Patterns of white matter degeneration in remote brain areas from the basal ganglion lesion of ischemic stroke patients with motor impairment

Abstract Background: Diffusion tensor imaging (DTI) studies have revealed distinct white matter characteristics of the brain following diseases. Beyond the lesion-symptom mapping, recent studies have demonstrated extensive structural and functional alterations of remote areas to local lesions caused by stroke in the brain. Here, we further investigated the structural changes from a global level using DTI data through multivariate pattern analysis (MVPA) and network-based statistic (NBS). Methods: Ten ischemic stroke patients with basal ganglia lesions and motor dysfunctions and eleven demographically matched adults as controls underwent brain Magnetic Resonance Imaging scans. DTI data were processed to obtain fractional anisotropy (FA) maps and MVPA was used to explore brain regions that play an important role in classification based on FA maps. The white matter (WM) structural network was constructed by the deterministic fiber tracking approach according to the Automated Anatomical Labeling (AAL) atlas. NBS was used to explore differences in structural networks between groups.Results: MVPA applied to FA images correctly identified stroke patients with a statistically significant accuracy of 100% (P≤0.001). Compared with the controls, the study patients showed FA reductions in the perilesional basal ganglia and brainstem, with a few showing reductions in bilateral frontal lobes. Using NBS, we found a significant decrease in FA-weighted WM subnetwork in stroke patients. Conclusions: We identified some patterns of WM degeneration affecting brain areas remote to the ischemic lesion, revealing the abnormal organization of WM network in stroke patients, which may be helpful for the understanding of the neural mechanisms of stroke sequela.

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Patterns of white matter degeneration in remote brain areas from the basal ganglion lesion of ischemic stroke patients with motor impairment

10.21203/rs.3.rs-36124/v3 ◽

2020 ◽

Author(s):

xuejin cao ◽

Zan Wang ◽

Xiaohui Chen ◽

Yanli Liu ◽

Wei Wang ◽

...

Keyword(s):

Ischemic Stroke ◽

White Matter ◽

Basal Ganglia ◽

Structural Changes ◽

Diffusion Tensor ◽

Brain Magnetic Resonance Imaging ◽

Stroke Patients ◽

Brain Areas ◽

Ischemic Lesion ◽

The Brain

Abstract Background: Diffusion tensor imaging (DTI) studies have revealed distinct white matter characteristics of the brain following diseases. Beyond the lesion-symptom mapping, recent studies have demonstrated extensive structural and functional alterations of remote areas to local lesions caused by stroke in the brain. Here, we further investigated the structural changes from a global level using DTI data through multivariate pattern analysis (MVPA) and network-based statistic (NBS). Methods: Ten ischemic stroke patients with basal ganglia lesions and motor dysfunctions and eleven demographically matched adults as controls underwent brain Magnetic Resonance Imaging scans. DTI data were processed to obtain fractional anisotropy (FA) maps and MVPA was used to explore brain regions that play an important role in classification based on FA maps. The white matter (WM) structural network was constructed by the deterministic fiber tracking approach according to the Automated Anatomical Labeling (AAL) atlas. NBS was used to explore differences in structural networks between groups. Results: MVPA applied to FA images correctly identified stroke patients with a statistically significant accuracy of 100% (P≤0.001). Compared with the controls, the study patients showed FA reductions in the perilesional basal ganglia and brainstem, with a few showing reductions in bilateral frontal lobes. Using NBS, we found a significant decrease in FA-weighted WM subnetwork in stroke patients. Conclusions: We identified some patterns of WM degeneration affecting brain areas remote to the ischemic lesion, revealing the abnormal organization of WM network in stroke patients, which may be helpful for the understanding of the neural mechanisms of stroke sequela.

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Pattern of white matter degeneration in remote brain areas from the basal ganglion lesion of ischemic stroke patients with motor impairment

10.21203/rs.3.rs-36124/v1 ◽

2020 ◽

Author(s):

xuejin cao ◽

Zan Wang ◽

Xiaohui Chen ◽

Yanli Liu ◽

Xi Yang ◽

...

