Regional Brain Atrophy Research Articles

Abstract 11878: Atrial Fibrillation is Correlated With Brain Atrophy in Regions Associated With Alzheimer Disease

Introduction: Atrial fibrillation (AF) has been associated with neurocognitive impairment. The broad effects of AF on the brain, however, remain to be clarified. We investigated using data from the UK Biobank (UKB) whether an automated electrocardiography (ECG) diagnosis of AF or atrial flutter (AFL) is associated with imaging-based markers of brain atrophy, including volume, thickness, and white matter microstructure, in brain regions associated with Alzheimer Disease (AD). Methods: We studied a subset of 48,705 UKB study participants with available brain magnetic resonance imaging (MRI) and cognitive function test data. AF/AFL were determined by either automatic ECG interpretation or history by self-reported and hospital-visit derived data. Participants were classified into four groups: 1) no history or ECG detection of AF/AFL; 2) history of AF/AFL but no AF/AFL on ECG; 3) no history of AF/AFL but AF/AFL on ECG; and 4) history of AF/AFL and AF/AFL on ECG. The following brain MRI measurements were obtained: mean bilateral hippocampal volume, fornix fractional anisotropy (FA), and an AD cortical thickness signature. The AD cortical thickness signature was computed as the average of thickness values in various frontal and temporal cortices involved in AD progression. Results: A total of 17,723 participants aged 46-81 (mean age 64 years, 52.2% female) with group sizes of 17182, 307, 100, and 134 (groups 1-4 respectively) were included. Compared to participants with no AF/AFL (group 1), hippocampal volume was significantly smaller in the two groups with AF/AFL on ECG (groups 3 and 4; 97.5 and 95.8 mm 3 smaller; p<0.005). No difference in the volume was found between groups 1 and 2. This pattern of group differences was similar for both fornix FA and the AD cortical thickness signature. A post-hoc analysis for the cognitive function variables showed that scores on the matrix pattern and symbol digit substitution cognitive tests were lower for participants with AF/AFL on ECG (groups 3+4) than those without AF/AFL (groups 1), each with a beta estimate of -0.16 standard deviations (p<0.05). Conclusion: AF/AFL on ECG at time of brain imaging, but not AF/AFL history, is associated with brain atrophy and disrupted white matter microstructure in AD-associated regions.

Effects of a physical activity intervention on brain atrophy in older adults at risk of dementia: a randomized controlled trial.

Lack of physical activity is a risk factor for dementia, however, the utility of interventional physical activity programs as a protective measure against brain atrophy and cognitive decline is uncertain. Here we present the effect of a randomized controlled trial of a 24-month physical activity intervention on global and regional brain atrophy as characterized by longitudinal voxel-based morphometry with T1-weighted MRI images. The study sample consisted of 98 participants at risk of dementia, with mild cognitive impairment or subjective memory complaints, and having at least one vascular risk factor for dementia, randomized into an exercise group and a control group. Between 0 and 24 months, there was no significant difference detected between groups in the rate of change in global, or regional brain volumes.

Regional brain atrophy and aberrant cortical folding relate to anxiety and depression in patients with traumatic brain injury and psychogenic nonepileptic seizures.

