An ex vivo imaging pipeline for producing high-quality and high-resolution diffusion-weighted imaging datasets

Diversity of Cortico-descending Projections: Histological and Diffusion MRI Characterization in the Monkey

The axonal composition of cortical projections originating in premotor, supplementary motor (SMA), primary motor (a4), somatosensory and parietal areas and descending towards the brain stem and spinal cord was characterized in the monkey with histological tract tracing, electron microscopy (EM) and diffusion MRI (dMRI). These 3 approaches provided complementary information. Histology provided accurate assessment of axonal diameters and size of synaptic boutons. dMRI revealed the topography of the projections (tractography), notably in the internal capsule. From measurements of axon diameters axonal conduction velocities were computed. Each area communicates with different diameter axons and this generates a hierarchy of conduction delays in this order: a4 (the shortest), SMA, premotor (F7), parietal, somatosensory, premotor F4 (the longest). We provide new interpretations for i) the well-known different anatomical and electrophysiological estimates of conduction velocity; ii) why conduction delays are probably an essential component of the cortical motor command; and iii) how histological and dMRI tractography can be integrated.

Cross-species cortical alignment identifies different types of anatomical reorganization in the primate temporal lobe

Evolutionary adaptations of temporo-parietal cortex are considered to be a critical specialization of the human brain. Cortical adaptations, however, can affect different aspects of brain architecture, including local expansion of the cortical sheet or changes in connectivity between cortical areas. We distinguish different types of changes in brain architecture using a computational neuroanatomy approach. We investigate the extent to which between-species alignment, based on cortical myelin, can predict changes in connectivity patterns across macaque, chimpanzee, and human. We show that expansion and relocation of brain areas can predict terminations of several white matter tracts in temporo-parietal cortex, including the middle and superior longitudinal fasciculus, but not the arcuate fasciculus. This demonstrates that the arcuate fasciculus underwent additional evolutionary modifications affecting the temporal lobe connectivity pattern. This approach can flexibly be extended to include other features of cortical organization and other species, allowing direct tests of comparative hypotheses of brain organization.

Uncovering a Role for the Dorsal Hippocampal Commissure in Recognition Memory

The dorsal hippocampal commissure (DHC) is a white matter tract that provides interhemispheric connections between temporal lobe brain regions. Despite the importance of these regions for learning and memory, there is scant evidence of a role for the DHC in successful memory performance. We used diffusion-weighted magnetic resonance imaging (DW-MRI) and white matter tractography to reconstruct the DHC in both humans (in vivo) and nonhuman primates (ex vivo). Across species, our findings demonstrate a close consistency between the known anatomy and tract reconstructions of the DHC. Anterograde tract-tracer techniques also highlighted the parahippocampal origins of DHC fibers in nonhuman primates. Finally, we derived diffusion tensor MRI metrics from the DHC in a large sample of human subjects to investigate whether interindividual variation in DHC microstructure is predictive of memory performance. The mean diffusivity of the DHC correlated with performance in a standardized recognition memory task, an effect that was not reproduced in a comparison commissure tract-the anterior commissure. These findings highlight a potential role for the DHC in recognition memory, and our tract reconstruction approach has the potential to generate further novel insights into the role of this previously understudied white matter tract in both health and disease.

Insight into the fundamental trade-offs of diffusion MRI from polarization-sensitive optical coherence tomography in ex vivo human brain

In the first study comparing high angular resolution diffusion MRI (dMRI) in the human brain to axonal orientation measurements from polarization-sensitive optical coherence tomography (PSOCT), we compare the accuracy of orientation estimates from various dMRI sampling schemes and reconstruction methods. We find that, if the reconstruction approach is chosen carefully, single-shell dMRI data can yield the same accuracy as multi-shell data, and only moderately lower accuracy than a full Cartesian-grid sampling scheme. Our results suggest that current dMRI reconstruction approaches do not benefit substantially from ultra-high b-values or from very large numbers of diffusion-encoding directions. We also show that accuracy remains stable across dMRI voxel sizes of 1 mm or smaller but degrades at 2 mm, particularly in areas of complex white-matter architecture. We also show that, as the spatial resolution is reduced, axonal configurations in a dMRI voxel can no longer be modeled as a small set of distinct axon populations, violating an assumption that is sometimes made by dMRI reconstruction techniques. Our findings have implications for in vivo studies and illustrate the value of PSOCT as a source of ground-truth measurements of white-matter organization that does not suffer from the distortions typical of histological techniques.

Characterization complex collagen fiber architecture in knee joint using high-resolution diffusion imaging

PURPOSE

To evaluate the complex fiber orientations and 3D collagen fiber network of knee joint connective tissues, including ligaments, muscle, articular cartilage, and meniscus using high spatial and angular resolution diffusion imaging.

METHODS

Two rat knee joints were scanned using a modified 3D diffusion-weighted spin echo pulse sequence with the isotropic spatial resolution of 45 μm at 9.4T. The b values varied from 250 to 1250 s/mm² with 31 diffusion encoding directions for 1 rat knee. The b value was fixed to 1000 s/mm² with 147 diffusion encoding directions for the second knee. Both the diffusion tensor imaging (DTI) model and generalized Q-sampling imaging (GQI) method were used to investigate the fiber orientation distributions and tractography with the validation of polarized light microscopy.

RESULTS

To better resolve the crossing fibers, the b value should be great than or equal to 1000 s/mm² . The tractography results were comparable between the DTI model and GQI method in ligament and muscle. However, the tractography exhibited apparent difference between DTI and GQI in connective tissues with more complex collagen fibers network, such as cartilage and meniscus. In articular cartilage, there were numerous crossing fibers found in superficial zone and transitional zone. Tractography generated with GQI also resulted in more intact tracts in articular cartilage than DTI.

CONCLUSION

High-resolution diffusion imaging with GQI method can trace the complex collagen fiber orientations and architectures of the knee joint at microscopic resolution.

Differences in Frontal Network Anatomy Across Primate Species

The frontal lobe is central to distinctive aspects of human cognition and behavior. Some comparative studies link this to a larger frontal cortex and even larger frontal white matter in humans compared with other primates, yet others dispute these findings. The discrepancies between studies could be explained by limitations of the methods used to quantify volume differences across species, especially when applied to white matter connections. In this study, we used a novel tractography approach to demonstrate that frontal lobe networks, extending within and beyond the frontal lobes, occupy 66% of total brain white matter in humans and 48% in three monkey species: vervets (Chlorocebus aethiops), rhesus macaque (Macaca mulatta) and cynomolgus macaque (Macaca fascicularis), all male. The simian-human differences in proportional frontal tract volume were significant for projection, commissural, and both intralobar and interlobar association tracts. Among the long association tracts, the greatest difference was found for tracts involved in motor planning, auditory memory, top-down control of sensory information, and visuospatial attention, with no significant differences in frontal limbic tracts important for emotional processing and social behaviour. In addition, we found that a nonfrontal tract, the anterior commissure, had a smaller volume fraction in humans, suggesting that the disproportionally large volume of human frontal lobe connections is accompanied by a reduction in the proportion of some nonfrontal connections. These findings support a hypothesis of an overall rearrangement of brain connections during human evolution.SIGNIFICANCE STATEMENT Tractography is a unique tool to map white matter connections in the brains of different species, including humans. This study shows that humans have a greater proportion of frontal lobe connections compared with monkeys, when normalized by total brain white matter volume. In particular, tracts associated with language and higher cognitive functions are disproportionally larger in humans compared with monkeys, whereas other tracts associated with emotional processing are either the same or disproportionally smaller. This supports the hypothesis that the emergence of higher cognitive functions in humans is associated with increased extended frontal connectivity, allowing human brains more efficient cross talk between frontal and other high-order associative areas of the temporal, parietal, and occipital lobes.

