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Purpose: To compare the estimation accuracy of axisymmetric diffusion kurtosis imaging (DKI) and standard DKI in combination with Rician bias correction (RBC) under the influence of noise. Methods: Axisymmetric DKI is more robust against noise-induced variation in the measured signal than standard DKI because of its reduced parameter space. However, its susceptibility to Rician noise bias at low signal-to-noise ratios (SNRs) is unknown. Here, we investigate two main questions: first, does Rician bias correction improve estimation accuracy of axisymmetric DKI?; second, is the estimation accuracy of axisymmetric DKI increased compared to standard DKI? Estimation accuracy was investigated on the five axisymmetric DKI tensor metrics (AxTM): the parallel and perpendicular diffusivity and kurtosis and the mean kurtosis, using a simulation study based on synthetic and in-vivo data. Results: We found that RBC was most effective for increasing accuracy of the parallel AxTM in highly to moderately aligned white matter. For the perpendicular AxTM, axisymmetric DKI without RBC performed slightly better than with RBC. However, the combination of axisymmetric DKI with RBC was the overall best performing algorithm across all five AxTM and the axisymmetric DKI framework itself substantially improved accuracy in tissues with low fiber alignment. Conclusion: The combination of axisymmetric DKI with RBC facilitates accurate DKI parameter estimation at unprecedented low SNRs (approx 15), possibly making it a valuable tool for neuroscience and clinical research studies where scan time is a limited resource. The tools used in this paper are publicly available in the open-source ACID toolbox for SPM.

The effective transverse relaxation rate (mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"mml:semanticsmml:mrowmml:msubsupmml:miR/mml:mimml:mn2/mml:mnmml:mo*/mml:mo/mml:msubsup/mml:mrowmml:annotation$$ {\mathrm{R}}_2^{\ast } $$/mml:annotation/mml:semantics/mml:math) is influenced by biological features that make it a useful means of probing brain microstructure. However, confounding factors such as dependence on flip angle (α) and fiber orientation with respect to the main field (mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"mml:semanticsmml:mrowmml:miθ/mml:mi/mml:mrowmml:annotation$$ \uptheta $$/mml:annotation/mml:semantics/mml:math) complicate interpretation. The α- andmml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"mml:semanticsmml:mrowmml:miθ/mml:mi/mml:mrowmml:annotation$$ \uptheta $$/mml:annotation/mml:semantics/mml:math-dependence stem from the existence of multiple sub-voxel micro-environments (e.g., myelin and non-myelin water compartments). Ordinarily, it is challenging to quantify these sub-compartments; therefore, neuroscientific studies commonly make the simplifying assumption of a mono-exponential decay obtaining a singlemml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"mml:semanticsmml:mrowmml:msubsupmml:miR/mml:mimml:mn2/mml:mnmml:mo*/mml:mo/mml:msubsup/mml:mrowmml:annotation$$ {\mathrm{R}}_2^{\ast } $$/mml:annotation/mml:semantics/mml:mathestimate per voxel. In this work, we investigated how the multi-compartment nature of tissue microstructure affects single compartmentmml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"mml:semanticsmml:mrowmml:msubsupmml:miR/mml:mimml:mn2/mml:mnmml:mo*/mml:mo/mml:msubsup/mml:mrowmml:annotation$$ {\mathrm{R}}_2^{\ast } $$/mml:annotation/mml:semantics/mml:mathestimates.We used 2-pool (myelin and non-myelin water) simulations to characterize the bias in single compartmentmml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"mml:semanticsmml:mrowmml:msubsupmml:miR/mml:mimml:mn2/mml:mnmml:mo*/mml:mo/mml:msubsup/mml:mrowmml:annotation$$ {\mathrm{R}}_2^{\ast } $$/mml:annotation/mml:semantics/mml:mathestimates. Based on our numeric observations, we introduced a linear model that partitionsmml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"mml:semanticsmml:mrowmml:msubsupmml:miR/mml:mimml:mn2/mml:mnmml:mo*/mml:mo/mml:msubsup/mml:mrowmml:annotation$$ {\mathrm{R}}_2^{\ast } $$/mml:annotation/mml:semantics/mml:mathinto α-dependent and α-independent components and validated this in vivo at 7T. We investigated the dependence of both components on the sub-compartment properties and assessed their robustness, orientation dependence, and reproducibility empirically.mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"mml:semanticsmml:mrowmml:msubsupmml:miR/mml:mimml:mn2/mml:mnmml:mo*/mml:mo/mml:msubsup/mml:mrowmml:annotation$$ {\mathrm{R}}_2^{\ast } $$/mml:annotation/mml:semantics/mml:mathincreased with myelin water fraction and residency time leading to a linear dependence on α. We observed excellent agreement between our numeric and empirical results. Furthermore, the α-independent component of the proposed linear model was robust to the choice of α and reduced dependence on fiber orientation, although it suffered from marginally higher noise sensitivity.We have demonstrated and validated a simple approach that mitigates flip angle and orientation biases in single-compartmentmml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"mml:semanticsmml:mrowmml:msubsupmml:miR/mml:mimml:mn2/mml:mnmml:mo*/mml:mo/mml:msubsup/mml:mrowmml:annotation$$ {\mathrm{R}}_2^{\ast } $$/mml:annotation/mml:semantics/mml:mathestimates.

