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Subthalamic deep brain stimulation (STN-DBS) is known to improve motor function in advanced Parkinson's disease (PD) and to enable a reduction of anti-parkinsonian medication. While the levodopa challenge test and disease duration are considered good predictors of STN-DBS outcome, other clinical and neuroanatomical predictors are less established. This study aimed to evaluate, in addition to clinical predictors, the effect of patients' individual brain topography on DBS outcome. The medical records of 35 PD patients were used to analyze DBS outcomes measured with the following scales: Part III of the Unified Parkinson's Disease Rating Scale (UPDRS-III) off medication at baseline, and at 6-months during medication off and stimulation on, use of anti-parkinsonian medication (LED), Abnormal Involuntary Movement Scale (AIMS) and Non-Motor Symptoms Questionnaire (NMS-Quest). Furthermore, preoperative brain MRI images were utilized to analyze the brain morphology in relation to STN-DBS outcome. With STN-DBS, a 44% reduction in the UPDRS-III score and a 43% decrease in the LED were observed (p<0.001). Dyskinesia and non-motor symptoms decreased significantly [median reductions of 78,6% (IQR 45,5%) and 18,4% (IQR 32,2%) respectively, p=0.001 – 0.047]. Along with the levodopa challenge test, patients' age correlated with the observed DBS outcome measured as UPDRS-III improvement (ρ= -0.466 – -0.521, p<0.005). Patients with greater LED decline had lower grey matter volumes in left superior medial frontal gyrus, in supplementary motor area and cingulum bilaterally. Additionally, patients with greater UPDRS-III score improvement had lower grey matter volume in similar grey matter areas. These findings remained significant when adjusted for sex, age, baseline LED and UPDRS scores respectively and for total intracranial volume (p=0.0041- 0.001). However, only the LED decrease finding remained significant when the analyses were further controlled for stimulation amplitude. It appears that along with the clinical predictors of STN-DBS outcome, individual patient topographic differences may influence DBS outcome. Clinical Trial Registration Number: NCT06095245, registration date October 23, 2023, retrospectively registered [ABSTRACT FROM AUTHOR]

Introduction: Early focal brain injuries lead to long-term disabilities with frequent cognitive impairments, suggesting global dysfunction beyond the lesion. While plasticity of the immature brain promotes better learning, outcome variability across individuals is multifactorial. Males are more vulnerable to early injuries and neurodevelopmental disorders than females, but long-term sex differences in brain growth after an early focal lesion have not been described yet. With this MRI longitudinal morphometry study of brain development after a Neonatal Arterial Ischemic Stroke (NAIS), we searched for differences between males and females in the trajectories of ipsi- and contralesional gray matter growth in childhood and adolescence, while accounting for lesion characteristics. Methods: We relied on a longitudinal cohort (AVCnn) of patients with unilateral NAIS who underwent clinical and MRI assessments at ages 7 and 16 were compared to age-matched controls. Non-lesioned volumes of gray matter (hemispheres, lobes, regions, deep structures, cerebellum) were extracted from segmented T1 MRI images at 7 (Patients: 23 M, 16 F; Controls: 17 M, 18 F) and 16 (Patients: 18 M, 11 F; Controls: 16 M, 15 F). These volumes were analyzed using a Linear Mixed Model accounting for age, sex, and lesion characteristics. Results: Whole hemisphere volumes were reduced at both ages in patients compared to controls (gray matter volume: -16% in males, -10% in females). In ipsilesional hemisphere, cortical gray matter and thalamic volume losses (average -13%) mostly depended on lesion severity, suggesting diaschisis, with minimal effect of patient sex. In the contralesional hemisphere however, we consistently found sex differences in gray matter volumes, as only male volumes were smaller than inmale controls (average-7.5%), mostly in territoriesmirroring the contralateral lesion. Females did not significantly deviate from the typical trajectories of female controls. Similar sex differences were found in both cerebellar hemispheres. Discussion: These results suggest sex-dependent growth trajectories after an early brain lesion with a contralesional growth deficit in males only. The similarity of patterns at ages 7 and 16 suggests that puberty has little effect on these trajectories, and that most of the deviation in males occurs in early childhood, in line with the well-described perinatal vulnerability of themale brain, and with no compensation thereafter. [ABSTRACT FROM AUTHOR]

Brain tissue morphometry further improves the radiologist’s assessment of brain atrophy. Conventional programs using this method are of limited use in normal practice due to their relatively long calculation time. Artificial intelligence, thanks to its speed, enables the routine use of morphometrics. Because the technology is relatively new, its contribution in day-to-day diagnostics has not yet been clearly determined. This text summarizes our initial experience with this method on a pilot cohort of patients with neurodegenerative diseases and describes those advantages and limitations which became apparent during our usage of the program. [ABSTRACT FROM AUTHOR]

With the rise of open data, identifiability of individuals based on 3D renderings obtained from routine structural magnetic resonance imaging (MRI) scans of the head has become a growing privacy concern. To protect subject privacy, several algorithms have been developed to de‐identify imaging data using blurring, defacing or refacing. Completely removing facial structures provides the best re‐identification protection but can significantly impact post‐processing steps, like brain morphometry. As an alternative, refacing methods that replace individual facial structures with generic templates have a lower effect on the geometry and intensity distribution of original scans, and are able to provide more consistent post‐processing results by the price of higher re‐identification risk and computational complexity. In the current study, we propose a novel method for anonymized face generation for defaced 3D T1‐weighted scans based on a 3D conditional generative adversarial network. To evaluate the performance of the proposed de‐identification tool, a comparative study was conducted between several existing defacing and refacing tools, with two different segmentation algorithms (FAST and Morphobox). The aim was to evaluate (i) impact on brain morphometry reproducibility, (ii) re‐identification risk, (iii) balance between (i) and (ii), and (iv) the processing time. The proposed method takes 9 s for face generation and is suitable for recovering consistent post‐processing results after defacing. [ABSTRACT FROM AUTHOR]