Mitigating gyral bias in cortical tractography via asymmetric fiber orientation distributions

Diffusion tractography in brain connectomics often involves tracing axonal trajectories across gray-white matter boundaries in gyral blades of complex cortical convolutions. To date, gyral bias is observed in most tractography algorithms with streamlines predominantly terminating at gyral crowns instead of sulcal banks. This work demonstrates that asymmetric fiber orientation distribution functions (AFODFs), computed via a multi-tissue global estimation framework, can mitigate the effects of gyral bias, enabling fiber streamlines at gyral blades to make sharper turns into the cortical gray matter. We use ex-vivo data of an adult rhesus macaque and in-vivo data from the Human Connectome Project (HCP) to show that the fiber streamlines given by AFODFs bend more naturally into the cortex than the conventional symmetric FODFs in typical gyral blades. We demonstrate that AFODF tractography improves cortico-cortical connectivity and provides highly consistent outcomes between two different field strengths (3T and 7T).

Relating diffusion tensor imaging measurements to microstructural quantities in the cerebral cortex in multiple sclerosis

To investigate whether the observed anisotropic diffusion in cerebral cortex may reflect its columnar cytoarchitecture and myeloarchitecture, as a potential biomarker for disease-related changes, we compared postmortem diffusion magnetic resonance imaging scans of nine multiple sclerosis brains with histology measures from the same regions. Histology measurements assessed the cortical minicolumnar structure based on cell bodies and associated axon bundles in dorsolateral prefrontal cortex (Area 9), Heschl's gyrus (Area 41), and primary visual cortex (V1). Diffusivity measures included mean diffusivity, fractional anisotropy of the cortex, and three specific measures that may relate to the radial minicolumn structure: the angle of the principal diffusion direction in the cortex, the component that was perpendicular to the radial direction, and the component that was parallel to the radial direction. The cellular minicolumn microcircuit features were correlated with diffusion angle in Areas 9 and 41, and the axon bundle features were correlated with angle in Area 9 and to the parallel component in V1 cortex. This may reflect the effect of minicolumn microcircuit organisation on diffusion in the cortex, due to the number of coherently arranged membranes and myelinated structures. Several of the cortical diffusion measures showed group differences between MS brains and control brains. Differences between brain regions were also found in histology and diffusivity measurements consistent with established regional variation in cytoarchitecture and myeloarchitecture. Therefore, these novel measures may provide a surrogate of cortical organisation as a potential biomarker, which is particularly relevant for detecting regional changes in neurological disorders.

Enabling Multi-Shell b-Value Generalizability of Data-Driven Diffusion Models with Deep SHORE

Intra-voxel models of the diffusion signal are essential for interpreting organization of the tissue environment at micrometer level with data at millimeter resolution. Recent advances in data driven methods have enabled direct comparison and optimization of methods for in-vivo data with externally validated histological sections with both 2-D and 3-D histology. Yet, all existing methods make limiting assumptions of either (1) model-based linkages between b-values or (2) limited associations with single shell data. We generalize prior deep learning models that used single shell spherical harmonic transforms to integrate the recently developed simple harmonic oscillator reconstruction (SHORE) basis. To enable learning on the SHORE manifold, we present an alternative formulation of the fiber orientation distribution (FOD) object using the SHORE basis while representing the observed diffusion weighted data in the SHORE basis. To ensure consistency of hyper-parameter optimization for SHORE, we present our Deep SHORE approach to learn on a data-optimized manifold. Deep SHORE is evaluated with eight-fold cross-validation of a preclinical MRI-histology data with four b-values. Generalizability of in-vivo human data is evaluated on two separate 3T MRI scanners. Specificity in terms of angular correlation (ACC) with the preclinical data improved on single shell: 0.78 relative to 0.73 and 0.73, multi-shell: 0.80 relative to 0.74 (p < 0.001). In the in-vivo human data, Deep SHORE was more consistent across scanners with 0.63 relative to other multi-shell methods 0.39, 0.52 and 0.57 in terms of ACC. In conclusion, Deep SHORE is a promising method to enable data driven learning with DW-MRI under conditions with varying b-values, number of diffusion shells, and gradient directions per shell.

Deep learning reveals untapped information for local white-matter fiber reconstruction in diffusion-weighted MRI

PURPOSE

Diffusion-weighted magnetic resonance imaging (DW-MRI) is of critical importance for characterizing in-vivo white matter. Models relating microarchitecture to observed DW-MRI signals as a function of diffusion sensitization are the lens through which DW-MRI data are interpreted. Numerous modern approaches offer opportunities to assess more complex intra-voxel structures. Nevertheless, there remains a substantial gap between intra-voxel estimated structures and ground truth captured by 3-D histology.

METHODS

Herein, we propose a novel data-driven approach to model the non-linear mapping between observed DW-MRI signals and ground truth structures using a sequential deep neural network regression using residual block deep neural network (ResDNN). Training was performed on two 3-D histology datasets of squirrel monkey brains and validated on a third. A second validation was performed using scan-rescan datasets of 12 subjects from Human Connectome Project. The ResDNN was compared with multiple micro-structure reconstruction methods and super resolved-constrained spherical deconvolution (sCSD) in particular as baseline for both the validations.

RESULTS

Angular correlation coefficient (ACC) is a correlation/similarity measure and can be interpreted as accuracy when compared with a ground truth. The median ACC of ResDNN is 0.82 and median ACC's of different variants of CSD are 0.75, 0.77, 0.79. The mean, median and std. of ResDNN & sCSD ACC across 12 subjects from HCP are 0.74, 0.88, 0.31 and 0.61, 0.71, 0.31 respectively.

CONCLUSION

This work highlights the ability of deep learning to capture linkages between ex-vivo ground truth data with feasible MRI sequences. The data-driven approach is applicable to human in-vivo data and results in intriguingly high reproducibility of orientation structure.

Acute ex vivo changes in brain white matter diffusion tensor metrics

Purpose

Diffusion magnetic resonance imaging and tractography has an important role in the visualization of brain white matter and assessment of tissue microstructure. There is a lack of correspondence between diffusion metrics of live tissue, ex vivo tissue, and histological findings. The objective of this study is to elucidate this connection by determining the specific diffusion alterations between live and ex vivo brain tissue. This may have an important role in the incorporation of diffusion imaging in ex vivo studies as a complement to histological sectioning as well as investigations of novel neurosurgical techniques.

