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•An approach for the estimation of MTE-NODDI parameters with released diffusivity is investigated.•Ischaemic stroke tissue properties are characterised via MTE-NODDI with released diffusivity.•MTE-NODDI diffusivity is significantly reduced in ischaemic tissue.•The intra-/extra-neurite transverse relaxation times provide complementary information.•The spatiotemporal evolution of MTE-NODDI parameters in ischaemic tissue is heterogeneous. The multi-echo neurite orientation dispersion and density imaging (MTE-NODDI) model has been proposed to overcome one of the shortcomings of conventional NODDI, namely the echo time (TE) dependence of the compartmental signal fractions, which stems from the intrinsic differences in the compartmental transverse relaxation times (T2). However, the model continues to be constrained by the limitation of having a fixed, brain-wide intrinsic diffusivity, d. The primary aim of this work is to assess the benefits and shortcomings of using MTE-NODDI to investigate the diffusion and T2 properties of ischaemic stroke tissue following middle cerebral artery occlusion (MCAo) in rat models. Given the known alterations in the diffusion properties in ischaemic tissue, a secondary aim is to assess an estimation approach for MTE-NODDI parameters that enables d to be released while also mitigating the consequent model degeneracy. Using the MTE-NODDI parameters, the spatiotemporal evolution of diffusion and T2 properties in ischaemic tissue was characterised from day one to day 23 post-MCAo. The proposed approach enables access to several unique tissue features that would otherwise be obscured by the conventional approach. Importantly, a marked reduction in d was observed, leading to significant changes in other MTE-NODDI parameters compared to the model employing a fixed d. The isotropic signal fraction displayed a significant increase in ischemic tissue, which appears in contradiction with previous works. Regarding the intra- and extra-neurite T2 values, T2,in and T2,en, a significant increment was observed at the ischaemic tissue, while the condition T2,in≥T2,en displayed a tendency to hold in both tissue types. More generally, some parameters, such as the isotropic signal fraction, the intrinsic diffusivity and both compartmental T2 values, display unique, heterogeneous spatiotemporal evolution, where the core and border zones of the ischaemic tissue show different behaviours. Overall, the newly estimated parameters show greater consistency with analogous estimates reported by published models, and are anticipated to significantly enhance the understanding of tissue properties following ischaemic stroke. [Display omitted]

IntroductionAmyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease involving widespread network disruption beyond the motor cortex. Deep gray matter (DGM) nuclei, crucial for motor and cognitive integration, remain underexplored in vivo. This study applied neurite orientation dispersion and density imaging (NODDI) to evaluate DGM microstructure and its relationship with clinical disability in ALS.MethodsDiffusion-weighted MRI data were acquired from 23 ALS patients and 24 age- and sex-matched healthy controls. Orientation dispersion index (ODI), neurite density index (NDI), and free water fraction (FWF) were extracted from the bilateral thalamus, caudate, putamen, pallidum, hippocampus, and amygdala using the Destrieux atlas. Group comparisons and partial correlations were adjusted for age, sex, and disease duration.ResultsNo significant group differences in DGM volumes or NODDI-derived metrics survived correction for multiple comparisons. Within the ALS group, several nominal (uncorrected) associations were observed between DGM microstructural metrics and ALSFRS-R subscores. Reduced respiratory subscores were associated with higher ODI in the left thalamus (ρ = 0.57, p = 0.0047, uncorrected). Fine-motor subscores showed nominal positive associations with ODI in the left (ρ = 0.48, p = 0.021, uncorrected) and right amygdala (ρ = 0.51, p = 0.012, uncorrected). Gross motor subscores were nominally associated with NDI in the right thalamus (ρ = 0.58, p = 0.004, uncorrected), left thalamus (ρ = 0.42, p = 0.047, uncorrected), left caudate (ρ = 0.52, p = 0.011, uncorrected), and right caudate (ρ = 0.57, p = 0.033, uncorrected). None of these associations survived false discovery rate correction and should therefore be interpreted as exploratory.DiscussionThese findings suggest subtle and predominantly exploratory associations between DGM microstructural properties and clinical measures in ALS. NODDI derived metrics, particularly ODI and NDI, may provide sensitive indices of subcortical microstructural variation, warranting further investigation in larger cohorts.