Keyword(s):

Ischemic Stroke ◽

White Matter ◽

Basal Ganglia ◽

Diffusion Tensor ◽

Brain Magnetic Resonance Imaging ◽

Motor Dysfunction ◽

Stroke Patients ◽

Brain Areas ◽

Ischemic Lesion ◽

Structural Network

Abstract Background Diffusion tensor imaging (DTI) studies have revealed distinct white matter characteristic of brain following diseases. Beyond the lesion-symptom mapping, recent studies have demonstrate extensive structural and functional alterations of remote areas to local lesions caused by stroke in the brain. Here, we investigated the influences further from a global level by multivariate pattern analysis (MVPA) and network-based statistic (NBS). Methods Ten ischemic stroke patients with basal ganglia lesion and motor dysfunction and eleven demographically matched adults underwent brain Magnetic Resonance Imaging scans. DTI data was processed to obtain fractional anisotropy (FA) map and MVPA was used to explore brain regions that play an important role in classification based on FA map. White matter (WM) structural network was constructed by the deterministic fiber tracking approach according to the Automated Anatomical Labeling (AAL) atlas. NBS was used to explore differences of structural network between groups. Results MVPA applied to FA images correctly identified stroke patients with a statistically significant accuracy of 100% (P ≤ 0.001). Compared with the controls, the patients showed an FA reduction in the perilesional basal ganglia and brainstem, with a few in bilateral frontal lobes. Using NBS, we found the significant decreased FA-weighted WM subnetwork in stroke patients. Conclusions We identified some patterns of WM degeneration in the affected brain areas remote from the ischemic lesion, revealed the abnormal topological organization of WM network in stroke patients, which may be helpful for understanding of the neural mechanism of stroke sequela.

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White matter degeneration in remote brain areas of stroke patients with motor impairment due to basal ganglia lesions

10.21203/rs.3.rs-36124/v4 ◽

2021 ◽

Author(s):

Xuejin Cao ◽

Zan Wang ◽

Xiaohui Chen ◽

Yanli Liu ◽

Wei Wang ◽

...

Keyword(s):

White Matter ◽

Basal Ganglia ◽

Structural Changes ◽

Diffusion Tensor ◽

Motor Impairment ◽

Brain Regions ◽

Stroke Patients ◽

Brain Areas ◽

Structural Network ◽

Multivariate Pattern

Abstract Diffusion tensor imaging (DTI) studies have revealed distinct white matter characteristics of the brain following diseases. Beyond the lesion-symptom maps, stroke is characterized by extensive structural and functional alterations of brain areas remote to local lesions. Here, we further investigated the structural changes over a global level by using DTI data of ten ischemic stroke patients showing motor impairment due to basal ganglia lesions and 11 healthy controls. DTI data were processed to obtain fractional anisotropy (FA) maps, and multivariate pattern analysis (MVPA) was used to explore brain regions that play an important role in classification based on FA maps. The white matter (WM) structural network was constructed by the deterministic fiber-tracking approach. In comparison with the controls, the stroke patients showed FA reductions in the perilesional basal ganglia, brainstem, and bilateral frontal lobes. Using network-based statistics (NBS), we found a significant reduction in the WM subnetwork in stroke patients. We identified the patterns of WM degeneration affecting brain areas remote to the lesions, revealing the abnormal organization of the structural network in stroke patients, which may be helpful in understanding of the neural mechanisms underlying hemiplegia.

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Abstract P64: Longitudinal Brain Structural Changes After Stroke

Stroke ◽

10.1161/str.52.suppl_1.p64 ◽

2021 ◽

Vol 52 (Suppl_1) ◽

Author(s):

Kyle C Kern ◽

Clinton B Wright ◽

Richard Leigh

Keyword(s):

