Improve the diagnosis of idiopathic normal pressure hydrocephalus by combining abnormal cortical thickness and ventricular morphometry

Background

The primary imaging markers for idiopathic Normal Pressure Hydrocephalus (iNPH) emphasize morphological measurements within the ventricular system, with no attention given to alterations in brain parenchyma. This study aimed to investigate the potential effectiveness of combining ventricular morphometry and cortical structural measurements as diagnostic biomarkers for iNPH.

Methods

A total of 57 iNPH patients and 55 age-matched healthy controls (HC) were recruited in this study. Firstly, manual measurements of ventricular morphology, including Evans Index (EI), z-Evans Index (z-EI), Cella Media Width (CMW), Callosal Angle (CA), and Callosal Height (CH), were conducted based on MRI scans. Cortical thickness measurements were obtained, and statistical analyses were performed using surface-based morphometric analysis. Secondly, three distinct models were developed using machine learning algorithms, each based on a different input feature: a ventricular morphology model (LVM), a cortical thickness model (CT), and a fusion model (All) incorporating both features. Model performances were assessed using 10-fold cross validation and tested on an independent dataset. Model interpretation utilized Shapley Additive Interpretation (SHAP), providing a visualization of the contribution of each variable in the predictive model. Finally, Spearman correlation coefficients were calculated to evaluate the relationship between imaging biomarkers and clinical symptoms.

Results

iNPH patients exhibited notable differences in cortical thickness compared to HC. This included reduced thickness in the frontal, temporal, and cingulate cortices, along with increased thickness in the supracentral gyrus. The diagnostic performance of the fusion model (All) for iNPH surpassed that of the single-feature models, achieving an average accuracy of 90.43%, sensitivity of 90.00%, specificity of 90.91%, and Matthews correlation coefficient (MCC) of 81.03%. This improvement in accuracy (6.09%), sensitivity (11.67%), and MCC (11.25%) compared to the LVM strategy was significant. Shap analysis revealed the crucial role of cortical thickness in the right isthmus cingulate cortex, emerging as the most influential factor in distinguishing iNPH from HC. Additionally, significant correlations were observed between the typical triad symptoms of iNPH patients and cortical structural alterations.

Conclusion

This study emphasizes the significant role of cortical structure changes in the diagnosis of iNPH, providing a novel insights for assisting clinicians in improving the identification and detection of iNPH.

A cross-sectional observational study for ethno-geographical disparities in sleep quality, brain morphometry and cognition (a SOLACE study) in Indians residing in India, and South Asians and Europeans residing in the UK - a study protocol

Introduction

As individuals age, their sleep patterns change, and sleep disturbances can increase the risk of dementia. Poor sleep quality can be a risk factor for mild cognitive impairment (MCI) and dementia. Epidemiological studies show a connection between sleep quality and cognitive changes, with brain imaging revealing grey matter volume reduction and amyloid beta accumulation in Alzheimer's disease. However, most research has focused on Europeans, with little attention to other ethnic groups.

Methods

This is a cross sectional study comparing effects across countries and ethnicities. Group 1 (n = 193) will be Indians residing in India (new participant recruitment), Group 2 will be South Asians residing in UK and group 3 will be Europeans residing in the UK. For group 2 and 3 (n = 193), data already collected by UK-based Southall and Brent REvisited (SABRE) tri-ethnic study will be used. For group 1, Pittsburgh Sleep Quality Index questionnaire (PSQI) will be used for assessment of sleep quality, Indian Council of Medical Research (Neurocognitive ToolBox) (ICMR-NCTB) for cognition testing and a 3 T MRI cerebral scan for brain morphometry. The data will be compared to sleep, cognitive function and brain MRI parameters from SABRE.

Discussion

Racial and ethnic differences can impact the relationships of cognitive function, sleep quality and brain structure in older adults. Earlier studies have highlighted higher prevalence of poor sleep among black individuals compared to white individuals. Genetic or epigenetic mechanisms may contribute to these variations. Socio-cultural and environmental factors, such as neighbourhood, migration, lifestyle, stress and perceived discrimination may influence sleep patterns. The aim of the study is to examine the ethnogeographic variations in sleep quality, cognitive performance and brain morphometry among Indians living in India, and South Asians and Europeans residing in the UK.

Independent and combined effects of methamphetamine use disorders and APOEε4 allele on cognitive performance and brain morphometry

AIMS

Prior studies showed that methamphetamine (METH) users had greater than normal age-related brain atrophy; whether having the apolipoprotein E (APOE)-ε4 allele may be a contributory factor has not been evaluated. We aimed to determine the independent and combined effects of chronic heavy METH use and having at least one copy of the APOE-ε4 allele (APOE-ε4+) on brain morphometry and cognition, especially in relation to aging.

METHODS

We compared brain morphometry and cognitive performance in 77 individuals with chronic heavy METH use (26 APOE-ε4+, 51 APOE-ε4-) and 226 Non-METH users (66 APOE-ε4+, 160 APOE-ε4-), using a 2 × 2 design (two-way analysis of co-variance). Vertex-wise cortical volumes, thickness and seven subcortical volumes, were automatically measured using FreeSurfer. Linear regression between regional brain measures, and cognitive scores that showed group differences were evaluated. Group differences in age-related decline in brain and cognitive measures were also explored.

RESULTS

Regardless of APOE-ε4 genotype, METH users had lower Motor Z-scores (P = 0.005), thinner right lateral-orbitofrontal cortices (P < 0.001), smaller left pars-triangularis gyrus volumes (P = 0.004), but larger pallida, hippocampi and amygdalae (P = 0.004-0.006) than nonusers. Across groups, APOE-ε4+ METH users had the smallest volumes of superior frontal cortical gyri bilaterally, and of the smallest volume in left rostral-middle frontal gyri (all P-values <0.001). Smaller right superior-frontal gyrus predicted poorer motor function only in APOE-ε4+ participants (interaction-P < 0.001). Cortical volumes and thickness declined with age similarly across all participants; however, APOE-ε4-carriers showed thinner right inferior parietal cortices than noncarriers at younger age (interaction-P < 0.001).

CONCLUSIONS

Chronic heavy use and having at least one copy of the APOE-ε4 allele may have synergistic effects on brain atrophy, particularly in frontal cortices, which may contribute to their poorer cognitive function. However, the enlarged subcortical volumes in METH users replicated prior studies, and are likely due to METH-mediated neuroinflammation.

Brain structural changes in blindness: a systematic review and an anatomical likelihood estimation (ALE) meta-analysis

In recent decades, numerous structural brain imaging studies investigated purported morphometric changes in early (EB) and late onset blindness (LB). The results of these studies have not yielded very consistent results, neither with respect to the type, nor to the anatomical locations of the brain morphometric alterations. To better characterize the effects of blindness on brain morphometry, we performed a systematic review and an Anatomical-Likelihood-Estimation (ALE) coordinate-based-meta-analysis of 65 eligible studies on brain structural changes in EB and LB, including 890 EB, 466 LB and 1257 sighted controls. Results revealed atrophic changes throughout the whole extent of the retino-geniculo-striate system in both EB and LB, whereas changes in areas beyond the occipital lobe occurred in EB only. We discuss the nature of some of the contradictory findings with respect to the used brain imaging methodologies and characteristics of the blind populations such as the onset, duration and cause of blindness. Future studies should aim for much larger sample sizes, eventually by merging data from different brain imaging centers using the same imaging sequences, opt for multimodal structural brain imaging, and go beyond a purely structural approach by combining functional with structural connectivity network analyses.

Patterns of structure-function association in normal aging and in Alzheimer's disease: Screening for mild cognitive impairment and dementia with ML regression and classification models

Background

The combined analysis of imaging and functional modalities is supposed to improve diagnostics of neurodegenerative diseases with advanced data science techniques.

Objective

To get an insight into normal and accelerated brain aging by developing the machine learning models that predict individual performance in neuropsychological and cognitive tests from brain MRI. With these models we endeavor to look for patterns of brain structure-function association (SFA) indicative of mild cognitive impairment (MCI) and Alzheimer's dementia.

Materials and methods

We explored the age-related variability of cognitive and neuropsychological test scores in normal and accelerated aging and constructed regression models predicting functional performance in cognitive tests from brain radiomics data. The models were trained on the three study cohorts from ADNI dataset-cognitively normal individuals, patients with MCI or dementia-separately. We also looked for significant correlations between cortical parcellation volumes and test scores in the cohorts to investigate neuroanatomical differences in relation to cognitive status. Finally, we worked out an approach for the classification of the examinees according to the pattern of structure-function associations into the cohorts of the cognitively normal elderly and patients with MCI or dementia.

Results

In the healthy population, the global cognitive functioning slightly changes with age. It also remains stable across the disease course in the majority of cases. In healthy adults and patients with MCI or dementia, the trendlines of performance in digit symbol substitution test and trail making test converge at the approximated point of 100 years of age. According to the SFA pattern, we distinguish three cohorts: the cognitively normal elderly, patients with MCI, and dementia. The highest accuracy is achieved with the model trained to predict the mini-mental state examination score from voxel-based morphometry data. The application of the majority voting technique to models predicting results in cognitive tests improved the classification performance up to 91.95% true positive rate for healthy participants, 86.21%-for MCI and 80.18%-for dementia cases.

