Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI

The key component of a microstructural diffusion MRI 'super-scanner' is a dedicated high-strength gradient system that enables stronger diffusion weightings per unit time compared to conventional gradient designs. This can, in turn, drastically shorten the time needed for diffusion encoding, increase the signal-to-noise ratio, and facilitate measurements at shorter diffusion times. This review, written from the perspective of the UK National Facility for In Vivo MR Imaging of Human Tissue Microstructure, an initiative to establish a shared 300 mT/m-gradient facility amongst the microstructural imaging community, describes ten advantages of ultra-strong gradients for microstructural imaging. Specifically, we will discuss how the increase of the accessible measurement space compared to a lower-gradient systems (in terms of Δ, b-value, and TE) can accelerate developments in the areas of 1) axon diameter distribution mapping; 2) microstructural parameter estimation; 3) mapping micro-vs macroscopic anisotropy features with gradient waveforms beyond a single pair of pulsed-gradients; 4) multi-contrast experiments, e.g. diffusion-relaxometry; 5) tractography and high-resolution imaging in vivo and 6) post mortem; 7) diffusion-weighted spectroscopy of metabolites other than water; 8) tumour characterisation; 9) functional diffusion MRI; and 10) quality enhancement of images acquired on lower-gradient systems. We finally discuss practical barriers in the use of ultra-strong gradients, and provide an outlook on the next generation of 'super-scanners'

Lessons on brain edema in HE: from cellular to animal models and clinical studies

Brain edema is considered as a common feature associated with hepatic encephalopathy (HE). However, its central role as cause or consequence of HE and its implication in the development of the neurological alterations linked to HE are still under debate. It is now well accepted that type A and type C HE are biologically and clinically different, leading to different manifestations of brain edema. As a result, the findings on brain edema/swelling in type C HE are variable and sometimes controversial. In the light of the changing natural history of liver disease, better description of the clinical trajectory of cirrhosis and understanding of molecular mechanisms of HE, and the role of brain edema as a central component in the pathogenesis of HE is revisited in the current review. Furthermore, this review highlights the main techniques to measure brain edema and their advantages/disadvantages together with an in-depth description of the main ex-vivo/in-vivo findings using cell cultures, animal models and humans with HE. These findings are instrumental in elucidating the role of brain edema in HE and also in designing new multimodal studies by performing in-vivo combined with ex-vivo experiments for a better characterization of brain edema longitudinally and of its role in HE, especially in type C HE where water content changes are small

Lessons on brain edema in HE : from cellular to animal models and clinical studies

Brain edema is considered as a common feature associated with hepatic encephalopathy (HE). However, its central role as cause or consequence of HE and its implication in the development of the neurological alterations linked to HE are still under debate. It is now well accepted that type A and type C HE are biologically and clinically different, leading to different manifestations of brain edema. As a result, the findings on brain edema/swelling in type C HE are variable and sometimes controversial. In the light of the changing natural history of liver disease, better description of the clinical trajectory of cirrhosis and understanding of molecular mechanisms of HE, and the role of brain edema as a central component in the pathogenesis of HE is revisited in the current review. Furthermore, this review highlights the main techniques to measure brain edema and their advantages/disadvantages together with an in-depth description of the main ex-vivo/in-vivo findings using cell cultures, animal models and humans with HE. These findings are instrumental in elucidating the role of brain edema in HE and also in designing new multimodal studies by performing in-vivo combined with ex-vivo experiments for a better characterization of brain edema longitudinally and of its role in HE, especially in type C HE where water content changes are small

Investigating exchange, structural disorder and restriction in Gray Matter via water and metabolites diffusivity and kurtosis time-dependence

