Journal of neuroimaging : official journal of the American Society of Neuroimaging
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The availability of cone-beam CT perfusion (CBCTP) in angiography suites may improve large-vessel occlusion (LVO) triage and reduce reperfusion times for patients presenting during extended time window. We aim to evaluate the perfusion maps correlation and agreement between multidetector CT perfusion (MDCTP) and CBCTP when obtained sequentially in patients undergoing endovascular therapy. ⋯ These results demonstrate promising accuracy of CBCTP in evaluating ischemic tissue in patients presenting with LVO ischemic stroke.
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Diffusion-weighted imaging is able to capture important information about cerebral white matter (WM) structure. However, diffusion data can suffer from MRI and biological noise that degrades the quality of the images and makes finding important features difficult. We investigated how effectively local and nonlocal denoising increased the sensitivity to detect differences in cerebral WM in neuroHIV. ⋯ PCA denoising had a beneficial effect on detecting significant differences in PWH after sample size reduction. The smaller forceps minor tract and right uncinate fasciculus showed greater sensitivity to PCA denoising than the larger corpus callosum. These results show the importance of identifying the most effective PCA denoising strategy when investigating WM in PWH.
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Differentiation of meningiomas, paragangliomas, and schwannomas in the cerebellopontine angle and jugular foramen remains challenging when conventional MRI findings are inconclusive. This study aimed to assess the clinical utility of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MRI (DCE-MRI) findings for tumor type differentiation and to identify the most significant diagnostic parameters. ⋯ DCE-MRI can provide promising parameters to differentiate meningiomas, paragangliomas, and schwannomas in the cerebellopontine angle and jugular foramen.
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Corpus callosum (CC) atrophy is a strong predictor of multiple sclerosis (MS) disability but the contributing pathological mechanisms remain uncertain. We aimed to apply advanced MRI to explore what drives the often nonuniform callosal atrophy. ⋯ Both white matter and cortical lesions contribute to regional corpus callosal atrophy. The lobe-specific lesion topology does not fully explain the inhomogeneous CC atrophy.
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Corpus callosum (CC) atrophy is predictive of future disability in multiple sclerosis (MS). However, current segmentation methods are either labor- or computationally intensive. We therefore developed an automated deep learning-based CC segmentation tool and hypothesized that its output would correlate with disability. ⋯ We present a fully automatic deep learning-based CC segmentation tool optimized to modern imaging in MS with clinical correlations on par with computationally expensive alternatives.