Rotationally-invariant mapping of scalar and orientational metrics of neuronal microstructure with diffusion MRI

We develop a general analytical and numerical framework for estimating intra- and extra-neurite water fractions and diffusion coefficients, as well as neurite orientational dispersion, in each imaging voxel. By employing a set of rotational invariants and their expansion in the powers of diffusion weighting, we analytically uncover the nontrivial topology of the parameter estimation landscape, showing that multiple branches of parameters describe the measurement almost equally well, with only one of them corresponding to the biophysical reality. A comprehensive acquisition shows that the branch choice varies across the brain. Our framework reveals hidden degeneracies in MRI parameter estimation for neuronal tissue, provides microstructural and orientational maps in the whole brain without constraints or priors, and connects modern biophysical modeling with clinical MRI.Comment: 25 pages, 12 figures, elsarticle two-colum

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

Cellular EXchange Imaging (CEXI): Evaluation of a diffusion model including water exchange in cells using numerical phantoms of permeable spheres

Purpose: Biophysical models of diffusion MRI have been developed to characterize microstructure in various tissues, but existing models are not suitable for tissue composed of permeable spherical cells. In this study we introduce Cellular Exchange Imaging (CEXI), a model tailored for permeable spherical cells, and compares its performance to a related Ball \& Sphere (BS) model that neglects permeability. Methods: We generated DW-MRI signals using Monte-Carlo simulations with a PGSE sequence in numerical substrates made of spherical cells and their extracellular space for a range of membrane permeability. From these signals, the properties of the substrates were inferred using both BS and CEXI models. Results: CEXI outperformed the impermeable model by providing more stable estimates cell size and intracellular volume fraction that were diffusion time-independent. Notably, CEXI accurately estimated the exchange time for low to moderate permeability levels previously reported in other studies ($\kappa<25\mu m/s$). However, in highly permeable substrates ($\kappa=50\mu m/s$), the estimated parameters were less stable, particularly the diffusion coefficients. Conclusion: This study highlights the importance of modeling the exchange time to accurately quantify microstructure properties in permeable cellular substrates. Future studies should evaluate CEXI in clinical applications such as lymph nodes, investigate exchange time as a potential biomarker of tumor severity, and develop more appropriate tissue models that account for anisotropic diffusion and highly permeable membranes.Comment: 7 figures, 2 tables, 21 pages, under revie

Orientation-Dispersed Apparent Axon Diameter via Multi-Stage Spherical Mean Optimization

The estimation of the apparent axon diameter (AAD) via diffusion MRI is affected by the incoherent alignment of single axons around its axon bundle direction, also known as orientational dispersion. The simultaneous estimation of AAD and dispersion is challenging and requires the optimization of many parameters at the same time. We propose to reduce the complexity of the estimation with an multi-stage approach, inspired to alternate convex search, that separates the estimation problem into simpler ones, thus avoiding the estimation of all the relevant model parameters at once. The method is composed of three optimization stages that are iterated, where we separately estimate the volume fractions, diffusivities, dispersion, and mean AAD, using a Cylinder and Zeppelin model. First, we use multi-shell data to estimate the undispersed axon micro-environment’s signal fractions and diffusivities using the spherical mean technique; then, to account for dispersion, we use the obtained micro-environment parameters to estimate a Watson axon orientation distribution; finally, we use data acquired perpendicularly to the axon bundle direction to estimate the mean AAD and updated signal fractions, while fixing the previously estimated diffusivity and dispersion parameters. We use the estimated mean AAD to initiate the following iteration. We show that our approach converges to good estimates while being more efficient than optimizing all model parameters at once. We apply our method to ex-vivo spinal cord data, showing that including dispersion effects results in mean apparent axon diameter estimates that are closer to their measured histological values

Recommendations and guidelines from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 1 -- In vivo small-animal imaging

