A novel framework for in-vivo diffusion tensor distribution MRI of the human brain

Tutorial: a guide to diffusion MRI and structural connectomics

Diffusion magnetic resonance imaging (dMRI) is a versatile imaging technique that has gained popularity thanks to its sensitive ability to measure displacement of water molecules within a living tissue on a micrometer scale. Although dMRI has been around since the early 1990s, its applications are constantly evolving, primarily regarding the inference of structural connectomics from nerve fiber trajectories. However, these applications require expertise in image processing and statistics, and it can be difficult for a newcomer to choose an appropriate pipeline to fit their research needs, not least because dMRI is such a flexible methodology that dozens of acquisition and analysis pipelines have been developed over the years. This introductory guide is designed for graduate students and researchers in the neuroscience community who are interested in integrating this new methodology regardless of their background in neuroimaging and computational tools. The guide provides a brief overview of the basic dMRI methodologies but focuses on its applications in neuroplasticity and connectomics. The guide starts with dMRI experimental designs and a complete step-by-step pipeline for structural connectomics. The following section covers the basics of dMRI, including parameters and clinical applications (apparent diffusion coefficient, mean diffusivity, fractional anisotropy and microscopic fractional anisotropy), as well as different approaches and models. The final section focuses on structural connectomics, covering subjects from fiber tracking (techniques, evaluation and limitations) to structural networks (constructing, analyzing and visualizing a network).

Opioid use and abuse in adolescents and young adults; dealing with science, laws and ethics: Charming the COBRAS

The subject of substance use disorders in the pediatric population remains a disturbing conundrum for clinicians, researchers and society in general. Many of our youth are at risk of being damaged and even killed by drug addictions that result from the collision of rapidly developing as well as vulnerable central nervous systems encountering the current global drug addiction crisis. A major motif of this chemical calamity is opioid use disorder in adolescents and young adults that was stimulated by the 19th century identification of such highly addictive drugs as morphine, heroin and a non-opiate, cocaine. This analysis focuses on the pervasive presence of opioid drugs such as heroin and fentanyl that has become a major tragedy in the 21st century arising from an overall substance use and misuse phenomenon rampant in global society. Themes covered in this article include the history of addictive drugs in humans, diagnostic terms in use, the role of neurobiology in drug addiction, and current psychopharmacologic approaches to opioid overdose as well as addiction. Our youth are continuously confronted by dangers of high-risk behaviors including death and injury from opioid use disorders due to their central nervous system neuroplasticity as well as the widespread availability of these harmful chemicals. Healthcare professionals should actively assist our youth who unknowingly and even innocently encounter this deadly menace in the 21st century.

An MRI Deep Brain Adult Template With An Advanced Atlas-Based Tool For Diffusion Tensor Imaging Analysis

Understanding the architecture of the human deep brain is especially challenging because of the complex organization of the nuclei and fascicles that support most sensorimotor and behaviour controls. There are scant dedicated tools to explore and analyse this region. Here we took a transdisciplinary approach to build a new deep-brain MRI architecture atlas drawing on advanced clinical experience of MRI-based deep brain mapping. This new tool comprises a young-male-adult MRI template spatially normalized to the ICBM152, containing T1, inversion-recovery, and diffusion MRI datasets (in vivo acquisition), and an MRI atlas of 118 labelled deep brain structures. It is open-source and gives users high resolution image datasets to describe nuclear-based and axonal architecture, combining pioneering and recent knowledge. It is a useful addition to current 3D atlases and clinical tools.

Direct segmentation of cortical cytoarchitectonic domains using ultra-high-resolution whole-brain diffusion MRI

We assess the potential of detecting cortical laminar patterns and areal borders by directly clustering voxel values of microstructural parameters derived from high-resolution mean apparent propagator (MAP) magnetic resonance imaging (MRI), as an alternative to conventional template-warping-based cortical parcellation methods. We acquired MAP-MRI data with 200μm resolution in a fixed macaque monkey brain. To improve the sensitivity to cortical layers, we processed the data with a local anisotropic Gaussian filter determined voxel-wise by the plane tangent to the cortical surface. We directly clustered all cortical voxels using only the MAP-derived microstructural imaging biomarkers, with no information regarding their relative spatial location or dominant diffusion orientations. MAP-based 3D cytoarchitectonic segmentation revealed laminar patterns similar to those observed in the corresponding histological images. Moreover, transition regions between these laminar patterns agreed more accurately with histology than the borders between cortical areas estimated using conventional atlas/template-warping cortical parcellation. By cross-tabulating all cortical labels in the atlas- and MAP-based segmentations, we automatically matched the corresponding MAP-derived clusters (i.e., cytoarchitectonic domains) across the left and right hemispheres. Our results demonstrate that high-resolution MAP-MRI biomarkers can effectively delineate three-dimensional cortical cytoarchitectonic domains in single individuals. Their intrinsic tissue microstructural contrasts enable the construction of whole-brain mesoscopic cortical atlases.