Psychogenic nonepileptic seizures (PNES) are characterized by multifocal and global abnormalities in brain function and connectivity. Only a few studies have examined neuroanatomic correlates of PNES. Traumatic brain injury (TBI) is reported in 83% of patients with PNES and may be a key component of PNES pathophysiology. In this study, we included patients with TBI preceding the onset of PNES (TBI-PNES) and TBI without PNES (TBI-only) to identify neuromorphometric abnormalities associated with PNES. Adults diagnosed with TBI-PNES (n=62) or TBI-only (n=59) completed psychological questionnaires and underwent 3-T magnetic resonance imaging. Imaging data were analyzed by voxel- and surface-based morphometry. Voxelwise general linear models computed group differences in gray matter volume, cortical thickness, sulcal depth, fractal dimension (FDf), and gyrification. Statistical models were assessed with permutation-based testing at 5000 iterations with the Threshold-Free Cluster Enhancement toolbox. Logarithmically scaled p-values corrected for multiple comparisons using familywise error were considered significant at p<.05. Post hoc analyses determined the association between structural and psychological measures (p<.05). TBI-PNES participants demonstrated atrophy of the left inferior frontal gyrus and the right cerebellum VIII. Relative to TBI-only, TBI-PNES participants had decreased FDf in the right superior parietal gyrus and decreased sulcal depth in the left insular cortex. Significant clusters were positively correlated with global assessment of functioning scores, and demonstrated varying negative associations with measures of anxiety, depression, somatization, and global severity of symptoms. The diagnosis of PNES was associated with brain atrophy and reduced cortical folding in regions implicated in emotion processing, regulation, and response inhibition. Cortical folds primarily develop during the third trimester of pregnancy and remain relatively constant throughout the remainder of one's life. Thus, the observed aberrations in FDf and sulcal depth could originate early in development. The convergence of environmental, developmental, and neurobiological factors may coalesce to reflect the neuropathophysiological substrate of PNES.

Machine Learning Techniques for the Diagnosis of Attention-Deficit/Hyperactivity Disorder from Magnetic Resonance Imaging: A Concise Review.

Attention-deficit/hyperactivity disorder (ADHD) is a neuro-developmental disease commonly seen in children and it is diagnosed via extensive interview procedures, behavioral studies, third-party observations, and comprehensive personal history. ADHD causes regional atrophy in brain regions and alters the pattern of functional brain connectivity networks. Automated/computerized methods based on magnetic resonance imaging (MRI) can replace subjective methods for the identification of ADHD. The aim of this study was to analyze various machine-learning algorithms for ADHD by feeding in vital input features extracted from functional brain connectivity and different existing methods and to review factors crucial for the diagnosis of ADHD. This paper is a concise review of machine learning methods for the diagnosis of ADHD from MRI. Techniques for feature extraction, dimensionality reduction/feature selection, and classification, employed in the computerized techniques for the diagnosis of ADHD from MRI and the accuracy of classification offered by the individual methods, are focussed on the review. Machine learning algorithms with features of functional brain connectivity networks as input, with hierarchical sparse feature elimination, exhibits the highest accuracy. Augmentation of the behavioral features does not contribute much to increased accuracy. The level of accuracy offered by the frameworks meant for the computer-aided diagnosis of ADHD, available in the literature, does not justify their feasibility in clinical practice. Computerized methods that exploit highly specific biomarkers of ADHD like brain iron concentration in Globus Pallidus, Putamen, Caudate nucleus, and thalamus as features are not available.

Age, vascular disease, and Alzheimer\u2019s disease pathologies in amyloid negative elderly adults

BackgroundWe recently reported that CSF phosphorylated tau (p-Tau181) relative to Aβ40 (CSF p-Tau/Aβ40 ratio) was less noisy and increased associations with Alzheimer’s disease (AD) biomarkers compared to CSF p-Tau181 alone. While elevations of CSF p-Tau/Aβ40 can occur in amyloid-β (Aβ) negative (Aβ-) individuals, the factors associated with these elevations and their role in neurodegeneration and cognitive decline are unknown. We aim to explore factors associated with elevated tau in CSF, and how these elevated tau are related to neurodegeneration and cognitive decline in the absence of Aβ positivity.MethodsWe examined relationships between CSF p-Tau/Aβ40, and CSF Aβ42/Aβ40, Aβ PET, and white matter hyperintensities (WMH) as well as vascular risk factors in 149 cognitively unimpaired and 52 impaired individuals who were presumably not on the Alzheimer’s disease (AD) pathway due to negative Aβ status on both CSF and PET. Subgroups had 18F-fluorodeoxyglucose (FDG) PET and adjusted hippocampal volume (aHCV), and longitudinal measures of CSF, aHCV, FDG PET, and cognition data, so we examined CSF p-Tau/Aβ40 associations with these measures as well.ResultsElevated CSF p-Tau/Aβ40 was associated with older age, male sex, greater WMH, and hypertension as well as a pattern of hippocampal atrophy and temporoparietal hypometabolism characteristic of AD. Lower CSF Aβ42/Aβ40, higher WMH, and hypertension but not age, sex, Aβ PET, APOE-ε4 status, body mass index, smoking, and hyperlipidemia at baseline predicted CSF p-Tau/Aβ40 increases over approximately 5 years of follow-up. The relationship between CSF p-Tau/Aβ40 and subsequent cognitive decline was partially or fully explained by neurodegenerative measurements.ConclusionsThese data provide surprising clues as to the etiology and significance of tau pathology in the absence of Aβ. It seems likely that, in addition to age, both cerebrovascular disease and subthreshold levels of Aβ are related to this tau accumulation. Crucially, this phenotype of CSF tau elevation in amyloid-negative individuals share features with AD such as a pattern of metabolic decline and regional brain atrophy.

