lost in standard bulk T₂-T₂ data. Future prospective applications of the method lie, in particular, in the local characterisation of mass transport phenomena in multi-component porous media, such as rock cores and heterogeneous catalysts.

Measuring intra-axonal T2 in white matter with direction-averaged diffusion MRI

PURPOSE

To demonstrate how the T₂ relaxation time of intra-axonal water (T_2a ) in white matter can be measured with direction-averaged diffusion MRI.

METHODS

For b-values larger than about 4000 s/mm² , the direction-averaged diffusion MRI signal from white matter is dominated by the contribution from water within axons, which enables T_2a to be estimated by acquiring data for multiple TE values and fitting a mono-exponential decay curve. If given a value of the intra-axonal diffusivity, an extension of the method allows the extra-axonal relaxation time (T_2e ) to be calculated also. This approach was applied to estimate T_2a in white matter for 3 healthy subjects at 3 T, as well as T_2e for a selected set of assumed intra-axonal diffusivities.

RESULTS

The estimated T_2a values ranged from about 50 ms to 110 ms, with considerable variation among white matter regions. For white matter tracts with primarily collinear fibers, T_2a was found to depend on the angle of the tract relative to the main magnetic field, which is consistent with T_2a being affected by magnetic field inhomogeneities arising from spatial differences in magnetic susceptibility. The T_2e values were significantly smaller than the T_2a values across white matter regions for several plausible choices of the intra-axonal diffusivity.

CONCLUSION

The relaxation time for intra-axonal water in white matter can be determined in a straightforward manner by measuring the direction-averaged diffusion MRI signal with a large b-value for multiple TEs. In healthy brain, T_2a is greater than T_2e and varies considerably with anatomical region.

Myelin volume fraction imaging with MRI

MRI is a valuable tool to assess myelin during development and demyelinating disease processes. While multiexponential T2 and quantitative magnetization transfer measures correlate with myelin content, neither provides the total myelin volume fraction. In many cases correlative measures are adequate; but to assess microstructure of myelin, (e.g. calculate the g-ratio using MRI), an accurate measure of myelin volume fraction is imperative. Using a volumetric model of white matter, we relate MRI measures of myelin to absolute measures of myelin volume fraction and compare them to quantitative histology. We assess our approach in control mice along with two models of hypomyelination and one model of hypermyelination and find strong agreement between MRI and histology amongst models. This work investigates the sensitivities of MRI myelin measures to changes in axon geometry and displays promise for estimating g-ratio from MRI.

Influence of the extracellular matrix on water mobility in subcortical gray matter

PURPOSE

Water mobility in tissues is related to the microstructure that modulates diffusion and spin relaxation. Previous work has shown that the extracellular matrix (ECM) impacts water diffusion in cartilage. To investigate if similar contributions to image contrast exist for brain, which is characterized by a substantially lower ECM content, diffusion and relaxation were studied in fixed samples from goat and human thalamus before and after enzymatic digestion of ECM compounds. Selected experiments in human corpus callosum were included for comparing subcortical gray matter and white matter.

METHODS

Digestion of matrix components was achieved by treatment with hyaluronidase. Nonlocalized pulsed field gradient measurements were performed with <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>b</mml:mi></mml:math> values between 0.6 and 18,000 s/mm² at 3T and temperatures between 0°C and 20°C, in addition to T₁ and T₂ relaxation measurements. The data were fitted to multiexponential models to account for different water compartments. After the measurements, the samples were sliced and stained for ECM-sensitive markers to verify efficient digestion.

RESULTS

Microstructural alterations associated with hyaluronan digestion did not lead to measurable effects on water diffusion or <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>T</mml:mi> <mml:mn>2</mml:mn></mml:msub> </mml:math> . However, T₁ of the main relaxographic component, attributed to intra-/extracellular water, decreased by 7%.

CONCLUSION

Investigations with very strong gradients did not reveal a detectable effect on water diffusion or <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>T</mml:mi> <mml:mn>2</mml:mn></mml:msub> </mml:math> after hyaluronan removal, indicating that the brain ECM content is too low to produce a detectable effect. The subtle alteration of T₁ upon hyaluronidase treatment might reflect a modulation of intercompartmental water exchange properties.