Methods

This study presents a method of high angular resolution diffusion imaging and tractography of intact and non-fixed ex vivo piglet brains. Most studies involving ex vivo brain specimens have been formalin-fixed or excised from their original biological environment, processes both of which are known to affect diffusion parameters. Thus, non-fixed ex vivo tissue is used. A region-of-interest based analysis of diffusion tensor metrics are compared to in vivo subjects in a selection of major white matter bundles in order to assess the translatability of ex vivo diffusion measurements.

Results

Tractography was successfully achieved in both in vivo and ex vivo groups. No significant differences were found in tract connectivity, average streamline length, or apparent fiber density. Significantly decreased diffusivity (mean, axial, and radial; p<0.0005) in the non-fixed ex vivo group and unaltered fractional anisotropy (p>0.059) between groups were observed.

Conclusion

This study validates the extrapolation of non-fixed fractional anisotropy measurements to live tissue and the potential use of ex vivo tissue for methodological development.

Validation of structural brain connectivity networks: The impact of scanning parameters

Evaluation of the structural connectivity (SC) of the brain based on tractography has mainly focused on the choice of diffusion model, tractography algorithm, and their respective parameter settings. Here, we systematically validate SC derived from a post mortem monkey brain, while varying key acquisition parameters such as the b-value, gradient angular resolution and image resolution. As gold standard we use the connectivity matrix obtained invasively with histological tracers by Markov et al. (2014). As performance metric, we use cross entropy as a measure that enables comparison of the relative tracer labeled neuron counts to the streamline counts from tractography. We find that high angular resolution and high signal-to-noise ratio are important to estimate SC, and that SC derived from low image resolution (1.0³ mm³) are in better agreement with the tracer network, than those derived from high image resolution (0.5³ mm³) or at an even lower image resolution (2.0³ mm³). In contradiction, sensitivity and specificity analyses suggest that if the angular resolution is sufficient, the balanced compromise in which sensitivity and specificity are identical remains 60-64% regardless of the other scanning parameters. Interestingly, the tracer graph is assumed to be the gold standard but by thresholding, the balanced compromise increases to 70-75%. Hence, by using performance metrics based on binarized tracer graphs, one risks losing important information, changing the performance of SC graphs derived by tractography and their dependence of different scanning parameters.

Comparison between diffusion MRI tractography and histological tract-tracing of cortico-cortical structural connectivity in the ferret brain

The anatomical wiring of the brain is a central focus in network neuroscience. Diffusion MRI tractography offers the unique opportunity to investigate the brain fiber architecture in vivo and noninvasively. However, its reliability is still highly debated. Here, we explored the ability of diffusion MRI tractography to match invasive anatomical tract-tracing connectivity data of the ferret brain. We also investigated the influence of several state-of-the-art tractography algorithms on this match to ground truth connectivity data. Tract-tracing connectivity data were obtained from retrograde tracer injections into the occipital, parietal, and temporal cortices of adult ferrets. We found that the relative densities of projections identified from the anatomical experiments were highly correlated with the estimates from all the studied diffusion tractography algorithms (Spearman's rho ranging from 0.67 to 0.91), while only small, nonsignificant variations appeared across the tractography algorithms. These results are comparable to findings reported in mouse and monkey, increasing the confidence in diffusion MRI tractography results. Moreover, our results provide insights into the variations of sensitivity and specificity of the tractography algorithms, and hence into the influence of choosing one algorithm over another.

A Web-Based Atlas Combining MRI and Histology of the Squirrel Monkey Brain

The squirrel monkey (Saimiri sciureus) is a commonly-used surrogate for humans in biomedical research. In the neuroimaging community, MRI and histological atlases serve as valuable resources for anatomical, physiological, and functional studies of the brain; however, no digital MRI/histology atlas is currently available for the squirrel monkey. This paper describes the construction of a web-based multi-modal atlas of the squirrel monkey brain. The MRI-derived information includes anatomical MRI contrast (i.e., T2-weighted and proton-density-weighted) and diffusion MRI metrics (i.e., fractional anisotropy and mean diffusivity) from data acquired both in vivo and ex vivo on a 9.4 Tesla scanner. The histological images include Nissl and myelin stains, co-registered to the corresponding MRI, allowing identification of cyto- and myelo-architecture. In addition, a bidirectional neuronal tracer, biotinylated dextran amine (BDA) was injected into the primary motor cortex, enabling highly specific identification of regions connected to the injection location. The atlas integrates the results of common image analysis methods including diffusion tensor imaging glyphs, labels of 57 white-matter tracts identified using DTI-tractography, and 18 cortical regions of interest identified from Nissl-revealed cyto-architecture. All data are presented in a common space, and all image types are accessible through a web-based atlas viewer, which allows visualization and interaction of user-selectable contrasts and varying resolutions. By providing an easy to use reference system of anatomical information, our web-accessible multi-contrast atlas forms a rich and convenient resource for comparisons of brain findings across subjects or modalities. The atlas is called the Combined Histology-MRI Integrated Atlas of the Squirrel Monkey (CHIASM). All images are accessible through our web-based viewer ( https://chiasm.vuse.vanderbilt.edu /), and data are available for download at ( https://www.nitrc.org/projects/smatlas/ ).

Structural mapping with fiber tractography of the human cuneate fasciculus at microscopic resolution in cervical region

Human spinal white matter tract anatomy has been mapped using post mortem histological information with the help of molecular tracing studies in animal models. This study used 7 Tesla diffusion MR tractography on a human cadaver that was harvested 24 hours post mortem to evaluate cuneate fasciculus anatomy in cervical spinal cord. Based on this method, for the first time much more nuanced tractographic anatomy was used to investigate possible new routes for cuneate fasciculus in the posterior and lateral funiculus. Additionally, current molecular tracing studies were reviewed, and confirmatory data was presented along with our radiological results. Both studies confirm that upon entry to the spinal cord, upper cervical level tracts (C1-2-3) travel inside lateral funiculus and lower level tracts travel medially inside the posterior funiculus after entry at posterolateral sulcus which is different than traditional knowledge of having cuneate fasciculus tracts concentrated in the lateral part of posterior funiculus.

Histological validation of per-bundle water diffusion metrics within a region of fiber crossing following axonal degeneration

Micro-architectural characteristics of white matter can be inferred through analysis of diffusion-weighted magnetic resonance imaging (dMRI). The diffusion-dependent signal can be analyzed through several methods, with the tensor model being the most frequently used due to its straightforward interpretation and low requirements for acquisition parameters. While valuable information can be gained from the tensor-derived metrics in regions of homogeneous tissue organization, this model does not provide reliable microstructural information at crossing fiber regions, which are pervasive throughout human white matter. Several multiple fiber models have been proposed that seem to overcome the limitations of the tensor, with few providing per-bundle dMRI-derived metrics. However, biological interpretations of such metrics are limited by the lack of histological confirmation. To this end, we developed a straightforward biological validation framework. Unilateral retinal ischemia was induced in ten rats, which resulted in axonal (Wallerian) degeneration of the corresponding optic nerve, while the contralateral was left intact; the intact and injured axonal populations meet at the optic chiasm as they cross the midline, generating a fiber crossing region in which each population has different diffusion properties. Five rats served as controls. High-resolution ex vivo dMRI was acquired five weeks after experimental procedures. We correlated and compared histology to per-bundle descriptors derived from three methodologies for dMRI analysis (constrained spherical deconvolution and two multi-tensor representations). We found a tight correlation between axonal density (as evaluated through automatic segmentation of histological sections) with per-bundle apparent fiber density and fractional anisotropy (derived from dMRI). The multi-fiber methods explored were able to correctly identify the damaged fiber populations in a region of fiber crossings (chiasm). Our results provide validation of metrics that bring substantial and clinically useful information about white-matter tissue at crossing fiber regions. Our proposed framework is useful to validate other current and future dMRI methods.