Diffusion tensor imaging in cerebral small vessel disease applications: opportunities and challenges

Cerebral small vessel disease (CSVD) is a syndrome of pathology, imaging, and clinical manifestations caused primarily by a variety of functional or structural lesions in the small blood vessels of the brain. CSVD contributes to approximately 45% of dementia and 25% of ischemic strokes worldwide and is one of the most important causes of disability. The disease progresses insidiously, and patients often have no typical symptoms in the early stages, but have an increased risk of stroke, death, and poor long-term prognosis. Therefore, early diagnosis of CSVD is particularly important. Neuroimaging is the most important diagnostic tool used for CSVD. Therefore, it is important to explore the imaging mechanisms of CSVD for its early diagnosis and precise treatment. In this article, we review the principles and analysis methods of DTI, analyze the latest DTI studies on CSVD, clarify the disease-lesion mapping relationships between cerebral white matter (WM) microstructural damage and CSVD, explore the pathogenic mechanisms and preclinical imaging features of CSVD, and summarize the latest research directions of CSVD and research methods to provide a comprehensive and objective imaging basis for the diagnosis and treatment of CSVD.

Water Diffusion in the Live Human Brain is Gaussian at the Mesoscale

Imaging the live human brain at the mesoscopic scale is a desideratum in basic and clinical neurosciences. Despite the promise of diffusion MRI, the lack of an accurate model relating the measured signal and the associated microstructure has hampered its success. The widely used diffusion tensor MRI (DTI) model assumes an anisotropic Gaussian diffusion process in each voxel, but lacks the ability to capture intravoxel heterogeneity. This study explores the extension of the DTI model to mesoscopic length scales by use of the diffusion tensor distribution (DTD) model, which assumes a Gaussian diffusion process in each subvoxel. DTD MRI has shown promise in addressing some limitations of DTI, particularly in distinguishing among different types of brain cancers and elucidating multiple fiber populations within a voxel. However, its validity in live brain tissue has never been established. Here, multiple diffusion-encoded (MDE) data were acquired in the living human brain using a 3 Tesla MRI scanner with large diffusion weighting factors. Two different diffusion times (Δ = 37, 74 ms) were employed, with other scanning parameters fixed to assess signal decay differences. In vivo diffusion-weighted signals in gray and white matter were nearly identical at the two diffusion times. Fitting the signals to the DTD model yielded indistinguishable results, except in the cerebrospinal fluid (CSF)-filled voxels likely due to pulsatile flow. Overall, the study supports the time invariance of water diffusion at the mesoscopic scale in live brain parenchyma, extending the validity of the anisotropic Gaussian diffusion model in clinical brain imaging.

The Subcortical Atlas of the Marmoset ("SAM") monkey based on high-resolution MRI and histology

A comprehensive three-dimensional digital brain atlas of cortical and subcortical regions based on MRI and histology has a broad array of applications in anatomical, functional, and clinical studies. We first generated a Subcortical Atlas of the Marmoset, called the "SAM," from 251 delineated subcortical regions (e.g. thalamic subregions, etc.) derived from high-resolution Mean Apparent Propagator-MRI, T2W, and magnetization transfer ratio images ex vivo. We then confirmed the location and borders of these segmented regions in the MRI data using matched histological sections with multiple stains obtained from the same specimen. Finally, we estimated and confirmed the atlas-based areal boundaries of subcortical regions by registering this ex vivo atlas template to in vivo T1- or T2W MRI datasets of different age groups (single vs. multisubject population-based marmoset control adults) using a novel pipeline developed within Analysis of Functional NeuroImages software. Tracing and validating these important deep brain structures in 3D will improve neurosurgical planning, anatomical tract tracer injections, navigation of deep brain stimulation probes, functional MRI and brain connectivity studies, and our understanding of brain structure-function relationships. This new ex vivo template and atlas are available as volumes in standard NIFTI and GIFTI file formats and are intended for use as a reference standard for marmoset brain research.

