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Background: Predicting the progression of cognitive decline in Alzheimer's disease (AD) is important for treatment selection and patient counseling. Structural MRI markers such as hippocampus or basal forebrain volumes might represent useful instruments for the prediction of cognitive decline. The primary objective was to determine the predictive value of hippocampus and basal forebrain volumes for global and domain specific cognitive decline in AD dementia during cholinergic treatment. Methods: We used MRI and cognitive data from 124 patients with the clinical diagnosis of AD dementia, derived from the ADNI-1 cohort, who were on standard of care cholinesterase inhibitor treatment during a follow-up period between 0.4 and 3.1 years. We used linear mixed effects models with cognitive function as outcome to assess the main effects as well as two-way interactions between baseline volumes and time controlling for age, sex, and total intracranial volume. This model accounts for individual variation in follow-up times. Results: Basal forebrain volume, but not hippocampus volume, was a significant predictor of rates of global cognitive decline. Larger volumes were associated with smaller rates of cognitive decline. Left hippocampus volume had a modest association with rates of episodic memory decline. Baseline performance in global cognition and memory was significantly associated with hippocampus and basal forebrain volumes; in addition, basal forebrain volume was associated with baseline performance in executive function. Conclusions: Our findings indicate that in AD dementia patients, basal forebrain volume may be a useful marker to predict subsequent cognitive decline during cholinergic treatment.

Background: International clinical criteria are the reference for the diagnosis of degenerative parkinsonism in clinical research, but they may lack sensitivity and specificity in the early stages. Objectives: To determine whether magnetic resonance imaging (MRI) analysis, through visual reading or machine‐learning approaches, improves diagnostic accuracy compared with clinical diagnosis at an early stage in patients referred for suspected degenerative parkinsonism. Materials: Patients with initial diagnostic uncertainty between Parkinson's disease (PD), progressive supranuclear palsy (PSP), and multisystem atrophy (MSA), with brain MRI performed at the initial visit (V1) and available 2‐year follow‐up (V2), were included. We evaluated the accuracy of the diagnosis established based on: (1) the international clinical diagnostic criteria for PD, PSP, and MSA at V1 ("Clin1"); (2) MRI visual reading blinded to the clinical diagnosis ("MRI"); (3) both MRI visual reading and clinical criteria at V1 ("MRI and Clin1"), and (4) a machine‐learning algorithm ("Algorithm"). The gold standard diagnosis was established by expert consensus after a 2‐year follow‐up. Results: We recruited 113 patients (53 with PD, 31 with PSP, and 29 with MSA). Considering the whole population, compared with clinical criteria at the initial visit ("Clin1": balanced accuracy, 66.2%), MRI visual reading showed a diagnostic gain of 14.3% ("MRI": 80.5%; P = 0.01), increasing to 19.2% when combined with the clinical diagnosis at the initial visit ("MRI and Clin1": 85.4%; P < 0.0001). The algorithm achieved a diagnostic gain of 9.9% ("Algorithm": 76.1%; P = 0.08). Conclusion: Our study shows the use of MRI analysis, whether by visual reading or machine‐learning methods, for early differentiation of parkinsonism. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Isolated rapid eye movement sleep behaviour disorder (iRBD) is a sleep disorder characterized by the loss of rapid eye movement sleep muscle atonia and the appearance of abnormal movements and vocalizations during rapid eye movement sleep. It is a strong marker of incipient synucleinopathy such as dementia with Lewy bodies and Parkinson's disease. Patients with iRBD already show brain changes that are reminiscent of manifest synucleinopathies including brain atrophy. However, the mechanisms underlying the development of this atrophy remain poorly understood. In this study, we performed cutting-edge imaging transcriptomics and comprehensive spatial mapping analyses in a multicentric cohort of 171 polysomnography-confirmed iRBD patients [67.7 ± 6.6 (49–87) years; 83% men] and 238 healthy controls [66.6 ± 7.9 (41–88) years; 77% men] with T1-weighted MRI to investigate the gene expression and connectivity patterns associated with changes in cortical thickness and surface area in iRBD. Partial least squares regression was performed to identify the gene expression patterns underlying cortical changes in iRBD. Gene set enrichment analysis and virtual histology were then done to assess the biological processes, cellular components, human disease gene terms, and cell types enriched in these gene expression patterns. We then used structural and functional neighbourhood analyses to assess whether the atrophy patterns in iRBD were constrained by the brain's structural and functional connectome. Moreover, we used comprehensive spatial mapping analyses to assess the specific neurotransmitter systems, functional networks, cytoarchitectonic classes, and cognitive brain systems associated with cortical changes in iRBD. All comparisons were tested against null models that preserved spatial autocorrelation between brain regions and compared to Alzheimer's disease to assess the specificity of findings to synucleinopathies. We found that genes involved in mitochondrial function and macroautophagy were the strongest contributors to the cortical thinning occurring in iRBD. Moreover, we demonstrated that cortical thinning was constrained by the brain's structural and functional connectome and that it mapped onto specific networks involved in motor and planning functions. In contrast with cortical thickness, changes in cortical surface area were related to distinct genes, namely genes involved in the inflammatory response, and to different spatial mapping patterns. The gene expression and connectivity patterns associated with iRBD were all distinct from those observed in Alzheimer's disease. In summary, this study demonstrates that the development of brain atrophy in synucleinopathies is constrained by specific genes and networks. [ABSTRACT FROM AUTHOR]