Conclusion

The machine learning model, when trained on the cases of this of that group, describes a disease-specific SFA pattern. The pattern serves as a "stamp" of the disease reflected by the model.

Neuroimaging alterations of the suicidal brain and its relevance to practice: an updated review of MRI studies

Suicide is a leading cause of death in the United States. Historically, scientific inquiry has focused on psychological theory. However, more recent studies have started to shed light on complex biosignatures using MRI techniques, including task-based and resting-state functional MRI, brain morphometry, and diffusion tensor imaging. Here, we review recent research across these modalities, with a focus on participants with depression and Suicidal Thoughts and Behavior (STB). A PubMed search identified 149 articles specific to our population of study, and this was further refined to rule out more diffuse pathologies such as psychotic disorders and organic brain injury and illness. This left 69 articles which are reviewed in the current study. The collated articles reviewed point to a complex impairment showing atypical functional activation in areas associated with perception of reward, social/affective stimuli, top-down control, and reward-based learning. This is broadly supported by the atypical morphometric and diffusion-weighted alterations and, most significantly, in the network-based resting-state functional connectivity data that extrapolates network functions from well validated psychological paradigms using functional MRI analysis. We see an emerging picture of cognitive dysfunction evident in task-based and resting state fMRI and network neuroscience studies, likely preceded by structural changes best demonstrated in morphometric and diffusion-weighted studies. We propose a clinically-oriented chronology of the diathesis-stress model of suicide and link other areas of research that may be useful to the practicing clinician, while helping to advance the translational study of the neurobiology of suicide.

Brain Age Prediction: A Comparison between Machine Learning Models Using Brain Morphometric Data

Brain structural morphology varies over the aging trajectory, and the prediction of a person's age using brain morphological features can help the detection of an abnormal aging process. Neuroimaging-based brain age is widely used to quantify an individual's brain health as deviation from a normative brain aging trajectory. Machine learning approaches are expanding the potential for accurate brain age prediction but are challenging due to the great variety of machine learning algorithms. Here, we aimed to compare the performance of the machine learning models used to estimate brain age using brain morphological measures derived from structural magnetic resonance imaging scans. We evaluated 27 machine learning models, applied to three independent datasets from the Human Connectome Project (HCP, n = 1113, age range 22-37), the Cambridge Centre for Ageing and Neuroscience (Cam-CAN, n = 601, age range 18-88), and the Information eXtraction from Images (IXI, n = 567, age range 19-86). Performance was assessed within each sample using cross-validation and an unseen test set. The models achieved mean absolute errors of 2.75-3.12, 7.08-10.50, and 8.04-9.86 years, as well as Pearson's correlation coefficients of 0.11-0.42, 0.64-0.85, and 0.63-0.79 between predicted brain age and chronological age for the HCP, Cam-CAN, and IXI samples, respectively. We found a substantial difference in performance between models trained on the same data type, indicating that the choice of model yields considerable variation in brain-predicted age. Furthermore, in three datasets, regularized linear regression algorithms achieved similar performance to nonlinear and ensemble algorithms. Our results suggest that regularized linear algorithms are as effective as nonlinear and ensemble algorithms for brain age prediction, while significantly reducing computational costs. Our findings can serve as a starting point and quantitative reference for future efforts at improving brain age prediction using machine learning models applied to brain morphometric data.

Reliable brain morphometry from contrast-enhanced T1w-MRI in patients with multiple sclerosis

Brain morphometry is usually based on non-enhanced (pre-contrast) T1-weighted MRI. However, such dedicated protocols are sometimes missing in clinical examinations. Instead, an image with a contrast agent is often available. Existing tools such as FreeSurfer yield unreliable results when applied to contrast-enhanced (CE) images. Consequently, these acquisitions are excluded from retrospective morphometry studies, which reduces the sample size. We hypothesize that deep learning (DL)-based morphometry methods can extract morphometric measures also from contrast-enhanced MRI. We have extended DL+DiReCT to cope with contrast-enhanced MRI. Training data for our DL-based model were enriched with non-enhanced and CE image pairs from the same session. The segmentations were derived with FreeSurfer from the non-enhanced image and used as ground truth for the coregistered CE image. A longitudinal dataset of patients with multiple sclerosis (MS), comprising relapsing remitting (RRMS) and primary progressive (PPMS) subgroups, was used for the evaluation. Global and regional cortical thickness derived from non-enhanced and CE images were contrasted to results from FreeSurfer. Correlation coefficients of global mean cortical thickness between non-enhanced and CE images were significantly larger with DL+DiReCT (r = 0.92) than with FreeSurfer (r = 0.75). When comparing the longitudinal atrophy rates between the two MS subgroups, the effect sizes between PPMS and RRMS were higher with DL+DiReCT both for non-enhanced (d = -0.304) and CE images (d = -0.169) than for FreeSurfer (non-enhanced d = -0.111, CE d = 0.085). In conclusion, brain morphometry can be derived reliably from contrast-enhanced MRI using DL-based morphometry tools, making additional cases available for analysis and potential future diagnostic morphometry tools.

A comparison of intracranial volume estimation methods and their cross-sectional and longitudinal associations with age

Intracranial volume (ICV) is frequently used in volumetric magnetic resonance imaging (MRI) studies, both as a covariate and as a variable of interest. Findings of associations between ICV and age have varied, potentially due to differences in ICV estimation methods. Here, we compared five commonly used ICV estimation methods and their associations with age. T1-weighted cross-sectional MRI data was included for 651 healthy individuals recruited through the NORMENT Centre (mean age = 46.1 years, range = 12.0-85.8 years) and 2410 healthy individuals recruited through the UK Biobank study (UKB, mean age = 63.2 years, range = 47.0-80.3 years), where longitudinal data was also available. ICV was estimated with FreeSurfer (eTIV and sbTIV), SPM12, CAT12, and FSL. We found overall high correlations across ICV estimation method, with the lowest observed correlations between FSL and eTIV (r = .87) and between FSL and CAT12 (r = .89). Widespread proportional bias was found, indicating that the agreement between methods varied as a function of head size. Body weight, age, sex, and mean ICV across methods explained the most variance in the differences between ICV estimation methods, indicating possible confounding for some estimation methods. We found both positive and negative cross-sectional associations with age, depending on dataset and ICV estimation method. Longitudinal ICV reductions were found for all ICV estimation methods, with annual percentage change ranging from -0.293% to -0.416%. This convergence of longitudinal results across ICV estimation methods offers strong evidence for age-related ICV reductions in mid- to late adulthood.

Cognitive efficacy and neural mechanisms of music-based neurological rehabilitation for traumatic brain injury

Traumatic brain injury (TBI) causes lifelong cognitive deficits, most often in executive function (EF). Both musical training and music-based rehabilitation have been shown to enhance EF and neuroplasticity. Thus far, however, there is little evidence for the potential rehabilitative effects of music for TBI. Here, we review the core findings from our recent cross-over randomized controlled trial in which a 10-week music-based neurological rehabilitation (MBNR) protocol was administered to 40 patients with moderate-to-severe TBI. Neuropsychological testing and structural/functional magnetic resonance imaging were collected at three time points (baseline, 3 months, and 6 months); one group received the MBNR between time points 1 and 2, while a second group received it between time points 2 and 3. We found that both general EF and set shifting improved after the intervention, and this effect was maintained long term. Morphometric analyses revealed therapy-induced gray matter volume changes most consistently in the right inferior frontal gyrus, changes that correlated with better outcomes in set shifting. Finally, we found changes in the between- and within-network functional connectivity of large-scale resting-state networks after MBNR, which also correlated with measures of EF. Taken together, the data provide evidence for concluding that MBNR improves EF in TBI; also, the data show that morphometric and resting-state functional connectivity are sensitive markers with which to monitor the neuroplasticity induced by the MBNR intervention.

Experimental Pain Phenotype Profiles in Community-dwelling Older Adults

OBJECTIVES

Pain sensitivity and the brain structure are critical in modulating pain and may contribute to the maintenance of pain in older adults. However, a paucity of evidence exists investigating the link between pain sensitivity and brain morphometry in older adults. The purpose of the study was to identify pain sensitivity profiles in healthy, community-dwelling older adults using a multimodal quantitative sensory testing protocol and to differentiate profiles based on brain morphometry.

MATERIALS AND METHODS

This study was a secondary analysis of the Neuromodulatory Examination of Pain and Mobility Across the Lifespan (NEPAL) study. Participants completed demographic and psychological questionnaires, quantitative sensory testing, and a neuroimaging session. A Principal Component Analysis with Varimax rotation followed by hierarchical cluster analysis identified 4 pain sensitivity clusters (the "pain clusters").

