Insights into hippocampal perfusion using high-resolution, multi-modal 7T MRI.

We present a comprehensive study on the non-invasive measurement of hippocampal perfusion. Using high-resolution 7 tesla arterial spin labeling (ASL) data, we generated robust perfusion maps and observed significant variations in perfusion among hippocampal subfields, with CA1 exhibiting the lowest perfusion levels. Notably, these perfusion differences were robust and already detectable with 50 perfusion-weighted images per subject, acquired in 5 min. To understand the underlying factors, we examined the influence of image quality metrics, various tissue microstructure and morphometric properties, macrovasculature, and cytoarchitecture. We observed higher perfusion in regions located closer to arteries, demonstrating the influence of vascular proximity on hippocampal perfusion. Moreover, ex vivo cytoarchitectonic features based on neuronal density differences appeared to correlate stronger with hippocampal perfusion than morphometric measures like gray matter thickness. These findings emphasize the interplay between microvasculature, macrovasculature, and metabolic demand in shaping hippocampal perfusion. Our study expands the current understanding of hippocampal physiology and its relevance to neurological disorders. By providing in vivo evidence of perfusion differences between hippocampal subfields, our findings have implications for diagnosis and potential therapeutic interventions. In conclusion, our study provides a valuable resource for extensively characterizing hippocampal perfusion.

Diffusion MRI of the Hippocampus.

The hippocampus is a brain structure that plays key roles in a variety of cognitive processes. Critically, a wide range of neurological disorders are associated with degeneration of the hippocampal microstructure, defined as neurons, dendrites, glial cells, and more. Thus, the hippocampus is a key target for methods that are sensitive to these microscale properties. Diffusion MRI is one such method, which can noninvasively probe neural architecture. Here we review the extensive use of diffusion MRI to capture hippocampal microstructure in both health and disease. The results of these studies indicate that (1) diffusion tensor imaging is sensitive but not specific to the hippocampal microstructure; (2) biophysical modeling of diffusion MRI signals is a promising avenue to capture more specific aspects of the hippocampal microstructure; (3) use of ultra-short diffusion times have shown unique laminar-specific microstructure and response to hippocampal injury; (4) dispersion of microstructure is likely abundant in the hippocampus; and (5) the angular richness of the diffusion MRI signal can be leveraged to improve delineation of the internal hippocampal circuitry. Overall, extant findings suggest that diffusion MRI offers a promising avenue for characterizing hippocampal microstructure.

Focal acetylcholinergic modulation of the human midcingulo-insular network during attention: Meta-analytic neuroimaging and behavioral evidence.

The basal forebrain cholinergic neurons provide acetylcholine to the cortex via large projections. Recent molecular imaging work in humans indicates that the cortical cholinergic innervation is not uniformly distributed, but rather may disproportionately innervate cortical areas relevant to supervisory attention. In this study, we therefore reexamined the spatial relationship between acetylcholinergic modulation and attention in the human cortex using meta-analytic strategies targeting both pharmacological and non-pharmacological neuroimaging studies. We found that pharmaco-modulation of acetylcholine evoked both increased activity in the anterior cingulate and decreased activity in the opercular and insular cortex. In large independent meta-analyses of non-pharmacological neuroimaging research, we demonstrate that during attentional engagement these cortical areas exhibit (1) task-related co-activation with the basal forebrain, (2) task-related co-activation with one another, and (3) spatial overlap with dense cholinergic innervations originating from the basal forebrain, as estimated by multimodal positron emission tomography and magnetic resonance imaging. Finally, we provide meta-analytic evidence that pharmaco-modulation of acetylcholine also induces a speeding of responses to targets with no apparent tradeoff in accuracy. In sum, we demonstrate in humans that acetylcholinergic modulation of midcingulo-insular hubs of the ventral attention/salience network via basal forebrain afferents may coordinate selection of task relevant information, thereby facilitating cognition and behavior.

Mapping the macrostructure and microstructure of the in vivo human hippocampus using diffusion MRI.