Isolated REM sleep behaviour disorder (iRBD) is a synucleinopathy characterized by abnormal behaviours and vocalizations during REM sleep. Most iRBD patients develop dementia with Lewy bodies, Parkinson's disease, or multiple system atrophy over time. Patients with iRBD exhibit brain atrophy patterns that are reminiscent of those observed in overt synucleinopathies. However, the mechanisms linking brain atrophy to the underlying alpha-synuclein pathophysiology are poorly understood. Our objective was to investigate how the prion-like and regional vulnerability hypotheses of alpha-synuclein might explain brain atrophy in iRBD. Using a multicentric cohort of 182 polysomnography-confirmed iRBD patients who underwent T1-weighted MRI, we performed vertex-based cortical surface and deformation-based morphometry analyses to quantify brain atrophy in patients (67.8 years, 84% men) and 261 healthy controls (66.2 years, 75%) and investigated the morphological correlates of motor and cognitive functioning in iRBD. Next, we applied the agent-based Susceptible-Infected-Removed model (i.e., a computational model that simulates in silico the spread of pathologic alpha-synuclein based on structural connectivity and gene expression) and tested if it recreated atrophy in iRBD by statistically comparing simulated regional brain atrophy to the atrophy observed in patients. The impact of SNCA and GBA gene expression and brain connectivity was then evaluated by comparing the model fit to the one obtained in null models where either gene expression or connectivity was randomized. The results showed that iRBD patients present with cortical thinning and tissue deformation, which correlated with motor and cognitive functioning. Next, we found that the computational model recreated cortical thinning (r = 0.51, p = 0.0007) and tissue deformation (r = 0.52, p = 0.0005) in patients, and that the connectome's architecture along with SNCA and GBA gene expression contributed to shaping atrophy in iRBD. We further demonstrated that the full agent-based model performed better than network measures or gene expression alone in recreating the atrophy pattern in iRBD. In summary, atrophy in iRBD is extensive, correlates with motor and cognitive function, and can be recreated using the dynamics of agent-based modelling, structural connectivity, and gene expression. These findings support the concepts that both prion-like spread and regional susceptibility account for the atrophy observed in prodromal synucleinopathies. Therefore, the agent-based Susceptible-Infected-Removed model may be a useful tool for testing hypotheses underlying neurodegenerative diseases and new therapies aimed at slowing or stopping the spread of alpha-synuclein pathology. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the spatiotemporal changes in neuromelanin-sensitive MRI signal in the substantia nigra and their relation to clinical scores of disease severity in patients with early or progressing Parkinson's disease and patients with idiopathic rapid eye movement sleep behaviour disorder (iRBD) exempt of Parkinsonian signs compared to healthy control subjects. Longitudinal T1-weighted anatomical and neuromelanin-sensitive MRI was performed in two cohorts, including patients with iRBD, patients with early or progressing Parkinson's disease, and control subjects. Based on the aligned substantia nigra segmentations using a study-specific brain anatomical template, parametric maps of the probability of a voxel belonging to the substantia nigra were calculated for patients with various degrees of disease severity and controls. For each voxel in the substantia nigra, probability map of controls, correlations between signal-to-noise ratios on neuromelanin-sensitive MRI in patients with iRBD and Parkinson's disease and clinical scores of motor disability, cognition and mood/behaviour were calculated. Our results showed that in patients, compared to the healthy control subjects, the volume of the substantia nigra was progressively reduced for increasing disease severity. The neuromelanin signal changes appeared to start in the posterolateral motor areas of the substantia nigra and then progressed to more medial areas of this region. The ratio between the volume of the substantia nigra in patients with Parkinson's disease relative to the controls was best fitted by a mono-exponential decay. Based on this model, the pre-symptomatic phase of the disease started at 5.3 years before disease diagnosis, and 23.1% of the substantia nigra volume was lost at the time of diagnosis, which was in line with previous findings using post-mortem histology of the human substantia nigra and radiotracer studies of the human striatum. Voxel-wise patterns of correlation between neuromelanin-sensitive MRI signal-to-noise ratio and motor, cognitive and mood/behavioural clinical scores were localized in distinct regions of the substantia nigra. This localization reflected the functional organization of the nigrostriatal system observed in histological and electrophysiological studies in non-human primates (motor, cognitive and mood/behavioural domains). In conclusion, neuromelanin-sensitive MRI enabled us to assess voxel-wise modifications of substantia nigra's morphology in vivo in humans, including healthy controls, patients with iRBD and patients with Parkinson's disease, and identify their correlation with nigral function across all motor, cognitive and behavioural domains. This insight could help assess disease progression in drug trials of disease modification. [ABSTRACT FROM AUTHOR]

