Multimodal Magnetic Resonance Imaging Analysis Research Articles

Structural-informed functional MRI analysis of patients with empathy impairment following stroke.

The underlying functional alterations of brain structural changes among patients with empathy impairment following stroke remain unclear. We sought to investigate functional connectivity changes informed by brain structural abnormalities in multimodal magnetic resonance imaging (MRI) among patients with empathy impairment following stroke. We enrolled people who had experienced their first ischemic stroke, along with healthy controls. We assessed empathy 3 months after stroke using the Chinese version of the Empathy Quotient (EQ). During the acute phase, all patients underwent basic magnetic resonance imaging (MRI), followed by multimodal MRI during follow-up. Our MRI analyses encompassed acute infarction segmentation, volumetric brain measurements, regional quantification of diffusion parameters, and both region-of-interest-based and seed-based functional connectivity assessments. We grouped patients based on the severity of their empathy impairment for comparative analysis. We included 84 patients who had stroke and 22 healthy controls. Patients had lower EQ scores than controls. Patients with low empathy had larger left cortical infarcts (odds ratio [OR] 4.082, 95% confidence interval [CI] 1.183-14.088), more pronounced atrophy in the right cingulate cortex (OR 1.248, 95% CI 1.038-1.502), and lower scores on the Montreal Cognitive Assessment (OR 0.873, 95% CI 0.74-0.947). In addition, the cingulate cortex served as the seed in the seed-based analysis, which showed heightened functional connectivity between the anterior cingulate gyrus and the right superior parietal lobule, specifically in the low-empathy group. We did not evaluate the relationship between specific network involvement and empathy impairment among patients following stroke. Among patients with subacute ischemic stroke, reduced empathy was strongly associated with a more severe cognitive profile and atrophy of the right cingulate cortex. Our subsequent structural-informed functional MRI analysis suggests that the enhanced connectivity between the anterior cingulate gyrus and the superior parietal lobule may function as a compensatory mechanism for this atrophy.

A multimodal MRI study of XNKQ acupuncture for limb dysfunction after ischemic stroke: a randomized controlled study protocol.

Limb motor dysfunction is one of the challenges in rehabilitation after cerebral ischemic stroke (CIS) and greatly affects the quality of life of patients. This study aims to investigate the central mechanisms of the curative effect with multimodal magnetic resonance imaging (MRI), which will provide additional evidence to support the application of Xingnao Kaiqiao (XNKQ) acupuncture. This trial is a randomized controlled trial. Patients who meet the criteria will be recruited and randomly divided into 2 groups. One group will receive acupuncture treatment and another group will not receive acupuncture treatment. Both groups will receive conventional treatment. In addition, 20 healthy individuals will be recruited who will not receive any treatment. The total course of treatment is 14 days. The primary outcome is multimodal MRI analysis. For safety assessment, adverse events will be observed and recorded. The study involving human subjects was reviewed and approved by the Ethics Committee of IRB of The First Teaching Hospital of Tianjin University of TCM (TYLL2023[K]031). This study complied with the Declaration of Helsinki. Written informed consent about this study was provided by the participants. The results of this study will be published in a peer-reviewed journal. Chinese Clinical Trial Registration Center (ChiCTR2300078315) https://www.chictr.org.cn/.

Neurovascular coupling dysfunction in high myopia patients: Evidence from a multi-modal magnetic resonance imaging analysis

Background and purposeTo investigate neurovascular coupling dysfunction in high myopia (HM) patients. Materials and methodsA total of 37 HM patients and 36 healthy controls were included in this study. Degree centrality (DC), regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), and fractional ALFF (fALFF) maps were employed to represent neuronal activity. Cerebral blood perfusion was characterized by cerebral blood flow (CBF). The correlation coefficient was calculated to reflect the relationship between neuronal activity and cerebral blood perfusion. Pearson partial correlation analysis was utilized to evaluate the association between HM dysfunction and clinical indicators. ResultsHM patients exhibited significant alterations in neurovascular coupling across 37 brain regions compared to healthy controls. The brain regions with marked changes varied among the four neurovascular coupling patterns, including the middle frontal gyrus, superior occipital gyrus, middle occipital gyrus, and fusiform gyrus. Additionally, the superior frontal gyrus orbital part, medial superior frontal gyrus, inferior occipital gyrus, and dorsolateral superior frontal gyrus displayed significant changes in three coupling patterns. In HM patients, the ReHo-CBF changes in the inferior frontal gyrus orbital part were positively correlated with best-corrected visual acuity (BCVA) and refractive diopter changes. Similarly, the ALFF-CBF changes in the inferior frontal gyrus orbital part showed a positive correlation with refractive diopter changes. ReHo-CBF and ALFF-CBF alterations in the paracentral lobule were positively correlated with BCVA and refractive diopter changes. ConclusionOur findings underscore the abnormal alterations in neurovascular coupling across multiple brain regions in HM patients. These results suggest that neurovascular dysfunction in HM patients may be associated with an aberrant visual regulation mechanism.

