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result(s) for
"brain imaging"
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Cognitive Motor Dissociation in Disorders of Consciousness
2024
Among 241 persons with disorders of consciousness who had no observable response to commands, 25% had a verifiable response to commands on EEG or functional MRI, a condition known as cognitive motor dissociation.
Journal Article
The new mind readers : what neuroimaging can and cannot reveal about our thoughts
The ability to read minds has long been a fascination of science fiction, but revolutionary new brain-imaging methods are bringing it closer to scientific reality. The New Mind Readers provides a compelling look at the origins, development, and future of these extraordinary tools, revealing how they are increasingly being used to decode our thoughts and experiences--and how this raises sometimes troubling questions about their application in domains such as marketing, politics, and the law. Russell Poldrack takes readers on a journey of scientific discovery, telling the stories of the visionaries behind these breakthroughs. Along the way, he gives an insider's perspective on what is perhaps the single most important technology in cognitive neuroscience today--functional magnetic resonance imaging, or fMRI, which is providing astonishing new insights into the contents and workings of the mind. He highlights both the amazing power and major limitations of these techniques and describes how applications outside the lab often exceed the bounds of responsible science. Poldrack also details the unique and sometimes disorienting experience of having his own brain scanned more than a hundred times as part of a landmark study of how human brain function changes over time. Written by one of the world's leading pioneers in the field, The New Mind Readers cuts through the hype and misperceptions surrounding these emerging new methods, offering needed perspective on what they can and cannot do--and demonstrating how they can provide new answers to age-old questions about the nature of consciousness and what it means to be human. -- Inside jacket flap.
EANM procedure guidelines for brain PET imaging using 18FFDG, version 3
by
Traub-Weidinger Tatjana
,
Lammertsma, Adriaan A
,
Law, Ian
in
Alzheimer's disease
,
Brain
,
Cognitive ability
2022
The present procedural guidelines summarize the current views of the EANM Neuro-Imaging Committee (NIC). The purpose of these guidelines is to assist nuclear medicine practitioners in making recommendations, performing, interpreting, and reporting results of [18F]FDG-PET imaging of the brain. The aim is to help achieve a high-quality standard of [18F]FDG brain imaging and to further increase the diagnostic impact of this technique in neurological, neurosurgical, and psychiatric practice. The present document replaces a former version of the guidelines that have been published in 2009. These new guidelines include an update in the light of advances in PET technology such as the introduction of digital PET and hybrid PET/MR systems, advances in individual PET semiquantitative analysis, and current broadening clinical indications (e.g., for encephalitis and brain lymphoma). Further insight has also become available about hyperglycemia effects in patients who undergo brain [18F]FDG-PET. Accordingly, the patient preparation procedure has been updated. Finally, most typical brain patterns of metabolic changes are summarized for neurodegenerative diseases. The present guidelines are specifically intended to present information related to the European practice. The information provided should be taken in the context of local conditions and regulations.
Journal Article
Traumatic Brain Injury as a Disorder of Brain Connectivity
by
Hayes, Jasmeet P.
,
Bigler, Erin D.
,
Verfaellie, Mieke
in
Anisotropy
,
Brain - diagnostic imaging
,
Brain - physiopathology
2016
Objectives: Recent advances in neuroimaging methodologies sensitive to axonal injury have made it possible to assess in vivo the extent of traumatic brain injury (TBI) -related disruption in neural structures and their connections. The objective of this paper is to review studies examining connectivity in TBI with an emphasis on structural and functional MRI methods that have proven to be valuable in uncovering neural abnormalities associated with this condition. Methods: We review studies that have examined white matter integrity in TBI of varying etiology and levels of severity, and consider how findings at different times post-injury may inform underlying mechanisms of post-injury progression and recovery. Moreover, in light of recent advances in neuroimaging methods to study the functional connectivity among brain regions that form integrated networks, we review TBI studies that use resting-state functional connectivity MRI methodology to examine neural networks disrupted by putative axonal injury. Results: The findings suggest that TBI is associated with altered structural and functional connectivity, characterized by decreased integrity of white matter pathways and imbalance and inefficiency of functional networks. These structural and functional alterations are often associated with neurocognitive dysfunction and poor functional outcomes. Conclusions: TBI has a negative impact on distributed brain networks that lead to behavioral disturbance. (JINS, 2016, 22, 120–137)
Journal Article
Direct attenuation correction of brain PET images using only emission data via a deep convolutional encoder-decoder (Deep-DAC)
by
Oveisi Mehrdad
,
Shiri Isaac
,
Leung, Kevin Ho-Yin
in
Artificial intelligence
,
Attenuation
,
Brain
2019
ObjectiveTo obtain attenuation-corrected PET images directly from non-attenuation-corrected images using a convolutional encoder-decoder network.MethodsBrain PET images from 129 patients were evaluated. The network was designed to map non-attenuation-corrected (NAC) images to pixel-wise continuously valued measured attenuation-corrected (MAC) PET images via an encoder-decoder architecture. Image quality was evaluated using various evaluation metrics. Image quantification was assessed for 19 radiomic features in 83 brain regions as delineated using the Hammersmith atlas (n30r83). Reliability of measurements was determined using pixel-wise relative errors (RE; %) for radiomic feature values in reference MAC PET images.ResultsPeak signal-to-noise ratio (PSNR) and structural similarity index metric (SSIM) values were 39.2 ± 3.65 and 0.989 ± 0.006 for the external validation set, respectively. RE (%) of SUVmean was − 0.10 ± 2.14 for all regions, and only 3 of 83 regions depicted significant differences. However, the mean RE (%) of this region was 0.02 (range, − 0.83 to 1.18). SUVmax had mean RE (%) of − 3.87 ± 2.84 for all brain regions, and 17 regions in the brain depicted significant differences with respect to MAC images with a mean RE of − 3.99 ± 2.11 (range, − 8.46 to 0.76). Homogeneity amongst Haralick-based radiomic features had the highest number (20) of regions with significant differences with a mean RE (%) of 7.22 ± 2.99.ConclusionsDirect AC of PET images using deep convolutional encoder-decoder networks is a promising technique for brain PET images. The proposed deep learning method shows significant potential for emission-based AC in PET images with applications in PET/MRI and dedicated brain PET scanners.Key Points• We demonstrate direct emission-based attenuation correction of PET images without using anatomical information.• We performed radiomics analysis of 83 brain regions to show robustness of direct attenuation correction of PET images.• Deep learning methods have significant promise for emission-based attenuation correction in PET images with potential applications in PET/MRI and dedicated brain PET scanners.
