Whole-brain Volume Research Articles

Mapping vascular network architecture in primate brain using ferumoxytol-weighted laminar MRI.

Mapping the vascular organization of the brain is of great importance across various domains of basic neuroimaging research, diagnostic radiology, and neurology. However, the intricate task of precisely mapping vasculature across brain regions and cortical layers presents formidable challenges, resulting in a limited understanding of neurometabolic factors influencing the brains microvasculature. Addressing this gap, our study investigates whole-brain vascular volume using ferumoxytol-weighted laminar-resolution multi-echo gradient-echo imaging in macaque monkeys. We validate the results with published data for vascular densities and compare them with cytoarchitecture, neuron and synaptic densities. The ferumoxytol-induced change in transverse relaxation rate (ΔR2*), an indirect proxy measure of cerebral blood volume (CBV), was mapped onto twelve equivolumetric laminar cortical surfaces. Our findings reveal that CBV varies 3-fold across the brain, with the highest vascular volume observed in the inferior colliculus and lowest in the corpus callosum. In the cerebral cortex, CBV is notably high in early primary sensory areas and low in association areas responsible for higher cognitive functions. Classification of CBV into distinct groups unveils extensive replication of translaminar vascular network motifs, suggesting distinct computational energy supply requirements in areas with varying cytoarchitecture types. Regionally, baseline R2* and CBV exhibit positive correlations with neuron density and negative correlations with receptor densities. Adjusting image resolution based on the critical sampling frequency of penetrating cortical vessels, allows us to delineate approximately 30% of the arterial-venous vessels. Collectively, these results mark significant methodological and conceptual advancements, contributing to the refinement of cerebrovascular MRI. Furthermore, our study establishes a linkage between neurometabolic factors and the vascular network architecture in the primate brain.

Sex differences in association between dietary sodium intake and white matter hyperintensity volume

Abstract Background There is limited evidence on the relationship between dietary sodium intake (dNa) and brain health, and very little on sex differences in associations. Purpose To study the relationship between dNa and imaging measures of brain health in men and women from the INSIGHT 46 substudy of the MRC National Survey of Health and Development (British 1946 birth cohort). Methods Participants had measurements (dNa using 5-day food diary, anthropometrics, blood pressure (BP) body mass index (BMI)) at 60-64years. Whole-brain and hippocampal volumes, white matter hyperintensity volume (WMHV) and florbetapir amyloid-β positivity were measured using MRI-PET imaging at 69-71years. Associations (β (95% confidence intervals)) were estimated separately in men and women using generalized linear models with robust standard errors adjusted for potential confounders (age, diet quality, energy intake, socioeconomic status) or potential mediators (BMI, BP). Results Participants’ characteristics are shown in Table 1. In women but not men dNa was positively associated with higher WMHV (β[women]=32(1, 72) %/g; p=0.043; β[men]=-10(-27, 11)%/g; p=0.342); this relationship in women was independent of BMI (β = 32(1, 72)%/g; p = 0.043) or systolic BP (β = 31(1, 70)%/g; p=0.041). dNa was not associated with total brain volume, hippocampal volume or amyloid-β positivity in either sex. Conclusions Elevated sodium consumption in the diet is associated with cerebral small vessel disease in older age women but not men. This association was independent of BMI or BP.Table 1

Associations Between High-Density Lipoprotein Cholesterol Efflux and Brain Grey Matter Volume.

Objective: High-density lipoprotein cholesterol efflux function may prevent brain amyloid beta deposition and neurodegeneration. However, the relevance of this finding has not been established in the diverse middle-aged population. Methods: We examined 1826 adults (47% Black adults) who participated in the Dallas Heart Study to determine associations between high-density lipoprotein (HDL) measures and brain structure and function. White matter hyperintensities (WMH) and whole-brain grey matter volume (GMV) were measured using brain MRI, and the Montreal Cognitive Assessment (MoCA) was used to measure neurocognitive function. HDL cholesterol efflux capacity (HDL-CEC) was assessed using fluorescence-labeled cholesterol efflux from J774 macrophages, and HDL particle size measures were assessed using nuclear magnetic resonance (NMR) spectroscopy (LipoScience). Multivariable linear regressions were performed to elucidate associations between HDL-CEC and brain and cognitive phenotypes after adjustment for traditional risk factors such as age, smoking status, time spent in daily physical activity, and education level. Results: Higher HDL-CEC and small HDL particle (HDL-P) concentration were positively associated with higher GMV normalized to total cranial volume (TCV) (GMV/TCV) after adjustment for relevant risk factors (β = 0.078 [95% CI: 0.029, 0.126], p = 0.002, and β = 0.063 [95% CI: 0.014, 0.111], p = 0.012, respectively). Conversely, there were no associations between HDL measures and WMH or MoCA (all p > 0.05). Associations of HDL-CEC and small HDL-P with GMV/TCV were not modified by ApoE-ε4 status or race/ethnicity. Interpretation: Higher HDL cholesterol efflux and higher plasma concentration of small HDL-P were associated with higher GMV/TCV. Additional studies are needed to explore the potential neuroprotective functions of HDL.