The hippocampus is classically divided into mesoscopic subfields which contain varying microstructure that contribute to their unique functional roles. It has been challenging to characterize this microstructure with current magnetic resonance based neuroimaging techniques. In this work, we used diffusion magnetic resonance imaging (dMRI) and a novel surface-based approach in the hippocampus which revealed distinct microstructural distributions of neurite density and dispersion, T1w/T2w ratio as a proxy for myelin content, fractional anisotropy, and mean diffusivity. We used the neurite orientation dispersion and density imaging (NODDI) model optimized for grey matter diffusivity to characterize neurite density and dispersion. We found that neurite dispersion was highest in the cornu ammonis (CA) 1 and subiculum subfields which likely captures the large heterogeneity of tangential and radial fibres, such as the Schaffer collaterals, perforant path, and pyramidal neurons. Neurite density and T1w/T2w were highest in the subiculum and CA3 and lowest in CA1, which may reflect known myeloarchitectonic differences between these subfields. Using a simple logistic regression model, we showed that neurite density, dispersion, and T1w/T2w measures were separable across the subfields, suggesting that they may be sensitive to the known variability in subfield cyto- and myeloarchitecture. We report macrostructural measures of gyrification, thickness, and curvature that were in line with ex vivo descriptions of hippocampal anatomy. We employed a multivariate orthogonal projective non-negative matrix factorization (OPNNMF) approach to capture co-varying regions of macro- and microstructure across the hippocampus. The clusters were highly variable along the medial-lateral (proximal-distal) direction, likely reflecting known differences in morphology, cytoarchitectonic profiles, and connectivity. Finally, we show that by examining the main direction of diffusion relative to canonical hippocampal axes, we could identify regions with stereotyped microstructural orientations that may map onto specific fibre pathways, such as the Schaffer collaterals, perforant path, fimbria, and alveus. These results highlight the value of combining in vivo dMRI with computational approaches for capturing hippocampal microstructure, which may provide useful features for understanding cognition and for diagnosis of disease states.

Mapping the subcortical connectome using in vivo diffusion MRI: Feasibility and reliability.

Tractography combined with regions of interest (ROIs) has been used to non-invasively study the structural connectivity of the cortex as well as to assess the reliability of these connections. However, the subcortical connectome (subcortex to subcortex) has not been comprehensively examined, in part due to the difficulty of performing tractography in this complex and compact region. In this study, we performed an in vivo investigation using tractography to assess the feasibility and reliability of mapping known connections between structures of the subcortex using the test-retest dataset from the Human Connectome Project (HCP). We further validated our observations using a separate unrelated subjects dataset from the HCP. Quantitative assessment was performed by computing tract densities and spatial overlap of identified connections between subcortical ROIs. Further, known connections between structures of the basal ganglia and thalamus were identified and visually inspected, comparing tractography reconstructed trajectories with descriptions from tract-tracing studies. Our observations demonstrate both the feasibility and reliability of using a data-driven tractography-based approach to map the subcortical connectome in vivo.

Ultra-High Field 7-Tesla Magnetic Resonance Imaging and Electroencephalography Findings in Epilepsy.