Visual Performance and Cortical Atrophy in Vision-Related Brain Regions Differ Between Older Adults with (or at Risk for) Alzheimer’s Disease

Background: Visual impairment is associated with deficits in cognitive function and risk for cognitive decline and Alzheimer’s disease (AD). Objective: The purpose of this study was to characterize the degree of visual impairment and explore the association thereof with cortical atrophy in brain regions associated with visual processing in individuals with (or at risk for) AD. Methods: Using the Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) dataset, we analyzed vision and brain imaging data from three diagnostic groups: individuals with subjective cognitive decline (SCD; N = 35), mild cognitive impairment (MCI; N = 74), and mild AD (N = 30). We used ANCOVAs to determine whether performance on reading acuity and contrast sensitivity tests differed across diagnostic groups. Hierarchical regression analyses were applied to determine whether visual performance predicted gray matter volume for vision-related regions of interest above and beyond group membership. Results: The AD group performed significantly worse on reading acuity (F(2,138) = 4.12, p &lt; 0.01, ω2 = 0.04) compared to the SCD group and on contrast sensitivity (F(2,138) = 7.6, p &lt; 0.01, ω2 = 0.09) compared to the SCD and MCI groups, which did not differ from each other. Visual performance was associated with volume in some vision-related structures beyond clinical diagnosis. Conclusion: Our findings demonstrate poor visual performance in AD and that both group membership and visual performance are predictors of cortical pathology, consistent with the idea that atrophy in visual areas and pathways contributes to the functional vision deficits observed in AD.

Thalamus Atrophy in the Peri-Pregnancy Period in Clinically Stable Multiple Sclerosis Patients: Preliminary Results.

Radiological activity in the post-partum period in MS patients is a well-known phenomenon, but there is no data concerning the influence of pregnancy on regional brain atrophy. The aim of this article was to investigate local brain atrophy in the peri-pregnancy period (PPP) in patients with MS. Thalamic volume (TV); corpus callosum volume (CCV) and classical MRI activity (new gadolinium enhancing lesions (Gd+), new T2 lesions, T1 lesions volume (T1LV) and T2 lesions volume (T2LV)) were analyzed in 12 clinically stable women with relapsing–remitting MS and with MRI performed in the PPP. We showed that there was a significant decrease in TV (p = 0.021) in the PPP. We also observed a significant increase in the T1 lesion volume (p = 0.028), new gadolinium-enhanced and new T2 lesions (in 46% and 77% of the scans, respectively) in the post-partum period. Our results suggest that the PPP in MS may be associated not only with classical MRI activity but, also, with regional brain atrophy.

