Cortical Thickness Analysis Research Articles

Cerebral cortical thinning in brain regions involved in emotional regulation relates to persistent symptoms in subjects with posttraumatic stress disorder

A considerable proportion of individuals exposed to trauma experience chronic and persistent posttraumatic stress disorder (PTSD). However, the specific brain and clinical features that render trauma-exposed individuals more susceptible to enduring symptoms remain elusive. This study investigated 112 trauma-exposed participants who had been diagnosed with PTSD and 112 demographically-matched healthy controls. Trauma-exposed participants were classified into those with current PTSD (persistent PTSD, n = 78) and those without (remitted PTSD, n = 34). Cortical thickness analysis was performed to discern group-specific brain structural characteristics. Coping strategies and resilience levels, assessed as clinical attributes, were compared across the groups. The persistent PTSD group displayed cortical thinning in the superior frontal cortex (SFC), insula, superior temporal cortex, dorsolateral prefrontal cortex, superior parietal cortex, and precuneus, relative to the remitted PTSD and control groups. Cortical thinning in the SFC was associated with increased utilization of maladaptive coping strategies, while diminished thickness in the insula correlated with lower resilience levels among trauma-exposed individuals. These findings imply that cortical thinning in brain regions related to coping strategy and resilience plays a vital role in the persistence of PTSD symptoms.

Correlation between immune-related genes and depression-like features in an animal model and in humans

A growing body of evidence suggests that immune-related genes play pivotal roles in the pathophysiology of depression. In the present study, we investigated a plausible connection between gene expression, DNA methylation, and brain structural changes in the pathophysiology of depression using a combined approach of murine and human studies. We ranked the immobility behaviors of 30 outbred Crl:CD1 (ICR) mice in the forced swim test (FST) and harvested their prefrontal cortices for RNA sequencing. Of the 24,532 analyzed genes, 141 showed significant correlations with FST immobility time, as determined through linear regression analysis with p ≤ 0.01. The identified genes were mostly involved in immune responses, especially interferon signaling pathways. Moreover, induction of virus-like neuroinflammation in the brains of two separate mouse cohorts (n = 30 each) using intracerebroventricular polyinosinic:polycytidylic acid injection resulted in increased immobility during FST and similar expression of top immobility-correlated genes. In human blood samples, candidate gene (top 5%) expression profiling using DNA methylation analysis found the interferon-related USP18 (cg25484698, p = 7.04 × 10−11, Δβ = 1.57 × 10–2; cg02518889, p = 2.92 × 10−3, Δβ = − 8.20 × 10–3) and IFI44 (cg07107453, p = 3.76 × 10–3, Δβ = − 4.94 × 10–3) genes to be differentially methylated between patients with major depressive disorder (n = 350) and healthy controls (n = 161). Furthermore, cortical thickness analyses using T1-weighted images revealed that the DNA methylation scores for USP18 were negatively correlated with the thicknesses of several cortical regions, including the prefrontal cortex. Our results reveal the important role of the interferon pathway in depression and suggest USP18 as a potential candidate target. The results of the correlation analysis between transcriptomic data and animal behavior carried out in this study provide insights that could enhance our understanding of depression in humans.

Presymptomatic grey matter alterations in ALS kindreds: a computational neuroimaging study of asymptomatic C9orf72 and SOD1 mutation carriers

BackgroundThe characterisation of presymptomatic disease-burden patterns in asymptomatic mutation carriers has a dual academic and clinical relevance. The understanding of disease propagation mechanisms is of considerable conceptual interests, and defining the optimal time of pharmacological intervention is essential for improved clinical trial outcomes.MethodsIn a prospective, multimodal neuroimaging study, 22 asymptomatic C9orf72 GGGGCC hexanucleotide repeat carriers, 13 asymptomatic subjects with SOD1, and 54 “gene-negative” ALS kindreds were enrolled. Cortical and subcortical grey matter alterations were systematically appraised using volumetric, morphometric, vertex, and cortical thickness analyses. Using a Bayesian approach, the thalamus and amygdala were further parcellated into specific nuclei and the hippocampus was segmented into anatomically defined subfields.ResultsAsymptomatic GGGGCC hexanucleotide repeat carriers in C9orf72 exhibited early subcortical changes with the preferential involvement of the pulvinar and mediodorsal regions of the thalamus, as well as the lateral aspect of the hippocampus. Volumetric approaches, morphometric methods, and vertex analyses were anatomically consistent in capturing focal subcortical changes in asymptomatic C9orf72 hexanucleotide repeat expansion carriers. SOD1 mutation carriers did not exhibit significant subcortical grey matter alterations. In our study, none of the two asymptomatic cohorts exhibited cortical grey matter alterations on either cortical thickness or morphometric analyses.DiscussionThe presymptomatic radiological signature of C9orf72 is associated with selective thalamic and focal hippocampal degeneration which may be readily detectable before cortical grey matter changes ensue. Our findings confirm selective subcortical grey matter involvement early in the course of C9orf72-associated neurodegeneration.

