Journal of neuroimaging : official journal of the American Society of Neuroimaging
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The diagnosis of Dementia with Lewy Bodies (DLB) is challenging due to various clinical presentations and clinical and neuropathological features that overlap with Alzheimer's disease (AD). The use of 18 F-Fluorodeoxyglucose-PET (18 F-FDG-PET) can be limited due to similar patterns in DLB and AD. However, metabolism in the posterior cingulate cortex is known to be relatively preserved in DLB and visual assessment of the "cingulate island sign" became a helpful tool in the analysis of 18F-FDG-PET. The aim of this study was the evaluation of visual and semiquantitative 18F-FDG-PET analyses in the diagnosis of DLB and the differentiation to AD as well as its relation to other dementia biomarkers. ⋯ Semiquantitative 18F-FDG-PET imaging and especially the use of an optimized cingulate island ratio are valuable tools to differentiate between DLB and AD.
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Conventional MRI measures of multiple sclerosis (MS) disease severity, such as lesion volume and brain atrophy, do not provide information about microstructural tissue changes, which may be driving physical and cognitive progression. Myelin damage in normal-appearing white matter (NAWM) is likely an important contributor to MS disability. Myelin water fraction (MWF) provides quantitative measurements of myelin. Mean MWF reflects average myelin content, while MWF standard deviation (SD) describes variation in myelin within regions. The myelin heterogeneity index (MHI = SD/mean MWF) is a composite metric of myelin content and myelin variability. We investigated how mean MWF, SD, and MHI compare in differentiating MS from controls and their associations with physical and cognitive disability. ⋯ Mean MWF, SD, and MHI provide complementary information when assessing regional and global NAWM abnormalities in MS and associations with clinical outcome measures. Examining all three metrics (mean MWF, SD, and MHI) enables a more detailed interpretation of results, depending on whether regions of interest include areas that are more heterogeneous, earlier in the demyelination process, or uniformly injured.
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We aimed to identify reliable neuroradiological features of the brainstem reflecting the neurological symptoms of patients with chronic disorders of consciousness (DOCs) due to severe traumatic brain injury (TBI). ⋯ The volume, FA value, and SUVmax of FDG of the brainstem are important neuroradiological features associated with the neurological conditions of patients with chronic DOCs due to severe TBI.
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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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Observational Study
Optic nerve sheath diameter in intracranial hypertension: Measurement external or internal of the dura mater?
Optic nerve sheath diameter (ONSD) is a promising metric to estimate intracranial pressure (ICP). There is no consensus whether ONSD should be measured external (ONSDext) or internal (ONSDint) of the dura mater. Expert opinion favors ONSDint, though without clear evidence to support this. Adjustments of ONSD for eye diameter (ED) and optic nerve diameter (OND) have been suggested to improve precision. We examined the diagnostic accuracy of ONSDext and ONSDint for estimating ICP, unadjusted as well as adjusted for ED and OND. ⋯ ONSDext and ONSDint differ significantly and are not interchangeable. However, there were no significant differences in diagnostic accuracy between ONSDext and ONSDint. Adjustment for ED may improve diagnostic accuracy of ONSD.