Andrada Ianuş

PGSE, OGSE, and sensitivity to axon diameter in diffusion MRI: Insight from a simulation study.

To identify optimal pulsed gradient spin‐echo (PGSE) and oscillating gradient spin‐echo (OGSE) sequence settings for maximizing sensitivity to axon diameter in idealized and practical conditions.

Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology?

Conventional magnetic resonance imaging (MRI) of the multiple sclerosis spinal cord is limited by low specificity regarding the underlying pathological processes, and new MRI metrics assessing microscopic damage are required. We aim to show for the first time that neurite orientation dispersion (i.e., variability in axon/dendrite orientations) is a new biomarker that uncovers previously undetected layers of complexity of multiple sclerosis spinal cord pathology. Also, we validate against histology a clinically viable MRI technique for dispersion measurement (neurite orientation dispersion and density imaging,NODDI), to demonstrate the strong potential of the new marker.

Gaussian phase distribution approximations for oscillating gradient spin echo diffusion MRI

Oscillating gradients provide an optimal probe of small pore sizes in diffusion MRI. While sinusoidal oscillations have been popular for some time, recent work suggests additional benefits of square or trapezoidal oscillating waveforms. This paper presents analytical expressions of the free and restricted diffusion signal for trapezoidal and square oscillating gradient spin echo (OGSE) sequences using the Gaussian phase distribution (GPD) approximation and generalises existing similar expressions for sinusoidal OGSE. Accurate analytical models are necessary for exploitation of these pulse sequences in imaging studies, as they allow model fitting and parameter estimation in reasonable computation times. We evaluate the accuracy of the approximation against synthesised data from the Monte Carlo (MC) diffusion simulator in Camino and Callaghans matrix method and we show that the accuracy of the approximation is within a few percent of the signal, while providing several orders of magnitude faster computation. Moreover, since the expressions for trapezoidal wave are complex, we test sine and square wave approximations to the trapezoidal OGSE signal. The best approximations depend on the gradient amplitude and the oscillation frequency and are accurate to within a few percent. Finally, we explore broader applications of trapezoidal OGSE, in particular for non-model based applications, such as apparent diffusion coefficient estimation, where only sinusoidal waveforms have been considered previously. We show that with the right apodisation, trapezoidal waves also have benefits by virtue of the higher diffusion weighting they provide compared to sinusoidal gradients.

Double oscillating diffusion encoding and sensitivity to microscopic anisotropy.

To introduce a novel diffusion pulse sequence, namely double oscillating diffusion encoding (DODE), and to investigate whether it adds sensitivity to microscopic diffusion anisotropy (µA) compared to the well‐established double diffusion encoding (DDE) methodology.

Model-based estimation of microscopic anisotropy using diffusion MRI: a simulation study

Non‐invasive estimation of cell size and shape is a key challenge in diffusion MRI. This article presents a model‐based approach that provides independent estimates of pore size and eccentricity from diffusion MRI data. The technique uses a geometric model of finite cylinders with gamma‐distributed radii to represent pores of various sizes and elongations. We consider both macroscopically isotropic substrates and substrates of semi‐coherently oriented anisotropic pores and we use Monte Carlo simulations to generate synthetic data. We compare the sensitivity of single and double diffusion encoding (SDE and DDE) sequences to the size distribution and eccentricity, and further analyse different protocols of DDE sequences with parallel and/or perpendicular pairs of gradients. We show that explicitly accounting for size distribution is necessary for accurate microstructural parameter estimates, and a model that assumes a single size yields biased eccentricity values. We also find that SDE sequences support estimates, although DDE sequences with mixed parallel and perpendicular gradients enhance accuracy. In the case of macroscopically anisotropic substrates, this model‐based approach can be extended to a rotationally invariant framework to provide features of pore shape (specifically eccentricity) in the presence of size distribution and orientation dispersion. Copyright

Low frequency oscillating gradient spin-echo sequences improve sensitivity to axon diameter: An experimental study in viable nerve tissue