The value of in vivo preclinical diffusion MRI (dMRI) is substantial. Small-animal dMRI has been used for methodological development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. Many of the influential works in this field were first performed in small animals or ex vivo samples. The steps from animal setup and monitoring, to acquisition, analysis, and interpretation are complex, with many decisions that may ultimately affect what questions can be answered using the data. This work aims to serve as a reference, presenting selected recommendations and guidelines from the diffusion community, on best practices for preclinical dMRI of in vivo animals. In each section, we also highlight areas for which no guidelines exist (and why), and where future work should focus. We first describe the value that small animal imaging adds to the field of dMRI, followed by general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in animal species and disease models and discuss how they are appropriate for different studies. We then give guidelines for in vivo acquisition protocols, including decisions on hardware, animal preparation, imaging sequences and data processing, including pre-processing, model-fitting, and tractography. Finally, we provide an online resource which lists publicly available preclinical dMRI datasets and software packages, to promote responsible and reproducible research. An overarching goal herein is to enhance the rigor and reproducibility of small animal dMRI acquisitions and analyses, and thereby advance biomedical knowledge.Comment: 69 pages, 6 figures, 1 tabl

Microscopie par résonance magnétique des neurones d’aplysie : étude du transport actif en présence de neurotransmetteurs, et de la réponse au stress

Recent progress in magnetic resonance imaging (MRI) has opened the way for micron-scale resolution, and thus for imaging biological cells. In this thesis work, we performed magnetic resonance microscopy (MRM) on the nervous system of Aplysia californica, a model particularly suited due to its simplicity and to its very large neuronal cell bodies, in the aim of studying cellular-scale processes with various MR contrasts. Experiments were performed on a 17.2 Tesla horizontal magnet, at resolutions down to 25 µm isotropic. Initial work consisted in conceiving and building radiofrequency microcoils adapted to the size of single neurons and ganglia. The first major part of the project consisted in using the manganese ion (Mn2+) as neural tract tracer in the buccal ganglia of Aplysia. Manganese is an MR contrast agent that enters neurons via voltage-gated calcium channels. We performed the mapping of axonal projections from motor neurons into the peripheral nerves of the buccal ganglia. We also confirmed the existence of active Mn2+ transport inside the neural network upon activation with the neurotransmitter dopamine. In the second major part of the project, we tested the potential of two diffusion MRI sequences for microscopy. On the one hand, we explored a very original mechanism for diffusion weighting, DESIRE (Diffusion Enhancement of SIgnal and REsolution), particularly suited for small samples. The two-dimensional DESIRE sequence was implemented and successfully tested on phantoms. The measured enhancement was consistent with theoretical predictions. Using this sequence to produce diffusion weighted images with an unprecedented contrast in biological tissue remains a challenge. On the other hand, a more “standard” sequence was implemented to measure the apparent diffusion coefficient (ADC) in nervous tissue with MRM. This sequence was a three-dimensional DP-FISP (Diffusion Prepared Fast Imaging with Steady-state free Precession), which met criteria for high resolution in a short acquisition time, with minimal artifacts. Using this sequence, we studied the changes in water ADC at different scales in the nervous system, triggered by cellular challenges. The challenges were hypotonic shock or exposure to ouabain. ADC measurements were performed on single isolated neuronal bodies and on ganglia tissue, before and after challenge. Both types of stress produced an ADC increase inside the cell and an ADC decrease at tissue level. The results favor the hypothesis that the increase in membrane surface area associated with cell swelling is responsible for the decrease of water ADC in tissue, typically measured in ischemia or other conditions associated with cell swelling.Les progrès technologiques récents en imagerie par résonance magnétique (IRM) ont ouvert la voie à une résolution spatiale de l’ordre de quelques microns, et donc à l’imagerie de cellules biologiques. Dans le cadre de ce projet, nous avons réalisé des expériences de microscopie IRM sur le système nerveux de l’aplysie (Aplysia californica), particulièrement adapté de par sa simplicité et de par la très grande taille de ses neurones, en vue d’étudier des processus à échelle cellulaire avec divers contrastes IRM. Les expériences d’imagerie ont été effectuées sur un aimant horizontal 17.2 Tesla, à des résolutions spatiales jusqu’à 25 µm isotrope. Le travail initial a consisté en la conception et fabrication de micro-antennes radiofréquences adaptées à la taille de neurones uniques et de ganglions. La première partie du projet a porté sur l’utilisation de l’ion manganèse (Mn2+) comme traceur de réseaux neuronaux dans le ganglion buccal de l’aplysie. Le manganèse (Mn) est un agent de contraste IRM qui pénètre dans les neurones par les canaux de calcium. La cartographie des projections axonales des neurones moteurs du ganglion dans chacun des nerfs périphériques a été établie. Il a également été démontré l’existence d’un transport actif du Mn2+ au sein du réseau neuronal activé par le neurotransmetteur dopamine. Dans un second temps, on s’est intéressé à deux méthodes de mesure de diffusion par IRM, à échelle microscopique. D’une part, un mécanisme de pondération en diffusion, DESIRE (Diffusion Enhancement of SIgnal and REsolution), original et particulièrement adapté à des échantillons petits, a été exploré. La séquence DESIRE a été implémentée en deux dimensions et testée avec succès sur fantôme. Le rehaussement mesuré était en accord avec les prévisions théoriques. Le grand défi à venir sera d’utiliser cette séquence pour acquérir des images de tissu biologique pondérées en diffusion avec un contraste unique. D’autre part, une séquence plus « classique » a été implémentée pour mesurer le coefficient de diffusion apparent (ADC) dans le tissu nerveux. Il s’agit d’une DP-FISP (Diffusion Prepared Fast Imaging with Steady-state free Precession) en trois dimensions, qui répond aux critères de résolution spatiale et de rapidité, avec un minimum d’artefacts. Cette séquence a permis d’étudier l’évolution de l’ADC de l’eau à différentes échelles du tissu nerveux en réponse à un stress cellulaire. Les deux sollicitations retenues étaient un choc hypotonique ou l’ajout d’ouabaïne. Des mesures d’ADC ont été effectuées sur des corps neuronaux isolés et sur du tissu de ganglion, avant et après sollicitation. Les deux types de stress ont entraîné une augmentation de l’ADC dans la cellule et une diminution globale de l’ADC dans le tissu. Ces résultats soutiennent l’hypothèse que la diffusion ralentie de l’eau habituellement observée dans un tissu ischémié (ou dans d’autres conditions associées à un gonflement cellulaire) est due à l’augmentation de surface membranaire

