Alexandru Vlad Avram

Purpose: To demonstrate the feasibility of whole-brain multidimensional T ₁ - T ₂ relaxation imaging on a portable 0.064 T MRI scanner. Methods: A two-dimensional inversion-recovery, fast spin-echo acquisition was used to jointly encode T ₁ and T ₂ relaxation. Joint relaxation distributions were reconstructed voxel-wise using marginal-distribution constrained optimization (MADCO). The approach was evaluated in a quantitative relaxation MRI phantom and subsequently applied in vivo in a healthy volunteer. Joint distributions, marginal distributions, distribution-derived measures, and statistical dependencies between the two relaxation dimensions were examined. Results: Phantom joint relaxation estimates showed good overall agreement with mono-exponential relaxation measurements and previously reported values at 0.064 T. The in vivo acquisition provided whole-brain coverage over a broad range of relaxation weightings and tissue contrasts. Reconstructed joint T ₁ - T ₂ distributions showed spatially organized features across the relaxation space, including broad and overlapping relaxation components that were not fully represented by single-value relaxation maps or by either 1D marginal distribution alone. Selected regions of the joint relaxation space produced component maps with distinct spatial patterns. Statistical analysis further showed a dependence between the two relaxation dimensions, supporting the presence of added information in the joint distribution that is lost when treating T ₁ and T ₂ separately. Conclusion: Whole-brain multidimensional T ₁ - T ₂ relaxation imaging is clinically feasible on a portable 0.064 T MRI scanner. Joint relaxation distributions provide information beyond single-value relaxation mapping and may support further developments of quantitative multidimensional imaging at ultra-low field.

The cerebellum shapes distributed motor and association networks through precisely organized pathways linking the cerebellar cortex to the deep cerebellar nuclei (DCN), its principal output structures. Whether these cortical and nuclear compartments scale proportionally across primates, and how their relative expansion relates to cerebellar organization, remains unresolved. Here, we generate multimodal, high-resolution cross-species 3D cerebellar atlases in marmoset, macaque, and human by integrating iron-sensitive and diffusion MRI (MAP-MRI) with histological markers, enabling direct delineation of cerebellar lobules and DCN subdivisions within a unified framework. Comparative volumetric analyses reveal strikingly nonuniform scaling of cerebellar cortical-nuclear architecture: cortical expansion markedly outpaces DCN enlargement, indicating disproportionate growth of input relative to output systems. This divergence is accompanied by progressive reorganization of the DCN, with increasing dominance of the dentate nucleus. In contrast, cortical expansion is driven by posterior hemispheric territories, with lobules VI-IX and Crus I/II, linked to higher-order functions, showing the strongest scaling and largest absolute gains, whereas DCN subdivisions show selective rather than uniform scaling. Together, these findings establish nonuniform cortical-nuclear scaling as a systems-level organizational principle that reshapes cerebellar input-output architecture across primates.

