Reclassifying stroke lesion anatomy.
Ontology highlight
ABSTRACT:
SUBMITTER: Bonkhoff AK
PROVIDER: S-EPMC8650827 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The strains, C57BL6/J, C3H/HeJ, and WSB/EiJ, show a similar collateral vessel anatomy but differ infarct volume after ischemic stroke induction. To identify a gene(s) exhibiting differential gene expression, we performed RNA seq experiment within these mouse strains.
2021-03-06 | GSE168383 | GEO
Project description:A long-held view is that stroke causes many distinct neurological syndromes due to damage of specialized cortical and subcortical centers. However, it is unknown if a syndrome-based description is helpful in characterizing behavioral deficits across a large number of patients. We studied a large prospective sample of first-time stroke patients with heterogeneous lesions at 1-2 weeks post-stroke. We measured behavior over multiple domains and lesion anatomy with structural MRI and a probabilistic atlas of white matter pathways. Multivariate methods estimated the percentage of behavioral variance explained by structural damage. A few clusters of behavioral deficits spanning multiple functions explained neurological impairment. Stroke topography was predominantly subcortical, and disconnection of white matter tracts critically contributed to behavioral deficits and their correlation. The locus of damage explained more variance for motor and language than memory or attention deficits. Our findings highlight the need for better models of white matter damage on cognition.
| S-EPMC4646844 | biostudies-literature
Project description:Background and purposeMany therapies are emerging that aim to improve motor function in people with stroke. Identifying key biological substrates needed for treatment gains would help to predict treatment effects and to maximize treatment impact. The current study addressed the hypothesis that behavioral gains from therapy targeting distal upper extremity are predicted by the structural integrity of key motor system white matter tracts.MethodsTwenty-three subjects with chronic left-sided stroke underwent robotic therapy targeting the distal right upper extremity. MRI was obtained at baseline and used to outline the infarct. For each subject, the degree to which stroke injured each of 4 descending white matter tracts (from the primary motor cortex, supplementary motor area, dorsal premotor cortex, and ventral premotor cortex, respectively) was determined. Correlations between tract-specific injury and behavioral gains from therapy were then examined.ResultsNumerous examples were found whereby tract-specific injury predicted treatment gains. The strongest correlations pertained to stroke injury to tracts descending from the primary motor cortex and dorsal premotor cortex. Infarct volume and baseline behavior were weak predictors of treatment gains.ConclusionsExtent of injury to specific motor tracts predicts behavioral gains from treatment in subjects with chronic stroke. This supports a role for these tracts in mediating treatment effects and reinforces the importance of lesion location in stroke. Tract-specific injury was stronger than infarct volume or baseline clinical status at predicting gains, identifies subjects with sufficient biological substrate to improve from therapy, and so might be useful as an entry criterion in repair-based trials.
| S-EPMC3026869 | biostudies-literature
Project description:The impact of stroke on motor functioning is analyzed at different levels. 'Impairment' denotes the loss of basic characteristics of voluntary movement. 'Activity limitation' denotes the loss of normal capacity for independent execution of daily activities. Recovery from impairment is accomplished by 'restitution' and recovery from activity limitation is accomplished by the combined effect of 'restitution' and 'compensation.' We aimed to unravel the long-term effects of variation in lesion topography on motor impairment of the hemiparetic lower limb (HLL), and gait capacity as a measure of related activity limitation. Gait was assessed by the 3 m walk test (3MWT) in 67 first-event chronic stroke patients, at their homes. Enduring impairment of the HLL was assessed by the Fugl-Meyer Lower Extremity (FMA-LE) test. The impact of variation in lesion topography on HLL impairment and on walking was analyzed separately for left and right hemispheric damage (LHD, RHD) by voxel-based lesion-symptom mapping (VLSM). In the LHD group, HLL impairment tended to be affected by damage to the posterior limb of the internal capsule (PLIC). Walking capacity tended to be affected by a larger array of structures: PLIC and corona radiata, external capsule and caudate nucleus. In the RHD group, both HLL impairment and walking capacity were sensitive to damage in a much larger number of brain voxels. HLL impairment was affected by damage to the corona radiata, superior longitudinal fasciculus and insula. Walking was affected by damage to the same areas, plus the internal and external capsules, putamen, thalamus and parts of the perisylvian cortex. In both groups, voxel clusters have been found where damage affected FMA-LE and also 3MWT, along with voxels where damage affected only one of the measures (mainly 3MWT). In stroke, enduring 'activity limitation' is affected by damage to a much larger array of brain structures and voxels within specific structures, compared to enduring 'impairment.' Differences between the effects of left and right hemisphere damage are likely to reflect variation in motor-network organization and post-stroke re-organization related to hemispheric dominance. Further studies with larger sample size are required for the validation of these results.
