Segmentation of scalp, skull, CSF, grey matter and white matter in MRI of mouse brain

2010 ◽  
Author(s):  
Xinzeng Wang ◽  
Xuena Wang ◽  
Weitao Li ◽  
Zhiyu Qian
Keyword(s):  
White Matter ◽  
Mouse Brain ◽  
Grey Matter

Individual differences in white and grey matter structure associated with verbal habits of thought

2019 ◽  
Author(s):  
Justin C. Hayes ◽  
Katherine L Alfred ◽  
Rachel Pizzie ◽  
Joshua S. Cetron ◽  
David J. M. Kraemer
Keyword(s):  
Individual Differences ◽  
White Matter ◽  
Cognitive Processing ◽  
Grey Matter ◽  
Structural Changes ◽  
Structural Integrity ◽  
Diffusion Tensor ◽  
Self Report ◽  
White Matter Tracts

Modality specific encoding habits account for a significant portion of individual differences reflected in functional activation during cognitive processing. Yet, little is known about how these habits of thought influence long-term structural changes in the brain. Traditionally, habits of thought have been assessed using self-report questionnaires such as the visualizer-verbalizer questionnaire. Here, rather than relying on subjective reports, we measured habits of thought using a novel behavioral task assessing attentional biases toward picture and word stimuli. Hypothesizing that verbal habits of thought are reflected in the structural integrity of white matter tracts and cortical regions of interest, we used diffusion tensor imaging and volumetric analyses to assess this prediction. Using a whole-brain approach, we show that word bias is associated with increased volume in several bilateral language regions, in both white and grey matter parcels. Additionally, connectivity within white matter tracts within an a priori speech production network increased as a function of word bias. These results demonstrate long-term structural and morphological differences associated with verbal habits of thought.

scholarly journals Modelling the cascade of biomarker changes in GRN-related frontotemporal dementia

2021 ◽  
pp. jnnp-2020-323541
Author(s):  
Jessica L Panman ◽  
Vikram Venkatraghavan ◽  
Emma L van der Ende ◽  
Rebecca M E Steketee ◽  
Lize C Jiskoot ◽  
...  
Keyword(s):  
White Matter ◽  
Frontotemporal Dementia ◽  
Disease Severity ◽  
Grey Matter ◽  
Clinical Stage ◽  
Data Driven ◽  
Grey Matter Volume ◽  
Matter Volume ◽  
Mutation Carriers ◽  
Individual Disease

ObjectiveProgranulin-related frontotemporal dementia (FTD-GRN) is a fast progressive disease. Modelling the cascade of multimodal biomarker changes aids in understanding the aetiology of this disease and enables monitoring of individual mutation carriers. In this cross-sectional study, we estimated the temporal cascade of biomarker changes for FTD-GRN, in a data-driven way.MethodsWe included 56 presymptomatic and 35 symptomatic GRN mutation carriers, and 35 healthy non-carriers. Selected biomarkers were neurofilament light chain (NfL), grey matter volume, white matter microstructure and cognitive domains. We used discriminative event-based modelling to infer the cascade of biomarker changes in FTD-GRN and estimated individual disease severity through cross-validation. We derived the biomarker cascades in non-fluent variant primary progressive aphasia (nfvPPA) and behavioural variant FTD (bvFTD) to understand the differences between these phenotypes.ResultsLanguage functioning and NfL were the earliest abnormal biomarkers in FTD-GRN. White matter tracts were affected before grey matter volume, and the left hemisphere degenerated before the right. Based on individual disease severities, presymptomatic carriers could be delineated from symptomatic carriers with a sensitivity of 100% and specificity of 96.1%. The estimated disease severity strongly correlated with functional severity in nfvPPA, but not in bvFTD. In addition, the biomarker cascade in bvFTD showed more uncertainty than nfvPPA.ConclusionDegeneration of axons and language deficits are indicated to be the earliest biomarkers in FTD-GRN, with bvFTD being more heterogeneous in disease progression than nfvPPA. Our data-driven model could help identify presymptomatic GRN mutation carriers at risk of conversion to the clinical stage.