Journal Article
Beyond sleepy: structural and functional changes of the default-mode network in idiopathic hypersomnia
by
Boucetta, Soufiane
,
Lachapelle, Francis
,
Kim, Hosung
in
Adult
,
Brain
,
Brain - diagnostic imaging
2019
Idiopathic hypersomnia (IH) is characterized by excessive daytime sleepiness but, in contrast to narcolepsy, does not involve cataplexy, sleep-onset REM periods, or any consistent hypocretin-1 deficiency. The pathophysiological mechanisms of IH remain unclear. Because of the involvement of the default-mode network (DMN) in alertness and sleep, our aim was to investigate the structural and functional modifications of the DMN in IH. We conducted multimodal magnetic resonance imaging (MRI) in 12 participants with IH and 15 good sleeper controls (mean age ± SD: 32 ± 9.6 years, range 22–53 years, nine males). Self-reported as well as objective measures of daytime sleepiness were collected. Gray matter volume and cortical thickness were analyzed to investigate brain structural differences between good sleepers and IH. Structural covariance and resting-state functional connectivity were analyzed to investigate changes in the DMN. Participants with IH had greater volume and cortical thickness in the precuneus, a posterior hub of the DMN. Cortical thickness in the left medial prefrontal cortex was positively correlated with thickness of the precuneus, and the strength of this correlation was greater in IH. In contrast, functional connectivity at rest was lower within the anterior DMN (medial prefrontal cortex) in IH, and correlated with self-reported daytime sleepiness. The present results show that IH is associated with structural and functional differences in the DMN, in proportion to the severity of daytime sleepiness, suggesting that a disruption of the DMN contributes to the clinical features of IH. Larger volume and thickness in this network might reflect compensatory changes to lower functional connectivity in IH.
Journal Article
Cerebrocerebellar hypometabolism associated with repetitive blast exposure mild traumatic brain injury in 12 Iraq war Veterans with persistent post-concussive symptoms
by
Yu, Chang-En
,
Peskind, Elaine R.
,
Raskind, Murray A.
in
Adult
,
Blast
,
Blast Injuries - diagnostic imaging
2011
Disagreement exists regarding the extent to which persistent post-concussive symptoms (PCS) reported by Iraq combat Veterans with repeated episodes of mild traumatic brain injury (mTBI) from explosive blasts represent structural or functional brain damage or an epiphenomenon of comorbid depression or posttraumatic stress disorder (PTSD). Objective assessment of brain function in this population may clarify the issue. To this end, twelve Iraq war Veterans (32.0
±
8.5 [mean
±
standard deviation (SD)] years of age) reporting one or more blast exposures meeting American Congress of Rehabilitation Medicine criteria for mTBI and persistent PCS and 12 cognitively normal community volunteers (53.0
±
4.6
years of age) without history of head trauma underwent brain fluorodeoxyglucose positron emission tomography (FDG-PET) and neuropsychological assessments and completed PCS and psychiatric symptom rating scales. Compared to controls, Veterans with mTBI (with or without PTSD) exhibited decreased cerebral metabolic rate of glucose in the cerebellum, vermis, pons, and medial temporal lobe. They also exhibited subtle impairments in verbal fluency, cognitive processing speed, attention, and working memory, similar to those reported in the literature for patients with cerebellar lesions. These FDG-PET imaging findings suggest that regional brain hypometabolism may constitute a neurobiological substrate for chronic PCS in Iraq combat Veterans with repetitive blast-trauma mTBI. Given the potential public health implications of these findings, further investigation of brain function in these Veterans appears warranted.
Journal Article
Estimation of brain age delta from brain imaging
2019
It is of increasing interest to study “brain age” - the apparent age of a subject, as inferred from brain imaging data. The difference between brain age and actual age (the “delta”) is typically computed, reflecting deviation from the population norm. This therefore may reflect accelerated aging (positive delta) or resilience (negative delta) and has been found to be a useful correlate with factors such as disease and cognitive decline. However, although there has been a range of methods proposed for estimating brain age, there has been little study of the optimal ways of computing the delta. In this technical note we describe problems with the most common current approach, and present potential improvements. We evaluate different estimation methods on simulated and real data. We also find the strongest correlations of corrected brain age delta with 5,792 non-imaging variables (non-brain physical measures, life-factor measures, cognitive test scores, etc.), and also with 2,641 multimodal brain imaging-derived phenotypes, with data from 19,000 participants in UK Biobank.
•It is of interest to study \"brain age'', as inferred from brain imaging data.•The delta between brain age and actual age is typically computed.•We describe problems with the most common current approach.•We present potential improvements.•We evaluate methods on simulated data and data from UK Biobank.
Journal Article