Multidimensional diffusion MRI with spectrally modulated gradients reveals unprecedented microstructural detail

Characterization of porous media is essential in a wide range of biomedical and industrial applications. Microstructural features can be probed non-invasively by diffusion magnetic resonance imaging (dMRI). However, diffusion encoding in conventional dMRI may yield similar signatures for very different microstructures, which represents a significant limitation for disentangling individual microstructural features in heterogeneous materials. To solve this problem, we propose an augmented multidimensional diffusion encoding (MDE) framework, which unlocks a novel encoding dimension to assess time-dependent diffusion specific to structures with different microscopic anisotropies. Our approach relies on spectral analysis of complex but experimentally efficient MDE waveforms. Two independent contrasts to differentiate features such as cell shape and size can be generated directly by signal subtraction from only three types of measurements. Analytical calculations and simulations support our experimental observations. Proof-of-concept experiments were applied on samples with known and distinctly different microstructures. We further demonstrate substantially different contrasts in different tissue types of a post mortem brain. Our simultaneous assessment of restriction size and shape may be instrumental in studies of a wide range of porous materials, enable new insights into the microstructure of biological tissues or be of great value in diagnostics.

Development, integration and use of an ultra-high-strength gradient system on a human-size 3 T magnet for small animal MRI

This study aims to integrate an ultra-high-strength gradient coil system on a clinical 3 T magnet and demonstrate its preclinical imaging capabilities. Dedicated phantoms were used to qualitatively and quantitatively assess the performance of the gradient system. Advanced MR imaging sequences, including diffusion tensor imaging (DTI) and quantitative susceptibility mapping (QSM), were implemented and executed on an ex vivo specimen as well as in vivo rats. The DTI and QSM results on the phantom agreed well with those in the literature. Furthermore, studies on ex vivo specimens have demonstrated the applicability of DTI and QSM on our system to probe microstructural changes in a mild traumatic brain injury rat model. The feasibility of in vivo rat DTI was also demonstrated. We showed that the inserted ultra-high-strength gradient coil was successfully integrated on a clinically used magnet. After careful tuning and calibration, we verified the accuracy and quantitative preclinical imaging capability of the integrated system in phantom and in vivo rat brain experiments. This study can be essential to establish dedicated animal MRI platform on clinical MRI scanners and facilitate translational studies at clinical settings.

Histologically derived fiber response functions for diffusion MRI vary across white matter fibers-An ex vivo validation study in the squirrel monkey brain

Understanding the relationship between the diffusion-weighted MRI signal and the arrangement of white matter fibers is fundamental for accurate voxel-wise reconstruction of the fiber orientation distribution (FOD) and subsequent fiber tractography. Spherical deconvolution reconstruction techniques model the diffusion signal as the convolution of the FOD with a response function that represents the signal profile of a single fiber orientation. Thus, given the signal and a fiber response function, the FOD can be estimated in every imaging voxel by deconvolution. However, the selection of the appropriate response function remains relatively under-studied, and requires further validation. In this work, using 3D histologically defined FODs and the corresponding diffusion signal from three ex vivo squirrel monkey brains, we derive the ground truth response functions. We find that the histologically derived response functions differ from those conventionally used. Next, we find that response functions statistically vary across brain regions, which suggests that the practice of using the same kernel throughout the brain is not optimal. We show that different kernels lead to different FOD reconstructions, which in turn can lead to different tractography results depending on algorithmic parameters, with large variations in the accuracy of resulting reconstructions. Together, these results suggest there is room for improvement in estimating and understanding the relationship between the diffusion signal and the underlying FOD.

VERDICT MRI validation in fresh and fixed prostate specimens using patient-specific moulds for histological and MR alignment

The VERDICT framework for modelling diffusion MRI data aims to relate parameters from a biophysical model to histological features used for tumour grading in prostate cancer. Validation of the VERDICT model is necessary for clinical use. This study compared VERDICT parameters obtained ex vivo with histology in five specimens from radical prostatectomy. A patient-specific 3D-printed mould was used to investigate the effects of fixation on VERDICT parameters and to aid registration to histology. A rich diffusion data set was acquired in each ex vivo prostate before and after fixation. At both time points, data were best described by a two-compartment model: the model assumes that an anisotropic tensor compartment represents the extracellular space and a restricted sphere compartment models the intracellular space. The effect of fixation on model parameters associated with tissue microstructure was small. The patient-specific mould minimized tissue deformations and co-localized slices, so that rigid registration of MRI to histology images allowed region-based comparison with histology. The VERDICT estimate of the intracellular volume fraction corresponded to histological indicators of cellular fraction, including high values in tumour regions. The average sphere radius from VERDICT, representing the average cell size, was relatively uniform across samples. The primary diffusion direction from the extracellular compartment of the VERDICT model aligned with collagen fibre patterns in the stroma obtained by structure tensor analysis. This confirmed the biophysical relationship between ex vivo VERDICT parameters and tissue microstructure from histology.

Imaging brain microstructure with diffusion MRI: practicality and applications

This article gives an overview of microstructure imaging of the brain with diffusion MRI and reviews the state of the art. The microstructure-imaging paradigm aims to estimate and map microscopic properties of tissue using a model that links these properties to the voxel scale MR signal. Imaging techniques of this type are just starting to make the transition from the technical research domain to wide application in biomedical studies. We focus here on the practicalities of both implementing such techniques and using them in applications. Specifically, the article summarizes the relevant aspects of brain microanatomy and the range of diffusion-weighted MR measurements that provide sensitivity to them. It then reviews the evolution of mathematical and computational models that relate the diffusion MR signal to brain tissue microstructure, as well as the expanding areas of application. Next we focus on practicalities of designing a working microstructure imaging technique: model selection, experiment design, parameter estimation, validation, and the pipeline of development of this class of technique. The article concludes with some future perspectives on opportunities in this topic and expectations on how the field will evolve in the short-to-medium term.

Ex vivo diffusion MRI of the human brain: Technical challenges and recent advances

This review discusses ex vivo diffusion magnetic resonance imaging (dMRI) as an important research tool for neuroanatomical investigations and the validation of in vivo dMRI techniques, with a focus on the human brain. We review the challenges posed by the properties of post-mortem tissue, and discuss state-of-the-art tissue preparation methods and recent advances in pulse sequences and acquisition techniques to tackle these. We then review recent ex vivo dMRI studies of the human brain, highlighting the validation of white matter orientation estimates and the atlasing and mapping of large subcortical structures. We also give particular emphasis to the delineation of layered gray matter structure with ex vivo dMRI, as this application illustrates the strength of its mesoscale resolution over large fields of view. We end with a discussion and outlook on future and potential directions of the field.

