Assessment of Gray Matter Microstructure and Synaptic Density in Alzheimer's Disease: A Multimodal Imaging Study With DTI and SV2A PET.

OBJECTIVE: Multimodal imaging techniques have furthered our understanding of how different aspects of Alzheimer's disease (AD) pathology relate to one another. Diffusion tensor imaging (DTI) measures such as mean diffusivity (MD) may be a surrogate measure of the changes in gray matter structure associated with AD. Positron emission tomography (PET) imaging of synaptic vesicle glycoprotein 2A (SV2A) has been used to quantify synaptic loss, which is the major pathological correlate of cognitive impairment in AD. In this study, we investigated the relationship between gray matter microstructure and synaptic density. METHODS: DTI was used to measure MD and [11C]UCB-J PET to measure synaptic density in 33 amyloid-positive participants with AD and 17 amyloid-negative cognitively normal (CN) participants aged 50-83. Univariate regression analyses were used to assess the association between synaptic density and MD in both the AD and CN groups. RESULTS: Hippocampal MD was inversely associated with hippocampal synaptic density in participants with AD (r = -0.55, p <0.001, df = 31) but not CN (r = 0.13, p = 0.62, df = 15). Exploratory analyses across other regions known to be affected in AD suggested widespread inverse associations between synaptic density and MD in the AD group. CONCLUSION: In the setting of AD, an increase in gray matter MD is inversely associated with synaptic density. These co-occurring changes may suggest a link between synaptic loss and gray matter microstructural changes in AD. Imaging studies of gray matter microstructure and synaptic density may allow important insights into AD-related neuropathology.

Reliability of brain atrophy measurements in multiple sclerosis using MRI: an assessment of six freely available software packages for cross-sectional analyses.

PURPOSE: Volume measurement using MRI is important to assess brain atrophy in multiple sclerosis (MS). However, differences between scanners, acquisition protocols, and analysis software introduce unwanted variability of volumes. To quantify theses effects, we compared within-scanner repeatability and between-scanner reproducibility of three different MR scanners for six brain segmentation methods. METHODS: Twenty-one people with MS underwent scanning and rescanning on three 3 T MR scanners (GE MR750, Philips Ingenuity, Toshiba Vantage Titan) to obtain 3D T1-weighted images. FreeSurfer, FSL, SAMSEG, FastSurfer, CAT-12, and SynthSeg were used to quantify brain, white matter and (deep) gray matter volumes both from lesion-filled and non-lesion-filled 3D T1-weighted images. We used intra-class correlation coefficient (ICC) to quantify agreement; repeated-measures ANOVA to analyze systematic differences; and variance component analysis to quantify the standard error of measurement (SEM) and smallest detectable change (SDC). RESULTS: For all six software, both between-scanner agreement (ICCs ranging 0.4-1) and within-scanner agreement (ICC range: 0.6-1) were typically good, and good to excellent (ICC > 0.7) for large structures. No clear differences were found between filled and non-filled images. However, gray and white matter volumes did differ systematically between scanners for all software (p < 0.05). Variance component analysis yielded within-scanner SDC ranging from 1.02% (SAMSEG, whole-brain) to 14.55% (FreeSurfer, CSF); and between-scanner SDC ranging from 4.83% (SynthSeg, thalamus) to 29.25% (CAT12, thalamus). CONCLUSION: Volume measurements of brain, GM and WM showed high repeatability, and high reproducibility despite substantial differences between scanners. Smallest detectable change was high, especially between different scanners, which hampers the clinical implementation of atrophy measurements.

Assessment of complementary white matter microstructural changes and grey matter atrophy in a preclinical model of Alzheimer's disease.