Towards clinically feasible relaxation-diffusion correlation MRI using MADCO

Multidimensional relaxation-diffusion correlation (REDCO) NMR is an assumption-free method that measures how water is distributed within materials. Although highly informative, REDCO had never been used in clinical MRI applications because of the large amount of data it requires, leading to infeasible scan times. A recently suggested novel experimental design and processing framework, marginal distributions constrained optimization (MADCO), was used here to accelerate and improve the reconstruction of such MRI correlations. MADCO uses the 1D marginal distributions as a priori information, which provide powerful constraints when 2D spectra are reconstructed, while their estimation requires an order of magnitude less data than conventional 2D approaches. In this work we experimentally examined the impact the complexity of the correlation distribution has on the accuracy and robustness of the estimates. MADCO and a conventional method were compared using two T1-D phantoms that differ in the proximity of their peaks, leading to a relatively simple case as opposed to a more challenging one. The phantoms were used to vet the achievable data compression using MADCO under these conditions. MADCO required ~43 and ~30 less data than the conventional approach for the simple and complex spectra, respectively, making it potentially feasible for preclinical and even clinical applications.

Yet more evidence that myelin protons can be directly imaged with UTE sequences on a clinical 3T scanner: Bicomponent T2* analysis of native and deuterated ovine brain specimens

PURPOSE

UTE sequences with a minimal nominal TE of 8 µs have shown promise for direct imaging of myelin protons (T2 , < 1 ms). However, there is still debate about the efficiency of 2D slice-selective UTE sequences in exciting myelin protons because the half excitation pulses used in these sequences have a relatively long duration (e.g., 0.3-0.6 ms). Here, we compared UTE and inversion-recovery (IR) UTE sequences used with either hard or half excitation pulses (durations 32 µs or 472 µs, respectively) for imaging myelin in native and deuterated ovine brain at 3T.

METHODS

Freshly frozen ovine brains were dissected into ∼2 mm-thick pure white matter and ∼3 to 8 mm-thick cerebral hemisphere specimens, which were imaged before and/or after different immersion time in deuterium oxide.

RESULTS

Bicomponent T2* analysis of UTE signals obtained with hard excitation pulses detected an ultrashort T2 component (STC) fraction (fS ) of 0% to 10% in native specimens, and up to ∼86% in heavily deuterated specimens. fS values were significantly affected by the TIs used in IR-UTE sequences with either hard or half excitation pulses in native specimens but not in heavily deuterated specimens. The STC T2* was in the range of 150 to 400 µs in all UTE and IR-UTE measurements obtained with either hard or half excitation pulses.

CONCLUSION

Our results further support myelin protons as the major source of the ultrashort T2* signals seen on IR-UTE images and demonstrate the potential of IR-UTE sequences with half excitation pulses for directly imaging myelin using clinical scanners. Magn Reson Med 80:538-547, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

PROBING IN VIVO MICROSTRUCTURE WITH T 1-T 2 RELAXATION CORRELATION SPECTROSCOPIC IMAGING

Quantitative MR relaxometry can provide unique subvoxel information about the microscopic tissue compartments that are present in a large imaging voxel. However, unambiguously distinguishing between these tissue compartments continues to be challenging with conventional methods due to the illposedness of the inverse problem. This paper describes a new imaging approach, which we call T ₁ Relaxation-T ₂ Relaxation Correlation Spectroscopic Imaging (RR-CSI), that uses two-dimensional relaxation encoding combined with spatially-constrained reconstruction to help overcome illposedness. Results are shown with real data, including what we believe to be the first in vivo demonstration of multidimensional relaxation correlation spectroscopic imaging.