Ischemic Stroke ◽

White Matter ◽

Stroke Volume ◽

Brain Atrophy ◽

Structural Changes ◽

Diffusion Tensor ◽

Brain Mri ◽

Mean Diffusivity ◽

Intracranial Volume ◽

Post Stroke

Background: Stroke causes focal and diffuse structural brain changes that may contribute to subsequent cognitive decline and dementia. We hypothesize that MRI structural measures can detect continued cerebral degeneration over the first year after stroke. We identify predictors for progression of brain atrophy, leukoaraiosis and diffusion tensor imaging (DTI) metrics. Methods: Patients with ischemic stroke were enrolled prospectively in an observational study that included serial brain MRI. Patients underwent MRI FLAIR and DTI at the time of acute stroke and were followed for at least 9 months with multiple MRIs between 30 days and 15 months post-stroke. We used FLAIR to measure brain atrophy as the percent brain parenchymal fraction (BPF) of the total intracranial volume (TICV) and white matter hyperintensity volume (WMHV) as a percentage of TICV. DTI was used to calculate Peak Skeletonized Mean Diffusivity (PSMD), a global measure of white matter integrity previously validated in cerebral small vessel disease. Longitudinal changes in BPF, WMHV or PSMD were measured from 30 days post-stroke onward using linear regression models that included age, stroke volume, baseline BPF and WMHV as predictors. Results: Twenty-six patients had a median of 4 follow-ups over 9-15 months. Median age was 74 years (range 51-84) and 38% were women. Mean stroke volume was 4.5cc (0 - 30cc). Mean BPF was 78% (72 - 86%) and mean baseline WMHV was 1.1% (0.1 - 3.9%). BPF was associated with age and declined by 0.7% per year (t(111) = 2.7, p = 0.007). Progression was associated with baseline BPF (t(111) = -3.4, p < 0.001). WMHV in the non-stroke hemisphere was associated with age and increased by 0.10% per year (t(87) = -5.8, p < 0.001). Accumulation was associated with age (t(87) = 5.8, p < 0.001). PSMD was associated with baseline WMHV and had a relative increase of 1.9% per year in the non-stroke hemisphere and 4.5% in the stroke hemisphere (t(174) = -2.1, p = 0.03). Progression was associated with age (t(174) = 2.3, p = 0.03) and stroke volume (t(174) = 2.4, p = 0.02). Conclusions: During the months after ischemic stroke, BPF, WMHV and PSMD can detect persistent structural changes that may reflect later phases of stroke injury or ongoing contributions of aging, silent ischemia, or neurodegeneration.

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White matter degeneration in remote brain areas of stroke patients with motor impairment due to basal ganglia lesions

Human Brain Mapping ◽

10.1002/hbm.25583 ◽

2021 ◽

Author(s):

Xuejin Cao ◽

Zan Wang ◽

Xiaohui Chen ◽

Yanli Liu ◽

Wei Wang ◽

...

Keyword(s):

White Matter ◽

Basal Ganglia ◽

Motor Impairment ◽

Stroke Patients ◽

Brain Areas ◽

White Matter Degeneration

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DTI Study on Brain Structure and Cognitive Function in Patients with Chronic Mountain Sickness

Scientific Reports ◽

10.1038/s41598-019-55498-9 ◽

2019 ◽

Vol 9 (1) ◽

Author(s):

Haihua Bao ◽

Ruiyang Li ◽

Mingli He ◽

Dongjie Kang ◽

Lili Zhao

Keyword(s):

Cognitive Function ◽

Structural Changes ◽

Diffusion Tensor ◽

Blood Stasis ◽

Brain Magnetic Resonance Imaging ◽

Chronic Mountain Sickness ◽

Adc Value ◽

Adc Values ◽

Mountain Sickness ◽

The Brain

AbstractIn chronic mountain sickness (CMS) patients, the structure of the brain, memory and cognition are often irreversibly damaged by chronic hypoxia due to red blood cell overcompensation, elevated haemoglobin and blood stasis. In this study, we aimed to evaluate this damage using diffusion tensor imaging (DTI) and to study the correlations among the fractional anisotropy (FA),the apparent diffusion coefficient (ADC) value, the severity index of CMS and the simple Mental State Examination (MMSE) score in CMS patients. A total of 17 patients with CMS and 15 healthy controls were recruited for conventional brain magnetic resonance imaging (MRI) and DTI scans, and ADC images were reconstructed along with FA and FA colour maps. The FA and ADC values of the selected regions of interest (ROIs) were measured and compared. The FA and ADC values were also compared with the haemoglobin (Hb) and MMSE scores. CMS patients are prone to intracranial ischaemia, infarction and haemorrhage. Multiple structural changes occur in the brain of CMS patients, and these changes are related to the severity of the disease and cognitive function variation. The white matter fibre bundles of CMS patients showed no obvious damage, except in the ischaemic site.