Alzheimer's disease (AD) has been associated with amyloid and tau pathology, as well as neurodegeneration. Beyond these hallmark features, white matter microstructural abnormalities have been observed using MRI. The objective of this study was to assess grey matter atrophy and white matter microstructural changes in a preclinical mouse model of AD (3xTg-AD) using voxel-based morphometry (VBM) and free-water (FW) diffusion tensor imaging (FW-DTI). Compared to controls, lower grey matter density was observed in the 3xTg-AD model, corresponding to the small clusters in the caudate-putamen, hypothalamus, and cortex. DTI-based fractional anisotropy (FA) was decreased in the 3xTg model, while the FW index was increased. Notably, the largest clusters for both FW-FA and FW index were in the fimbria, with other regions including the anterior commissure, corpus callosum, forebrain septum, and internal capsule. Additionally, the presence of amyloid and tau in the 3xTg model was confirmed with histopathology, with significantly higher levels observed across many regions of the brain. Taken together, these results are consistent with subtle neurodegenerative and white matter microstructural changes in the 3xTg-AD model that manifest as increased FW, decreased FW-FA, and decreased grey matter density.

Volumetric Assessment of Hippocampus and Subcortical Gray Matter Regions in Alzheimer Disease and Amnestic Mild Cognitive Impairment.

BACKGROUND: Quantitative MRI assessment methods have limited utility due to a lack of standardized methods and measures for Alzheimer disease (AD) and amnestic mild cognitive impairment (aMCI). OBJECTIVE: To employ a relatively new and easy-to-use quantitative assessment method to reveal volumetric changes in subcortical gray matter (GM) regions, hippocampus, and global intracranial structures as well as the diagnostic performance and best thresholds of total hippocampal volumetry in individuals with AD and those with aMCI. METHOD: A total of 74 individuals-37 with mild to moderate AD, 19 with aMCI, and 18 with normal cognition (NC)-underwent a 3T MRI. Fully automated segmentation and volumetric measurements were performed. RESULTS: The AD and aMCI groups had smaller volumes of amygdala, nucleus accumbens, and hippocampus compared with the NC group. These same two groups had significantly smaller total white matter volume than the NC group. The AD group had smaller total GM volume compared with the aMCI and NC groups. The thalamus in the AD group showed a subtle atrophy. There were no significant volumetric differences in the caudate nucleus, putamen, or globus pallidus between the groups. CONCLUSION: The amygdala and nucleus accumbens showed atrophy comparable to the hippocampal atrophy in both the AD and aMCI groups, which may contribute to cognitive impairment. Hippocampal volumetry is a reliable tool for differentiating between AD and NC groups but has substantially less power in differentiating between AD and aMCI groups. The loss of total GM volume differentiates AD from aMCI and NC.

The efficacy of gray matter atrophy and cognitive assessment in differentiation of aMCI and naMCI.

BACKGROUND: Mild cognitive impairment (MCI) is a heterogeneous entity that can be categorized into related but different subtypes. In this study, we analyzed the gray matter structural changes of amnestic MCI (aMCI) and non-amnestic MCI (naMCI), and how it resulted in diverse cognitive impairment. METHODS: Altogether 77 individuals were recruited, including 28 cognitively normal controls (NC), 25 naMCI subjects, and 24 aMCI subjects. All participants underwent a 3.0 T magnetic resonance (MR) scan and a detailed neuropsychological examination. Cortical thickness and subcortical nuclei volume were extracted by Freesurfer software and compared among groups. The areas with significant differences were further analyzed by general linear regression to identify the risk factors of each cognitive impairment subtypes. RESULTS: Significant differences were observed in bilateral hippocampi, amygdala, thalamus, accumbens, left transverse temporal gyrus and left precuneus among groups. AMCI and naMCI were significantly different in the right hippocampus, bilateral amygdala, left precuneus, and left transverse temporal gyrus. Linear regression analysis revealed that the atrophy of left precuneus was a risk factor of memory, executive function (EF) and visuospatial impairment (p < 0.001). The atrophy of left amygdala, right accumbens and left thalamus were risk factors of memory, EF and language impairment respectively (p < 0.05). CONCLUSIONS: These findings confirmed that different gray matter structural changes could lead to specific neuropsychological features in MCI subtypes. Thorough understanding of MCI subtypes and the underlying pathology would be beneficial for precise diagnosis and intervention.

Multimodal assessment of regional gray matter integrity in early relapsing-remitting multiple sclerosis patients with normal cognition: a voxel-based structural and perfusion approach.