RESULTS

Sixty-two older adults ranging from 60 to 94 years old without a specific pain condition (mean [SD] age=71.44 [6.69] y, 66.1% female) were analyzed. Four pain clusters were identified characterized by (1) thermal pain insensitivity; (2) high pinprick pain ratings and pressure pain insensitivity; (3) high thermal pain ratings and high temporal summation; and (4) thermal pain sensitivity, low thermal pain ratings, and low mechanical temporal summation. Sex differences were observed between pain clusters. Pain clusters 2 and 4 were distinguished by differences in the brain cortical volume in the parieto-occipital region.

DISCUSSION

While sufficient evidence exists demonstrating pain sensitivity profiles in younger individuals and in those with chronic pain conditions, the finding that subgroups of experimental pain sensitivity also exist in healthy older adults is novel. Identifying these factors in older adults may help differentiate the underlying mechanisms contributing to pain and aging.

Brain Morphometry and Cognitive Performance in Normal Brain Aging: Age- and Sex-Related Structural and Functional Changes

BACKGROUND

The human brain structure undergoes considerable changes throughout life. Cognitive function can be affected either negatively or positively. It is challenging to segregate normal brain aging from the accelerated one.

OBJECTIVE

To work out a descriptive model of brain structural and functional changes in normal aging.

MATERIALS AND METHODS

By using voxel-based morphometry and lesion segmentation along with linear statistics and machine learning (ML), we analyzed the structural changes in the major brain compartments and modeled the dynamics of neurofunctional performance throughout life. We studied sex differences in lifelong dynamics of brain volumetric data with Mann-Whitney U-test. We tested the hypothesis that performance in some cognitive domains might decline as a linear function of age while other domains might have a non-linear dependence on it. We compared the volumetric changes in the major brain compartments with the dynamics of psychophysiological performance in 4 age groups. Then, we tested linear models of structural and functional decline for significant differences between the slopes in age groups with the T-test.

RESULTS

White matter hyperintensities (WMH) are not the major structural determinant of the brain normal aging. They should be viewed as signs of a disease. There is a sex difference in the speed and/or in the onset of the gray matter atrophy. It either starts earlier or goes faster in males. Marked sex difference in the proportion of total cerebrospinal fluid (CSF) and intraventricular CSF (iCSF) justifies that elderly men are more prone to age-related brain atrophy than women of the same age.

CONCLUSION

The article gives an overview and description of the conceptual structural changes in the brain compartments. The obtained data justify distinct patterns of age-related changes in the cognitive functions. Cross-life slowing of decision-making may follow the linear tendency of enlargement of the interhemispheric fissure because the center of task switching and inhibitory control is allocated within the medial wall of the frontal cortex, and its atrophy accounts for the expansion of the fissure. Free online tool at https://med-predict.com illustrates the tests and study results.

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.

Improving the Quantification of the Lateral Geniculate Nucleus in Magnetic Resonance Imaging Using a Novel 3D-Edge Enhancement Technique

The lateral geniculate nucleus (LGN) is a small, inhomogeneous structure that relays major sensory inputs from the retina to the visual cortex. LGN morphology has been intensively studied due to various retinal diseases, as well as in the context of normal brain development. However, many of the methods used for LGN structural evaluations have not adequately addressed the challenges presented by the suboptimal routine MRI imaging of this structure. Here, we propose a novel method of edge enhancement that allows for high reliability and accuracy with regard to LGN morphometry, using routine 3D-MRI imaging protocols. This new algorithm is based on modeling a small brain structure as a polyhedron with its faces, edges, and vertices fitted with one plane, the intersection of two planes, and the intersection of three planes, respectively. This algorithm dramatically increases the contrast-to-noise ratio between the LGN and its surrounding structures as well as doubling the original spatial resolution. To show the algorithm efficacy, two raters (MA and ML) measured LGN volumes bilaterally in 19 subjects using the edge-enhanced LGN extracted areas from the 3D-T1 weighted images. The averages of the left and right LGN volumes from the two raters were 175 ± 8 and 174 ± 9 mm³, respectively. The intra-class correlations between raters were 0.74 for the left and 0.81 for the right LGN volumes. The high contrast edge-enhanced LGN images presented here, from a 7-min routine 3T-MRI acquisition, is qualitatively comparable to previously reported LGN images that were acquired using a proton density sequence with 30–40 averages and 1.5-h of acquisition time. The proposed edge-enhancement algorithm is not limited only to the LGN, but can significantly improve the contrast-to-noise ratio of any small deep-seated gray matter brain structure that is prone to high-levels of noise and partial volume effects, and can also increase their morphometric accuracy and reliability. An immensely useful feature of the proposed algorithm is that it can be used retrospectively on noisy and low contrast 3D brain images previously acquired as part of any routine clinical MRI visit.

Changes in Brain Volume Resulting from Cognitive Intervention by Means of the Feuerstein Instrumental Enrichment Program in Older Adults with Mild Cognitive Impairment (MCI): A Pilot Study

There is increasing interest in identifying biological and imaging markers for the early detection of neurocognitive decline. In addition, non-pharmacological strategies, including physical exercise and cognitive interventions, may be beneficial for those developing cognitive impairment. The Feuerstein Instrumental Enrichment (FIE) Program is a cognitive intervention based on structural cognitive modifiability and the mediated learning experience (MLE) and aims to promote problem-solving strategies and metacognitive abilities. The FIE program uses a variety of instruments to enhance the cognitive capacity of the individual as a result of mediation. A specific version of the FIE program was developed for the cognitive enhancement of older adults, focusing on strengthening orientation skills, categorization skills, deductive reasoning, and memory. We performed a prospective interventional pilot observational study on older subjects with MCI who participated in 30 mediated FIE sessions (two sessions weekly for 15 weeks). Of the 23 subjects who completed the study, there was a significant improvement in memory on the NeuroTrax cognitive assessment battery. Complete sets of anatomical MRI data for voxel-based morphometry, taken at the beginning and the end of the study, were obtained from 16 participants (mean age 83.5 years). Voxel-based morphometry showed an interesting and unexpected increase in grey matter (GM) in the anterolateral occipital border and the middle cingulate cortex. These initial findings of our pilot study support the design of randomized trials to evaluate the effect of cognitive training using the FIE program on brain volumes and cognitive function.

Altered Structural Covariance of Insula, Cerebellum and Prefrontal Cortex Is Associated with Somatic Symptom Levels in Irritable Bowel Syndrome (IBS)

Somatization, defined as the presence of multiple somatic symptoms, frequently occurs in irritable bowel syndrome (IBS) and may constitute the clinical manifestation of a neurobiological sensitization process. Brain imaging data was acquired with T1 weighted 3 tesla MRI, and gray matter morphometry were analyzed using FreeSurfer. We investigated differences in networks of structural covariance, based on graph analysis, between regional gray matter volumes in IBS-related brain regions between IBS patients with high and low somatization levels, and compared them to healthy controls (HCs). When comparing IBS low somatization (N = 31), IBS high somatization (N = 35), and HCs (N = 31), we found: (1) higher centrality and neighbourhood connectivity of prefrontal cortex subregions in IBS high somatization compared to healthy controls; (2) higher centrality of left cerebellum in IBS low somatization compared to both IBS high somatization and healthy controls; (3) higher centrality of the anterior insula in healthy controls compared to both IBS groups, and in IBS low compared to IBS high somatization. The altered structural covariance of prefrontal cortex and anterior insula in IBS high somatization implicates that prefrontal processes may be more important than insular in the neurobiological sensitization process associated with IBS high somatization.

Whole-brain morphometry in Canadian soldiers with posttraumatic stress disorder

Patients with posttraumatic stress disorder (PTSD) display several structural brain differences when compared with healthy individuals. However, findings are particularly inconsistent for soldiers with PTSD. Here, we characterized the brain morphometry of 37 soldiers from the Canadian Armed Forces with adulthood war-related PTSD using structural magnetic resonance imaging. We assessed time since trauma, as well as PTSD, depressive, and anxiety symptoms with the Modified PTSD Symptoms Scale, Beck Depression Inventory, and Beck Anxiety Inventory, respectively. Whole-brain morphometry was extracted with FreeSurfer and compared with a validated normative database of more than 2700 healthy individuals. Volume and thickness from several regions differed from the norms. Frontal regions were smaller and thinner, particularly the superior and rostral middle frontal gyri. Furthermore, smaller left rostral middle frontal gyrus, left pericalcarine cortex, and right fusiform gyrus were associated with more recent trauma. All subcortical structures were bigger, except the hippocampus. These findings suggest a particular brain morphometric signature of PTSD in soldiers. Smaller and thinner frontal and larger subcortical regions support impaired top-down and/or downregulation of emotional response in PTSD. Finally, the correlation of smaller frontal, temporal, and occipital regions with more recent trauma might inform future therapeutic approaches.

Changes in brain morphometry after motor rehabilitation in chronic stroke

PURPOSE

Recent studies have revealed structural changes after motor rehabilitation, but its morphological changes related to upper limb motor behaviours have not been studied exhaustively. Therefore, we aimed to map the grey matter (GM) changes associated with motor rehabilitation after stroke using voxel-based morphometry (VBM), deformation-based morphometry (DBM), and surface-based morphometry (SBM).