Background: Experimental autoimmune encephalomyelitis (EAE) in the common marmoset is a nonhuman primate model of multiple sclerosis (MS) that shares numerous clinical, radiological, and pathological features with MS. Among the clinical features are motor and sensory deficits that are highly suggestive of spinal cord (SC) damage. Objective: To characterize the extent and nature of SC damage in symptomatic marmosets with EAE using a combined magnetic resonance imaging (MRI) and histopathology approach. Materials and Methods: SC tissues from five animals were scanned using 7 T MRI to collect high-resolution ex vivo images. Lesions were segmented and classified based on shape, size, and distribution along the SC. Tissues were processed for histopathological characterization (myelin and microglia/macrophages). Statistical analysis, using linear mixed-effects models, evaluated the association between MRI and histopathology. Results: Marmosets with EAE displayed two types of SC lesions: focal and subpial lesions. Both lesion types were heterogeneous in size and configuration and corresponded to areas of marked demyelination with high density of inflammatory cells. Inside the lesions, the MRI signal was significantly correlated with myelin content (p < 0.001). Conclusions: Our findings underscore the relevance of this nonhuman primate EAE model for better understanding mechanisms of MS lesion formation in the SC. [ABSTRACT FROM AUTHOR]

Purpose To validate semiautomated spinal cord segmentation in healthy subjects and patients with neurodegenerative diseases and trauma. Materials and Methods Forty-nine healthy subjects, as well as 29 patients with amyotrophic lateral sclerosis, 19 with spinal muscular atrophy, and 14 with spinal cord injuries were studied. Cord area was measured from T2-weighted 3D turbo spin echo images (cord levels from C2 to T9) using the semiautomated segmentation method of Losseff et al (Brain [1996] 119(Pt 3):701-708), compared with manual segmentation. Reproducibility was evaluated using the inter- and intraobserver coefficient of variation (CoV). Accuracy was assessed using the Dice similarity coefficient (DSC). Robustness to initialization was assessed by simulating modifications to the contours drawn manually prior to segmentation. Results Mean interobserver CoV was 4.00% for manual segmentation (1.90% for Losseff's method) in the cervical region and 5.62% (respectively 2.19%) in the thoracic region. Mean intraobserver CoV was 2.34% for manual segmentation (1.08% for Losseff's method) in the cervical region and 2.35% (respectively 1.34%) in the thoracic region. DSC was high (0.96) in both cervical and thoracic regions. DSC remained higher than 0.8 even when modifying initial contours by 50%. Conclusion The semiautomated segmentation method showed high reproducibility and accuracy in measuring spinal cord area. J. Magn. Reson. Imaging 2015;41:454-459.© 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Severe cognitive impairment involving multiple cognitive domains can occur early during the course of multiple sclerosis (MS). We investigated resting state functional connectivity changes in large-scale brain networks and related structural damage underlying cognitive dysfunction in patients with early MS. Patients with relapsing MS (3-5 years disease duration) were prospectively assigned to two groups based on a standardized neuropsychological evaluation: (1) cognitively impaired group (CI group, n = 15), with abnormal performances in at least 3 tests; (2) cognitively preserved group (CP group, n = 20) with normal performances in all tests. Patients and age-matched healthy controls underwent a multimodal 3T magnetic resonance imaging (MRI) including anatomical T1 and T2 images, diffusion imaging and resting state functional MRI. Structural MRI analysis revealed that CI patients had a higher white matter lesion load compared to CP and a more severe atrophy in gray matter regions highly connected to networks involved in cognition. Functional connectivity measured by integration was increased in CP patients versus controls in attentional networks (ATT), while integration was decreased in CI patients compared to CP both in the default mode network (DMN) and ATT. An anatomofunctional study within the DMN revealed that functional connectivity was mostly altered between the medial prefrontal cortex (MPFC) and the posterior cingulate cortex (PCC) in CI patients compared to CP and controls. In a multilinear regression model, functional correlation between MPFC and PCC was best predicted by PCC atrophy. Disconnection in the DMN and ATT networks may deprive the brain of compensatory mechanisms required to face widespread structural damage. Hum Brain Mapp 35:4706-4717, 2014. © 2014 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Neuropathological studies in Huntington disease (HD) have demonstrated neuronal loss in the striatum, as well as in other brain regions including the cortex. With diffusion tensor MRI we evaluated the hypothesis that the clinical dysfunction in HD is related to regionally specific lesions of circuit-specific cortico-basal ganglia networks rather than to the striatum only. We included 27 HD and 24 controls from the TRACK-HD Paris cohort. The following assessments were used: self-paced tapping tasks, trail B making test (TMT), University of Pennsylvania smell identification test (UPSIT), and apathy scores from the problem behaviors assessment. Group comparisons of fractional anisotropy and mean diffusivity and correlations were performed using voxel-based analysis. In the cortex, HD patients showed significant correlations between: (i) self paced tapping and mean diffusivity in the parietal lobe at 1.8 Hz and prefrontal areas at 3 Hz, (ii) UPSIT and mean diffusivity in the parietal, and median temporal lobes, the cingulum and the insula, and fractional anisotropy in the insula and the external capsule, (iii) TMT B and mean diffusivity in the white matter of the superior frontal, orbital, temporal, superior parietal and post central areas, and (iv) apathy and fractional anisotropy in the white matter of the rectus gyrus. In the basal ganglia, we found correlations between the self paced tapping, UPSIT, TMT tests, and mean diffusivity in the anterior part of the putamen and the caudate nucleus. In conclusion, disruption of motor, associative and limbic cortico-striatal circuits differentially contribute to the clinical signs of the disease. Hum Brain Mapp 34:2141-2153, 2013. © 2012 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