Uncovering the inferior fronto-occipital fascicle and its topological organization in non-human primates: the missing connection for language evolution

Whether brain networks underlying the multimodal processing of language in humans are present in non-human primates is an unresolved question in primate evolution. Conceptual awareness in humans, which is the backbone of verbal and non-verbal semantic elaboration, involves intracerebral connectivity via the inferior fronto-occipital fascicle (IFOF). While non-human primates can communicate through visual information channels, there has been no formal demonstration that they possess a functional homologue of the human IFOF. Therefore, we undertook a post-mortem diffusion MRI tractography study in conjunction with Klingler micro-dissection to search for IFOF fiber tracts in brain of Old-World (vervet) monkeys. We found clear and concordant evidence from both techniques for the existence of bilateral fiber tracts connecting the frontal and occipital lobes. These tracts closely resembled the human IFOF with respect to trajectory, topological organization, and cortical terminal fields. Moreover, these fibers are clearly distinct from other bundles previously described in this region of monkey brain, i.e., the inferior longitudinal and uncinate fascicles, and the external and extreme capsules. This demonstration of an IFOF in brain of a species that diverged from the human lineage some 22 millions years ago enhances our comprehension about the evolution of language and social behavior.

Gray Matter Microstructural Abnormalities and Working Memory Deficits in Individuals with Schizophrenia

OBJECTIVE

Working memory impairments serve as prognostic factors for patients with schizophrenia. Working memory deficits are mainly associated with gray matter (GM) thickness and volume. We investigated the association between GM diffusivity and working memory in controls and individuals with schizophrenia.

METHODS

T1 and diffusion tensor images of the brain, working memory task (letter number sequencing) scores, and the demographic data of 90 individuals with schizophrenia and 97 controls were collected from the SchizConnect database. T1 images were parcellated into the 68 GM Regions of Interest (ROI). Axial Diffusivity (AD), Fractional Anisotropy (FA), Radial Diffusivity (RD), and Trace (TR) were calculated for each of the ROIs.

RESULTS

Compared to the controls, schizophrenia group showed significantly increased AD, RD, and TR in specific regions on the frontal, temporal, and anterior cingulate area. Moreover, working memory was negatively correlated with AD, RD, and TR in the lateral orbitofrontal, superior temporal, inferior temporal, and rostral anterior cingulate area on left hemisphere in the individuals with schizophrenia.

CONCLUSION

These results demonstrated GM microstructural abnormalities in the frontal, temporal, and anterior cingulate regions of individuals with schizophrenia. Furthermore, these regional GM microstructural abnormalities suggest a neuropathological basis for the working memory deficits observed clinically in individuals with schizophrenia.

Histopathology of diffusion imaging abnormalities in cerebral amyloid angiopathy

OBJECTIVE

We sought to determine the underlying mechanism for altered white matter diffusion tensor imaging (DTI) measures at the histopathologic level in patients with cerebral amyloid angiopathy (CAA).

METHODS

Formalin-fixed intact hemispheres from 9 CAA cases and 2 elderly controls were scanned at 3-tesla MRI, including a diffusion-weighted sequence. DTI measures (i.e., fractional anisotropy [FA] and mean diffusivity [MD]) and histopathology measures were obtained from 2 tracts: the anterior thalamic radiation and inferior longitudinal fasciculus.

RESULTS

FA was reduced in both tracts and MD was increased in cases with CAA compared to controls. Regional FA was significantly correlated with tissue rarefaction, myelin density, axonal density, and white matter microinfarcts. MD correlated significantly with tissue rarefaction, myelin density, and white matter microinfarcts, but not axonal density. FA and MD did not correlate with oligodendrocytes, astrocytes, or gliosis. Multivariate analysis revealed that tissue rarefaction (β = -0.32 ± 0.12, p = 0.009) and axonal density (β = 0.25 ± 0.12, p = 0.04) were both independently associated with FA, whereas myelin density was independently associated with MD (β = -0.32 ± 0.12, p = 0.013). Finally, we found an association between increased MD in the frontal white matter and CAA severity in the frontal cortex (p = 0.035).

CONCLUSIONS

These results suggest that overall tissue loss, and in particular axonal and myelin loss, are major components underlying CAA-related alterations in DTI properties observed in living patients. The findings allow for a more mechanistic interpretation of DTI parameters in small vessel disease and for mechanism-based selection of candidate treatments to prevent vascular cognitive impairment.

Post mortem high resolution diffusion MRI for large specimen imaging at 11.7 T with 3D segmented echo-planar imaging

BACKGROUND

Diffusion weighted imaging (DWI) is the only in vivo technique allowing for the mapping of tissue fiber architecture. Post mortem DWI is an increasingly popular method, since longer acquisition times (compared to in vivo) allow higher spatial and angular resolutions to be achieved. However, DWI protocols must be adapted to post mortem tissue (e.g., tuning acquisition parameters to account for changes in T1/T2). New method: In this work, we developed a framework to obtain high quality diffusion weighted images on post mortem large samples by using a combination of fast imaging with 3D diffusion-weighted segmented EPI (3D-DW seg-EPI), Gadolinium soaking and data denoising. Analyses including tractography were used to check the quality of the acquired data, including a comparison with 3D-DW SE acquisitions. Comparison with existing method: Effects on diffusion data of each of the components of the framework were tested: 3D-DW seg-EPI versus 3D-DW SE EPI; with and without data denoising; with and without Gd-soaking.

CONCLUSIONS

Our study demonstrated the feasibility of analysing anatomical connectivity using diffusion imaging of a post mortem macaque brain with a 3D-DW seg-EPI sequence acquired at ultra-high field. The combination of high angular and spatial resolution DWI with Gd-soaking and denoising provided data allowing us to perform diffusion tractography with results very similar to those obtained with a 3D-DW SE acquisition (with shorter acquisition times: 222 h versus 37 h for 3D-DW seg-EPI).

Topological principles and developmental algorithms might refine diffusion tractography

The identification and reconstruction of axonal pathways in the living brain or "ex-vivo" is promising a revolution in connectivity studies bridging the gap from animal to human neuroanatomy with extensions to brain structural-functional correlates. Unfortunately, the methods suffer from juvenile drawbacks. In this perspective paper we mention several computational and developmental principles, which might stimulate a new generation of algorithms and a discussion bridging the neuroimaging and neuroanatomy communities.

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

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

Identification of the pedunculopontine nucleus and surrounding white matter tracts on 7T diffusion tensor imaging, combined with histological validation

BACKGROUND

The pedunculopontine nucleus (PPN) has been studied as a possible target for deep brain stimulation (DBS) for Parkinson's disease (PD). However, identifying the PPN can be challenging as the PPN is poorly visualized on conventional or even high-resolution MR scans. From histological studies it is known that the PPN is surrounded by major white matter tracts, which could function as possible anatomical landmarks.