PURPOSE: Assessment of patients for temporal lobe epilepsy (TLE) surgery requires multimodality input, including EEG recordings to ensure optimal surgical planning. Often EEG demonstrates abnormal foci not detected on 1.5T MRI. Ultra-high field MRI at 7T provides improved resolution of the brain. We investigated the utility of 7T MRI to detect potential anatomical abnormalities associated with EEG changes. METHODS: Ultra-high field data were acquired on a 7T MRI scanner for 13 patients with history of drug resistant TLE who had had EEG telemetry recordings. Qualitative evaluation of 7T imaging for presence of focal abnormalities detected on EEG was performed. Correlation of 7T MRI findings with EEG recordings of focal slowing or interictal epileptic spikes (IEDs), and seizures was performed. RESULTS: Assessment of 7T MRI demonstrated concordance with TLE as determined by the multidisciplinary team in 61.5% of cases (n = 8). Among these, 3 patients exhibited supportive abnormal 7T MRI abnormalities not detected by 1.5T MRI. In patients who underwent surgery, 72.7% had concordant histopathology findings with 7T MRI findings (n = 8). However, qualitative assessment of 7T images revealed focal anatomical abnormalities to account for EEG findings in only 15.4% of patients (n = 2). Other regions that were found to have localized IEDs in addition to the lesional temporal lobe, included the contralateral temporal lobe (n = 5), frontal lobe (n = 3), and parieto-occipital lobe (n = 2). CONCLUSION: Ultra-high field 7T MRI findings show concordance with clinical data. However, 7T MRI did not reveal anatomical findings to account for abnormalities detected by EEG.

Effects of MP2RAGE B1+ sensitivity on inter-site T1 reproducibility and hippocampal morphometry at 7T.

Most neuroanatomical studies are based on T1-weighted MR images, whose intensity profiles are not solely determined by the tissue's longitudinal relaxation times (T1), but also affected by varying non-T1 contributions, hampering data reproducibility. In contrast, quantitative imaging using the MP2RAGE sequence, for example, allows direct characterization of the brain based on the tissue property of interest. Combined with 7 Tesla (7T) MRI, this offers unique opportunities to obtain robust high-resolution brain data characterized by a high reproducibility, sensitivity and specificity. However, specific MP2RAGE parameter choices - e.g., to emphasize intracortical myelin-dependent contrast variations - can substantially impact image quality and cortical analyses through remnants of B1+-related intensity variations, as illustrated in our previous work. To follow up on this: we (1) validate this protocol effect using a dataset acquired with a particularly B1+ insensitive set of MP2RAGE parameters combined with parallel transmission excitation; and (2) extend our analyses to evaluate the effects on hippocampal morphometry. The latter remained unexplored initially, but can provide important insights related to generalizability and reproducibility of neurodegenerative research using 7T MRI. We confirm that B1+ inhomogeneities have a considerably variable effect on cortical T1 estimates, as well as on hippocampal morphometry depending on the MP2RAGE setup. While T1 differed substantially across datasets initially, we show the inter-site T1 comparability improves after correcting for the spatially varying B1+ field using a separately acquired Sa2RAGE B1+ map. Finally, removal of B1+ residuals affects hippocampal volumetry and boundary definitions, particularly near structures characterized by strong intensity changes (e.g. cerebral spinal fluid). Taken together, we show that the choice of MP2RAGE parameters can impact T1 comparability across sites and present evidence that hippocampal segmentation results are modulated by B1+ inhomogeneities. This calls for careful (1) consideration of sequence parameters when setting acquisition protocols, as well as (2) acquisition of a B1+ map to correct MP2RAGE data for potential B1+ variations to allow comparison across datasets.

Regional Lipid Expression Abnormalities Identified Using MALDI IMS Correspond to MRI-Defined White Matter Hyperintensities within Post-mortem Human Brain Tissues.

Periventricular white matter hyperintensities (pvWMHs) are a neurological feature detected with magnetic resonance imaging that are clinically associated with an increased risk of stroke and dementia. pvWMHs represent white matter lesions characterized by regions of myelin and axon rarefaction and as such likely involve changes in lipid composition; however, these alterations remain unknown. Lipids are critical in determining cell function and survival. Perturbations in lipid expression have previously been associated with neurological disorders. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is an emerging technique for untargeted, high-throughput investigation of lipid expression and spatial distribution in situ; however, the use of MALDI IMS has been previously been limited by the need for non-embedded, non-fixed, fresh-frozen samples. In the current study, we demonstrate the novel use of MALDI IMS to distinguish regional lipid abnormalities that correlate with magnetic resonance imaging (MRI) defined pvWMHs within ammonium formate washed, formalin-fixed human archival samples. MALDI IMS scans were conducted in positive or negative ion detection mode on tissues sublimated with 2,5-dihydroxybenzoic acid or 1,5-diaminonaphthalene matrices, respectively. Using a broad, untargeted approach to lipid analysis, we consistently detected 116 lipid ion species in 21 tissue blocks from 11 different post-mortem formalin-fixed human brains. Comparing the monoisotopic mass peaks of these lipid ions elucidated significant differences in lipid expression between pvWMHs and NAWM for 31 lipid ion species. Expanding our understanding of alterations in lipid composition will provide greater knowledge of molecular mechanisms underpinning ischemic white matter lesions and provides the potential for novel therapeutic interventions targeting lipid composition abnormalities.

