Alterations of mean diffusivity in brain white matter and deep gray matter in Parkinson's disease

2013 ◽  
Vol 550 ◽  
pp. 64-68 ◽  
Author(s):  
Hengjun J. Kim ◽  
Sang Joon Kim ◽  
Ho Sung Kim ◽  
Choong Gon Choi ◽  
Namkug Kim ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
White Matter ◽  
Gray Matter ◽  
Mean Diffusivity ◽  
Brain White Matter ◽  
Deep Gray Matter

scholarly journals Odor Identification and Regional Gray Matter Atrophy in Patients with Alzheimer’s Disease, Parkinson’s Disease, and the Healthy Elderly: A Cross-Sectional Structural MRI Study

2021 ◽  
Vol 11 (10) ◽  
pp. 1296
Author(s):  
Simonas Jesmanas ◽  
Rymantė Gleiznienė ◽  
Mindaugas Baranauskas ◽  
Vaidas Matijošaitis ◽  
Daiva Rastenytė
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Gray Matter ◽  
Odor Identification ◽  
Identification Performance ◽  
Healthy Elderly ◽  
Gray Matter Atrophy ◽  
Deep Gray Matter

Multiple associations between impaired olfactory performance and regional cortical and deep gray matter atrophy have been reported in separate studies of patients with Alzheimer’s disease (AD), Parkinson’s disease (PD), and of the healthy elderly. We aimed to evaluate such possible associations among these populations in a unified manner. Twenty AD, twenty PD patients’ and twenty healthy age- and sex-matched controls’ odor identification performance was assessed with the Lithuanian adaptation of the Sniffin’ Sticks 12 odor identification test, followed by morphometric gray matter analysis by MRI using FreeSurfer. AD patients had significantly lower cognitive performance than both PD patients and the healthy elderly, as evaluated with the Mini-Mental State Examination (MMSE). Odor identification performance was significantly worse in AD and PD patients compared with the healthy elderly; AD patients performed slightly worse than PD patients, but the difference was not statistically significant. Among patients with AD, worse odor identification performance was initially correlated with atrophy of multiple cortical and deep gray matter regions known to be involved in olfactory processing, however, only two measures—decreased thicknesses of the right medial and left lateral orbitofrontal cortices—remained significant after adjustment for possible confounders (age, MMSE score, and global cortical thickness). Among patients with PD and the healthy elderly we found no similar statistically significant correlations. Our findings support the key role of the orbitofrontal cortex in odor identification among patients with AD, and suggest that correlations between impaired odor identification performance and regional gray matter atrophy may be relatively more pronounced in AD rather than in PD.

scholarly journals White Matter Microstructural Integrity and Executive Function in Parkinson's Disease

2013 ◽  
Vol 19 (3) ◽  
pp. 349-354 ◽  
Author(s):  
Catherine Gallagher ◽  
Brian Bell ◽  
Barbara Bendlin ◽  
Matthew Palotti ◽  
Ozioma Okonkwo ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Executive Function ◽  
White Matter ◽  
Diffusion Tensor ◽  
A Priori ◽  
Mean Diffusivity ◽  
Pathological Process ◽  
Intracranial Volume ◽  
Mean Values

AbstractRecent studies suggest that white matter abnormalities contribute to both motor and non-motor symptoms of Parkinson's disease. The present study was designed to investigate the degree to which diffusion tensor magnetic resonance imaging (DTI) indices are related to executive function in Parkinson's patients. We used tract-based spatial statistics to compare DTI data from 15 patients to 15 healthy, age- and education-matched controls. We then extracted mean values of fractional anisotropy (FA) and mean diffusivity (MD) within an a priori frontal mask. Executive function composite Z scores were regressed against these DTI indices, age, and total intracranial volume. In Parkinson's patients, FA was related to executive composite scores, and both indices were related to Stroop interference scores. We conclude that white matter microstructural abnormalities contribute to cognitive deficits in Parkinson's disease. Further work is needed to determine whether these white matter changes reflect the pathological process or a clinically important comorbidity. (JINS, 2013, 19, 1–6)

scholarly journals The role of brain perivascular space burden in early-stage Parkinson’s disease

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Ting Shen ◽  
Yumei Yue ◽  
Shuai Zhao ◽  
Juanjuan Xie ◽  
Yanxing Chen ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
White Matter ◽  
Early Stage ◽  
Mean Diffusivity ◽  
Perivascular Space ◽  
Motor Symptom ◽  
Imaging Features ◽  
Subcortical Nuclei ◽  
The Difference

AbstractPerivascular space (PVS) is associated with neurodegenerative diseases, while its effect on Parkinson’s disease (PD) remains unclear. We aimed to investigate the clinical and neuroimaging significance of PVS in basal ganglia (BG) and midbrain in early-stage PD. We recruited 40 early-stage PD patients and 41 healthy controls (HCs). Both PVS number and volume were calculated to evaluate PVS burden on 7 T magnetic resonance imaging images. We compared PVS burden between PD and HC, and conducted partial correlation analysis between PVS burden and clinical and imaging features. PD patients had a significantly more serious PVS burden in BG and midbrain, and the PVS number in BG was significantly correlated to the PD disease severity and L-dopa equivalent dosage. The fractional anisotropy and mean diffusivity values of certain subcortical nuclei and white matter fibers within or nearby the BG and midbrain were significantly correlated with the ipsilateral PVS burden indexes. Regarding to the midbrain, the difference between bilateral PVS burden was, respectively, correlated to the difference between fiber counts of white fiber tract passing through bilateral substantia nigra in PD. Our study suggests that PVS burden indexes in BG are candidate biomarkers to evaluate PD motor symptom severity and aid in predicting medication dosage. And our findings also highlight the potential correlations between PVS burden and both grey and white matter microstructures.

