12 research outputs found

    Diffusion imaging markers of cerebral small vessel disease

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    Diffusion magnetic resonance imaging (MRI) is widely used as a research tool to assess (subtle) alterations of the cerebral white matter. Measures derived from diffusion MRI appear to be valuable markers for cerebral small vessel disease (SVD). However, SVD is frequently co-occurring with Alzheimer’s disease (AD), and disturbed white matter integrity and altered diffusion measures are considered key findings in both conditions. Yet, the contribution of SVD and AD to diffusion alterations is unclear, which hampers the interpretation of research studies in patients with mixed disease, e.g. memory clinic patients. Study 1 of this thesis aimed to clarify the effect of SVD and AD on diffusion measures by including multiple (memory clinic) samples covering the entire spectrum of SVD, mixed disease, and AD. We calculated diffusion measures from diffusion tensor imaging (DTI) and free water imaging. Within each sample of the disease spectrum, we applied simple regression analyses and multivariable random forest analyses between AD biomarkers (amyloid-beta, tau), conventional MRI markers of SVD, and global diffusion measures. Furthermore, we investigated regional associations between tau on positron emission tomography (PET) and diffusion measures in voxel-wise analyses. Our main findings are that conventional MRI markers of SVD were strongly associated with diffusion measures and showed a higher contribution than AD biomarkers in multivariable analyses across all memory clinic samples. Regional analyses between tau PET and diffusion measures were not significant. We conclude that SVD rather than AD determines diffusion alterations in memory clinic patients. Our findings validate diffusion measures as markers for SVD. Study 2 applied diffusion MRI markers to study gait impairment in SVD. Gait impairment is a commonly reported clinical deficit in SVD patients, but the underlying mechanisms are still debated. The proposed mechanisms include SVD-related white matter alterations resulting in impaired supraspinal locomotor control, cognitive deficits (e.g. planning and execution of movements), and factors independent of SVD, such as age-related instability (e.g. joint wear, sarcopenia) and comorbidities (e.g. neurodegenerative pathology). A reason for the lack of knowledge on gait impairment in SVD is that studies in elderly, sporadic SVD patients are typically confounded by effects of normal-aging and age-related comorbidities. Therefore, Study 2 of this thesis aimed to study the effect of pure SVD on gait performance in a relatively young sample of genetically defined SVD patients without age-related confounding. We performed comprehensive gait assessment using an electronic walkway to obtain multiple spatio-temporal gait parameters standardized based on data from healthy controls. Importantly, we tested the association between diffusion MRI markers of SVD-related white matter alterations and gait performance, since (strategic) white matter alterations are discussed as a major cause of gait decline in the elderly. Furthermore, we assessed the relation between cognitive deficits and gait performance. Our main finding is that, despite severe white matter alterations in pure SVD patients, gait performance was relatively preserved. Cognitive deficits in our study participants were not related to gait impairment. Thus, our results query isolated white matter alterations, in the absence of comorbidities, as a main factor of gait impairment in SVD and suggest that their combination with age-related comorbidities and/or normal-aging may play a crucial role in gait decline. In conclusion, diffusion measures are valid MRI markers of SVD-related white matter alterations. They have significant value both in future research on altered white matter and potentially also in the diagnostic work-up of memory clinic patients, to differentiate between vascular and neurodegenerative disease. Researchers may select target populations for clinical trials based on diffusion measures, e.g. to identify patients with a low SVD burden as targets for prevention and early intervention in SVD. Clinicians and researchers should always consider SVD as the origin of diffusion alterations in patients with mixed pathology. The field of application of diffusion measures is wide and may provide new insights into effects of subtle white matter alterations on clinical deficits, as shown in Study 2 on gait impairment in pure SVD. Future studies should investigate measures from advanced diffusion models and diffusion-based brain network analysis, to further elucidate the mechanisms of clinical deficits in SVD patients