Biomarker pathway heterogeneity of amyloid-positive individuals.

In amyloid-positive individuals, disease-related biomarker heterogeneity is understudied. We used Subtype and Stage Inference (SuStaIn) to identify data-driven subtypes among cerebrospinal fluid (CSF) amyloid beta (1-42)-positive individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNIGO/2 [n=376]). Variables included: CSF phosphorylated tau (p-tau181), hippocampal and whole-brain volume, logical memory (LM), composite Trail Making Test score, and white matter hyperintensity (WMH) volumes. CSF amyloid-negative, apolipoprotein E ε4 non-carrier cognitively unimpaired controls (n=86) were used to calculate z scores. One subtype (n=145) had early LM changes, with later p-tau and WMH changes. A second subtype (n=88) had early WMH changes, were older, and more hypertensive. A third subtype (n=100) had early p-tau changes, and reflected typical Alzheimer's disease. Some amyloid positive (n=43) individuals were similar to the amyloid-negative group. This work identified heterogeneity in individuals who are conventionally considered homogeneous, which is likely driven by co-pathologies including cerebrovascular disease. Data-driven modeling identified marker heterogeneity in amyloid-positive individuals. Heterogeneity reflected Alzheimer's disease-like, vascular-like, and mixed pathology presentations. Some amyloid-positive individuals were more similar to amyloid-negative controls. Vascular pathology plays a key role in understanding heterogeneity in those on the amyloid pathway.

Motion Artifact Detection for T1-Weighted Brain MR Images Using Convolutional Neural Networks.

Quality assessment (QA) of magnetic resonance imaging (MRI) encompasses several factors such as noise, contrast, homogeneity, and imaging artifacts. Quality evaluation is often not standardized and relies on the expertise, and vigilance of the personnel, posing limitations especially with large datasets. Machine learning based on convolutional neural networks (CNNs) is a promising approach to address these challenges by performing automated inspection of MR images. In this study, a CNN for the detection of random head motion artifacts (RHM) in T1-weighted MRI as one aspect of image quality is proposed. A two-step approach aimed to first identify images exhibiting pronounced motion artifacts, and second to evaluate the feasibility of a more detailed three-class classification. The utilized dataset consisted of 420 T1-weighted whole-brain image volumes with isotropic resolution. Human experts assigned each volume to one of three classes of artifact prominence. Results demonstrate an accuracy of 95% for the identification of images with pronounced artifact load. The addition of an intermediate class retained an accuracy of 76%. The findings highlight the potential of CNN-based approaches to increase the efficiency of post-hoc QAs in large datasets by flagging images with potentially relevant artifact loads for closer inspection.

Longitudinal mapping of cortical change during early adolescence associated with prenatal tobacco and/or alcohol exposure in the Adolescent Brain Cognitive Development Study.