OBJECTIVE: There is increasing evidence that gray matter (GM) impairment is strongly associated with clinical performance decline. We aim to perform a voxelwise analysis between regional GM (rGM) perfusion and structural abnormalities in early relapsing-remitting multiple sclerosis patients with normal cognition (RRMS-IC) and explore clinical correlate of early rGM abnormalities. METHODS AND MATERIALS: We studied 14 early RRMS-IC patients and 14 healthy age- and sex-matched controls. Brain perfusion single photon emission computed tomography (SPECT), structural MRI, and a comprehensive neuropsychological examination were acquired from all participants. Neuropsychological tests include expanded disability status scale, minimal mental status examination, short physical performance battery, Wechsler memory scale, and quick smell test. Voxel-based morphometry was used for analyzing SPECT and T1-MR images to identify rGM hypoperfusion and atrophy, respectively (RRMS-IC vs controls (group analysis), and also, each patient vs controls (individual analysis)) (p < 0.001). Then, anatomical location of impaired regions was acquired by automated anatomical labeling software. RESULTS: There was no significant difference in total GM volume between RRMS-IC and healthy controls, however, rGM atrophy and hypoperfusion were detected. Individual analysis revealed more rGM impairment compared with group analysis. rGM hypoperfusion was more extensive rather than rGM atrophy in RRMS-IC. There was no spatial association between rGM atrophy and rGM hypoperfusion (p > 0.05). rGM abnormalities correlated with several relevant minimal clinical deficits. CONCLUSION: Lack of spatial correlation between rGM atrophy and hypoperfusion might suggest that independent mechanisms might underlie atrophy and hypoperfusion. Perfusion SPECT may provide supplementary information along with MRI. ADVANCES IN KNOWLEDGE: Association between rGM atrophy and rGM hypoperfusion and their clinical significance in early RRMS-IC is not well described yet. Our study showed that there is spatial dissociation between rGM atrophy and rGM hypoperfusion, suggesting that different mechanisms might underlie these pathologies.

Assessment of the genetic contribution to brain magnetic resonance imaging lesion load and atrophy measures in multiple sclerosis patients.

BACKGROUND AND PURPOSE: Multiple sclerosis (MS) susceptibility is influenced by genetics; however, little is known about genetic determinants of disease expression. We aimed at assessing genetic factors influencing quantitative neuroimaging measures in two cohorts of progressive MS (PMS) and relapsing-remitting MS (RRMS) patients. METHODS: Ninety-nine PMS and 214 RRMS patients underwent a 3-T brain magnetic resonance imaging (MRI) scan, with the measurement of five MRI metrics including T2 lesion volumes and measures of white matter, grey matter, deep grey matter, and hippocampal volumes. A candidate pathway strategy was adopted; gene set analysis was carried out to estimate cumulative contribution of genes to MRI phenotypes, adjusting for relevant confounders, followed by single nucleotide polymorphism (SNP) regression analysis. RESULTS: Seventeen Kyoto Encyclopedia of Genes and Genomes pathways and 42 Gene Ontology (GO) terms were tested. We additionally included in the analysis genes with enriched expression in brain cells. Gene set analysis revealed a differential pattern of association across the two cohorts, with processes related to sodium homeostasis being associated with grey matter volume in PMS (p = 0.002), whereas inflammatory-related GO terms such as adaptive immune response and regulation of inflammatory response appeared to be associated with T2 lesion volume in RRMS (p = 0.004 and p = 0.008, respectively). As for SNPs, the rs7104613T mapping to SPON1 gene was associated with reduced deep grey matter volume (ß = -0.731, p = 3.2*10-7 ) in PMS, whereas we found evidence of association between white matter volume and rs740948A mapping to SEMA3A gene (ß = 22.04, p = 5.5*10-6 ) in RRMS. CONCLUSIONS: Our data suggest a different pattern of associations between MRI metrics and functional processes across MS disease courses, suggesting different phenomena implicated in MS.

Towards individualized cortical thickness assessment for clinical routine.