Water diffusion MRI is a very powerful tool for probing tissue microstructure, but disentangling the contribution of compartment-specific structural disorder from cellular restriction and inter-compartment exchange remains an open challenge. Here, we use diffusion MR spectroscopy (dMRS) of water and metabolites as a function of diffusion time in vivo in mouse Gray Matter (GM) to shed light on: which of these concomitant mechanisms dominates the MR measurements and with which specific signature. We report the diffusion time-dependence of water with excellent SNR conditions up to 500 ms. Water kurtosis decreases with increasing diffusion time, showing the concomitant influence of both structural disorder and exchange. Despite the excellent SNR, we were not able to identify clearly the nature of the structural disorder (i.e. 1D versus 2D/3D short-range disorder). Measurements of intracellular metabolites diffusion time-dependence (up to 500 ms) show opposite behavior to water, with metabolites kurtosis increasing as a function of diffusion time. We show that this is a signature of diffusion restricted in the intracellular space from which cellular microstructural features can be estimated. Finally, by comparing water and metabolites diffusion time-dependencies, we attempt to disentangle the effect of intra/extracellular exchange and structural disorder of the extracellular space (both impacting water diffusion only). Our results suggest a relatively short intra/extracellular exchange time (1-50 ms) and short-range disorder (still unclear if 1D or 2D/3D) most likely coming from the extracellular compartment. This work provides novel insights to interpret water diffusion time-dependent measurements in terms of the underlying GM microstructure and suggests that diffusion time-dependent measurements of intracellular metabolites may offer a new way to quantify microstructural restrictions in GM

Axon diameters and myelin content modulate microscopic fractional anisotropy at short diffusion times in fixed rat spinal cord

Mapping tissue microstructure accurately and noninvasively is one of the frontiers of biomedical imaging. Diffusion Magnetic Resonance Imaging (MRI) is at the forefront of such efforts, as it is capable of reporting on microscopic structures orders of magnitude smaller than the voxel size by probing restricted diffusion. Double Diffusion Encoding (DDE) and Double Oscillating Diffusion Encoding (DODE) in particular, are highly promising for their ability to report on microscopic fractional anisotropy ({\mu}FA), a measure of the pore anisotropy in its own eigenframe, irrespective of orientation distribution. However, the underlying correlates of {\mu}FA have insofar not been studied. Here, we extract {\mu}FA from DDE and DODE measurements at ultrahigh magnetic field of 16.4T in the aim to probe fixed rat spinal cord microstructure. We further endeavor to correlate {\mu}FA with Myelin Water Fraction (MWF) derived from multiexponential T2 relaxometry, as well as with literature-based spatially varying axonal diameters. In addition, a simple new method is presented for extracting unbiased {\mu}FA from three measurements at different b-values. Our findings reveal strong anticorrelations between {\mu}FA (derived from DODE) and axon diameter in the distinct spinal cord tracts; a moderate correlation was also observed between {\mu}FA derived from DODE and MWF. These findings suggest that axonal membranes strongly modulate {\mu}FA, which - owing to its robustness towards orientation dispersion effects - reflects axon diameter much better than its typical FA counterpart. The {\mu}FA exhibited modulations when measured via oscillating or blocked gradients, suggesting selective probing of different parallel path lengths and providing insight into how those modulate {\mu}FA metrics. Our findings thus shed light into the underlying microstructural correlates of {\mu}FA and are (...

Macromolecular background signal and non-Gaussian metabolite diffusion determined in human brain using ultra-high diffusion weighting.

PURPOSE Definition of a macromolecular MR spectrum based on diffusion properties rather than relaxation time differences and characterization of non-Gaussian diffusion of brain metabolites with strongly diffusion-weighted MR spectroscopy. METHODS Short echo time MRS with strong diffusion-weighting with b-values up to 25 ms/μm2 at two diffusion times was implemented on a Connectom system and applied in combination with simultaneous spectral and diffusion decay modeling. Motion-compensation was performed with a combined method based on the simultaneously acquired water and a macromolecular signal. RESULTS The motion compensation scheme prevented spurious signal decay reflected in very small apparent diffusion constants for macromolecular signal. Macromolecular background signal patterns were determined using multiple fit strategies. Signal decay corresponding to non-Gaussian metabolite diffusion was represented by biexponential fit models yielding parameter estimates for human gray matter that are in line with published rodent data. The optimal fit strategies used constraints for the signal decay of metabolites with limited signal contributions to the overall spectrum. CONCLUSION The determined macromolecular spectrum based on diffusion properties deviates from the conventional one derived from longitudinal relaxation time differences calling for further investigation before use as experimental basis spectrum when fitting clinical MR spectra. The biexponential characterization of metabolite signal decay is the basis for investigations into pathologic alterations of microstructure