BACKGROUND: Mild traumatic brain injury (mTBI) is a signature injury in civilian and military populations that remains invisible to detection by conventional radiological methods. Diffusion MRI has been identified as a potential clinical tool for revealing subtle microstructural alterations associated with mTBI. OBJECTIVE: This study evaluates whether a comprehensive and powerful diffusion MRI (dMRI) technique called mean apparent propagator (MAP) MRI can detect sequelae of mTBI. METHODS: We analyzed data from 417 participants of the GE/NFL prospective mTBI study which included 143 matched controls (mean age, 21.9; 76 women) and 274 patients with acute mTBI and GCS ≥13 (mean age, 21.9; 131 women). All participants underwent MRI exams at up to four visits including structural high-resolution T1W, T2W, FLAIR-T2W, and dMRI, in addition to clinical assessments of post-concussive physical symptoms (RPQ-3), psychosocial functioning and lifestyle symptoms (RPQ-13), and postural stability (BESS). The dMRI data for each subject were co-registered across all visits and analyzed using the MAP-MRI framework to measure and map the distribution of net microscopic displacements of diffusing water molecules in tissue and ultimately compute the microstructural MAP-MRI tissue parameters including propagator anisotropy (PA), Non-Gaussianity (NG), return-to-origin probability (RTOP), return-to-axis probability (RTAP), and return-to-plane probability (RTPP). We quantified voxelwise and region-of-interest (ROI)-based changes in these parameters across all four visits. RESULTS: MAP-MRI parameter values were within the expected ranges and showed relatively little variation across visits. We found no significant differences in the longitudinal trajectories of these parameters between mTBI patients and controls. At acute post-injury timepoints, RPQ-3 and RPQ-13 scores were increased in mTBI patients relative to controls, while BESS scores were not significantly different between groups. Analysis of dMRI metrics and clinical mTBI markers showed significant correspondence between MAP-MRI metrics in cortical gray matter, caudate and pallidum and BESS scores. CONCLUSION:We developed and tested a state-of-the-art quantitative image processing pipeline for sensitive analysis and detection of subtle tissue changes in longitudinal clinical diffusion MRI data. The absence of a significant statistical difference between populations in the dMRI parameters in this study suggests that the mTBI corresponded to acute post-injury clinical symptoms but that the injury was not severe enough to cause detectable microstructural damage/alterations, and that increased diffusion sensitization combined with improved analysis techniques may be needed. CLINICAL IMPACT: These findings suggest that acute mTBI (GCS≥13) may not be detectable with diffusion MRI. TRIAL REGISTRATION. ClinicalTrials.gov NCT02556177 Keywords: traumatic brain injury, longitudinal study, diffusion MRI, mean apparent propagator

The cerebellum shapes distributed motor and association networks through precisely organized pathways linking the cerebellar cortex to the deep cerebellar nuclei (DCN), its principal output structures. Whether these cortical and nuclear compartments scale proportionally across primates and how their relative expansion influences large-scale brain organization remains unclear. We generated multimodal, high-resolution cross-species 3D cerebellar atlases in marmoset, macaque, and human, integrating iron-sensitive magnetic resonance contrast with complementary histological markers to delineate DCN subdivisions in detail. Comparative volumetric analyses reveal nonuniform scaling of cerebellar cortical-nuclear architecture: cortical expansion markedly outpaces enlargement of the DCN, indicating disproportionate growth of input relative to output structures. This divergence parallels preferential expansion of posterior hemispheric territories, particularly lobules VI-IX and Crus I/II linked to higher-order association networks, whereas DCN subdivisions show selective rather than uniform scaling. Together, these findings establish nonuniform cortical-nuclear scaling as a systems-level organizational principle that reshapes cerebellar contributions to distributed brain networks.

“Remote palpation” appears to be an oxymoron, but here we demonstrate a non-contacting MRI method to obtain mechanical stiffness parameters of the human brain solely by measuring deformations caused by the pumping action of the heart. Mechanical stiffness is an important tissue property that is highly sensitive to subtle changes in the tissue milieu; MR elastography (MRE) is among a handful of methods used to measure it, typically via an external driver/tamper that introduces mechanical waves into the tissue. Applying MRE in the brain is challenging due to the use of an external actuator/tamper and the mechanical anisotropy of brain tissue, which requires a 4 ^th -order tensor to describe it. In this study, we use the intrinsic deformation of brain tissue caused by periodic cardiac pulsations to measure the 4 ^th -order elasticity tensor throughout the brain while simultaneously estimating the 2 ^nd -order diffusion tensor in each voxel throughout the cardiac cycle which we use as a priori information in the reconstruction of the elasticity tensor. While the DTI-derived mean diffusivity (MD) appears uniform throughout brain parenchyma, stiffness maps obtained at about 1 Hz (i.e., at the fundamental cardiac frequency) show that brain tissue is very soft within gray matter, and within white matter pathways, such as along the corpus callosum, corona radiata, etc. Generally, stiffness differences at internal tissue boundaries are expected to produce local stress concentration there, which may predispose tissues to damage, e.g., in traumatic brain injury (TBI). Therefore, our novel tamperless MRE method has the potential to not only identify such interfaces, but assess and follow changes in tissue stiffness there that might occur following injury.

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 200 μm 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.

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 200 µ m 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.

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.

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.

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 S ubcortical A tlas of the M armoset, 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.