BACKGROUND: Cortical thickness measures the width of gray matter of the human cortex. It can be calculated from T1-weighted magnetic resonance images (MRI). In group studies, this measure has been shown to correlate with the diagnosis/prognosis of a number of neurologic and psychiatric conditions, but has not been widely adapted for clinical routine. One of the reasons for this might be that there is no reference system which allows to rate individual cortical thickness data with respect to a control population. METHODS: To address this problem, this study compared different methods to assess statistical significance of cortical thinning, i.e. atrophy. All compared methods were nonparametric and encompassed rating an individual subject's data set with respect to a control data population. Null distributions were calculated using data from the Human Connectome Project (HCP, n = 1000), and an additional HCP data set (n = 113) was used to calculate sensitivity and specificity to compare the different methods, whereas atrophy was simulated for sensitivity assessment. Validation measures were calculated for the entire cortex ("cumulative") and distinct brain regions ("regional") where possible. RESULTS: The approach yielding the highest combination of specificity and sensitivity implemented generating null distributions for anatomically distinct brain regions, based on the most extreme values observed in the population. With that method, while regional variations were observed, cumulative specificity of 98.9% and cumulative sensitivity at 80% was achieved for simulated atrophy of 23%. CONCLUSIONS: This study shows that validated rating of individual cortical thickness measures is possible, which can help clinicians in their daily routine to discover signs of atrophy before they become visually apparent on an unprocessed MRI. Furthermore, given different pathologies present with distinct atrophy patterns, the regional validation proposed here allows to detect distinct patterns of atrophy, which can further enhance differential diagnosis/prognosis.

Anxiety symptoms are associated with smaller insular and orbitofrontal cortex volumes in late-life depression.

BACKGROUND: Increasing understanding of the neural correlates of anxiety symptoms in late-life depression (LLD) could inform the development of more targeted and effective treatments. METHODS: Grey matter volume (GMV) was assessed with volumetric magnetic resonance imaging in a sample of 113 adults ≥60 years with MDD using the following regions of interest: amygdala, anterior cingulate cortex (ACC), insula, orbitofrontal cortex (OFC), and temporal cortex. RESULTS: After controlling for demographic (age, sex, education) and clinical variables (antidepressant use, anxiolytic use, duration of illness, medical comorbidity, cognitive functioning), greater severity of anxiety symptoms was associated with lower GMV bilaterally in the insula, F(1,102) = 6.63, p = 0.01, and OFC, F(1,102) = 8.35, p = 0.005. By contrast, depressive symptom severity was significantly associated with lower bilateral insula volumes, F(1,102) = 6.43, p = 0.01, but not OFC volumes, F(1,102) = 5.37, p = 0.02. LIMITATIONS: Limitations include (1) the relatively mild nature of anxiety symptoms in our sample; (2) the cross-sectional research design, which prohibits inferences of directionality; (3) the relatively homogenous demographic of the sample, and (4) the exclusion of participants with significant psychiatric comorbidity, suicidality, or cognitive impairment. CONCLUSIONS: Decreased OFC volumes may serve as a unique biomarker of anxiety symptoms in LLD. Future longitudinal and clinical studies with long-term follow up and more diverse samples will help further elucidate the biological, psychological, and social factors affecting associations between anxiety and brain morphology in LLD.

Amygdala volume is associated with risky probability cognition in gambling disorder.

Gambling disorder (GD) is characterized by continual gambling despite negative consequences. Risky decision-making is a hallmark of the disorder. We applied a tool from behavioral economics for assessing probability cognition in both gain and loss domains to GD. We aimed to examine the alteration of probability cognition and its relationship with brain structure in GD. Forty-six GD patients and 52 age-matched healthy controls (HCs) conducted a risky choice task in which subjects should choose between a sure and a risky option in both loss and gain domains. The distortion and elevation parameters of the probability weighting function were estimated. We compared the parameters between GD and HC and examined their relationships with the striatum and amygdala volumes in GD. GD showed greater elevation parameter in the gain domain and smaller regional gray matter volume in the left amygdala than HC. The elevation parameter in the gain domain showed a negative correlation with the left amygdala volume in GD. Altered probability cognition in the gain domain but not in the loss domain might be more relevant to risky decision-making in GD. Our findings indicate that alteration in the amygdala might play a significant role in risky decision-making of GD. Longitudinal studies are recommended to examine the causal relationship between brain abnormalities and risky decision-making in GD.