Altered microstructure of the contralesional ventral premotor cortex and motor output after stroke.

Cortical thickness analyses have provided valuable insights into changes in cortical brain structure after stroke and their association with recovery. Across studies though, relationships between cortical structure and function show inconsistent results. Recent developments in diffusion-weighted imaging of the cortex have paved the way to uncover hidden aspects of stroke-related alterations in cortical microstructure, going beyond cortical thickness as a surrogate for cortical macrostructure. We re-analysed clinical and imaging data of 42 well-recovered chronic stroke patients from 2 independent cohorts (mean age 64 years, 4 left-handed, 71% male, 16 right-sided strokes) and 33 healthy controls of similar age and gender. Cortical fractional anisotropy and cortical thickness values were obtained for six key sensorimotor areas of the contralesional hemisphere. The regions included the primary motor cortex, dorsal and ventral premotor cortex, supplementary and pre-supplementary motor areas, and primary somatosensory cortex. Linear models were estimated for group comparisons between patients and controls and for correlations between cortical fractional anisotropy and cortical thickness and clinical scores. Compared with controls, stroke patients exhibited a reduction in fractional anisotropy in the contralesional ventral premotor cortex (P = 0.005). Fractional anisotropy of the other regions and cortical thickness did not show a comparable group difference. Higher fractional anisotropy of the ventral premotor cortex, but not cortical thickness, was positively associated with residual grip force in the stroke patients. These data provide novel evidence that the contralesional ventral premotor cortex might constitute a key sensorimotor area particularly susceptible to stroke-related alterations in cortical microstructure as measured by diffusion MRI and they suggest a link between these changes and residual motor output after stroke.

Adolescent brain development in girls with Turner syndrome.

Turner syndrome (TS) is a common sex chromosome aneuploidy in females associated with various physical, cognitive, and socio-emotional phenotypes. However, few studies have examined TS-associated alterations in the development of cortical gray matter volume and the two components that comprise this measure-surface area and thickness. Moreover, the longitudinal direct (i.e., genetic) and indirect (i.e., hormonal) effects of X-monosomy on the brain are unclear. Brain structure was assessed in 61 girls with TS (11.3 ± 2.8 years) and 55 typically developing girls (10.8 ± 2.3 years) for up to 4 timepoints. Surface-based analyses of cortical gray matter volume, thickness, and surface area were conducted to examine the direct effects of X-monosomy present before pubertal onset and indirect hormonal effects of estrogen deficiency/X-monosomy emerging after pubertal onset. Longitudinal analyses revealed that, whereas typically developing girls exhibited normative declines in gray matter structure during adolescence, this pattern was reduced or inverted in TS. Further, girls with TS demonstrated smaller total surface area and larger average cortical thickness overall. Regionally, the TS group exhibited decreased volume and surface area in the pericalcarine, postcentral, and parietal regions relative to typically developing girls, as well as larger volume in the caudate, amygdala, and temporal lobe regions and increased thickness in parietal and temporal regions. Surface area alterations were predominant by age 8, while maturational differences in thickness emerged by age 10 or later. Taken together, these results suggest the involvement of both direct and indirect effects of X-chromosome haploinsufficiency on brain development in TS.

Changes in motor activity level in individuals with frontotemporal dementia.