MRI gradient-echo phase contrast of the brain at ultra-short TE with off-resonance saturation

Larmor-frequency shift or image phase measured by gradient-echo sequences has provided a new source of MRI contrast. This contrast is being used to study both the structure and function of the brain. So far, phase images of the brain have been largely obtained at long echo times as maximum phase signal-to-noise ratio (SNR) is achieved at TE = T2* (∼40 ms at 3T). The structures of the brain, however, are compartmentalized and complex with a wide range of signal relaxation times. At such long TE, the short-T2 components are largely attenuated and contribute minimally to phase contrast. The purpose of this study was to determine whether proton gradient-echo images of the brain exhibit phase contrast at ultra-short TE (UTE). Our data showed that UTE images acquired at 7 T without off-resonance saturation do not contain significant phase contrast between gray and white matter. However, UTE images of the brain can attain strong phase contrast even at a nominal TE of 106 μs by using off-resonance RF saturation pulses, which provide direct saturation of ultra-short-T2 components and indirect saturation of longer-T2 components via magnetization transfer. In addition, phase contrast between gray and white matter acquired at UTE with off-resonance saturation is reversed compared to that of the long-T2 signals acquired at long TEs. This finding opens up a potential new way to manipulate image phase contrast of the brain. By accessing short and ultra-short-T2 species, MRI phase images may further improve the characterization of tissue microstructure in the brain.

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.

Diffusion-relaxation correlation spectroscopic imaging: A multidimensional approach for probing microstructure

PURPOSE

To propose and evaluate a novel multidimensional approach for imaging subvoxel tissue compartments called Diffusion-Relaxation Correlation Spectroscopic Imaging.

THEORY AND METHODS

Multiexponential modeling of MR diffusion or relaxation data is commonly used to infer the many different microscopic tissue compartments that contribute signal to macroscopic MR imaging voxels. However, multiexponential estimation is known to be difficult and ill-posed. Observing that this ill-posedness is theoretically reduced in higher dimensions, diffusion-relaxation correlation spectroscopic imaging uses a novel multidimensional imaging experiment that jointly encodes diffusion and relaxation information, and then uses a novel constrained reconstruction technique to generate a multidimensional diffusion-relaxation correlation spectrum for every voxel. The peaks of the multidimensional spectrum are expected to correspond to the distinct tissue microenvironments that are present within each macroscopic imaging voxel.

RESULTS

Using numerical simulations, experiment data from a custom-built phantom, and experiment data from a mouse model of traumatic spinal cord injury, diffusion-relaxation correlation spectroscopic imaging is demonstrated to provide substantially better multicompartment resolving power compared to conventional diffusion- and relaxation-based methods.

CONCLUSION

The diffusion-relaxation correlation spectroscopic imaging approach provides powerful new capabilities for resolving the different components of multicompartment tissue models, and can be leveraged to significantly expand the insights provided by MRI in studies of tissue microstructure. Magn Reson Med 78:2236-2249, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Inversion recovery ultrashort echo time imaging of ultrashort T2 tissue components in ovine brain at 3 T: a sequential D2 O exchange study

Inversion recovery ultrashort echo time (IR-UTE) imaging holds the potential to directly characterize MR signals from ultrashort T2 tissue components (STCs), such as collagen in cartilage and myelin in brain. The application of IR-UTE for myelin imaging has been challenging because of the high water content in brain and the possibility that the ultrashort T2 * signals are contaminated by water protons, including those associated with myelin sheaths. This study investigated such a possibility in an ovine brain D2 O exchange model and explored the potential of IR-UTE imaging for the quantification of ultrashort T2 * signals in both white and gray matter at 3 T. Six specimens were examined before and after sequential immersion in 99.9% D2 O. Long T2 MR signals were measured using a clinical proton density-weighted fast spin echo (PD-FSE) sequence. IR-UTE images were first acquired with different inversion times to determine the optimal inversion time to null the long T2 signals (TInull ). Then, at this TInull , images with echo times (TEs) of 0.01-4 ms were acquired to measure the T2 * values of STCs. The PD-FSE signal dropped to near zero after 24 h of immersion in D2 O. A wide range of TInull values were used at different time points (240-330 ms for white matter and 320-350 ms for gray matter at TR = 1000 ms) because the T1 values of the long T2 tissue components changed significantly. The T2 * values of STCs were 200-300 μs in both white and gray matter (comparable with the values obtained from myelin powder and its mixture with D2 O or H2 O), and showed minimal changes after sequential immersion. The ultrashort T2 * signals seen on IR-UTE images are unlikely to be from water protons as they are exchangeable with deuterons in D2 O. The source is more likely to be myelin itself in white matter, and might also be associated with other membranous structures in gray matter.