Characterizing white matter alterations subject to clinical laterality in drug-naïve de novo Parkinson's disease.

Parkinson's disease (PD) is a progressive neurodegenerative disorder that is characterized by a range of motor and nonmotor symptoms, often with the motor dysfunction initiated unilaterally. Knowledge regarding disease-related alterations in white matter pathways can effectively help improve the understanding of the disease and propose targeted treatment strategies. Microstructural imaging techniques, including diffusion tensor imaging (DTI), allows inspection of white matter integrity to study the pathogenesis of various neurological conditions. Previous voxel-based analyses with DTI measures, such as fractional anisotropy and mean diffusivity have uncovered changes in brain regions that are associated with PD, but the conclusions were inconsistent, partially due to small patient cohorts and the lack of consideration for clinical laterality onset, particularly in early PD. Fixel-based analysis (FBA) is a recent framework that offers tract-specific insights regarding white matter health, but very few FBA studies on PD exist. We present a study that reveals strengthened and weakened white matter integrity that is subject to symptom laterality in a large drug-naïve de novo PD cohort using complementary DTI and FBA measures. The findings suggest that the disease gives rise to tissue degeneration and potential re-organization in the early stage.

Design and characterization of a 3D-printed axon-mimetic phantom for diffusion MRI.

PURPOSE: To introduce and characterize inexpensive and easily produced 3D-printed axon-mimetic diffusion MRI phantoms in terms of pore geometry and diffusion kurtosis imaging metrics. METHODS: Phantoms were 3D-printed with a composite printing material that, after the dissolution of the polyvinyl alcohol, exhibits microscopic fibrous pores. Confocal microscopy and synchrotron phase-contrast micro-CT imaging were performed to visualize and assess the pore sizes. Diffusion MRI scans of four identical phantoms and phantoms with varying print parameters in water were performed at 9.4 T. Diffusion kurtosis imaging was fit to both data sets and used to assess the reproducibility between phantoms and effects of print parameters on diffusion kurtosis imaging metrics. Identical scans were performed 25 and 76 days later, to test their stability. RESULTS: Segmentation of pores in three microscopy images yielded a mean, median, and SD of equivalent pore diameters of 7.57 µm, 3.51 µm, and 12.13 µm, respectively. Phantoms had T1 /T2 = 2 seconds/180 ms, and those with identical parameters showed a low coefficient of variation (~10%) in mean diffusivity (1.38 × 10-3 mm2 /s) and kurtosis (0.52) metrics and radial diffusivity (1.01 × 10-3 mm2 /s) and kurtosis (1.13) metrics. Printing temperature and speed had a small effect on diffusion kurtosis imaging metrics (< 16%), whereas infill density had a larger and more variable effect (> 16%). The stability analysis showed small changes over 2.5 months (< 7%). CONCLUSION: Three-dimension-printed axon-mimetic phantoms can mimic the fibrous structure of axon bundles on a microscopic scale, serving as complex, anisotropic diffusion MRI phantoms.

Evaluating High Spatial Resolution Diffusion Kurtosis Imaging at 3T: Reproducibility and Quality of Fit.