Structural Brain Alterations Before and After Total Knee Arthroplasty: A Longitudinal Assessment.

Objective: Many studies have provided evidence of altered brain structure in chronic pain conditions, as well as further adaptations following treatment that are coincident with changes in pain. Less is known regarding how these structural brain adaptations relate to assessments of nociceptive processing. The current study aimed to investigate brain structure in people with knee osteoarthritis (OA) before and after total knee arthroplasty (TKA) and to investigate the relationships between these findings and quantitative sensory testing (QST) of the nociceptive system. Methods: Twenty-nine people with knee OA underwent magnetic resonance imaging (MRI) scans and QST before and six months after TKA and were compared with a pain-free control group (N = 18). MRI analyses involved voxel-based morphometry and fractional anisotropy. Results: Before TKA, there was reduced gray matter volume and impaired fractional anisotropy in areas associated with nociceptive processing, with further gray matter adaptations and improvements in fractional anisotropy evident after TKA. QST revealed increased nociceptive facilitation and impaired inhibition in knee OA that was reversed after TKA. There were minimal relationships found between MRI data and QST assessments or pain report. Conclusions: In people with end-stage knee OA, region-specific gray matter atrophy was detected, with further changes in gray matter volume and improvements in white matter integrity observed after joint replacement. Despite coincident alterations in nociceptive inhibition and facilitation processes, there did not appear to be any association between these functional assessments of the nociceptive system and changes in brain structure.

[Assessment of the brain volume alterations in patients with hyposmia based on voxel-based morphometry].

Objective: To investigate the brain volume alterations in patients with hyposmia using voxel-based morphometry (VBM) and to correlate these alterations with the degree and duration of hyposmia. Methods: Forty patients with hyposmia from Department of Otorhinolaryngology Head and Neck Surgery, Beijing Anzhen Hospital since 2013 to 2016 and forty age and sex matched normal subjects were recruited in this study. Sniffin' Sticks olfactory test was performed to evaluate the olfactory function of all subjects. We acquired T1-weighted magnetic resonance images from all subject on a 3T scanner. VBM was performed using VBM8 toolbox and SPM8 in a Matlab environment. Independent sample t test analysis was used to compare the volume of gray and white matter between the controls and patients. In addition, the Pearson or Spearman correlation analysis was used for the correlation between the voxel value of cerebral volume alterations area and the degree and duration of hyposmia on patients (threshold discrimination identification, TDI). Results: Compared with the controls, patients showed significantly decreased volume in the gray matter of right orbitofrontal cortex (number of voxel in clusters was 226, t=-4.46, P<0.001, uncorrected). There was negative correlation between decreased gray matter volume of the right orbitofrontal cortex with significantly decreased area and the TDI results (r=-0.40, P=0.01), but positive correlation with duration of hyposmia (r=0.37, P=0.02). Conclusions: The patients with hyposmia show gray matter atrophy of the right orbitofrontal cortex. The duration may be an important risk factor for decreased gray matter in patients with hyposmia.

Measurement of Whole-Brain and Gray Matter Atrophy in Multiple Sclerosis: Assessment with MR Imaging.

