Spatiotemporal subtypes of brain and spinal cord atrophy in neuromyelitis optica spectrum disorders and multiple sclerosis.

Background: Neuromyelitis optica spectrum disorders (NMOSD) and multiple sclerosis (MS) are autoimmune demyelinating diseases with overlapping clinical features but distinct patterns of brain and spinal cord atrophy. The precise atrophy subtypes specific to each disease remain elusive. This study aimed to identify shared and distinct atrophy subtypes in NMOSD and MS, using neuroimaging to explore their clinical significance and potential implications for tailored treatment strategies.

Brain Structure Deviations in Patients with Parkinson Disease without Dementia Using Normative Modeling.

Background And Purpose: Cortical alterations in Parkinson disease (PD) without dementia remain inconsistent. This study aimed to determine the cortical alterations of PD without dementia and the relationships between cortical alterations and both motor and nonmotor symptoms.

Materials And Methods: Individualized centile scores for brain structure in 225 patients with PD without dementia were derived from life span brain charts from the Lifespan Brain Chart Consortium and adjusted using a local sample of 451 healthy controls (HC).

Deep Gray Matter Iron Deposition in NMOSD and MOGAD: A Comparative Study with MS.

Rationale And Objectives: To investigate deep gray matter (DGM) susceptibility in neuromyelitis optica spectrum disorders (NMOSD) and myelin-oligodendrocyte glycoprotein antibody-associated disease (MOGAD) using quantitative susceptibility mapping (QSM) with multiple sclerosis (MS) as a disease comparison, and explore its clinical significance.

Materials And Methods: We prospectively recruited 200 participants with QSM images: 81 NMOSD (62 aquaporin-4 [AQP4] antibody seropositive [AQP4+] and 19 AQP4 antibody seronegative [AQP4-]), 20 MOGAD, 71 relapsing-remitting MS, and 28 healthy controls (HC). We used voxel-wise analysis to compare differences in DGM susceptibility across groups, and linear regression analysis to relate susceptibility with structural MRI measures and clinical variables.

Brain corticospinal tract abnormalities in aquaporin-4 seropositive neuromyelitis optica spectrum disorder with longitudinally extensive transverse myelitis.

Widespread white matter changes, including those in the corticospinal tract (CST), have been observed in patients with neuromyelitis optica spectrum disorder (NMOSD). However, whether these alterations originate within the brain or result from spinal cord damage remains unclear. To investigate the CST alteration in AQP4-IgG positive NMOSD with longitudinally extensive transverse myelitis (LETM), and evaluate its relevance to LETM via fixel-based analysis.

Thalamic Network Controllability Predicts Cognitive Impairment in Multiple Sclerosis.

Recent research suggests that individuals with multiple sclerosis (MS) and cognitive impairment exhibit more effortful and less efficient transitions in brain network activity. Previous studies further highlight the increased vulnerability of specific regions, particularly the thalamus, to disease-related damage. This study investigates whether MS affects the controllability of specific brain regions in driving network activity transitions across the brain and examines the relationship between these changes and cognitive impairment in patients.

Anatomy-guided slice-description interaction for multimodal brain disease diagnosis based on 3D image and radiological report.

Accurate brain disease diagnosis based on radiological images is desired in clinical practice as it can facilitate early intervention and reduce the risk of damage. However, existing unimodal image-based models struggle to process high-dimensional 3D brain imaging data effectively. Multimodal disease diagnosis approaches based on medical images and corresponding radiological reports achieved promising progress with the development of vision-language models.

Unsupervised brain MRI tumour segmentation via two-stage image synthesis.

Deep learning shows promise in automated brain tumour segmentation, but it depends on costly expert annotations. Recent advances in unsupervised learning offer an alternative by using synthetic data for training. However, the discrepancy between real and synthetic data limits the accuracy of the unsupervised approaches.

Complexity of intrinsic brain activity in relapsing-remitting multiple sclerosis patients: patterns, association with structural damage, and clinical disability.

Functional plasticity has been demonstrated in multiple sclerosis (MS) studies. However, the intrinsic brain activity complexity alterations remain unclear. Here, using a coarse-graining time-series procedure algorithm, we obtained multiscale entropy (MSE) from a retrospective multi-centre dataset (208 relapsing-remitting MS patients and 228 healthy controls).

Imaging Transcriptomics of Brain Functional Alterations in MS and Neuromyelitis Optica Spectrum Disorder.

Background And Purpose: The underlying transcriptomic signatures driving brain functional alterations in MS and neuromyelitis optica spectrum disorder (NMOSD) are still unclear.

Materials And Methods: Regional fractional amplitude of low-frequency fluctuation (fALFF) values were obtained and compared among 209 patients with MS, 90 patients with antiaquaporin-4 antibody (AQP4)+ NMOSD, 49 with AQP4- NMOSD, and 228 healthy controls from a discovery cohort. We used partial least squares (PLS) regression to identify the gene transcriptomic signatures associated with disease-related fALFF alterations.

Spatial structural abnormality maps associated with cognitive and physical performance in relapsing-remitting multiple sclerosis.

Objectives: We aimed to characterize the brain abnormalities that are associated with the cognitive and physical performance of patients with relapsing-remitting multiple sclerosis (RRMS) using a deep learning algorithm.

Materials And Methods: Three-dimensional (3D) nnU-Net was employed to calculate a novel spatial abnormality map by T1-weighted images and 281 RRMS patients (Dataset-1, male/female = 101/180, median age [range] = 35.0 [17.