Biophysical models enable the non-invasive estimation of microstructural tissue features of the central nervous system such as the axonal volume fraction using diffusion weighted imaging (DWI)-data. However, these models trade accuracy with complexity and demands for time-efficient data acquisition. In this study, we hypothesise that their accuracy can be improved substantially through biophysically motivated, linear calibration. We test this hypothesis in the context of axonal volume fraction estimation in four different DWI-models of different complexity using multi-modal data including ex-vivo diffusion MRI- and electron microscopy (EM)-data in mice with broad dynamic range, whereby the latter served as gold standard. We found that two calibration parameters, an offset accounting for the fraction of unmyelinated axons in severely hypomyelinated mice and a scaling accounting for the compartment-specific relaxation, substantially improved the accuracy of axonal volume fraction. Furthermore, we theoretically predict the scaling parameter, and demonstrate that similar accuracy improvement can be achieved for a subset of DWI-models, if the scaling parameter is fixed to the predicted value instead of estimating it on basis of data. This is of practical relevance because it allows to estimate the remaining offset calibration parameter from a limited amount of multi-modal data and thus makes the proposed method usable in human brain data.

The effective transverse relaxation rate (R2*) is sensitive to the microstructure of the human brain, e.g. the g-ratio characterising the relative myelination of axons. However, R2* depends on the orientation of the fibres relative to the main magnetic field degrading its reproducibility and that of any microstructural derivative measure. To decipher its orientation-independent part (R2,iso*), a second-order polynomial in time (M2) can be applied to single multi-echo gradient-recalled-echo (meGRE) measurements at arbitrary orientation. The linear-time dependent parameter, β1, of M2 can be biophysically related to R2,iso* when neglecting the signal from the myelin water (MW) in the hollow cylinder fibre model (HCFM). Here, we examined the effectiveness of M2 using experimental and simulated data with variable g-ratio and fibre dispersion. We showed that the fitted β1 effectively estimates R2,iso*when using meGRE with long maximum echo time (TEmax ≈ 54 ms) but its microscopic dependence on the g-ratio was not accurately captured. This error was reduced to less than 12% when accounting for the MW contribution in a newly introduced biophysical expression for β1. We further used this new expression to estimate the MW fraction (0.14) and g-ratio (0.79) in a human optic chiasm. However, the proposed method failed to estimate R2,iso* for a typical in-vivo meGRE protocol (TEmax ≈ 18 ms). At this TEmax and around the magic angle, the HCFM-based simulations failed to explain the R2*-orientation-dependence. In conclusion, estimation of R2,iso* with M2 in vivo requires meGRE protocols with very long TEmax ≈ 54 ms.

ObjectivesTraumatic and non-traumatic spinal cord injury produce neurodegeneration across the entire neuraxis. However, the spatiotemporal dynamics of spinal cord grey and white matter neurodegeneration above and below the injury is understudied.MethodsWe acquired longitudinal data from 13 traumatic and 3 non-traumatic spinal cord injury patients (8–8 cervical and thoracic cord injuries) within 1.5 years after injury and 10 healthy controls over the same period. The protocol encompassed structural and diffusion-weighted MRI rostral (C2/C3) and caudal (lumbar enlargement) to the injury level to track tissue-specific neurodegeneration. Regression models assessed group differences in the temporal evolution of tissue-specific changes and associations with clinical outcomes.ResultsAt 2 months post-injury, white matter area was decreased by 8.5% and grey matter by 15.9% in the lumbar enlargement, while at C2/C3 only white matter was decreased (−9.7%). Patients had decreased cervical fractional anisotropy (FA: −11.3%) and increased radial diffusivity (+20.5%) in the dorsal column, while FA was lower in the lateral (−10.3%) and ventral columns (−9.7%) of the lumbar enlargement. White matter decreased by 0.34% and 0.35% per month at C2/C3 and lumbar enlargement, respectively, and grey matter decreased at C2/C3 by 0.70% per month.ConclusionsThis study describes the spatiotemporal dynamics of tissue-specific spinal cord neurodegeneration above and below a spinal cord injury. While above the injury, grey matter atrophy lagged initially behind white matter neurodegeneration, in the lumbar enlargement these processes progressed in parallel. Tracking trajectories of tissue-specific neurodegeneration provides valuable assessment tools for monitoring recovery and treatment effects.

The accessibility of new wide-scale multimodal imaging techniques led to numerous clearing techniques emerging over the last decade. However, clearing mesoscopic-sized blocks of aged human brain tissue remains an extremely challenging task. Homogenizing refractive indices and reducing light absorption and scattering are the foundation of tissue clearing. Due to its dense and highly myelinated nature, especially in white matter, the human brain poses particular challenges to clearing techniques. Here, we present a comparative study of seven tissue clearing approaches and their impact on aged human brain tissue blocks (> 5 mm). The goal was to identify the most practical and efficient method in regards to macroscopic transparency, brief clearing time, compatibility with immunohistochemical processing and wide-scale multimodal microscopic imaging. We successfully cleared 26 �� 26 �� 5 mm3-sized human brain samples with two hydrophilic and two hydrophobic clearing techniques. Optical properties as well as light and antibody penetration depths highly vary between these methods. In addition to finding the best clearing approach, we compared three microscopic imaging setups (the Zeiss Laser Scanning Microscope (LSM) 880 , the Miltenyi Biotec Ultramicroscope ll (UM ll) and the 3i Marianas LightSheet microscope) regarding optimal imaging of large-scale tissue samples. We demonstrate that combining the CLARITY technique (Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging compatible Tissue hYdrogel) with the Zeiss LSM 880 and combining the iDISCO technique (immunolabeling-enabled three-dimensional imaging of solvent-cleared organs) with the Miltenyi Biotec UM ll are the most practical and efficient approaches to sufficiently clear aged human brain tissue and generate 3D microscopic images. Our results point out challenges that arise from seven clearing and three imaging techniques applied to non-standardized tissue samples such as aged human brain tissue.