Resting-state functional magnetic resonance imaging in a randomized clinical trial for Alzheimer's disease

Resting-state functional connectivity has been used to study Alzheimer's disease, revealing underlying differences between groups of individuals at different levels of cognitive impairment, or groupwise changes over time. Most of these studies have employed a single scanner and/or a single scan per subject. In this study, we used data collected from a substudy to two randomized clinical trials in patients with mild-to-moderate Alzheimer's Disease to investigate the robustness of functional connectivity in a multicenter, longitudinal setting. This substudy was not powered to detect drug treatment effects. With a basic imaging charter for inter-site acquisition standardization, we found no changes to functional connectivity over time in the placebo group, despite observable changes in clinical test scores and regional brain atrophy. We infer that functional connectivity, as implemented in our study, is not sensitive enough to detect disease progression in our patients. Using an 8-week interval between scans (in both treatment and placebo groups), we found that our test-retest reproducibility was comparable with other published results. We also found that the dominant source of measurement variability was within individuals over time, compared with variability between subjects and sites. Finally, we propose a simple method of visual inspection to identify scans that should be excluded from longitudinal analysis.

Regional brain atrophy is related to social cognition impairment in multiple sclerosis.

Multiple sclerosis exhibits specific neuropathological phenomena driving to both global and regional brain atrophy. At the clinical level, the disease is related to functional decline in cognitive domains as the working memory, processing speed, and verbal fluency. However, the compromise of social-cognitive abilities has concentrated some interest in recent years despite the available evidence suggesting the risk of disorganization in social life. Recent studies have used the MiniSEA test to assess the compromise of social cognition and have found relevant relationships with memory and executive functions, as well as with the level of global and regional brain atrophy. The present article aimed to identify structural changes related to socio-cognitive performance in a sample of patients with relapsing-remitting multiple sclerosis. 68 relapsing-remitting multiple sclerosis Chilean patients and 50 healthy control subjects underwent MRI scans and neuropsychological evaluation including social-cognition tasks. Total brain, white matter, and gray matter volumes were estimated. Also, voxel-based morphometry was applied to evaluate regional structural changes. Patients exhibited lower scores in all neuropsychological tests. Social cognition exhibited a significant decrease in this group mostly related to the declining social perception. Normalized brain volume and white matter volume were significantly decreased when compared to healthy subjects. The regional brain atrophy analysis showed that changes in the insular cortex and medial frontal cortices are significantly related to the variability of social-cognitive performance among patients. In the present study, social cognition was only correlated with the deterioration of verbal fluency, despite the fact that previous studies have reported its link with memory and executive functions. The identification of specific structural correlates supports the comprehension of this phenomenon as an independent source of cognitive disability in these patients.

Interacting effects of frontal lobe neuroanatomy and working memory capacity to older listeners' speech recognition in noise

Many older adults are struggling with understanding spoken language, particularly when background noise interferes with comprehension. In the present study, we investigated a potential interaction between two well-known factors associated with greater speech-in-noise (SiN) reception thresholds in older adults, namely a) lower working memory capacity and b) age-related structural decline of frontal lobe regions.In a sample of older adults (N = 25) and younger controls (N = 13) with normal pure-tone thresholds, SiN reception thresholds and working memory capacity were assessed. Furthermore, T1-weighted structural MR-images were recorded to analyze neuroanatomical traits (i.e., cortical thickness (CT) and cortical surface area (CSA)) of the cortex.As expected, the older group showed greater SiN reception thresholds compared to the younger group. We also found consistent age-related atrophy (i.e., lower CT) in brain regions associated with SiN recognition, namely the superior temporal lobe bilaterally, the right inferior frontal and precentral gyrus, as well as the left superior frontal gyrus. Those older participants with greater atrophy in these brain regions showed greater SiN reception thresholds. Interestingly, the association between CT in the left superior frontal gyrus and SiN reception thresholds was moderated by individual working memory capacity. Older adults with greater working memory capacity benefitted more strongly from thicker frontal lobe regions leading to better SiN recognition.Overall, our results fit well into the literature showing that age-related structural decline in auditory- and cognition-related brain areas is associated with greater SiN reception thresholds in older adults. However, we highlight that this association changes as a function of individual working memory capacity. We therefore believe that future interventions to improve SiN recognition in older adults should take into account the role of the frontal lobe as well as individual working memory capacity.

Causal structural covariance network revealing atrophy progression in Alzheimer's disease continuum.