Neurite orientation dispersion and density imaging (NODDI) has become a popular diffusion MRI technique for investigating microstructural alternations during brain development, maturation and aging in health and disease. However, the NODDI model of diffusion does not explicitly account for compartment-specific T2 relaxation and its model parameters are usually estimated from data acquired with a single echo time (TE). Thus, the NODDI-derived measures, such as the intra-neurite signal fraction, also known as the neurite density index, could be T2-weighted and TE-dependent. This may confound the interpretation of studies as one cannot disentangle differences in diffusion from those in T2 relaxation. To address this challenge, we propose a multi-TE NODDI (MTE-NODDI) technique, inspired by recent studies exploiting the synergy between diffusion and T2 relaxation. MTE-NODDI could give robust estimates of the non-T2-weighted signal fractions and compartment-specific T2 values, as demonstrated by both simulation and in vivo data experiments. Results showed that the estimated non-T2 weighted intra-neurite fraction and compartment-specific T2 values in white matter were consistent with previous studies. The T2-weighted intra-neurite fractions from the original NODDI were found to be overestimated compared to their non-T2-weighted estimates; the overestimation increases with TE, consistent with the reported intra-neurite T2 being larger than extra-neurite T2. Finally, the inclusion of the free water compartment reduces the estimation error in intra-neurite T2 in the presence of cerebrospinal fluid contamination. With the ability to disentangle non-T2-weighted signal fractions from compartment-specific T2 relaxation, MTE-NODDI could help improve the interpretability of future neuroimaging studies, especially those in brain development, maturation and aging. •Conventional NODDI-derived compartment fractions are T2-weighted and TE-dependent.•MTE-NODDI disentangles non-T2-weighted signal fractions from T2 relaxation.•Robust intra-neurite T2 estimation in WM even with CSF contamination.•Non-T2-weighted fractions may improve the interpretability of neurodevelopmental studies.

Preterm infants are at high risk of neurodevelopmental impairment, which may be due to altered development of brain connectivity. We aimed to (i) assess structural brain development from 25 to 45 weeks gestational age (GA) using graph theoretical approaches and (ii) test the hypothesis that preterm birth results in altered white matter network topology. Sixty-five infants underwent MRI between 25+3 and 45+6 weeks GA. Structural networks were constructed using constrained spherical deconvolution tractography and were weighted by measures of white matter microstructure (fractional anisotropy, neurite density and orientation dispersion index). We observed regional differences in brain maturation, with connections to and from deep grey matter showing most rapid developmental changes during this period. Intra-frontal, frontal to cingulate, frontal to caudate and inter-hemispheric connections matured more slowly. We demonstrated a core of key connections that was not affected by GA at birth. However, local connectivity involving thalamus, cerebellum, superior frontal lobe, cingulate gyrus and short range cortico-cortical connections was related to the degree of prematurity and contributed to altered global topology of the structural brain network. The relative preservation of core connections at the expense of local connections may support more effective use of impaired white matter reserve following preterm birth. [Display omitted] •First characterisation of preterm brain networks weighted by microstructural features.•Preterm brain is resistant to disruptions in development of core connections.•Peripheral connections associated with cognition and behaviour are more vulnerable.

White matter maturation is a nonlinear and heterogeneous phenomenon characterized by axonal packing, increased axon caliber, and a prolonged period of myelination. While current in vivo diffusion MRI (dMRI) methods, like diffusion tensor imaging (DTI), have successfully characterized the gross structure of major white matter tracts, these measures lack the specificity required to unravel the distinct processes that contribute to microstructural development. Neurite orientation dispersion and density imaging (NODDI) is a dMRI approach that probes tissue compartments and provides biologically meaningful measures that quantify neurite density index (NDI) and orientation dispersion index (ODI). The purpose of this study was to characterize the magnitude and timing of major white matter tract maturation with NODDI from infancy through adolescence in a cross-sectional cohort of 104 subjects (0.6–18.8 years). To probe the regional nature of white matter development, we use an along-tract approach that partitions tracts to enable more fine-grained analysis. Major white matter tracts showed exponential age-related changes in NDI with distinct maturational patterns. Overall, analyses revealed callosal fibers developed before association fibers. Our along-tract analyses elucidate spatially varying patterns of maturation with NDI that are distinct from those obtained with DTI. ODI was not significantly associated with age in the majority of tracts. Our results support the conclusion that white matter tract maturation is heterochronous process and, furthermore, we demonstrate regional variability in the developmental timing within major white matter tracts. Together, these results help to disentangle the distinct processes that contribute to and more specifically define the time course of white matter maturation. •Neurite density index increases nonlinearly with age in major white matter tracts.•Callosal fibers develop earlier than association fibers using neurite density index.•Neurite density index rate of change varies along the length of tracts.•Orientation dispersion index is not related to age in the majority of tracts.