Background: Individual differences in gray-matter morphometry in the limbic system and frontal cortex have been linked to clinical features of cocaine use disorder (CUD). Self-administration paradigms can provide more direct measurements of the relationship between the regulation of cocaine use and gray-matter morphometry when compared to self-report assessments. Objectives: Our goal was to investigate associations with self-administration behavior in subcortical and cortical brain regions. We hypothesized the number of cocaine infusions self-administered would be correlated with gray-matter volumes (GMVs) in the striatum, amygdala, and hippocampus. Due to scarcity in human studies, we did not hypothesize subcortical directionality. In the frontal cortex, we hypothesized thickness would be negatively correlated with self-administered cocaine. Methods: We conducted an analysis of cocaine self-administration and structural MRI data from 33 (nFemales = 10) individuals with moderate-to-severe CUD. Self-administration lasted 60-minutes and cocaine (8, 16, or 32 mg/70 kg) was delivered on an FR1 schedule (5-minute lockout). Subcortical and cortical regression analyses were performed that included combined bilateral regions and age, experimental variables and use history as confounders. Results: Self-administered cocaine infusions were positively associated with caudal GMV (b = 0.18, p = 0.030) and negatively with putamenal GMV (b = −0.10, p = 0.041). In the cortical model, infusions were positively associated with insular thickness (b = 0.39, p = 0.008) and women appeared to self-administer cocaine more frequently (b = 0.23, p = 0.019). Conclusions: Brain morphometry features in the striatum and insula may contribute to cocaine consumption in CUD. These differences in morphometry may reflect consequences of prolonged use, predisposed vulnerability, or other possibilities. Clinical Trial Numbers: NCT01978431; NCT03471182 [ABSTRACT FROM AUTHOR]

Schizophrenic symptoms are known to segregate into reality distortion, negative and disorganization syndromes, but the correlates of these syndromes with regional brain structural change are not well established. Cognitive impairment is a further clinical feature of schizophrenia, whose brain structural correlates are the subject of conflicting findings. 165 patients with schizophrenia were rated for symptoms using the PANSS, and cognitive impairment was indexed by estimated premorbid-current IQ discrepancy. Cortical volume was measured using surface-based morphometry in the patients and in 50 healthy controls. Correlations between clinical and cognitive measures and cortical volume were examined using whole-brain FreeSurfer tools. No clusters of volume reduction were seen associated with reality distortion or disorganization. Negative symptom scores showed a significant inverse correlation with volume in a small cluster in the left medial orbitofrontal gyrus. Larger estimated premorbid-current IQ discrepancies were associated with clusters of reduced cortical volume in the left precentral gyrus and the left temporal lobe. The cluster of association with negative symptoms disappeared when estimated premorbid-current IQ discrepancy was controlled for. This study does not provide support for an association between brain structural abnormality and reality distortion or disorganization syndromes in schizophrenia. The cluster of volume reduction found in the left medial orbitofrontal cortex correlated with negative symptoms may have reflected the association between this class of symptoms and cognitive impairment. The study adds to existing findings of an association between cognitive impairment and brain structural changes in the disorder. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

High-tension glaucoma (HTG) is one of the most common forms of primary open angle glaucoma. The purpose of this study was to assess in HTG brain, whether the elevated intraocular pressure (IOP) had an effect on the brain morphological alterations via structural MRI. We acquired T1WI structural MRI images from 56 subjects including 36 HTG patients and 20 healthy controls. We tested whether the brain morphometry was associated with the mean IOP in HTG patients. Moreover, we conducted moderation analysis to assess the interactions between subject type (HTG - healthy controls) and IOP. In HTG group, cortical thickness was negatively correlated with the mean IOP in the left rostral middle frontal gyrus, left pars triangularis, right precentral gyrus, left postcentral gyrus, left superior temporal gyrus (p < 0.05, FDR corrected). Four of the five regions negatively correlated with mean IOP showed reduced cortical thickness in HTG group compared with healthy controls, which were the left rostral middle frontal gyrus, left pars triangularis, left postcentral gyrus and left superior temporal gyrus (p < 0.05, FDR corrected). IOP moderated the interaction between subject type and cortical thickness of the left rostral middle frontal gyrus (p = 0.0017), left pars triangularis (p = 0.0011), left postcentral gyrus (p = 0.0040) and left superior temporal gyrus (p = 0.0066). Elevated IOP may result brain morphometry alterations such as cortical thinning. The relationship between IOP and brain morphometry underlines the importance of the IOP regulation for HTG patients. [ABSTRACT FROM AUTHOR]

IntroductionEarly focal brain injuries lead to long-term disabilities with frequent cognitive impairments, suggesting global dysfunction beyond the lesion. While plasticity of the immature brain promotes better learning, outcome variability across individuals is multifactorial. Males are more vulnerable to early injuries and neurodevelopmental disorders than females, but long-term sex differences in brain growth after an early focal lesion have not been described yet. With this MRI longitudinal morphometry study of brain development after a Neonatal Arterial Ischemic Stroke (NAIS), we searched for differences between males and females in the trajectories of ipsi- and contralesional gray matter growth in childhood and adolescence, while accounting for lesion characteristics.MethodsWe relied on a longitudinal cohort (AVCnn) of patients with unilateral NAIS who underwent clinical and MRI assessments at ages 7 and 16 were compared to age-matched controls. Non-lesioned volumes of gray matter (hemispheres, lobes, regions, deep structures, cerebellum) were extracted from segmented T1 MRI images at 7 (Patients: 23 M, 16 F; Controls: 17 M, 18 F) and 16 (Patients: 18 M, 11 F; Controls: 16 M, 15 F). These volumes were analyzed using a Linear Mixed Model accounting for age, sex, and lesion characteristics.ResultsWhole hemisphere volumes were reduced at both ages in patients compared to controls (gray matter volume: −16% in males, −10% in females). In ipsilesional hemisphere, cortical gray matter and thalamic volume losses (average −13%) mostly depended on lesion severity, suggesting diaschisis, with minimal effect of patient sex. In the contralesional hemisphere however, we consistently found sex differences in gray matter volumes, as only male volumes were smaller than in male controls (average −7.5%), mostly in territories mirroring the contralateral lesion. Females did not significantly deviate from the typical trajectories of female controls. Similar sex differences were found in both cerebellar hemispheres.DiscussionThese results suggest sex-dependent growth trajectories after an early brain lesion with a contralesional growth deficit in males only. The similarity of patterns at ages 7 and 16 suggests that puberty has little effect on these trajectories, and that most of the deviation in males occurs in early childhood, in line with the well-described perinatal vulnerability of the male brain, and with no compensation thereafter.