Changes in motor activity are common in individuals with Frontotemporal dementia (FTD). Yet, it remains unclear why some individuals become motorically hyperactive, while others hypoactive even in early stages of the disease. This study aimed to examine the relationship between motor activity level and (1) FTD clinical subtype, and (2) cortical thickness and subcortical volumes. Eighty-two charts were retrospectively reviewed from patients meeting consensus criteria for one of the three main clinical subtypes of FTD: probable bvFTD, semantic variant Primary Progressive Aphasia (PPA), or non-fluent variant PPA. Participants were assigned to one of three groups: (1) hyperactive, (2) hypoactive, or (3) no record of change. Hyperactivity was prevalent among bvFTD (58.5%) and semantic PPA (68.8%) subtypes while hypoactivity was less common in both subtypes (29.3% and 18.8%, respectively). The majority of patients with non-fluent PPA showed no record of change in motor activity (66.7%). The analysis of cortical thickness and subcortical volumes did not identify significant associations with motor activity levels. In conclusion, increased motor activity is highly prevalent among individuals with FTD, especially bvFTD and svPPA subtypes. These findings may inform prognosis and prediction of changes in motor activity, and allow planning for appropriate environmental and behavioural interventions. Future studies with prospective, standardized longitudinal collection of information regarding the type and level of change in motor activity, including wearable measures of actigraphy, may help to further delineate the onset and progression of abnormal motor behaviours and determine neuroanatomic associations in FTD.

Effect of geometric distortion correction on thickness and volume measurements of cortical parcellations in 3D T1w gradient echo sequences.

Automated brain volumetric analysis based on high-resolution T1-weighted MRI datasets is a frequently used tool in neuroimaging for early detection, diagnosis, and monitoring of various neurological diseases. However, image distortions can corrupt and bias the analysis. The aim of this study was to explore the variability of brain volumetric analysis due to gradient distortions and to investigate the effect of distortion correction methods implemented on commercial scanners. 36 healthy volunteers underwent brain imaging using a 3T magnetic resonance imaging (MRI) scanner, including a high-resolution 3D T1-weighted sequence. For all participants, each T1-weighted image was reconstructed directly on the vendor workstation with (DC) and without (nDC) distortion correction. For each participant's set of DC and nDC images, FreeSurfer was used for the determination of regional cortical thickness and volume. Overall, significant differences were found in 12 cortical ROIs comparing the volumes of the DC and nDC data and in 19 cortical ROIs comparing the thickness of the DC and nDC data. The most pronounced differences for cortical thickness were found in the precentral gyrus, the lateral occipital and postcentral ROI (2.69, -2.91% and -2.79%, respectively) while cortical volumes differed most prominently in the paracentral, the pericalcarine and lateral occipital ROI (5.52%, -5.40% and -5.11%, respectively). Correcting for gradient non-linearities can have significant influence on volumetric analysis of cortical thickness and volume. Since the distortion correction is an automatic feature of the MR scanner, it should be stated by each study that applies volumetric analysis which images were used.

320 Deep-Learning Cortical Thickness Analysis as Predictor for Shunt Surgery Effectiveness in Possible iNPH Patients

INTRODUCTION: While optimal treatment for iNPH is quite known, diagnosis remains a topic of debate, with different procedures suggested as potential predictors for shunt surgery effectiveness. Various tests, biomarkers, and neuroimaging techniques can be used; however, the diagnostic accuracy is below optimal when performed with neuroimaging techniques alone and not always cost-effective when achieved with CSF biomarkers. Quantitative computational methods for cortical thickness analysis have become available in the last decade, and they only require regularly available T1-weighted brain MR images. METHODS: We analyzed 294 total patients referred to our clinic from January 2015 until December 2021. After exclusion criteria, the final sample consisted of 98 possible iNPH patients: 64 were diagnosed as probable iNPH and underwent VPS surgery, while 34 did not receive a surgical indication after diagnostic procedures. We investigated differences in cortical thickness for all possible iNPH patients using a public deep-learning based neuroimaging pipeline composed by an advanced semantic segmentation neural network architecture and automated surface-based cortical thickness analysis. RESULTS: In 38 total patients with a negative CSFTT or not responsive to shunt surgery, a significant localized cortical thinning was seen in the lateral surface of the frontal and parietal lobes (bilateral superior and middle frontal gyrus, bilateral pars opercularis, bilateral superior parietal gyrus, bilateral supramarginal gyrus, left inferior parietal gyrus, bilateral precuneus). CONCLUSIONS: Preoperative cortical thickness is a feasible analysis that might be useful in defining the optimal therapeutic plan for possible iNPH patients. A large multicentric study is encouraged to elucidate specific patterns and ratios of cortical thickness that might be used as potential predictors for shunt surgery effectiveness.