METHODS

This study aimed to localize the PPN using 7T magnetic resonance (MR) imaging and diffusion tensor imaging (DTI) of its white matter borders in one post-mortem brain. Histological validation of the same specimen was performed. The PPN was segmented in both spaces, after which the two masks were compared using the Dice Similarity Index (DSI). The DSI compared the similarity of two samples on an inter-individual level and validated the MR findings. The error in distance between the center of the two 3D segmentations was measured by use of the Euclidean distance.

RESULTS

The PPN can be found in between the superior cerebellar peduncle and the medial lemniscus on both the FA-maps of the DTI images and the histological sections. The histological transverse sections showed to be superior to recognize the PPN (DSI: 1.0). The DTI images have a DSI of 0.82. The overlap-masks of both spaces showed a DSI of 0.32, whereas the concatenation-masks of both spaces showed a remarkable overlap, a DSI of 0.94. Euclidean distance of the overlap- and concatenation-mask in the two spaces showed to be 1.29 mm and 1.59 mm, respectively.

CONCLUSION

This study supports previous findings that the PPN can be identified using FA-maps of DTI images. For possible clinical application in DBS localization, in vivo validation of the findings of our study is needed.

Limits to anatomical accuracy of diffusion tractography using modern approaches

Diffusion MRI fiber tractography is widely used to probe the structural connectivity of the brain, with a range of applications in both clinical and basic neuroscience. Despite widespread use, tractography has well-known pitfalls that limits the anatomical accuracy of this technique. Numerous modern methods have been developed to address these shortcomings through advances in acquisition, modeling, and computation. To test whether these advances improve tractography accuracy, we organized the 3-D Validation of Tractography with Experimental MRI (3D-VoTEM) challenge at the ISBI 2018 conference. We made available three unique independent tractography validation datasets - a physical phantom and two ex vivo brain specimens - resulting in 176 distinct submissions from 9 research groups. By comparing results over a wide range of fiber complexities and algorithmic strategies, this challenge provides a more comprehensive assessment of tractography's inherent limitations than has been reported previously. The central results were consistent across all sub-challenges in that, despite advances in tractography methods, the anatomical accuracy of tractography has not dramatically improved in recent years. Taken together, our results independently confirm findings from decades of tractography validation studies, demonstrate inherent limitations in reconstructing white matter pathways using diffusion MRI data alone, and highlight the need for alternative or combinatorial strategies to accurately map the fiber pathways of the brain.

Whole mouse brain structural connectomics using magnetic resonance histology

Diffusion tensor histology holds great promise for quantitative characterization of structural connectivity in mouse models of neurological and psychiatric conditions. There has been extensive study in both the clinical and preclinical domains on the complex tradeoffs between the spatial resolution, the number of samples in diffusion q-space, scan time, and the reliability of the resultant data. We describe here a method for accelerating the acquisition of diffusion MRI data to support quantitative connectivity measurements in the whole mouse brain using compressed sensing (CS). The use of CS allows substantial increase in spatial resolution and/or reduction in scan time. Compared to the fully sampled results at the same scan time, the subtle anatomical details of the brain, such as cortical layers, dentate gyrus, and cerebellum, were better visualized using CS due to the higher spatial resolution. Compared to the fully sampled results at the same spatial resolution, the scalar diffusion metrics, including fractional anisotropy (FA) and mean diffusivity (MD), showed consistently low error across the whole brain (< 6.0%) even with 8.0 times acceleration. The node properties of connectivity (strength, cluster coefficient, eigenvector centrality, and local efficiency) demonstrated correlation of better than 95.0% between accelerated and fully sampled connectomes. The acceleration will enable routine application of this technology to a wide range of mouse models of neurologic diseases.

Anatomical accuracy of standard-practice tractography algorithms in the motor system - A histological validation in the squirrel monkey brain

For two decades diffusion fiber tractography has been used to probe both the spatial extent of white matter pathways and the region to region connectivity of the brain. In both cases, anatomical accuracy of tractography is critical for sound scientific conclusions. Here we assess and validate the algorithms and tractography implementations that have been most widely used - often because of ease of use, algorithm simplicity, or availability offered in open source software. Comparing forty tractography results to a ground truth defined by histological tracers in the primary motor cortex on the same squirrel monkey brains, we assess tract fidelity on the scale of voxels as well as over larger spatial domains or regional connectivity. No algorithms are successful in all metrics, and, in fact, some implementations fail to reconstruct large portions of pathways or identify major points of connectivity. The accuracy is most dependent on reconstruction method and tracking algorithm, as well as the seed region and how this region is utilized. We also note a tremendous variability in the results, even though the same MR images act as inputs to all algorithms. In addition, anatomical accuracy is significantly decreased at increased distances from the seed. An analysis of the spatial errors in tractography reveals that many techniques have trouble properly leaving the gray matter, and many only reveal connectivity to adjacent regions of interest. These results show that the most commonly implemented algorithms have several shortcomings and limitations, and choices in implementations lead to very different results. This study should provide guidance for algorithm choices based on study requirements for sensitivity, specificity, or the need to identify particular connections, and should serve as a heuristic for future developments in tractography.

Validation strategies for the interpretation of microstructure imaging using diffusion MRI

Extracting microanatomical information beyond the image resolution of MRI would provide valuable tools for diagnostics and neuroscientific research. A number of mathematical models already suggest microstructural interpretations of diffusion MRI (dMRI) data. Examples of such microstructural features could be cell bodies and neurites, e.g. the axon's diameter or their orientational distribution for global connectivity analysis using tractography, and have previously only been possible to access through conventional histology of post mortem tissue or invasive biopsies. The prospect of gaining the same knowledge non-invasively from the whole living human brain could push the frontiers for the diagnosis of neurological and psychiatric diseases. It could also provide a general understanding of the development and natural variability in the healthy brain across a population. However, due to a limited image resolution, most of the dMRI measures are indirect estimations and may depend on the whole chain from experimental parameter settings to model assumptions and implementation. Here, we review current literature in this field and highlight the integrative work across anatomical length scales that is needed to validate and trust a new dMRI method. We encourage interdisciplinary collaborations and data sharing in regards to applying and developing new validation techniques to improve the specificity of future dMRI methods.

The VALiDATe29 MRI Based Multi-Channel Atlas of the Squirrel Monkey Brain

We describe the development of the first digital atlas of the normal squirrel monkey brain and present the resulting product, VALiDATe29. The VALiDATe29 atlas is based on multiple types of magnetic resonance imaging (MRI) contrast acquired on 29 squirrel monkeys, and is created using unbiased, nonlinear registration techniques, resulting in a population-averaged stereotaxic coordinate system. The atlas consists of multiple anatomical templates (proton density, T1, and T2* weighted), diffusion MRI templates (fractional anisotropy and mean diffusivity), and ex vivo templates (fractional anisotropy and a structural MRI). In addition, the templates are combined with histologically defined cortical labels, and diffusion tractography defined white matter labels. The combination of intensity templates and image segmentations make this atlas suitable for the fundamental atlas applications of spatial normalization and label propagation. Together, this atlas facilitates 3D anatomical localization and region of interest delineation, and enables comparisons of experimental data across different subjects or across different experimental conditions. This article describes the atlas creation and its contents, and demonstrates the use of the VALiDATe29 atlas in typical applications. The atlas is freely available to the scientific community.