IntroductionType 2 diabetes (T2D) has been linked to cognitive impairment and dementia, but its impact on brain cortical structures in individuals prior to or without cognitive impairment remains unclear.MethodsWe conducted a systematic review of 2,331 entries investigating cerebral cortical thickness changes in T2D individuals without cognitive impairment, 55 of which met our inclusion criteria.ResultsMost studies (45/55) reported cortical brain atrophy and reduced thickness in the anterior cingulate, temporal, and frontal lobes between T2D and otherwise cognitively healthy controls. However, the balance of studies (10/55) reported no significant differences in either cortical or total brain volumes. A few reports also noticed changes in the occipital cortex and its gyri. As part of the reports, less than half of studies (18/55) described a correlation between T2D and hippocampal atrophy. Variability in sample characteristics, imaging methods, and software could affect findings on T2D and cortical atrophy.DiscussionIn conclusion, T2D appears linked to reduced cortical thickness, possibly impacting cognition and dementia risk. Microvascular disease and inflammation in T2D may also contribute to this risk. Further research is needed to understand the underlying mechanisms and brain health implications.

The use of magnetic resonance imaging in morphometry, as quantitative assessment of brain parameters (thickness, surface area, volume), allows to detect changes in many neuropsichiatric conditions that were previously considered intact. This article provides data on neuroimaging brain morphometry and effective use of this method in neurosciences.

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. [ABSTRACT FROM AUTHOR]

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.

Pulsatile tinnitus (PT) can be a debilitating condition characterized by rhythmic, heartbeat-synchronous sounds, which can severely impact patients’ quality of life. Understanding the neuroanatomical changes in PT patients may provide critical insights into the impacts of this condition. This study aimed to investigate potential differences in cortical and subcortical brain volume between adults with PT and age-matched controls (60 to 70 years of age). A retrospective, cross-sectional analysis of imaging and medical records was conducted, with data collected from January 2015 to December 2021. The study was conducted in a tertiary referral center with a specialized tinnitus clinic. A total of 135 adults diagnosed with PT and 135 age-matched controls were included. All participants were screened for PT and relevant medical history, with consecutive sampling used for selection. Cortical and subcortical brain volume differences between PT patients and controls were measured using Freesurfer. PT patients (n = 79, after exclusion of patients with inadequate imaging data) exhibited significant decreases in cortical thickness in the anterior cingulate and entorhinal cortex, and decreased volume in the left putamen, compared to age-matched controls (n = 135). PT patients also demonstrated significant increased volume in frontal and occipital lobe structures, the cerebellum, hippocampi, and ventral pallidum. In conclusion, our findings suggest that individuals with PT may have structural differences in brain regions related to auditory processing, and depression, which provides additional evidence of the psychiatric sequalae of PT. These findings demonstrate that there are neuroanatomical alterations in patients with PT, emphasizing the value in evaluating and treating this disease to prevent these neuroanatomical differences from developing.

Over the past decades, morphometric analysis of brain MRI has contributed substantially to the understanding of healthy brain structure, development and aging as well as to improved characterisation of disease related pathologies. Certified commercial tools based on normative modeling of these metrics are meanwhile available for diagnostic purposes, but they are cost intensive and their clinical evaluation is still in its infancy. Here we have compared the performance of “ScanOMetrics”, an open-source research-level tool for detection of statistical anomalies in individual MRI scans, depending on whether it is operated on the output of FreeSurfer or of the deep learning based brain morphometry tool DL + DiReCT. When applied to the public OASIS3 dataset, containing patients with Alzheimer’s disease (AD) and healthy controls (HC), cortical thickness anomalies in patient scans were mainly detected in regions that are known as predilection areas of cortical atrophy in AD, regardless of the software used for extraction of the metrics. By contrast, anomaly detections in HCs were up to twenty-fold reduced and spatially unspecific using both DL + DiReCT and FreeSurfer. Progression of the atrophy pattern with clinical dementia rating (CDR) was clearly observable with both methods. DL + DiReCT provided results in less than 25 min, more than 15 times faster than FreeSurfer. This difference in computation time might be relevant when considering application of this or similar methodology as diagnostic decision support for neuroradiologists.