Magnetic resonance microdynamic imaging reveals distinct tissue microenvironments

Magnetic resonance imaging (MRI) provides a powerful set of tools with which to investigate biological tissues noninvasively and in vivo. Tissues are heterogeneous in nature; an imaging voxel contains an ensemble of different cells and extracellular matrix components. A long-standing challenge has been to infer the content of and interactions among these microscopic tissue components within a macroscopic imaging voxel. Spatially resolved multidimensional relaxation-diffusion correlation (REDCO) spectroscopy holds the potential to deliver such microdynamic information. However, to date, vast data requirements have mostly relegated these type of measurements to nuclear magnetic resonance applications and prevented them from being widely and successfully used in conjunction with imaging. By using a novel data acquisition and processing strategy in this study, spatially resolved REDCO could be performed in reasonable scanning times with excellent prospects for clinical applications. This new MR imaging framework-which we term "magnetic resonance microdynamic imaging (MRMI)"-permits the simultaneous noninvasive and model-free quantification of multiple subcellular, cellular, and interstitial tissue microenvironments within a voxel. MRMI is demonstrated with a fixed spinal cord specimen, enabling the quantification of microscopic tissue components with unprecedented specificity. Tissue components, such as axons, neuronal and glial soma, and myelin were identified on the basis of their multispectral signature within individual imaging voxels. These tissue elements could then be composed into images and be correlated with immunohistochemistry findings. MRMI provides novel image contrasts of tissue components and a new family of microdynamic biomarkers that could lead to new diagnostic imaging approaches to probe biological tissue alterations accompanied by pathological or developmental changes.

Exploring the origins of echo-time-dependent quantitative susceptibility mapping (QSM) measurements in healthy tissue and cerebral microbleeds

Quantitative susceptibility mapping (QSM) is increasingly used to measure variation in tissue composition both in the brain and in other areas of the body in a range of disease pathologies. Although QSM measurements were originally believed to be independent of the echo time (TE) used in the gradient-recalled echo (GRE) acquisition from which they are derived; recent literature (Sood et al., 2016) has shown that these measurements can be highly TE-dependent in a number of brain regions. In this work we systematically investigate possible causes of this effect through analysis of apparent frequency and QSM measurements derived from data acquired at multiple TEs in vivo in healthy brain regions and in cerebral microbleeds (CMBs); QSM data acquired in a gadolinium-doped phantom; and in QSM data derived from idealized simulated phase data. Apparent frequency measurements in the optic radiations (OR) and central corpus callosum (CC) were compared to those predicted by a 3-pool white matter model, however the model failed to fully explain contrasting frequency profiles measured in the OR and CC. Our results show that TE-dependent QSM measurements can be caused by a failure of phase unwrapping algorithms in and around strong susceptibility sources such as CMBs; however, in healthy brain regions this behavior appears to result from intrinsic non-linear phase evolution in the MR signal. From these results we conclude that care must be taken when deriving frequency and QSM measurements in strong susceptibility sources due to the inherent limitations in phase unwrapping; and that while signal compartmentalization due to tissue microstructure and content is a plausible cause of TE-dependent frequency and QSM measurements in healthy brain regions, better sampling of the MR signal and more complex models of tissue are needed to fully exploit this relationship.

Synthetic quantitative MRI through relaxometry modelling

Quantitative MRI (qMRI) provides standardized measures of specific physical parameters that are sensitive to the underlying tissue microstructure and are a first step towards achieving maps of biologically relevant metrics through in vivo histology using MRI. Recently proposed models have described the interdependence of qMRI parameters. Combining such models with the concept of image synthesis points towards a novel approach to synthetic qMRI, in which maps of fundamentally different physical properties are constructed through the use of biophysical models. In this study, the utility of synthetic qMRI is investigated within the context of a recently proposed linear relaxometry model. Two neuroimaging applications are considered. In the first, artefact-free quantitative maps are synthesized from motion-corrupted data by exploiting the over-determined nature of the relaxometry model and the fact that the artefact is inconsistent across the data. In the second application, a map of magnetization transfer (MT) saturation is synthesized without the need to acquire an MT-weighted volume, which directly leads to a reduction in the specific absorption rate of the acquisition. This feature would be particularly important for ultra-high field applications. The synthetic MT map is shown to provide improved segmentation of deep grey matter structures, relative to segmentation using T₁ -weighted images or R₁ maps. The proposed approach of synthetic qMRI shows promise for maximizing the extraction of high quality information related to tissue microstructure from qMRI protocols and furthering our understanding of the interrelation of these qMRI parameters.