Topological structural characteristics in patients with systemic lupus erythematosus with and without neuropsychiatric symptoms.

Purpose: This study investigated the topological structural characteristics of systemic lupus erythematosus (SLE) with and without neuropsychiatric symptoms (NPSLE and non-NPSLE), and explore their clinical implications.

Methods: We prospectively recruited 50 patients with SLE (21 non-NPSLE and 29 NPSLE) and 32 age-matched healthy controls (HCs), using MRI diffusion tensor imaging. Individual structural networks were constructed using fibre numbers between brain areas as edge weights.

Neuroimaging analysis reveals distinct cerebral perfusion responses to fasting-postprandial metabolic switching in Alzheimer's disease patients.

Aims: Extended fasting-postprandial switch intermitting time has been shown to affect Alzheimer's disease (AD). Few studies have investigated the cerebral perfusion response to fasting-postprandial metabolic switching (FMS) in AD patients. We aimed to evaluate the cerebral perfusion response to FMS in AD patients.

Assessment of multi-modal magnetic resonance imaging for glioma based on a deep learning reconstruction approach with the denoising method.

Background: Deep learning reconstruction (DLR) with denoising has been reported as potentially improving the image quality of magnetic resonance imaging (MRI). Multi-modal MRI is a critical non-invasive method for tumor detection, surgery planning, and prognosis assessment; however, the DLR on multi-modal glioma imaging has not been assessed.

Purpose: To assess multi-modal MRI for glioma based on the DLR method.

Choroid plexus volume as a novel candidate neuroimaging marker of the Alzheimer's continuum.

Background: Enlarged choroid plexus (ChP) volume has been reported in patients with Alzheimer's disease (AD) and inversely correlated with cognitive performance. However, its clinical diagnostic and predictive value, and mechanisms by which ChP impacts the AD continuum remain unclear.

Methods: This prospective cohort study enrolled 607 participants [healthy control (HC): 110, mild cognitive impairment (MCI): 269, AD dementia: 228] from the Chinese Imaging, Biomarkers, and Lifestyle study between January 1, 2021, and December 31, 2022.

Mapping macrostructural and microstructural brain alterations in patients with neuronal intranuclear inclusion disease.

Background And Purpose: Neuronal intranuclear inclusion disease (NIID) is a rare complex neurodegenerative disorder presents with various radiological features. The study aimed to investigate the structural abnormalities in NIID using multi-shell diffusion MR.

Materials And Methods: Twenty-eight patients with adult-onset NIID and 32 healthy controls were included.

Distinct virtual histology of grey matter atrophy in four neuroinflammatory diseases.

Grey matter (GM) atrophies are observed in multiple sclerosis, neuromyelitis optica spectrum disorders [NMOSD; both anti-aquaporin-4 antibody-positive (AQP4+) and -negative (AQP4-) subtypes] and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). Revealing the pathogenesis of brain atrophy in these disorders would help their differential diagnosis and guide therapeutic strategies. To determine the neurobiological underpinnings of GM atrophies in multiple sclerosis, AQP4+ NMOSD, AQP4- NMOSD and MOGAD, we conducted a virtual histology analysis that links T1-weighted image derived GM atrophy and gene expression using a multicentre cohort of 324 patients with multiple sclerosis, 197 patients with AQP4+ NMOSD, 75 patients with AQP4- NMOSD, 47 patients with MOGAD and 2169 healthy control subjects.

Spinal cord and brain atrophy patterns in neuromyelitis optica spectrum disorder and multiple sclerosis.

Background: Spinal cord and brain atrophy are common in neuromyelitis optica spectrum disorder (NMOSD) and relapsing-remitting multiple sclerosis (RRMS) but harbor distinct patterns accounting for disability and cognitive impairment.

Methods: This study included 209 NMOSD and 304 RRMS patients and 436 healthy controls. Non-negative matrix factorization was used to parse differences in spinal cord and brain atrophy at subject level into distinct patterns based on structural MRI.

Interpretable and Intuitive Machine Learning Approaches for Predicting Disability Progression in Relapsing-Remitting Multiple Sclerosis Based on Clinical and Gray Matter Atrophy Indicators.

Rationale And Objectives: To investigate whether clinical and gray matter (GM) atrophy indicators can predict disability in relapsing-remitting multiple sclerosis (RRMS) and to enhance the interpretability and intuitiveness of a predictive machine learning model.

Materials And Methods: 145 and 50 RRMS patients with structural MRI and at least 1-year follow-up Expanded Disability Status Scale (EDSS) results were retrospectively enrolled and placed in the discovery and external test cohorts, respectively. Six clinical and radiomics feature-based machine learning classifiers were trained and tested to predict disability progression in the discovery cohort and validated in the external test set.

Association of Mean Upper Cervical Spinal Cord Cross-Sectional Area With Cerebral Small Vessel Disease: A Community-Based Cohort Study.

Background: The purpose of this study was to investigate the association between the mean upper cervical spinal cord cross-sectional area (MUCCA) and the risk and severity of cerebral small vessel disease (CSVD).

Methods: Community-dwelling residents in Lishui City, China, from the cross-sectional survey in the PRECISE cohort study (Polyvascular Evaluation for Cognitive Impairment and Vascular Events) conducted from 2017 to 2019. We included 1644 of 3067 community-dwelling adults in the PRECISE study after excluding those with incorrect, incomplete, insufficient, or missing clinical or imaging data.