The structural covariance network (SCN) has provided a perspective on the large‐scale brain organization impairment in the Alzheimer's Disease (AD) continuum. However, the successive structural impairment across brain regions, which may underlie the disrupted SCN in the AD continuum, is not well understood. In the current study, we enrolled 446 subjects with AD, mild cognitive impairment (MCI) or normal aging (NA) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The SCN as well as a casual SCN (CaSCN) based on Granger causality analysis were applied to the T1‐weighted structural magnetic resonance images of the subjects. Compared with that of the NAs, the SCN was disrupted in the MCI and AD subjects, with the hippocampus and left middle temporal lobe being the most impaired nodes, which is in line with previous studies. In contrast, according to the 194 subjects with records on CSF amyloid and Tau, the CaSCN revealed that during AD progression, the CaSCN was enhanced. Specifically, the hippocampus, thalamus, and precuneus/posterior cingulate cortex (PCC) were identified as the core regions in which atrophy originated and could predict atrophy in other brain regions. Taken together, these findings provide a comprehensive view of brain atrophy in the AD continuum and the relationships among the brain atrophy in different regions, which may provide novel insight into the progression of AD.

Sarcopenia is independently associated with parietal atrophy in older adults

As populations age, sarcopenia becomes a major health problem among adults aged 65years and older. However, little information is available about the relationship between sarcopenia and brain structure abnormalities. The objective of this study was to investigate associations between sarcopenia and brain atrophy in older adults and relationships with regional brain areas. This prospective cohort study recruited 102 retirement community residents aged 65years and older. All participants underwent gait speed measurement, handgrip strength measurement and muscle mass measurement by dual X-ray absorptiometry. Diagnosis of sarcopenia was made according to criteria of the Asian Working Group for Sarcopenia (AWGSOP). All patients underwent magnetic resonance imaging (MRI), and images were analysed for global cortical atrophy (GCA) (range 0-3), parietal atrophy (PA) (range 0-3) and medial temporal atrophy (MTA) (range 0-4). Among 102 older adult participants (81.4±8.2years), 47 (46.1%) were diagnosed with sarcopenia according to AWGSOP criteria. The sarcopenia group had more moderate to severe PA (Grade 2: 19.1% vs. 5.5%; grade 3:6.4% vs. 0%, P=0.016) and GCA (Grade 2: 40.4% vs. 18.2%, P=0.003) and a trend of more moderate to severe MTA (Grade 2: 46.8% vs. 30.9%; grade 3: 8.5% vs. 1.8%, P=0.098) than the non-sarcopenia group. In univariate logistic regression, sarcopenia was significantly associated with PA (OR 5.94, 95% CI 1.56-22.60, P=0.009), GCA (OR 3.05, 95% CI 1.24-7.51, P=0.015), and MTA (OR 2.55, 95% CI 1.14-5.69, P=0.023). In multivariable logistic regression analysis, sarcopenia was an independent risk factor for PA (adjusted OR 6.90, 95% CI 1.30-36.47, P=0.023). After adjusting for all covariates, only age had a significant relationship with GCA (Adjusted OR 1.09, 95% CI 1.00-1.19, P=0.044) and MTA (Adjusted OR 1.09, 95% CI 1.01-1.17, P=0.022). This is the first study to explore associations between sarcopenia and global as well as regional brain atrophy in older adults. The sarcopenia group had higher rates of moderate to severe PA, GCA and MTA than the non-sarcopenia group. PA was significantly associated with sarcopenia in older adults. Further longitudinal studies are needed to address the mechanism and pathogenesis of brain atrophy and sarcopenia.

Entorhinal Perfusion Predicts Future Memory Decline, Neurodegeneration, and White Matter Hyperintensity Progression in Older Adults.