METHODS

Forty-one patients with chronic stroke received twelve sessions of low-frequency repetitive transcranial magnetic stimulation plus intensive occupational therapy. MRI data were obtained before and after the intervention. Fugl-Meyer Assessment and Wolf Motor Function Test-Functional Ability Scale were assessed at the two-time points. We performed VBM, DBM, and SBM analyses using T1-weighted images. A correlation analysis was performed between cortical thickness in motor areas and clinical outcomes.

RESULTS

Clinical outcomes significantly improved after the intervention. VBM showed significant GM volume changes in ipsilesional and contralesional primary motor regions. DBM results demonstrated GM changes contralesionally and ipsilesionally after the intervention. SBM results showed significant cortical thickness changes in posterior visuomotor coordination, precentral, postcentral gyri of the ipsilesional hemisphere and contralesional visuomotor area after the intervention. A combination of threshold p < .05, False Discovery Rate and p < .001 (uncorrected) were considered significant. In addition, cortical thickness changes of the ipsilesional motor areas were significantly correlated with the clinical outcome changes.

CONCLUSIONS

We found GM structural changes in areas involved in motor, visuomotor and somatosensory functions after the intervention. Furthermore, our findings suggest that structural plasticity changes in chronic stroke could occur in the ipsilesional and contralesional hemispheres after motor rehabilitation.

A Simulation Toolkit for Testing the Sensitivity and Accuracy of Corticometry Pipelines

In recent years, the replicability of neuroimaging findings has become an important concern to the research community. Neuroimaging pipelines consist of myriad numerical procedures, which can have a cumulative effect on the accuracy of findings. To address this problem, we propose a method for simulating artificial lesions in the brain in order to estimate the sensitivity and specificity of lesion detection, using different automated corticometry pipelines. We have applied this method to different versions of two widely used neuroimaging pipelines (CIVET and FreeSurfer), in terms of coefficients of variation; sensitivity and specificity of detecting lesions in 4 different regions of interest in the cortex, while introducing variations to the lesion size, the blurring kernel used prior to statistical analyses, and different thickness metrics (in CIVET). These variations are tested in a between-subject design (in two random groups, with and without lesions, using T1-weigted MRIs of 152 individuals from the International Consortium of Brain Mapping (ICBM) dataset) and in a within-subject pre-/post-lesion design [using 21 T1-Weighted MRIs of a single adult individual, scanned in the Infant Brain Imaging Study (IBIS)]. The simulation method is sensitive to partial volume effect and lesion size. Comparisons between pipelines illustrate the ability of this method to uncover differences in sensitivity and specificity of lesion detection. We propose that this method be adopted in the workflow of software development and release.

The morphometry of left cuneus mediating the genetic regulation on working memory

Working memory is a basic human cognitive function. However, the genetic signatures and their biological pathway remain poorly understood. In the present study, we tried to clarify this issue by exploring the potential associations and pathways among genetic variants, brain morphometry and working memory performance. We first carried out association analyses between 2‐back accuracy and 212 image‐derived phenotypes from 1141 Human Connectome Project (HCP) subjects using a linear mixed model (LMM). We found a significantly positive correlation between the left cuneus volume and 2‐back accuracy (T = 3.615, p = 3.150e−4, Cohen's d = 0.226, corrected using family‐wise error [FWE] method). Based on the LMM‐based genome‐wide association study (GWAS) on the HCP dataset and UK Biobank 33 k GWAS summary statistics, we identified eight independent single nucleotide polymorphisms (SNPs) that were reliably associated with left cuneus volume in both UKB and HCP dataset. Within the eight SNPs, we found a negative correlation between the rs76119478 polymorphism and 2‐back accuracy accuracy (T = −2.045, p = .041, Cohen's d = −0.129). Finally, an LMM‐based mediation analysis elucidated a significant effect of left cuneus volume in mediating rs76119478 polymorphism on the 2‐back accuracy (indirect effect = −0.007, 95% BCa CI = [−0.045, −0.003]). These results were also replicated in a subgroup of Caucasians in the HCP population. Further fine mapping demonstrated that rs76119478 maps on intergene CTD‐2315A10.2 adjacent to protein‐encoding gene DAAM1, and is significantly associated with L3HYPDH mRNA expression. Our study suggested this new variant rs76119478 may regulate the working memory through exerting influence on the left cuneus volume.

Putamen volume predicts real-time fMRI neurofeedback learning success across paradigms and neurofeedback target regions

Real-time fMRI guided neurofeedback training has gained increasing interest as a noninvasive brain regulation technique with the potential to modulate functional brain alterations in therapeutic contexts. Individual variations in learning success and treatment response have been observed, yet the neural substrates underlying the learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for learning success with pooled data from three real-time fMRI data sets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback learning success across the three data sets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with learning success independent of specific aspects of the experimental design. Given the role of the putamen in associative learning this finding may reflect an important role of instrumental learning processes and brain structural variations in associated brain regions for successful acquisition of fMRI neurofeedback-guided self-regulation.

Direct cortical thickness estimation using deep learning-based anatomy segmentation and cortex parcellation

Accurate and reliable measures of cortical thickness from magnetic resonance imaging are an important biomarker to study neurodegenerative and neurological disorders. Diffeomorphic registration-based cortical thickness (DiReCT) is a known technique to derive such measures from non-surface-based volumetric tissue maps. ANTs provides an open-source method for estimating cortical thickness, derived by applying DiReCT to an atlas-based segmentation. In this paper, we propose DL+DiReCT, a method using high-quality deep learning-based neuroanatomy segmentations followed by DiReCT, yielding accurate and reliable cortical thickness measures in a short time. We evaluate the methods on two independent datasets and compare the results against surface-based measures from FreeSurfer. Good correlation of DL+DiReCT with FreeSurfer was observed (r = .887) for global mean cortical thickness compared to ANTs versus FreeSurfer (r = .608). Experiments suggest that both DiReCT-based methods had higher sensitivity to changes in cortical thickness than Freesurfer. However, while ANTs showed low scan-rescan robustness, DL+DiReCT showed similar robustness to Freesurfer. Effect-sizes for group-wise differences of healthy controls compared to individuals with dementia were highest with the deep learning-based segmentation. DL+DiReCT is a promising combination of a deep learning-based method with a traditional registration technique to detect subtle changes in cortical thickness.

Brain Oscillatory Activity during Tactile Stimulation Correlates with Cortical Thickness of Intact Areas and Predicts Outcome in Post-Traumatic Comatose Patients

In this study, we have reported a correlation between structural brain changes and electroencephalography (EEG) in response to tactile stimulation in ten comatose patients after severe traumatic brain injury (TBI). Structural morphometry showed a decrease in whole-brain cortical thickness, cortical gray matter volume, and subcortical structures in ten comatose patients compared to fifteen healthy controls. The observed decrease in gray matter volume indicated brain atrophy in coma patients induced by TBI. In resting-state EEG, the power of slow-wave activity was significantly higher (2–6 Hz), and the power of alpha and beta rhythms was lower in coma patients than in controls. During tactile stimulation, coma patients’ theta rhythm power significantly decreased compared to that in the resting state. This decrease was not observed in the control group and correlated positively with better coma outcome and the volume of whole-brain gray matter, the right putamen, and the insula. It correlated negatively with the volume of damaged brain tissue. During tactile stimulation, an increase in beta rhythm power correlated with the thickness of patients’ somatosensory cortex. Our results showed that slow-wave desynchronization, as a nonspecific response to tactile stimulation, may serve as a sensitive index of coma outcome and morphometric changes after brain injury.

Cumulative Effects of Prior Concussion and Primary Sport Participation on Brain Morphometry in Collegiate Athletes: A Study From the NCAA-DoD CARE Consortium

Prior studies have reported long-term differences in brain structure (brain morphometry) as being associated with cumulative concussion and contact sport participation. There is emerging evidence to suggest that similar effects of prior concussion and contact sport participation on brain morphometry may be present in younger cohorts of active athletes. We investigated the relationship between prior concussion and primary sport participation with subcortical and cortical structures in active collegiate contact sport and non-contact sport athletes. Contact sport athletes (CS; N = 190) and matched non-contact sport athletes (NCS; N = 95) completed baseline clinical testing and participated in up to four serial neuroimaging sessions across a 6-months period. Subcortical and cortical structural metrics were derived using FreeSurfer. Linear mixed-effects (LME) models examined the effects of years of primary sport participation and prior concussion (0, 1+) on brain structure and baseline clinical variables. Athletes with prior concussion across both groups reported significantly more baseline concussion and psychological symptoms (all ps < 0.05). The relationship between years of primary sport participation and thalamic volume differed between CS and NCS (p = 0.015), driven by a significant inverse association between primary years of participation and thalamic volume in CS (p = 0.007). Additional analyses limited to CS alone showed that the relationship between years of primary sport participation and dorsal striatal volume was moderated by concussion history (p = 0.042). Finally, CS with prior concussion had larger hippocampal volumes than CS without prior concussion (p = 0.015). Years of contact sport exposure and prior concussion(s) are associated with differences in subcortical volumes in young-adult, active collegiate athletes, consistent with prior literature in retired, primarily symptomatic contact sport athletes. Longitudinal follow-up studies in these athletes are needed to determine clinical significance of current findings.

