Structural Brain Magnetic Resonance Imaging Research Articles

Deep learning of structural MRI predicts fluid, crystallized, and general intelligence.

Can brain structure predict human intelligence? T1-weighted structural brain magnetic resonance images (sMRI) have been correlated with intelligence. However, the population-level association does not fully account for individual variability in intelligence. To address this, studies have emerged recently to predict individual subject's intelligence or neurocognitive scores. However, they are mostly on predicting fluid intelligence (the ability to solve new problems). Studies are lacking to predict crystallized intelligence (the ability to accumulate knowledge) or general intelligence (fluid and crystallized intelligence combined). This study tests whether deep learning of sMRI can predict an individual subject's verbal, comprehensive, and full-scale intelligence quotients (VIQ, PIQ, and FSIQ), which reflect fluid and crystallized intelligence. We performed a comprehensive set of 432 experiments, using different input image channels, six deep learning models, and two outcome settings, in 850 healthy and autistic subjects 6-64 years of age. Our findings indicate a statistically significant potential of T1-weighted sMRI in predicting intelligence, with a Pearson correlation exceeding 0.21 (p < 0.001). Interestingly, we observed that an increase in the complexity of deep learning models does not necessarily translate to higher accuracy in intelligence prediction. The interpretations of our 2D and 3D CNNs, based on GradCAM, align well with the Parieto-Frontal Integration Theory (P-FIT), reinforcing the theory's suggestion that human intelligence is a result of interactions among various brain regions, including the occipital, temporal, parietal, and frontal lobes. These promising results invite further studies and open new questions in the field.

FONDUE: Robust resolution-invariant denoising of MR Images using Nested UNets

Abstract Recent human magnetic resonance imaging (MRI) studies continually push the boundaries of spatial resolution as a means to enhance levels of neuroanatomical detail and increase the accuracy and sensitivity of derived brain morphometry measures. However, acquisitions required to achieve these resolutions have a higher noise floor, potentially impacting segmentation and morphometric analysis results. This study proposes a novel, fast, robust, and resolution-invariant deep learning method to denoise structural human brain MRIs. We explore denoising of T1-weighted (T1w) brain images from varying field strengths (1.5T to 7T), voxel sizes (1.2mm to 250µm), scanner vendors (Siemens, GE, and Phillips), and diseased and healthy participants from a wide age range (young adults to aging individuals). Our proposed Fast-Optimized Network for Denoising through residual Unified Ensembles (FONDUE) method demonstrated stable denoising capabilities across multiple resolutions with performance on par or superior to the state-of-the-art methods while being several orders of magnitude faster at low relative cost when using a dedicated Graphics Processing Unit (GPU). FONDUE achieved the best performance on at least one of the four denoising-performance metrics on all the test datasets used, showing its generalization capabilities and stability. Due to its high-quality performance, robustness, fast execution times, and relatively low-GPU memory requirements, as well as its open-source public availability, FONDUE can be widely used for structural MRI denoising, especially in large-cohort studies. We have made the FONDUE repository and all training and evaluation scripts as well as the trained weights available at https://github.com/waadgo/FONDUE.

Comparison of brief olfactory and cognitive assessments to neuroimaging biomarkers in the prediction of cognitive decline and dementia in the MCSA cohort.

We evaluated impaired odor identification and global cognition as simple, cost-effective alternatives to neuroimaging biomarkers to predict cognitive decline and dementia in the Mayo Clinic Study of Aging. Six hundred forty-seven participants (mean 8.1, standard deviation 3.4 years' follow-up) had the following baseline procedures: modified Blessed Information Memory Concentration Test (BIMCT), 12-item Brief Smell Identification Test (BSIT), structural brain magnetic resonance imaging (MRI), and positron emission tomography (PET) imaging with 11C-Pittsburgh compound B (11C-PiB) and fluorodeoxyglucose (FDG; subset). Cognitive decline developed in 102 participants and dementia in 34 participants. In survival analyses, PiB PET showed robust prediction for cognitive decline. Impaired BSIT, impaired BIMCT, MRI, and FDG measures were also significant predictors. The combination of demographics + BSIT + BIMCT showed strong predictive utility (C-index 0.81), similar to demographics + PiB PET (C-index 0.80). Similar but stronger results were obtained for prediction of dementia. Impairment in both odor identification test and global cognition was comparable to PiB PET for predicting cognitive decline and dementia. In 647 participants in the population-based Mayo Clinic Study of Aging, several clinical markers and biomarkers each predicted cognitive decline or dementia during an average 8 years of follow-up. The combination of the demographic variables of age, sex, and education with a brief odor identification test (BSIT) and a global cognitive test (Blessed Information Memory Concentration Test) showed strong predictive utility (C-index 0.81) for cognitive decline that was similar to the demographic variables combined with Pittsburgh Compound B amyloid imaging (C-index 0.80). Combining a brief odor identification test with a brief cognitive test needs consideration as a simple, cost-effective option in the clinical assessment of individuals at risk of cognitive decline and dementia, as well as a potential tool to identify individuals who may benefit from disease-modifying treatments and to screen participants for prevention trials.