Altered cerebral blood flow (CBF) has been linked to increased risk for Alzheimer's disease (AD). However, whether altered CBF contributes to AD risk by accelerating cognitive decline remains unclear. It also remains unclear whether reductions in CBF accelerate neurodegeneration and development of small vessel cerebrovascular disease. To examine associations between CBF and trajectories of memory performance, regional brain atrophy, and global white matter hyperintensity (WMH) volume. 147 Alzheimer's Disease Neuroimaging Initiative participants free of dementia underwent arterial spin labeling (ASL) magnetic resonance imaging (MRI) to measure CBF and serial neuropsychological and structural MRI examinations. Linear mixed effects models examined 5-year rate of change in memory and 4-year rate of change in regional brain atrophy and global WMH volumes as a function of baseline regional CBF. Entorhinal and hippocampal CBF were examined in separate models. Adjusting for demographic characteristics, pulse pressure, apolipoprotein E ɛ4 positivity, cerebrospinal fluid p-tau/Aβ ratio, and neuronal metabolism (i.e., fluorodeoxyglucose standardized uptake value ratio), lower baseline entorhinal CBF predicted faster rates of decline in memory as well as faster entorhinal thinning and WMH progression. Hippocampal CBF did not predict cognitive or brain structure trajectories. Findings highlight the importance of early cerebrovascular dysfunction in AD risk and suggest that entorhinal CBF as measured by noninvasive ASL MRI is a useful biomarker predictive of future cognitive decline and of risk of both.

SvReg: Structural varying-coefficient regression to differentiate how regional brain atrophy affects motor impairment for Huntington disease severity groups.

For Huntington disease, identification of brain regions related to motor impairment can be useful for developing interventions to alleviate the motor symptom, the major symptom of the disease. However, the effects from the brain regions to motor impairment may vary for different groups of patients. Hence, our interest is not only to identify the brain regions but also to understand how their effects on motor impairment differ by patient groups. This can be cast as a model selection problem for a varying-coefficient regression. However, this is challenging when there is a pre-specified group structure among variables. We propose a novel variable selection method for a varying-coefficient regression with such structured variables and provide a publicly available R package svreg for implementation of our method. Our method is empirically shown to select relevant variables consistently. Also, our method screens irrelevant variables better than existing methods. Hence, our method leads to a model with higher sensitivity, lower false discovery rate and higher prediction accuracy than the existing methods. Finally, we found that the effects from the brain regions to motor impairment differ by disease severity of the patients. To the best of our knowledge, our study is the first to identify such interaction effects between the disease severity and brain regions, which indicates the need for customized intervention by diseaseseverity.

Linear brain atrophy measures in multiple sclerosis and clinically isolated syndromes: a 30-year follow-up

ObjectiveTo determine 30-year brain atrophy rates following clinically isolated syndromes and the relationship of atrophy in the first 5 years and clinical outcomes 25 years later.MethodsA cohort of 132 people...

Midbrain atrophy related to parkinsonism in a non-coding repeat expansion disorder: five cases of spinocerebellar ataxia type 31 with nigrostriatal dopaminergic dysfunction

BackgroundSpinocerebellar ataxia type 31 (SCA31) is caused by non-coding pentanucleotide repeat expansions in the BEAN1 gene. Clinically, SCA31 is characterized by late adult-onset, pure cerebellar ataxia. To explore the association between parkinsonism and SCA31, five patients with SCA31 with concomitant nigrostriatal dopaminergic dysfunction (NSDD) development, including three cases of L-DOPA responsive parkinsonism, were analyzed.MethodsTo assess regional brain atrophy, cross-sectional and longitudinal imaging analyses were retrospectively performed using magnetic resonance imaging (MRI) planimetry. The midbrain-to-pons (M/P) area ratio and cerebellar area were measured on midsagittal T1-weighted MRI in five patients with SCA31 with concomitant NSDD (NSDD(+)), 14 patients with SCA31 without NSDD (NSDD(−)), 32 patients with Parkinson’s disease (PD), and 15 patients with progressive supranuclear palsy (PSP). Longitudinal changes in the M/P area ratio were assessed by serial MRI of NSDD(+) (n = 5) and NSDD(−) (n = 9).ResultsThe clinical characteristics assessed in the five patients with NSDD were as follows: the mean age at NSDD onset (72.0 ± 10.8 years), prominence of bradykinesia/akinesia (5/5), rigidity (4/5), tremor (2/5), dysautonomia (0/5), vertical gaze limitation (1/5), and abnormalities on 123I-ioflupane dopamine transporter scintigraphy (3/3) and 3-Tesla neuromelanin MRI (4/4). A clear reduction in the midbrain area and the M/P area ratio was observed in the NSDD(+) group (p < 0.05) while there was no significant difference in disease duration or in the pons area among the NSDD(+), NSDD(−), and PD groups. There was also a significant difference in the midbrain and pons area between NSDD(+) and PSP (p < 0.05). Thus, mild but significant midbrain atrophy was observed in NSDD(+). A faster rate of decline in the midbrain area and the M/P area ratio was evident in NSDD(+) (p < 0.05).ConclusionThe clinical characteristics of the five patients with SCA31 with concomitant NSDD, together with the topographical pattern of atrophy, were inconsistent with PD, PSP, and multiple system atrophy, suggesting that SCA31 may manifest NSDD in association with the pathomechanisms underlying SCA31.