Valproate Use Is Associated With Posterior Cortical Thinning and Ventricular Enlargement in Epilepsy Patients

Valproate is a drug widely used to treat epilepsy, bipolar disorder, and occasionally to prevent migraine headache. Despite its clinical efficacy, prenatal exposure to valproate is associated with neurodevelopmental impairments and its use in children and adults was associated with rare cases of reversible brain atrophy and ventricular enlargement. To determine whether valproate use is related with structural brain changes we examined through a cross-sectional study cortical and subcortical structures in a group of 152 people with epilepsy and a normal clinical brain MRI. Patients were grouped into those currently using valproate (n = 54), those taking drugs other than valproate (n = 47), and drug-naïve patients (n = 51) at the time of MRI, irrespectively of their epilepsy syndrome. Cortical thickness and subcortical volumes were analyzed using Freesurfer, version 5.0. Subjects exposed to valproate (either in mono- or polytherapy) showed reduced cortical thickness in the occipital lobe, more precisely in the cuneus bilaterally, in the left lingual gyrus, and in left and right pericalcarine gyri when compared to patients who used other antiepileptic drugs, to drug-naïve epilepsy patients, and to healthy controls. Considering the subgroup of patients using valproate monotherapy (n = 25), both comparisons with healthy controls and drug-naïve groups confirmed occipital lobe cortical thickness reduction. Moreover, patients using valproate showed increased left and right lateral ventricle volume compared to all other groups. Notably, subjects who were non-valproate users at the time of MRI, but who had valproate exposure in the past (n = 27) did not show these cortical or subcortical brain changes. Cortical changes in the posterior cortex, particularly in the visual cortex, and ventricular enlargement, are present in people with epilepsy using valproate, independently from clinical and demographical variables. These findings are relevant both for the efficacy and adverse events profile of valproate use in people with epilepsy.

Maternal Dietary Intake of Omega-3 Fatty Acids Correlates Positively with Regional Brain Volumes in 1-Month-Old Term Infants

Maternal nutrition is an important factor for infant neurodevelopment. However, prior magnetic resonance imaging (MRI) studies on maternal nutrients and infant brain have focused mostly on preterm infants or on few specific nutrients and few specific brain regions. We present a first study in term-born infants, comprehensively correlating 73 maternal nutrients with infant brain morphometry at the regional (61 regions) and voxel (over 300 000 voxel) levels. Both maternal nutrition intake diaries and infant MRI were collected at 1 month of life (0.9 ± 0.5 months) for 92 term-born infants (among them, 54 infants were purely breastfed and 19 were breastfed most of the time). Intake of nutrients was assessed via standardized food frequency questionnaire. No nutrient was significantly correlated with any of the volumes of the 61 autosegmented brain regions. However, increased volumes within subregions of the frontal cortex and corpus callosum at the voxel level were positively correlated with maternal intake of omega-3 fatty acids, retinol (vitamin A) and vitamin B12, both with and without correction for postmenstrual age and sex (P < 0.05, q < 0.05 after false discovery rate correction). Omega-3 fatty acids remained significantly correlated with infant brain volumes after subsetting to the 54 infants who were exclusively breastfed, but retinol and vitamin B12 did not. This provides an impetus for future larger studies to better characterize the effect size of dietary variation and correlation with neurodevelopmental outcomes, which can lead to improved nutritional guidance during pregnancy and lactation.

Hippocampal Volume in Psychiatric Diagnoses: Should Psychiatry Biomarker Research Account for Comorbidities?

Background

Many research papers claim that patients with specific psychiatric disorders (major depressive disorder, posttraumatic stress disorder, borderline personality disorder, alcohol use disorder, and others) have smaller hippocampi, but most of those reports compared patients to healthy controls. We hypothesized that if psychiatrically matched controls (psychiatric control, matched for demographics and psychiatric comorbidities) were used, much of the biomarker literature in psychiatric research would not replicate. We used hippocampus and amygdala volume only as examples, as these are very commonly replicated results in psychiatry biomarker research. We propose that psychiatry biomarker research could benefit from using psychiatric controls, as the use of healthy controls results in data that are not disorder-specific.

Method

Hippocampus/amygdala volumes were compared between major depressive disorder, sex-/age-/race-matched healthy control, and psychiatric control (N = 126/group). Similar comparisons were performed for posttraumatic stress disorder (N = 67), borderline personality disorder (N = 111), and alcohol use disorder (N = 136).

Results

Major depressive disorder patients had smaller left (p = 8.79 × 10⁻³) and right (p = 3.13 × 10⁻³) hippocampal volumes than healthy control. Posttraumatic stress disorder had smaller left (p = 0.018) and right (p = 8.64 × 10⁻⁴) hippocampi than healthy control. Borderline personality disorder had smaller right hippocampus (p = 7.90 × 10⁻³) and amygdala (p = 1.49 × 10⁻³) than healthy control. Alcohol use disorder had smaller right hippocampus (p = 0.034) and amygdala (p = .024) than healthy control. No differences were found between any of the four diagnostic groups and psychiatric control.

Conclusion

When psychiatric controls were used, there was no difference in hippocampal or amygdalar volume between any of the diagnoses studied and controls. This strategy (keeping all possible relevant variables matched between experimental groups) has been used to advance science for hundreds of years, and we propose should also be used in biomarker psychiatry research.

Test-retest variability of brain morphometry analysis: an investigation of sequence and coil effects

Background

Precise and reliable brain morphometry analysis is critical for clinical and research purposes. The magnetization-prepared rapid gradient echo (MPRAGE), multi-echo MPRAGE (MEMPRAGE) and magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) sequences have all been used to acquire brain structural images, but it is unclear which of these sequences is the most suitable for brain morphometry and whether the number of coil channels (20 or 32) affects scan precision. This study aimed to assess the impact of T1-weighted image acquisition variables (sequence and head coil) on the repeatability of resultant automated volumetric measurements.

Methods

Twenty-four healthy volunteers underwent back-to-back scanning protocols with three sequences and two different coils (i.e., six scanning conditions in total) presented in a randomized order in a single session. MorphoBox prototype and FreeSurfer were used for brain segmentation. Brain structures were divided into cortical and subcortical regions for more precise analysis. The acquired volume and thickness values were used to calculate test-retest variability (TRV) values. TRV values from the six different combinations were compared for total brain structures, total cortical structures, total subcortical structures, and every single structure.

Results

The median TRV value for all brain regions was 1.23% with MorphoBox and 3.14% with FreeSurfer. When using FreeSurfer results to compare the six combinations, for total brain structures volume and total cortical structures volume and thickness, the MEMPRAGE-32 channel combination showed significantly lower TRV values than the others (P<0.01). Similar results were observed with MorphoBox. For total subcortical structures, the MP2RAGE-32 channel combination showed the lowest TRV values with both MorphoBox (lower about 0.01% to 0.17%) and FreeSurfer analyses (lower about 0.02% to 0.37%).

Conclusions

TRV values were generally low, indicating generally high reliability for every region. The MEMPRAGE sequence was the most reliable of the three sequences for total brain structures and cortical structures. However, MP2RAGE was the most reliable for subcortical structures. The 32-channel coil showed better repeatability results than the 20-channel coil.

Morphometric correlates of anomia in patients with small left temporopolar lesions

Visual object naming is a complex cognitive process that engages an interconnected network of cortical regions moving from occipitotemporal to anterior-inferior temporal cortices, and extending into the inferior frontal cortex. Naming can fail for diverse reasons, and different stages of the naming multi-step process appear to be reliant upon the integrity of different neuroanatomical locations. While the neural correlates of semantic errors have been extensively studied, the neural basis of omission errors remains relatively unspecified. Although a strong line of evidence supports an association between anterior temporal lobe damage and semantic errors, there are some studies suggesting that the anterior temporal lobe could be also associated with omissions. However, support for this hypothesis comes from studies with patients in whom damage affected extensive brain regions, sometimes bilaterally. Here, we availed of a group of 12 patients with epilepsy associated with a small lesion at the tip of the left temporal pole. Using an unbiased surface-based morphometry methodology, we correlated two morphological features with errors observed during visual naming. Analyses revealed a correlation between omission errors and reduced local gyrification index in three cortical clusters: one in the left anteromedial temporal lobe region (AMTL) and two in the left anterior cingulate cortex (ACC). Our findings support the view that regions in ACC and AMTL are critical structures within a network engaged in word selection from semantics.