ABSTRACT This review will consider the knowledge that neuroimaging studies have provided to the understanding of the anatomy of dystonia. Major advances have occurred in the use of neuroimaging for dystonia in the past 2 decades. At present, the most developed imaging approaches include whole-brain or region-specific studies of structural or diffusion changes, functional imaging using fMRI or positron emission tomography (PET), and metabolic imaging using fluorodeoxyglucose PET. These techniques have provided evidence that regions other than the basal ganglia are involved in dystonia. In particular, there is increasing evidence that primary dystonia can be viewed as a circuit disorder, involving the basal ganglia-thalamo-cortical and cerebello-thalamo-cortical pathways. This suggests that a better understanding of the dysfunction in each region in the network and their interactions are important topics to address. Current views of interpretation of imaging data as cause or consequence of dystonia, and the postmortem correlates of imaging data are presented. The application of imaging as a tool to monitor therapy and its use as an outcome measure will be discussed. © 2013 Movement Disorder Society [ABSTRACT FROM AUTHOR]

Until recently, conventional magnetic resonance imaging (MRI) was most often negative in Parkinson's disease or showed nonspecific findings. Recent developments in structural MRI, including relaxometry, magnetization transfer, and neuromelanin imaging, have demonstrated improved contrast and enabled more accurate visualization of deep brain nuclei, in particular, the substantia nigra. Meanwhile, diffusion imaging has provided useful biomarkers of substantia nigra degeneration, showing reduced anisotropy and anatomical connectivity with the striatum and thalamus. These advances in structural imaging are complemented by findings of magnetic resonance spectroscopy on brain metabolism and resting-state functional MRI on functional connectivity. This article presents an overview of these new structural, metabolic, and resting-state functional MRI techniques and their implications for Parkinson's disease. The techniques are reviewed in the context of their potential for better understanding the disease in terms of diagnosis and pathophysiology and as biomarkers of its progression. © 2012 Movement Disorder Society [ABSTRACT FROM AUTHOR]