Associations of Brain Atrophy and Cerebral Iron Accumulation at MRI with Clinical Severity in Wilson Disease.

Background Abnormal findings at brain MRI in patients with neurologic Wilson disease (WD) are characterized by signal intensity changes and cerebral atrophy. T2 signal hypointensities and atrophy are largely irreversible with treatment; their relationship with permanent disability has not been systematically investigated. Purpose To investigate associations of regional brain atrophy and iron accumulation at MRI with clinical severity in participants with neurologic WD who are undergoing long-term anti-copper treatment. Materials and Methods Participants with WD and controls were compared in a prospective study performed from 2015 to 2019. MRI at 3.0 T included three-dimensional T1-weighted and six-echo multigradient-echo pulse sequences for morphometry and quantitative susceptibility mapping, respectively. Neurologic severity was assessed with the Unified WD Rating Scale (UWDRS). Automated multi-atlas segmentation pipeline with dual contrast (susceptibility and T1) was used for the calculation of volumes and mean susceptibilities in deep gray matter nuclei. Additionally, whole-brain analysis using deformation and surface-based morphometry was performed. Least absolute shrinkage and selection operator regression was used to assess the association of regional volumes and susceptibilities with the UWDRS score. Results Twenty-nine participants with WD (mean age, 47 years ± 9 [standard deviation]; 15 women) and 26 controls (mean age, 45 years ± 12; 14 women) were evaluated. Whole-brain analysis demonstrated atrophy of the deep gray matter nuclei, brainstem, internal capsule, motor cortex and corticospinal pathway, and visual cortex and optic radiation in participants with WD (P < .05 at voxel level, corrected for family-wise error). The UWDRS score was negatively correlated with volumes of putamen (r = -0.63, P < .001), red nucleus (r = -0.58, P = .001), globus pallidus (r = -0.53, P = .003), and substantia nigra (r = -0.50, P = .006) but not with susceptibilities. Only the putaminal volume was identified as a stable factor associated with the UWDRS score (R2 = 0.38, P < .001) using least absolute shrinkage and selection operator regression. Conclusion Individuals with Wilson disease (WD) had widespread brain atrophy most pronounced in the central structures. The putaminal volume was associated with the Unified WD Rating Scale score and can be used as a surrogate imaging marker of clinical severity. © RSNA, 2021 Supplemental material is available for this article. See also the editorial by Du and Bydder in this issue.

Clinical utility of brain computed tomography in prediction of post-stroke delirium.

Delirium is a common and serious complication of stroke. Early prediction of delirium is important for preventive strategies and close monitoring of high-risk patients. Pre-existing degenerative and vascular changes in the brain could predispose to delirium. We aimed to determine if computed tomography (CT)-based indices could provide additional information about a risk of stroke-associated delirium beyond easiest-to-access clinical predictors. Using semi-quantitative scales (global cortical atrophy, age-related white matter changes, and Scheltens scale), we assessed global and regional brain atrophy and white matter changes in 88 stroke patients with delirium and 142 patients without delirium matched for age and stroke severity. Patients with delirium had greater global and local brain atrophy (the right temporal region, the left parieto-occipital region, the right frontal and occipital horn, and the right and left temporal horn) than patients without delirium. Scores of white matter changes did not differ between groups with exception of greater white matter damage in the right parieto-occipital area in patients with delirium. The discriminatory properties of studied radiological indices were modest (areas under receiver operator curves: 0.58-0.64). CT-based indices of brain atrophy and white matter changes do not provide additional information about a risk of post-stroke delirium beyond the most important clinical predictors.