    Diffusion imaging markers of cerebral small vessel disease

    Get PDF
    Diffusion magnetic resonance imaging (MRI) is widely used as a research tool to assess (subtle) alterations of the cerebral white matter. Measures derived from diffusion MRI appear to be valuable markers for cerebral small vessel disease (SVD). However, SVD is frequently co-occurring with Alzheimer’s disease (AD), and disturbed white matter integrity and altered diffusion measures are considered key findings in both conditions. Yet, the contribution of SVD and AD to diffusion alterations is unclear, which hampers the interpretation of research studies in patients with mixed disease, e.g. memory clinic patients. Study 1 of this thesis aimed to clarify the effect of SVD and AD on diffusion measures by including multiple (memory clinic) samples covering the entire spectrum of SVD, mixed disease, and AD. We calculated diffusion measures from diffusion tensor imaging (DTI) and free water imaging. Within each sample of the disease spectrum, we applied simple regression analyses and multivariable random forest analyses between AD biomarkers (amyloid-beta, tau), conventional MRI markers of SVD, and global diffusion measures. Furthermore, we investigated regional associations between tau on positron emission tomography (PET) and diffusion measures in voxel-wise analyses. Our main findings are that conventional MRI markers of SVD were strongly associated with diffusion measures and showed a higher contribution than AD biomarkers in multivariable analyses across all memory clinic samples. Regional analyses between tau PET and diffusion measures were not significant. We conclude that SVD rather than AD determines diffusion alterations in memory clinic patients. Our findings validate diffusion measures as markers for SVD. Study 2 applied diffusion MRI markers to study gait impairment in SVD. Gait impairment is a commonly reported clinical deficit in SVD patients, but the underlying mechanisms are still debated. The proposed mechanisms include SVD-related white matter alterations resulting in impaired supraspinal locomotor control, cognitive deficits (e.g. planning and execution of movements), and factors independent of SVD, such as age-related instability (e.g. joint wear, sarcopenia) and comorbidities (e.g. neurodegenerative pathology). A reason for the lack of knowledge on gait impairment in SVD is that studies in elderly, sporadic SVD patients are typically confounded by effects of normal-aging and age-related comorbidities. Therefore, Study 2 of this thesis aimed to study the effect of pure SVD on gait performance in a relatively young sample of genetically defined SVD patients without age-related confounding. We performed comprehensive gait assessment using an electronic walkway to obtain multiple spatio-temporal gait parameters standardized based on data from healthy controls. Importantly, we tested the association between diffusion MRI markers of SVD-related white matter alterations and gait performance, since (strategic) white matter alterations are discussed as a major cause of gait decline in the elderly. Furthermore, we assessed the relation between cognitive deficits and gait performance. Our main finding is that, despite severe white matter alterations in pure SVD patients, gait performance was relatively preserved. Cognitive deficits in our study participants were not related to gait impairment. Thus, our results query isolated white matter alterations, in the absence of comorbidities, as a main factor of gait impairment in SVD and suggest that their combination with age-related comorbidities and/or normal-aging may play a crucial role in gait decline. In conclusion, diffusion measures are valid MRI markers of SVD-related white matter alterations. They have significant value both in future research on altered white matter and potentially also in the diagnostic work-up of memory clinic patients, to differentiate between vascular and neurodegenerative disease. Researchers may select target populations for clinical trials based on diffusion measures, e.g. to identify patients with a low SVD burden as targets for prevention and early intervention in SVD. Clinicians and researchers should always consider SVD as the origin of diffusion alterations in patients with mixed pathology. The field of application of diffusion measures is wide and may provide new insights into effects of subtle white matter alterations on clinical deficits, as shown in Study 2 on gait impairment in pure SVD. Future studies should investigate measures from advanced diffusion models and diffusion-based brain network analysis, to further elucidate the mechanisms of clinical deficits in SVD patients

    Minor gait impairment despite white matter damage in pure small vessel disease

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    Objective Gait impairment is common in patients with cerebral small vessel disease (SVD). However, gait studies in elderly SVD patients might be confounded by age‐related comorbidities, such as polyneuropathy or sarcopenia. We therefore studied young patients with the genetically defined SVD CADASIL. Our aim was to examine the effects of pure SVD on single and dual task gait, and to investigate associations of gait performance with cognitive deficits and white matter alterations. Methods We investigated single task walking and calculatory, semantic, or motoric dual task costs in 39 CADASIL patients (mean age 50 ± 8) using a computerized walkway. We obtained 3.0T MRI and neuropsychological data on processing speed, the main cognitive deficit in CADASIL. Spatiotemporal gait parameters were standardized based on data from 192 healthy controls. Associations between white matter integrity, assessed by diffusion tensor imaging, and gait were analyzed using both a global marker and voxel‐wise analysis. Results Compared to controls, CADASIL patients showed only mild single task gait impairment, and only in the rhythm domain. The semantic dual task additionally uncovered mild deficits in the pace domain. Processing speed was not associated with gait. White matter alterations were related to single task stride length but not to dual task performance. Interpretation Despite severe disease burden, gait performance in patients with pure small vessel disease was relatively preserved in single and dual tasks. Results suggest that age‐related pathologies other than small vessel disease might play a role for gait impairment in elderly SVD patients