Not a benign motor neuron disease: longitudinal imaging captures relentless motor connectome disintegration in primary lateral sclerosis.

Primary lateral sclerosis (PLS) is a progressive upper motor neuron disorder associated with considerable clinical disability. Symptoms are typically exclusively linked to primary motor cortex degeneration and the contribution of pre-motor, supplementary motor, cortico-medullary and inter-hemispheric connectivity alterations are less well characterized. In a single-centre, prospective, longitudinal neuroimaging study 41 patients with PLS were investigated. Patients underwent standardized neuroimaging, genetic profiling with whole exome sequencing, and comprehensive clinical assessments including upper motor neuron scores, tapping rates, mirror movements, spasticity assessment, cognitive screening and evaluation for pseudobulbar affect. Longitudinal neuroimaging data from 108 healthy controls were used for image interpretation. A standardized imaging protocol was implemented including 3D T1-weighted structural, diffusion tensor imaging and resting-state functional magnetic resonance imaging. Following somatotopic segmentation, cortical thickness analyses, probabilistic tractography, blood oxygenation level dependent signal analyses and brainstem volumetry were conducted to evaluate cortical, brainstem, cortico-medullary and inter-hemispheric connectivity alterations both cross-sectionally and longitudinally. Our data confirm progressive primary motor cortex degeneration, considerable supplementary motor and pre-motor area involvement, progressive brainstem atrophy, cortico-medullary and inter-hemispheric disconnection, and close associations between clinical upper motor neuron scores and somatotopic connectivity indices in PLS. Primary lateral sclerosis is associated with relentlessly progressive motor connectome degeneration. Clinical disability in PLS is likely to stem from a combination of intra- and inter-hemispheric connectivity decline and primary, pre- and supplementary motor cortex degeneration. Simple 'bedside' clinical tools, such as tapping rates, are excellent proxies of the integrity of the relevant fibres of the contralateral corticospinal tract.

Bilingualism and creativity across development: Evidence from divergent thinking and convergent thinking.

Numerous studies have demonstrated the benefits of creativity from bilingualism. Divergent thinking and convergent thinking are considered the two most important components of creativity. Various (although not all) studies have concluded that bilingual children outperform monolingual children in divergent thinking, however, no study on children or adolescents so far has explored the relation between bilingualism and convergent thinking, or the brain structural basis of interaction between bilingualism and creativity. This study aimed to explore the impact of bilingualism on both convergent and divergent thinking in children and adolescents based on neuropsychological assessments, and the possible structural basis of the effect of bilingualism on creativity by a whole-brain analysis of regional gray matter volume (rGMV) and cortical thickness in children and adolescents. 92 healthy children and adolescents of age 4-18 were recruited from public or private schools in the French-speaking side of Switzerland. Demographic data of the participants were collected, including gender, age, pedagogy, usage of language, and parents' socioeconomic status. Most of the participants underwent the neuropsychological assessments of divergent thinking, convergent thinking, and fluid intelligence. Structural image data of 75 participants were analyzed. Both voxel-based morphometry (VBM) and surface-based morphometry (SBM) were processed, to perform the analyses of rGMV and cortical thickness respectively. The outcomes indicated that convergent thinking, but not divergent thinking benefits from bilingualism in children and adolescents. However, this bilingual advantage appears to weaken across development. Unexpectedly, no significant correlation between morphometry and bilingualism was found. Neither divergent thinking scores nor convergent thinking scores showed any significant correlation with rGMV. However, the whole brain SBM showed that the cortical thickness in the right supplementary motor area (SMA) was negatively correlated with convergent thinking scores, which suggested that the children and adolescents with higher convergent thinking abilities may have thinner, more mature, and more activated cortex in the right SMA. Bilingualism and cortical thinness in the right SMA might facilitate convergent thinking independently, by enhancing this selective ability.

Mild behavioral impairment linked to progression to Alzheimer's disease and cortical thinning in amnestic mild cognitive impairment.