Empirical examination of the replicability of associations between brain structure and psychological variables

Linking interindividual differences in psychological phenotype to variations in brain structure is an old dream for psychology and a crucial question for cognitive neurosciences. Yet, replicability of the previously-reported 'structural brain behavior' (SBB)-associations has been questioned, recently. Here, we conducted an empirical investigation, assessing replicability of SBB among heathy adults. For a wide range of psychological measures, the replicability of associations with gray matter volume was assessed. Our results revealed that among healthy individuals 1) finding an association between performance at standard psychological tests and brain morphology is relatively unlikely 2) significant associations, found using an exploratory approach, have overestimated effect sizes and 3) can hardly be replicated in an independent sample. After considering factors such as sample size and comparing our findings with more replicable SBB-associations in a clinical cohort and replicable associations between brain structure and non-psychological phenotype, we discuss the potential causes and consequences of these findings.

Markerless high-frequency prospective motion correction for neuroanatomical MRI

PURPOSE

To integrate markerless head motion tracking with prospectively corrected neuroanatomical MRI sequences and to investigate high-frequency motion correction during imaging echo trains.

METHODS

A commercial 3D surface tracking system, which estimates head motion by registering point cloud reconstructions of the face, was used to adapt the imaging FOV based on head movement during MPRAGE and T₂ SPACE (3D variable flip-angle turbo spin-echo) sequences. The FOV position and orientation were updated every 6 lines of k-space (< 50 ms) to enable "within-echo-train" prospective motion correction (PMC). Comparisons were made with scans using "before-echo-train" PMC, in which the FOV was updated only once per TR, before the start of each echo train (ET). Continuous-motion experiments with phantoms and in vivo were used to compare these high-frequency and low-frequency correction strategies. MPRAGE images were processed with FreeSurfer to compare estimates of brain structure volumes and cortical thickness in scans with different PMC.

RESULTS

The median absolute pose differences between markerless tracking and MR image registration were 0.07/0.26/0.15 mm for x/y/z translation and 0.06º/0.02º/0.12° for rotation about x/y/z. The PMC with markerless tracking substantially reduced motion artifacts. The continuous-motion experiments showed that within-ET PMC, which minimizes FOV encoding errors during ETs that last over 1 second, reduces artifacts compared with before-ET PMC. T₂ SPACE was found to be more sensitive to motion during ETs than MPRAGE. FreeSurfer morphometry estimates from within-ET PMC MPRAGE images were the most accurate.

CONCLUSION

Markerless head tracking can be used for PMC, and high-frequency within-ET PMC can reduce sensitivity to motion during long imaging ETs.

Longitudinal Trajectories of Brain Volume and Cortical Thickness in Treated and Untreated Primary Human Immunodeficiency Virus Infection

Background

Human immunodeficiency virus (HIV) penetrates the brain in early infection. We used neuroimaging to longitudinally examine the impact of HIV and combination antiretroviral therapy (cART) on the brain in treated and untreated HIV-infected participants, starting in primary HIV infection (PHI).

Methods

Sixty-five participants, enrolled during PHI, underwent longitudinal magnetic resonance imaging, 30 of whom commenced cART during follow-up. Cross-sectional data from 16 patients with chronic HIV infection (CHI) and 19 HIV-uninfected participants were included for comparison. Brain volume and cortical thickness were estimated using tensor-based morphometry and cortical modeling, respectively. Mixed-effects models longitudinally mapped structural brain changes before and after cART. The relationship between brain morphometry estimates and blood and cerebrospinal fluid (CSF) biomarkers were also tested. Region-of-interest analyses were performed to compare brain morphometry estimates between the groups.

Results

Prior to cART, longer duration of untreated infection in PHI correlated with volume loss in the thalamus, caudate, and cerebellum, and with cortical thinning in the frontal and temporal lobes and cingulate cortex. After cART, no further volume loss was observed. However, small increases of cortical thickness in the frontal and temporal lobe correlated with longer cART duration. No correlations were observed with blood or CSF measures. The PHI group did not have different brain morphometric measures compared to the HIV-uninfected group, but had larger volumes in the thalamus, caudate, putamen, and cortical gray matter compared with CHI participants.

Conclusions

Subcortical atrophy and cortical thinning occur during untreated infection but may be arrested by cART. These findings emphasize the importance of early cART.

Mesocorticolimbic Connectivity and Volumetric Alterations in DCC Mutation Carriers

The axon guidance cue receptor DCC (deleted in colorectal cancer) plays a critical role in the organization of mesocorticolimbic pathways in rodents. To investigate whether this occurs in humans, we measured (1) anatomical connectivity between the substantia nigra/ventral tegmental area (SN/VTA) and forebrain targets, (2) striatal and cortical volumes, and (3) putatively associated traits and behaviors. To assess translatability, morphometric data were also collected in Dcc-haploinsufficient mice. The human volunteers were 20 DCC^+/- mutation carriers, 16 DCC^+/+ relatives, and 20 DCC^+/+ unrelated healthy volunteers (UHVs; 28 females). The mice were 11 Dcc^+/- and 16 wild-type C57BL/6J animals assessed during adolescence and adulthood. Compared with both control groups, the human DCC^+/- carriers exhibited the following: (1) reduced anatomical connectivity from the SN/VTA to the ventral striatum [DCC^+/+: p = 0.0005, r(effect size) = 0.60; UHV: p = 0.0029, r = 0.48] and ventral medial prefrontal cortex (DCC^+/+: p = 0.0031, r = 0.53; UHV: p = 0.034, r = 0.35); (2) lower novelty-seeking scores (DCC^+/+: p = 0.034, d = 0.82; UHV: p = 0.019, d = 0.84); and (3) reduced striatal volume (DCC^+/+: p = 0.0009, d = 1.37; UHV: p = 0.0054, d = 0.93). Striatal volumetric reductions were also present in Dcc^+/- mice, and these were seen during adolescence (p = 0.0058, d = 1.09) and adulthood (p = 0.003, d = 1.26). Together these findings provide the first evidence in humans that an axon guidance gene is involved in the formation of mesocorticolimbic circuitry and related behavioral traits, providing mechanisms through which DCC mutations might affect susceptibility to diverse neuropsychiatric disorders.SIGNIFICANCE STATEMENT Opportunities to study the effects of axon guidance molecules on human brain development have been rare. Here, the identification of a large four-generational family that carries a mutation to the axon guidance molecule receptor gene, DCC, enabled us to demonstrate effects on mesocorticolimbic anatomical connectivity, striatal volumes, and personality traits. Reductions in striatal volumes were replicated in DCC-haploinsufficient mice. Together, these processes might influence mesocorticolimbic function and susceptibility to diverse neuropsychiatric disorders.

Plasma Amyloid Is Associated with White Matter and Subcortical Alterations and Is Modulated by Age and Seasonal Rhythms in Mouse Lemur Primates

Accumulation of amyloid-β (Aβ) peptides in the brain is a critical early event in the pathogenesis of Alzheimer's disease (AD), the most common age-related neurodegenerative disorder. There is increasing interest in measuring levels of plasma Aβ since this could help in diagnosis of brain pathology. However, the value of plasma Aβ in such a diagnosis is still controversial and factors modulating its levels are still poorly understood. The mouse lemur (Microcebus murinus) is a primate model of cerebral aging which can also present with amyloid plaques and whose Aβ is highly homologous to humans'. In an attempt to characterize this primate model and to evaluate the potential of plasma Aβ as a biomarker for brain alterations, we measured plasma Aβ₄₀ concentration in 21 animals aged from 5 to 9.5 years. We observed an age-related increase in plasma Aβ₄₀ levels. We then evaluated the relationships between plasma Aβ₄₀ levels and cerebral atrophy in these mouse lemurs. Voxel-based analysis of cerebral MR images (adjusted for the age/sex/brain size of the animals), showed that low Aβ₄₀ levels are associated with atrophy of several white matter and subcortical brain regions. These results suggest that low Aβ₄₀ levels in middle-aged/old animals are associated with brain deterioration. One special feature of mouse lemurs is that their metabolic and physiological parameters follow seasonal changes strictly controlled by illumination. We evaluated seasonal-related variations of plasma Aβ₄₀ levels and found a strong effect, with higher plasma Aβ₄₀ concentrations in winter conditions compared to summer. This question of seasonal modulation of Aβ plasma levels should be addressed in clinical studies. We also focused on the amplitude of the difference between plasma Aβ₄₀ levels during the two seasons and found that this amplitude increases with age. Possible mechanisms leading to these seasonal changes are discussed.

Method for retrospective estimation of natural head movement during structural MRI

BACKGROUND

Head motion during brain structural MRI scans biases brain morphometry measurements but quantitative retrospective methods estimating head motion from structural MRI have not been evaluated.

PURPOSE

To verify the hypothesis that two metrics retrospectively computed from MR images: 1) average edge strength (AES, reduced with image blurring) and 2) entropy (ENT, increased with blurring and ringing artifacts) could be sensitive to in-scanner head motion during acquisition of T₁ -weighted MR images.

STUDY TYPE

Retrospective.

POPULATION/SUBJECTS/PHANTOM/SPECIMEN/ANIMAL MODEL

In all, 83 healthy control (HC) and 120 Parkinson's disease (PD) patients.