The effects of prenatal alcohol (PAE) and tobacco exposure (PTE) on adolescent neuroanatomical development are typically evaluated cross-sectionally. It is unclear if observed effects persist throughout life or reflect different developmental trajectories. To determine how PAE and PTE are associated with cortical structure and development across two timepoints in early adolescence. Observational, longitudinal analyses of data within the Adolescent Brain Cognitive Development Study. 21 study sites in the United States. 5,417 youth participants, aged ~9-12 years old. PAE and PTE based on caregiver (self) reports of alcohol/tobacco use during pregnancy, before and after pregnancy recognition. Cortical thickness (mm) and cortical surface area (mm2) measured approximately 2 years apart in early adolescence, across 68 bilateral cortical regions. At baseline data collection, youth participants were ~9.9 years old (SD=0.6). At the second neuroimaging appointment, youth participants were ~11.9 years old (SD=0.6). When modelling cortical thickness, we controlled for individuals' whole-brain volume; when modelling cortical surface area, individuals' total surface area. Cortical thickness generally declined with age. Cortical surface area either expanded or contracted with age, depending on region. PAE had minimal effects on cortical structure (main effects) and development (PAE×Age interactions). PTE had robust effects on cortical thickness and was associated with faster rates of cortical thinning in several regions within the frontal lobe. Post hoc analyses on (1) the effects of PTE for those who continued tobacco use after pregnancy recognition and (2) the effects of PTE in those who did not also use alcohol revealed weaker effects. PTE had robust effects on neuroanatomical structure and longitudinal development, particularly cortical thickness. Analyzing developmental cortical trajectories informs how PTE and/or PAE not only affects cortical structure but how it develops long after those prenatal exposures occurred. Future analyses involving cotinine biomarkers of PTE would enhance the temporal resolution of the ABCD Study®'s PTE-related queries of tobacco use before and after learning of the pregnancy.

Association of cortical morphology, white matter hyperintensity, and glymphatic function in frontotemporal dementia variants.

Frontotemporal dementia (FTD) can be phenotypically divided into behavioral variant FTD (bvFTD), nonfluent variant primary progressive aphasia (nfvPPA), and semantic variant PPA (svPPA). However, the neural underpinnings of this phenotypic heterogeneity remain elusive. Cortical morphology, white matter hyperintensities (WMH), diffusion tensor image analysis along the perivascular space (DTI-ALPS), and their interrelationships were assessed in subtypes of FTD. Neuroimaging-transcriptional analyses on the regional cortical morphological deviances among subtypes were also performed. Changes in cortical thickness, surface area, gyrification, WMH, and DTI-ALPS were subtype-specific in FTD. The three morphologic indices are related to whole-brain WMH volume and cognitive performance, while cortical thickness is related to DTI-ALPS. Neuroimaging-transcriptional analyses identified key biological pathways linked to the formation and/or spread of TDP-43/tau pathologies. We found subtype-specific changes in cortical morphology, WMH, and glymphatic function in FTD. Our findings have the potential to contribute to the development of personalized predictions and treatment strategies for this disorder. Cortical morphologic changes, white matter hyperintensities (WMH), and glymphatic dysfunction are subtype-specific. Cortical morphologic changes, WMH, and glymphatic dysfunction are inter-correlated. Cortical morphologic changes and WMH burden contribute to cognitive impairments.

AB038. Establishing a reliable semi-automated segmentation method for assessing chemoradiotherapy effects on the non-tumoral brain.

Current voxel-based morphometry (VBM) studies of chemoradiotherapy effects on healthy tissues of the glioblastoma multiforme (GBM) brain face a challenge with neuroanatomical distortions (tumor, tumor edema, and resection cavities) and limited comparisons can be drawn across studies due to lack of a universally accepted software package. Our aim is to compare current semi-automated segmentation methods and optimize them for reliability in investigating the effects of chemoradiotherapy on GBM patients. A publicly available dataset was used based on predefined inclusion and exclusion criteria. VBM pipelines CAT12 and FSL were tested and optimized to reduce the impact of neuroanatomical distortions. T1-weighted images were screened, and post-processed with FSL and CAT12. Gray matter (GM) and white matter (WM), and cerebrospinal fluid (CSF) volumes of whole brain, tumour-containing and non-tumor containing hemispheres, pre- and post-chemoradiotherapy were calculated and analyzed with Wilcoxon signed-rank tests. Agreement and consistency between FSL and CAT12 were assessed using Bland-Altman plots and intraclass correlation coefficients (ICCs). Post-chemoradiotherapy GM volumes were significantly reduced in whole brain with a compensatory significant increase in CSF volumes, while WM volumes had no significant changes. Similar trends were noted in tumor-containing and non-tumor-containing hemispheres. Bland-Altman plots showed good agreement between FSL and CAT12 processed GM and WM volumes of whole brain, tumor-containing, and non-tumor-containing hemispheres. ICC ≥0.70 was observed in GM [0.70 (0.53-0.82)] and WM [0.75 (0.60-0.85)] volumes of non-tumor-containing hemisphere, and WM [0.71 (0.55-0.83)] volumes of whole brain. GM volumes of tumor-containing hemisphere had good agreement but surprisingly, poor consistency [0.50 (0.25-0.68)]. CSF volumes in non-tumor-containing hemisphere had better agreement and consistency [0.55 (0.32-0.71)] than whole brain [0.49 (0.25-0.67)] and tumor-containing hemisphere CSF [0.36 (0.10-0.58)] volumes. Visual inspection revealed both CAT12 and FSL mis-segmented in the presence of neuroanatomical distortion although CAT12 was more susceptible in the presence of a hematoma. VBM studies of chemoradiotherapy effects on the brain post-tumor resection remain challenging due to neuroanatomical distortions. A reliable alternative is to use non-tumor-containing hemispheres with no anatomical distortion. Should tumor-containing brains be used, FSL is a more suitable choice, especially in the presence of hematoma distortion.