Manual segmentation from magnetic resonance imaging (MR) is the gold standard for evaluating hippocampal atrophy in Alzheimer's disease (AD). Nonetheless, different segmentation protocols provide up to 2.5-fold volume differences. Here we surveyed the most frequently used segmentation protocols in the AD literature as a preliminary step for international harmonization. The anatomical landmarks (anteriormost and posteriormost slices, superior, inferior, medial, and lateral borders) were identified from 12 published protocols for hippocampal manual segmentation ([Abbreviation] first author, publication year: [B] Bartzokis, 1998; [C] Convit, 1997; [dTM] deToledo-Morrell, 2004; [H] Haller, 1997; [J] Jack, 1994; [K] Killiany, 1993; [L] Lehericy, 1994; [M] Malykhin, 2007; [Pa] Pantel, 2000; [Pr] Pruessner, 2000; [S] Soininen, 1994; [W] Watson, 1992). The hippocampi of one healthy control and one AD patient taken from the 1.5T MR ADNI database were segmented by a single rater according to each protocol. The accuracy of the protocols' interpretation and translation into practice was checked with lead authors of protocols through individual interactive web conferences. Semantically harmonized landmarks and differences were then extracted, regarding: (a) the posteriormost slice, protocol [B] being the most restrictive, and [H, M, Pa, Pr, S] the most inclusive; (b) inclusion [C, dTM, J, L, M, Pr, W] or exclusion [B, H, K, Pa, S] of alveus/fimbria; (c) separation from the parahippocampal gyrus, [C] being the most restrictive, [B, dTM, H, J, Pa, S] the most inclusive. There were no substantial differences in the definition of the anteriormost slice. This survey will allow us to operationalize differences among protocols into tracing units, measure their impact on the repeatability and diagnostic accuracy of manual hippocampal segmentation, and finally develop a harmonized protocol. [ABSTRACT FROM AUTHOR]

The Free and Cued Selective Reminding Test (FCSRT) is a verbal episodic memory test used to identify patients with mild Alzheimer's disease (AD). The present study investigates the relationships between performance on FCSRT and grey matter atrophy assessed with structural MRI in patients with AD. Three complementary MRI-based analyses (VBM analysis, ROI-based analysis, and three-dimensional hippocampal surface-based shape analysis) were performed in 35 patients with AD to analyze correlations between regional atrophy and their scores for episodic memory using the FCSRT. With VBM analysis, the total score on the FCSRT was correlated with left medial temporal lobe atrophy including the left hippocampus but also the thalami. In addition, using ROI-based analysis, the total recall score on the FCSRT was correlated with the left hippocampal volume. With three-dimensional hippocampal surface-based shape analysis, both free recall and total recall scores were correlated with regions corresponding approximately to the CA1 field. No correlation was found with short term memory scores using any of these methods of analysis. In AD, the FCSRT may be considered as a useful clinical marker of memory disorders due to medial temporal damage, specially the CA1 field of the hippocampus. [ABSTRACT FROM AUTHOR]

Quantitative biomarkers for clinical differentiation of parkinsonian syndromes are still lacking. Our aim was to evaluate the value of combining clinically feasible manual measurements of R2* relaxation rates and mean diffusivity (MD) in subcortical regions and brainstem morphometric measurements to improve the discrimination of parkinsonian syndromes. Twenty-two healthy controls (HC), 25 patients with Parkinson's disease (PD), 19 with progressive supranuclear palsy (PSP) and 27 with multiple system atrophy (MSA, 21 with the parkinsonian variant -MSAp, 6 with the cerebellar variant -MSAc) were recruited. R2*, MD measurements and morphometric biomarkers including the midbrain to pons area ratio and the Magnetic Resonance Parkinsonism Index (MRPI) were compared between groups and their diagnostic performances were assessed. Morphometric biomarkers discriminated better patients with PSP (ratio: AUC 0.89, MRPI: AUC 0.89) and MSAc (ratio: AUC 0.82, MRPI: AUC 0.75) from other groups. R2* and MD measurements in the posterior putamen performed better in separating patients with MSAp from PD (R2*: AUC 0.89; MD: AUC 0.89). For the three-class classification "MSA vs PD vs PSP", the combination of MD and R2* measurements in the posterior putamen with morphometric biomarkers (AUC: 0.841) outperformed each marker separately. At the individual-level, there were seven discordances between imaging-based prediction and clinical diagnosis involving MSA. Using the new Movement Disorder Society criteria for the diagnosis of MSA, three of these seven patients were clinically reclassified as predicted by quantitative imaging. Combining R2* and MD measurements in the posterior putamen with morphometric biomarkers improves the discrimination of parkinsonism. • R2* and MD measurements in the posterior putamen are robust clinically usable biomarkers for the discrimination of MSAp. • Their combination with brainstem morphometric biomarkers increases the performance of the multiclass classification "MSA versus PD versus PSP". • Concordance between MRI-based diagnostic prediction and clinical diagnosis was improved using the new diagnostic criteria for MSA. [ABSTRACT FROM AUTHOR]