Non-invasive assessment of axon radii via MRI bears great potential for clinical and neuroscience research as it is a main determinant of the neuronal conduction velocity. However, there is a lack of representative histological reference data on the scale of the cross-section of MRI voxels for validating the MRI-visible, effective radius (reff). Because the current gold standard stems from neuroanatomical studies designed to estimate the frequency-weighted arithmetic mean radius (rarith) on small ensembles of axons, it is unsuited to estimate the tail-weighted reff. We propose CNN-based segmentation on high-resolution, large-scale light microscopy (lsLM) data to generate a representative reference for reff. In a human corpus callosum, we assessed estimation accuracy and bias of rarith and reff. Furthermore, we investigated whether mapping anatomy-related variation of rarith and reff is confounded by low-frequency variation of the image intensity, e.g., due to staining heterogeneity. Finally, we analyzed the potential error due to outstandingly large axons in reff. Compared to rarith, reff was estimated with higher accuracy (normalized-root-mean-square-error of reff: 7.2 %; rarith: 21.5 %) and lower bias (normalized-mean-bias-error of reff: −1.7 %; rarith: 16 %). While rarith was confounded by variation of the image intensity, variation of reff seemed anatomy-related. The largest axons contributed between 0.9 % and 3 % to reff. In conclusion, the proposed method accurately estimates reff at MRI voxel resolution across a human corpus callosum sample. Further investigations are required to assess generalization to brain areas with different axon radii ensembles.

Non-invasive assessment of axon radii via MRI bears great potential for clinical and neuroscience research as it is a main determinant of the neuronal conduction velocity. However, there is a lack of representative histological reference data at the scale of the cross-section of MRI voxels for validating the MRI-visible, effective radius (reff). Because the current gold standard stems from neuroanatomical studies designed to estimate the bulk-determined arithmetic mean radius (rarith) on small ensembles of axons, it is unsuited to estimate the tail-weighted reff. We propose CNN-based segmentation on high-resolution, large-scale light microscopy (lsLM) data to generate a representative reference for reff. In a human corpus callosum, we assessed estimation accuracy and bias of rarith and reff. Furthermore, we investigated whether mapping anatomy-related variation of rarith and reff is confounded by low-frequency variation of the image intensity, e.g., due to staining heterogeneity. Finally, we analyzed the error due to outstandingly large axons in reff. Compared to rarith, reff was estimated with higher accuracy (maximum normalized-root-mean-square-error of reff: 8.5 %; rarith: 19.5 %) and lower bias (maximum absolute normalized-mean-bias-error of reff: 4.8 %; rarith: 13.4 %). While rarith was confounded by variation of the image intensity, variation of reff seemed anatomy-related. The largest axons contributed between 0.8 % and 2.9 % to reff. In conclusion, the proposed method is a step towards representatively estimating reff at MRI voxel resolution. Further investigations are required to assess generalization to other brains and brain areas with different axon radii distributions.

Pathophysiological changes in the spinal cord white and grey matter resulting from injury can be observed with MRI techniques. These techniques provide sensitive markers of macrostructural and microstructural tissue integrity, which correlate with histological findings. Spinal cord MRI findings in traumatic spinal cord injury (tSCI) and nontraumatic spinal cord injury - the most common form of which is degenerative cervical myelopathy (DCM) - have provided important insights into the pathophysiological processes taking place not just at the focal injury site but also rostral and caudal to the spinal injury. Although tSCI and DCM have different aetiologies, they show similar degrees of spinal cord pathology remote from the injury site, suggesting the involvement of similar secondary degenerative mechanisms. Advanced quantitative MRI protocols that are sensitive to spinal cord pathology have the potential to improve diagnosis and, more importantly, predict outcomes in patients with tSCI or nontraumatic spinal cord injury. This Review describes the insights into tSCI and DCM that have been revealed by neuroimaging and outlines current activities and future directions for the field.

Purpose To propose and validate an efficient method, based on a biophysically motivated signal model, for removing the orientation-dependent part of R 2 * using a single gradient-recalled echo (GRE) measurement. Methods The proposed method utilized a temporal second-order approximation of the hollow-cylinder-fiber model, in which the parameter describing the linear signal decay corresponded to the orientation-independent part of R 2 * . The estimated parameters were compared to the classical, mono-exponential decay model for R 2 * in a sample of an ex vivo human optic chiasm (OC). The OC was measured at 16 distinct orientations relative to the external magnetic field using GRE at 7T. To show that the proposed signal model can remove the orientation dependence of R 2 * , it was compared to the established phenomenological method for separating R 2 * into orientation-dependent and -independent parts. Results Using the phenomenological method on the classical signal model, the well-known separation of R 2 * into orientation-dependent and -independent parts was verified. For the proposed model, no significant orientation dependence in the linear signal decay parameter was observed. Conclusions Since the proposed second-order model features orientation-dependent and -independent components at distinct temporal orders, it can be used to remove the orientation dependence of R 2 * using only a single GRE measurement.

