Neuroimaging clinics of North America
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Neuroimaging Clin. N. Am. · Nov 2017
ReviewResting-state Functional Magnetic Resonance Imaging in Presurgical Functional Mapping: Sensorimotor Localization.
This article compares resting-state functional magnetic resonance (fMR) imaging with task fMR imaging for presurgical functional mapping of the sensorimotor (SM) region. Before tumor resection, 38 patients were scanned using both methods. ⋯ A paired t-test showed higher overlap between resting-state maps and anatomic references compared with task activation when using a maximal overlap criterion. Resting state-derived maps are more comprehensive than those derived from task fMR imaging.
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Neuroimaging Clin. N. Am. · Nov 2017
ReviewApplications of Resting-State Functional MR Imaging to Epilepsy.
We discuss the value of resting-state functional MR imaging (rsfMR imaging) as an emerging technique to address questions about memory and language that are central in surgery for temporal-lobe epilepsy, namely the identification and characterization of eloquent cortex to avoid surgical morbidity. The emergence of a robust set of data using rsfMR imaging has opened new avenues for exploring more direct relationships between neural networks and current cognitive function and prediction of postoperative change. These techniques are also being explored for their potential to characterize epilepsy subtypes, identify epileptic foci, and monitor treatment effects.
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Neuroimaging Clin. N. Am. · Nov 2017
ReviewMachine Learning Applications to Resting-State Functional MR Imaging Analysis.
Machine learning is one of the most exciting and rapidly expanding fields within computer science. Academic and commercial research entities are investing in machine learning methods, especially in personalized medicine via patient-level classification. There is great promise that machine learning methods combined with resting state functional MR imaging will aid in diagnosis of disease and guide potential treatment for conditions thought to be impossible to identify based on imaging alone, such as psychiatric disorders. We discuss machine learning methods and explore recent advances.
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Neuroimaging Clin. N. Am. · Nov 2017
ReviewApplications of Resting State Functional MR Imaging to Traumatic Brain Injury.
Traumatic brain injury (TBI) is an important public health issue. TBI includes a broad spectrum of injury severities and abnormalities. ⋯ Specifically, graph theory is being used to study the change in networks after TBI. Machine learning methods allow researchers to build models capable of predicting injury severity and recovery trajectories.
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Neuroimaging Clin. N. Am. · Nov 2017
ReviewApplications of Resting-State Functional Connectivity to Neurodegenerative Disease.
Neurodegenerative diseases target specific large-scale neuronal networks, leading to distinct behavioral and cognitive dysfunctions. Resting-state functional magnetic resonance imaging (rsfMR imaging)-based functional connectivity method maps symptoms-associated functional network deterioration in vivo. ⋯ Understanding of disease mechanism can further guide early detection and predictions of disease progression and inform development of more effective treatment. With better clinical phenotyping and larger samples across multiple sites, we discuss several possible future directions to further develop rsfMR imaging-based functional connectivity methods into scientifically and clinically useful assays for neurodegenerative disorders.