Showing papers in "NeuroImage: Clinical in 2018"

TL;DR: The results improved the state-of-the-art by achieving 70% accuracy in identification of ASD versus control patients in the dataset, and identified the areas of the brain that contributed most to differentiating ASD from typically developing controls as per the deep learning model.

TL;DR: Overall at this point in time, the data on AD are most promising towards the eventual use of resting-state fMRI as an imaging biomarker, although there remain issues such as reproducibility of results and a lack of data demonstrating longitudinal changes.

TL;DR: For the first time, a highly accurate and fully automated method for electrode reconstruction that considers curved trajectories is presented that is made publicly available and constitutes an important step towards future integration of lead reconstruction into standard clinical care.

TL;DR: In this article, the authors used a convolutional neural network (CNN) to segment hyperintensities and differentiate between WMHs and stroke lesions in magnetic resonance images (MRI) of healthy elderly subjects.

TL;DR: It is concluded that probabilistic tractography techniques can be used to segment the VL and VP thalamus based on cortical and cerebellar connectivity in patients that will undergo thalamic DBS for tremor.

TL;DR: PFS can be predicted non-invasively in patients with LGGs by a group of radiomics features that could reflect the biological processes of these tumors.

TL;DR: The presence of dynamic functional brain deteriorations in Parkinson's disease patients with mild cognitive impairment that are not present in PD-NC is suggested, showing the PD-MCI group dynamic FC dysfunctions, reduced FC mostly between SM-CC networks and graph-topological deterioration in the SM network.

TL;DR: An extensive overview of machine learning techniques applied to structural magnetic resonance imaging (MRI) data to obtain clinical classifiers is provided, to provide a comprehensive view of the state of the art in different fields.

TL;DR: It is suggested that, in mild AD, tau aggregation drives local neurodegeneration, whereas the relationships between Aβ and neuro degeneration are not region specific and may be mediated by the interaction between A β and tau.

TL;DR: The findings suggest that combined FET PET/CE-MRI radiomics using textural feature analysis offers a great potential to contribute significantly to the management of patients with brain metastases.

TL;DR: In this paper, the authors used graph theory and machine learning to investigate the properties of change between the pre-operative and predicted post-operative networks, and found that the use of network change metrics may have clinical value for predicting seizure outcome.

TL;DR: The results revealed that the MDD and BD patients were more similar than different in GMV and RSFC, which indicates that investigating the frontal-limbic system could be useful for understanding the underlying mechanisms of these two disorders.

TL;DR: The results support the relevant role of FDG-PET-SPM classification in predicting progression to different dementia conditions in prodromal MCI phase, and in the exclusion of progression, outperforming CSF biomarkers.

TL;DR: Clinical fMRI's applications, limitations and potential solutions are discussed, and fMRI is compared to other brain mapping modalities which should be considered as alternatives or adjuncts when appropriate.

TL;DR: Functional magnetic resonance imaging is used to measure resting state infra-slow oscillatory activity and functional connectivity in patients with chronic orofacial pain at rest and in healthy controls during a 20-minute tonic pain stimulus and shows that similar alterations in DMN function occur in healthy individuals during acute noxious stimuli as well as in individuals with chronic pain.

TL;DR: Neurofeedback training to increase amygdala hemodynamic activity during positive AM recall increased amygdala connectivity with regions involved in self-referential, salience, and reward processing, and suggest future targets for neurofeedback interventions, particularly interventions involving the precuneus.

TL;DR: In a double-blind, randomized, cross-over study, 100 μg LSD and placebo were orally administered to 20 healthy participants and seed-to-voxel analyses consistently indicated increased connectivity between networks and subcortical and cortical hub structures, consistent with findings on the importance of hubs in psychopathological states, especially in psychosis.

TL;DR: The mixed picture of regional decreases and increases in FC is compatible with compensatory change, in what should be viewed as a brain-based disease characterised by larger-scale disintegration of motor and frontal projection cerebral networks.

TL;DR: The data indicate that further research to determine optimal management of opioid use disorder during pregnancy is required and future studies should evaluate childhood outcomes including infant brain development and long-term neurocognitive function.

TL;DR: The anatomical description of the human MFB shows far reaching connectivity of VTA to reward-related subcortical and cortical prefrontal regions - but not to emotion-related regions on the medial cortical surface - realized via the superolateral branch of the MFB.

TL;DR: The present findings of changes in neuroprotective growth factors and neurocognitive performances through acute AE or RE suggest that molecular and neural prerequisites for exercise-dependent plasticity are preserved in elderly aMCI individuals.

TL;DR: This study shows that a convolutional neural network-based segmentation method can accurately segment brain tissues and WMH in MR images of older patients with varying degrees of brain abnormalities and motion artefacts.

TL;DR: It is demonstrated that MR image texture features are predictive of p53 mutation status in lower-grade gliomas based on radiomic features extracted from conventional magnetic resonance (MR) images and can be conveniently used to facilitate presurgical molecular pathological diagnosis.

TL;DR: Average controllability is a concept from network control theory that extends structural connectivity data to estimate the manner in which local neuronal fluctuations spread from a node or subnetwork to alter the state of the rest of the brain.

TL;DR: The hypothesis that increased exposure to perinatal risk factors was associated with lower fractional anisotropy (FA), and higher radial, axial and mean diffusivity (RD, AD, MD) in white matter was tested and support for the multiple hit hypothesis was found.

TL;DR: Dynamic functional network connectivity (dFNC) can be used to identify optimal dFNC states for classification excluding those that does not contain useful features, as well as identifying optimal states in mTBI patients and healthy controls.

TL;DR: The Centiloids approach successfully converts quantitative amyloid burden measurements into a common Centiloid scale (CL) and comparable dynamic range and the impact of differences in underlying image analysis methodologies using both cross-sectional and longitudinal datasets is evaluated.

TL;DR: Higher impulsivity, but not depressive symptoms, was associated with reduced cortical thickness in the frontal pole, rostral middle frontal gyrus, and pars orbitalis, and no differences were found for regional surface area.

TL;DR: 3D image patches are extracted from myelin maps and the corresponding T1-weighted MRIs, and are used to learn a latent joint myelin-T1w feature representation via unsupervised deep learning, suggesting that the proposed method has strong potential for identifying image features that are more sensitive and specific to MS pathology in normal-appearing brain tissues.

TL;DR: It was showed that volumetry outperformed clinical scores to measure disease progression in SCA1, SCA2,SCA3 and SCA7 and the use of volumetric biomarkers in therapeutic trials of autosomal dominant ataxias is advocated.