Non-invasive assessment of axon radii via MRI is of increasing interest in human brain research. Its validation requires representative reference data that covers the spatial extent of an MRI voxel (e.g., 1mm2). Due to its small field of view, the commonly used manually labeled electron microscopy (mlEM) can not representatively capture sparsely occurring, large axons, which are the main contributors to the effective mean axon radius (reff) measured with MRI. To overcome this limitation, we investigated the feasibility of generating representative reference data from large-scale light microscopy (lsLM) using automated segmentation methods including a convolutional neural network (CNN). We determined large, mis-/undetected axons as the main error source for the estimation of reff (\(\approx \) 10 %). Our results suggest that the proposed pipeline can be used to generate reference data for the MRI-visible reff and even bears the potential to map spatial, anatomical variation of reff.

Highlights • Second review on the topic of g-ratio mapping using MRI. • A summary of the most recent developments in the fieldproviding methodological background. • Discussion of pitfalls associated with g-ratio mapping using MRI., Background The g-ratio, quantifying the comparative thickness of the myelin sheath encasing an axon, is a geometrical invariant that has high functional relevance because of its importance in determining neuronal conduction velocity. Advances in MRI data acquisition and signal modelling have put in vivo mapping of the g-ratio, across the entire white matter, within our reach. This capacity would greatly increase our knowledge of the nervous system: how it functions, and how it is impacted by disease. New method This is the second review on the topic of g-ratio mapping using MRI. Results This review summarizes the most recent developments in the field, while also providing methodological background pertinent to aggregate g-ratio weighted mapping, and discussing pitfalls associated with these approaches. Comparison with existing methods Using simulations based on recently published data, this review reveals caveats to the state-of-the-art calibration methods that have been used for in vivo g-ratio mapping. It highlights the need to estimate both the slope and offset of the relationship between these MRI-based markers and the true myelin volume fraction if we are really to achieve the goal of precise, high sensitivity g-ratio mapping in vivo. Other challenges discussed in this review further evidence the need for gold standard measurements of human brain tissue from ex vivo histology. Conclusions We conclude that the quest to find the most appropriate MRI biomarkers to enable in vivo g-ratio mapping is ongoing, with the full potential of many novel techniques yet to be investigated.

Pathophysiological changes in the spinal cord white and grey matter resulting from injury can be observed with MRI techniques. These techniques provide sensitive markers of macrostructural and microstructural tissue integrity, which correlate with histological findings. Spinal cord MRI findings in traumatic spinal cord injury (tSCI) and nontraumatic spinal cord injury - the most common form of which is degenerative cervical myelopathy (DCM) - have provided important insights into the pathophysiological processes taking place not just at the focal injury site but also rostral and caudal to the spinal injury. Although tSCI and DCM have different aetiologies, they show similar degrees of spinal cord pathology remote from the injury site, suggesting the involvement of similar secondary degenerative mechanisms. Advanced quantitative MRI protocols that are sensitive to spinal cord pathology have the potential to improve diagnosis and, more importantly, predict outcomes in patients with tSCI or nontraumatic spinal cord injury. This Review describes the insights into tSCI and DCM that have been revealed by neuroimaging and outlines current activities and future directions for the field.

Purpose To propose and validate an efficient method, based on a biophysically motivated signal model, for removing the orientation‐dependent part of R2* using a single gradient‐recalled echo (GRE) measurement. Methods The proposed method utilized a temporal second‐order approximation of the hollow‐cylinder‐fiber model, in which the parameter describing the linear signal decay corresponded to the orientation‐independent part of R2*. The estimated parameters were compared to the classical, mono‐exponential decay model for R2* in a sample of an ex vivo human optic chiasm (OC). The OC was measured at 16 distinct orientations relative to the external magnetic field using GRE at 7T. To show that the proposed signal model can remove the orientation dependence of R2*, it was compared to the established phenomenological method for separating R2* into orientation‐dependent and ‐independent parts. Results Using the phenomenological method on the classical signal model, the well‐known separation of R2* into orientation‐dependent and ‐independent parts was verified. For the proposed model, no significant orientation dependence in the linear signal decay parameter was observed. Conclusions Since the proposed second‐order model features orientation‐dependent and ‐independent components at distinct temporal orders, it can be used to remove the orientation dependence of R2* using only a single GRE measurement.

BackgroundGray matter (GM) ‘pseudoatrophy’ is well-documented in patients with anorexia nervosa (AN), but changes in white matter (WM) are less well understood. Here we investigated the dynamics of microstructural WM brain changes in AN patients during short-term weight restoration in a combined longitudinal and cross-sectional study design.MethodsDiffusion-weighted images were acquired in young AN patients before (acAN-Tp1, n = 56) and after (acAN-Tp2, n = 44) short-term weight restoration as well as in age-matched healthy controls (HC, n = 60). Images were processed using Tract-Based-Spatial-Statistics to compare fractional anisotropy (FA) across groups and timepoints.ResultsIn the cross-sectional comparison, FA was significantly reduced in the callosal body in acAN-Tp1 compared with HC, while no differences were found between acAN-Tp2 and HC. In the longitudinal arm, FA increased with weight gain in acAN-Tp2 relative to acAN-Tp1 in large parts of the callosal body and the fornix, while it decreased in the right corticospinal tract.ConclusionsOur findings reveal that dynamic, bidirectional changes in WM microstructure in young underweight patients with AN can be reversed with brief weight restoration therapy. These results parallel those previously observed in GM and suggest that alterations in WM in non-chronic AN are also state-dependent and rapidly reversible with successful intervention.