| S-EPMC7882502 | biostudies-literature
Project description:BACKGROUND AND PURPOSE:Similar-sized stroke lesions at similar locations can have different prognoses in clinical practice. Lesion-network mapping elucidates network-level effects of lesions that cause specific neurologic symptoms and signs, and also provides a group-level understanding. This study visualized the effects of stroke lesions on the functional brain networks of individual patients. METHODS:We enrolled patients with ischemic stroke who were hospitalized within 1 week of the stroke occurrence. Resting-state functional magnetic resonance imaging was performed 3 months after the index stroke. For image preprocessing, acute stroke lesions were visually delineated based on diffusion-weighted images obtained at admission, and the lesion mask was drawn using MRIcron software. Correlation matrices were calculated from 280 brain regions using the Brainnetome Atlas, and connectograms were visualized using in-house MATLAB code. RESULTS:We found characteristic differences in connectograms between pairs of patients who had comparable splenial, frontal cortical, cerebellar, and thalamocapsular lesions. Two representative patients with bilateral thalamic infarctions showed significant differences in their reconstructed connectograms. The cognitive function had recovered well at 3 months after stroke occurrence in patients with well-maintained interhemispheric and intrahemispheric connectivities. CONCLUSIONS:This pilot study has visualized the effects of stroke lesions on the functional brain networks of individual patients. Consideration of the neurobiologic mechanisms underlying the differences between their connectograms has yielded new hypotheses about differences in the effects of stroke lesions.
| S-EPMC6974837 | biostudies-literature
Project description:The fate of subcortical diffusion-weighted imaging (DWI) lesions in stroke patients is highly variable, ranging from complete tissue loss to no visible lesion on follow-up. Little is known about within-lesion heterogeneity and its relevance for stroke outcome. Patients with subcortical stroke and recruited through the prospective DEDEMAS study (NCT01334749) were examined at baseline (n = 45), six months (n = 45), and three years (n = 28) post-stroke. We performed high-resolution structural MRI including DWI. Tissue fate was determined voxel-wise using fully automated tissue segmentation. Within-lesion heterogeneity at baseline was assessed by free water diffusion imaging measures. The majority of DWI lesions (66%) showed cavitation on six months follow-up but the proportion of tissue turning into a cavity was small (9 ± 13.5% of the DWI lesion). On average, 69 ± 25% of the initial lesion resolved without any visually apparent signal abnormality. The extent of cavitation at six months post-stroke was independently associated with clinical outcome, i.e. modified Rankin scale score at six months (OR = 4.71, p = 0.005). DWI lesion size and the free water-corrected tissue mean diffusivity at baseline independently predicted cavitation. In conclusion, the proportion of cavitating tissue is typically small, but relevant for clinical outcome. Within-lesion heterogeneity at baseline on advanced diffusion imaging is predictive of tissue fate.
| S-EPMC7308518 | biostudies-literature
Project description:Spatial neglect is a common consequence of stroke in the territory of the right middle cerebral artery. Damage to a perisylvian fronto-temporo-parietal network has been demonstrated to underlie this disorder. Less common, stroke to the posterior cerebral artery territory may also lead to spatial neglect. This study aimed to uncover the anatomical underpinnings of spatial neglect after posterior cerebral artery infarction. A sample of 50 posterior cerebral artery infarct patients was screened for spatial neglect. Neural correlates of neglect were investigated both with voxel-based lesion behaviour mapping and with region-of-interest analyses. Brain damage neither to the splenium, nor to the parahippocampal gyrus, nor to the thalamus was predictive of spatial neglect. Only damage to the perisylvian fronto-temporo-parietal network of spatial neglect was significantly associated with neglect severity. We conclude that both posterior and middle cerebral artery stroke induce spatial neglect after damage to the same perisylvian brain network. The findings contradict previous theories that postulated neural correlates of spatial neglect specifically supplied by the posterior cerebral artery. In posterior cerebral artery stroke patients, affected parts of this network are located at the border zone between the posterior and middle cerebral artery territories. Inter-individual variability in the localization of the border between both artery territories appears to mediate the occurrence of spatial neglect after posterior cerebral artery stroke.