Purpose To compare available methods for whole-brain and gray matter (GM) atrophy estimation in multiple sclerosis (MS) in terms of repeatability (same magnetic resonance [MR] imaging unit) and reproducibility (different system/field strength) for their potential clinical applications. Materials and Methods The softwares ANTs-v1.9, CIVET-v2.1, FSL-SIENAX/SIENA-5.0.1, Icometrix-MSmetrix-1.7, and SPM-v12 were compared. This retrospective study, performed between March 2015 and March 2017, collected data from (a) eight simulated MR images and longitudinal data (2 weeks) from 10 healthy control subjects to assess the cross-sectional and longitudinal accuracy of atrophy measures, (b) test-retest MR images in 29 patients with MS acquired within the same day at different imaging unit field strengths/manufacturers to evaluate precision, and (c) longitudinal data (1 year) in 24 patients with MS for the agreement between methods. Tissue segmentation, image registration, and white matter (WM) lesion filling were also evaluated. Multiple paired t tests were used for comparisons. Results High values of accuracy (0.87-0.97) for whole-brain and GM volumes were found, with the lowest values for MSmetrix. ANTs showed the lowest mean error (0.02%) for whole-brain atrophy in healthy control subjects, with a coefficient of variation of 0.5%. SPM showed the smallest mean error (0.07%) and coefficient of variation (0.08%) for GM atrophy. Globally, good repeatability (P > .05) but poor reproducibility (P < .05) were found for all methods. WM lesion filling technique mainly affected ANTs, MSmetrix, and SPM results (P < .05). Conclusion From this comparison, it would be possible to select a software for atrophy measurement, depending on the requirements of the application (research center, clinical trial) and its goal (accuracy and repeatability or reproducibility). An improved reproducibility is required for clinical application. © RSNA, 2018 Online supplemental material is available for this article.

Iron-Insensitive Quantitative Assessment of Subcortical Gray Matter Demyelination in Multiple Sclerosis Using the Macromolecular Proton Fraction.

BACKGROUND AND PURPOSE: Fast macromolecular proton fraction mapping is a recent quantitative MR imaging method for myelin assessment. The objectives of this study were to evaluate the macromolecular proton fraction as a measure of demyelination in subcortical GM structures in multiple sclerosis and assess a potential relationship between demyelination and excess iron deposition using the macromolecular proton fraction and T2* mapping. MATERIALS AND METHODS: Macromolecular proton fraction and T2* maps were obtained from 12 healthy controls, 18 patients with relapsing-remitting MS, and 12 patients with secondary-progressive MS using 3T MR imaging. Parameter values in the caudate nucleus, globus pallidus, putamen, substantia nigra, and thalamus were compared between groups and correlated to clinical data. RESULTS: The macromolecular proton fraction in all subcortical structures and T2* in the globus pallidus, putamen, and caudate nucleus demonstrated a significant monotonic decrease from controls to patients with relapsing-remitting MS and from those with relapsing-remitting MS to patients with secondary-progressive MS. The macromolecular proton fraction in all subcortical structures significantly correlated with the Expanded Disability Status Scale and MS Functional Composite scores with absolute Pearson correlation coefficient (r) values in a range of 0.4-0.6. Significant correlations (r = -0.4 to -0.6) were also identified between the macromolecular proton fraction and the 9-Hole Peg Test, indicating a potential relationship with nigrostriatal pathway damage. Among T2* values, weak significant correlations with clinical variables were found only in the putamen. The macromolecular proton fraction did not correlate with T2* in any of the studied anatomic structures. CONCLUSIONS: The macromolecular proton fraction provides an iron-insensitive measure of demyelination. Myelin loss in subcortical GM structures in MS is unrelated to excess iron deposition. Subcortical GM demyelination is more closely associated with the disease phenotype and disability than iron overload.

Longitudinal assessment of gray matter volumes and white matter integrity in patients with medication-overuse headache.

Background Medication-overuse headache is a common clinical entity, but neuroimaging studies investigating volumetric and microstructural alterations of the brain in medication-overuse headache are rare. Therefore, in the current longitidunal study we evaluated gray matter volume and white matter integrity in patients with medication-overuse headache before and after drug withdrawal. Methods A prospective study evaluated 27 patients with medication-overuse headache and 27 age-, sex-, and education-matched healthy adults. High-resolution T1-weighted magnetic resonance imaging and diffusion tensor imaging were obtained from the control group and medication-overuse headache patients before and six months after drug withdrawal. Tract-based spatial statistics of multiple diffusivity indices and voxel-based morphometry were employed to investigate white and gray matter abnormalities. Results No correlation was found between age, gender, education and smoking status in both groups. The most commonly overused medications were simple analgesics (96.3%) and combined analgesics (3.7%). The mean duration of the history of medication overuse and headaches was 56.7 ± 63.5 months. White matter diffusional and gray matter morphological alterations including volume, fractional anisotropy, radial diffusivity, and axial diffusivity analyses showed no significant relationship in the patients before and six months after withdrawal of analgesics. Also no difference was observed between the patients versus controls. Conclusion Our data demonstrated no structural alterations within the brain in medication-overuse headache.

