Journal of neuroimaging : official journal of the American Society of Neuroimaging
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Multicenter Study
Spinal arachnoid webs in adults: Clinical and imaging features in a multicenter study.
Spinal arachnoid webs (SAWs) are rare and can present with myelopathic symptoms. This study aims to add 85 more cases of SAWs to the literature so we can continue to analyze clinical and imaging trends of SAWs to better understand this entity and its natural history. ⋯ We present 85 additional cases of SAWs to the existing literature. Our cases all occurred in the dorsal thoracic subarachnoid space, predominantly from T2 to T6. Patients present with symptoms like other causes of cord compression, and spinal MR studies should be evaluated routinely for the findings of SAWs. Further research could focus on understanding SAW prevalence, risk factors, and pathophysiology.
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In multiple sclerosis (MS), iron rim lesions (IRLs) are characterized by pronounced tissue matrix damage. The T1/T2-weighted (T1/T2w) ratio represents a postprocessing MRI approach to investigate tissue integrity, but studies investigating spinal cord pathology are missing until now. The aim of this study was to characterize tissue integrity using the T1/T2w ratio in lesions and the normal-appearing white and gray matter (NAWM, NAGM) in the spinal cord and brain in MS patients with and without brain IRLs. ⋯ IRLs constitute an imaging marker of disease severity. T1/T2w ratio maps represent an interesting technique to capture diffuse tissue properties. Calculation of T1/T2w ratio maps of the spinal cord might provide additional insights into the pathophysiological processes of MS.
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Intracranial hemorrhage (ICH) is a common life-threatening condition that must be rapidly diagnosed and treated. However, there is still a lack of consensus regarding treatment, driven to some extent by prognostic uncertainty. While several prediction models for ICH detection have already been published, here we present a deep learning predictive model for ICH prognosis. ⋯ The proposed hybrid model was able to accurately classify patients into good and poor prognosis. To the best of our knowledge, this is the first ICH prognosis prediction deep learning model. We concluded that deep learning can be applied for prognosis prediction in ICH that could have a great impact on clinical decision-making. Further, hybrid inputs could be a promising technique for deep learning in medical imaging.
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Commonly used fatigue-lowering medications have not been proven effective in treating multiple sclerosis (MS)-related fatigue. A neuroanatomical basis for treatment-resistant fatigue in MS has not been explored. The aim of this study was to investigate the association between brain diffusion abnormality patterns and resistance to fatigue-lowering treatment. ⋯ Fronto-striatal damage may play a role in the development of resistance to fatigue-lowering treatment. Fronto-striatal FA may serve as a biomarker to predict response to fatigue-lowering medications in MS.