Discriminative analysis of schizophrenia patients using graph convolutional networks: A combined multimodal MRI and connectomics analysis.

Recent studies in human brain connectomics with multimodal magnetic resonance imaging (MRI) data have widely reported abnormalities in brain structure, function and connectivity associated with schizophrenia (SZ). However, most previous discriminative studies of SZ patients were based on MRI features of brain regions, ignoring the complex relationships within brain networks. We applied a graph convolutional network (GCN) to discriminating SZ patients using the features of brain region and connectivity derived from a combined multimodal MRI and connectomics analysis. Structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 140 SZ patients and 205 normal controls. Eighteen types of brain graphs were constructed for each subject using 3 types of node features, 3 types of edge features, and 2 brain atlases. We investigated the performance of 18 brain graphs and used the TopK pooling layers to highlight salient brain regions (nodes in the graph). The GCN model, which used functional connectivity as edge features and multimodal features (sMRI + fMRI) of brain regions as node features, obtained the highest average accuracy of 95.8%, and outperformed other existing classification studies in SZ patients. In the explainability analysis, we reported that the top 10 salient brain regions, predominantly distributed in the prefrontal and occipital cortices, were mainly involved in the systems of emotion and visual processing. Our findings demonstrated that GCN with a combined multimodal MRI and connectomics analysis can effectively improve the classification of SZ at an individual level, indicating a promising direction for the diagnosis of SZ patients. The code is available at https://github.com/CXY-scut/GCN-SZ.git.

Manual lesion segmentations for traumatic brain injury characterization.

Traumatic brain injury (TBI) often results in heterogenous lesions that can be visualized through various neuroimaging techniques, such as magnetic resonance imaging (MRI). However, injury burden varies greatly between patients and structural deformations often impact usability of available analytic algorithms. Therefore, it is difficult to segment lesions automatically and accurately in TBI cohorts. Mislabeled lesions will ultimately lead to inaccurate findings regarding imaging biomarkers. Therefore, manual segmentation is currently considered the gold standard as this produces more accurate masks than existing automated algorithms. These masks can provide important lesion phenotype data including location, volume, and intensity, among others. There has been a recent push to investigate the correlation between these characteristics and the onset of post traumatic epilepsy (PTE), a disabling consequence of TBI. One motivation of the Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) is to identify reliable imaging biomarkers of PTE. Here, we report the protocol and importance of our manual segmentation process in patients with moderate-severe TBI enrolled in EpiBioS4Rx. Through these methods, we have generated a dataset of 127 validated lesion segmentation masks for TBI patients. These ground-truths can be used for robust PTE biomarker analyses, including optimization of multimodal MRI analysis via inclusion of lesioned tissue labels. Moreover, our protocol allows for analysis of the refinement process. Though tedious, the methods reported in this work are necessary to create reliable data for effective training of future machine-learning based lesion segmentation methods in TBI patients and subsequent PTE analyses.

Brain Degeneration in Synucleinopathies Based on Analysis of Cognition and Other Nonmotor Features: A Multimodal Imaging Study.