Investigating grey matter volumetric trajectories through the lifespan at the individual level

Adolescents exhibit remarkable heterogeneity in the structural architecture of brain development. However, due to limited large-scale longitudinal neuroimaging studies, existing research has largely focused on population averages, and the neurobiological basis underlying individual heterogeneity remains poorly understood. Here we identify, using the IMAGEN adolescent cohort followed up over 9 years (14–23 y), three groups of adolescents characterized by distinct developmental patterns of whole-brain gray matter volume (GMV). Group 1 show continuously decreasing GMV associated with higher neurocognitive performances than the other two groups during adolescence. Group 2 exhibit a slower rate of GMV decrease and lower neurocognitive performances compared with Group 1, which was associated with epigenetic differences and greater environmental burden. Group 3 show increasing GMV and lower baseline neurocognitive performances due to a genetic variation. Using the UK Biobank, we show these differences may be attenuated in mid-to-late adulthood. Our study reveals clusters of adolescent neurodevelopment based on GMV and the potential long-term impact.

Longitudinal network-based brain grey matter MRI measures are clinically relevant and sensitive to treatment effects in multiple sclerosis.

In multiple sclerosis clinical trials, MRI outcome measures are typically extracted at a whole-brain level, but pathology is not homogeneous across the brain and so whole-brain measures may overlook regional treatment effects. Data-driven methods, such as independent component analysis, have shown promise in identifying regional disease effects but can only be computed at a group level and cannot be applied prospectively. The aim of this work was to develop a technique to extract longitudinal independent component analysis network-based measures of co-varying grey matter volumes, derived from T1-weighted volumetric MRI, in individual study participants, and assess their association with disability progression and treatment effects in clinical trials. We used longitudinal MRI and clinical data from 5089 participants (22 045 visits) with multiple sclerosis from eight clinical trials. We included people with relapsing-remitting, primary and secondary progressive multiple sclerosis. We used data from five negative clinical trials (2764 participants, 13 222 visits) to extract the independent component analysis-based measures. We then trained and cross-validated a least absolute shrinkage and selection operator regression model (which can be applied prospectively to previously unseen data) to predict the independent component analysis measures from the same regional MRI volume measures and applied it to data from three positive clinical trials (2325 participants, 8823 visits). We used nested mixed-effect models to determine how networks differ across multiple sclerosis phenotypes are associated with disability progression and to test sensitivity to treatment effects. We found 17 consistent patterns of co-varying regional volumes. In the training cohort, volume loss was faster in four networks in people with secondary progressive compared with relapsing-remitting multiple sclerosis and three networks with primary progressive multiple sclerosis. Volume changes were faster in secondary compared with primary progressive multiple sclerosis in four networks. In the combined positive trials cohort, eight independent component analysis networks and whole-brain grey matter volume measures showed treatment effects, and the magnitude of treatment-placebo differences in the network-based measures was consistently greater than with whole-brain grey matter volume measures. Longitudinal network-based analysis of grey matter volume changes is feasible using clinical trial data, showing differences cross-sectionally and longitudinally between multiple sclerosis phenotypes, associated with disability progression, and treatment effects. Future work is required to understand the pathological mechanisms underlying these regional changes.

Clinically feasible automated MRI volumetry of the brain as a prognostic marker in subjective and mild cognitive impairment.

