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Structural and functional connectivity assessment in patients with Parkinson's disease
Klobušiaková, Patrícia ; Keller, Jiří (oponent) ; Mekyska, Jiří (vedoucí práce)
Early changes in visuospatial functions predict dementia in Parkinson’s disease (PD). The aim of this work is to assess both structural and functional connectivity of the fasciculus longitudinalis inferior (ILF), which is engaged in visuospatial processing, in PD patients in comparison to healthy controls, and to find associations between connectivity changes and cognitive performance in the patient groups with or without mild cognitive impairment (MCI). To achieve our goal we recruited PD patients with normal cognition (PD-NC, n = 23) and PD with MCI (PD-MCI, n = 21) as well as healthy controls (HC, n = 48). Bidirectional iterative parcellation was used to isolate ILF tracts and their respective endpoints (occipital lobe and anterior temporal lobe) in each subject. The endpoints then served as regions of interest for functional connectivity calculation. We found ILF microstructural connectivity impairment in PD-MCI group, as measured by mean diffusivity, fractional anisotropy and radial diffusivity. In addition, the functional connectivity of ILF tracts was decreased already in the PD-NC. Both structural and functional connectivity deterioration was associated with visuospatial dysfunction in PD-MCI. These changes could serve as potential markers of disease progression or treatment effects monitoring.
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Functional connectivity and brain structure assessment in patients at risk of synucleinopathies
Klobušiaková, Patrícia ; Gajdoš, Martin (oponent) ; Mekyska, Jiří (vedoucí práce)
Synucleinopathy is a neurodegenerative disorder characterized by the presence of pathological protein -synuclein in neurons. So far, treatment that could heal or permanently stop this disease is not known. The aim of this work is to identify prodromal stages of synucleinopathies using functional connectivity processed applying graph metrics and assessing cortical thickness and subcortical structures volumes from magnetic resonance imaging data, and to verify specificity and sensitivity of combinations of parameters that sufficiently differentiate patients in risk of synucleinopathies. To accomplish this goal, we collected data from patients in the risk of synucleinopathy (preDLB, n = 27) and healthy controls (HC, n = 28). We found reduced volume of right pallidum and increased hippocampal volume to cortical volume ratio, increased normalised clustering coefficient and higher modularity in the preDLB group in comparison to HC. These four parameters were modeled using machine learning. The resulting model differentiated preDLB and HC with balanced accuracy of 88 %, specificity of 89 % and sensitivity of 86 %. The findings of this thesis can serve as the basis for further studies searching for specific MRI markers of prodromal stage of synucleinopathy that could be targeted with therapy in the future.
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Functional connectivity and brain structure assessment in patients at risk of synucleinopathies
Klobušiaková, Patrícia ; Gajdoš, Martin (oponent) ; Mekyska, Jiří (vedoucí práce)
Synucleinopathy is a neurodegenerative disorder characterized by the presence of pathological protein -synuclein in neurons. So far, treatment that could heal or permanently stop this disease is not known. The aim of this work is to identify prodromal stages of synucleinopathies using functional connectivity processed applying graph metrics and assessing cortical thickness and subcortical structures volumes from magnetic resonance imaging data, and to verify specificity and sensitivity of combinations of parameters that sufficiently differentiate patients in risk of synucleinopathies. To accomplish this goal, we collected data from patients in the risk of synucleinopathy (preDLB, n = 27) and healthy controls (HC, n = 28). We found reduced volume of right pallidum and increased hippocampal volume to cortical volume ratio, increased normalised clustering coefficient and higher modularity in the preDLB group in comparison to HC. These four parameters were modeled using machine learning. The resulting model differentiated preDLB and HC with balanced accuracy of 88 %, specificity of 89 % and sensitivity of 86 %. The findings of this thesis can serve as the basis for further studies searching for specific MRI markers of prodromal stage of synucleinopathy that could be targeted with therapy in the future.
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Connectivity Between Brain Networks Dynamically Reflects Cognitive Status Of Parkinson’S Disease
Klobušiaková, Patrícia
Parkinson’s disease patients display a less efficient transfer of information globally and reduced between-network connectivity of large-scale brain networks as compared to healthy controls. Between-network connectivity increases with worse cognitive status, reflecting compensatory efforts. This pattern is observed in the results of each complementary method applied: seed-based between-network connectivity analysis, partial least squares analysis and graph theory measures analysis. Longitudinal studies with longer follow-up periods might show whether distinct internetwork connectivity patterns may predict dementia conversion in Parkinson’s disease.
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Structural and functional connectivity assessment in patients with Parkinson's disease
Klobušiaková, Patrícia ; Keller, Jiří (oponent) ; Mekyska, Jiří (vedoucí práce)
Early changes in visuospatial functions predict dementia in Parkinson’s disease (PD). The aim of this work is to assess both structural and functional connectivity of the fasciculus longitudinalis inferior (ILF), which is engaged in visuospatial processing, in PD patients in comparison to healthy controls, and to find associations between connectivity changes and cognitive performance in the patient groups with or without mild cognitive impairment (MCI). To achieve our goal we recruited PD patients with normal cognition (PD-NC, n = 23) and PD with MCI (PD-MCI, n = 21) as well as healthy controls (HC, n = 48). Bidirectional iterative parcellation was used to isolate ILF tracts and their respective endpoints (occipital lobe and anterior temporal lobe) in each subject. The endpoints then served as regions of interest for functional connectivity calculation. We found ILF microstructural connectivity impairment in PD-MCI group, as measured by mean diffusivity, fractional anisotropy and radial diffusivity. In addition, the functional connectivity of ILF tracts was decreased already in the PD-NC. Both structural and functional connectivity deterioration was associated with visuospatial dysfunction in PD-MCI. These changes could serve as potential markers of disease progression or treatment effects monitoring.
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Effect Of Intensive Dance-Exercise Intervention
On Brain Plasticity In Healthy Seniors And
Patients With Mild Cognitive Impairment
Klobušiaková, Patrícia
Intensive dance-exercise intervention leads to cortical thickening in the inferior temporal and lateral occipital cortices of the right hemisphere that are engaged in the ventral visual pathway; and to the increase in resting-state functional connectivity within the frontoparietal control network, i.e. the cognitive brain network that controls visual attention tasks. Subjects undergoing an active intervention improved in the five-point task that evaluates particularly executive functions. These findings show that 6-month intensive non-pharmacological intervention may enhance distinct brain plasticity and executive functions in a mixed cohort of healthy seniors and patients with mild cognitive impairment. Further longitudinal studies should examine whether it may also prevent/postpone cognitive decline and dementia in this population.
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