scholarly journals Mild cognitive impairment in Parkinson's disease is associated with a distributed pattern of brain white matter damage

2013 ◽  
Vol 35 (5) ◽  
pp. 1921-1929 ◽  
Author(s):  
Federica Agosta ◽  
Elisa Canu ◽  
Elka Stefanova ◽  
Lidia Sarro ◽  
Aleksandra Tomić ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
White Matter ◽  
White Matter Damage ◽  
Brain White Matter

scholarly journals Corpus Callosum and Cingulum Tractography in Parkinson's Disease

2010 ◽  
Vol 37 (5) ◽  
pp. 595-600 ◽  
Author(s):  
Katie Wiltshire ◽  
Luis Concha ◽  
Myrlene Gee ◽  
Thomas Bouchard ◽  
Christian Beaulieu ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
White Matter ◽  
Corpus Callosum ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Imaging Method ◽  
Motor Symptoms ◽  
Mri Scans

Background:In Parkinson's disease (PD) cell loss in the substantia nigra is known to result in motor symptoms; however widespread pathological changes occur and may be associated with non-motor symptoms such as cognitive impairment. Diffusion tensor imaging is a quantitative imaging method sensitive to the micro-structure of white matter tracts.Objective:To measure fractional anisotropy (FA) and mean diffusivity (MD) values in the corpus callosum and cingulum pathways, defined by diffusion tensor tractography, in patients with PD, PD with dementia (PDD) and controls and to determine if these measures correlate with Mini-Mental Status Examination (MMSE) scores in parkinsonian patients.Methods:Patients with PD (17 Males [M], 12 Females [F]), mild PDD (5 M, 1F) and controls (8 M, 7F) underwent cognitive testing and MRI scans. The corpus callosum was divided into four regions and the cingulum into two regions bilaterally to define tracts using the program DTIstudio (Johns Hopkins University) using the fiber assignment by continuous tracking algorithm. Volumetric MRI scans were used to measure white and gray matter volumes.Results:Groups did not differ in age or education. There were no overall FA or MD differences between groups in either the corpus callosum or cingulum pathways. In PD subjects the MMSE score correlated with MD within the corpus callosum. These findings were independent of age, sex and total white matter volume.Conclusions:The data suggest that the corpus callosum or its cortical connections are associated with cognitive impairment in PD patients.

scholarly journals Characterizing white matter alterations in drug-naïve de novo Parkinson’s disease with diffusion MRI

2021 ◽  
Author(s):  
Yiming Xiao ◽  
Terry M. Peters ◽  
Ali R. Khan
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
White Matter ◽  
De Novo ◽  
Neurodegenerative Disorder ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Motor Dysfunction ◽  
White Matter Integrity ◽  
Drug Naïve

AbstractParkinson’s disease (PD) is a progressive neurodegenerative disorder that is characterized by a range of motor and non-motor symptoms, often with the motor dysfunction initiated unilaterally. Knowledge regarding disease-related alterations in white matter pathways can effectively help improve the understanding of the disease and propose targeted treatment strategies. Microstructural imaging techniques, including diffusion tensor imaging (DTI), allows inspection of white matter integrity to study the pathogenesis of various neurological conditions. Previous voxel-based analyses with DTI measures, such as fractional anisotropy and mean diffusivity have uncovered changes in brain regions that are associated with PD, but the conclusions were inconsistent, partially due to small patient cohorts and the lack of consideration for clinical laterality onset, particularly in early PD. Fixel-based analysis (FBA) is a recent framework that offers tract-specific insights regarding white matter health, but very few FBA studies on PD exist. We present a study that reveals strengthened and weakened white matter integrity that is subject to symptom laterality in a large drug-naïve de novo PD cohort using complementary DTI and FBA measures. The findings suggest that the disease gives rise to both functional degeneration and the creation of compensatory networks in the early stage.

scholarly journals Alterations of white matter abnormalities in Parkinson’s disease: a machine learning approach

2021 ◽  
Author(s):  
long qian ◽  
chaoyong xiao ◽  
Sidong Liu ◽  
zaixu cui ◽  
xiao hu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
White Matter ◽  
Rating Scale ◽  
Mean Diffusivity ◽  
Learning Approach ◽  
Healthy Controls ◽  
White Matter Tracts ◽  
Machine Learning Approach

Abstract The inter-tract/region dependencies of white-matter in Parkinson’s disease are usually ignored by standard statistical tests. Moreover, it remains unclear whether the disruption of white-matter tracts/regions suffices to identify Parkinson’s disease patients from healthy controls. A machine learning approach was applied to capture the interdependencies between white-matter tracts/regions and to differentiate PD patients from healthy controls. First, the mean regional white-matter profiles, including white-matter volume, fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity, were extracted as features in Parkinson’s disease patients (N = 78) and in healthy controls (N = 91). Then, the feature selection and classification were performed using t-test and linear support vector machine, respectively. Last, the relationships between clinical variables and regional magnetic resonance indices were estimated. Our results showed the combined features (white-matter volume, fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity) had the best performance with an accuracy of 75.15% and area under curve of 0.8171, respectively. The most discriminative white-matter features were centered on the association fibers, commissural fibers, projection fibers, and striatal fibers. The discriminative regions of right anterior limb of internal capsule had positive association trends with the Unified Parkinson Disease Rating Scale III score; while the genu of corpus callosum and right retrolenticular part of internal capsule had positively association trends with the Hamilton Depression Rating Scale score. Our finding showed the multivariate machine learning approach is a promising tool to detect abnormal white-matter tracts/regions in Parkinson’s disease, and provides us a multidimensional means for neuroimaging classification.

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