A New Strategy for Fast MRI-Based Quantification of the Myelin Water Fraction: Application to Brain Imaging in Infants

The volume fraction of water related to myelin (fmy) is a promising MRI index for in vivo assessment of brain myelination, that can be derived from multi-component analysis of T1 and T2 relaxometry signals. However, existing quantification methods require rather long acquisition and/or post-processing times, making implementation difficult both in research studies on healthy unsedated children and in clinical examinations. The goal of this work was to propose a novel strategy for fmy quantification within acceptable acquisition and post-processing times. Our approach is based on a 3-compartment model (myelin-related water, intra/extra-cellular water and unrestricted water), and uses calibrated values of inherent relaxation times (T1c and T2c) for each compartment c. Calibration was first performed on adult relaxometry datasets (N = 3) acquired with large numbers of inversion times (TI) and echo times (TE), using an original combination of a region contraction approach and a non-negative least-square (NNLS) algorithm. This strategy was compared with voxel-wise fitting, and showed robust estimation of T1c and T2c. The accuracy of fmy calculations depending on multiple factors was investigated using simulated data. In the testing stage, our strategy enabled fast fmy mapping, based on relaxometry datasets acquired with reduced TI and TE numbers (acquisition <6 min), and analyzed with NNLS algorithm (post-processing <5min). In adults (N = 13, mean age 22.4±1.6 years), fmy maps showed variability across white matter regions, in agreement with previous studies. In healthy infants (N = 18, aged 3 to 34 weeks), asynchronous changes in fmy values were demonstrated across bundles, confirming the well-known progression of myelination.

Use of marginal distributions constrained optimization (MADCO) for accelerated 2D MRI relaxometry and diffusometry

Measuring multidimensional (e.g., 2D) relaxation spectra in NMR and MRI clinical applications is a holy grail of the porous media and biomedical MR communities. The main bottleneck is the inversion of Fredholm integrals of the first kind, an ill-conditioned problem requiring large amounts of data to stabilize a solution. We suggest a novel experimental design and processing framework to accelerate and improve the reconstruction of such 2D spectra that uses a priori information from the 1D projections of spectra, or marginal distributions. These 1D marginal distributions provide powerful constraints when 2D spectra are reconstructed, and their estimation requires an order of magnitude less data than a conventional 2D approach. This marginal distributions constrained optimization (MADCO) methodology is demonstrated here with a polyvinylpyrrolidone-water phantom that has 3 distinct peaks in the 2D D-T1 space. The stability, sensitivity to experimental parameters, and accuracy of this new approach are compared with conventional methods by serially subsampling the full data set. While the conventional, unconstrained approach performed poorly, the new method had proven to be highly accurate and robust, only requiring a fraction of the data. Additionally, synthetic T1-T2 data are presented to explore the effects of noise on the estimations, and the performance of the proposed method with a smooth and realistic 2D spectrum. The proposed framework is quite general and can also be used with a variety of 2D MRI experiments (D-T2,T1-T2,D-D, etc.), making these potentially feasible for preclinical and even clinical applications for the first time.

Assessment of the myelin water fraction in rodent spinal cord using T2-prepared ultrashort echo time MRI

OBJECTIVE

Multi-component T2 relaxation allows for assessing the myelin water fraction in nervous tissue, providing a surrogate marker for demyelination. The assessment of the number and distribution of different T2 components for devising exact models of tissue relaxation has been limited by T2 sampling with conventional MR methods.

MATERIALS AND METHODS

A T2-prepared UTE sequence was used to assess multicomponent T2 relaxation at 9.4 T of fixed mouse and rat spinal cord samples and of mouse spinal cord in vivo. For in vivo scans, a cryogenically cooled probe allowed for 78-µm resolution in 1-mm slices. Voxel-wise non-negative least square analysis was used to assess the number of myelin water-associated T2 components.