FIELD STRENGTH/SEQUENCE

3D magnetization-prepared rapid gradient-echo (MPRAGE) images at 3T.

ASSESSMENT

We 1) compared AES and ENT distribution between HC and PD; 2) evaluated the correlation between tremor score (TS) and AES (or ENT) in PD; and 3) investigated cortical regions showing an association between AES (or ENT) and local and network-level covariance measures of cortical thickness (CT), gray to white matter contrast (GWC) and gray matter density maps (GMx).

STATISTICAL TESTS

1) Student's t-test. 2) Spearman's rank correlation. 3) General linear model and partial least square analysis.

RESULTS

AES, but not ENT, differentiated HC and PD (P = 0.02, HC median AES = 39.8, interquartile range = 9.8, PD median AES = 37.6, interquartile range = 8.1). In PD, AES correlated negatively with TS (ρ = -0.21, P = 0.02) and showed a significant relationship (|Z| >3, P < 0.001) with structural covariance of CT and GWC in 54 out of 68 cortical regions.

DATA CONCLUSION

In clinical populations prone to head motion, AES can provide a reliable retrospective index of motion during structural scans, identifying brain areas whose morphometric measures covary with motion.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:927-937.

Brain Structural Correlates of Subclinical Obsessive-Compulsive Symptoms in Healthy Children

OBJECTIVE

Subclinical obsessive-compulsive (OC) symptoms are frequently observed in children and have been reported to predict a subsequent diagnosis of OC disorder (OCD). Therefore, identifying the putative neurobiological signatures of such risk is crucial, because it would allow for the characterization of the underpinnings of OCD without the interfering effects of chronicity, medication, or comorbidities, especially when interpreted within the context of OCD clinical heterogeneity and taking into account normal neurodevelopmental changes. The present study aimed to identify the brain volumetric features associated with subclinical OC symptoms and the potential modulatory effects of sex and age in a large sample of healthy children.

METHOD

Two hundred fifty-five healthy children were assessed using the Obsessive-Compulsive Inventory-Child Version and underwent a brain structural magnetic resonance examination. The relation between total and symptom-specific scores and regional gray and white matter (GM and WM) volumes was evaluated. Participants were grouped according to sex and age (younger versus older) to assess the effect of these factors on symptom-brain morphometry associations.

RESULTS

Ordering symptoms were negatively related to GM volumes in the ventral caudate. Hoarding symptoms were positively associated with GM and WM volumes in the left inferior frontal gyrus, and obsessing symptoms correlated negatively with GM and WM volumes in the right temporal pole. Doubt-checking symptoms correlated positively with WM volumes in the right inferior fronto-occipital fasciculus and the corpus callosum. Sex and age modulated some of these associations.

CONCLUSION

Subclinical OC symptoms are associated with specific brain volumetric features, which could be considered potential neural signatures of increased risk for OCD.

Dual-Sensitivity Multiple Sclerosis Lesion and CSF Segmentation for Multichannel 3T Brain MRI

BACKGROUND AND PURPOSE

A pipeline for fully automated segmentation of 3T brain MRI scans in multiple sclerosis (MS) is presented. This 3T morphometry (3TM) pipeline provides indicators of MS disease progression from multichannel datasets with high‐resolution 3‐dimensional T1‐weighted, T2‐weighted, and fluid‐attenuated inversion‐recovery (FLAIR) contrast. 3TM segments white (WM) and gray matter (GM) and cerebrospinal fluid (CSF) to assess atrophy and provides WM lesion (WML) volume.

METHODS

To address nonuniform distribution of noise/contrast (eg, posterior fossa in 3D‐FLAIR) of 3T magnetic resonance imaging, the method employs dual sensitivity (different sensitivities for lesion detection in predefined regions). We tested this approach by assigning different sensitivities to supratentorial and infratentorial regions, and validated the segmentation for accuracy against manual delineation, and for precision in scan‐rescans.

RESULTS

Intraclass correlation coefficients of .95, .91, and .86 were observed for WML and CSF segmentation accuracy and brain parenchymal fraction (BPF). Dual sensitivity significantly reduced infratentorial false‐positive WMLs, affording increases in global sensitivity without decreasing specificity. Scan‐rescan yielded coefficients of variation (COVs) of 8% and .4% for WMLs and BPF and COVs of .8%, 1%, and 2% for GM, WM, and CSF volumes. WML volume difference/precision was .49 ± .72 mL over a range of 0–24 mL. Correlation between BPF and age was r = .62 (P = .0004), and effect size for detecting brain atrophy was Cohen's d = 1.26 (standardized mean difference vs. healthy controls).

CONCLUSIONS

This pipeline produces probability maps for brain lesions and tissue classes, facilitating expert review/correction and may provide high throughput, efficient characterization of MS in large datasets.

Structural correlates of apathy in Alzheimer's disease: a multimodal MRI study

OBJECTIVE

Apathy is one of the most frequent symptoms of dementia, whose underlying neurobiology is not well understood. The objective was to analyze the correlations of apathy and its dimensions with gray and white matter damage in the brain of patients with advanced Alzheimer's disease (AD).

METHODS

The setting of the study was at the Alzheimer Center Reina Sofía Foundation Research Unit. Participants include 37 nursing home patients with moderate to severe AD, 78.4% were women, and mean Standard Deviation (SD) age is 82.7 (5.8). Several measurements were taken: severe mini-mental state examination and Global Deterioration Scale for cognitive and functional status, Neuropsychiatric Inventory for behavioral problems, and Apathy In Dementia-Nursing Home Version Scale for apathy, including total score and subscores of emotional blunting, deficit of thinking, and cognitive inertia. 3T magnetic resonance imaging measures (voxel-based morphometry, fluid-attenuated inversion recovery, and diffusion tensor imaging) were also conducted.

RESULTS

Moderate levels of apathy (mean Apathy In Dementia-Nursing Home Version Scale: 31.1 ± 18.5) were found. Bilateral damage to the corpus callosum and internal capsule was associated with apathy severity (cluster size 2435, p < 0.0005, family-wise error [FWE]-corrected). A smaller and more anteriorly located region of the right internal capsule and corpus callosum was associated with higher emotional blunting (cluster size 334, p < 0.0005, FWE-corrected). Ischemic damage in the right periventricular frontal region was associated with higher deficit of thinking (cluster size 3805, p < 0.005, FWE-corrected).

CONCLUSIONS

Brain damage related to apathy may have different features in the advanced stages of AD and differs between the three apathy dimensions. Besides atrophy, brain connectivity and vascular lesions are relevant in the study of apathy, especially in the more severe stages of dementia. Further magnetic resonance imaging studies should include multimodal techniques. Copyright © 2016 John Wiley & Sons, Ltd.

Birth weight discordance, DNA methylation, and cortical morphology of adolescent monozygotic twins

BACKGROUND

Several studies have shown that the in utero environment, which can be indexed by birth weight (BW), is associated with cortical morphology in adolescence and adulthood. Work in monozygotic (MZ) twins suggests that this association is driven by non-shared environmental factors. This correlation could be the result of in utero impacts on DNA methylation. The aim of the present study with MZ twins is to replicate the association between discordance in BW and brain morphology and test whether discordance in DNA methylation mediates this relationship.

METHODS

One hundred and four adolescent MZ twins (52 pairs, of which 42% were male pairs) who have been followed regularly since birth underwent T1 weighted structural MRI, and epigenome-wide assessment of DNA methylation from saliva at age 15.

RESULTS

Co-twins had very similar measures of DNA methylation and cortical morphology. Higher BW members of a twin pair had increased total cortical surface area, and decreased cortical thickness compared to their lower BW sibling. BW Discordance was positively associated with both cortical surface area and cortical volume discordance. Genes involved in neurodevelopment were tentatively identified as mediators of both the BW - cortical volume, and BW- cortical surface area relationships.

CONCLUSIONS

The association between BW and cortical morphology in adolescence appears to be attributable to in utero environmental effects, and DNA methylation may play a role in mediating this relationship. Hum Brain Mapp 38:2037-2050, 2017. © 2017 Wiley Periodicals, Inc.

Neuroanatomical and Symptomatic Sex Differences in Individuals at Clinical High Risk for Psychosis

Sex differences have been widely observed in clinical presentation, functional outcome and neuroanatomy in individuals with a first-episode of psychosis, and chronic patients suffering from schizophrenia. However, little is known about sex differences in the high-risk stages for psychosis. The present study investigated sex differences in cortical and subcortical neuroanatomy in individuals at clinical high risk (CHR) for psychosis and healthy controls (CTL), and the relationship between anatomy and clinical symptoms in males at CHR. Magnetic resonance images were collected in 26 individuals at CHR (13 men) and 29 CTLs (15 men) to determine total and regional brain volumes and morphology, cortical thickness, and surface area (SA). Clinical symptoms were assessed with the brief psychiatric rating scale. Significant sex-by-diagnosis interactions were observed with opposite directions of effect in male and female CHR subjects relative to their same-sex controls in multiple cortical and subcortical areas. The right postcentral, left superior parietal, inferior parietal supramarginal, and angular gyri [<5% false discovery rate (FDR)] were thicker in male and thinner in female CHR subjects compared with their same-sex CTLs. The same pattern was observed in the right superior parietal gyrus SA at the regional and vertex level. Using a recently developed surface-based morphology pipeline, we observed sex-specific shape differences in the left hippocampus (<5% FDR) and amygdala (<10% FDR). Negative symptom burden was significantly higher in male compared with female CHR subjects (p = 0.04) and was positively associated with areal expansion of the left amygdala in males (<5% FDR). Some limitations of the study include the sample size, and data acquisition at 1.5 T. This study demonstrates neuroanatomical sex differences in CHR subjects, which may be associated with variations in symptomatology in men and women with psychotic symptoms.