The number of patients suffering from cognitive decline and dementia increases, and new possible treatments are being developed. Thus, the need for time efficient and cost-effective methods to facilitate an early diagnosis and prediction of future cognitive decline in patients with early cognitive symptoms is becoming increasingly important. The aim of this study was to evaluate whether an MRI based software, NeuroQuant® (NQ), producing volumetry of the hippocampus and whole brain volume (WBV) could predict: (1) conversion from subjective cognitive decline (SCD) at baseline to mild cognitive impairment (MCI) or dementia at follow-up, and from MCI at baseline to dementia at follow-up and (2) progression of cognitive and functional decline defined as an annual increase in the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) score. MRI was performed in 156 patients with SCD or MCI from the memory clinic at Oslo University Hospital (OUH) that had been assessed with NQ and had a clinical follow-up examination. Logistic and linear regression analyses were performed with hippocampus volume and WBV as independent variables, and conversion or progression as dependent variables, adjusting for demographic and other relevant covariates including Mini-Mental State Examination-Norwegian Revised Version score (MMSE-NR) and Apolipoprotein E ɛ4 (APOE ɛ4) carrier status. Hippocampus volume, but not WBV, was associated with conversion to MCI or dementia, but neither were associated with conversion when adjusting for MMSE-NR. Both hippocampus volume and WBV were associated with progression as measured by the annual change in CDR-SB score in both unadjusted and adjusted analyses. The results indicate that automated regional MRI volumetry of the hippocampus and WBV can be useful in predicting further cognitive decline in patients with early cognitive symptoms.

Reproductive hormones in relation to white matter hyperintensity volumes among midlife women.

Although reproductive hormones are implicated in cerebral small vessel disease in women, few studies consider measured hormones in relation to white matter hyperintensity volume (WMHV), a key indicator of cerebral small vessel disease. Even fewer studies consider estrone (E1), the primary postmenopausal estrogen, or follicle-stimulating hormone (FSH), an indicator of ovarian age. We tested associations of estradiol (E2), E1, and FSH to WMHV among women. Two hundred twenty-two women (mean age=59) underwent hormone assays (E1, E2, FSH) and 3T brain magnetic resonance imaging. Associations of hormones to WMHV were tested with linear regression. Higher E2 (B[standard error (SE)]=-0.17[0.06], P=0.008) and E1 (B[SE]=-0.26[0.10], P=0.007) were associated with lower whole-brain WMHV, and higher FSH (B[SE]=0.26[0.07], P=0.0005) with greater WMHV (covariates age, race, education). When additionally controlling for cardiovascular disease risk factors, associations of E1 and FSH to WMHV remained. Reproductive hormones, particularly E1 and FSH, are important to women's cerebrovascular health. Despite widespread belief that sex hormones are important to women's brain health, little work has considered how these hormones in women relate to white matter hyperintensities (WMH), a major indicator of cerebral small vessel disease. We considered relations of estradiol (E2), estrone (E1), and follicle-stimulating hormone (FSH) to WMH in midlife women. Higher E2 and E1 were associated with lower whole-brain WMH volume (WMHV), and higher FSH with higher whole-brain WMHV. Associations of E1 and FSH, but not E2, to WMHV persisted with adjustment for cardiovascular disease risk factors. Findings underscore the importance of E2 and FSH to women's cerebrovascular health.

Interictal Electroencephalography and Functional Magnetic Resonance Imaging Reveals Involvement of Mesial Anterior Frontal Structures in Patients With Hyperkinetic Semiology Type I.

This work investigates the presence of common anatomic regions associated with interictal activity in patients with hyperkinetic seizures type I by means of concurrent electroencephalography and functional magnetic resonance imaging. Six patients with hyperkinetic seizures type I were evaluated with video-EEG and electroencephalography and functional magnetic resonance imaging in the context of their presurgical evaluation. Statistical Parametric Mapping was used to perform a correlation study between the occurrence of interictal spikes on EEG and suprathreshold blood oxygen level-dependent changes in the whole-brain volume. In all patients, Statistical Parametric Mapping revealed suprathreshold blood oxygen level-dependent clusters in the mesial anterior frontal areas, including the rostral mesial superior frontal gyrus and the anterior cingulate, associated with the patients' typical interictal activity. The electroencephalography and functional magnetic resonance imaging findings contribute to our understanding of hyperkinetic seizures type I semiology generation and can inform stereo-EEG targeting for surgical planning in refractory cases.