Mild behavioral impairment (MBI) is a neurobehavioral syndrome characterized by later life emergence of sustained neuropsychiatric symptoms, as an at-risk state for dementia. However, the associations between MBI and a risk of progression to Alzheimer's disease (AD) and its neuroanatomical correlates in mild cognitive impairment (MCI) are still unclear. A total 1,184 older adults with amnestic MCI was followed for a mean of 3.1 ± 2.0 years. MBI was approximated using a transformation algorithm for the Neuropsychiatric Inventory at baseline. A two-step cluster analysis was used to identify subgroups of individuals with amnestic MCI based on profiles of 5 MBI domain symptoms (decreased motivation, affective dysregulation, impulse dyscontrol, social inappropriateness, abnormal perception/thought content). A Cox regression analysis was applied to investigate differences in the risk of progression to AD between subgroups. A subset of participants (n = 202) underwent 3D T1-weighted MRI scans at baseline and cortical thickness was compared between the subgroups of amnestic MCI patients. The cluster analysis classified the patients into 3 groups: (1) patients without any MBI domain symptoms (47.4%, asymptomatic group); (2) those with only affective dysregulation (29.4%, affective dysregulation group); (3) those with multiple MBI domain symptoms, particularly affective dysregulation, decreased motivation and impulse dyscontrol (23.2%, complex group). Compared to the asymptomatic group, the complex group was associated with a higher risk of progression to AD (hazard ratio = 2.541 [1.904-3.392], p < 0.001), but the affective dysregulation group was not (1.214 [0.883-1.670], p = 0.232). In cortical thickness analysis, the complex group revealed cortical thinning bilaterally in the inferior parietal, lateral occipital, lateral superior temporal, and frontopolar regions compared with the affective dysregulation group. The multiple co-occuring MBI domains in individuals with amnestic MCI are associated with a higher risk of progression to AD and cortical thinning in temporal, parietal and frontal areas. These results suggest that evaluation of MBI could be useful for risk stratification for AD and appropriate intervention in MCI individuals.

Cortical Thickness and Brain Glucose Metabolism in Healthy Aging.

We aimed to determine the effect of demographic factors on cortical thickness and brain glucose metabolism in healthy aging subjects. The following tests were performed on 71 subjects with normal cognition: neurological examination, 3-tesla magnetic resonance imaging, 18F-fluorodeoxyglucose positron-emission tomography, and neuropsychological tests. Cortical thickness and brain metabolism were measured using vertex- and voxelwise analyses, respectively. General linear models (GLMs) were used to determine the effects of age, sex, and education on cortical thickness and brain glucose metabolism. The effects of mean lobar cortical thickness and mean lobar metabolism on neuropsychological test scores were evaluated using GLMs after controlling for age, sex, and education. The intracranial volume (ICV) was further included as a predictor or covariate for the cortical thickness analyses. Age was negatively correlated with the mean cortical thickness in all lobes (frontal and parietal lobes, p=0.001; temporal and occipital lobes, p<0.001) and with the mean temporal metabolism (p=0.005). Education was not associated with cortical thickness or brain metabolism in any lobe. Male subjects had a lower mean parietal metabolism than did female subjects (p<0.001), while their mean cortical thicknesses were comparable. ICV was positively correlated with mean cortical thickness in the frontal (p=0.016), temporal (p=0.009), and occipital (p=0.007) lobes. The mean lobar cortical thickness was not associated with cognition scores, while the mean temporal metabolism was positively correlated with verbal memory test scores. Age and sex affect cortical thickness and brain glucose metabolism in different ways. Demographic factors must therefore be considered in analyses of cortical thickness and brain metabolism.

Evolution of gliding in squirrel-related rodents (Mammalia: Sciuromorpha) did not induce a new optimum on the cortical thickness of the scapular glenoid fossa.

Many of the squirrel-related rodents (i.e., Sciuromorpha) are tree-dwelling species known to be very agile climbers. This taxon also includes the most diverse clade of gliding (aerial) mammals that likely descended from a non-gliding arboreal ancestor and evolved a patagium (i.e., a gliding membrane) to increase gliding performance. Glides can cover distances of up to 150 m and landing is typically accomplished by stalling the patagium to reduce impact velocity. It remains unclear if this behavior suffices to keep stresses on the locomotor apparatus similar to those experienced by their arboreal relatives or whether gliding behavior increases landing forces and stresses. The sparsely available support reaction force data are ambiguous, but bone microstructure is highly adaptable to changes in loading regime and likely provides insights into this question. Using μCT scans, we compared the cortical thickness of the glenoid fossa of the shoulder joint between arboreal and aerial Sciuromorpha using evolutionary model comparison, while also accounting for regional differences of the glenoid fossa. We did not find any differences between these locomotor behaviors, irrespective of the glenoid region. These findings agree with previous analyses of the microstructure of the femur in Sciuromorpha. We discuss different aspects that could explain the similarity in cortical thickness. According to our analysis of glenoid cortical thickness the loading regime appears not to have changed after the evolution of gliding locomotion, likely due to adjustments in landing performance.

