Journal of neuroimaging : official journal of the American Society of Neuroimaging
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Susceptibility estimates derived from quantitative susceptibility mapping (QSM) images for the cerebral cortex and major subcortical structures are variably reported in brain magnetic resonance imaging (MRI) studies, as average of all ( μ all ${{{{\mu}}}_{{\mathrm{all}}}}$ ), absolute ( μ abs ${{{{\mu}}}_{{\mathrm{abs}}}}$ ), or positive- ( μ p ${{{{\mu}}}_{\mathrm{p}}}$ ) and negative-only ( μ n ${{{{\mu}}}_{\mathrm{n}}}$ ) susceptibility values using a region of interest (ROI) approach. This pilot study presents a reliability analysis of currently used ROI-QSM metrics and an alternative ROI-based approach to obtain voxel-weighted ROI-QSM metrics ( μ wp ${{{{\mu}}}_{{\mathrm{wp}}}}$ and μ wn ${{{{\mu}}}_{{\mathrm{wn}}}}$ ). ⋯ Among the evaluated ROI-QSM metrics, μ all ${{{{\mu}}}_{{\mathrm{all}}}}$ and μ abs ${{{{\mu}}}_{{\mathrm{abs}}}}$ estimates were less reliable, whereas separating positive and negative values (using μ p , μ n , μ wp , μ wn ${{{{\mu}}}_{\mathrm{p}}},\ {{{{\mu}}}_{\mathrm{n}}},\ {{{{\mu}}}_{{\mathrm{wp}}}},\ {{{{\mu}}}_{{\mathrm{wn}}}}$ ) improved the reproducibility within, and the comparability between, subjects, even when reducing the slice thickness. These preliminary findings may offer valuable insights toward standardizing ROI-QSM metrics across different patient cohorts and imaging settings in future clinical MRI studies.
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To develop and test a decision tree for predicting contrast enhancement quality and shape using precontrast magnetic resonance imaging (MRI) sequences in a large adult-type diffuse glioma cohort. ⋯ The proposed EPDT has high accuracy in predicting enhancement patterns of gliomas irrespective of rater experience.
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In recent years, there has been a growing interest in the study of resting neural networks in different neurological and mental disorders. While previous studies suggest that the default mode network (DMN) may be altered in dyscalculia, the study of resting-state networks in the development of numerical skills, especially in children with developmental dyscalculia (DD), is scarce and relatively recent. Based on this, this study examines differences in resting-state functional connectivity (rs-FC) data of children with DD using functional connectivity multivariate pattern analysis (fc-MVPA), a data-driven methodology that summarizes properties of the entire connectome. ⋯ Our results suggest an aberrant information flow between resting-state networks in children with DD, demonstrating the importance of these networks for arithmetic development.
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Spinal cord stimulation (SCS) is approved by the Food and Drug Administration for treating chronic intractable pain in the back, trunk, or limbs through stimulation of the dorsal column. Numerous studies have used swine as an analog of the human spinal cord to better understand SCS and further improve its efficacy. We performed high-resolution imaging of the porcine spinal cord with intact dura mater using micro-computed tomography (μCT) to construct detailed 3-dimensional (3D) visualizations of the spinal cord and characterize the morphology of the dorsal and ventral rootlets. ⋯ Detailed measurements and highlighted differences between human and porcine spinal cords can inform variations in modeling and electrophysiological experiments between the two species. In contrast to other approaches for measuring the spinal cord and rootlet morphology, our method keeps the dura intact, reducing potential artifacts from dissection.
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The brain connectivity-based atlas is a promising tool for understanding neural communication pathways in the brain, gaining relevance in predicting personalized outcomes for various brain pathologies. This critical review examines the robustness of the brain connectivity-based atlas for predicting post-stroke outcomes. A comprehensive literature search was conducted from 2012 to May 2023 across PubMed, Scopus, EMBASE, EBSCOhost, and Medline databases. ⋯ Studies predicting post-stroke functional outcomes relied on the atlases for multivariate lesion analysis and region of interest identification, often employing atlases derived from young, healthy populations. Current brain connectivity-based atlases for stroke applications lack standardized methods to define and map brain connectivity across atlases and cover sensorimotor functional connectivity to a limited extent. In conclusion, this review highlights the need to develop more comprehensive, robust, and adaptable brain connectivity-based atlases specifically tailored to post-stroke populations.