Reproducible brain PET data analysis: easier said than done.

While a great deal of recent effort has focused on addressing a perceived reproducibility crisis within brain structural magnetic resonance imaging (MRI) and functional MRI research communities, this article argues that brain positron emission tomography (PET) research stands on even more fragile ground, lagging behind efforts to address MRI reproducibility. We begin by examining the current landscape of factors that contribute to reproducible neuroimaging data analysis, including scientific standards, analytic plan pre-registration, data and code sharing, containerized workflows, and standardized processing pipelines. We then focus on disparities in the current status of these factors between brain MRI and brain PET. To demonstrate the positive impact that further developing such reproducibility factors would have on brain PET research, we present a case study that illustrates the many challenges faced by one laboratory that attempted to reproduce a community-standard brain PET processing pipeline. We identified key areas in which the brain PET community could enhance reproducibility, including stricter reporting policies among PET dedicated journals, data repositories, containerized analysis tools, and standardized processing pipelines. Other solutions such as mandatory pre-registration, data sharing, code availability as a condition of grant funding, and online forums and standardized reporting templates, are also discussed. Bolstering these reproducibility factors within the brain PET research community has the potential to unlock the full potential of brain PET research, propelling it toward a higher-impact future.

Association of birth weight with neuropsychological functioning in early adolescence: A retrospective cohort study

ObjectiveThis study aimed to compare the neuropsychological function in early adolescence between children born small for gestational age (SGA) or large for gestational age (LGA) and those born appropriate for gestational age (AGA). MethodsThis retrospective cohort study utilized data from the Adolescent Brain Cognitive Development study in 2016–18. Children born of singleton pregnancy with complete information of birth weight and delivery week were enrolled. Their neuropsychological functioning were assessed by the brain structural magnetic resonance imaging (MRI), combined with cognitive and behavioral measurements. Linear mixed-effects models and subgroup analyses were performed. ResultsAmong 5,922 children aged 9–11, children born SGA and LGA demonstrated similar cognitive and behavioral performances as children born AGA (P > 0.05). In the MRI measurement, brain area and volume were lower among SGA children compared to AGA children (t=-5.626, Cohen's d = 0.448, P < 0.001; t=-6.071, Cohen's d = 0.427, P < 0.001); brain area and volume were higher among LGA children compared to AGA children (t = 8.562, Cohen's d = 0.470, P < 0.001; t = 8.562, Cohen's d = 0.470, P < 0.001). Cortical thickness was of no statistical difference (P > 0.05). These associations were confirmed by sensitivity analyses and propensity score matching. ConclusionChildren born of SGA and LGA status were associated with altered brain area and volume structure in early adolescence.

Correlations between Immunoinflammatory Factor Levels and Cognitive Functions and Brain Structural Magnetic Resonance Imaging Features among Patients with Primary Schizophrenia.