BACKGROUND: Diffusion kurtosis imaging (DKI) quantifies the non-Gaussian diffusion of water within tissue microstructure. However, it has increased fitting parameters and requires higher b-values. Evaluation of DKI reproducibility is important for clinical purposes. PURPOSE: To assess the reproducibility in whole-brain high-resolution DKI at varying b-values. STUDY TYPE: Retrospective. SUBJECTS AND PHANTOMS: In all, 44 individuals from the test-retest Human Connectome Project (HCP) database and 12 3D-printed phantoms. FIELD STRENGTH/SEQUENCE: Diffusion-weighted multiband echo-planar imaging sequence at 3T and 9.4T. magnetization-prepared rapid acquisition gradient echo at 3T for in vivo structural data only. ASSESSMENT: From HCP data with b-values = 1000, 2000, 3000 s/mm2 (dataset A), two additional datasets with b-values = 1000, 3000 s/mm2 (dataset B) and b-values = 1000, 2000 s/mm2 (dataset C) were extracted. Estimated DKI metrics from each dataset were used for evaluating reproducibility and fitting quality in white matter (WM) and gray matter (GM) based on whole-brain and regions of interest (ROIs). STATISTICAL TESTS: DKI reproducibility was assessed using the within-subject coefficient of variation (CoV), fitting residuals to evaluate DKI fitting accuracy and Pearson's correlation to investigate the presence of systematic biases. Repeated measures analysis of variance was used for statistical comparison. RESULTS: Datasets A and B exhibited lower DKI CoVs (<20%) compared to C (<50%) in both WM and GM ROIs (all P < 0.05). This effect varies between DKI and DTI parameters (P < 0.005). Whole-brain fitting residuals were consistent across datasets (P > 0.05), but lower residuals in dataset B were detected for the WM ROIs (P < 0.001). A similar trend was observed for the phantom data CoVs (<7.5%) at varying fiber orientations for datasets A and B. Finally, dataset C was characterized by higher residuals across the different fiber crossings (P < 0.05). DATA CONCLUSION: The study demonstrates that high reproducibility can still be achieved within a reasonable scan time, specifically dataset B, supporting the potential of DKI for aiding clinical tools in detecting microstructural changes.

Acute conceptual disorganization in untreated first-episode psychosis: a combined magnetic resonance spectroscopy and diffusion imaging study of the cingulum.

Background: Disorganized thinking is a core feature of acute psychotic episodes that is linked to social and vocational functioning. Several lines of evidence implicate disrupted cognitive control, excitatory overdrive and oxidative stress relating to the anterior cingulate cortex as mechanisms of conceptual disorganization (CD). We examined 3 candidate mechanistic markers related to CD in firstepisode psychosis: glutamate excess, cortical antioxidant (glutathione) status and the integrity of the cingulum bundle that connects regions implicated in cognitive control. Methods: We used fractional anisotropy maps from 7 T diffusion-weighted imaging to investigate the bilateral cingulum based on a probabilistic white matter atlas. We compared high CD, low CD and healthy control groups and performed probabilistic fibre tracking from the identified clusters (regions of interest within the cingulum) to the rest of the brain. We quantified glutamate and glutathione using magnetic resonance spectroscopy (MRS) in the dorsal anterior cingulate cortex. Results: We found a significant fractional anisotropy reduction in a cluster in the left cingulum in the high CD group compared to the low CD group (Cohen's d = 1.39; p < 0.001) and controls (Cohen's d = 0.86; p = 0.009). Glutamate levels did not vary among groups, but glutathione levels were higher in the high CD group than in the low CD group. We also found higher glutathione related to lower fractional anisotropy in the cingulum cluster in the high CD group. Limitations: The MRS measures of glutamine were highly uncertain, and MRS was acquired from a single voxel only. Conclusion: Acute CD relates to indicators of oxidative stress, as well as reduced white matter integrity of the cingulum, but not to MRI-based glutamatergic excess. We propose that both oxidative imbalance and structural dysconnectivity underlie acute disorganization.

Frontal-striatal connectivity and positive symptoms of schizophrenia: implications for the mechanistic basis of prefrontal rTMS.