We aimed to characterize subtypes of synucleinopathies using a clustering approach based on cognitive and other nonmotor data and to explore structural and functional magnetic resonance imaging (MRI) brain differences between identified clusters. Sixty-two patients (n = 6 E46K-SNCA, n = 8 dementia with Lewy bodies (DLB) and n = 48 idiopathic Parkinson's disease (PD)) and 37 normal controls underwent nonmotor evaluation with extensive cognitive assessment. Hierarchical cluster analysis (HCA) was performed on patients' samples based on nonmotor variables. T1, diffusion-weighted, and resting-state functional MRI data were acquired. Whole-brain comparisons were performed. HCA revealed two subtypes, the mild subtype (n = 29) and the severe subtype (n = 33). The mild subtype patients were slightly impaired in some nonmotor domains (fatigue, depression, olfaction, and orthostatic hypotension) with no detectable cognitive impairment; the severe subtype patients (PD patients, all DLB, and the symptomatic E46K-SNCA carriers) were severely impaired in motor and nonmotor domains with marked cognitive, visual and bradykinesia alterations. Multimodal MRI analyses suggested that the severe subtype exhibits widespread brain alterations in both structure and function, whereas the mild subtype shows relatively mild disruptions in occipital brain structure and function. These findings support the potential value of incorporating an extensive nonmotor evaluation to characterize specific clinical patterns and brain degeneration patterns of synucleinopathies.

Parkinsonism Is Associated with Altered SMA-Basal Ganglia Structural and Functional Connectivity in Frontotemporal Degeneration.

Patients with frontotemporal degeneration (FTD) often manifest parkinsonism, which likely results from cortical and subcortical degeneration of brain structures involved in motor control. We used a multimodal magnetic resonance imaging (MRI) approach to investigate possible structural and/or functional alterations in FTD patients with and without parkinsonism (Park+ and Park-). Thirty FTD patients (12 Park+, 18 Park-) and 30 healthy controls were enrolled and underwent 3T MRI scanning. MRI analyses included: (1) surface-based morphometry; (2) basal ganglia and thalamic volumetry; (3) diffusion-based probabilistic tractography of fiber tracts connecting the supplementary motor area (SMA) and primary motor cortex (M1) to the putamen, globus pallidus, and thalamus; and (4) resting-state functional connectivity (RSFC) between the aforementioned regions. Patients in Park+ and Park- groups showed comparable patterns of cortical thinning in frontotemporal regions and reduced thalamic volume with respect to controls. Only Park+ patients showed reduced putaminal volume and reduced fractional anisotropy of the fibers connecting the SMA to the globus pallidus, putamen, and thalamus, with respect to controls. Park+ patients also showed decreased RSFC between the SMA and putamen with respect to both Park- patients and controls. The present findings support the hypothesis that FTD patients with parkinsonism are characterized by neurodegenerative processes in specific corticobasal ganglia-thalamocortical motor loops.

Multi-modal MRI measures reveal sensory abnormalities in major depressive disorder patients: A surface-based study

BackgroundMulti-modal magnetic resonance imaging (MRI) measures are supposed to be able to capture different brain neurobiological aspects of major depressive disorder (MDD). A fusion analysis of structural and functional modalities may better reveal the disease biomarker specific to the MDD disease. MethodsWe recruited 30 MDD patients and 30 matched healthy controls (HC). For each subject, we acquired high-resolution brain structural images and resting-state fMRI (rs-fMRI) data using a 3 T MRI scanner. We first extracted the brain morphometric measures, including the cortical volume (CV), cortical thickness (CT), and surface area (SA), for each subject from the structural images, and then detected the structural clusters showing significant between-group differences in each measure using the surface-based morphology (SBM) analysis. By taking the identified structural clusters as seeds, we performed seed-based functional connectivity (FC) analyses to determine the regions with abnormal FC in the patients. Based on a logistic regression model, we performed a classification analysis by selecting these structural and functional cluster-wise measures as features to distinguish the MDD patients from the HC. ResultsThe MDD patients showed significantly lower CV in a cluster involving the right superior temporal gyrus (STG) and middle temporal gyrus (MTG), and lower SA in three clusters involving the bilateral STG, temporal pole gyrus, and entorhinal cortex, and the left inferior temporal gyrus, and fusiform gyrus, than the controls. No significant difference in CT was detected between the two groups. By taking the above-detected clusters as seeds to perform the seed-based FC analysis, we found that the MDD patients showed significantly lower FC between STG/MTG (CV’s cluster) and two clusters located in the bilateral visual cortices than the controls. The logistic regression model based on the structural and functional features reached a classification accuracy of 86.7% (p < 0.001) between MDD and controls. ConclusionThe present study showed sensory abnormalities in MDD patients using the multi-modal MRI analysis. This finding may act as a disease biomarker distinguishing MDD patients from healthy individuals.