Schizophrenia is associated with significant cognitive impairment. However, the pathophysiological mechanisms underlying cognitive dysfunction in schizophrenia remain unclear. Based on the latest concept of cognition, immunoinflammatory factors and structural magnetic resonance imaging (sMRI) features of the brain are considered markers of schizophrenia. This study explored the correlations between cognitive function and immunoinflammatory factors and sMRI in primary schizophrenia patients. Non-interventional cross-sectional study was conducted, including 21 patients with primary schizophrenia, who were identified based on the Diagnostic and Statistical Manual, Fifth Edition (DSM-V) and grouped under the observation group. Thirty healthy volunteers with age, gender, hand dominance, and education duration matched with those of the primary schizophrenia patients were recruited to the control group. All subjects underwent sMRI examination. MATRICS consensus cognitive battery (MCCB) was employed to assess the cognitive functions among patients with primary schizophrenia. The levels of serum amyloid A (SAA), monocyte chemoattractant protein 1 (MCP-1), and chitinase-3-like protein 1 (YKL-40) were measured by means of enzyme-linked immunosorbent assay (ELISA). Pearson's correlation analysis was carried out to analyze the correlation between immunoinflammatory factor levels and cognitive functions as well as brain sMRI features. The scores for all MCCB items and the total score for the observation group were apparently lower than those for the control group (p < 0.001), while the YKL-40 and SAA levels were notably higher in the observation group (t = 3.406, p < 0.05; t = 5.656, p < 0.001). Compared to the control group, the observation group exhibited reduced volumes of left and right insular lobes, left and right anterior cingulate cortexes, left and right hippocampi, right parahippocampal gyrus, right amygdala, left inferior occipital lobe, left superior temporal lobe, left temporal pole, and left middle and inferior temporal lobes (p < 0.001). The levels of YKL-40 and SAA were both negatively correlated with MCCB score (r = -0.3668, p = 0.004; r = -0.8495, p < 0.001). The volumes of right insular lobe, left and right anterior cingulate cortexes, right parahippocampal gyrus, right amygdala, and gray matter in left middle temporal lobe were all negatively correlated with the levels of YKL-40 and SAA (p < 0.05). Cognitive impairment in patients with primary schizophrenia is associated with increased serum SAA and YKL-40 levels and decreased gray matter volume.

Itching Frequency and Neuroanatomic Correlates in Frontotemporal Lobar Degeneration

Itching is common in geriatric populations and is frequently linked to dermatological or systemic conditions. Itching engages specific brain regions that are implicated in the pathogenesis of frontotemporal lobar degeneration spectrum disorders (FTLD-SD). Thus, itching of undetermined origin (IUO) may indicate the presence of a neurodegenerative process. To compare the frequency of itching in FTLD-SD and Alzheimer disease (AD) and to determine the neuroanatomical underpinnings of IUO. This case-control study evaluated data and brain magnetic resonance images (MRIs) for participants with FTLD-SD or AD. Participants of a research study on FTLD-SD at the University of California, San Francisco, Memory and Aging Center were evaluated from May 1, 2002, to December 31, 2021. The exposure group underwent structural brain MRI within 6 months of initial diagnosis. Research visit summaries were reviewed to validate qualitative details and accurately identify itching with undetermined origin (IUO). Symptoms suggestive of FTLD-SD or AD. Frequency of itching in FTLD-SD and AD and neuroanatomic correlates. A total of 2091 research visit summaries were reviewed for 1112 patients exhibiting symptoms indicative of FTLD-SD or AD. From 795 records where itching or a related phrase was endorsed, 137 had IUO. A total of 454 participants were included in the study: 137 in the itching group (mean [SD] age, 62.7 [9.9] years; 74 [54%] females and 63 males [46%]) and 317 in the nonitching group (mean [SD] age, 60.7 [10.8] years; 154 [49%] females and 163 males [51%]). Groups were similar in age, sex, and disease severity. More frequent itching was found in FTLD-SD (95/248 patients [38%], of which 44 [46%] had behavioral variant frontotemporal dementia [bvFTD]) compared with the AD group (14/77 patients [18%]; P = .001). The odds of itching were 2.4 (95% CI, 1.48-3.97) times higher for FTLD-SD compared with all other cases of dementia. Compared with healthy controls, the group with IUO exhibited greater gray matter atrophy bilaterally in the amygdala, insula, precentral gyrus, and cingulum, as well as in the right frontal superior gyrus and thalamus. Among patients with bvFTD and itching vs bvFTD without itching, itching was associated with right-lateralized gray matter atrophy affecting the insula, thalamus, superior frontal gyrus, and cingulum. Among individuals with IUO, FTLD-SD was disproportionately represented compared with AD. In FTLD-SD, dysfunction in the right anterior insula and its connected regions, including the right precentral gyrus, cingulum, and bilateral amygdala, contribute to dysregulation of the itching-scratching networks, resulting in uncontrollable itching or skin picking. Awareness among physicians about the relationship between neurodegeneration and itching may help in the management of itch in older individuals. Further studies are needed to determine the best treatments for these symptoms in patients with neurodegenerative disorders.