Repetitive transcranial magnetic stimulation (rTMS), when applied to left dorsolateral prefrontal cortex (LDLPFC), reduces negative symptoms of schizophrenia, but has no effect on positive symptoms. In a small number of cases, it appears to worsen the severity of positive symptoms. It has been hypothesized that high-frequency rTMS of the LDLPFC might increase the dopaminergic neurotransmission by driving the activity of the left striatum in the basal ganglia (LSTR)-increasing striatal dopaminergic activity. This hypothesis relies on the assumption that either the frontal-striatal connection or the intrinsic frontal and/or striatal connections covary with the severity of positive symptoms. The current work aimed to evaluate this assumption by studying the association between positive and negative symptoms severity and the effective connectivity within the frontal and striatal network using dynamic causal modeling of resting state fMRI in a sample of 19 first episode psychosis subjects. We found that the total score of positive symptoms of schizophrenia is strongly associated with the frontostriatal circuitry. Stronger intrinsic inhibitory tone of LDLPFC and LSTR, as well as decreased bidirectional excitatory influence between the LDLPFC and the LSTR is related to the severity of positive symptoms, especially delusions. We interpret that an increase in striatal dopaminergic tone that underlies positive symptoms is likely associated with increased prefrontal inhibitory tone, strengthening the frontostriatal 'brake'. Furthermore, based on our model, we propose that lessening of positive symptoms could be achieved by means of continuous theta-burst or low-frequency (1 Hz) rTMS of the prefrontal area.

Direct visualization and characterization of the human zona incerta and surrounding structures.

The zona incerta (ZI) is a small gray matter region of the deep brain first identified in the 19th century, yet direct in vivo visualization and characterization has remained elusive. Noninvasive detection of the ZI and surrounding region could be critical to further our understanding of this widely connected but poorly understood deep brain region and could contribute to the development and optimization of neuromodulatory therapies. We demonstrate that high resolution (submillimetric) longitudinal (T1) relaxometry measurements at high magnetic field strength (7 T) can be used to delineate the ZI from surrounding white matter structures, specifically the fasciculus cerebellothalamicus, fields of Forel (fasciculus lenticularis, fasciculus thalamicus, and field H), and medial lemniscus. Using this approach, we successfully derived in vivo estimates of the size, shape, location, and tissue characteristics of substructures in the ZI region, confirming observations only previously possible through histological evaluation that this region is not just a space between structures but contains distinct morphological entities that should be considered separately. Our findings pave the way for increasingly detailed in vivo study and provide a structural foundation for precise functional and neuromodulatory investigation.

Diffusion dispersion imaging: Mapping oscillating gradient spin-echo frequency dependence in the human brain.

PURPOSE: Oscillating gradient spin-echo (OGSE) diffusion MRI provides information about the microstructure of biological tissues by means of the frequency dependence of the apparent diffusion coefficient (ADC). ADC dependence on OGSE frequency has been explored in numerous rodent studies, but applications in the human brain have been limited and have suffered from low contrast between different frequencies, long scan times, and a limited exploration of the nature of the ADC dependence on frequency. THEORY AND METHODS: Multiple frequency OGSE acquisitions were acquired in healthy subjects at 7T to explore the power-law frequency dependence of ADC, the "diffusion dispersion." Furthermore, a method for optimizing the estimation of the ADC difference between different OGSE frequencies was developed, which enabled the design of a highly efficient protocol for mapping diffusion dispersion. RESULTS: For the first time, evidence of a linear dependence of ADC on the square root of frequency in healthy human white matter was obtained. Using the optimized protocol, high-quality, full-brain maps of apparent diffusion dispersion rate were also demonstrated at an isotropic resolution of 2 mm in a scan time of 6 min. CONCLUSIONS: This work sheds light on the nature of diffusion dispersion in the healthy human brain and introduces full-brain diffusion dispersion mapping at clinically relevant scan times. These advances may lead to new biomarkers of pathology or improved microstructural modeling.