Association of Visual Health With Depressive Symptoms and Brain Imaging Phenotypes Among Middle-Aged and Older Adults

Vision loss and depression are common conditions with major health implications. However, mechanisms of the association of visual health (across the full acuity spectrum) with depression remain unclear. To characterize the association between visual health and depression and investigate the association between depression and brain microstructure and macrostructure in subgroups divided by visual acuity. In the UK Biobank Study cohort, 114 583 volunteers were included at baseline from March to June 2006 to July 2010. Habitual distance visual acuity was examined using the logarithm of the minimum angle of resolution (LogMAR) characters. Depression was identified based on Patient Health Questionnaire (PHQ) or through an interview-based psychiatric diagnosis. Subgroup participants completed multimodal magnetic resonance imaging (MRI) of the brain and PHQ evaluation during the imaging visit after 2014. Data were analyzed from May 5 to August 9, 2022. Depression, depressive symptoms, and imaging-derived phenotypes from T1-weighted and diffusion MRI. Of the 114 583 participants from the UK Biobank Study, 62 401 (54.5%) were women, and the mean (SD) age was 56.8 (8.1) years (range, 39-72 years). A 1-line worse visual acuity (0.1 LogMAR increase) was associated with 5% higher odds of depression (odds ratio, 1.05 [95% CI, 1.04-1.07]) after adjustment for age, sex, race and ethnicity, Townsend index, educational qualifications, smoking, alcohol consumption, obesity, physical activity, history of hypertension, diabetes, hyperlipidemia, and family history of depression. Of the 7844 participants eligible for MRI analysis, there were linear associations between PHQ score and the left volume of gray matter in supracalcarine cortex (coefficient, 7.61 [95% CI, 3.90-11.31]) and mean isotropic volume fraction (ISOVF) in the right fornix (cres) and/or stria terminalis (coefficient, 0.003 [95% CI, 0.001-0.004]) after correction for multiple comparison. In addition, their association could be moderated by visual acuity, whereby increased PHQ score was associated with higher ISOVF levels only among those with poorer visual acuity (P = .02 for interaction). This study suggests an association between visual health and depression and that the diffusion characteristic of ISOVF in the fornix (cres) and/or stria terminalis is associated with depressive symptoms in participants with poorer visual acuity.

Effect of Neurorepair for Motor Functional Recovery Enhanced by Total Saponins From Trillium tschonoskii Maxim. Treatment in a Rat Model of Focal Ischemia.

Trillium tschonoskii Maxim. (TTM), is a perennial herb from Liliaceae, that has been widely used as a traditional Chinese medicine treating cephalgia and traumatic hemorrhage. The present work was designed to investigate whether the total saponins from Trillium tschonoskii Maxim. (TSTT) would promote brain remodeling and improve gait impairment in the chronic phase of ischemic stroke. A focal ischemic model of male Sprague-Dawley (SD) rats was established by permanent middle cerebral artery occlusion (MCAO). Six hours later, rats were intragastrically treated with TSTT (120, 60, and 30 mg/kg) and once daily up to day 30. The gait changes were assessed by the CatWalk-automated gait analysis system. The brain tissues injuries, cerebral perfusion and changes of axonal microstructures were detected by multimodal magnetic resonance imaging (MRI), followed by histological examinations. The axonal regeneration related signaling pathways including phosphatidylinositol 3-kinases (PI3K)/protein kinase B (AKT)/glycogen synthase kinase-3 (GSK-3)/collapsin response mediator protein-2 (CRMP-2) were measured by western blotting. TSTT treatment significantly improved gait impairment of rats. MRI analysis revealed that TSTT alleviated tissues injuries, significantly improved cerebral blood flow (CBF), enhanced microstructural integrity of axon and myelin sheath in the ipsilesional sensorimotor cortex and internal capsule. In parallel to MRI findings, TSTT preserved myelinated axons and promoted oligodendrogenesis. Specifically, TSTT interventions markedly up-regulated expression of phosphorylated GSK-3, accompanied by increased expression of phosphorylated PI3K, AKT, but reduced phosphorylated CRMP-2 expression. Taken together, our results suggested that TSTT facilitated brain remodeling. This correlated with improving CBF, encouraging reorganization of axonal microstructure, promoting oligodendrogenesis and activating PI3K/AKT/GSK-3/CRMP-2 signaling, thereby improving poststroke gait impairments.

Prediction of Alzheimer's Disease Progression Based on Magnetic Resonance Imaging.