Cortical thickness analysis in temporal lobe epilepsy using fully Bayesian spectral method in magnetic resonance imaging

BackgroundTemporal lobe epilepsy (TLE) is the most common type of epilepsy associated with changes in the cerebral cortex throughout the brain. Magnetic resonance imaging (MRI) is widely used for detecting such anomalies; nevertheless, it produces spatially correlated data that cannot be considered by the usual statistical models. This study aimed to compare cortical thicknesses between patients with TLE and healthy controls by considering the spatial dependencies across different regions of the cerebral cortex in MRI.MethodsIn this study, T1-weighted MRI was performed on 20 healthy controls and 33 TLE patients. Nineteen patients had a left TLE and 14 had a right TLE. Cortical thickness was measured for all individuals in 68 regions of the cerebral cortex based on images. Fully Bayesian spectral method was utilized to compare the cortical thickness of different brain regions between groups. Neural networks model was used to classify the patients using the identified regions.ResultsFor the left TLE patients, cortical thinning was observed in bilateral caudal anterior cingulate, lateral orbitofrontal (ipsilateral), the bilateral rostral anterior cingulate, frontal pole and temporal pole (ipsilateral), caudal middle frontal and rostral middle frontal (contralateral side). For the right TLE patients, cortical thinning was only observed in the entorhinal area (ipsilateral). The AUCs of the neural networks for classification of left and right TLE patients versus healthy controls were 0.939 and 1.000, respectively.ConclusionAlteration of cortical gray matter thickness was evidenced as common effect of epileptogenicity, as manifested by the patients in this study using the fully Bayesian spectral method by taking into account the complex structure of the data.

Deep learning pipeline for cortical gray matter segmentation and thickness analysis in Ultra High Resolution T2w 7 Tesla Ex vivo MRI across neurodegenerative diseases reveals associations with underlying neuropathology

AbstractBackgroundEx vivo magnetic resonance imaging (MRI) enables detailed characterization of neuroanatomy (Augustinack et al. 2013), such as hippocampal subfields in the medial temporal lobe (MTL) (Yushkevich et al. 2021, Ravikumar et al. 2021). However, automated cortical segmentation methods in ex vivo MRI are not well developed due to limited data availability and heterogeneity in scanners and acquisition. Here, we investigate a deep learning framework to parcellate the cortical mantle, compute thickness and link them with neuropathology ratings across 16 cortical regions in 7 Tesla MRIs of 38 ex vivo brain specimens spanning Alzheimer Disease and Related Dementias.MethodA deep learning method, nnU‐Net (Isensee et al. 2021), was trained on manually segmented 3D image patches (Figure 1C) to obtain automated cortical segmentations across 38 subjects (Table 1). We identified 16 landmarks (Figure 1A) for localized quantitative signatures of cortical morphometry and used the pipeline in Wisse et al. 2021 to measure local thickness (Figure 1B). Associations were computed between cortical thickness from manual and automated segmentations via Pearson’s correlation and average fixed‐raters Intra‐class Correlation Coefficient (ICC) for 16 locations (Figure 3). We also correlated thickness from both automated and manual segmentations with neuropathological ratings of tau and neuronal loss in corresponding contralateral regions and global Braak staging (Figures 4 and 5).ResultFigure 2 depicts cortical mantle segmentation across brain hemispheres. Figure 3 shows good agreement between ground truth and automated thickness, with 15 regions with significant associations (p&lt;0.05) and 8 regions having r&gt;0.6. We observe high ICC scores with 9 regions where ICC&gt;0.7, confirming that automated segmentations accurately measure thickness. Figure 4 shows significant correlations between thickness and Tau ratings for Brodmann Area 35 (BA35) and midfrontal regions and trends between neuronal loss and thickness in entorhinal cortex (ERC), anterior temporal pole and anterior insula. Figure 5 shows significant correlations between thickness and Braak staging in ventrolateral temporal cortex and ERC, with trends in other regions.ConclusionOur automated ex vivo neuroimaging framework accurately segments the cortical mantle, provides thickness measurements that concur with user‐supervised thickness and links morphometry with underlying neurodegeneration, thus suggesting the strengths of ex vivo MRI.