Cholinergic nucleus degeneration and its association with gait impairment in Parkinson’s disease

BackgroundThe contribution of cholinergic degeneration to gait disturbance in Parkinson’s disease (PD) is increasingly recognized, yet its relationship with dopaminergic-resistant gait parameters has been poorly investigated. We investigated the association between comprehensive gait parameters and cholinergic nucleus degeneration in PD.MethodsThis cross-sectional study enrolled 84 PD patients and 69 controls. All subjects underwent brain structural magnetic resonance imaging to assess the gray matter density (GMD) and volume (GMV) of the cholinergic nuclei (Ch123/Ch4). Gait parameters under single-task (ST) and dual-task (DT) walking tests were acquired using sensor wearables in PD group. We compared cholinergic nucleus morphology and gait performance between groups and examined their association.ResultsPD patients exhibited significantly decreased GMD and GMV of the left Ch4 compared to controls after reaching HY stage > 2. Significant correlations were observed between multiple gait parameters and bilateral Ch123/Ch4. After multiple testing correction, the Ch123/Ch4 degeneration was significantly associated with shorter stride length, lower gait velocity, longer stance phase, smaller ankle toe-off and heel-strike angles under both ST and DT condition. For PD patients with HY stage 1–2, there were no significant degeneration of Ch123/4, and only right side Ch123/Ch4 were corrected with the gait parameters. However, as the disease progressed to HY stage > 2, bilateral Ch123/Ch4 nuclei showed correlations with gait performance, with more extensive significant correlations were observed in the right side.ConclusionsOur study demonstrated the progressive association between cholinergic nuclei degeneration and gait impairment across different stages of PD, and highlighting the potential lateralization of the cholinergic nuclei’s impact on gait impairment. These findings offer insights for the design and implementation of future clinical trials investigating cholinergic treatments as a promising approach to address gait impairments in PD.

Neuroprotective Effects of Inhaled Xenon Gas on Brain Structural Gray Matter Changes After Out-of-Hospital Cardiac Arrest Evaluated by Morphometric Analysis: A Substudy of the Randomized Xe-Hypotheca Trial.

We have earlier reported that inhaled xenon combined with hypothermia attenuates brain white matter injury in comatose survivors of out-of-hospital cardiac arrest (OHCA). A predefined secondary objective was to assess the effect of inhaled xenon on the structural changes in gray matter in comatose survivors after OHCA. Patients were randomly assigned to receive either inhaled xenon combined with target temperature management (33°C) for 24h (n = 55, xenon group) or target temperature management alone (n = 55, control group). A change of brain gray matter volume was assessed with a voxel-based morphometry evaluation of high-resolution structural brain magnetic resonance imaging (MRI) data with Statistical Parametric Mapping. Patients were scheduled to undergo the first MRI between 36 and 52h and a second MRI 10days after OHCA. Of the 110 randomly assigned patients in the Xe-Hypotheca trial, 66 patients completed both MRI scans. After all imaging-based exclusions, 21 patients in the control group and 24 patients in the xenon group had both scan 1 and scan 2 available for analyses with scans that fulfilled the quality criteria. Compared with the xenon group, the control group had a significant decrease in brain gray matter volume in several clusters in the second scan compared with the first. In a between-group analysis, significant reductions were found in the right amygdala/entorhinal cortex (p = 0.025), left amygdala (p = 0.043), left middle temporal gyrus (p = 0.042), left inferior temporal gyrus (p = 0.008), left parahippocampal gyrus (p = 0.042), left temporal pole (p = 0.042), and left cerebellar cortex (p = 0.005). In the remaining gray matter areas, there were no significant changes between the groups. In comatose survivors of OHCA, inhaled xenon combined with targeted temperature management preserved gray matter better than hypothermia alone. ClinicalTrials.gov: NCT00879892.

Gait Analysis and Magnetic Resonance Imaging Characteristics in Patients with Isolated Rapid Eye Movement Sleep Behavior Disorder.

