NeuroImage. Clinical
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NeuroImage. Clinical · Jan 2014
Randomized Controlled Trial Comparative StudyRandom Forest ensembles for detection and prediction of Alzheimer's disease with a good between-cohort robustness.
Computer-aided diagnosis of Alzheimer's disease (AD) is a rapidly developing field of neuroimaging with strong potential to be used in practice. In this context, assessment of models' robustness to noise and imaging protocol differences together with post-processing and tuning strategies are key tasks to be addressed in order to move towards successful clinical applications. In this study, we investigated the efficacy of Random Forest classifiers trained using different structural MRI measures, with and without neuroanatomical constraints in the detection and prediction of AD in terms of accuracy and between-cohort robustness. ⋯ The models trained using parcelled and high-dimensional (HD) input demonstrated equivalent performance, but the former was more effective in terms of computation/memory and time costs. The sensitivity/specificity for detecting MCI-to-AD conversion (but not AD/HC classification performance) was further improved from 79.5%/75%-83.3%/81.3% by a combination of morphometric measurements with ApoE-genotype and demographics (age, sex, education). When applied to the independent AddNeuroMed cohort, the best ADNI models produced equivalent performance without substantial accuracy drop, suggesting good robustness sufficient for future clinical implementation.
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NeuroImage. Clinical · Jan 2014
Intersession reliability of fMRI activation for heat pain and motor tasks.
As the practice of conducting longitudinal fMRI studies to assess mechanisms of pain-reducing interventions becomes more common, there is a great need to assess the test-retest reliability of the pain-related BOLD fMRI signal across repeated sessions. This study quantitatively evaluated the reliability of heat pain-related BOLD fMRI brain responses in healthy volunteers across 3 sessions conducted on separate days using two measures: (1) intraclass correlation coefficients (ICC) calculated based on signal amplitude and (2) spatial overlap. The ICC analysis of pain-related BOLD fMRI responses showed fair-to-moderate intersession reliability in brain areas regarded as part of the cortical pain network. ⋯ A simple motor task (finger-thumb opposition) was performed by the same subjects in the same sessions as the painful heat stimuli were delivered. Intersession reliability of fMRI activation in cortical motor areas was comparable to previously published findings for both spatial overlap and ICC measures, providing support for the validity of the analytical approach used to assess intersession reliability of pain-related fMRI activation. A secondary finding of this study is that the use of standard ICC alone as a measure of reliability may not be sufficient, as the underlying variance structure of an fMRI dataset can result in inappropriately high ICC values; a method to eliminate these false positive results was used in this study and is recommended for future studies of test-retest reliability.
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NeuroImage. Clinical · Jan 2014
Anatomical and diffusion MRI of deep gray matter in pediatric spina bifida.
Individuals with spina bifida myelomeningocele (SBM) exhibit brain abnormalities in cortical thickness, white matter integrity, and cerebellar structure. Little is known about deep gray matter macro- and microstructure in this population. The current study utilized volumetric and diffusion-weighted MRI techniques to examine gray matter volume and microstructure in several subcortical structures: basal ganglia nuclei, thalamus, hippocampus, and amygdala. ⋯ These results provide further support that SBM differentially disrupts brain regions whereby some structures are volumetrically normal whereas others are reduced or enlarged. In the hippocampus, volumetric reduction coupled with increased MD may imply reduced cellular density and aberrant organization. Alternatively, the enlarged volume and significantly reduced MD in the putamen suggest increased density.
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Schizophrenia is characterized by loss of brain volume, which may represent an ongoing pathophysiological process. This loss of brain volume may be explained by reduced neuropil rather than neuronal loss, suggesting abnormal synaptic plasticity and cortical microcircuitry. A possible mechanism is hypofunction of the NMDA-type of glutamate receptor, which reduces the excitation of inhibitory GABAergic interneurons, resulting in a disinhibition of glutamatergic pyramidal neurons. ⋯ No significant change in the GABA/Cr ratio was found between patients and controls in the parieto-occipital cortex, nor were levels of glutamate, NAA, creatine, and choline differed in patients and controls in the prefrontal and parieto-occipital cortices. Our findings support a mechanism involving altered GABA levels distinguished from glutamate levels in the medial prefrontal cortex in schizophrenia, particularly in high functioning patients. A (compensatory) role for GABA through altered inhibitory neurotransmission in the prefrontal cortex may be ongoing in (higher functioning) patients with schizophrenia.
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NeuroImage. Clinical · Jan 2014
Parkinson's disease-related perfusion and glucose metabolic brain patterns identified with PCASL-MRI and FDG-PET imaging.
Under normal conditions, the spatial distribution of resting cerebral blood flow and cerebral metabolic rate of glucose are closely related. A relatively new magnetic resonance (MR) technique, pseudo-continuous arterial spin labeling (PCASL), can be used to measure regional brain perfusion. We identified a Parkinson's disease (PD)-related perfusion and metabolic covariance pattern in the same patients using PCASL and FDG-PET imaging and assessed (dis)similarities in the disease-related pattern between perfusion and metabolism in PD patients. ⋯ We identified PD-related perfusion and metabolic brain patterns using PCASL and FDG-PET in the same patients which were comparable with results of existing research. In this respect, PCASL appears to be a promising addition in the early diagnosis of individual parkinsonian patients.