RESULTS

More than one myelin water-associated T2 component was detected in only 12 % of analyzed voxels in rat spinal cords and 6 % in mouse spinal cords, both in vivo and in vitro. However, myelin water-associated T2 values of individual voxels varied between 0.1 and 20 ms. While in fixed samples almost no components below 1 ms were identified, in vivo, these contributed 14 % of the T2 spectrum. No significant differences in MWF were observed in mouse spinal cord in vivo versus ex vivo measurements.

CONCLUSION

Voxel-wise analysis methods using relaxation models with one myelin water-associated T2 component are appropriate for assessing myelin content of nervous tissue.

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

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

Effects of magnetization transfer on T1 contrast in human brain white matter

MRI based on T1 relaxation contrast is increasingly being used to study brain morphology and myelination. Although it provides for excellent distinction between the major tissue types of gray matter, white matter, and CSF, reproducible quantification of T1 relaxation rates is difficult due to the complexity of the contrast mechanism and dependence on experimental details. In this work, we perform simulations and inversion-recovery MRI measurements at 3T and 7T to show that substantial measurement variability results from unintended and uncontrolled perturbation of the magnetization of MRI-invisible (1)H protons of lipids and macromolecules. This results in bi-exponential relaxation, with a fast component whose relative contribution under practical conditions can reach 20%. This phenomenon can strongly affect apparent relaxation rates, affect contrast between tissue types, and result in contrast variations over the brain. Based on this novel understanding, ways are proposed to minimize this experimental variability and its effect on T1 contrast, quantification accuracy and reproducibility.

Visualizing functional pathways in the human brain using correlation tensors and magnetic resonance imaging

Functional magnetic resonance imaging usually detects changes in blood oxygenation level dependent (BOLD) signals from T2*-sensitive acquisitions, and is most effective in detecting activity in brain cortex which is irrigated by rich vasculature to meet high metabolic demands. We recently demonstrated that MRI signals from T2*-sensitive acquisitions in a resting state exhibit structure-specific temporal correlations along white matter tracts. In this report we validate our preliminary findings and introduce spatio-temporal functional correlation tensors to characterize the directional preferences of temporal correlations in MRI signals acquired at rest. The results bear a remarkable similarity to data obtained by diffusion tensor imaging but without any diffusion-encoding gradients. Just as in gray matter, temporal correlations in resting state signals may reflect intrinsic synchronizations of neural activity in white matter. Here we demonstrate that functional correlation tensors are able to visualize long range white matter tracts as well as short range sub-cortical fibers imaged at rest, and that evoked functional activities alter these structures and enhance the visualization of relevant neural circuitry. Furthermore, we explore the biophysical mechanisms underlying these phenomena by comparing pulse sequences, which suggest that white matter signal variations are consistent with hemodynamic (BOLD) changes associated with neural activity. These results suggest new ways to evaluate MRI signal changes within white matter.

Analysis and correction of biases in cross-relaxation MRI due to biexponential longitudinal relaxation

PURPOSE

Cross-relaxation imaging (CRI) is a family of quantitative magnetization transfer techniques that utilize images obtained with off-resonance saturation and longitudinal relaxation rate (R1) maps reconstructed by the variable flip angle (VFA) method. It was demonstrated recently that a significant bias in an apparent VFA R1 estimation occurs in macromolecule-rich tissues due to magnetization transfer (MT)-induced biexponential behavior of longitudinal relaxation of water protons. The purpose of this article is to characterize theoretically and experimentally the resulting bias in the CRI maps and propose methods to correct it.

THEORY

The modified CRI algorithm is proposed, which corrects for such biases and yields accurate parametric bound pool fraction f, cross-relaxation rate k, and R1 maps. Additionally, an analytical correction procedure is introduced to recalculate previously obtained parameter values.

RESULTS

The systematic errors due to unaccounted MT-induced biexponential relaxation can be characterized as an overestimation of R1, f, and k, with a relative bias comparable with the magnitude of f. The phantom and human in vivo experiments demonstrate that both proposed modified CRI and analytical correction approaches significantly improve the accuracy of the CRI method.

CONCLUSION

The accuracy of the CRI method can be considerably improved by taking into account the contribution of MT-induced biexponential longitudinal relaxation into variable flip angle R1 measurements.