Left dorsolateral prefrontal cortex atrophy is associated with frontal lobe function in Alzheimer's disease and contributes to caregiver burden.

OBJECTIVE: Caregivers of patients with dementia experience physical and mental deterioration. We have previously reported a correlation between caregiver burden and the Frontal Assessment Battery (FAB) total scores of patients with Alzheimer's disease (AD), especially regarding the dependency factor from the Zarit Burden Interview. The present study aimed to identify an objective biomarker for predicting caregiver burden. METHODS: The participants were 26 pairs of caregivers and patients with AD and mild-to-moderate dementia. Correlations between regional gray matter volumes in the patients with AD and the FAB total scores were explored by using whole-brain voxel-based morphometric analysis. Path analysis was used to estimate the relationships between regional gray matter volumes, FAB total scores, and caregiver burden based on the Zarit Burden Interview. RESULTS: The voxel-based morphometric revealed a significant positive correlation between the FAB total scores and the volume of the left dorsolateral prefrontal cortex. This positive correlation persisted after controlling for the effect of general cognitive dysfunction, which was assessed by using the Mini-Mental State Examination. Path analysis revealed that decreases in FAB scores, caused by reduced frontal lobe volumes, negatively affected caregiver burden. CONCLUSIONS: The present study revealed that frontal lobe function, based on FAB scores, was affected by the volume of the left dorsolateral prefrontal cortex. Decreased scores were associated with greater caregiver burden, especially for the dependency factor. These findings may facilitate the development of an objective biomarker for predicting caregiver burden.

SIENA-XL for improving the assessment of gray and white matter volume changes on brain MRI.

In this article, SIENA-XL, a new segmentation-based longitudinal pipeline is introduced, for: (i) increasing the precision of longitudinal volume change estimation for white (WM) and gray (GM) matter separately, compared with cross-sectional segmentation methods such as SIENAX; and (ii) avoiding potential biases in registration-based methods when Jacobians are used, with a smoothing extent larger than spatial scale between tissue-interfaces, which is where atrophy usually occurs. SIENA-XL implements a new brain extraction procedure and a multi-time-point intensity equalization step before performing the final segmentation that also includes separate segmentation of deep GM structures by using FMRIB's Integrated Registration and Segmentation Tool. The detection of GM and WM volume changes with SIENA-XL was evaluated using different healthy control (HC) and multiple sclerosis (MS) MRI datasets and compared with the traditional SIENAX and two Jacobian-based approaches, SPM12 and SIENAX-JI (a version of SIENAX including Jacobian integration - JI). In scan-rescan data from HCs, SIENA-XL showed: (i) a significant decrease in error, of 50-70% when compared with SIENAX; (ii) no significant differences in error when compared with SIENAX-JI and SPM12 in a scan-rescan HC dataset that included repositioning. When tested in a HC dataset with scan-rescan both at baseline and after 1 year of follow-up, SIENA-XL showed: (i) significantly higher precision (P < 0.01) than SIENAX; (ii) no significant differences to SIENAX-JI and SPM12. Finally, in a dataset of 79 MS patients with a 2 years follow-up, SIENA-XL showed a substantial reduction of sample size, by comparison with SIENAX, SIENAX-JI, and SPM12, for detecting treatment effects of 25, 30, and 50%. Hum Brain Mapp 39:1063-1077, 2018. © 2017 Wiley Periodicals, Inc.

Structural alterations in patients with obsessive-compulsive disorder: a surface-based analysis of cortical volume, surface area and thickness.