Isolated rapid eye movement sleep behavioral disorder (iRBD) can precede neurodegenerative diseases. There is an urgent need for biomarkers to aid early intervention and neuroprotection. The aim is to assess quantitative motor, cognitive, and brain magnetic resonance imaging (MRI) characteristics in iRBD patients. Thirty-eight polysomnography-confirmed iRBD patients and 28 age- and sex-matched healthy controls underwent clinical, cognitive, and motor functional evaluations, along with brain MRI. Motor tasks included nine-hole peg test, five-times-sit-to-stand test, timed-up-and-go test, and 4-meter walking test with and without cognitive dual task. Quantitative spatiotemporal gait parameters were obtained using an optoelectronic system. Brain MRI analysis included functional connectivity (FC) of the main resting-state networks, gray matter (GM) volume using voxel-based morphometry, cortical thickness, and deep GM and brainstem volumes using FMRIB's Integrated Registration and Segmentation Tool and FreeSurfer. iRBD patients relative to healthy subjects exhibited a poorer performance during the nine-hole peg test and five-times-sit-to-stand test, and greater asymmetry of arm-swing amplitude and stride length variability during dual-task gait. Dual task significantly worsened the walking performance of iRBD patients more than healthy controls. iRBD patients exhibited nonmotor symptoms, and memory, abstract reasoning, and visuospatial deficits. iRBD patients exhibited decreased FC of pallidum and putamen within the basal ganglia network and occipital and temporal areas within the visuo-associative network, and a reduced volume of the supramarginal gyrus. Brain functional alterations correlated with gait changes. Subtle motor and nonmotor alterations were identified in iRBD patients, alongside brain structural and functional MRI changes. These findings may represent early signs of neurodegeneration and contribute to the development of predictive models for progression to parkinsonism. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Prolonged ventricular repolarization associated with mild cognitive impairment and white matter hyperintensities: a cross-sectional study

Prolonged ventricular repolarization has been associated with cardiovascular disease. We sought to investigate the association of prolonged ventricular repolarization with mild cognitive impairment (MCI) and the potential underlying neuropathological mechanisms in older adults. This cross-sectional study included 4328 dementia-free participants (age ≥ 65 years; 56.8% female) in the baseline examination of the Multidomain INterventions to delay dementia and Disability in rural China; of these, 989 undertook structural brain magnetic resonance imaging (MRI) scans. QT, QTc, JT, JTc, and QRS intervals were derived from 12-lead electrocardiograph. MCI, amnestic MCI (aMCI), and non-amnestic MCI (naMCI) were defined following the Petersen’s criteria. Volumes of gray matter (GM), white matter, cerebrospinal fluid, total white matter hyperintensities (WMH), periventricular WMH (PWMH), and deep WMH (DWMH) were automatically estimated. Data were analyzed using logistic and general linear regression models. Prolonged QT, QTc, JT, and JTc intervals were significantly associated with an increased likelihood of MCI and aMCI, but not naMCI (p < 0.05). In the MRI subsample, QT, QTc, JT, and JTc intervals were significantly associated with larger total WMH and PWMH volumes (p < 0.05), but not with DWMH volume. Statistical interactions were detected, such that prolonged QT and JT intervals were significantly associated with reduced GM volume only among participants with coronary heart disease or without APOE ε4 allele (p < 0.05). Prolonged ventricular repolarization is associated with MCI and cerebral microvascular lesions in a general population of older adults. This underlies the importance of cognitive assessments and brain MRI examination among older adults with prolonged QT interval.

The gut-brain axis in individuals with alcohol use disorder: Anexploratory study of associations among clinical symptoms, brain morphometry, and the gut microbiome.

Alcohol use disorder (AUD) is commonly associated with distressing psychological symptoms. Pathologic changes associated with AUD have been described in both the gut microbiome and brain, but the mechanisms underlying gut-brain signaling in individuals with AUD are unknown. This study examined associations among the gut microbiome, brain morphometry, and clinical symptoms in treatment-seeking individuals with AUD. We performed a secondary analysis of data collected during inpatient treatment for AUD in subjects who provided gut microbiome samples and had structural brain magnetic resonance imaging (MRI; n = 16). Shotgun metagenomics sequencing was performed, and the morphometry of brain regions of interest was calculated. Clinical symptom severity was quantified using validated instruments. Gut-brain modules (GBMs) used to infer neuroactive signaling potential from the gut microbiome were generated in addition to microbiome features (e.g., alpha diversity and bacterial taxa abundance). Bivariate correlations were performed between MRI and clinical features, microbiome and clinical features, and MRI and microbiome features. Amygdala volume was significantly associated with alpha diversity and the abundance of several bacteria including taxa classified to Blautia, Ruminococcus, Bacteroides, and Phocaeicola. There were moderate associations between amygdala volume and GBMs, including butyrate synthesis I, glutamate synthesis I, and GABA synthesis I & II, but these relationships were not significant after false discovery rate (FDR) correction. Other bacterial taxa with shared associations to MRI features and clinical symptoms included Escherichia coli and Prevotella copri. We identified gut microbiome features associated with MRI morphometry and AUD-associated symptom severity. Given the small sample size and bivariate associations performed, these results require confirmation in larger samples and controls to provide meaningful clinical inferences. Nevertheless, these results will inform targeted future research on the role of the gut microbiome in gut-brain communication and how signaling may be altered in patients with AUD.