| S-EPMC7846084 | biostudies-literature
Project description:Inference of etiology from lesion pattern in acute magnetic resonance imaging is valuable for management and prognosis of acute stroke patients. This study aims to assess the value of three-dimensional geometrical lesion-shape descriptors for stroke-subtype classification, specifically regarding stroke of cardioembolic origin.Stroke Etiology was classified according to ASCOD in retrospectively selected patients with acute stroke. Lesions were segmented on diffusion-weighed datasets, and descriptors of lesion shape quantified: surface area, sphericity, bounding box volume, and ratio between bounding box and lesion volume. Morphological measures were compared between stroke subtypes classified by ASCOD and between patients with embolic stroke of cardiac and non-cardiac source.150 patients (mean age 77 years; 95% CI, 65-80 years; median NIHSS 6, range 0-22) were included. Group comparison of lesion shape measures demonstrated that lesions caused by small-vessel disease were smaller and more spherical compared to other stroke subtypes. No significant differences of morphological measures were detected between patients with cardioembolic and non-cardioembolic stroke.Stroke lesions caused by small vessel disease can be distinguished from other stroke lesions based on distinctive morphological properties. However, within the group of embolic strokes, etiology could not be inferred from the morphology measures studied in our analysis.
| S-EPMC5720627 | biostudies-literature
Project description:Morphologic evolution of recent small subcortical infarcts (RSSI) ranges from lesion disappearance to lacune formation and the reasons for this variability are still poorly understood. We hypothesized that diffusion tensor imaging (DTI) and blood-brain-barrier (BBB) abnormalities early on can predict tissue damage 1 year after an RSSI. We studied prospectively recruited patients with a symptomatic MRI-defined RSSI who underwent baseline and two pre-specified MRI examinations at 1-3-month and 1-year post-stroke. We defined the extent of long-term tissue destruction, termed cavitation index, as the ratio of the 1-year T1-weighted cavity volume to the baseline RSSI volume on FLAIR. We calculated fractional anisotropy and mean diffusivity (MD) of the RSSI and normal-appearing white matter, and BBB leakage in different tissues on dynamic contrast-enhanced MRI. Amongst 60 patients, at 1-year post-stroke, 44 patients showed some degree of RSSI cavitation on FLAIR, increasing to 50 on T2- and 56 on T1-weighted high-resolution scans, with a median cavitation index of 7% (range, 1-36%). Demographic, clinical, and cerebral small vessel disease features were not associated with the cavitation index. While lower baseline MD of the RSSI (rs?=?-?0.371; p?=?0.004) and more contrast leakage into CSF (rs?=?0.347; p?=?0.007) were associated with the cavitation index in univariable analysis, only BBB leakage in CSF remained independently associated with cavitation (beta?=?0.315, p?=?0.046). Increased BBB leakage into CSF may indicate worse endothelial dysfunction and increased risk of tissue destruction post RSSI. Although cavitation was common, it only affected a small proportion of the original RSSI.
| S-EPMC7235062 | biostudies-literature
Project description:MotivationIschemic stroke, triggered by an obstruction in the cerebral blood supply, leads to infarction of the affected brain tissue. An accurate and reproducible automatic segmentation is of high interest, since the lesion volume is an important end-point for clinical trials. However, various factors, such as the high variance in lesion shape, location and appearance, render it a difficult task.MethodsIn this article, nine classification methods (e.g. Generalized Linear Models, Random Decision Forests and Convolutional Neural Networks) are evaluated and compared with each other using 37 multiparametric MRI datasets of ischemic stroke patients in the sub-acute phase in terms of their accuracy and reliability for ischemic stroke lesion segmentation. Within this context, a multi-spectral classification approach is compared against mono-spectral classification performance using only FLAIR MRI datasets and two sets of expert segmentations are used for inter-observer agreement evaluation.Results and conclusionThe results of this study reveal that high-level machine learning methods lead to significantly better segmentation results compared to the rather simple classification methods, pointing towards a difficult non-linear problem. The overall best segmentation results were achieved by a Random Decision Forest and a Convolutional Neural Networks classification approach, even outperforming all previously published results. However, none of the methods tested in this work are capable of achieving results in the range of the human observer agreement and the automatic ischemic stroke lesion segmentation remains a complicated problem that needs to be explored in more detail to improve the segmentation results.
| S-EPMC4687679 | biostudies-literature