To characterize remote secondary neurodegeneration of spinal tracts and neurons below a cervical spinal cord injury (SCI) and its relation to the severity of injury, the integrity of efferent and afferent pathways, and clinical impairment.A comprehensive high-resolution MRI protocol was acquired in 17 traumatic cervical SCI patients and 14 controls at 3T. At the cervical lesion, a sagittal T2-weighted scan provided information on the width of preserved midsagittal tissue bridges. In the lumbar enlargement, high-resolution T2*-weighted and diffusion-weighted scans were used to calculate tissue-specific cross-sectional areas and diffusion indices, respectively. Regression analyses determined associations between MRI readouts and the electrophysiologic and clinical measures.At the cervical injury level, preserved midsagittal tissue bridges were present in the majority of patients. In the lumbar enlargement, neurodegeneration-in terms of macrostructural and microstructural MRI changes-was evident in the white matter and ventral and dorsal horns. Patients with thinner midsagittal tissue bridges had smaller ventral horn area, higher radial diffusivity in the gray matter, smaller motor evoked potential amplitude from the lower extremities, and lower motor score. In addition, smaller width of midsagittal tissue bridges was also associated with smaller tibialis sensory evoked potential amplitude and lower light-touch score.This study shows extensive tissue-specific cord pathology in infralesional spinal networks following cervical SCI, its magnitude relating to lesion severity, electrophysiologic integrity, and clinical impairment of the lower extremity. The clinical eloquence of remote neurodegenerative changes speaks to the application of neuroimaging biomarkers in diagnostic workup and planning of clinical trials.

The neocortex of the human brain is the seat of higher brain function. Modern imaging techniques, chief among them magnetic resonance imaging (MRI), allow non-invasive imaging of this important structure. Knowledge of the microstructure of the neocortex has classically come from post-mortem histological studies of human tissue, and extrapolations from invasive animal studies. From these studies, we know that the scale of important neocortical structure spans six orders of magnitude, ranging from the size of axonal diameters (microns), to the size of cortical areas responsible for integrating sensory information (centimetres). MRI presents an opportunity to move beyond classical methods, because MRI is non-invasive and MRI contrast is sensitive to neocortical microstructure over all these length scales. MRI thus allows inferences to be made about neocortical microstructure in vivo, i.e. MRI-based in vivo histology. We review recent literature that has applied and developed MRI-based in vivo histology to probe the microstructure of the human neocortex, focusing specifically on myelin, iron, and neuronal fibre mapping. We find that applications such as cortical parcellation (using [Formula: see text] maps as proxies for myelin content) and investigation of cortical iron deposition with age (using [Formula: see text] maps) are already contributing to the frontiers of knowledge in neuroscience. Neuronal fibre mapping in the cortex remains challenging in vivo, but recent improvements in diffusion MRI hold promise for exciting applications in the near future. The literature also suggests that utilising multiple complementary quantitative MRI maps could increase the specificity of inferences about neocortical microstructure relative to contemporary techniques, but that further investment in modelling is required to appropriately combine the maps. In vivo histology of human neocortical microstructure is undergoing rapid development. Future developments will improve its specificity, sensitivity, and clinical applicability, granting an ever greater ability to investigate neuroscientific and clinical questions about the human neocortex.

Remote gray matter pathology has been suggested rostral to the compression site in cervical spondylotic myelopathy (CSM). We therefore assessed neurodegeneration in the gray matter ventral and dorsal horns. Twenty patients with CSM and 18 healthy subjects underwent a high-resolution structural and diffusion magnetic resonance imaging protocol at vertebra C2/C3. Patients received comprehensive clinical assessments. T2*-weighted data provided cross-sectional area measurements of gray matter ventral and dorsal horns to identify atrophy. At the identical location, mean diffusivity (MD) and fractional anisotropy (FA) determined the microstructural integrity. Finally, the relationships between neurodegeneration occurring in the gray and white matter and clinical impairment were investigated. Patients suffered from mild-to-moderate CSM with mainly sensory impairment. In the ventral horns, cross-sectional area was not reduced (p = 0.863) but MD was increased (p = 0.045). The magnitude of MD changes within the ventral horn was associated with white matter diffusivity changes (MD: p = 0.013; FA: p = 0.028) within the lateral corticospinal tract. In contrast, dorsal horn cross-sectional area was reduced by 16.0% (p 0.001) without alterations in diffusivity indices, compared with controls. No associations between the magnitude of ventral and dorsal horn neurodegeneration and clinical impairment were evident. Focal cord gray matter pathology is evident remote to the compression site in vivo in CSM patients. Microstructural changes in the ventral horns (i.e., motoneurons) related to corticospinal tract integrity in the absence of atrophy and marked motor impairment. Dorsal horn atrophy corresponded to main clinical representation of sensory impairment. Thus, neuroimaging biomarkers of cord gray matter integrity reveal focal neurodegeneration prior to marked clinical impairment and thus could serve as predictors of ensuing impairment in CSM patients.

A defining feature of the basal ganglia is their anatomical organization into multiple cortico-striatal loops. A central tenet of this architecture is the idea that local striatal function is determined by its precise connectivity with cortex, creating a functional topography that is mirrored within cortex and striatum. Here we formally test this idea using both human anatomical and functional imaging, specifically asking whether within striatal subregions one can predict between-voxel differences in functional signals based on between-voxel differences in corticostriatal connectivity. We show that corticostriatal connectivity profiles predict local variation in reward signals in bilateral caudate nucleus and putamen, expected value signals in bilateral caudate nucleus, and response effector activity in bilateral putamen. These data reveal that, even within individual striatal regions, local variability in corticostriatal anatomical connectivity predicts functional differentiation., Highlights • We use diffusion imaging to predict striatal reinforcement learning BOLD responses. • Structural cortico-striatal connectivity can explain intra-regional BOLD variability. • These results suggest a fine functional parcellation based on afferent connectivity.