Lower arterial cerebral blood flow is associated with worse neuroinflammation and immunomodulation composite proteomic scores

BackgroundBrain hypoperfusion is linked with worse physical, cognitive and MRI outcomes in multiple sclerosis (MS). Understanding the proteomic signatures related to hypoperfusion could provide insights into the pathophysiological mechanism. Methods140 people with MS (pwMS; 86 clinically isolated syndrome (CIS)/relapsing-remitting (RRMS) and 54 progressive (PMS)) were included. Cerebral arterial blood flow (CABF) was determined using ultrasound Doppler measurement as the sum of blood flow in the bilateral common carotid arteries and vertebral arteries. Proteomic analysis was performed using the Multiple Sclerosis Disease Activity (MSDA) test assay panel performed on the Olink™ platform. The MSDA test measures the concentrations of 18 proteins that are age and sex-adjusted. It utilizes a stacked classifier logistic regression model to determine 4 disease pathway scores (immunomodulation, neuroinflammation, myelin biology, and neuroaxonal integrity) as well as an overall disease activity score (1 to 10). MRI measures of T2 lesion volume (LV) and whole brain volume (WBV) were derived. ResultsThe pwMS were on average 54 years old and had an average CABF of 951 mL/min. There were no differences in CABF between CIS/RRMS vs. PMS groups. Lower CABF levels were correlated with the overall disease activity score (r = -0.26, p = 0.003) and with the neuroinflammation (r = -0.29, p = 0.001), immunomodulation (r = -0.26, p = 0.003) and neuroaxonal integrity (r = -0.23, p = 0.007) pathway scores. After age and body mass index (BMI)-adjustment, lower CABF remained associated with the neuroinflammatory (r = -0.23, p = 0.011) and immunomodulation (r = -0.20, p = 0.024) pathway scores. The relationship between CABF and the neuroinflammation pathway score remained significant after adjusting for T2-LV and WBV (p = 0.038). Individual analyses identified neurofilament light chain, CCL-20 and TNFSF13B as contributors. When compared to the highest quartile (>1133.5 mL/min), the pwMS in the lowest CABF quartile (<764 mL/min) had greater overall disease activity score (p = 0.003), neuroinflammation (p = 0.001), immunomodulation (p = 0.004) and neuroaxonal integrity pathway scores (p = 0.007). ConclusionLower cerebral arterial perfusion in MS is associated with changes in neuroinflammatory/immunomodulation pathways and their respective proteomic biomarkers. These findings may suggest a relationship between the hypoperfusion and pro-inflammatory MS changes rather than being merely an epiphenomenon subsequent to lower energy demands.

Medical image foundation models in assisting diagnosis of brain tumors: a pilot study.

To build self-supervised foundation models for multicontrast MRI of the whole brain and evaluate their efficacy in assisting diagnosis of brain tumors. In this retrospective study, foundation models were developed using 57,621 enhanced head MRI scans through self-supervised learning with a pretext task of cross-contrast context restoration with two different content dropout schemes. Downstream classifiers were constructed based on the pretrained foundation models and fine-tuned for brain tumor detection, discrimination, and molecular status prediction. Metrics including accuracy, sensitivity, specificity, and area under the ROC curve (AUC) were used to evaluate the performance. Convolutional neural networks trained exclusively on downstream task data were employed for comparative analysis. The pretrained foundation models demonstrated their ability to extract effective representations from multicontrast whole-brain volumes. The best classifiers, endowed with pretrained weights, showed remarkable performance with accuracies of 94.9, 92.3, and 80.4%, and corresponding AUC values of 0.981, 0.972, and 0.852 on independent test datasets in brain tumor detection, discrimination, and molecular status prediction, respectively. The classifiers with pretrained weights outperformed the convolutional classifiers trained from scratch by approximately 10% in terms of accuracy and AUC across all tasks. The saliency regions in the correctly predicted cases are mainly clustered around the tumors. Classifiers derived from the two dropout schemes differed significantly only in the detection of brain tumors. Foundation models obtained from self-supervised learning have demonstrated encouraging potential for scalability and interpretability in downstream brain tumor-related tasks and hold promise for extension to neurological diseases with diffusely distributed lesions. The application of our proposed method to the prediction of key molecular status in gliomas is expected to improve treatment planning and patient outcomes. Additionally, the foundation model we developed could serve as a cornerstone for advancing AI applications in the diagnosis of brain-related diseases.

Evaluating the Effect of Alzheimer's Disease-Related Biomarker Change in Corticobasal Syndrome and Progressive Supranuclear Palsy.