    Alterations and test-retest reliability of functional connectivity network measures in cerebral small vessel disease

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    While structural network analysis consolidated the hypothesis of cerebral small vessel disease (SVD) being a disconnection syndrome, little is known about functional changes on the level of brain networks. In patients with genetically defined SVD (CADASIL,n= 41) and sporadic SVD (n= 46), we independently tested the hypothesis that functional networks change with SVD burden and mediate the effect of disease burden on cognitive performance, in particular slowing of processing speed. We further determined test-retest reliability of functional network measures in sporadic SVD patients participating in a high-frequency (monthly) serial imaging study (RUN DMC-InTENse, median: 8 MRIs per participant). Functional networks for the whole brain and major subsystems (i.e., default mode network, DMN;fronto-parietal task control network, FPCN;visual network, VN;hand somatosensory-motor network, HSMN) were constructed based on resting-state multi-band functional MRI. In CADASIL, global efficiency (a graph metric capturing network integration) of the DMN was lower in patients with high disease burden (standardized beta = -.44;p[corrected] = .035) and mediated the negative effect of disease burden on processing speed (indirect path: std. beta = -.20,p= .047;direct path: std. beta = -.19,p= .25;total effect: std. beta = -.39,p= .02). The corresponding analyses in sporadic SVD showed no effect. Intraclass correlations in the high-frequency serial MRI dataset of the sporadic SVD patients revealed poor test-retest reliability and analysis of individual variability suggested an influence of age, but not disease burden, on global efficiency. In conclusion, our results suggest that changes in functional connectivity networks mediate the effect of SVD-related brain damage on cognitive deficits. However, limited reliability of functional network measures, possibly due to age-related comorbidities, impedes the analysis in elderly SVD patients

    Deficit in feature-based attention following a left thalamic lesion

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    Selective attention enables us to prioritise the processing of relevant over irrelevant information. The model of priority maps with stored attention weights provides a conceptual framework that accounts for the visual prioritisation mechanism of selective attention. According to this model, high attention weights can be assigned to spatial locations, features, or objects. Converging evidence from neuroimaging and neuropsychological studies propose the involvement of thalamic and frontoparietal areas in selective attention. However, it is unclear whether the thalamus is critically involved in generating different types of modulatory signals for attentional selection. The aim of the current study was to investigate feature- and spatial-based selection in stroke survivors with subcortical thalamic and non-thalamic lesions. A single case with a left-hemispheric lesion extending into the thalamus, five cases with right-hemispheric lesions sparing the thalamus and 34 healthy, age-matched controls participated in the study. Participants performed a go/no-go task on task-relevant stimuli, while ignoring simultaneously presented task-irrelevant stimuli. Stimulus relevance was determined by colour or spatial location. The thalamic lesion case was specifically impaired in feature-based selection but not in spatial-based selection, whereas performance of non-thalamic lesion patients was similar to controls' performance in both types of selective attention. In summary, our thalamic lesion case showed difficulties in computing differential attention weights based on features, but not based on spatial locations. The results suggest that different modulatory signals are generated mediating attentional selection for features versus space in the thalamus.status: publishe

    Alterations and test–retest reliability of functional connectivity network measures in cerebral small vessel disease

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    While structural network analysis consolidated the hypothesis of cerebral small vessel disease (SVD) being a disconnection syndrome, little is known about functional changes on the level of brain networks. In patients with genetically defined SVD (CADASIL, n = 41) and sporadic SVD (n = 46), we independently tested the hypothesis that functional networks change with SVD burden and mediate the effect of disease burden on cognitive performance, in particular slowing of processing speed. We further determined test-retest reliability of functional network measures in sporadic SVD patients participating in a high-frequency (monthly) serial imaging study (RUN DMC-InTENse, median: 8 MRIs per participant). Functional networks for the whole brain and major subsystems (i.e., default mode network, DMN; fronto-parietal task control network, FPCN; visual network, VN; hand somatosensory-motor network, HSMN) were constructed based on resting-state multi-band functional MRI. In CADASIL, global efficiency (a graph metric capturing network integration) of the DMN was lower in patients with high disease burden (standardized beta = -.44; p [corrected] = .035) and mediated the negative effect of disease burden on processing speed (indirect path: std. beta = -.20, p = .047; direct path: std. beta = -.19, p = .25; total effect: std. beta = -.39, p = .02). The corresponding analyses in sporadic SVD showed no effect. Intraclass correlations in the high-frequency serial MRI dataset of the sporadic SVD patients revealed poor test-retest reliability and analysis of individual variability suggested an influence of age, but not disease burden, on global efficiency. In conclusion, our results suggest that changes in functional connectivity networks mediate the effect of SVD-related brain damage on cognitive deficits. However, limited reliability of functional network measures, possibly due to age-related comorbidities, impedes the analysis in elderly SVD patients