NODDI-DTI is a simplification of the NODDI model that, when its underlying assumptions are met, allows extraction of biophysical parameters from standard single-shell DTI data, permitting biophysical analysis of DTI datasets.In contrast to the NODDI signal model, the NODDI-DTI signal model contains no CSF compartment, restricting its application to voxels with very low CSF partial-volume contamination. This simplification allowed derivation of simple analytical relations between parameters representing axon density, v and dispersion, τ, and DTI invariants (MD and FA) through moment expansion of the NODDI-DTI signal model. These relations formally allow extraction of biophysical parameters from DTI data. It should be emphasised that the NODDI-DTI model inherits the strong assumptions of the NODDI model, and so is nominally restricted to analysis of healthy brains.NODDI-DTI parameter estimates were computed by applying the proposed analytical relations to DTI parameters extracted from the first shell of data, and compared to parameters extracted by fitting the NODDI-DTI model to (i) both shells (recommended) and (ii) the first shell (as for DTI) of data in the white matter of three different in vivo diffusion datasets. NODDI-DTI parameters estimated from DTI and NODDI-DTI parameters estimated by fitting the model to the first shell of data gave similar errors compared to two-shell NODDI-DTI estimates. The NODDI-DTI method gave unphysical parameter estimates in a small percentage of voxels, reflecting voxelwise DTI estimation error or NODDI-DTI model invalidity. In the course of evaluating the NODDI-DTI model it was found that diffusional kurtosis strongly biased DTI-based MD values, and so a novel heuristic correction requiring only DTI data was derived and used to account for this bias.Our results demonstrate that NODDI-DTI is a promising model and technique to interpret restricted datasets acquired for DTI analysis with greater biophysical specificity, though its limitations must be borne in mind.

The blood oxygenation level-dependent (BOLD) signal is widely used for functional magnetic resonance imaging (fMRI) of brain function in health and disease. The statistical power of fMRI group studies is significantly hampered by high inter-subject variance due to differences in baseline vascular physiology. Several methods have been proposed to account for physiological vascularization differences between subjects and hence improve the sensitivity in group studies. However, these methods require the acquisition of additional reference scans (such as a full resting-state fMRI session or ASL-based calibrated BOLD). We present a vascular autorescaling (VasA) method, which does not require any additional reference scans. VasA is based on the observation that slow oscillations (, Highlights • We present a vascular autocalibration method (VasA) for fMRI studies. • VasA fMRI accounts for physiological vascularization differences between subjects. • VasA fMRI significantly increases functional sensitivity in group analyses. • VasA does not require additional reference scans or other complicated procedures. • VasA can be readily applied to any task-related fMRI data set, even retrospectively.

Diffusion tensor imaging is widely used in research and clinical applications, but this modality is highly sensitive to artefacts. We developed an easy-to-implement extension of the original diffusion tensor model to account for physiological noise in diffusion tensor imaging using measures of peripheral physiology (pulse and respiration), the so-called extended tensor model. Within the framework of the extended tensor model two types of regressors, which respectively modeled small (linear) and strong (nonlinear) variations in the diffusion signal, were derived from peripheral measures. We tested the performance of four extended tensor models with different physiological noise regressors on nongated and gated diffusion tensor imaging data, and compared it to an established data-driven robust fitting method. In the brainstem and cerebellum the extended tensor models reduced the noise in the tensor-fit by up to 23% in accordance with previous studies on physiological noise. The extended tensor model addresses both large-amplitude outliers and small-amplitude signal-changes. The framework of the extended tensor model also facilitates further investigation into physiological noise in diffusion tensor imaging. The proposed extended tensor model can be readily combined with other artefact correction methods such as robust fitting and eddy current correction.

Freely available automated MR image analysis techniques are being increasingly used to investigate neuroanatomical abnormalities in patients with neurological disorders. It is important to assess the specificity and validity of automated measurements of structure volumes with respect to reliable manual methods that rely on human anatomical expertise. The thalamus is widely investigated in many neurological and neuropsychiatric disorders using MRI, but thalamic volumes are notoriously difficult to quantify given the poor between-tissue contrast at the thalamic gray-white matter interface. In the present study we investigated the reliability of automatically determined thalamic volume measurements obtained using FreeSurfer software with respect to a manual stereological technique on 3D T1-weighted MR images obtained from a 3 T MR system. Further to demonstrating impressive consistency between stereological and FreeSurfer volume estimates of the thalamus in healthy subjects and neurological patients, we demonstrate that the extent of agreeability between stereology and FreeSurfer is equal to the agreeability between two human anatomists estimating thalamic volume using stereological methods. Using patients with juvenile myoclonic epilepsy as a model for thalamic atrophy, we also show that both automated and manual methods provide very similar ratios of thalamic volume loss in patients. This work promotes the use of FreeSurfer for reliable estimation of global volume in healthy and diseased thalami.