Efficient 2D MRI relaxometry using compressed sensing

Potential applications of 2D relaxation spectrum NMR and MRI to characterize complex water dynamics (e.g., compartmental exchange) in biology and other disciplines have increased in recent years. However, the large amount of data and long MR acquisition times required for conventional 2D MR relaxometry limits its applicability for in vivo preclinical and clinical MRI. We present a new MR pipeline for 2D relaxometry that incorporates compressed sensing (CS) as a means to vastly reduce the amount of 2D relaxation data needed for material and tissue characterization without compromising data quality. Unlike the conventional CS reconstruction in the Fourier space (k-space), the proposed CS algorithm is directly applied onto the Laplace space (the joint 2D relaxation data) without compressing k-space to reduce the amount of data required for 2D relaxation spectra. This framework is validated using synthetic data, with NMR data acquired in a well-characterized urea/water phantom, and on fixed porcine spinal cord tissue. The quality of the CS-reconstructed spectra was comparable to that of the conventional 2D relaxation spectra, as assessed using global correlation, local contrast between peaks, peak amplitude and relaxation parameters, etc. This result brings this important type of contrast closer to being realized in preclinical, clinical, and other applications.

The microstructural correlates of T1 in white matter

PURPOSE

Several studies have shown strong correlations between myelin content and T1 within the brain, and have even suggested that T1 can be used to estimate myelin content. However, other micro-anatomical features such as compartment size are known to affect longitudinal relaxation rates, similar to compartment size effects in porous media.

METHODS

T1 measurements were compared with measured or otherwise published axon size measurements in white matter tracts of the rat spinal cord, rat brain, and human brain.

RESULTS

In both ex vivo and in vivo studies, correlations were present between the relaxation rate 1/T1 and axon size across regions of rat spinal cord with nearly equal myelin content.

CONCLUSION

While myelination is likely the dominant determinant of T1 in white matter, variations in white matter microstructure, independent of myelin volume fraction, may also be reflected in T1 differences between regions or subjects.

In vivo magnetic resonance imaging at 11.7 Tesla visualized the effects of neonatal transection of infraorbital nerve upon primary and secondary trigeminal pathways in rats

Using 11.7T ultra high-field T2-weighted MRI, the present study aimed to investigate pathological changes of primary and secondary trigeminal pathways following neonatal transection of infraorbital nerve in rats. The trigeminal pathways consist of spinal trigeminal tract, trigeminal sensory nuclear complex, medial lemniscus, ventromedial portion of external medullary lamina and ventral posterior nucleus of thalamus. By selecting optimum parameters of MRI such as repetition time, echo time, and slice orientation, this study visualized the trigeminal pathways in rats without any contrast agents. Pathological changes due to the nerve transection were found at 8 weeks of age as a marked reduction of the areas of the trigeminal pathways connecting from the injured nerve. In addition, T2-weighted MR images of the trigeminal nerve trunk and the spinal trigeminal tract suggest a communication of CSF through the trigeminal nerve between the inside and outside of the brain stem. These results support the utility of ultra high-field MRI system for noninvasive assessment of effects of trigeminal nerve injury upon the trigeminal pathways.

Probing signal phase in direct visualization of short transverse relaxation time component (ViSTa)

PURPOSE

To demonstrate the phase evolutions of direct visualization of short transverse relaxation time component (ViSTa) matches with those of myelin water.

METHOD

Myelin water imaging (MWI) measures short transverse signals and has been suggested as a biomarker for myelin. Recently, a new approach, ViSTa, has been proposed to acquire short T2* signals by suppressing long T1 signals. This method does not require any ill-conditioned data processing and therefore provides high-quality images. In this study, the phase of the ViSTa signal was compared with the phase of myelin water simulated by the magnetic susceptibility model of hollow cylinder.

RESULTS

The phase evolutions of the ViSTa signal were similar to the simulated myelin water phase evolutions. When fiber orientation was perpendicular relative to the main magnetic field, both the ViSTa and the simulated myelin water phase showed large positive frequency shifts, whereas the gradient echo phase showed a slightly negative frequency shift. Additionally, the myelin water phase map generated using diffusion tensor imaging (DTI) information revealed a good match with the ViSTa phase image.

CONCLUSION

The results of this study support the origin of ViSTa signal as myelin water. ViSTa phase may potentially provide sensitivity to demyelination.