    Small vessel disease more than Alzheimer's disease determines diffusion MRI alterations in memory clinic patients

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    Introduction: Microstructural alterations as assessed by diffusion tensor imaging (DTI) are key findings in both Alzheimer's disease (AD) and small vessel disease (SVD). We determined the contribution of each of these conditions to diffusion alterations. Methods: We studied six samples (N = 365 participants) covering the spectrum of AD and SVD, including genetically defined samples. We calculated diffusion measures from DTI and free water imaging. Simple linear, multivariable random forest, and voxel-based regressions were used to evaluate associations between AD biomarkers (amyloid beta, tau), SVD imaging markers, and diffusion measures. Results: SVD markers were strongly associated with diffusion measures and showed a higher contribution than AD biomarkers in multivariable analysis across all memory clinic samples. Voxel-wise analyses between tau and diffusion measures were not significant. Discussion: In memory clinic patients, the effect of SVD on diffusion alterations largely exceeds the effect of AD, supporting the value of diffusion measures as markers of SVD.Fil: Finsterwalder, Sofia. Ludwig Maximilians Universitat; AlemaniaFil: Vlegels, Naomi. University of Utrecht; Países BajosFil: Gesierich, Benno. Ludwig Maximilians Universitat; AlemaniaFil: Araque Caballero, Miguel Á.. Ludwig Maximilians Universitat; Alemania. German Center for Neurodegenerative Diseases; AlemaniaFil: Weaver, Nick A.. University of Utrecht; Países BajosFil: Franzmeier, Nicolai. Ludwig Maximilians Universitat; AlemaniaFil: Georgakis, Marios K.. Ludwig Maximilians Universitat; AlemaniaFil: Konieczny, Marek J.. Ludwig Maximilians Universitat; AlemaniaFil: Koek, Huiberdina L.. University of Utrecht; Países BajosFil: Karch, Celeste M.. Washington University in St. Louis; Estados UnidosFil: Graff Radford, Neill R.. Mayo Clinic In Jacksonville; Estados UnidosFil: Salloway, Stephen. Butler Hospital; Estados UnidosFil: Oh, Hwamee. University Brown; Estados UnidosFil: Allegri, Ricardo Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Chhatwal, Jasmeer P.. Harvard Medical School; Estados UnidosFil: Jessen, Frank. Universitat zu Köln; Alemania. German Center for Neurodegenerative Diseases; AlemaniaFil: Düzel, Emrah. Otto-von-Guericke-Universität Magdeburg; Alemania. German Center for Neurodegenerative Diseases; AlemaniaFil: Dobisch, Laura. Otto-von-Guericke-Universität Magdeburg; Alemania. German Center for Neurodegenerative Diseases; AlemaniaFil: Metzger, Coraline. Otto-von-Guericke-Universität Magdeburg; Alemania. German Center for Neurodegenerative Diseases; AlemaniaFil: Peters, Oliver. German Center for Neurodegenerative Diseases; Alemania. Freie Universität Berlin; AlemaniaFil: Incesoy, Enise I.. Freie Universität Berlin; AlemaniaFil: Priller, Josef. Freie Universität Berlin; Alemania. German Center for Neurodegenerative Diseases; AlemaniaFil: Spruth, Eike J.. Freie Universität Berlin; Alemania. German Center for Neurodegenerative Diseases; AlemaniaFil: Schneider, Anja. German Center for Neurodegenerative Diseases; Alemania. University Hospital Bonn; AlemaniaFil: Fließbach, Klaus. German Center for Neurodegenerative Diseases; Alemania. University Hospital Bonn; AlemaniaFil: Buerger, Katharina. Ludwig Maximilians Universitat; Alemania. German Center for Neurodegenerative Diseases; AlemaniaFil: Janowitz, Daniel. Ludwig Maximilians Universitat; AlemaniaFil: Teipel, Stefan J.. German Center for Neurodegenerative Diseases; Alemania. Rostock University Medical Center; AlemaniaFil: Kilimann, Ingo. German Center for Neurodegenerative Diseases; Alemania. Rostock University Medical Center; AlemaniaFil: Laske, Christoph. German Center for Neurodegenerative Diseases; Alemania. University of Tübingen; Alemani
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