The Subcortical Atlas of the Marmoset ("SAM") monkey based on high-resolution MRI and histology

A comprehensive three-dimensional digital brain atlas of cortical and subcortical regions based on MRI and histology has a broad array of applications for anatomical, functional, and clinical studies. We first generated a Subcortical Atlas of the Marmoset, called the "SAM," from 251 delineated subcortical regions (e.g., thalamic subregions, etc.) derived from the high-resolution MAP-MRI, T2W, and MTR images ex vivo. We then confirmed the location and borders of these segmented regions in MRI data using matched histological sections with multiple stains obtained from the same specimen. Finally, we estimated and confirmed the atlas-based areal boundaries of subcortical regions by registering this ex vivo atlas template to in vivo T1- or T2W MRI datasets of different age groups (single vs. multisubject population-based marmoset control adults) using a novel pipeline developed within AFNI. Tracing and validating these important deep brain structures in 3D improves neurosurgical planning, anatomical tract tracer injections, navigation of deep brain stimulation probes, fMRI and brain connectivity studies, and our understanding of brain structure-function relationships. This new ex vivo template and atlas are available as volumes in standard NIFTI and GIFTI file formats and are intended for use as a reference standard for marmoset brain research.

Multimodal anatomical mapping of subcortical regions in marmoset monkeys using high-resolution MRI and matched histology with multiple stains

Subcortical nuclei and other deep brain structures play essential roles in regulating the central and peripheral nervous systems. However, many of these nuclei and their subregions are challenging to identify and delineate in conventional MRI due to their small size, hidden location, and often subtle contrasts compared to neighboring regions. To address these limitations, we scanned the whole brain of the marmoset monkeys in ex vivo using a clinically feasible diffusion MRI method, called the mean apparent propagator (MAP)-MRI, along with T2W and MTR (T1-like contrast) images acquired at 7 Tesla. Additionally, we registered these multimodal MRI volumes to the high-resolution images of matched whole-brain histology sections with seven different stains obtained from the same brain specimens. At high spatial resolution, the microstructural parameters and fiber orientation distribution functions derived with MAP-MRI can distinguish the subregions of many subcortical and deep brain structures, including fiber tracts of different sizes and orientations. The good correlation with multiple but distinct histological stains from the same brain serves as a thorough validation of the structures identified with MAP-MRI and other MRI parameters. Moreover, the anatomical details of deep brain structures found in the volumes of MAP-MRI parameters are not visible in conventional T1W or T2W images. The high-resolution mapping using novel MRI contrasts, combined and correlated with histology, can elucidate structures that were previously invisible radiologically. Thus, this multimodal approach offers a roadmap toward identifying salient brain areas in vivo in future neuroradiological studies. It also provides a useful anatomical standard reference for the region definition of subcortical targets and the generation of a 3D digital template atlas for the marmoset brain research (Saleem et al., 2023). Additionally, we conducted a cross-species comparison between marmoset and macaque monkeys using results from our previous studies (Saleem et al., 2021). We found that the two species had distinct patterns of iron distribution in subregions of the basal ganglia, red nucleus, and deep cerebellar nuclei, confirmed with T2W MRI and histology.

Multimodal anatomical mapping of subcortical regions in Marmoset monkeys using high-resolution MRI and matched histology with multiple stains

Subcortical nuclei and other deep brain structures play essential roles in regulating the central and peripheral nervous systems. However, many of these nuclei and their subregions are challenging to identify and delineate in conventional MRI due to their small size, hidden location, and often subtle contrasts compared to neighboring regions. To address these limitations, we scanned the whole brain of the marmoset monkeys in ex vivo using a clinically feasible diffusion MRI method, called the mean apparent propagator (MAP)-MRI, along with T2W and MTR (T1-like contrast) images acquired at 7 Tesla. Additionally, we registered these multimodal MRI volumes to the high-resolution images of matched whole-brain histology sections with seven different stains obtained from the same brain specimens. At high spatial resolution, the microstructural parameters and fiber orientation distribution functions derived with MAP-MRI can distinguish the subregions of many subcortical and deep brain structures, including fiber tracts of different sizes and orientations. The good correlation with multiple but distinct histological stains from the same brain serves as a thorough validation of the structures identified with MAP-MRI and other MRI parameters. Moreover, the anatomical details of deep brain structures found in the volumes of MAP-MRI parameters are not visible in conventional T1W or T2W images. The high-resolution mapping using novel MRI contrasts, combined and correlated with histology, can elucidate structures that were previously invisible radiologically. Thus, this multimodal approach offers a roadmap toward identifying salient brain areas in vivo in future neuroradiological studies. It also provides a useful anatomical standard reference for the region definition of subcortical targets and the generation of a 3D digital template atlas for the marmoset brain research (Saleem et al., 2023). Additionally, we conducted a cross-species comparison between marmoset and macaque monkeys using results from our previous studies (Saleem et al., 2021). We found that the two species had distinct patterns of iron distribution in subregions of the basal ganglia, red nucleus, and deep cerebellar nuclei, confirmed with T2W MRI and histology.