Microstructural changes in human brain white matter of young to middle-aged adults were studied using advanced diffusion Magnetic Resonance Imaging (dMRI). Multiple shell diffusion-weighted data were acquired using the Hybrid Diffusion Imaging (HYDI). The HYDI method is extremely versatile and data were analyzed using Diffusion Tensor Imaging (DTI), Neurite Orientation Dispersion and Density Imaging (NODDI), and q-space imaging approaches. Twenty-four females and 23 males between 18 and 55years of age were included in this study. The impact of age and sex on diffusion metrics were tested using least squares linear regressions in 48 white matter regions of interest (ROIs) across the whole brain and adjusted for multiple comparisons across ROIs. In this study, white matter projections to either the hippocampus or the cerebral cortices were the brain regions most sensitive to aging. Specifically, in this young to middle-aged cohort, aging effects were associated with more dispersion of white matter fibers while the tissue restriction and intra-axonal volume fraction remained relatively stable. The fiber dispersion index of NODDI exhibited the most pronounced sensitivity to aging. In addition, changes of the DTI indices in this aging cohort were correlated mostly with the fiber dispersion index rather than the intracellular volume fraction of NODDI or the q-space measurements. While men and women did not differ in the aging rate, men tend to have higher intra-axonal volume fraction than women. This study demonstrates that advanced dMRI using a HYDI acquisition and compartmental modeling of NODDI can elucidate microstructural alterations that are sensitive to age and sex. Finally, this study provides insight into the relationships between DTI diffusion metrics and advanced diffusion metrics of NODDI model and q-space imaging. •Age-related white matter changes were studied using Hybrid Diffusion Imaging.•NODDI diffusion indices are more sensitive to aging and sex differences than DTI.•Aging mainly causes dispersion in white matter fibers in middle-aged adults.•In young to middle-aged adults, men have greater axonal fractions and dispersion.•Age-related changes in axial and radial diffusivity are driven by fiber dispersion.

•Demonstrate how NODDI outputs change when the assumed axial diffusivity is modified.•Combine high b-value data (to isolate intra-axonal signal) with dispersed stick model.•Simultaneously estimate the intra-axonal axial diffusivity and orientation dispersion.•Results from in vivo data show intra-axonal axial diffusivity in range 2-2.5 µm2/ms.•Simulations demonstrate importance of incorporating noise characteristics in low SNR regime. To estimate microstructure-related parameters from diffusion MRI data, biophysical models make strong, simplifying assumptions about the underlying tissue. The extent to which many of these assumptions are valid remains an open research question. This study was inspired by the disparity between the estimated intra-axonal axial diffusivity from literature and that typically assumed by the Neurite Orientation Dispersion and Density Imaging (NODDI) model (d∥=1.7μm2/ms). We first demonstrate how changing the assumed axial diffusivity results in considerably different NODDI parameter estimates. Second, we illustrate the ability to estimate axial diffusivity as a free parameter of the model using high b-value data and an adapted NODDI framework. Using both simulated and in vivo data we investigate the impact of fitting to either real-valued or magnitude data, with Gaussian and Rician noise characteristics respectively, and what happens if we get the noise assumptions wrong in this high b-value and thus low SNR regime. Our results from real-valued human data estimate intra-axonal axial diffusivities of ∼2−2.5μm2/ms, in line with current literature. Crucially, our results demonstrate the importance of accounting for both a rectified noise floor and/or a signal offset to avoid biased parameter estimates when dealing with low SNR data.

•Diffusion metrics from multi-shell sequences are reliable and sensitive to gray matter microstructure.•NODDI complements traditional tensor and volume measures when predicting age and cognition.•NODDI metrics greatly improve the predictive power of models estimating individual differences. Recent advances in diffusion-weighted imaging have enabled us to probe the microstructure of even gray matter non-invasively. However, these advanced multi-shell protocols are often not included in large-scale studies as they significantly increase scan time. In this study, we investigated whether one set of multi-shell diffusion metrics commonly used in gray matter (as derived from Neurite Orientation Dispersion and Density Imaging, NODDI) provide enough additional information over typical tensor and volume metrics to justify the increased acquisition time, using the cognitive aging framework in the human hippocampus as a testbed. We first demonstrated that NODDI metrics are robust and reliable by replicating previous findings from our lab in a larger population of 79 younger (20.41 ± 1.89 years, 46 females) and 75 older (73.56 ± 6.26 years, 45 females) adults, showing that these metrics in the hippocampal subfields are sensitive to age and memory performance. We then asked how these subfield specific hippocampal NODDI metrics compared with standard tensor metrics and volume in predicting age and memory ability. We discovered that both NODDI and tensor measures separately predicted age and cognition in comparable capacities. However, integrating these modalities together considerably increased the predictive power of our logistic models, indicating that NODDI and tensor measures may be capturing independent microstructural information. We use these findings to encourage neuroimaging data collection consortiums to include a multi-shell diffusion sequence in their protocols since existing NODDI measures (and potential future multi-shell measures) may be able to capture microstructural variance that is missed by traditional approaches, even in studies exclusively examining gray matter.