To evaluate the effect of Alzheimer's disease (AD) -related biomarker change on clinical features, brain atrophy and functional connectivity of patients with corticobasal syndrome (CBS) and progressive supranuclear palsy (PSP). Data from patients with a clinical diagnosis of CBS, PSP, and AD and healthy controls were obtained from the 4-R-Tauopathy Neuroimaging Initiative 1 and 2, the Alzheimer's Disease Neuroimaging Initiative, and a local cohort from the Toronto Western Hospital. Patients with CBS and PSP were divided into AD-positive (CBS/PSP-AD) and AD-negative (CBS/PSP-noAD) groups based on fluid biomarkers and amyloid PET scans. Cognitive, motor, and depression scores; AD fluid biomarkers (cerebrospinal p-tau, t-tau, and amyloid-beta, and plasma ptau-217); and neuroimaging data (amyloid PET, MRI and fMRI) were collected. Clinical features, whole-brain gray matter volume and functional networks connectivity were compared across groups. Data were analyzed from 87 CBS/PSP-noAD and 23 CBS/PSP-AD, 18 AD, and 30 healthy controls. CBS/PSP-noAD showed worse performance in comparison to CBS/PSP-AD in the PSPRS [mean(SD): 34.8(15.8) vs 23.3(11.6)] and the UPDRS scores [mean(SD): 34.2(17.0) vs 21.8(13.3)]. CBS/PSP-AD demonstrated atrophy in AD signature areas and brainstem, while CBS/PSP-noAD patients displayed atrophy in frontal and temporal areas, globus pallidus, and brainstem compared to healthy controls. The default mode network showed greatest disconnection in CBS/PSP-AD compared with CBS/PSP-no AD and controls. The thalamic network connectivity was most affected in CBS/PSP-noAD. AD biomarker positivity may modulate the clinical presentation of CBS/PSP, with evidence of distinctive structural and functional brain changes associated with the AD pathology/co-pathology. ANN NEUROL 2024;96:99-109.

101 Glymphatic System Impairment Associated With Neurocognitive Dysfunction and Alzheimers Biomarkers in Moyamoya Disease

INTRODUCTION: Glymphatic system alterations have been proved to be associated with cognitive dysfunction in Alzheimer’s Disease (AD). The glymphatic pathway has not been elucidated in moyamoya disease (MMD), which was recognized as a chronic hypoperfusion model for AD. METHODS: We prospectively recruited 30 MMD patients and 30 matched healthy controls (HC) from October 2022 to March 2023. Participants underwent neurocognition evaluation, and multimodal magnetic resonance imaging (MRI). AD-related serum biomarkers, as well as correlations among these variables were examined. The glymphatic function was assessed by diffusion tensor image analysis along perivascular space (DTI-ALPS). Whole-brain (white matter and grey matter) volumes were calculated by using 3D T1-weighted MRI. Microstructural changes of white matter (intracellular volume fraction, Vic; orientation dispersion index, OD) were evaluated by neurite orientation dispersion and density imaging (NODDI). RESULTS: Serum Alzheimer’s biomarkers (ApoE, Aβ40, Aβ42, and tau) were significantly elevated and associated with neurocognitive dysfunction in MMD. Lower periventricular ALPS-index was identified in patients with MMD (P &lt; 0.001). The decreased ALPS-index correlated with declined neurocognitive performance of intelligence quotient, attention, and memory, increased levels of serum ApoE, Aβ40, Aβ42, as well as higher periventricular white matter volume and lower periventricular grey matter volume (P &lt; 0.001). Moreover, MMD patients had significantly lower Vic in the white matter and a lower OD in the cortex than HC. CONCLUSIONS: We firstly demonstrated the impaired glymphatic system as assessed by lower ALPS-index in patients with MMD. Glymphatic impairment was associated with AD-related biomarkers and cognitive dysfunction in MMD. These findings suggested that glymphatic disorder may interact with MMD-related pathophysiological processes.

Biomarkers of preschool children with autism spectrum disorder: quantitative analysis of whole-brain tissue component volumes, intelligence scores, ADOS-CSS, and ages of first-word production and walking onset.

