Frontiers in neurology
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Frontiers in neurology · Jan 2019
ReviewDementia and Parkinson's Disease: Similar and Divergent Challenges in Providing Palliative Care.
Dementia and Parkinson's disease are incurable neurological conditions. Patients often experience specific, complex, and varying needs along their disease trajectory. Current management typically employs a multidisciplinary team approach. ⋯ These should be integrated seamlessly with disease-specific care. Substantial research is already being performed on dementia palliative care. This may also inform the further development of palliative care for Parkinson's disease, including an evaluation of palliative interventions and services.
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Frontiers in neurology · Jan 2019
ReviewDiffusion Tensor Tractography Studies of Central Post-stroke Pain Due to the Spinothalamic Tract Injury: A Mini-Review.
Elucidation of the pathophysiological mechanism of central post-stroke pain (CPSP) is essential to the development of effective therapeutic modalities for CPSP. However, the pathophysiological mechanism of CPSP has not yet been clearly elucidated. The recent development of diffusion tensor tractography (DTT), derived from diffusion tensor imaging (DTI), has allowed visualization and estimation of the spinothalamic tract (STT), which has been considered the most plausible neural tract responsible for the pathogenesis of CPSP. ⋯ We believe that the reviewed studies will facilitate neurorehabilitation of stroke patients with CPSP. However, DTT studies of CPSP are still in the beginning stage because the total number (six studies) of the reviewed studies is very low and half were case reports. Therefore, further studies involving large numbers of subjects are warranted.
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Frontiers in neurology · Jan 2019
Longitudinal Assessment of Cortical Excitability in Children and Adolescents With Mild Traumatic Brain Injury and Persistent Post-concussive Symptoms.
Introduction: Symptoms following a mild traumatic brain injury (mTBI) usually resolve quickly but may persist past 3 months in up to 15% of children. Mechanisms of mTBI recovery are poorly understood, but may involve alterations in cortical neurophysiology. Transcranial Magnetic Stimulation (TMS) can non-invasively investigate such mechanisms, but the time course of neurophysiological changes in mTBI are unknown. ⋯ TMS was well tolerated with no serious adverse events. Conclusions: TMS-assessed cortical excitability is altered in children following mild TBI and is dependent on recovery trajectory. Our findings support delayed return to contact sports in children even where clinical symptoms have resolved.
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Frontiers in neurology · Jan 2019
Embodiment and Presence in Virtual Reality After Stroke. A Comparative Study With Healthy Subjects.
The ability of virtual reality (VR) to recreate controlled, immersive, and interactive environments that provide intensive and customized exercises has motivated its therapeutic use after stroke. Interaction and bodily presence in VR-based interventions is usually mediated through virtual selves, which synchronously represent body movements or responses to events on external input devices. Embodied self-representations in the virtual world not only provide an anchor for visuomotor tasks, but their morphologies can have behavioral implications. ⋯ All measures were consistently higher for healthy controls than for individuals with stroke, but differences between groups only reached statistical significance in presence under the first-person condition (p < 0.010, η p 2 = 0.084). In spite of these differences, the participants experienced a vivid sense of embodiment and presence in almost all conditions. These results provide first evidence that, although less intensively, embodiment and presence are similarly experienced by individuals who have suffered a stroke and by healthy individuals, which could support the vividness of their experience and, consequently, the effectiveness of VR-based interventions.
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Many clinical applications based on deep learning and pertaining to radiology have been proposed and studied in radiology for classification, risk assessment, segmentation tasks, diagnosis, prognosis, and even prediction of therapy responses. There are many other innovative applications of AI in various technical aspects of medical imaging, particularly applied to the acquisition of images, ranging from removing image artifacts, normalizing/harmonizing images, improving image quality, lowering radiation and contrast dose, and shortening the duration of imaging studies. This article will address this topic and will seek to present an overview of deep learning applied to neuroimaging techniques.