NeuroImage. Clinical
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NeuroImage. Clinical · Jan 2019
Association of short-term cognitive decline and MCI-to-AD dementia conversion with CSF, MRI, amyloid- and 18F-FDG-PET imaging.
Disease-modifying treatment trials are increasingly advanced to the prodromal or preclinical phase of Alzheimer's disease (AD), and inclusion criteria are based on biomarkers rather than clinical symptoms. Therefore, it is of great interest to determine which biomarkers should be combined to accurately predict conversion from mild cognitive impairment (MCI) to AD dementia. However, up to date, only few studies performed a complete A/T/N subject characterization using each of the CSF and imaging markers, or they only investigated long-term (≥ 2 years) prognosis. ⋯ Patients with MCI converted to AD dementia at an annual rate of 31%, which could be best predicted by combining neuropsychological testing (visuospatial construction skills) with either MRI-based HV or 18F-FDG-PET. Combining all three markers resulted in 96% specificity and 92% sensitivity. Neither amyloid-PET nor CSF biomarkers could discriminate short-term converters from non-converters.
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NeuroImage. Clinical · Jan 2019
Microstructural neuroimaging of white matter tracts in persistent post-concussion syndrome: A prospective controlled cohort study.
Children with mild traumatic brain injury (mTBI) typically recover quickly, however approximately 15% experience persistent post-concussive symptoms (PPCS) past 3 months. The microstructural pathology associated with underlying persistent symptoms is poorly understood but is suggested to involve axonal injury to white matter tracts. Diffusion tensor imaging (DTI) can be used to visualize and characterize damage to white matter microstructure of the brain. ⋯ Our findings provide evidence of microstructural injury following mTBI in children with ongoing post-concussive symptoms one month post injury. The changes were persistent 4-6 weeks later. Further longitudinal studies of white matter microstructure in PPCS will be helpful to clarify whether these white matter alterations resolve over time.
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NeuroImage. Clinical · Jan 2019
Differential medial temporal lobe and default-mode network functional connectivity and morphometric changes in Alzheimer's disease.
We report group level differential detection of medial temporal lobe resting-state functional connectivity disruption and morphometric changes in the transition from cognitively normal to early mild cognitive impairment in an age-, education- and gender-matched 105 subjects Alzheimer's Disease Neuroimaging Initiative dataset. In mild Alzheimer's Disease, but not early mild cognitive impairment, characteristic brain atrophy was detected in FreeSurfer estimates of subcortical and hippocampal subfield volumes and cortical thinning. ⋯ Key findings include: a) focal, bilaterally symmetric spatial organization of affected medial temporal lobe regions; b) mutual hyperconnectivity involving ventral medial temporal lobe structures (temporal pole, uncus); c) dorsal medial temporal lobe hypoconnectivity with anterior and posterior midline default-mode network nodes; and d) a complex pattern of transient and persistent changes in hypo- and hyper-connectivity across Alzheimer's Disease stages. These findings position medial temporal lobe resting state functional connectivity as a candidate biomarker of an Alzheimer's Disease pathophysiological cascade, potentially in advance of clinical biomarkers, and coincident with biomarkers of the earliest stages of Alzheimer's neuropathology.
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NeuroImage. Clinical · Jan 2019
Cerebellar atrophy and its contribution to motor and cognitive performance in multiple system atrophy.
Neuroanatomical differences in the cerebellum are among the most consistent findings in multiple system atrophy (MSA) patients. This study performed a detailed cerebellar morphology in MSA patients and its two subtypes: MSA-P (parkinson's symptoms predominate) and MSA-C (cerebellar symptoms predominant), and their relations to profiles of motor and cognitive deficits. ⋯ Our data suggest that volumetric abnormalities of cerebellum contribute substantially to motor and cognitive performance in patients with MSA. In patients with MSA-P and MSA-C, affected regions of cerebellum differed.
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NeuroImage. Clinical · Jan 2019
ReviewAddressing heterogeneity (and homogeneity) in treatment mechanisms in depression and the potential to develop diagnostic and predictive biomarkers.
It has been 10 years since machine learning was first applied to neuroimaging data in psychiatric disorders to identify diagnostic and prognostic markers at the level of the individual. Proof of concept findings in major depression have since been extended in international samples and are beginning to include hundreds of samples from multisite data. Neuroimaging provides the unique capability to detect an acute depressive state in major depression, while we would not expect perfect classification with current diagnostic criteria which are based solely on clinical features. ⋯ Irrespective of the mechanism, the capacity for response will moderate the outcome, which includes inherent models of interpersonal relationships that could be associated with genetic risk load and represented by patterns of functional and structural neural correlates as a predictive biomarker. We propose that methods which directly address heterogeneity are essential and that a synergistic combination could bring together data-driven inductive and symptom-based deductive approaches. Through this iterative process, major depression can develop from being syndrome characterized by a collection of symptoms to a disease with an identifiable pathophysiology.