NeuroImage. Clinical
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NeuroImage. Clinical · Jan 2017
Simulation of spreading depolarization trajectories in cerebral cortex: Correlation of velocity and susceptibility in patients with aneurysmal subarachnoid hemorrhage.
In many cerebral grey matter structures including the neocortex, spreading depolarization (SD) is the principal mechanism of the near-complete breakdown of the transcellular ion gradients with abrupt water influx into neurons. Accordingly, SDs are abundantly recorded in patients with traumatic brain injury, spontaneous intracerebral hemorrhage, aneurysmal subarachnoid hemorrhage (aSAH) and malignant hemispheric stroke using subdural electrode strips. SD is observed as a large slow potential change, spreading in the cortex at velocities between 2 and 9 mm/min. ⋯ We then correlated variables indicating SD susceptibility with algorithm-estimated SD velocities in twelve aSAH patients. Highly significant correlations supported the algorithm's validity. The trajectory search failed significantly more often for SDs recorded directly over emerging focal brain lesions suggesting in humans similar to animals that the complexity of SD propagation paths increase in tissue undergoing injury.
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NeuroImage. Clinical · Jan 2017
Structurofunctional resting-state networks correlate with motor function in chronic stroke.
Motor function and recovery after stroke likely rely directly on the residual anatomical connections in the brain and its resting-state functional connectivity. Both structural and functional properties of cortical networks after stroke are revealed using multimodal magnetic resonance imaging (MRI). Specifically, functional connectivity MRI (fcMRI) can extract functional networks of the brain at rest, while structural connectivity can be estimated from white matter fiber orientations measured with high angular-resolution diffusion imaging (HARDI). A model that marries these two techniques may be the key to understanding functional recovery after stroke. In this study, a novel set of voxel-level measures of structurofunctional correlations (SFC) was developed and tested in a group of chronic stroke subjects. ⋯ The results demonstrate that changes after a stroke in both intrinsic and network-based structurofunctional correlations at rest are correlated with motor function, underscoring the importance of residual structural connectivity in cortical networks.
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NeuroImage. Clinical · Jan 2017
The relationship between cortical lesions and periventricular NAWM abnormalities suggests a shared mechanism of injury in primary-progressive MS.
In subjects with multiple sclerosis (MS), pathology is more frequent near the inner and outer surfaces of the brain. Here, we sought to explore if in subjects with primary progressive MS (PPMS) cortical lesion load is selectively associated with the severity of periventricular normal appearing white matter (NAWM) damage, as assessed with diffusion weighted imaging. To this aim, twenty-four subjects with PPMS and twenty healthy controls were included in the study. ⋯ Our main result was the observation in the PPMS group of a significant correlation between periventricular NAWM MD values and cortical lesion load, with a greater cortical lesion burden being associated with more abnormal periventricular NAWM MD. Conversely, there was no correlation between cortical lesion load and deep NAWM MD values or periventricular WM lesions. Our data thus suggest that a common - and relatively selective - factor plays a role in the development of both cortical lesion and periventricular NAWM abnormalities in PPMS.
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NeuroImage. Clinical · Jan 2016
Abnormalities in large scale functional networks in unmedicated patients with schizophrenia and effects of risperidone.
To describe abnormalities in large scale functional networks in unmedicated patients with schizophrenia and to examine effects of risperidone on networks. ⋯ Our results demonstrate abnormalities in large scale functional networks in patients with schizophrenia that are modulated by risperidone only to a certain extent, underscoring the dire need for development of novel antipsychotic medications that have the ability to alleviate symptoms through attenuation of dysconnectivity.
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NeuroImage. Clinical · Jan 2016
Comparative StudyComparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI.
Tumor segmentation is a particularly challenging task in high-grade gliomas (HGGs), as they are among the most heterogeneous tumors in oncology. An accurate delineation of the lesion and its main subcomponents contributes to optimal treatment planning, prognosis and follow-up. Conventional MRI (cMRI) is the imaging modality of choice for manual segmentation, and is also considered in the vast majority of automated segmentation studies. ⋯ In this paper, we compare the performance of several unsupervised classification methods for HGG segmentation based on MP-MRI data including cMRI, DWI, MRSI and PWI. Two independent MP-MRI datasets with a different acquisition protocol were available from different hospitals. We demonstrate that a hierarchical non-negative matrix factorization variant which was previously introduced for MP-MRI tumor segmentation gives the best performance in terms of mean Dice-scores for the pathologic tissue classes on both datasets.