Abstract Background Previous studies have repeatedly found distinct brain morphometric changes in patients with fibromyalgia (FM), mainly affecting gray and white matter abnormalities in areas related to sensory and affective pain processing. However, few studies have thus far linked different types of structural changes and not much is known about behavioral and clinical determinants that might influence the emergence and progression of such changes. Methods We used voxel-based morphometry (VBM) and diffusion-tensor imaging (DTI) to detect regional patterns of (micro)structural gray (GM) and white matter (WM) alterations in 23 patients with FM compared to 21 healthy controls (HC), while considering the influence of demographic, psychometric, and clinical variables (age, symptom severity, pain duration, heat pain threshold, depression scores). Results VBM and DTI revealed striking patterns of brain morphometric changes in FM patients. Bilateral middle temporal gyrus (MTG), parahippocampal gyrus, left dorsal anterior cingulate cortex (dACC), right putamen, right caudate nucleus, and left dorsolateral prefrontal cortex (DLPFC) showed significantly decreased GM volumes. In contrast, increased GM volume was observed in bilateral cerebellum and left thalamus. Beyond that, patients displayed microstructural changes of WM connectivity within the medial lemniscus, corpus callosum, and tracts surrounding and connecting the thalamus. Sensory-discriminative aspects of pain (pain severity, pain thresholds) primarily showed negative correlations with GM within bilateral putamen, pallidum, right midcingulate cortex (MCC), and multiple thalamic substructures, whereas the chronicity of pain was negatively correlated with GM volumes within right insular cortex and left rolandic operculum. Affective-motivational aspects of pain (depressive mood, general activity) were related to GM and FA values within bilateral putamen and thalamus. Conclusions Our results suggest a variety of distinct structural brain changes in FM, particularly affecting areas involved in pain and emotion processing such as the thalamus, putamen, and insula.

The thalamus is central to brain functions ranging from primary sensory processing to higher-order cognition. Structural deficits in thalamic association nuclei such as the pulvinar and mediodorsal nuclei have previously been reported in schizophrenia. However, the specificity with regards to clinical presentation, and whether or not bipolar disorder (BD) is associated with similar alterations is unclear. We investigated thalamic nuclei volumes in 334 patients with schizophrenia spectrum disorders (SSD) (median age 29 years, 59 % male), 322 patients with BD (30 years, 40 % male), and 826 healthy controls (HC) (34 years, 54 % male). Volumes of 25 thalamic nuclei were extracted from T1-weighted magnetic resonance imaging using an automated Bayesian segmentation method and compared between groups. Furthermore, we explored associations with clinical characteristics across diagnostic groups, including psychotic and mood symptoms and medication use, as well as diagnostic subtype in BD. Significantly smaller volumes were found in the mediodorsal, pulvinar, and lateral and medial geniculate thalamic nuclei in SSD. Similarly, smaller volumes were found in BD in the same four regions, but mediodorsal nucleus volume alterations were limited to its lateral part and pulvinar alterations to its anterior region. Smaller volumes in BD compared to HC were seen only in BD type I, not BD type II. Across diagnoses, having more negative symptoms was associated with smaller pulvinar volumes. Structural alterations were found in both SSD and BD, mainly in the thalamic association nuclei. Structural deficits in the pulvinar may be of relevance for negative symptoms. [ABSTRACT FROM AUTHOR]

Background and purposeIn this study, we used power analysis to calculate required sample sizes to detect group-level changes in quantitative neuroanatomical estimates derived from MRI scans obtained from multiple imaging centers. Sample size estimates were derived from (i) standardized 3T image acquisition protocols and (ii) nonstandardized clinically acquired images obtained at both 1.5 and 3T as part of the multicenter Human Epilepsy Project. Sample size estimates were compared to assess the benefit of standardizing acquisition protocols.MethodsCortical thickness, hippocampal volume, and whole brain volume were estimated from whole brain T1-weighted MRI scans processed using Freesurfer v6.0. Sample sizes required to detect a range of effect sizes were calculated using (i) standard t-test based power analysis methods and (ii) a nonparametric bootstrap approach.ResultsA total of 32 participants were included in our analyses, aged 29.9 ± 12.62 years. Standard deviation estimates were lower for all quantitative neuroanatomical metrics when assessed using standardized protocols. Required sample sizes per group to detect a given effect size were markedly reduced when using standardized protocols, particularly for cortical thickness changes

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.

Abstract Background Angelman syndrome (AS) is a neurodevelopmental disorder with serious seizures. We aim to explore the brain morphometry of patients with AS and figure out whether the seizure is associated with brain development. Methods Seventy-three patients and 26 healthy controls (HC) underwent high-resolution structural brain MRI. Group differences between the HC group and the AS group and also between AS patients with seizure (AS-Se) and age-matched AS patients with non-seizure (AS-NSe) were compared. The voxel-based and surface-based morphometry analyses were used in our study. Gray matter volume, cortical thickness (CTH), and local gyrification index (LGI) were assessed to analyze the cortical and subcortical structure alteration in the AS brain. Results Firstly, compared with the HC group, children with AS were found to have a significant decrease in gray matter volume in the subcortical nucleus, cortical, and cerebellum. However, the gray matter volume of AS patients in the inferior precuneus was significantly increased. Secondly, patients with AS had significantly increased LGI in the whole brain as compared with HC. Thirdly, the comparison of AS-Se and the AS-NSe groups revealed a significant decrease in caudate volume in the AS-Se group. Lastly, we further selected the caudate and the precuneus as ROIs for volumetric analysis, the AS group showed significantly increased LGI in the precuneus and reduced CTH in the right precuneus. Between the AS-Se and the AS-NSe groups, the AS-Se group exhibited significantly lower density in the caudate, while only the CTH in the left precuneus showed a significant difference. Conclusions These results revealed cortical and subcortical morphological alterations in patients with AS, including globally the decreased brain volume in the subcortical nucleus, the increased gray matter volume of precuneus, and the whole-brain increase of LGI and reduction of CTH. The abnormal brain pattern was more serious in patients with seizures, suggesting that the occurrence of seizures may be related to abnormal brain changes.