Measurement of T1 of the ultrashort T2* components in white matter of the brain at 3T

Recent research demonstrates that white matter of the brain contains not only long T2 components, but a minority of ultrashort T2* components. Adiabatic inversion recovery prepared dual echo ultrashort echo time (IR-dUTE) sequences can be used to selectively image the ultrashort T2* components in white matter of the brain using a clinical whole body scanner. The T2*s of the ultrashort T2* components can be quantified using mono-exponential decay fitting of the IR-dUTE signal at a series of different TEs. However, accurate T1 measurement of the ultrashort T2* components is technically challenging. Efficient suppression of the signal from the majority of long T2 components is essential for robust T1 measurement. In this paper we describe a novel approach to this problem based on the use of IR-dUTE data acquisitions with different TR and TI combinations to selectively detect the signal recovery of the ultrashort T2* components. Exponential recovery curve fitting provides efficient T1 estimation, with minimized contamination from the majority of long T2 components. A rubber phantom and a piece of bovine cortical bone were used for validation of this approach. Six healthy volunteers were studied. An averaged T2* of 0.32±0.09 ms, and a short mean T1 of 226±46 ms were demonstrated for the healthy volunteers at 3T.

MRI-based myelin water imaging: A technical review

Multiexponential T2 relaxation time measurement in the central nervous system shows a component that originates from water trapped between the lipid bilayers of myelin. This myelin water component is of significant interest as it provides a myelin-specific MRI signal of value in assessing myelin changes in cerebral white matter in vivo. In this article, the various acquisition and analysis strategies proposed to date for myelin water imaging are reviewed and research conducted into their validity and clinical applicability is presented. Comparisons between the imaging methods are made with a discussion regarding potential difficulties and model limitations.

Quantifying the local tissue volume and composition in individual brains with magnetic resonance imaging

We describe a quantitative neuroimaging method to estimate the macromolecular tissue volume (MTV), a fundamental measure of brain anatomy. By making measurements over a range of field strengths and scan parameters, we tested the key assumptions and the robustness of the method. The measurements confirm that a consistent, quantitative estimate of macromolecular volume can be obtained across a range of scanners. MTV estimates are sufficiently precise to enable a comparison between data obtained from an individual subject with control population data. We describe two applications. First, we show that MTV estimates can be combined with T1 and diffusion measurements to augment our understanding of the tissue properties. Second we show that MTV provides a sensitive measure of disease status in individual patients with multiple sclerosis. The MTV maps are obtained using short clinically appropriate scans that can reveal how tissue changes influence behavior and cognition.

Ultrashort echo time (UTE) magnetic resonance imaging of the short T2 components in white matter of the brain using a clinical 3T scanner

White matter of the brain contains a majority of long T2 components as well as a minority of short T2 components. These are not detectable using clinical magnetic resonance imaging (MRI) sequences with conventional echo times (TEs). In this study we used ultrashort echo time (UTE) sequences to investigate the ultrashort T2 components in white matter of the brain and quantify their T2*s and relative proton densities (RPDs) (relative to water with a proton density of 100%) using a clinical whole body 3T scanner. An adiabatic inversion recovery prepared dual echo UTE (IR-dUTE) sequence was used for morphological imaging of the ultrashort T2 components in white matter. IR-dUTE acquisitions at a constant TR of 1000 ms and a series of TIs were performed to determine the optimal TI which corresponded to the minimum signal to noise ratio (SNR) in white matter of the brain on the second echo image. T2*s of the ultrashort T2 components were quantified using mono-exponential decay fitting of the IR-dUTE signal at a series of TEs. RPD was quantified by comparing IR-dUTE signal of the ultrashort T2 components with that of a rubber phantom. Nine healthy volunteers were studied. The IR-dUTE sequence provided excellent image contrast for the ultrashort T2 components in white matter of the brain with a mean signal to noise ratio of 18.7 ± 3.7 and a contrast to noise ratio of 14.6 ± 2.4 between the ultrashort T2 white matter and gray matter in a 4.4 min scan time with a nominal voxel size of 1.25 × 1.25 × 5.0mm(3). On average a T2* value of 0.42 ± 0.08 ms and a RPD of 4.05 ± 0.88% were demonstrated for the ultrashort T2 components in white matter of the brain of healthy volunteers at 3T.