PURPOSE To determine regional alterations of fractional anisotropy (FA) and mean diffusivity (MD) in patients with magnetic resonance imaging (MRI)-negative temporal lobe epilepsy with unknown cause (TLEu) using diffusion tensor imaging (DTI) and voxel-based statistics (VBS). METHODS Ten patients with left TLEu and no abnormality on conventional MRI and 81 age-matched neurological healthy controls were studied. VBS analyses were used to compare FA and MD differences between patients and controls. All results were reported using stringent statistical thresholds corrected for multiple comparisons. RESULTS Patients with TLEu had widespread and bilateral reduction of white matter FA, encompassing the temporal lobes, entire corpus callosum, thalamus, and other regions relative to controls. Increased MD was more spatially limited in patients, but was also observed in the thalamus. FA of the putamen was significantly increased bilaterally in patients relative to controls, which correlated with increasing macroscopic atrophy of the putamen. DISCUSSION Water diffusion abnormalities are widespread and bilaterally distributed in patients with unilateral TLEu, which are beyond the resolution of conventional MRI. FA alterations are more widespread relative to MD alterations. This is the first study to show evidence of interrelated microscopic (ie, FA increase) and macroscopic (ie, atrophy) alterations of the putamen in patients with TLEu.

Summary Purpose: Patients with juvenile myoclonic epilepsy (JME) show evidence of microstructural white matter (WM) damage of thalamocortical fiber tracts and changes of blood oxygen level dependent (BOLD) signal in a striatothalamocortical network. The objective of the present study was to investigate microstructural and volumetric alterations of the putamen in patients with JME using diffusion tensor imaging (DTI) and conventional magnetic resonance imaging (MRI). Methods: We performed DTI and MRI for 10 patients with JME and 59 age-matched neurologically healthy volunteers. Evaluation of microstructural damage was investigated using calculation of mean fractional anisotropy (FA) values in a priori regions of interest (ROIs) for the putamen, frontal lobe, and a thalamocortical region, after application of an improved eddy current correction method and a new statistical parametric mapping (SPM)–compatible toolbox incorporating intensive multicontrast FA image registration. Stereologic analysis on MRI was performed to estimate macroscopic volume of the putamen in both cerebral hemispheres for all subjects. Key Findings: Relative to controls, patients had significantly reduced FA in the frontal lobe (p = 0.01) and thalamocortical fiber WM (p

Background Susac's syndrome is an underdiagnosed disease that is thought to occur mainly in young women. It is characterized by the triad of hearing loss, branch retinal artery occlusions, and encephalopathy with predominantly cognitive and psychiatric symptoms. Treatment consists of immunosuppressive therapy. Focal ischemic lesions in the central portion of the corpus callosum detectable by conventional MRI (“snowballs”) are a typical feature of Susac's syndrome. The appearance of these lesions is not, however, correlated with the type and severity of the neuropsychological deficits. Methods Nine patients with Susac's syndrome, four men and five women, were investigated using Diffusion Tensor Imaging (DTI), a non-invasive technique for the detection of macro- and microstructural impairment of fiber integrity on the basis of normal values for the fractional anisotropy (FA). Patients were compared to a group of 83 healthy controls on a voxel-by-voxel basis. Several regions of interest were defined. Results Impairment of fiber integrity was found in every patient. As compared to the controls, every patient showed disruption of fiber integrity in the genu of the corpus callosum. Reduction of FA was found particularly in the prefrontal white matter. Conclusion The type and severity of the encephalopathic symptoms in Susac's syndrome are much better represented by the prefrontal FA reductions detected by DTI than by the mostly sparse white matter abnormalities seen on conventional MRI. The fiber damage in the genu seems to be specific for patients with Susac's syndrome.

Aphasia after middle cerebral artery (MCA) stroke shows highly variable degrees of recovery. One possible explanation may be offered by the variability of the occlusion location. Branches from the proximal portion of the MCA often supply the mesial temporal lobe including parts of the hippocampus, a structure known to be involved in language learning. Therefore, we assessed whether language recovery in chronic aphasia is dependent on the proximity of the MCA infarct and correlated with the integrity of the hippocampus and its surrounding white matter. Language reacquisition capability was determined after 2weeks of intensive language therapy and 8months after treatment in ten chronic aphasia patients. Proximity of MCA occlusion relative to the internal carotid artery was determined by magnetic resonance imaging (MRI) based on the most proximal anatomical region infarcted. Structural damage to the hippocampus was assessed by MRI-based volumetry, regional microstructural integrity of hippocampus adjacent white matter by fractional anisotropy. Language learning success for trained materials was correlated with the proximity of MCA occlusion, microstructural integrity of the left hippocampus and its surrounding white matter, but not with lesion size, overall microstructural brain integrity and a control region outside of the MCA territory. No correlations were found for untrained language materials, underlining the specificity of our results for training-induced recovery. Our results suggest that intensive language therapy success in chronic aphasia after MCA stroke is critically dependent on damage to the hippocampus and its surrounding structures.

Hereditary spastic paraplegias (HSP) are genetically and clinically heterogeneous neurodegenerative disorders. Most MR studies on HSP include very heterogeneous samples of patients, and findings were inconsistent. Here, we examined six patients with pure HSP and SPG4 mutations by clinical evaluation, detailed neuropsychological testing, and neuroimaging analyses, including conventional MRI, diffusion tensor imaging (DTI), and brain volumetry. Differences of voxel-wise statistics and ROI-based analysis of DTI data between patients and 32 healthy volunteers were evaluated. Although conventional MRI and brain volumetry were normal, DTI revealed widespread disturbance of white matter (WM) integrity (P < 0.001), mainly affecting the corticospinal tract. With longer disease duration, frontal regions were also involved. The WM changes were also present in subclinical subjects harbouring the pathogenic mutation. These subtle WM abnormalities have functional relevance because they correlated with clinical symptoms. Thus, early alterations of nerve fibres, which can be detected by DTI, might serve as a biological marker in HSP, in particular with respect to future longitudinal studies.