A framework for evaluating correspondence between brain images using anatomical fiducials.

Accurate spatial correspondence between template and subject images is a crucial step in neuroimaging studies and clinical applications like stereotactic neurosurgery. In the absence of a robust quantitative approach, we sought to propose and validate a set of point landmarks, anatomical fiducials (AFIDs), that could be quickly, accurately, and reliably placed on magnetic resonance images of the human brain. Using several publicly available brain templates and individual participant datasets, novice users could be trained to place a set of 32 AFIDs with millimetric accuracy. Furthermore, the utility of the AFIDs protocol is demonstrated for evaluating subject-to-template and template-to-template registration. Specifically, we found that commonly used voxel overlap metrics were relatively insensitive to focal misregistrations compared to AFID point-based measures. Our entire protocol and study framework leverages open resources and tools, and has been developed with full transparency in mind so that others may freely use, adopt, and modify. This protocol holds value for a broad number of applications including alignment of brain images and teaching neuroanatomy.

Unfolding the hippocampus: An intrinsic coordinate system for subfield segmentations and quantitative mapping.

The hippocampus, like the neocortex, has a morphological structure that is complex and variable in its folding pattern, especially in the hippocampal head. The current study presents a computational method to unfold hippocampal grey matter, with a particular focus on the hippocampal head where complexity is highest due to medial curving of the structure and the variable presence of digitations. This unfolding was performed on segmentations from high-resolution, T2-weighted 7T MRI data from 12 healthy participants and one surgical patient with epilepsy whose resected hippocampal tissue was used for histological validation. We traced a critical image feature composed of the hippocampal sulcus and stratum radiatum lacunosum-moleculare, (SRLM) in these images, then employed user-guided semi-automated techniques to detect and subsequently unfold the surrounding hippocampal grey matter. This unfolding was performed by solving Laplace's equation in three dimensions of interest (long-axis, proximal-distal, and laminar). The resulting 'unfolded coordinate space' provides an intuitive way of mapping the hippocampal subfields in 2D space (long-axis and proximal-distal), such that similar borders can be applied in the head, body, and tail of the hippocampus independently of variability in folding. This unfolded coordinate space was employed to map intracortical myelin and thickness in relation to subfield borders, which revealed intracortical myelin differences that closely follow the subfield borders used here. Examination of a histological resected tissue sample from a patient with epilepsy reveals that our unfolded coordinate system has biological validity, and that subfield segmentations applied in this space are able to capture features not seen in manual tracing protocols.

Quantification of local geometric distortion in structural magnetic resonance images: Application to ultra-high fields.

Ultra-high field magnetic resonance imaging (MRI) provides superior visualization of brain structures compared to lower fields, but images may be prone to severe geometric inhomogeneity. We propose to quantify local geometric distortion at ultra-high fields in in vivo datasets of human subjects scanned at both ultra-high field and lower fields. By using the displacement field derived from nonlinear image registration between images of the same subject, focal areas of spatial uncertainty are quantified. Through group and subject-specific analysis, we were able to identify regions systematically affected by geometric distortion at air-tissue interfaces prone to magnetic susceptibility, where the gradient coil non-linearity occurs in the occipital and suboccipital regions, as well as with distance from image isocenter. The derived displacement maps, quantified in millimeters, can be used to prospectively evaluate subject-specific local spatial uncertainty that should be taken into account in neuroimaging studies, and also for clinical applications like stereotactic neurosurgery where accuracy is critical. Validation with manual fiducial displacement demonstrated excellent correlation and agreement. Our results point to the need for site-specific calibration of geometric inhomogeneity. Our methodology provides a framework to permit prospective evaluation of the effect of MRI sequences, distortion correction techniques, and scanner hardware/software upgrades on geometric distortion.

Novel connectivity map normalization procedure for improved quantitative investigation of structural thalamic connectivity in temporal lobe epilepsy patients.