Cortical fibers orientation mapping using in-vivo whole brain 7 T diffusion MRI

Diffusion MRI of the cortical gray matter is challenging because the micro-environment probed by water molecules is much more complex than within the white matter. High spatial and angular resolutions are therefore necessary to uncover anisotropic diffusion patterns and laminar structures, which provide complementary (e.g. to anatomical and functional MRI) microstructural information about the cortex architectonic. Several ex-vivo and in-vivo MRI studies have recently addressed this question, however predominantly with an emphasis on specific cortical areas. There is currently no whole brain in-vivo data leveraging multi-shell diffusion MRI acquisition at high spatial resolution, and depth dependent analysis, to characterize the complex organization of cortical fibers. Here, we present unique in-vivo human 7T diffusion MRI data, and a dedicated cortical depth dependent analysis pipeline. We leverage the high spatial (1.05 mm isotropic) and angular (198 diffusion gradient directions) resolution of this whole brain dataset to improve cortical fiber orientations mapping, and study neurites (axons and/or dendrites) trajectories across cortical depths. Tangential fibers in superficial cortical depths and crossing fiber configurations in deep cortical depths are identified. Fibers gradually inserting into the gyral walls are visualized, which contributes to mitigating the gyral bias effect. Quantitative radiality maps and histograms in individual subjects and cortex-based aligned datasets further support our results.

Postmortem diffusion MRI of the entire human spinal cord at microscopic resolution

The human spinal cord is a central nervous system structure that plays an important role in normal motor and sensory function, and can be affected by many debilitating neurologic diseases. Due to its clinical importance, the spinal cord is frequently the subject of imaging research. Common methods for visualizing spinal cord anatomy and pathology include histology and magnetic resonance imaging (MRI), both of which have unique benefits and drawbacks. Postmortem microscopic resolution MRI of fixed specimens, sometimes referred to as magnetic resonance microscopy (MRM), combines many of the benefits inherent to both techniques. However, the elongated shape of the human spinal cord, along with hardware and scan time limitations, have restricted previous microscopic resolution MRI studies (both in vivo and ex vivo) to small sections of the cord. Here we present the first MRM dataset of the entire postmortem human spinal cord. These data include 50 μm isotropic resolution anatomic image data and 100 μm isotropic resolution diffusion data, made possible by a 280 h long multi-segment acquisition and automated image segment composition. We demonstrate the use of these data for spinal cord lesion detection, automated volumetric gray matter segmentation, and quantitative spinal cord morphometry including estimates of cross sectional dimensions and gray matter fraction throughout the length of the cord.

The Crossed Projection to the Striatum in Two Species of Monkey and in Humans: Behavioral and Evolutionary Significance

The corpus callosum establishes the anatomical continuity between the 2 hemispheres and coordinates their activity. Using histological tracing, single axon reconstructions, and diffusion tractography, we describe a callosal projection to n caudatus and putamen in monkeys and humans. In both species, the origin of this projection is more restricted than that of the ipsilateral projection. In monkeys, it consists of thin axons (0.4-0.6 µm), appropriate for spatial and temporal dispersion of subliminal inputs. For prefrontal cortex, contralateral minus ipsilateral delays to striatum calculated from axon diameters and conduction distance are <2 ms in the monkey and, by extrapolation, <4 ms in humans. This delay corresponds to the performance in Poffenberger's paradigm, a classical attempt to estimate central conduction delays, with a neuropsychological task. In both species, callosal cortico-striatal projections originate from prefrontal, premotor, and motor areas. In humans, we discovered a new projection originating from superior parietal lobule, supramarginal, and superior temporal gyrus, regions engaged in language processing. This projection crosses in the isthmus the lesion of which was reported to dissociate syntax and prosody. The projection might originate from an overproduction of callosal projections in development, differentially pruned depending on species.

Voxel-wise comparisons of cellular microstructure and diffusion-MRI in mouse hippocampus using 3D Bridging of Optically-clear histology with Neuroimaging Data (3D-BOND)

A key challenge in medical imaging is determining a precise correspondence between image properties and tissue microstructure. This comparison is hindered by disparate scales and resolutions between medical imaging and histology. We present a new technique, 3D Bridging of Optically-clear histology with Neuroimaging Data (3D-BOND), for registering medical images with 3D histology to overcome these limitations. Ex vivo 120 × 120 × 200 μm resolution diffusion-MRI (dMRI) data was acquired at 7 T from adult C57Bl/6 mouse hippocampus. Tissue was then optically cleared using CLARITY and stained with cellular markers and confocal microscopy used to produce high-resolution images of the 3D-tissue microstructure. For each sample, a dense array of hippocampal landmarks was used to drive registration between upsampled dMRI data and the corresponding confocal images. The cell population in each MRI voxel was determined within hippocampal subregions and compared to MRI-derived metrics. 3D-BOND provided robust voxel-wise, cellular correlates of dMRI data. CA1 pyramidal and dentate gyrus granular layers had significantly different mean diffusivity (p > 0.001), which was related to microstructural features. Overall, mean and radial diffusivity correlated with cell and axon density and fractional anisotropy with astrocyte density, while apparent fibre density correlated negatively with axon density. Astrocytes, axons and blood vessels correlated to tensor orientation.

Magnetic resonance temporal diffusion tensor spectroscopy of disordered anisotropic tissue

Molecular diffusion measured with diffusion weighted MRI (DWI) offers a probe for tissue microstructure. However, inferring microstructural properties from conventional DWI data is a complex inverse problem and has to account for heterogeneity in sizes, shapes and orientations of the tissue compartments contained within an imaging voxel. Alternative experimental means for disentangling the signal signatures of such features could provide a stronger link between the data and its interpretation. Double diffusion encoding (DDE) offers the possibility to factor out variation in compartment shapes from orientational dispersion of anisotropic domains by measuring the correlation between diffusivity in multiple directions. Time dependence of the diffusion is another effect reflecting the dimensions and distributions of barriers. In this paper we extend on DDE with a modified version of the oscillating gradient spin echo (OGSE) experiment, giving a basic contrast mechanism closely linked to both the temporal diffusion spectrum and the compartment anisotropy. We demonstrate our new method on post mortem brain tissue and show that we retrieve the correct temporal diffusion tensor spectrum in synthetic data from Monte Carlo simulations of random walks in a range of disordered geometries of different sizes and shapes.