Imaging Usual Addictions: Tobacco, Canabis and Alcohol

2009 ◽  
Vol 24 (S1) ◽  
pp. 1-1
Author(s):  
C. Leroy ◽  
S. Chanraud ◽  
E. Artiges ◽  
C. Martelli ◽  
A. Cachia ◽  
...  
Keyword(s):  
White Matter ◽  
Psychosocial Functioning ◽  
Grey Matter ◽  
Diffusion Imaging ◽  
Temporal Cortex ◽  
List Type ◽  
Dopamine Level ◽  
Type Number ◽  
Positron Emission ◽  
Brain Microstructure

Background:Brain models of drug addiction are being tackled in humans, using PET and MRI.Results:1.Whereas tobacco and cannabis do not interact directly with dopamine sites, positron emission tomography detected lower availability in sites regulating the catecholamines homeostasis, notably in dopamine transporter sites in striatal and in extrastriatal regions. This further supports repeated and long term substance use progress towards an adaptative diminished basal dopamine level that would contribute to the switch to an addicted brain.2.Alcohol: abnormalities in brain macro- and micro- structure were searched in detoxified alcohol-dependents with preserved psychosocial functioning:-Brain function (fMRI): fronto-cerebellar overactivation detected during an auditory language task in alcohol-dependents may reflect the compensatory effort required for patients to maintain the same level of performance as controls.-Brain macrostructure (MRI). Widespread lower white matter volumes, and lower grey matter volumes in the frontal lobe, insula, hippocampus, thalami and cerebellum, were detected. Poorer neuropsychological performance correlated with smaller grey matter volumes in these regions and with lower white matter volume in the brainstem.-Brain microstructure (DTI): tractography of white matter fiber bundles revealed that brainstem bundles alteration may contribute to cognitive flexibility impairment. Regression analyses showed memory scores were related to brain microstructure in parahippocampal areas, frontal cortex, and left temporal cortex. This suggest diffusion imaging (DTI) is a useful probe to early alcohol-induced brain alterations.Conclusion:While indices of dopamine down-regulation are consistency detected in several drug addictions, even “socially-adapted” alcohol dependence may induce change in brain structure.Psychol Med. 1998 28:1039-48.Neuropsychopharmacology. 2007 32:429-38.IEEE Trans Med Imaging. 2007 26:553-65J Nucl Med. 2007 48:538-46.Neuropsychopharmacology (Chanraud S et al., 2008 Jul 9. [Epub ahead of print]).J Clin Psychopharmacol (Leroy C et al, in press).

Spinal cord grey matter lesions in multiple sclerosis detected by post-mortem high field MR imaging

2008 ◽  
Vol 15 (2) ◽  
pp. 180-188 ◽  
Author(s):  
CP Gilmore ◽  
JJG Geurts ◽  
N Evangelou ◽  
JCJ Bot ◽  
RA van Schijndel ◽  
...  
Keyword(s):  
Spinal Cord ◽  
White Matter ◽  
Mr Imaging ◽  
High Field ◽  
Grey Matter ◽  
Great Majority ◽  
Proton Density ◽  
Post Mortem ◽  
Mr Images ◽  
The Brain

Background Post-mortem studies demonstrate extensive grey matter demyelination in MS, both in the brain and in the spinal cord. However the clinical significance of these plaques is unclear, largely because they are grossly underestimated by MR imaging at conventional field strengths. Indeed post-mortem MR studies suggest the great majority of lesions in the cerebral cortex go undetected, even when performed at high field. Similar studies have not been performed using post-mortem spinal cord material. Aim To assess the sensitivity of high field post-mortem MRI for detecting grey matter lesions in the spinal cord in MS. Methods Autopsy material was obtained from 11 MS cases and 2 controls. Proton Density-weighted images of this formalin-fixed material were acquired at 4.7Tesla before the tissue was sectioned and stained for Myelin Basic Protein. Both the tissue sections and the MR images were scored for grey matter and white matter plaques, with the readers of the MR images being blinded to the histopathology results. Results Our results indicate that post-mortem imaging at 4.7Tesla is highly sensitive for cord lesions, detecting 87% of white matter lesions and 73% of grey matter lesions. The MR changes were highly specific for demyelination, with all lesions scored on MRI corresponding to areas of demyelination. Conclusion Our work suggests that spinal cord grey matter lesions may be detected on MRI more readily than GM lesions in the brain, making the cord a promising site to study the functional consequences of grey matter demyelination in MS.

Abstract 44: Associations of Atrial Fibrillation, Neuroimaging Measures of Cerebrovascular Disease and Alzheimer’S Disease-related Pathology, and Cognitive Impairment

Stroke ◽  
2015 ◽  
Vol 46 (suppl_1) ◽  
Author(s):  
Jonathan Graff-Radford ◽  
Rosebud Roberts ◽  
Malini Madhavan ◽  
Alejandro Rabinstein ◽  
Ruth Cha ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
White Matter ◽  
Cerebrovascular Disease ◽  
Regression Models ◽  
Grey Matter ◽  
White Matter Hyperintensity ◽  
Carrier Status