The neuroimaging method of multimodal magnetic resonance imaging (MRI) can identify the changes in brain structure and function caused by Alzheimer's disease (AD) at different stages, and it is a practical method to study the mechanism of AD progression. This paper reviews the studies of methods and biomarkers for predicting AD progression based on multimodal MRI. First, different approaches for predicting AD progression are analyzed and summarized, including machine learning, deep learning, regression, and other MRI analysis methods. Then, the effective biomarkers of AD progression under structural magnetic resonance imaging, diffusion tensor imaging, functional magnetic resonance imaging, and arterial spin labeling modes of MRI are summarized. It is believed that the brain changes shown on MRI may be related to the cognitive decline in different prodrome stages of AD, which is conducive to the further realization of early intervention and prevention of AD. Finally, the deficiencies of the existing studies are analyzed in terms of data set size, data heterogeneity, processing methods, and research depth. More importantly, future research directions are proposed, including enriching data sets, simplifying biomarkers, utilizing multimodal magnetic resonance, etc. In the future, the study of AD progression by multimodal MRI will still be a challenge but also a significant research hotspot.

Atypical functional connectome hierarchy impacts cognition in temporal lobe epilepsy.

Drug-resistant temporal lobe epilepsy (TLE) is typically associated with hippocampal pathology. However, widespread network alterations are increasingly recognized and suggested to perturb cognitive function in multiple domains. Here we tested (1) whether TLE shows atypical cortical hierarchical organization, differentiating sensory and higher order systems; and (2) whether atypical hierarchy predicts cognitive impairment. We studied 72 well-characterized drug-resistant TLE patients and 41healthy controls, statistically matched for age and sex, using multimodal magnetic resonance imaging analysis and cognitive testing. To model cortical hierarchical organization in vivo, we used a bidirectional stepwise functional connectivity analysis tapping into the differentiation between sensory/unimodal and paralimbic/transmodal cortices. Linear models compared patients to controls. Finally, we assessed associations of functional anomalies to cortical atrophy and microstructural anomalies, as well as clinical and cognitive parameters. Compared to controls, TLE presented with bidirectional disruptions of sensory-paralimbic functional organization. Stepwise connectivity remained segregated within paralimbic and salience networks at the top of the hierarchy, and sensorimotor and dorsal attention at the bottom. Whereas paralimbic segregation was associated with atypical cortical myeloarchitecture and hippocampal atrophy, dysconnectivity of sensorimotor cortices reflected diffuse cortical thinning. The degree of abnormal hierarchical organization in sensory-petal streams covaried, with broad cognitive impairments spanning sensorimotor, attention, fluency, and visuoconstructional ability and memory, and was more marked in patients with longer disease duration and Engel I outcome. Our findings show atypical functional integration between paralimbic/transmodal and sensory/unimodal systems in TLE. Differential associations with paralimbic microstructure and sensorimotor atrophy suggest that system-level imbalance likely reflects complementary structural processes, but ultimately accounts for a broad spectrum of cognitive impairments. Hierarchical contextualization of cognitive deficits promises to open new avenues for personalized counseling in TLE.

A Structure–Function Substrate of Memory for Spatial Configurations in Medial and Lateral Temporal Cortices

Abstract Prior research has shown a role of the medial temporal lobe, particularly the hippocampal–parahippocampal complex, in spatial cognition. Here, we developed a new paradigm, the conformational shift spatial task (CSST), which examines the ability to encode and retrieve spatial relations between unrelated items. This task is short, uses symbolic cues, incorporates two difficulty levels, and can be administered inside the scanner. A cohort of 48 healthy young adults underwent the CSST, together with a set of behavioral measures and multimodal magnetic resonance imaging (MRI). Inter-individual differences in CSST performance correlated with scores on an established spatial memory paradigm, but neither with episodic memory nor mnemonic discrimination, supporting specificity. Analyzing high-resolution structural MRI data, individuals with better spatial memory showed thicker medial and lateral temporal cortices. Functional relevance of these findings was supported by task-based functional MRI analysis in the same participants and ad hoc meta-analysis. Exploratory resting-state functional MRI analyses centered on clusters of morphological effects revealed additional modulation of intrinsic network integration, particularly between lateral and medial temporal structures. Our work presents a novel spatial memory paradigm and supports an integrated structure–function substrate in the human temporal lobe. Task paradigms are programmed in python and made open access.