Preschooling is a critical time for intervention in children with autism spectrum disorder (ASD); thus, we analyzed brain tissue component volumes (BTCVs) and clinical indicators in preschool children with ASD to identify new biomarkers for early screening. Eighty preschool children (3-6 years) with ASD were retrospectively included. The whole-brain myelin content (MyC), white matter (WM), gray matter (GM), cerebrospinal fluid (CSF), and non-WM/GM/MyC/CSF brain component volumes were obtained using synthetic magnetic resonance imaging (SyMRI). Clinical data, such as intelligence scores, autism diagnostic observation schedule-calibrated severity scores, age at first production of single words (AFSW), age at first production of phrases (AFP), and age at walking onset (AWO), were also collected. The correlation between the BTCV and clinical data was evaluated, and the effect of BTCVs on clinical data was assessed by a regression model. WM and GM volumes were positively correlated with intelligence scores (both P < 0.001), but WM and GM did not affect intelligence scores (P = 0.116, P = 0.290). AWO was positively correlated with AFSW and AFP (both P < 0.001). The multivariate linear regression analysis revealed that MyC, AFSW, AFP, and AWO were significantly different (P = 0.005, P < 0.001, P < 0.001). This study revealed positive correlations between WM and GM volumes and intelligence scores. Whole-brain MyC affected AFSW, AFP, and AWO in preschool children with ASD. Noninvasive quantification of BTCVs via SyMRI revealed a new visualizable and quantifiable biomarker (abnormal MyC) for early ASD screening in preschool children.

Structural MRI measures are associated with fatigue severity and persistence in a large, real-world cohort of people with multiple sclerosis

Background: Results of research on radiological hallmarks of multiple sclerosis (MS) fatigue have been conflicting. Objective: To investigate the associations of lesion and brain compartment volumes with fatigue severity and persistence in people with multiple sclerosis (PwMS). Methods: The Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS PATHS) network collects standardized data during routine care of PwMS from 10 healthcare institutions. Magnetic resonance imaging (MRI) predictors included baseline brain parenchymal (BPF) and gray matter fractions (GMF) and T2 lesion volume (T2LV). The Quality of Life in Neurological Disorders (Neuro-QOL) fatigue subscore was analyzed linearly and categorically using T-score cutpoints, with a period of elevated symptoms defined as T-score ⩾ mean + 0.5 SD over follow-up. Results: At baseline, of 4012 participants (average age: 45.6 ± 11.8 years; 73% female; 31% progressive MS), 2058 (51%) had no fatigue, 629 (16%) had mild fatigue, and 1325 (33%) had moderate-to-severe fatigue. One SD greater baseline BPF and GMF were associated with 0.83 (p < 0.001) and 0.38 (p = 0.02) lower values in the baseline Neuro-QOL fatigue T-score. A 1 SD lower log of total T2LV was associated with a 0.49 (p < 0.001) lower baseline fatigue T-score. Higher BPF and lower T2LV at baseline were associated with lower odds of subsequent periods of elevated fatigue. Conclusion: Baseline lesion burden and lower generalized whole-brain volumes were associated with MS fatigue in cross-sectional and longitudinal analyses in a large, real-world cohort of PwMS.

Brain volume loss in Japanese patients with multiple sclerosis is present in the early to middle stage of the disease

BackgroundTo determine which disease-modifying therapies should be used in patients with multiple sclerosis (MS), identifying patients at high and low risk for brain volume loss (BVL) is important. Although the BVL rate in MS is nearly constant from early to late disease onset, regardless of the disease stage, individual differences have been noted. Moreover, as disease duration increases, the risk of chronic progression increases, and brain atrophy becomes more noticeable. Therefore, measuring prognosis using a classification that considers BVL rate and disease duration is appropriate. We aimed to investigate the BVL in Japanese patients with MS. MethodsHerein, with an observational period of approximately 3.5 years, 82 Japanese patients with MS were included. The volumes and annualised volume changes (AVCs) of the grey matter (GM) and whole brain were evaluated using icobrain ms. ResultsWhole-brain AVCs varied, especially among patients with a disease duration within approximately 16 years. Cluster analysis using two variables, disease duration and whole-brain AVC, identified the SM (short to middle duration and mild atrophy rates), SS (short to middle duration and severe atrophy rates), and L (long duration) groups. The optimal cut-off values for disease duration and whole-brain AVC to discriminate among the three groups were 15.8 years and −0.43%, respectively. Compared with the SM group, the SS group had higher Multiple Sclerosis Severity Scale (MSSS) and Expanded Disability Status Scale (EDSS) scores, lower information processing speed (IPS), higher lesion loads, higher whole-brain and GM volume loss, and higher GM atrophy rates. Moreover, among the 63 patients with MS included in the SM and SS groups, whole-brain AVCs were significantly correlated with the EDSS and MSSS scores and IPS. ConclusionBVL rates vary, especially among Japanese patients with MS with short to middle disease duration, and BVL degree is associated with poor prognosis.