Journal of neuroimaging : official journal of the American Society of Neuroimaging
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Magnetic resonance imaging (MRI) is heavily relied upon for the diagnosis and monitoring of multiple sclerosis (MS), a chronic, demyelinating disease of the central nervous system. Serum biomarkers may serve as an accessible tool for increasing sensitivity, improving accessibility, corroborating symptoms, and providing additional data to guide clinical management. This scoping review investigates the current understanding of how the serum biomarker glial fibrillary acidic protein (sGFAP) relates to brain MRI metrics. ⋯ These results highlight that while sGFAP may not be specific for MS, it may have utility for increasing sensitivity in postdiagnosis monitoring of MS progression.
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The 3-dimensional cranial nerve imaging (CRANI) sequence may assist visualization of anatomical details of extraforaminal cranial nerves and aid in clinical diagnosis and preoperative planning. In this study, we investigated the feasibility of using a combined CRANI and magnetization-prepared rapid-acquisition gradient-echo (MPRAGE) imaging protocol to comprehensively identify trigeminal nerve projections. ⋯ A combined CRANI and MPRAGE protocol can be combined to visualize distal branches of V1, V2, and V3 and has potential for clinical use.
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This study sought to explore dynamic degree centrality (DC) variability in particular regions of the brain in patients with poststroke Broca aphasia (BA) using a resting-state functional magnetic resonance imaging (rs-fMRI) approach, comparing differences between Uyghur and Chinese BA patients. ⋯ The observed enhancement of dynamic DC variability in ORBmid.R and PCUN.R among Chinese BA patients and in CAL.R in Uyghur BA patients may be attributable to language network restructuring. Overall, these results suggest that BA patients who use different language families may exhibit differences in the network mechanisms that characterize observed impairments of language function.
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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.
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Meningiomas are the most common neoplasms of the central nervous system, accounting for approximately 40% of all brain tumors. Surgical resection represents the mainstay of management for symptomatic lesions. Preoperative planning is largely informed by neuroimaging, which allows for evaluation of anatomy, degree of parenchymal invasion, and extent of peritumoral edema. ⋯ We also summarize the role of advanced imaging techniques, including magnetic resonance perfusion and spectroscopy, for the preoperative evaluation of meningiomas. In addition, we describe the potential impact of emerging technologies, such as artificial intelligence and machine learning, on meningioma diagnosis and management. A strong foundation of knowledge in the latest meningioma imaging techniques will allow the neuroradiologist to help optimize preoperative planning and improve patient outcomes.