Monitoring Value of Multimodal Magnetic Resonance Imaging in Disease Progression of Amyotrophic Lateral Sclerosis: A Prospective Observational Study.

Background:Ongoing efforts have been made to identify new neuroimaging markers to track amyotrophic lateral sclerosis (ALS) progression. This study aimed to explore the monitoring value of multimodal magnetic resonance imaging (MRI) in the disease progression of ALS.Methods:From September 2015 to March 2017, ten patients diagnosed with ALS in Peking Union Medical College Hospital completed head MRI scans at baseline and during follow-up. Multimodal MRI analyses, including gray matter (GM) volume measured by voxel-based morphometry; cerebral blood flow (CBF) evaluated by arterial spin labeling; functional connectivity, including low-frequency fluctuation (fALFF) and regional homogeneity (ReHo), measured by resting-state functional MRI; and integrity of white-matter (WM) fiber tracts evaluated by diffusion tensor imaging, were performed in these patients. Comparisons of imaging metrics were made between baseline and follow-up using paired t-test.Results:In the longitudinal comparisons, the brain structure (GM volume of the right precentral gyri, left postcentral gyri, and right thalami) and perfusion (CBF of the bilateral temporal poles, left precentral gyri, postcentral gyri, and right middle temporal gyri) in both motor and extramotor areas at follow-up were impaired to different extents when compared with those at baseline (all P < 0.05, false discovery rate adjusted). Functional connectivity was increased in the motor areas (fALFF of the right precentral gyri and superior frontal gyri, and ReHo of right precentral gyri) and decreased in the extramotor areas (fALFF of the bilateral middle frontal gyri and ReHo of the right precuneus and cingulate gyri) (all P < 0.001, unadjusted). No significant changes were detected in terms of brain WM measures.Conclusion:Multimodal MRI could be used to monitor short-term brain changes in ALS patients.

A Novel Multimodal MRI Analysis for Alzheimer's Disease Based on Convolutional Neural Network.

Recent years, Alzheimer's disease (AD) has become a significant threat to human health while the accurate screening and diagnosis of AD remain a tough problem. Multimodal Magnetic resonance imaging (MRI) can help to identify the variation of brain function and structure in a non-invasive way. Deep learning, especially the convolutional neural networks (CNN), can be utilized to automatically detect appropriate features for classification, which is well adapted for computer-aided AD screening and identification. This paper proposed a multimodal MRI analytical method based on CNN, which is also suitable for single type MRI data analysis. First, the human brain network connectivity matrix were extracted from multimodal MRI data, used as the input data for CNN. Then a novel CNN framework was proposed to process the network matrix and classify AD, amnestic mild cognitive impairment (aMCI) patients and normal controls (NC). The advantage of this method lies in that we combined multimodal MRI information through CNN convolution kernel, and achieved a higher classification accuracy. In our experiments, the comprehensive classification accuracy of AD, aMCI patients and NC was as high as 92.06% when using multimodal MRI data as input, which is effective enough to provide a reference for multimodal MRI data analysis.

Structural and functional abnormalities of the insular cortex in trigeminal neuralgia: a multimodal magnetic resonance imaging analysis.

Trigeminal neuralgia (TN) is a chronic neuropathic pain disorder characterized by intense, lancinating attacks of facial pain. Increasing evidence suggests that TN is accompanied by abnormalities in brain morphology, white matter microstructure, and function. However, whether these abnormalities are linked or reflect independent etiologies remains unknown. Using multimodal magnetic resonance imaging data of 20 patients with TN and 21 healthy controls, we investigated cortical gyrification abnormalities, their relationships with abnormalities of the underlying white matter microstructure and gray matter morphology, as well as their functional significance in TN. Compared with controls, patients with TN showed significant local gyrification index (LGI) reductions predominantly in the left insular cortex, which were negatively correlated with pain intensity. In this cluster, patients with TN had concurrent cortical thickness reductions but unaltered cortical surface area. Meanwhile, LGI of this cluster was not correlated with overlying cortical thickness or surface area but was positively correlated with the fractional anisotropy of 2 nearby white matter clusters, suggesting that insular LGI reductions may be primarily driven by microstructural abnormalities of the underlying white matter tracts, rather than by abnormalities in cortical thickness and surface area. In addition, patients with TN exhibited increased insula functional connectivity to the left posterior cingulate cortex and thalamus, which was positively correlated with disease duration. These findings provide new evidence for the involvement of insular abnormalities in the pathophysiology of TN.