MP-PCA denoising for diffusion MRS data: promises and pitfalls

Diffusion-weighted (DW) magnetic resonance spectroscopy (MRS) suffers from a lower signal to noise ratio (SNR) compared to conventional MRS owing to the addition of diffusion attenuation. This technique can therefore strongly benefit from noise reduction strategies. In the present work, the Marchenko-Pastur principal component analysis (MP-PCA) denoising is tested on Monte Carlo simulations and on in vivo DW-MRS data acquired at 9.4T in the rat brain. We provide a descriptive study of the effects observed following different MP-PCA denoising strategies (denoising the entire matrix versus using a sliding window), in terms of apparent SNR, rank selection, noise correlation within and across b-values and quantification of metabolite concentrations and fitted diffusion coefficients. MP-PCA denoising yielded an increased apparent SNR, a more accurate B0 drift correction between shots, and similar estimates of metabolite concentrations and diffusivities compared to the raw data. No spectral residuals on individual shots were observed but correlations in the noise level across shells were introduced, an effect which was mitigated using a sliding window, but which should be carefully considered.Comment: Cristina Cudalbu and Ileana O. Jelescu have contributed equally to this manuscrip

MP-PCA denoising for diffusion MRS data: promises and pitfalls.

Diffusion-weighted (DW) magnetic resonance spectroscopy (MRS) suffers from a lower signal to noise ratio (SNR) compared to conventional MRS owing to the addition of diffusion attenuation. This technique can therefore strongly benefit from noise reduction strategies. In the present work, Marchenko-Pastur principal component analysis (MP-PCA) denoising is tested on Monte Carlo simulations and on in vivo DW-MRS data acquired at 9.4T in rat brain and at 3T in human brain. We provide a descriptive study of the effects observed following different MP-PCA denoising strategies (denoising the entire matrix versus using a sliding window), in terms of apparent SNR, rank selection, noise correlation within and across b-values and quantification of metabolite concentrations and fitted diffusion coefficients. MP-PCA denoising yielded an increased apparent SNR, a more accurate B0 drift correction between shots, and similar estimates of metabolite concentrations and diffusivities compared to the raw data. No spectral residuals on individual shots were observed but correlations in the noise level across shells were introduced, an effect which was mitigated using a sliding window, but which should be carefully considered

Early detection of human glioma sphere xenografts in mouse brain using diffusion MRI at 14.1 T.

Glioma models have provided important insights into human brain cancers. Among the investigative tools, MRI has allowed their characterization and diagnosis. In this study, we investigated whether diffusion MRI might be a useful technique for early detection and characterization of slow-growing and diffuse infiltrative gliomas, such as the proposed new models, LN-2669GS and LN-2540GS glioma sphere xenografts. Tumours grown in these models are not visible in conventional T2 -weighted or contrast-enhanced T1 -weighted MRI at 14.1 T. Diffusion-weighted imaging and diffusion tensor imaging protocols were optimized for contrast by exploring long diffusion times sensitive for probing the microstructural alterations induced in the normal brain by the slow infiltration of glioma sphere cells. Compared with T2 -weighted images, tumours were properly identified in their early stage of growth using diffusion MRI, and confirmed by localized proton MR spectroscopy as well as immunohistochemistry. The first evidence of tumour presence was revealed for both glioma sphere xenograft models three months after tumour implantation, while no necrosis, oedema or haemorrhage were detected either by MRI or by histology. Moreover, different values of diffusion indices, such as mean diffusivity and fractional anisotropy, were obtained in tumours grown from LN-2669GS and LN-2540GS glioma sphere lines. These observations highlighted diverse tumour microstructures for both xenograft models, which were reflected in histology. This study demonstrates the ability of diffusion MRI techniques to identify and investigate early stages of slow-growing, invasive tumours in the mouse brain, thus providing a potential imaging biomarker for early detection of tumours in humans