Journal of neuroimaging : official journal of the American Society of Neuroimaging
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Elevated intracranial pressure (ICP) resulting from severe head injury or stroke poses a risk of secondary brain injury that requires neurosurgical intervention. However, currently available noninvasive monitoring techniques for predicting ICP are not sufficiently advanced. We aimed to develop a minimally invasive ICP prediction model using simple CT images to prevent secondary brain injury caused by elevated ICP. ⋯ Overall, the outcomes suggest that these newly developed models may be valuable tools for the rapid and accurate detection of elevated ICP in clinical practice. These models can easily be applied to other sites, as a single CT image at the midbrain level can provide a highly accurate diagnosis.
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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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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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Lateral elbow pain is quite common in everyday life. Lateral epicondylitis and radial tunnel syndrome are the most common causes of lateral elbow pain. The aim of this study was to evaluate the sensitivity and specificity of neuromuscular ultrasound examination in the diagnosis of lateral epicondylitis versus radial tunnel syndrome. ⋯ The present study highlights the importance of the neuromuscular ultrasound's diagnostic role in differentiating radial tunnel syndrome from lateral epicondylitis in the clinical scenario of lateral elbow pain.
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Multicenter Study
Multicenter validation of automated detection of paramagnetic rim lesions on brain MRI in multiple sclerosis.
Paramagnetic rim lesions (PRLs) are an MRI biomarker of chronic inflammation in people with multiple sclerosis (MS). PRLs may aid in the diagnosis and prognosis of MS. However, manual identification of PRLs is time-consuming and prone to poor interrater reliability. To address these challenges, the Automated Paramagnetic Rim Lesion (APRL) algorithm was developed to automate PRL detection. The primary objective of this study is to evaluate the accuracy of APRL for detecting PRLs in a multicenter setting. ⋯ Our study demonstrated APRL's capability to differentiate between PRLs and lesions without paramagnetic rims in a multicenter study. Automated identification of PRLs offers greater efficiency over manual identification and could facilitate large-scale assessments of PRLs in clinical trials.