NeuroImage. Clinical
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NeuroImage. Clinical · Jan 2016
ReviewTranslating state-of-the-art spinal cord MRI techniques to clinical use: A systematic review of clinical studies utilizing DTI, MT, MWF, MRS, and fMRI.
A recent meeting of international imaging experts sponsored by the International Spinal Research Trust (ISRT) and the Wings for Life Foundation identified 5 state-of-the-art MRI techniques with potential to transform the field of spinal cord imaging by elucidating elements of the microstructure and function: diffusion tensor imaging (DTI), magnetization transfer (MT), myelin water fraction (MWF), MR spectroscopy (MRS), and functional MRI (fMRI). However, the progress toward clinical translation of these techniques has not been established. ⋯ State-of-the-art spinal cord MRI techniques are emerging with great potential to improve the diagnosis and management of various spinal pathologies, but the current body of evidence has only showed limited clinical utility to date. Among these imaging tools DTI is the most mature, but further work is necessary to standardize and validate its use before it will be adopted in the clinical realm. Large, well-designed studies with a priori hypotheses, standardized acquisition methods, detailed clinical data collection, and robust automated analysis techniques are needed to fully demonstrate the potential of these rapidly evolving techniques.
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NeuroImage. Clinical · Jan 2015
ReviewNeuroimaging and neuromodulation approaches to study eating behavior and prevent and treat eating disorders and obesity.
Functional, molecular and genetic neuroimaging has highlighted the existence of brain anomalies and neural vulnerability factors related to obesity and eating disorders such as binge eating or anorexia nervosa. In particular, decreased basal metabolism in the prefrontal cortex and striatum as well as dopaminergic alterations have been described in obese subjects, in parallel with increased activation of reward brain areas in response to palatable food cues. Elevated reward region responsivity may trigger food craving and predict future weight gain. ⋯ First, we will discuss the possibility to identify new biological markers of brain functions. Second, we will highlight the potential of neuroimaging and neuromodulation in individualized medicine. Third, we will introduce the ethical questions that are concomitant to the emergence of new neuromodulation therapies.
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NeuroImage. Clinical · Jan 2015
ReviewRisk, diagnostic error, and the clinical science of consciousness.
In recent years, a number of new neuroimaging techniques have detected covert awareness in some patients previously thought to be in a vegetative state/unresponsive wakefulness syndrome. This raises worries for patients, families, and physicians, as it indicates that the existing diagnostic error rate in this patient group is higher than assumed. Recent research on a subset of these techniques, called active paradigms, suggests that false positive and false negative findings may result from applying different statistical methods to patient data. ⋯ We argue that false positive and false negative findings carry particular moral risks, which may bear on investigators' decisions to use certain methods when independent means for estimating their clinical utility are absent. We review and critically analyze this methodological problem as it relates to both fMRI and EEG active paradigms. We conclude by drawing attention to three common clinical scenarios where the risk of diagnostic error may be most pronounced in this patient group.
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NeuroImage. Clinical · Jan 2012
ReviewNeuroimaging of structural pathology and connectomics in traumatic brain injury: Toward personalized outcome prediction.
Recent contributions to the body of knowledge on traumatic brain injury (TBI) favor the view that multimodal neuroimaging using structural and functional magnetic resonance imaging (MRI and fMRI, respectively) as well as diffusion tensor imaging (DTI) has excellent potential to identify novel biomarkers and predictors of TBI outcome. This is particularly the case when such methods are appropriately combined with volumetric/morphometric analysis of brain structures and with the exploration of TBI-related changes in brain network properties at the level of the connectome. ⋯ The themes being explored cover notable trends in this area of research, including (1) the role of advanced MRI processing methods in the analysis of structural pathology, (2) the use of brain connectomics and network analysis to identify outcome biomarkers, and (3) the application of multivariate statistics to predict outcome using neuroimaging metrics. The goal of the review is to draw the community's attention to these recent advances on TBI outcome prediction methods and to encourage the development of new methodologies whereby structural neuroimaging can be used to identify biomarkers of TBI outcome.