The pattern of cortical thickness underlying disruptive behaviors in Alzheimer's disease.

Disruptive behaviors, including agitation, disinhibition, irritability, and aberrant motor behaviors, are commonly observed in patients with Alzheimer's disease (AD). However, the neuroanatomical basis of these disruptive behaviors is not fully understood. To confirm the differences in cortical thickness and surface area between AD patients and healthy controls and to further investigate the features of cortical thickness and surface area associated with disruptive behaviors in patients with AD. One hundred seventy-four participants (125 AD patients and 49 healthy controls) were recruited from memory clinics at the Peking University Institute of Sixth Hospital. Disruptive behaviors, including agitation/aggression, disinhibition, irritability/lability, and aberrant motor activity subdomain scores, were evaluated using the Neuropsychiatry Inventory. Both whole-brain vertex-based and region-of-interest-based cortical thickness and surface area analyses were automatically conducted with the CIVET pipeline based on structural magnetic resonance images. Both group-based statistical comparisons and brain-behavior association analyses were performed using general linear models, with age, sex, and education level as covariables. Compared with healthy controls, the AD patients exhibited widespread reduced cortical thickness, with the most significant thinning located in the medial and lateral temporal and parietal cortex, and smaller surface areas in the left fusiform and left inferior temporal gyrus. High total scores of disruptive behaviors were significantly associated with cortical thinning in several regions that are involved in sensorimotor processing, language, and expression functions. The total score of disruptive behaviors did not show significant associations with surface areas. We highlight that disruptive behaviors in patients with AD are selectively associated with cortical thickness abnormalities in sensory, motor, and language regions, which provides insights into neuroanatomical substrates underlying disruptive behaviors. These findings could lead to sensory, motor, and communication interventions for alleviating disruptive behaviors in patients with AD.

Hypometabolic and hypermetabolic brain regions in patients with ALS-FTD show distinct patterns of grey and white matter degeneration: A pilot multimodal neuroimaging study

BackgroundUp to 50% of amyotrophic lateral sclerosis (ALS) patients develop some degree of cognitive dysfunction and a small proportion of these develop frontotemporal dementia (FTD). Non-invasive techniques of magnetic resonance imaging (MRI) and [18F]-fluoro-2-deoxy-d-glucose (18F-FDG) positron emission tomography (PET) have demonstrated structural and metabolic abnormalities, respectively, in the brains of such patients with ALS-FTD. Although initial 18F-FDG PET studies in ALS patients showed only hypometabolism of motor and extramotor brain regions, subsequent studies have demonstrated hypermetabolic changes as well. Such contrasting findings prompted us to hypothesize that hypo- and hypermetabolic brain regions in ALS-FTD patients are associated with divergent degeneration of structural grey matter (GM) and white matter (WM). MethodsCerebral glucose metabolic rate (CMRglc), cortical thickness (CT), fractal dimension (FD), and graph theory WM network analyses were performed on clinical MRI and 18F-FDG PET images from 8 ALS-FTD patients and 14 neurologic controls to explore the relationship between GM-WM degeneration and hypo- and hypermetabolic brain regions. ResultsCMRglc revealed significant hypometabolism in frontal and precentral gyrus brain regions, with hypermetabolism in temporal, occipital and cerebellar regions. Cortical thinning was noted in both hypo- and hypermetabolic brain areas. Unlike CT, FD did not reveal widespread GM degeneration in hypo- and hypermetabolic brain regions of ALS-FTD patients. Graph theory analysis showed severe WM degeneration in hypometabolic but not hypermetabolic areas, especially in the right hemisphere. ConclusionOur multimodal MRI-PET study provides insights into potentially differential pathophysiological mechanisms between hypo- and hypermetabolic brain regions of ALS-FTD patients.