Sheep (Ovis aries) training protocol for voluntary awake and unrestrained structural brain MRI acquisitions

Magnetic resonance imaging (MRI) is a non-invasive technique that requires the participant to be completely motionless. To date, MRI in awake and unrestrained animals has only been achieved with humans and dogs. For other species, alternative techniques such as anesthesia, restraint and/or sedation have been necessary. Anatomical and functional MRI studies with sheep have only been conducted under general anesthesia. This ensures the absence of movement and allows relatively long MRI experiments but it removes the non-invasive nature of the MRI technique (i.e., IV injections, intubation). Anesthesia can also be detrimental to health, disrupt neurovascular coupling, and does not permit the study of higher-level cognition. Here, we present a proof-of-concept that sheep can be trained to perform a series of tasks, enabling them to voluntarily participate in MRI sessions without anesthesia or restraint. We describe a step-by-step training protocol based on positive reinforcement (food and praise) that could be used as a basis for future neuroimaging research in sheep. This protocol details the two successive phases required for sheep to successfully achieve MRI acquisitions of their brain. By providing structural brain MRI images from six out of ten sheep, we demonstrate the feasibility of our training protocol. This innovative training protocol paves the way for the possibility of conducting animal welfare-friendly functional MRI studies with sheep to investigate ovine cognition.

Major brain injuries at term continue to influence DTI parameters in adolescents born very preterm: a 13-year follow-up study.

Major brain injuries in structural brain magnetic resonance imaging (MRI) at term affect concurrent diffusion tensor imaging (DTI) parameters in very preterm infants. White matter is known to gradually maturate along with increasing gestational age, which is characterized by increasing fractional anisotropy (FA) and decreasing mean diffusivity (MD). To study the difference between DTI parameters at term and 13 years in adolescents born very preterm with and without major pathologies in structural brain MRI at term. Adolescents born very preterm (gestational age <32 weeks and/or birth weight ≤1500 g) in 2004-2006 at Turku University Hospital, Finland were included. We evaluated FA and MD at term and 13 years in 18 regions of interest using the JHU-neonate-SS atlas to compare the differences in these parameters between adolescents with and without major injuries identified on MRI at term. A total of 24 adolescents underwent brain MRI including DTI both at term and 13 years. Adolescents with major brain injury pathologies (n = 6) in structural MRI at term had decreased FA in the left corpus callosum and right cingulate gyrus part, and increased MD in the left corpus callosum, right anterior limb of internal capsule, and right posterior limb of the internal capsule at 13 years, in comparison with adolescents without major brain injuries (n = 18) in structural MRI at term. Our findings suggest that major brain injuries identified on structural MRI at term affect brain maturation, with adverse effects in FA and MD still during adolescence.

Predicting 2-year neurodevelopmental outcomes in preterm infants using multimodal structural brain magnetic resonance imaging with local connectivity

The neurodevelopmental outcomes of preterm infants can be stratified based on the level of prematurity. We explored brain structural networks in extremely preterm (EP; < 28 weeks of gestation) and very-to-late (V-LP; ≥ 28 and < 37 weeks of gestation) preterm infants at term-equivalent age to predict 2-year neurodevelopmental outcomes. Using MRI and diffusion MRI on 62 EP and 131 V-LP infants, we built a multimodal feature set for volumetric and structural network analysis. We employed linear and nonlinear machine learning models to predict the Bayley Scales of Infant and Toddler Development, Third Edition (BSID-III) scores, assessing predictive accuracy and feature importance. Our findings revealed that models incorporating local connectivity features demonstrated high predictive performance for BSID-III subsets in preterm infants. Specifically, for cognitive scores in preterm (variance explained, 17%) and V-LP infants (variance explained, 17%), and for motor scores in EP infants (variance explained, 15%), models with local connectivity features outperformed others. Additionally, a model using only local connectivity features effectively predicted language scores in preterm infants (variance explained, 15%). This study underscores the value of multimodal feature sets, particularly local connectivity, in predicting neurodevelopmental outcomes, highlighting the utility of machine learning in understanding microstructural changes and their implications for early intervention.