BACKGROUND: Connectivity studies targeting the thalamus have revealed patterns of atrophy and deafferentiation in temporal lobe epilepsy (TLE). The thalamus can be parcellated using probabilistic tractography to demonstrate regions of cortical connectivity; however, sensitivity to smaller or less connected regions is low. PURPOSE/HYPOTHESIS: To investigate thalamic structural connectivity in a wider range of cortical and limbic structures in TLE patients using a novel connectivity map normalization procedure. STUDY TYPE: Retrospective. POPULATION/SUBJECTS: Patients (N = 23) with medication-resistant TLE and 34 healthy age-matched controls. FIELD STRENGTH/SEQUENCE: For T1 and diffusion weighting a spoiled gradient sequence was used (41 gradient directions [b = 1000]). For T2 mapping balanced steady-state free precession was used. Images were acquired at 3T. ASSESSMENT: Probabilistic tractography and a novel normalization procedure allowed comparison of groups with respect to thalamic connected volume, quantitative MRI, and diffusion tensor imaging (DTI) metrics. STATISTICAL TESTS: Independent samples t-test, Cohen's d, and Mann-Whitney tests. RESULTS: Following normalization, significant differences in thalamic connected volumes were found in left TLE vs. controls bilaterally within the posterior parahippocampal gyrus (L: P = 0.007, confidence interval [CI]: [173.306,1044.41], effect size [ES] = 1.072; R: P = 0.017, CI: [98.677,947.653], ES = 0.945), and contralaterally in the anterior temporal neocortex (P = 0.01, CI: (-2348.09, -333.719), ES = -1.021). This procedure revealed differences in thalamic connected volumes, where previously published procedures could not, and provided a basis for exploratory analysis of quantitative MRI and DTI metrics. DATA CONCLUSION: The novel connectivity map normalization scheme proposed here successfully allowed comparison between a wider range of cortical and limbic structures. Multiple volumetric and quantitative MRI and DTI-related differences between TLE patients and controls were revealed following normalization. With validation from a larger cohort, thalamo-temporal connection aberrancies may become useful biomarkers of disease states and probabilistic tractography as a procedure for identification of thalamic targets in modulatory therapies for TLE. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:1529-1539.

Pathophysiology and Risk of Atrial Fibrillation Detected after Ischemic Stroke (PARADISE): A Translational, Integrated, and Transdisciplinary Approach.

BACKGROUND: It has been hypothesized that ischemic stroke can cause atrial fibrillation. By elucidating the mechanisms of neurogenically mediated paroxysmal atrial fibrillation, novel therapeutic strategies could be developed to prevent atrial fibrillation occurrence and perpetuation after stroke. This could result in fewer recurrent strokes and deaths, a reduction or delay in dementia onset, and in the lessening of the functional, structural, and metabolic consequences of atrial fibrillation on the heart. METHODS: The Pathophysiology and Risk of Atrial Fibrillation Detected after Ischemic Stroke (PARADISE) study is an investigator-driven, translational, integrated, and transdisciplinary initiative. It comprises 3 complementary research streams that focus on atrial fibrillation detected after stroke: experimental, clinical, and epidemiological. The experimental stream will assess pre- and poststroke electrocardiographic, autonomic, anatomic (brain and heart pathology), and inflammatory trajectories in an animal model of selective insular cortex ischemic stroke. The clinical stream will prospectively investigate autonomic, inflammatory, and neurocognitive changes among patients diagnosed with atrial fibrillation detected after stroke by employing comprehensive and validated instruments. The epidemiological stream will focus on the demographics, clinical characteristics, and outcomes of atrial fibrillation detected after stroke at the population level by means of the Ontario Stroke Registry, a prospective clinical database that comprises over 23,000 patients with ischemic stroke. CONCLUSIONS: PARADISE is a translational research initiative comprising experimental, clinical, and epidemiological research aimed at characterizing clinical features, the pathophysiology, and outcomes of neurogenic atrial fibrillation detected after stroke.