Abstract Mapping axon diameters within the central and peripheral nervous system could play an important role in our understanding of nerve pathways, and help diagnose and monitor an array of neurological disorders. Numerous diffusion MRI methods have been proposed for imaging axon diameters, most of which use conventional single diffusion encoding (SDE) spin echo sequences. However, a growing number of studies show that oscillating gradient spin echo (OGSE) sequences can provide additional advantages over conventional SDE sequences. Recent theoretical results suggest that this is especially the case in realistic scenarios, such as when fibres have unknown or dispersed orientation. In the present study, we adopt the ActiveAx approach to experimentally investigate the extent of these advantages by comparing the performances of SDE and trapezoidal OGSE in viable nerve tissue. We optimise SDE and OGSE ActiveAx protocols for a rat peripheral nerve tissue and test their performance using Monte Carlo simulations and a 800 mT/m gradient strength pre‐clinical imaging experiment. The imaging experiment uses excised sciatic nerve from a rats leg placed in a MRI compatible viable isolated tissue (VIT) maintenance chamber, which keeps the tissue in a viable physiological state that preserves the structural complexity of the nerve and enables lengthy scan times. We compare model estimates to histology, which we perform on the nerve post scanning. Optimisation produces a three‐shell SDE and OGSE ActiveAx protocol, with the OGSE protocol consisting of one SDE sequence and two low‐frequency oscillating gradient waveform sequences. Both simulation and imaging results show that the OGSE ActiveAx estimates of the axon diameter index have a higher accuracy and a higher precision compared to those from SDE. Histology estimates of the axon diameter index in our nerve tissue samples are 4–5.8 &mgr;m and these are excellently matched with the OGSE estimates 4.2–6.5 &mgr;m, while SDE overestimates at 5.2–8 &mgr;m for the same sample. We found OGSE estimates to be more precise with on average a 0.5 &mgr;m standard deviation compared to the SDE estimates which have a 2 &mgr;m standard deviation. When testing the robustness of the estimates when the number of the diffusion gradient directions reduces, we found that both OGSE and SDE estimates are affected, however OGSE is more robust to these changes than the SDE. Overall, these results suggest, quantitatively and in in vivo conditions, that low‐frequency OGSE sequences may provide improved accuracy of axon diameter mapping compared to standard SDE sequences. HighlightsPerformance of SDE and OGSE ActiveAx are compared for axon diameter imaging.A viable rat sciatic nerve and Monte Carlo simulations are used as samples.OGSE outperforms SDE in accuracy, precision and robustness of diameter estimates.Optimal OGSE has low frequency with results matching histology at 800 mT/m.

Microstructure Imaging Sequence Simulation Toolbox

This work describes Microstructure Imaging Sequence Simulation Toolbox (MISST), a practical diffusion MRI simulator for development, testing, and optimisation of novel MR pulse sequences for microstructure imaging. Diffusion MRI measures molecular displacement at microscopic level and provides a non-invasive tool for probing tissue microstructure. The measured signal is determined by various cellular features such as size, shape, intracellular volume fraction, orientation, etc., as well as the acquisition parameters of the diffusion sequence. Numerical simulations are a key step in understanding the effect of various parameters on the measured signal, which is important when developing new techniques for characterizing tissue microstructure using diffusion MRI. Here we present MISST - a semi-analytical simulation software, which is based on a matrix method approach and computes diffusion signal for fully general, user specified pulse sequences and tissue models. Its key purpose is to provide a deep understanding of the restricted diffusion MRI signal for a wide range of realistic, fully flexible scanner acquisition protocols, in practical computational time.

Sensitivity of OGSE ActiveAx to Microstructural Dimensions on a Clinical Scanner

Axon diameter can play a key role in the function and performance of nerve pathways of the central and peripheral nervous system. Previously, a number of techniques to measure axon diameter using diffusion MR I have been proposed, majority of which uses single diffusion encoding (SDE) spin-echo sequence. However, recent theoretical research suggests that low-frequency oscillating gradient spin echo (OGSE ) offers benefits over SDE for imaging diameters when fibres are of unknown orientation. Furthermore, it suggests that resolution limit for clinical scanners (gradient strength of 60–80 mT/m) is ≈ 6 μm. Here we investigate the sensitivity of OGSE to fibre diameters experimentally on a clinical scanner, using microcapillaries of unknown orientation. We use the orientationally invariant OGSE ActiveAx method to image microcapillaries with diameters of 5, 10 or 20 μm. As predicted by theory, we find that 5 μm diameters are undistinguishable from zero. Furthermore, we find accurate and precise estimates for 10 and 20 μm. Finally, we find that low frequency oscillating gradient waveforms are optimal for accurate diameter estimation.

An optimized framework for quantitative magnetization transfer imaging of the cervical spinal cord in vivo

To develop a framework to fully characterize quantitative magnetization transfer indices in the human cervical cord in vivo within a clinically feasible time.

Model-Based Estimation of Microscopic Anisotropy in Macroscopically Isotropic Substrates Using Diffusion MRI

Non-invasive estimation of cell size and shape is a key challenge in diffusion MRI. Changes in cell size and shape discriminate functional areas in the brain and can highlight different degrees of malignancy in cancer tumours. Consequently various methods have emerged recently that aim to measure the microscopic anisotropy of porous media such as biological tissue and aim to reflect pore eccentricity, the simplest shape feature. However, current methods assume a substrate of identical pores, and are strongly influenced by non-trivial size distribution. This paper presents a model-based approach that provides estimates of pore size and shape from diffusion MRI data. The technique uses a geometric model of randomly oriented finite cylinders with gamma distributed radii. We use Monte Carlo simulation to generate synthetic data in substrates consisting of randomly oriented cuboids with various size distributions and eccentricities. We compare the sensitivity of single and double pulsed field gradient (sPFG and dPFG) sequences to the size distribution and eccentricity and further compare different protocols of dPFG sequences with parallel and/or perpendicular pairs of gradients. The key result demonstrates that this model-based approach can provide features of pore shape (specifically eccentricity) that are independent of the size distribution unlike previous attempts to characterise microscopic anisotropy. We show further that explicitly accounting for size distribution is necessary for accurate estimates of average size and eccentricity, and a model that assumes a single size fails to recover the ground truth values. We find the most accurate parameter estimates for dPFG sequences with mixed parallel and perpendicular gradients, nevertheless all other sequences, including sPFG, show sensitivity as well.