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Neurotherapeutics : the Journal of the... Apr 2021
Topics: Brain; Humans; Nervous System Diseases; Neurodegenerative Diseases; Neuroimaging
PubMed: 34410634
DOI: 10.1007/s13311-021-01105-7 -
NeuroImage Jan 2019The baby brain is constantly changing due to its active neurodevelopment, and research into the baby brain is one of the frontiers in neuroscience. To help guide... (Review)
Review
The baby brain is constantly changing due to its active neurodevelopment, and research into the baby brain is one of the frontiers in neuroscience. To help guide neuroscientists and clinicians in their investigation of this frontier, maps of the baby brain, which contain a priori knowledge about neurodevelopment and anatomy, are essential. "Brain atlas" in this review refers to a 3D-brain image with a set of reference labels, such as a parcellation map, as the anatomical reference that guides the mapping of the brain. Recent advancements in scanners, sequences, and motion control methodologies enable the creation of various types of high-resolution baby brain atlases. What is becoming clear is that one atlas is not sufficient to characterize the existing knowledge about the anatomical variations, disease-related anatomical alterations, and the variations in time-dependent changes. In this review, the types and roles of the human baby brain MRI atlases that are currently available are described and discussed, and future directions in the field of developmental neuroscience and its clinical applications are proposed. The potential use of disease-based atlases to characterize clinically relevant information, such as clinical labels, in addition to conventional anatomical labels, is also discussed.
Topics: Atlases as Topic; Brain; Female; Humans; Infant; Infant, Newborn; Magnetic Resonance Imaging; Male; Neuroimaging
PubMed: 29625234
DOI: 10.1016/j.neuroimage.2018.04.003 -
NeuroImage Jan 2019Pediatric neuroimaging is challenging due the rapid structural, metabolic, and functional changes that occur in the developing brain. A specially trained team is needed... (Review)
Review
Pediatric neuroimaging is challenging due the rapid structural, metabolic, and functional changes that occur in the developing brain. A specially trained team is needed to produce high quality diagnostic images in children, due to their small physical size and immaturity. Patient motion, cooperation and medical condition dictate the methods and equipment used. A customized approach tailored to each child's age and functional status with the appropriate combination of dedicated staff, imaging hardware, and software is key; these range from low-tech techniques, such as feed and swaddle, to specialized small bore MRI scanners, MRI compatible incubators and neonatal head coils. New pre-and post-processing techniques can also compensate for the motion artifacts and low signal that often degrade neonatal scans.
Topics: Brain; Child; Female; Humans; Infant; Infant, Newborn; Male; Neuroimaging
PubMed: 29684645
DOI: 10.1016/j.neuroimage.2018.04.044 -
NeuroImage Aug 2019
Topics: Brain; Humans; Machine Learning; Neuroimaging
PubMed: 30296563
DOI: 10.1016/j.neuroimage.2018.10.003 -
AJNR. American Journal of Neuroradiology Jul 2020The appropriate imaging of patients with headache presents a number of important and vexing challenges for clinicians. Despite a number of guidelines and studies... (Review)
Review
The appropriate imaging of patients with headache presents a number of important and vexing challenges for clinicians. Despite a number of guidelines and studies demonstrating a lack of cost-effectiveness, clinicians continue to image patients with chronic nonfocal headaches, and the trend toward imaging is increasing. The reasons are complex and include the fear of missing a clinically significant lesion and litigation, habitual and standard of care practices, lack of tort reform, regulatory penalties and potential impact on one's professional reputation, patient pressures, and financial motivation. Regulatory and legislative reforms are needed to encourage best practices without fear of professional sanctions when following the guidelines. The value of negative findings on imaging tests requires better understanding because they appear to provide some measure of societal value. Clinical decision support tools and machine intelligence may offer additional guidance and improve quality and cost-efficient management of this challenging patient population.
Topics: Cost-Benefit Analysis; Headache; Humans; Neuroimaging
PubMed: 32616575
DOI: 10.3174/ajnr.A6591 -
AJNR. American Journal of Neuroradiology Dec 2016Diagnostic imaging is the most rapidly growing physician service in the Medicare and privately insured population. The growing share of medical costs devoted to imaging... (Review)
Review
Diagnostic imaging is the most rapidly growing physician service in the Medicare and privately insured population. The growing share of medical costs devoted to imaging procedures has led to increasing concerns among the key federal agencies and private payers. In an attempt to educate health care providers, patients, and families on the importance of making optimal clinical decisions, the American Board of Internal Medicine Foundation organized the Choosing Wisely initiative with strong collaboration from specialty societies representing nearly all medical disciplines. Among 45 tests and treatments listed on the Choosing Wisely Web site, 24 are directly related to imaging. Eleven of the 24 are associated with neuroimaging. The listing of imaging tests in the Choosing Wisely program by multiple medical societies other than the radiology societies acknowledges that appropriate use of medical imaging is a shared responsibility between radiologists and referring physicians. In this article, we highlight why radiologists are uniquely positioned to support the appropriate use of imaging. We review some of the strategies that radiologists can use to help their referring physicians with appropriate ordering of neuroimaging in real-world practice and address some the challenges and pitfalls in implementing patient-centered imaging decision-making and shifting to a value-based focus in radiology.