Post-mortem inference of the human hippocampal connectivity and microstructure using ultra-high field diffusion MRI at 11.7 T

The human hippocampus plays a key role in memory management and is one of the first structures affected by Alzheimer's disease. Ultra-high magnetic resonance imaging provides access to its inner structure in vivo. However, gradient limitations on clinical systems hinder access to its inner connectivity and microstructure. A major target of this paper is the demonstration of diffusion MRI potential, using ultra-high field (11.7 T) and strong gradients (750 mT/m), to reveal the extra- and intra-hippocampal connectivity in addition to its microstructure. To this purpose, a multiple-shell diffusion-weighted acquisition protocol was developed to reach an ultra-high spatio-angular resolution with a good signal-to-noise ratio. The MRI data set was analyzed using analytical Q-Ball Imaging, Diffusion Tensor Imaging (DTI), and Neurite Orientation Dispersion and Density Imaging models. High Angular Resolution Diffusion Imaging estimates allowed us to obtain an accurate tractography resolving more complex fiber architecture than DTI models, and subsequently provided a map of the cross-regional connectivity. The neurite density was akin to that found in the histological literature, revealing the three hippocampal layers. Moreover, a gradient of connectivity and neurite density was observed between the anterior and the posterior part of the hippocampus. These results demonstrate that ex vivo ultra-high field/ultra-high gradients diffusion-weighted MRI allows the mapping of the inner connectivity of the human hippocampus, its microstructure, and to accurately reconstruct elements of the polysynaptic intra-hippocampal pathway using fiber tractography techniques at very high spatial/angular resolutions.

Validation of diffusion MRI estimates of compartment size and volume fraction in a biomimetic brain phantom using a human MRI scanner with 300 mT/m maximum gradient strength

Diffusion microstructural imaging techniques have attracted great interest in the last decade due to their ability to quantify axon diameter and volume fraction in healthy and diseased human white matter. The estimates of compartment size and volume fraction continue to be debated, in part due to the lack of a gold standard for validation and quality control. In this work, we validate diffusion MRI estimates of compartment size and volume fraction using a novel textile axon ("taxon") phantom constructed from hollow polypropylene yarns with distinct intra- and extra-taxonal compartments to mimic white matter in the brain. We acquired a comprehensive set of diffusion MRI measurements in the phantom using multiple gradient directions, diffusion times and gradient strengths on a human MRI scanner equipped with maximum gradient strength (G_max) of 300 mT/m. We obtained estimates of compartment size and restricted volume fraction through a straightforward extension of the AxCaliber/ActiveAx frameworks that enables estimation of mean compartment size in fiber bundles of arbitrary orientation. The voxel-wise taxon diameter estimates of 12.2 ± 0.9 μm were close to the manufactured inner diameter of 11.8 ± 1.2 μm with G_max = 300 mT/m. The estimated restricted volume fraction demonstrated an expected decrease along the length of the fiber bundles in accordance with the known construction of the phantom. When G_max was restricted to 80 mT/m, the taxon diameter was overestimated, and the estimates for taxon diameter and packing density showed greater uncertainty compared to data with G_max = 300 mT/m. In conclusion, the compartment size and volume fraction estimates resulting from diffusion measurements on a human scanner were validated against ground truth in a phantom mimicking human white matter, providing confidence that this method can yield accurate estimates of parameters in simplified but realistic microstructural environments. Our work also demonstrates the importance of a biologically analogous phantom that can be applied to validate a variety of diffusion microstructural imaging methods in human scanners and be used for standardization of diffusion MRI protocols for neuroimaging research.

Confirmation of a gyral bias in diffusion MRI fiber tractography

Diffusion MRI fiber tractography has been increasingly used to map the structural connectivity of the human brain. However, this technique is not without limitations; for example, there is a growing concern over anatomically correlated bias in tractography findings. In this study, we demonstrate that there is a bias for fiber tracking algorithms to terminate preferentially on gyral crowns, rather than the banks of sulci. We investigate this issue by comparing diffusion MRI (dMRI) tractography with equivalent measures made on myelin-stained histological sections. We begin by investigating the orientation and trajectories of axons near the white matter/gray matter boundary, and the density of axons entering the cortex at different locations along gyral blades. These results are compared with dMRI orientations and tract densities at the same locations, where we find a significant gyral bias in many gyral blades across the brain. This effect is shown for a range of tracking algorithms, both deterministic and probabilistic, and multiple diffusion models, including the diffusion tensor and a high angular resolution diffusion imaging technique. Additionally, the gyral bias occurs for a range of diffusion weightings, and even for very high-resolution datasets. The bias could significantly affect connectivity results using the current generation of tracking algorithms.

Can increased spatial resolution solve the crossing fiber problem for diffusion MRI?

It is now widely recognized that voxels with crossing fibers or complex geometrical configurations present a challenge for diffusion MRI (dMRI) reconstruction and fiber tracking, as well as microstructural modeling of brain tissues. This "crossing fiber" problem has been estimated to affect anywhere from 30% to as many as 90% of white matter voxels, and it is often assumed that increasing spatial resolution will decrease the prevalence of voxels containing multiple fiber populations. The aim of this study is to estimate the extent of the crossing fiber problem as we progressively increase the spatial resolution, with the goal of determining whether it is possible to mitigate this problem with higher resolution spatial sampling. This is accomplished using ex vivo MRI data of the macaque brain, followed by histological analysis of the same specimen to validate these measurements, as well as to extend this analysis to resolutions not yet achievable in practice with MRI. In both dMRI and histology, we find unexpected results: the prevalence of crossing fibers increases as we increase spatial resolution. The problem of crossing fibers appears to be a fundamental limitation of dMRI associated with the complexity of brain tissue, rather than a technical problem that can be overcome with advances such as higher fields and stronger gradients.

Short parietal lobe connections of the human and monkey brain

The parietal lobe has a unique place in the human brain. Anatomically, it is at the crossroad between the frontal, occipital, and temporal lobes, thus providing a middle ground for multimodal sensory integration. Functionally, it supports higher cognitive functions that are characteristic of the human species, such as mathematical cognition, semantic and pragmatic aspects of language, and abstract thinking. Despite its importance, a comprehensive comparison of human and simian intraparietal networks is missing. In this study, we used diffusion imaging tractography to reconstruct the major intralobar parietal tracts in twenty-one datasets acquired in vivo from healthy human subjects and eleven ex vivo datasets from five vervet and six macaque monkeys. Three regions of interest (postcentral gyrus, superior parietal lobule and inferior parietal lobule) were used to identify the tracts. Surface projections were reconstructed for both species and results compared to identify similarities or differences in tract anatomy (i.e., trajectories and cortical projections). In addition, post-mortem dissections were performed in a human brain. The largest tract identified in both human and monkey brains is a vertical pathway between the superior and inferior parietal lobules. This tract can be divided into an anterior (supramarginal gyrus) and a posterior (angular gyrus) component in both humans and monkey brains. The second prominent intraparietal tract connects the postcentral gyrus to both supramarginal and angular gyri of the inferior parietal lobule in humans but only to the supramarginal gyrus in the monkey brain. The third tract connects the postcentral gyrus to the anterior region of the superior parietal lobule and is more prominent in monkeys compared to humans. Finally, short U-shaped fibres in the medial and lateral aspects of the parietal lobe were identified in both species. A tract connecting the medial parietal cortex to the lateral inferior parietal cortex was observed in the monkey brain only. Our findings suggest a consistent pattern of intralobar parietal connections between humans and monkeys with some differences for those areas that have cytoarchitectonically distinct features in humans. The overall pattern of intraparietal connectivity supports the special role of the inferior parietal lobule in cognitive functions characteristic of humans.