BACKGROUND: Mounting evidence indicates the presence of structural brain alterations in individuals with obsessive-compulsive disorder (OCD). Findings are, however, rather heterogeneous, which may be partly because of differences in methodological approaches or clinical sample characteristics. The aim of the present study was to analyze the whole brain cortical volume, surface area and thickness in a large sample of patients with OCD compared with age- and sex-matched healthy controls. METHODS: We conducted whole brain surface-based analyses of grey matter measures using the automated FreeSurfer software in patients with OCD and matched controls. Group analyses were performed and corrected for multiple testing using Monte Carlo simulations (p < 0.05). Altered brain regions and their average morphological values were associated to symptom severity and type (Yale-Brown Obsessive Compulsive Scale scores). RESULTS: We included 75 patients and 75 controls in our analyses. Patients with OCD showed decreases in both volume and surface area compared with healthy controls in inferior-superior parieto-occipital regions. In addition, the precuneus, posterior cingulate areas, middle frontal and orbitofrontal areas, and middle inferior temporal areas extending to the fusiform gyrus were characterized by a reduced surface area only. There were no differences in grey matter thickness between the groups. LIMITATIONS: The presence of comorbidities, medication usage and the multisymptomatic feature of OCD could have influenced our results to a certain degree. CONCLUSION: Our results suggest decreased grey matter volume and surface area in several key regions in patients with OCD. Parietal regions showed reductions in both volume and surface area, which underlines the potential relevance of these regions for the pathophysiology of the disorder.

Association between the scores of the Japanese version of the Brief Assessment of Cognition in Schizophrenia and whole-brain structure in patients with chronic schizophrenia: A voxel-based morphometry and diffusion tensor imaging study.

AIM: The Brief Assessment of Cognition in Schizophrenia (BACS) is a concise tool designed to evaluate cognitive deficits in schizophrenia. We examined the possible association between BACS scores and whole-brain structure, as observed using magnetic resonance imaging with a relatively large sample. METHODS: The study sample comprised 116 patients with schizophrenia (mean age, 39.3 ± 11.1 years; 66 men) and 118 healthy controls (HC; mean age, 40.0 ± 13.6 years; 58 men) who completed the Japanese version of the BACS (BACS-J). All participants were of Japanese ethnicity. The magnetic resonance imaging volume and diffusion tensor imaging data were processed with voxel-based morphometry and tract-based spatial statistics, respectively. RESULTS: There were significant reductions in the regional gray matter volumes and white matter fractional anisotropy values in patients with schizophrenia compared to HC. For the gray matter areas, the working memory score had a significant positive correlation with the anterior cingulate and medial frontal cortices volumes in the patients. For the white matter areas, the motor speed score had a significant positive correlation with fractional anisotropy values in the corpus callosum, internal capsule, superior corona radiata, and superior longitudinal fasciculus in the patients. However, there was no significant correlation among either the gray or white matter areas in the HC. CONCLUSION: Our results suggest that among the BACS-J measures, the working memory and motor speed scores are associated with several structural alterations in the brains of patients with schizophrenia.

Serial Assessment of Gray Matter Abnormalities after Sport-Related Concussion.

There is an urgent need to characterize the acute physiological effects of sport-related concussion (SRC). We investigated the effects of SRC on gray matter structure and diffusion metrics in collegiate athletes at 1.64 (T1; n = 33), 8.33 (T2; n = 30), and 32.15 days (T3; n = 36) post-concussion, with healthy collegiate contact-sport athletes serving as controls (HA; n = 46). Plasma levels of glial fibrillary acidic protein (GFAP) were assessed in a subset of athletes. We hypothesized that acute SRC would be associated with increased fractional anisotropy (FA), decreased mean diffusivity (MD), and increased GFAP relative to noninjured HA, without acute differences in gray matter volume or cortical thickness. Further, we hypothesized that neither diffusion nor structure would show longitudinal changes across the first month post-SRC. Finally, we hypothesized that gray matter diffusion metrics would correlate with plasma GFAP levels, as indicated by pre-clinical literature. Consistent with our hypothesis, acute SRC was associated with decreased MD in the left pallidum, increased FA in the right amygdala, and a significantly greater number and volume of subject-specific clusters with increased FA compared to HA. No differences in gray matter volume, cortical thickness, or GFAP were observed between groups. There were no longitudinal changes in any measure across the first month post-SRC. Finally, FA in the right amygdala was inversely correlated with GFAP at T2. These results suggest that gray matter diffusion metrics may be useful in determining the physiological effects of SRC.