Randomized controlled double-blind trial of methylprednisolone versus placebo in patients with post-COVID-19 syndrome and cognitive deficits: study protocol of the post-corona-virus immune treatment (PoCoVIT) trial

IntroductionPost-COVID-19 Syndrome (PCS) includes neurological manifestations, especially fatigue and cognitive deficits. Immune dysregulation, autoimmunity, endothelial dysfunction, viral persistence, and viral reactivation are discussed as potential pathophysiological mechanisms. The post-corona-virus immune treatment (PoCoVIT) trial is a phase 2a randomized, controlled, double-blind trial designed to evaluate the effect of methylprednisolone versus placebo on cognitive impairment in PCS. This trial is designed based on the hypothesised autoimmunological pathogenesis and positive aberrations, employing a series of off-label applications.MethodsRecruitment criteria include a diagnosis of PCS, a minimum age of 18 years and self-reported cognitive deficits at screening. A total of 418 participants will be randomly assigned to either verum or placebo intervention in the first phase of the trial. The trial will consist of a first trial phase intervention with methylprednisolone versus placebo for six weeks, followed by a six-week treatment interruption period. Subsequently, an open second phase will offer methylprednisolone to all participants for six weeks. Outpatient follow-up visits will take place two weeks after each trial medication cessation. The third and final follow-up, at week 52, will be conducted through a telephone interview. The primary outcome measures an intra-patient change of 15 or more points in the memory satisfaction subscale of the Multifactorial Memory Questionnaire (MMQ) from baseline to follow-up 1 (week 8). Key secondary outcomes include long-term intra-patient changes in memory satisfaction from baseline to follow-up 2 (week 20), changes in other MMQ subscales (follow-up 1 and 2), and changes in neuropsychological and cognitive scores, along with assessments through questionnaires focusing on quality of life, fatigue, and mood over the same periods. Exploratory outcomes involve molecular biomarkers variations in serum and cerebrospinal fluid, as well as structural and functional brain magnetic resonance imaging (MRI) parameters changes related to cognition.PerspectiveThis trial aims to contribute novel evidence for treating patients with PCS, with a primary focus on those manifesting cognitive deficits. By doing so, it may enhance comprehension of the underlying pathophysiological mechanisms, thereby facilitating biomarker research to advance our understanding and treatment of patients with PCS.

Multimodal integration of neuroimaging and genetic data for the diagnosis of mood disorders based on computer vision models

Mood disorders, particularly major depressive disorder (MDD) and bipolar disorder (BD), are often underdiagnosed, leading to substantial morbidity. Harnessing the potential of emerging methodologies, we propose a novel multimodal fusion approach that integrates patient-oriented brain structural magnetic resonance imaging (sMRI) scans with DNA whole-exome sequencing (WES) data. Multimodal data fusion aims to improve the detection of mood disorders by employing established deep-learning architectures for computer vision and machine-learning strategies. We analyzed brain imaging genetic data of 321 East Asian individuals, including 147 patients with MDD, 78 patients with BD, and 96 healthy controls. We developed and evaluated six fusion models by leveraging common computer vision models in image classification: Vision Transformer (ViT), Inception-V3, and ResNet50, in conjunction with advanced machine-learning techniques (XGBoost and LightGBM) known for high-dimensional data analysis. Model validation was performed using a 10-fold cross-validation. Our ViT ⊕ XGBoost fusion model with MRI scans, genomic Single Nucleotide polymorphism (SNP) data, and unweighted polygenic risk score (PRS) outperformed baseline models, achieving an incremental area under the curve (AUC) of 0.2162 (32.03% increase) and 0.0675 (+8.19%) and incremental accuracy of 0.1455 (+25.14%) and 0.0849 (+13.28%) compared to SNP-only and image-only baseline models, respectively. Our findings highlight the opportunity to refine mood disorder diagnostics by demonstrating the transformative potential of integrating diverse, yet complementary, data modalities and methodologies.

The effect of intrathecal recombinant arylsulfatase A therapy on structural brain magnetic resonance imaging in children with metachromatic leukodystrophy.