Genetic risk for obesity predicts nucleus accumbens size and responsivity to real-world food cues

Obesity is a major public health concern that involves an interaction between genetic susceptibility and exposure to environmental cues (e.g., food marketing); however, the mechanisms that link these factors and contribute to unhealthy eating are unclear. Using a well-known obesity risk polymorphism (FTO rs9939609) in a sample of 78 children (ages 9-12 y), we observed that children at risk for obesity exhibited stronger responses to food commercials in the nucleus accumbens (NAcc) than children not at risk. Similarly, children at a higher genetic risk for obesity demonstrated larger NAcc volumes. Although a recessive model of this polymorphism best predicted body mass and adiposity, a dominant model was most predictive of NAcc size and responsivity to food cues. These findings suggest that children genetically at risk for obesity are predisposed to represent reward signals more strongly, which, in turn, may contribute to unhealthy eating behaviors later in life.

Hippocampal structure, metabolism, and inflammatory response after a 6-week intense aerobic exercise in healthy young adults: a controlled trial

Interventional studies suggest that changes in physical fitness affect brain function and structure. We studied the influence of high intensity physical exercise on hippocampal volume and metabolism in 17 young healthy male adults during a 6-week exercise program compared with matched controls. We further aimed to relate these changes to hypothesized changes in exercised-induced brain-derived neurotrophic factor (BDNF), interleukin-6 (IL-6), and tumor necrosis factor alpha (TNF-α). We show profound improvement of physical fitness in most subjects and a positive correlation between the degree of fitness improvement and increased BDNF levels. We unexpectedly observed an average volume decrease of about 2%, which was restricted to right hippocampal subfields CA2/3, subiculum, and dentate gyrus and which correlated with fitness improvement and increased BDNF levels negatively. This result indicates that mainly those subjects who did not benefit from the exercise program show decreased hippocampal volume, reduced BDNF levels, and increased TNF-α concentrations. While spectroscopy results do not indicate any neuronal loss (unchanged N-acetylaspartate levels) decreased glutamate-glutamine levels were observed in the right anterior hippocampus in the exercise group only. Responder characteristics need to be studied in more detail. Our results point to an important role of the inflammatory response after exercise on changes in hippocampal structure.

Indices of Regional Brain Atrophy: Formulae and Nomenclature

The pattern of brain atrophy helps to discriminate normal age-related changes from neurodegenerative diseases. Albeit indices of regional brain atrophy have proven to be a parameter useful in the early diagnosis and differential diagnosis of some neurodegenerative diseases, indices of absolute regional atrophy still have some important limitations. We propose using indices of relative atrophy for representing how the volume of a given region of interest (ROI) changes over time in comparison to changes in global brain measures over the same time. A second problem in morphometric studies is terminology. There is a lack of systematization naming indices and the same measure can be named with different terms by different research groups or imaging softwares. This limits the understanding and discussion of studies. In this technological report, we provide a general description on how to compute indices of absolute and relative regional brain atrophy and propose a standardized nomenclature.

The dynamics of growth cone morphology

BACKGROUND

Normal brain function depends on the development of appropriate patterns of neural connections. A critical role in guiding axons to their targets during neural development is played by neuronal growth cones. These have a complex and rapidly changing morphology; however, a quantitative understanding of this morphology, its dynamics and how these are related to growth cone movement, is lacking.

RESULTS

Here we use eigenshape analysis (principal components analysis in shape space) to uncover the set of five to six basic shape modes that capture the most variance in growth cone form. By analysing how the projections of growth cones onto these principal modes evolve in time, we found that growth cone shape oscillates with a mean period of 30 min. The variability of oscillation periods and strengths between different growth cones was correlated with their forward movement, such that growth cones with strong, fast shape oscillations tended to extend faster. A simple computational model of growth cone shape dynamics based on dynamic microtubule instability was able to reproduce quantitatively both the mean and variance of oscillation periods seen experimentally, suggesting that the principal driver of growth cone shape oscillations may be intrinsic periodicity in cytoskeletal rearrangements.

CONCLUSIONS

Intrinsically driven shape oscillations are an important component of growth cone shape dynamics. More generally, eigenshape analysis has the potential to provide new quantitative information about differences in growth cone behaviour in different conditions.

Impact of early vs. late childhood early life stress on brain morphometrics

Previous studies of early life trauma suggest that in addition to its emotional impact, exposure to early life stress (ELS) is associated with alterations in brain structure. However, little attention has been devoted to the relationship between emotional processing and brain integrity as a function of age of ELS onset. In the present study we examined whether ELS onset in older ages of youth rather than younger ages is associated with smaller limbic and basal ganglia volumes as measured by magnetic resonance imaging (MRI). We hypothesized that later age of manifestation during youth is associated with smaller volumetric morphology in limbic and basal ganglia volumes in adulthood. A total of 173 individuals were divided into three groups based on the age of self-reported ELS. The three groups included individuals only experiencing early childhood ELS (1 month-7 years, n = 38), those only experiencing later childhood ELS (8 years -17 years, n = 59), and those who have not experienced ELS (n = 76). Anterior cingulate cortex (ACC), hippocampus, amygdala, insula and caudate volumes were measured using a T1-weighted MRI. Analyses confirmed that later childhood ELS was associated with volumetric reductions in the ACC and insula volumes, while ELS experienced between the ages of 1 month and 7 years was not associated with lower brain volumes in these regions. The results may reflect the influence of more fully developed emotional processing of ELS on the developing brain and reinforce a body of research implicating both the ACC and insula in neuropsychiatric disorders and emotional regulation.

Annual research review: progress in using brain morphometry as a clinical tool for diagnosing psychiatric disorders

Brain morphometry in recent decades has increased our understanding of the neural bases of psychiatric disorders by localizing anatomical disturbances to specific nuclei and subnuclei of the brain. At least some of these disturbances precede the overt expression of clinical symptoms and possibly are endophenotypes that could be used to diagnose an individual accurately as having a specific psychiatric disorder. More accurate diagnoses could significantly reduce the emotional and financial burden of disease by aiding clinicians in implementing appropriate treatments earlier and in tailoring treatment to the individual needs. Several methods, especially those based on machine learning, have been proposed that use anatomical brain measures and gold-standard diagnoses of participants to learn decision rules that classify a person automatically as having one disorder rather than another. We review the general principles and procedures for machine learning, particularly as applied to diagnostic classification, and then review the procedures that have thus far attempted to diagnose psychiatric illnesses automatically using anatomical measures of the brain. We discuss the strengths and limitations of extant procedures and note that the sensitivity and specificity of these procedures in their most successful implementations have approximated 90%. Although these methods have not yet been applied within clinical settings, they provide strong evidence that individual patients can be diagnosed accurately using the spatial pattern of disturbances across the brain.

Models of the aging brain structure and individual decline

The aging brain's structural development constitutes a spatiotemporal process that is accessible by MR-based computational morphometry. Here we introduce basic concepts and analytical approaches to quantify age-related differences and changes in neuroanatomical images of the human brain. The presented models first address the estimation of age trajectories, then we consider inter-individual variations of structural decline, using a repeated measures design. We concentrate our overview on preprocessed neuroanatomical images of the human brain to facilitate practical applications to diverse voxel- and surface-based structural markers. Together these methods afford analysis of aging brain structure in relation to behavioral, health, or cognitive parameters.

Effect of cocaine on structural changes in brain: MRI volumetry using tensor-based morphometry

Magnetic resonance imaging (MRI) was performed in cocaine-dependent subjects to determine the structural changes in brain compared to non-drug using controls. Cocaine-dependent subjects and controls were carefully screened to rule out brain pathology of undetermined origin. Magnetic resonance images were analyzed using tensor-based morphometry (TBM) and voxel-based morphometry (VBM) without and with modulation to adjust for volume changes during normalization. For TBM analysis, unbiased atlases were generated using two different inverse consistent and diffeomorphic nonlinear registration techniques. Two different control groups were used for generating unbiased atlases. Independent of the nonlinear registration technique and normal cohorts used for creating the unbiased atlases, our analysis failed to detect any statistically significant effect of cocaine on brain volumes. These results show that cocaine-dependent subjects do not show differences in regional brain volumes compared to non-drug using controls.