Manzar Ashtari,1– 3 Mikhail Lipin,1,2 Michelle Duong,4 Gui-Shuang Ying,5 Yinxi Yu,5 Albert Maguire,1,2 Jean Bennett1,2 1Department of Ophthalmology, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA; 2Department of Ophthalmology, Center for Advanced Retinal & Ocular Therapeutics (CAROT) at the University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA; 3Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA; 4Emergency Department, Mainline Health, Bryn Mawr, PA, USA; 5Department of Ophthalmology, Center for Preventative Ophthalmology and Biostatistics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USACorrespondence: Manzar Ashtari, University of Pennsylvania, Perelman School of Medicine, Room 201 Anatomy/Chemistry Building, Philadelphia, PA, 19102, USA, Tel +1 215– 746-8259, Email ashtari@pennmedicine.upenn.eduIntroduction: Previous works on experience-dependent brain plasticity have been limited to the cortical structures, overlooking subcortical visual structures such as the lateral geniculate nucleus (LGN). Animal studies have shown substantial experience dependent plasticity and using fMRI, human studies have demonstrated similar properties in patients with cataract surgery. However, in neither animal nor human studies LGN has not been directly assessed, mainly due to its small size, tissue heterogeneity, low contrast/noise ratio, and low spatial resolution.Methods: Utilizing a new algorithm that markedly improves the LGN visibility, LGN was evaluated in a group of low vision patients before and after retinal intervention to reinstate vision and normal sighted matched controls.Results: Between and within groups comparisons showed that patients had significantly smaller left (p< 0.0001) and right (p < 0.00002) LGN volumes at baseline as compared to the one-year follow-up volumes. The same baseline and one year comparison in controls was not significant. Significant positive correlations were observed between the incremental volume increase after gene therapy of the left LGN and the incremental increase in the right (r = 0.71, p < 0.02) and left (r = 0.72, p = 0.018) visual fields. Incremental volume increase of the right LGN also showed a similar positive slope but did not reach significance.Discussion: These results show that despite significantly less volume at baseline, retinal gene therapy promotes robust expansion and increase in LGN volume. Reinstating vision may have facilitated the establishment of new connections between the retina and the LGN and/or unmasking of the dormant connections. The exact trajectory of the structural changes taking place in LGN is unclear but our data shows that even after years of low vision, the LGN in RPE65 patients has the potential for plasticity and expansion to a nearly normal volume one year after gene therapy administration.Keywords: brain plasticity, retinal gene therapy, lateral geniculate nucleus, image processing, brain morphometry

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. [ABSTRACT FROM AUTHOR]

Adherence to 24-hour movement guidelines of ≥60 minutes of physical activity, ≤2 hours of screen time, and 9–11 hours of sleep has been shown to benefit cognitive, physical, and psychosocial health in children and young adolescents aged 5–13 years. However, these findings have mostly been based on cross-sectional studies or relatively small samples and the associations between adherence to guidelines and brain structure remain to be evaluated. Data from the Adolescent Brain Cognitive Development℠ (ABCD) study of 10,574 early adolescents aged 9–14 years from September 2016 to January 2021 were used to examine whether adherence to 24-hour movement guidelines benefits cognition (general cognitive ability, executive function, and learning/memory assessed by the National Institutes of Health Toolbox neurocognitive battery), body mass index, psychosocial health (internalizing, externalizing, and total problems from the parent-reported Child Behavior Checklist), and magnetic resonance imaging–derived brain morphometric measures at baseline (T1), ∼2 years later (T2), and longitudinally from T1 to T2 (T2-T1). Multivariable linear mixed models were used, with adjustments for sociodemographic confounders. Time elapsed and T1 outcome measures were also controlled for in longitudinal models. Better cognitive scores, fewer behavioral problems, lower adiposity levels, and greater gray matter volumes were observed in those who met both sleep and screen time recommendations compared to those who met none. Longitudinal follow-up further supports these findings; participants who met both recommendations at T1 and T2 evidenced better outcome measures than those who met none. These findings support consideration of integrated rather than isolated movement recommendations across the day in early adolescence for better cognitive, physical and psychosocial health. Although the associations between physical activity and health indicators were less consistent in this study, the significant findings from sleep and screen time demonstrate the importance of considering movement recommendations in an integrated rather than isolated manner for adolescent health. It is recommended that movement behaviors be simultaneously targeted for better developmental outcomes. [ABSTRACT FROM AUTHOR]

Bullying victimization is associated with a doubled risk of attempting suicide in adulthood. Two longitudinal brain morphometry studies identified the fusiform gyrus and putamen as vulnerable to bullying. No study identified how neural alterations may mediate the effect of bullying on cognition. We assessed participants with caregiver-reported bullying (N = 323) and matched non-bullied controls (N = 322) from the Adolescent Brain Cognitive Development Study dataset to identify changes in brain morphometry associated with ongoing bullying victimization over two years and determine whether such alterations mediated the effect of bullying on cognition.Bullied children (38.7% girls, 47.7% racial minorities, 9.88 ± 0.62 years at baseline) had poorer cognitive performance (P

Abstract Background SPG11-linked hereditary spastic paraplegia is characterized by multisystem neurodegeneration leading to a complex clinical and yet incurable phenotype of progressive spasticity and weakness. Severe cognitive symptoms are present in the majority of SPG11 patients, but a systematic and multidimensional analysis of the neuropsychological phenotype in a larger cohort is lacking. While thinning of the corpus callosum is a well-known structural hallmark observed in SPG11 patients, the neuroanatomical pattern of cortical degeneration is less understood. We here aimed to integrate neuropsychological and brain morphometric measures in SPG11. Methods We examined the neuropsychological profile in 16 SPG11 patients using a defined neuropsychological testing battery. Long-term follow up testing was performed in 7 patients. Cortical and subcortical degeneration was analyzed using an approved, artificial intelligence based magnetic resonance imaging brain morphometry, comparing patients to established reference values and to matched controls. Results In SPG11 patients, verbal fluency and memory as well as frontal-executive functions were severely impaired. Later disease stages were associated with a global pattern of impairments. Interestingly, reaction times correlated significantly with disease progression. Brain morphometry showed a significant reduction of cortical and subcortical parenchymal volume following a rostro-caudal gradient in SPG11. Whereas performance in memory tasks correlated with white matter damage, verbal fluency measures showed strong associations with frontal and parietal cortical volumes. Conclusions The present data will help define neuropsychological and imaging read out parameters in early as well as in advanced clinical stages for future interventional trials in SPG11.