The objective of this study was to investigate the cross-sectional associations of atrial fibrillation with neuroimaging measures of cerebrovascular disease and Alzheimer’s disease-related pathology, and their interaction with cognitive impairment. MRI scans of non-demented individuals (n=1044) from the population-based Mayo Clinic Study of Aging were analyzed for infarctions, total grey matter, hippocampal and white matter hyperintensity volumes. A subset of 496 individuals underwent FDG and C-11 Pittsburgh compound B (PiB) PET scans. We assessed the associations of atrial fibrillation with i) categorical MRI measures (cortical and subcortical infarctions) using multivariable logistic regression models, and with ii) continuous MRI measures ( hippocampal, total grey matter, and white matter hyperintensity volumes) and FDG-PET and PiB-PET measures using multivariable linear regression models, and adjusting for confounders. Among participants who underwent MRI (median age, 77.8, 51.6% male), 13.5% had atrial fibrillation. Presence of atrial fibrillation was associated with subcortical infarctions (odds ratio [OR], 1.83; p=0.002), cortical infarctions (OR, 1.91; p=0.03), total grey matter volume (Beta [β], -.025, p<.0001) after controlling for age, education, gender, APOE e4 carrier status, coronary artery disease, diabetes, history of clinical stroke, and hypertension. However, atrial fibrillation was not associated with white matter hyperintensity volume, hippocampal volume, Alzheimer’s pattern of FDG hypometabolism or PiB uptake. There was a significant interaction of cortical infarction (p for interaction=0.004) and subcortical infarction (p for interaction =0.015) with atrial fibrillation with regards to odds of mild cognitive impairment (MCI). Using subjects with no atrial fibrillation and no infarction as the reference, the OR (95% confidence intervals [CI]) for MCI was 2.98 (1.66, 5.35;p = 0.0002) among participants with atrial fibrillation and any infarction, 0.69 (0.36, 1.33;p= 0.27) for atrial fibrillation and no infarction, and 1.50 (0.96, 2.32;p = 0.07) for no atrial fibrillation and any infarction. These data highlight that atrial fibrillation is associated with MCI in the presence of infarctions.

Regional White Matter Hyperintensity Influences Grey Matter Atrophy in Mild Cognitive Impairment

2018 ◽  
Vol 66 (2) ◽  
pp. 533-549 ◽  
Author(s):  
Ashwati Vipin ◽  
Heidi Jing Ling Foo ◽  
Joseph Kai Wei Lim ◽  
Russell Jude Chander ◽  
Ting Ting Yong ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
White Matter ◽  
Grey Matter ◽  
White Matter Hyperintensity ◽  
Grey Matter Atrophy

scholarly journals Age differentiation within grey matter, white matter and between memory and white matter in an adult lifespan cohort

2017 ◽  
Author(s):  
Susanne M. M. de Mooij ◽  
Richard N. A. Henson ◽  
Lourens J. Waldorp ◽  
Cam-CAN ◽  
Rogier A. Kievit
Keyword(s):  
White Matter ◽  
Cognitive Functions ◽  
Structural Equation ◽  
Grey Matter ◽  
Fluid Intelligence ◽  
Cognitive Factors ◽  
Equation Modeling ◽  
Grey Matter Volume ◽  
Adult Lifespan ◽  
Age Related

AbstractIt is well-established that brain structures and cognitive functions change across the lifespan. A longstanding hypothesis called age differentiation additionally posits that the relations between cognitive functions also change with age. To date however, evidence for age-related differentiation is mixed, and no study has examined differentiation of the relationship between brain and cognition. Here we use multi-group Structural Equation Modeling and SEM Trees to study differences within and between brain and cognition across the adult lifespan (18-88 years) in a large (N>646, closely matched across sexes), population-derived sample of healthy human adults from the Cambridge Centre for Ageing and Neuroscience (www.cam-can.org). After factor analyses of grey-matter volume (from T1- and T2-weighted MRI) and white-matter organisation (fractional anisotropy from Diffusion-weighted MRI), we found evidence for differentiation of grey and white matter, such that the covariance between brain factors decreased with age. However, we found no evidence for age differentiation between fluid intelligence, language and memory, suggesting a relatively stable covariance pattern between cognitive factors. Finally, we observed a specific pattern of age differentiation between brain and cognitive factors, such that a white matter factor, which loaded most strongly on the hippocampal cingulum, became less correlated with memory performance in later life. These patterns are compatible with reorganization of cognitive functions in the face of neural decline, and/or with the emergence of specific subpopulations in old age.Significance statementThe theory of age differentiation posits age-related changes in the relationships between cognitive domains, either weakening (differentiation) or strengthening (de-differentiation), but evidence for this hypothesis is mixed. Using age-varying covariance models in a large cross-sectional adult lifespan sample, we found age-related reductions in the covariance among both brain measures (neural differentiation), but no covariance change between cognitive factors of fluid intelligence, language and memory. We also observed evidence of uncoupling (differentiation) between a white matter factor and cognitive factors in older age, most strongly for memory. Together, our findings support age-related differentiation as a complex, multifaceted pattern that differs for brain and cognition, and discuss several mechanisms that might explain the changing relationship between brain and cognition.

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