Design and Validation of Diffusion MRI Models of White Matter

Diffusion MRI is arguably the method of choice for characterizing white matter microstructure in vivo. Over the typical duration of diffusion encoding, the displacement of water molecules is conveniently on a length scale similar to that of the underlying cellular structures. Moreover, water molecules in white matter are largely compartmentalized which enables biologically-inspired compartmental diffusion models to characterize and quantify the true biological microstructure. A plethora of white matter models have been proposed. However, overparameterization and mathematical fitting complications encourage the introduction of simplifying assumptions that vary between different approaches. These choices impact the quantitative estimation of model parameters with potential detriments to their biological accuracy and promised specificity. First, we review biophysical white matter models in use and recapitulate their underlying assumptions and realms of applicability. Second, we present up-to-date efforts to validate parameters estimated from biophysical models. Simulations and dedicated phantoms are useful in assessing the performance of models when the ground truth is known. However, the biggest challenge remains the validation of the “biological accuracy” of estimated parameters. Complementary techniques such as microscopy of fixed tissue specimens have facilitated direct comparisons of estimates of white matter fiber orientation and densities. However, validation of compartmental diffusivities remains challenging, and complementary MRI-based techniques such as alternative diffusion encodings, compartment-specific contrast agents and metabolites have been used to validate diffusion models. Finally, white matter injury and disease pose additional challenges to modeling, which are also discussed. This review aims to provide an overview of the current state of models and their validation and to stimulate further research in the field to solve the remaining open questions and converge toward consensus