Background: Genome-wide association studies (GWAS) have identified large numbers of genetic variants associated with cognition. However, little is known about how these genetic discoveries impact cognitive aging. Methods: We conducted polygenic-index (PGI) analysis of cognitive performance in n = 168 European-ancestry adults aged 20–80. We computed PGIs based on GWAS of cognitive performance in young/middle-aged and older adults. We tested associations of the PGI with cognitive performance, as measured through neuropsychological evaluation. We explored whether these associations were accounted for by magnetic resonance imaging (MRI) measures of brain-aging phenotypes: total gray matter volume (GM), cortical thickness (CT), and white matter hyperintensities burden (WMH). Results: Participants with higher PGI values performed better on cognitive tests (B = 0.627, SE = 0.196, p = 0.002) (age, sex, and principal components as covariates). Associations remained significant with inclusion of covariates for MRI measures of brain aging; B = 0.439, SE: 0.198, p = 0.028). PGI associations were stronger in young and middle-aged (age

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. [ABSTRACT FROM AUTHOR]

Background: Angelman syndrome (AS) is a neurodevelopmental disorder with serious seizures. We aim to explore the brain morphometry of patients with AS and figure out whether the seizure is associated with brain development. Methods: Seventy-three patients and 26 healthy controls (HC) underwent high-resolution structural brain MRI. Group differences between the HC group and the AS group and also between AS patients with seizure (AS-Se) and age-matched AS patients with non-seizure (AS-NSe) were compared. The voxel-based and surface-based morphometry analyses were used in our study. Gray matter volume, cortical thickness (CTH), and local gyrification index (LGI) were assessed to analyze the cortical and subcortical structure alteration in the AS brain. Results: Firstly, compared with the HC group, children with AS were found to have a significant decrease in gray matter volume in the subcortical nucleus, cortical, and cerebellum. However, the gray matter volume of AS patients in the inferior precuneus was significantly increased. Secondly, patients with AS had significantly increased LGI in the whole brain as compared with HC. Thirdly, the comparison of AS-Se and the AS-NSe groups revealed a significant decrease in caudate volume in the AS-Se group. Lastly, we further selected the caudate and the precuneus as ROIs for volumetric analysis, the AS group showed significantly increased LGI in the precuneus and reduced CTH in the right precuneus. Between the AS-Se and the AS-NSe groups, the AS-Se group exhibited significantly lower density in the caudate, while only the CTH in the left precuneus showed a significant difference. Conclusions: These results revealed cortical and subcortical morphological alterations in patients with AS, including globally the decreased brain volume in the subcortical nucleus, the increased gray matter volume of precuneus, and the whole-brain increase of LGI and reduction of CTH. The abnormal brain pattern was more serious in patients with seizures, suggesting that the occurrence of seizures may be related to abnormal brain changes. [ABSTRACT FROM AUTHOR]

Evidence suggests that psychopathology is associated with an advanced brain ageing process, typically mapped using machine learning models that predict an individual's age based on structural neuroimaging data. The brain predicted age difference (brain-PAD) captures the deviation of brain age from chronological age. Substantial heterogeneity between studies has introduced uncertainty regarding the magnitude of the brain-PAD in adult psychopathology. The present meta-analysis aimed to quantify structural MRI-based brain-PAD in adult psychotic and mood disorders, while addressing possible sources of heterogeneity related to diagnosis subtypes, segmentation method, age and sex. Clinical factors influencing brain ageing in axis 1 psychiatric disorders were systematically reviewed. Thirty-three studies were included for review. A random-effects meta-analysis revealed a brain-PAD of +3.12 (standard error = 0.49) years in psychotic disorders (n = 16 studies), +2.04 (0.10) years in bipolar disorder (n = 5), and +0.90 (0.20) years in major depression (n = 7). An exploratory meta-analysis found a brain-PAD of +1.57 (0.67) in first episode psychosis (n = 4), which was smaller than that observed in psychosis and schizophrenia (n = 10, +3.87 (0.61)). Patient mean age significantly explained heterogeneity in effect size estimates in psychotic disorders, but not mood disorders. The systematic review determined that clinical factors, such as higher symptom severity, may be associated with a larger brain-PAD in psychopathology. In conclusion, larger structural MRI-based brain-PAD was confirmed in adult psychopathology. Preliminary evidence was obtained that brain ageing is greater in those with prolonged duration of psychotic disorders. Accentuated brain ageing may underlie the cognitive difficulties experienced by some patients, and may be progressive in nature. • Machine learning models can accurately predict brain age from brain imaging data. • This meta-analysis found advanced brain ageing in psychotic and mood disorders. • Brain ageing may possibly advance with prolonged duration of psychotic disorders. • Symptom severity of psychopathology is associated with advanced brain ageing. [ABSTRACT FROM AUTHOR]