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Longitudinal Structural and Functional Differences Between Proportional and Poor Motor Recovery After Stroke

Neurorehabilitation and Neural Repair ◽

10.1177/1545968317740634 ◽

2017 ◽

Vol 31 (12) ◽

pp. 1029-1041 ◽

Cited By ~ 21

Author(s):

Adrian G. Guggisberg ◽

Pierre Nicolo ◽

Leonardo G. Cohen ◽

Armin Schnider ◽

Ethan R. Buch

Keyword(s):

White Matter ◽

Structural Changes ◽

Primary Motor Cortex ◽

Diffusion Tensor ◽

Motor Recovery ◽

Brain Organization ◽

Fiber Tracts ◽

Functional Differences ◽

Eeg Functional Connectivity ◽

The Brain

Background. Evolution of motor function during the first months after stroke is stereotypically bifurcated, consisting of either recovery to about 70% of maximum possible improvement (“proportional recovery, PROP”) or in little to no improvement (“poor recovery, POOR”). There is currently no evidence that any rehabilitation treatment will prevent POOR and favor PROP. Objective. To perform a longitudinal and multimodal assessment of functional and structural changes in brain organization associated with PROP. Methods. Fugl-Meyer Assessments of the upper extremity and high-density electroencephalography (EEG) were obtained from 63 patients, diffusion tensor imaging from 46 patients, at 2 and 4 weeks (T0) and at 3 months (T1) after stroke onset. Results. We confirmed the presence of 2 distinct recovery patterns (PROP and POOR) in our sample. At T0, PROP patients had greater integrity of the corticospinal tract (CST) and greater EEG functional connectivity (FC) between the affected hemisphere and rest of the brain, in particular between the ventral premotor and the primary motor cortex. POOR patients suffered from degradation of corticocortical and corticofugal fiber tracts in the affected hemisphere between T0 and T1, which was not observed in PROP patients. Better initial CST integrity correlated with greater initial global FC, which was in turn associated with less white matter degradation between T0 and T1. Conclusions. These findings suggest links between initial CST integrity, systems-level cortical network plasticity, reduction of white matter atrophy, and clinical motor recovery after stroke. This identifies candidate treatment targets.

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Characterization of Ischemic Stroke in CT Images using Image Processing

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i9.405 ◽

2017 ◽

Vol 7 (9) ◽

pp. 18

Author(s):

Amal Alzain ◽

Suhaib Alameen ◽

Rani Elmaki ◽

Mohamed E. M. Gar-Elnabi

Keyword(s):

Ischemic Stroke ◽

White Matter ◽

Classification Accuracy ◽

Ct Images ◽

Gray Level ◽

Level Variation ◽

Interactive Data ◽

The Brain ◽

Brain Tissues

This study concern to characterize the brain tissues to ischemic stroke, gray matter, white matter and CSF using texture analysisto extract classification features from CT images. The First Order Statistic techniques included sevenfeatures. To find the gray level variation in CT images it complements the FOS features extracted from CT images withgray level in pixels and estimate the variation of thesubpatterns. analyzing the image with Interactive Data Language IDL software to measure the grey level of images. The results show that the Gray Level variation and features give classification accuracy of ischemic stroke 97.6%, gray matter95.2%, white matter 97.3% and the CSF classification accuracy 98.0%. The overall classification accuracy of brain tissues 97.0%.These relationships are stored in a Texture Dictionary that can be later used to automatically annotate new CT images with the appropriate brain tissues names.

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

10.31234/osf.io/ukgyr ◽

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.

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