Topics: Humans; Neuroimaging; Radiology; Societies, Medical
PubMed: 27282861
DOI: 10.3174/ajnr.A4821 -
NeuroImage Apr 2021Multi-modal neuroimaging projects such as the Human Connectome Project (HCP) and UK Biobank are advancing our understanding of human brain architecture, function,... (Review)
Review
Multi-modal neuroimaging projects such as the Human Connectome Project (HCP) and UK Biobank are advancing our understanding of human brain architecture, function, connectivity, and their variability across individuals using high-quality non-invasive data from many subjects. Such efforts depend upon the accuracy of non-invasive brain imaging measures. However, 'ground truth' validation of connectivity using invasive tracers is not feasible in humans. Studies using nonhuman primates (NHPs) enable comparisons between invasive and non-invasive measures, including exploration of how "functional connectivity" from fMRI and "tractographic connectivity" from diffusion MRI compare with long-distance connections measured using tract tracing. Our NonHuman Primate Neuroimaging & Neuroanatomy Project (NHP_NNP) is an international effort (6 laboratories in 5 countries) to: (i) acquire and analyze high-quality multi-modal brain imaging data of macaque and marmoset monkeys using protocols and methods adapted from the HCP; (ii) acquire quantitative invasive tract-tracing data for cortical and subcortical projections to cortical areas; and (iii) map the distributions of different brain cell types with immunocytochemical stains to better define brain areal boundaries. We are acquiring high-resolution structural, functional, and diffusion MRI data together with behavioral measures from over 100 individual macaques and marmosets in order to generate non-invasive measures of brain architecture such as myelin and cortical thickness maps, as well as functional and diffusion tractography-based connectomes. We are using classical and next-generation anatomical tracers to generate quantitative connectivity maps based on brain-wide counting of labeled cortical and subcortical neurons, providing ground truth measures of connectivity. Advanced statistical modeling techniques address the consistency of both kinds of data across individuals, allowing comparison of tracer-based and non-invasive MRI-based connectivity measures. We aim to develop improved cortical and subcortical areal atlases by combining histological and imaging methods. Finally, we are collecting genetic and sociality-associated behavioral data in all animals in an effort to understand how genetic variation shapes the connectome and behavior.
Topics: Animals; Brain; Callithrix; Connectome; Humans; Image Processing, Computer-Assisted; Internationality; Macaca mulatta; Neuroanatomy; Neuroimaging; Primates; Species Specificity
PubMed: 33484849
DOI: 10.1016/j.neuroimage.2021.117726 -
NeuroImage Jul 2021Brain perturbation studies allow detailed causal inferences of behavioral and neural processes. Because the combination of brain perturbation methods and neural... (Review)
Review
Brain perturbation studies allow detailed causal inferences of behavioral and neural processes. Because the combination of brain perturbation methods and neural measurement techniques is inherently challenging, research in humans has predominantly focused on non-invasive, indirect brain perturbations, or neurological lesion studies. Non-human primates have been indispensable as a neurobiological system that is highly similar to humans while simultaneously being more experimentally tractable, allowing visualization of the functional and structural impact of systematic brain perturbation. This review considers the state of the art in non-human primate brain perturbation with a focus on approaches that can be combined with neuroimaging. We consider both non-reversible (lesions) and reversible or temporary perturbations such as electrical, pharmacological, optical, optogenetic, chemogenetic, pathway-selective, and ultrasound based interference methods. Method-specific considerations from the research and development community are offered to facilitate research in this field and support further innovations. We conclude by identifying novel avenues for further research and innovation and by highlighting the clinical translational potential of the methods.
Topics: Animals; Brain; Humans; Neuroimaging; Optogenetics; Primates
PubMed: 33794355
DOI: 10.1016/j.neuroimage.2021.118017 -
NeuroImage Nov 2022Most neuroimaging studies of brain function analyze data in normalized space to identify regions of common activation across participants. These studies treat... (Review)
Review
Most neuroimaging studies of brain function analyze data in normalized space to identify regions of common activation across participants. These studies treat interindividual differences in brain organization as noise, but this approach can obscure important information about the brain's functional architecture. Recently, a number of studies have adopted a person-specific approach that aims to characterize these individual differences and explore their reliability and implications for behavior. A subset of these studies has taken a precision imaging approach that collects multiple hours of data from each participant to map brain function on a finer scale. In this review, we provide a broad overview of how person-specific and precision imaging techniques have used resting-state measures to examine individual differences in the brain's organization and their impact on behavior, followed by how task-based activity continues to add detail to these discoveries. We argue that person-specific and precision approaches demonstrate substantial promise in uncovering new details of the brain's functional organization and its relationship to behavior in many areas of cognitive neuroscience. We also discuss some current limitations in this new field and some new directions it may take.
Topics: Humans; Magnetic Resonance Imaging; Connectome; Reproducibility of Results; Brain; Neuroimaging
PubMed: 36030062
DOI: 10.1016/j.neuroimage.2022.119589 -
NeuroImage Jan 2017Neuroimaging increasingly exploits machine learning techniques in an attempt to achieve clinically relevant single-subject predictions. An alternative to machine... (Review)
Review
Neuroimaging increasingly exploits machine learning techniques in an attempt to achieve clinically relevant single-subject predictions. An alternative to machine learning, which tries to establish predictive links between features of the observed data and clinical variables, is the deployment of computational models for inferring on the (patho)physiological and cognitive mechanisms that generate behavioural and neuroimaging responses. This paper discusses the rationale behind a computational approach to neuroimaging-based single-subject inference, focusing on its potential for characterising disease mechanisms in individual subjects and mapping these characterisations to clinical predictions. Following an overview of two main approaches - Bayesian model selection and generative embedding - which can link computational models to individual predictions, we review how these methods accommodate heterogeneity in psychiatric and neurological spectrum disorders, help avoid erroneous interpretations of neuroimaging data, and establish a link between a mechanistic, model-based approach and the statistical perspectives afforded by machine learning.
Topics: Brain Diseases; Humans; Mental Disorders; Models, Theoretical; Neuroimaging
PubMed: 27346545
DOI: 10.1016/j.neuroimage.2016.06.038