Compelling evidence has been presented in favor of herpes simplex virus type 1 (HSV1) being one of the causative agents of Alzheimer's disease (AD). The success of HSV1 as a pathogen relates to its sophisticated strategies to evade host immunosurveillance. One strategy involves encoding a decoy Fcγ receptor (FcγR) that thwarts the Fcγ-mediated effector functions, such as antibody-dependent cellular cytotoxicity (ADCC), a potent host immunosurveillance mechanism against virally infected cells. The decoy FcγR binds to antibodies of all IgG subclasses, except IgG3; therefore, IgG3 would be expected to play an important role in viral clearance by neutralization and ADCC, and thus contribute to protection from HSV1-spurred diseases. Previous studies have shown significant association between anti-HSV1 IgG3 antibodies and cortical thinning of the areas of the brain typically altered in AD and also targeted by HSV1. The aim of the present investigation was to determine whether GM (γ marker) 5 and GM 21 allotypes, hereditary allelic determinants expressed on IgG3, together with brain biomarkers of neural integrity, contributed to neurodegeneration—as measured by mini-mental state examination (MMSE) score—in patients with AD. Multiple regression analyses showed that the homozygous GM 5/5 genotype, preserved right hippocampus, and right insula thickness were associated with higher MMSE scores (p < 0.001), whereas the opposite pattern and GM 5/21 genotype were associated with worse clinical profiles. Influence of GM 5/21-expressing IgG3 antibodies on the ADCC of HSV1-infected neurons could, at least partially, explain these results. • Immunoglobulin GM 5/5 genotype, preserved right hippocampus, and right insula thickness were associated with higher MMSE scores. • Whereas the opposite pattern and GM 5/21 genotype were associated with worse clinical profiles. • Influence of GM 5/21-expressing IgG3 antibodies on the ADCC of HSV1-infected neurons could, at least partially, explain these results. [ABSTRACT FROM AUTHOR]

BackgroundThe combined analysis of imaging and functional modalities is supposed to improve diagnostics of neurodegenerative diseases with advanced data science techniques.ObjectiveTo 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 methodsWe 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.ResultsIn 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.ConclusionThe 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.

BackgroundHuman 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).MethodsSixty-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.ResultsPrior 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.ConclusionsSubcortical atrophy and cortical thinning occur during untreated infection but may be arrested by cART. These findings emphasize the importance of early cART.

Several approaches have emerged to measure the cortical thickness (CT), which can be broadly divided into surface-based and voxel-based algorithms. We aimed to compare parcel-based CT estimation of the widely used FreeSurfer (FS) software and CAT12 software, which is a widely used voxel-based approach, and evaluate the test–retest (TRT) reliability of both methods. MRI images of 417 healthy individuals were analyzed. TRT reliability was performed on 60 participants. The mean CT of the parcels of the Desikan-Killiany atlas were calculated both in FS and CAT12. Linear mixed model was performed to compare the two methods and the TRT reliability, and paired-sample t-test for post-hoc analyses. Linear regression analyses were utilized to examine the regressions between the two methods and between different sessions with each method. CT values calculated using the two methods were significantly correlated (R2adj = 0.67). The significant interaction effect between the method and the parcels were due to larger CT values of FS in 32 of 68 parcels, whereas CT values of CAT12 were higher in 31 of 68 parcels. The TRT reliabilities of both approaches were excellent (FS R2adj = 0.95, CAT12 R2adj = 0.93). We conclude that both techniques can provide equally valid results for groups comparisons or follow-up studies as long as they are not mixed with each other. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Anhedonia is a core symptom of major depressive disorder (MDD) resulting from maladaptive reward processing. Electroconvulsive therapy (ECT) is an effective treatment for patients with MDD. No previous neuroimaging studies have taken a dimensional approach to assess whether ECT-induced volume changes are specifically related to improvements in anhedonia and positive valence emotional constructs. We aimed to assess the relationship between ECT-induced brain volumetric changes and improvement in anhedonia and reward processing in patients with MDD.Methods: We evaluated 15 patients with MDD before and after ECT. We used magnetic resonance imaging, clinical scales (i.e., Quick Inventory of Depressive Symptomatology for syndromal depression severity and Snaith-Hamilton Pleasure Scale for anhedonia) and the Temporal Experience of Pleasure Scale for anticipatory and consummatory experiences of pleasure. We identified 5 regions of interest within the reward circuit and a 6th control region relevant for MDD but not core to the reward system (Brodmann Area 25).Results: Anhedonia, anticipatory and consummatory reward processing improved after ECT. Volume increases within the right reward system separated anhedonia responders and non-responders. Improvement in anticipatory (but not consummatory) reward correlated with increases in volume in hippocampus, amygdala, ventral tegmental area and nucleus accumbens.Limitations: We evaluated a modest sample size of patients with concurrent pharmacological treatment using a subjective psychometric assessment.Conclusions: We highlight the importance of a dimensional and circuit-based approach to understanding target engagement and the mechanism of action of ECT, with the goal to define symptom- and circuit-specific response biomarkers for device neuromodulation therapies. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective: T helper 17 (Th17) pathway has been reported to be abnormal in schizophrenia; however, it is not known whether variation within genes of this pathway has any impact on schizophrenia. Herein, the impact of genetic variations and gene–gene interactions of Th17 pathway-related genes on the risk, psychopathology, and brain volume was examined in schizophrenia patients. Methods: Functional polymorphisms within interleukin 6 (IL6)(rs1800795 and rs1800797), IL10 (rs1800872 and rs1800896), IL17A (rs2275913 and rs8193036), IL22 (rs2227484 and rs2227485), IL23R (rs1884444), and IL27 (rs153109 and rs181206) genes were studied in 224 schizophrenia patients and 226 healthy controls. These variants were correlated with the brain morphometry, analyzed using MRI in a subset of patients (n = 117) and controls (n = 137). Results: Patients carrying CC genotype of rs2227484 of IL22 gene had significantly higher apathy total score [ F (1,183) = 5.60; P = 0.019; partial ɳ2 = 0.030]. Significant epistatic interactions between IL6 (rs1800797) and IL17A (rs2275913) genes were observed in schizophrenia patients. GG genotype of rs2275913 of IL17A gene was associated with reduced right middle occipital gyrus volume in schizophrenia patients (T = 4.56; P < 0.001). Conclusion: Interactions between genes of Th17 pathway impact the risk for schizophrenia. The variants of Th17 pathway-related genes seem to have a determining effect on psychopathology and brain morphometric changes in schizophrenia. [ABSTRACT FROM AUTHOR]