This paper presents Bingham–NODDI, a clinically-feasible technique for estimating the anisotropic orientation dispersion of neurites. Direct quantification of neurite morphology on clinical scanners was recently realised by a diffusion MRI technique known as neurite orientation dispersion and density imaging (NODDI). However in its current form NODDI cannot estimate anisotropic orientation dispersion, which is widespread in the brain due to common fanning and bending of neurites. This work proposes Bingham–NODDI that extends the NODDI formalism to address this limitation. Bingham–NODDI characterises anisotropic orientation dispersion by utilising the Bingham distribution to model neurite orientation distribution. The new model estimates the extent of dispersion about the dominant orientation, separately along the primary and secondary dispersion orientations. These estimates are subsequently used to estimate the overall dispersion about the dominant orientation and the dispersion anisotropy. We systematically evaluate the ability of the new model to recover these key parameters of anisotropic orientation dispersion with standard NODDI protocol, both in silico and in vivo. The results demonstrate that the parameters of the proposed model can be estimated without additional acquisition requirements over the standard NODDI protocol. Thus anisotropic dispersion can be determined and has the potential to be used as a marker for normal brain development and ageing or in pathology. We additionally find that the original NODDI model is robust to the effects of anisotropic orientation dispersion, when the quantification of anisotropic dispersion is not of interest. •We propose a method to estimate anisotropic orientation dispersion of neurites.•Estimation of this anisotropy enhances tractography and is a potential marker of disease.•The method uses NODDI, a clinically feasible technique to estimate neurite morphology.•We show that the estimation of indices of the proposed model is clinically feasible.•The new model explains the data better in white matter compared to the original model.

Human cortical development during the third trimester is characterised by macro- and microstructural changes which are reflected in alterations in diffusion MRI (dMRI) measures, with significant decreases in cortical mean diffusivity (MD) and fractional anisotropy (FA). This has been interpreted as reflecting increased cellular density and dendritic arborisation. However, the fall in FA stops abruptly at 38 weeks post-menstrual age (PMA), and then tends to plateau, while MD continues to fall, suggesting a more complex picture and raising the hypothesis that after this age development is dominated by continuing increase in neural and organelle density rather than alterations in the geometry of dendritic trees. To test this, we used neurite orientation dispersion and density imaging (NODDI), acquiring multi-shell, high angular resolution dMRI and measures of cortical volume and mean curvature in 99 preterm infants scanned between 25 and 47 weeks PMA. We predicted that increased neurite and organelle density would be reflected in increases in neurite density index (NDI), while a relatively unchanging geometrical structure would be associated with constant orientation dispersion index (ODI). As dendritic arborisation is likely to be one of the drivers of gyrification, we also predicted that measures of cortical volume and curvature would correlate with ODI and show slower growth after 38 weeks. We observed a decrease of MD throughout the period, while cortical FA decreased from 25 to 38 weeks PMA and then increased. ODI increased up to 38 weeks and then plateaued, while NDI rose after 38 weeks. The evolution of ODI correlated with cortical volume and curvature. Regional analysis of cortical microstructure revealed a heterogenous pattern with increases in FA and NDI after 38 weeks confined to primary motor and sensory regions. These results support the interpretation that cortical development between 25 and 38 weeks PMA shows a predominant increase in dendritic arborisation and neurite growth, while between 38 and 47 weeks PMA it is dominated by increasing cellular and organelle density. [Display omitted] •DTI and NODDI cortical measures between 25 and 47 weeks GA•Early cortical changes consistent with dendritic arborisation and neurite growth•After 38 weeks cortical changes consistent with increasing cellular density•Cortical curvature evolves in parallel with dendritic arborisation