Relationship Between Interpersonal Depressive Symptoms and Reduced Amygdala Volume in People with Multiple Sclerosis: Considerations for Clinical Practice.

The lifetime prevalence of depression in people with multiple sclerosis (MS) is approximately 50% compared with around 15% in the general population. There is a relationship between depression and quality of life in people with MS and evidence that depression may contribute to disease progression. This cross-sectional pilot study assessed the association between depression and regional brain atrophy, including amygdala and hippocampal volume. Forty-nine participants with MS recruited through a hospital MS clinic were administered the Center for Epidemiological Studies Depression Scale Revised (CESD-R) to investigate whether higher endorsements on the items depressive affect and interpersonal symptoms were associated with volumetric magnetic resonance imaging measurements of hippocampal and amygdala atrophy. Regression analysis revealed an association between depression-related interpersonal symptoms and right amygdala volume. No association was found between depression and hippocampal volume. These results provide preliminary support for a unilateral, biologically based relationship between the right amygdala and characteristic interpersonal depressive symptoms expressed by people with MS and add to the growing body of literature implicating regional brain atrophy in MS-associated depression. Given that the interpersonal subcomponent of the CESD-R measures social functioning, and the neural networks in the amygdala are known to be implicated in processing social stimuli, this research suggests that targeted diagnosis and treatments for depression in people with MS may be particularly beneficial. Further confirmatory research of this relationship is required.

Correlation between regional brain atrophy, cognitive function, adipose tissue and CSF biomarkers in mild cognitive impairment

AbstractBackgroundCharacterization of mild cognitive impairment (MCI) for clinical and research purposes involves identification of biological and neuropsychological markers in order to predict possible progression to dementia. The main aim of this work was to analyze the correlation of anthropometric measurements and plasmatic levels of leptin, testosterone and estrogens with cognitive, CSF and MRI regional atrophy markers in a sample of MCI participants.MethodsEighty‐one patients from the Compostela Aging Study diagnosed as MCI according to the Petersen criteria (Petersen, 2004; Albert et al., 2011) underwent neuropsychological assessment (CAMCOG‐R memory, CVLT short and long delayed free recall, subjective memory complains), CSF (Aβ42, t‐Tau and p‐Tau) and plasmatic analyses as well as an MRI study (parahippocampal and entorhinal cortex thickness measurements) (Table 1). Spearman’s correlation was used to evaluate the relationship between anthropometric measurements and blood test results with memory scores, CSF and MRI regional atrophy markers.ResultsEpisodic memory scores correlated with CSF measurements (Aβ42, t‐Tau, p‐Tau) and parahippocampal and entorhinal cortical thickness (right and left) (Table 2). BMI, suprailiac, pectoral and subscapular skinfolds, circumference of waist, hip, arm and calf were negatively correlated with t‐Tau and p‐Tau levels. BMI, triccipital, thigh and pectoral skin folds as well as calf circumference were positively correlated with parahippocampal and entorhinal cortical thickness. Suprailiac, triccipital and thigh skin folds were positively correlated with episodic memory scores. Leptin plasma levels showed a negative correlation with CSF biomarkers (t‐Tau and p‐Tau) and a positive correlation with parahippocampal cortex thickness. Testosterone and estradiol levels showed a negative correlation with scores on memory tests and enthorhinal cortical thickness.ConclusionsOur findings suggest that body composition is associated with episodic memory function, CSF biomarkers and cortical atrophy in patients with MCI. Leptin levels and sexual hormones may play a role in this association. These results point to a role of fat tissue and its regulating mechanisms in AD pathology and progression from MCI to dementia.