Eddy-current (EC) and motion effects in diffusion-tensor imaging (DTI) bias the estimation of quantitative diffusion indices, such as the fractional anisotropy. Both effects can be retrospectively corrected by registering the strongly distorted diffusion-weighted images to less-distorted T2-weighted images acquired without diffusion weighting. Two different affine spatial transformations are usually employed for this correction: slicewise and whole-brain transformations. However, a relation between estimated transformation parameters and EC distortions has not been established yet for the latter approach. In this study, a novel diffusion-gradient-direction-independent estimation of the EC field is proposed based solely on affine whole-brain registration parameters. Using this model, it is demonstrated that a more distinct evaluation of the whole-brain EC effects is possible if the through-plane distortion was considered in addition to the well-known in-plane distortions. Moreover, a comparison of different whole-brain registrations relative to a slicewise approach is performed, in terms of the relative tensor error. Our findings suggest that for appropriate intersubject comparison of DTI data, a whole-brain registration containing nine affine parameters provides comparable performance (between 0 and 3%) to slicewise methods and can be performed in a fraction of the time.

C-reactive protein is a marker of inflammation and vascular disease. It also seems to be associated with an increased risk of dementia. To better understand potential underlying mechanisms, we assessed microstructural brain integrity and cognitive performance relative to serum levels of high-sensitivity C-reactive protein (hs-CRP).We cross-sectionally examined 447 community-dwelling and stroke-free individuals from the Systematic Evaluation and Alteration of Risk Factors for Cognitive Health (SEARCH) Health Study (mean age 63 years, 248 female). High-field MRI was performed in 321 of these subjects. Imaging measures included fluid-attenuated inversion recovery sequences for assessment of white matter hyperintensities, automated quantification of brain parenchyma volumes, and diffusion tensor imaging for calculation of global and regional white matter integrity, quantified by fractional anisotropy (FA). Psychometric analyses covered verbal memory, word fluency, and executive functions.Higher levels of hs-CRP were associated with worse performance in executive function after adjustment for age, gender, education, and cardiovascular risk factors in multiple regression analysis (beta = -0.095, p = 0.02). Moreover, higher hs-CRP was related to reduced global fractional anisotropy (beta = -0.237, p0.001), as well as regional FA scores of the frontal lobes (beta = -0.246, p0.001), the corona radiata (beta = -0.222, p0.001), and the corpus callosum (beta = -0.141, p = 0.016), in particular the genu (beta = -0.174, p = 0.004). We did not observe a significant association of hs-CRP with measures of white matter hyperintensities or brain atrophy.These data suggest that low-grade inflammation as assessed by high-sensitivity C-reactive protein is associated with cerebral microstructural disintegration that predominantly affects frontal pathways and corresponding executive function.

Background Conventional structural MRI fails to identify a cerebral lesion in 25% of patients with cryptogenic partial epilepsy (CPE). Diffusion tensor imaging is an MRI technique sensitive to microstructural abnormalities of cerebral white matter (WM) by quantification of fractional anisotropy (FA). The objectives of the present study were to identify focal FA abnormalities in patients with CPE who were deemed MRI negative during routine presurgical evaluation. Methods Diffusion tensor imaging at 3 T was performed in 12 patients with CPE and normal conventional MRI and in 67 age matched healthy volunteers. WM integrity was compared between groups on the basis of automated voxel-wise statistics of FA maps using an analysis of covariance. Volumetric measurements from high resolution T1-weighted images were also performed. Results Significant FA reductions in WM regions encompassing diffuse areas of the brain were observed when all patients as a group were compared with controls. On an individual basis, voxel based analyses revealed widespread symmetrical FA reduction in CPE patients. Furthermore, asymmetrical temporal lobe FA reduction was consistently ipsilateral to the electroclinical focus. No significant correlations were found between FA alterations and clinical data. There were no differences in brain volumes of CPE patients compared with controls. Conclusion Despite normal conventional MRI, WM integrity abnormalities in CPE patients extend far beyond the epileptogenic zone. Given that unilateral temporal lobe FA abnormalities were consistently observed ipsilateral to the seizure focus, analysis of temporal FA may provide an informative in vivo investigation into the localisation of the epileptogenic zone in MRI negative patients.

We describe a 40-year-old patient with gelastic seizures triggered by hand movement. Despite nonlesional magnetic resonance imaging (MRI), electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and diffusion tensor imaging (DTI) are concordant with seizure onset in the right frontocentral area. Seizure semiology and EEG recordings imply involvement of mesial frontal structures remote from seizure initiation site. We reviewed all published cases on gelastic seizures of frontal lobe origin to find characteristic features. For further investigation of the phenomenon of movement-induced seizures, fMRI was performed using a finger tapping paradigm. Interictal fMRI revealed widespread activation of right motor cortex during finger tapping on either side outreaching the anatomical representation of the left finger. In line with this finding DTI revealed fiber track impairment in the right frontocentral region, supporting the hypothesis of a focal derangement. This case highlights the importance of complementary functional investigations in MRI-negative epilepsies.