This study aimed to evaluate the effect of intrathecal (IT) recombinant human arylsulfatase A (rhASA) on magnetic resonance imaging (MRI)-assessed brain tissue changes in children with metachromatic leukodystrophy (MLD). In total, 510 MRI scans were collected from 12 intravenous (IV)rhASA-treated children with MLD, 24 IT rhASA-treated children with MLD, 32 children with untreated MLD, and 156 normally developing children. Linear mixed models were fitted to analyze the time courses of gray matter (GM) volume and fractional anisotropy (FA) in the posterior limb of the internal capsule. Time courses for demyelination load and FA in the centrum semiovale were visualized using locally estimated scatterplot smoothing regression curves. All assessed imaging parameters demonstrated structural evidence of neurological deterioration in children with MLD. GM volume was significantly lower at follow-up (median duration, 104 weeks) in IV rhASA-treated versus IT rhASA-treated children. GM volume decline over time was steeper in children receiving low-dose (10 or 30 mg) versus high-dose (100 mg) IT rhASA. Similar effects were observed for demyelination. FA in the posterior limb of the internal capsule showed a higher trend over time in IT rhASA-treated versus children with untreated MLD, but FA parameters were not different between children receiving the low dosesversus those receiving the high dose. GM volume in IT rhASA-treated children showed a strong positive correlation with 88-item Gross Motor Function Measure score over time. In some children with MLD, IT administration of high-dose rhASA may delay neurological deterioration (assessed using MRI), offering potential therapeutic benefit.

Development of Efficient Brain Age Estimation Method Based on Regional Brain Volume From Structural Magnetic Resonance Imaging.

We aimed to create an efficient and valid predicting model which can estimate individuals' brain age by quantifying their regional brain volumes. A total of 2,560 structural brain magnetic resonance imaging (MRI) scans, along with demographic and clinical data, were obtained. Pretrained deep-learning models were employed to automatically segment the MRI data, which enabled fast calculation of regional brain volumes. Brain age gaps for each subject were estimated using volumetric values from predefined 12 regions of interest (ROIs): bilateral frontal, parietal, occipital, and temporal lobes, as well as bilateral hippocampus and lateral ventricles. A larger weight was given to the ROIs having a larger mean volumetric difference between the cognitively unimpaired (CU) and cognitively impaired group including mild cognitive impairment (MCI), and dementia groups. The brain age was predicted by adding or subtracting the brain age gap to the chronological age according to the presence or absence of the atrophy region. The study showed significant differences in brain age gaps among CU, MCI, and dementia groups. Furthermore, the brain age gaps exhibited significant correlations with education level and measures of cognitive function, including the clinical dementia rating sum-of-boxes and the Korean version of the Mini-Mental State Examination. The brain age that we developed enabled fast and efficient brain age calculations, and it also reflected individual's cognitive function and cognitive reserve. Thus, our study suggested that the brain age might be an important marker of brain health that can be used effectively in real clinical settings.

Systematic reduction of gray matter volume in anorexia nervosa, but relative enlargement with clinical symptoms in the prefrontal and posterior insular cortices: a multicenter neuroimaging study

Although brain morphological abnormalities have been reported in anorexia nervosa (AN), the reliability and reproducibility of previous studies were limited due to insufficient sample sizes, which prevented exploratory analysis of the whole brain as opposed to regions of interest (ROIs). Objective was to identify brain morphological abnormalities in AN and the association with severity of AN by brain structural magnetic resonance imaging (MRI) in a multicenter study, and to conduct exploratory analysis of the whole brain. Here, we conducted a cross-sectional multicenter study using T1-weighted imaging (T1WI) data collected between May 2014 and February 2019 in Japan. We analyzed MRI data from 103 female AN patients (58 anorexia nervosa restricting type [ANR] and 45 anorexia nervosa binge-purging type [ANBP]) and 102 age-matched female healthy controls (HC). MRI data from five centers were preprocessed using the latest harmonization method to correct for intercenter differences. Gray matter volume (GMV) was calculated from T1WI data of all participants. Of the 205 participants, we obtained severity of eating disorder symptom scores from 179 participants, including 87 in the AN group (51 ANR, 36 ANBP) and 92 HC using the Eating Disorder Examination Questionnaire (EDE-Q) 6.0. GMV reduction were observed in the AN brain, including the bilateral cerebellum, middle and posterior cingulate gyrus, supplementary motor cortex, precentral gyrus medial segment, and thalamus. In addition, the orbitofrontal cortex (OFC), ventromedial prefrontal cortex (vmPFC), rostral anterior cingulate cortex (ACC), and posterior insula volumes showed positive correlations with severity of symptoms. This multicenter study was conducted with a large sample size to identify brain morphological abnormalities in AN. The findings provide a better understanding of the pathogenesis of AN and have potential for the development of brain imaging biomarkers of AN. Trial Registration: UMIN000017456. https://center6.umin.ac.jp/cgi-open-bin/icdr/ctr_view.cgi?recptno=R000019303.