Corticobasal syndrome and Parkinson’s disease at the beginning: asymmetrical patterns of MRI and Blink Reflex for early diagnosis

Differential diagnosis between Parkinson’s disease (PD) and corticobasal syndrome (CBS) could be challenging at the early stage, due to the asymmetric onset of both diseases. Despite the clinical overlap, the anatomical circuits involved in these disorders are different. We evaluated R2 Blink Reflex Recovery Cycle (R2BRRC) and cortical thickness (CTh) in drug-naïve PD and CBS patients for characterizing pathophysiological mechanisms underlying these conditions. Patients with a clinically probable diagnosis of PD and possible CBS were recruited. R2BRRC was evaluated bilaterally at interstimulus intervals (ISIs) of 100–150–200–300–400–500–750 ms. Asymmetry index (AI) of R2BRRC for each ISI was computed. Patients underwent a structural brain MRI and hemisphere CTh and AI of MRI was calculated. Fourteen drug-naïve PD patients and 10 patients with early CBS diagnosis were enrolled. R2BRRC of PD patients showed an increased brainstem excitability for less affected side (LAS) stimulation at ISIs of 100 and 150 ms (p < 0.001) compared to most affected side (MAS), whereas no differences between LAS and MAS were found in CBS. AI of R2BRRC at ISI-100 ms showed significant difference, being higher in PD. CTh analysis showed significant differences between groups in hemisphere cortical volume contralateral to MAS, and, conversely, AI of MRI was significantly higher in CBS. PD patients exhibited an asymmetric pattern of brainstem excitability, compared to CBS. Conversely, CBS patients showed an asymmetric pattern of cortical atrophy. This opposite pattern of neurophysiological and structural abnormalities involving cortical and subcortical brain structures could highlight the different pathophysiological mechanisms underlying these disorders.

Brain structure correlates with auditory function in children diagnosed with auditory neuropathy spectrum disorder.

Auditory neuropathy spectrum disorder (ANSD) is a term for a collection of test results which indicate disruption of the auditory signal at some point along the neural pathway. This results in a spectrum of functional outcomes, ranging from reasonably normal hearing to profound hearing loss. This study assessed brain structure changes and behavioral correlates in children diagnosed with ANSD. Seventeen children who had previously been diagnosed with ANSD were recruited to the study and underwent a battery of behavioral measures of hearing, language, and communication, along with structural MR imaging. Analysis of cortical thickness of temporal lobe structures was carried out using FreeSurfer. Tract-based spatial statistics were performed on standard diffusion parameters of fractional anisotropy and diffusivity metrics. The control group comprised imaging data taken from a library of MRI scans from neurologically normal children. Control images were matched as closely as possible to the ANSD group for age and sex. Reductions in right temporal lobe cortical thickness were observed in children with ANSD compared to controls. Increases in medial diffusivity in areas including the corpus callosum and in the right occipital white matter were also seen in the group with ANSD compared to controls. Speech perception abilities, both in quiet and in noise, were correlated with cortical thickness measurements for several temporal lobe structures in children with ANSD, and relationships were also seen between diffusion metrics and measures of auditory function. This study shows that children with ANSD have structural brain differences compared to healthy controls. It also demonstrates associations between brain structure and behavioral hearing abilities in children diagnosed with ANSD. These results show that there is a potential for structural imaging to be used as a biomarker in this population with the possibility of predicting functional hearing outcome.

Mapping structural covariance networks in children and adolescents with post-traumatic stress disorder after earthquake.

For children and adolescents, there is a high risk of developing post-traumatic stress disorder (PTSD) after suffering from catastrophic events. Previous studies have identified brain functionally and subcortical brain volumes structurally abnormalities in this population. However, up till now, researches exploring alterations of regional cortical thickness (CTh) and brain interregional structural covariance networks (SCNs) are scarce. In this cross-sectional study, CTh measures are derived from 3-Tesla Tl-weighted MRI imaging data in a well-characterized combined group of children and adolescents with PTSD after an earthquake (N = 35) and a traumatized healthy control group (N = 24). By using surface-based morphometry (SBM) techniques, the regional CTh analysis was conducted. To map interregional SCNs derived from CTh, twenty-five altered brain regions reported in the PTSD population were selected as seeds. Whole-brain SBM analysis discovered a significant thickness reduction in the left medial orbitofrontal cortex for the subjects with PTSD. Similarly, analysis of SCNs associated with “seed” regions primarily located in default mode network (DMN), midline cortex structures, motor cortex, auditory association cortex, limbic system, and visual cortex demonstrated that children and adolescents with PTSD are associated with altered structural covariance with six key regions. This study provides evidence for distinct CTh correlates of PTSD that are present across children and adolescents, suggesting that brain cortical abnormalities related to trauma exposure are present in this population, probably by driving specific symptom clusters associated with disrupted extinction recall mechanisms for fear, episodic memory network and visuospatial attention.