Neural Reorganization Due to Neonatal Amygdala Lesions in the Rhesus Monkey: Changes in Morphology and Network Structure.

It is generally believed that neural damage that occurs early in development is associated with greater adaptive capacity relative to similar damage in an older individual. However, few studies have surveyed whole brain changes following early focal damage. In this report, we employed multimodal magnetic resonance imaging analyses of adult rhesus macaque monkeys who had previously undergone bilateral, neurotoxic lesions of the amygdala at about 2 weeks of age. A deformation-based morphometric approach demonstrated reduction of the volumes of the anterior temporal lobe, anterior commissure, basal ganglia, and pulvinar in animals with early amygdala lesions compared to controls. In contrast, animals with early amygdala lesions had an enlarged cingulate cortex, medial superior frontal gyrus, and medial parietal cortex. Diffusion-weighted imaging tractography and network analysis were also used to compare connectivity patterns and higher-level measures of communication across the brain. Using the communicability metric, which integrates direct and indirect paths between regions, lesioned animals showed extensive degradation of network integrity in the temporal and orbitofrontal cortices. This work demonstrates both degenerative as well as progressive large-scale neural changes following long-term recovery from neonatal focal brain damage.

Multimodal MRI Analysis of the Corpus Callosum Reveals White Matter Differences in Presymptomatic and Early Huntington's Disease

Recent magnetic resonance imaging (MRI) studies suggest that abnormalities in Huntington's disease (HD) extend to white matter (WM) tracts in early HD and even in presymptomatic stages. Thus, changes of the corpus callosum (CC) may reflect various aspects of HD pathogenesis. We recruited 17 HD patients, 17 pre-HD subjects, and 34 healthy age-matched controls. Three-dimensional anatomical MRI and diffusion tensor images of the brain were acquired on a 3T scanner. Combining region-of-interest analyses, voxel-based morphometry, and tract-based spatial statistics, we investigated callosal thickness, WM density, fractional anisotropy, and radial and axial diffusivities. Compared with controls, pre-HD subjects showed reductions of the isthmus, likely due to myelin damage. Compared with pre-HD subjects, HD patients showed reductions of isthmus and body, with axonal damage confined to the body. Compared with controls, HD patients had significantly decreased callosal measures in extended regions across almost the entire CC. At this disease stage, both myelin and axonal damage are detectable. Supplementary multiple regression analyses revealed that WM reduction density in the isthmus as well as Disease Burden scores allowed to predict the "HD development" index. While callosal changes seem to proceed in a posterior-to-anterior direction as the diseases progresses, this observation requires validation in future longitudinal investigations.

Human brain atlas-based multimodal MRI analysis of volumetry, diffusimetry, relaxometry and lesion distribution in multiple sclerosis patients and healthy adult controls: Implications for understanding the pathogenesis of multiple sclerosis and consolidation of quantitative MRI results in MS

Multiple sclerosis (MS) is the most common immune-mediated disabling neurological disease of the central nervous system. The pathogenesis of MS is not fully understood. Histopathology implicates both demyelination and axonal degeneration as the major contributors to the accumulation of disability. The application of several in vivo quantitative magnetic resonance imaging (MRI) methods to both lesioned and normal-appearing brain tissue has not yet provided a solid conclusive support of the hypothesis that MS might be a diffuse disease. In this work, we adopted FreeSurfer to provide standardized macrostructure or volumetry of lesion free normal-appearing brain tissue in combination with multiple quantitative MRI metrics (T 2 relaxation time, diffusion tensor anisotropy and diffusivities) that characterize tissue microstructural integrity. By incorporating a large number of healthy controls, we have attempted to separate the natural age-related change from the disease-induced effects. Our work shows elevation in diffusivity and relaxation times and reduction in volume in a number of normal-appearing white matter and gray matter structures in relapsing–remitting multiple sclerosis patients. These changes were related in part with the spatial distribution of lesions. The whole brain lesion load and age-adjusted expanded disability status score showed strongest correlations in regions such as corpus callosum with qMRI metrics that are believed to be specific markers of axonal dysfunction, consistent with histologic data of others indicating axonal loss that is independent of focal lesions. Our results support that MS at least in part has a neurodegenerative component.