NeuroImage
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The average pathlength map: a diffusion MRI tractography-derived index for studying brain pathology.
Magnetic resonance diffusion tractography provides a powerful tool for the assessment of white matter architecture in vivo. Quantitative tractography metrics, such as streamline length, have successfully been used in the study of brain pathology. To date, these studies have relied on a priori knowledge of which tracts are affected by injury or pathology and manual delineation of regions of interest (ROIs) for use as waypoints in tractography. ⋯ Our analysis shows that voxel-wise average pathlength values are comparable to fractional anisotropy (FA) in terms of reproducibility and variability. For the TBI patient, we observed a significant reduction in streamline pathlength in the genu of the corpus callosum and its projections into the frontal lobe. This study demonstrates that the average pathlength map can be used for voxel-based analysis of a quantitative tractography metric within the whole brain, removing both the dependence on a priori knowledge of affected pathways and time-consuming manual delineation of ROIs.
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Surgery is often the only effective treatment for intractable epilepsy, but its benefits must be balanced by potential disruption of eloquent cortical functions. Wada test is the standard technique to lateralize language before surgery; however, it is invasive and associated with complications. fMRI provides an attractive noninvasive alternative, which has been previously shown to correlate with Wada results. However this correlation is imperfect since standard fMRI laterality indices are dependent on a particular arbitrary statistical threshold used in the data processing. ⋯ The lateralization scores correlated well with the objective measures of language lateralization (r(2)=0.46). Cumulative historical data were utilized to prospectively determine probabilities of language lateralization for individual patients. In conclusion, hemispheric language lateralization can be accurately determined using a novel objective and automated methodology that calculates language lateralization in a threshold-independent manner and can be used to determine the probability of language dominance in individual patients.
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The Default Mode Network (DMN) is a higher order functional neural network that displays activation during passive rest and deactivation during many types of cognitive tasks. Accordingly, the DMN is viewed to represent the neural correlate of internally-generated self-referential cognition. This hypothesis implies that the DMN requires the involvement of cognitive processes, like declarative memory. ⋯ Our findings show less deactivation during semantic compared to the two non-semantic tasks for the entire DMN unit and within left-hemispheric DMN regions, i.e., the dorsal medial prefrontal cortex, the anterior cingulate cortex, the retrosplenial cortex, the angular gyrus, the middle temporal gyrus and the anterior temporal region, as well as the right cerebellum. These results demonstrate that well-known semantic regions are spatially and functionally involved in the DMN. The present study further supports the hypothesis of the DMN as an internal mentation system that involves declarative memory functions.
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The present study utilized diffusion MR imaging and fractional anisotropy (FA) mapping to delineate the microstructure of spinal cord. The concept of Shannon entropy was introduced to analyze the complex microstructure of healthy and injured spinal cords based on FA map. A total of 30 volunteers were recruited in this study with informed consent, including 13 healthy adult subjects (group A, 25±3 years), 12 healthy elderly subjects (group B, 53±7 years) and 5 cervical spondylotic myelopathy (CSM) patients (group C, 53±15 years). ⋯ In CSM patients, there was a loss of architectural structural complexity in the cervical spinal cord tissue as noted by the lower Shannon entropy value. It indicated the potential application of entropy-based analysis for the diagnosis of the severity of chronic compressive spinal cord injuries, i.e. CSM.
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The United States National Institutes of Health (NIH) commit significant support to open-source data and software resources in order to foment reproducibility in the biomedical imaging sciences. Here, we report and evaluate a recent product of this commitment: Advanced Neuroimaging Tools (ANTs), which is approaching its 2.0 release. The ANTs open source software library consists of a suite of state-of-the-art image registration, segmentation and template building tools for quantitative morphometric analysis. ⋯ Furthermore, our two-fold cross-validation allows us to quantify the similarity of templates derived from different subgroups. Our open code, data and evaluation scripts set performance benchmark parameters for this state-of-the-art toolkit. This is the first study to use a consistent transformation framework to provide a reproducible evaluation of the isolated effect of the similarity metric on optimal template construction and brain labeling.