Background: SPG11-linked hereditary spastic paraplegia is characterized by multisystem neurodegeneration leading to a complex clinical and yet incurable phenotype of progressive spasticity and weakness. Severe cognitive symptoms are present in the majority of SPG11 patients, but a systematic and multidimensional analysis of the neuropsychological phenotype in a larger cohort is lacking. While thinning of the corpus callosum is a well-known structural hallmark observed in SPG11 patients, the neuroanatomical pattern of cortical degeneration is less understood. We here aimed to integrate neuropsychological and brain morphometric measures in SPG11.Methods: We examined the neuropsychological profile in 16 SPG11 patients using a defined neuropsychological testing battery. Long-term follow up testing was performed in 7 patients. Cortical and subcortical degeneration was analyzed using an approved, artificial intelligence based magnetic resonance imaging brain morphometry, comparing patients to established reference values and to matched controls.Results: In SPG11 patients, verbal fluency and memory as well as frontal-executive functions were severely impaired. Later disease stages were associated with a global pattern of impairments. Interestingly, reaction times correlated significantly with disease progression. Brain morphometry showed a significant reduction of cortical and subcortical parenchymal volume following a rostro-caudal gradient in SPG11. Whereas performance in memory tasks correlated with white matter damage, verbal fluency measures showed strong associations with frontal and parietal cortical volumes.Conclusions: The present data will help define neuropsychological and imaging read out parameters in early as well as in advanced clinical stages for future interventional trials in SPG11. [ABSTRACT FROM AUTHOR]

ART interruption in children can occur especially in resource-limited settings for reasons including poor adherence, stock-outs, ART intolerance of non-pediatric formulas and pill size, as well as ultimately to test for HIV remission. Although early ART initiation is now standard of care in pediatric HIV management, very little is known on the effect of early ART initiation or subsequent interruption on brain development. This study aimed to investigate the effect of ART interruption on brain cortical thickness (CT) and folding in a subset of children from the Children with HIV Early antiRetroviral therapy (CHER) trial cohort who all started ART before 18 months of age. CHER participants in the neuroimaging follow-up study had magnetic resonance (MRI) scans on a 3T Siemens Allegra brain scanner at age 5.44 ± 0.37 years. MR images were processed using the automated cross-sectional stream in FreeSurfer v6.0 and vertex wise comparisons of CT and local gyrification indices (LGIs) were performed between HIV+ children and HIV- controls, as well as between HIV+ children on interrupted or continuous ART and controls. HIV+ children (n = 46) showed thicker cortex than HIV- children (n = 29) in bilateral frontal and left temporo-insular regions but lower LGIs in left superior and bilateral medial orbitofrontal cortex extending into rostral anterior cingulate. Children on interrupted ART (n = 21) had thicker cortex than HIV- controls in left frontal and right insular regions, but children on continuous treatment (n = 25) showed no difference from controls. Children on both interrupted and continuous ART showed region-specific alterations in LGI relative to controls. Cortical folding appears more sensitive than CT to early life events including early ART and interruption. However, immune health resilience in children can translate to long term preservation of morphometric brain development, especially for those on early and continuous treatment.

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. [ABSTRACT FROM AUTHOR]

Principal and Gaussian curvatures are commonly used intrinsic metrics for geometric morphometrics analysis: to assess morphometric changes in brain geometry (developmental neuroimaging studies), to quantify shape deformation (organ motion assessment), or to analyze shape variability across subjects in musculoskeletal studies (statistical shape analysis of bones). However, most of existing algorithms for estimating curvatures act on explicit surfaces (triangle meshes), making them time consuming and sensitive to parameterization and neighborhood size. In this paper, we present a suite of fast and parameterization-free algorithms to estimate second order morphometric parameters given an implicit representation for the surface and without any loss of accuracy. We first show results for direct comparisons of our algorithms with a suite of popular algorithms for estimating curvatures of surfaces represented by triangular meshes. Then, in the context of brain imaging, methods were validated against developmental brain MRI data in which surface based analysis has very often failed. We also provided a modified version of the algorithm that can deal with a Freesurfer output surface mesh, and which was evaluated using an adult brain with more complicated folding patterns. Our algorithm provided a more realistic measures of intrinsic curvature for the white matter (mostly ranged between ±0.07 mm−2) which confirms its robustness. As compared to mesh-based algorithms, our algorithm reduces computation times from a few minutes to only a few seconds, showing a decrease by a factor of up to 7.

Generative Adversarial Networks (GAN) are emerging as an exciting training paradigm which promises a step improvement to the impressive feature learning capabilities of deep neural networks. Unlike supervised learning approaches, GAN learns generalizable features without requiring labeled images to achieve new capabilities like distinguishing previously unseen anomalies, creating novel instances of data and factorizing learned features into explainable dimensions in fully unsupervised fashion. The advanced feature learning property of GAN will enable the next generation of computational image understanding tasks. However, GAN models are difficult to train to converge towards good models, especially for high resolution and high dimensional datasets like image volumes. We develop a GAN approach to learn a generative model of T1-contrast 3D MRI image volumes of the healthy human brain by training on 1112 MRI images from the Human Connectome Project. Our method utilizes a first unconditional Super-Resolution GAN, dubbed the shape network, to learn the 3D shape variations in adult brains and a second conditional pix2pix GAN, dubbed the texture network, to upgrade image slices with realistic local contrast patterns. Novel 3D MRI images are synthesized by first applying the 3D voxel-wise deformation map which is generated from the shape network to deform the Montreal Neurological Institute (MNI) brain template and subsequently performing style transfer on axial-wise slices using the texture network. The Maximum Mean Discrepancy (MMD) and Multi-scale Structural Similarity Index Measure (MS-SSIM) scores of MRI image volumes synthesized using our GAN approach are competitive with state-of-art GAN methods. Our work establishes the feasibility of an alternative approach to high-dimensional GAN learning - splitting the type of information content learned among several GANs can be an effective form of regularization and complementary to latent code shaping or super-resolution approaches in state-of-the-art methods.