High density event-related potential data acquisition in cognitive neuroscience.

PubMed

Slotnick, Scott D

2010-04-16

Functional magnetic resonance imaging (fMRI) is currently the standard method of evaluating brain function in the field of Cognitive Neuroscience, in part because fMRI data acquisition and analysis techniques are readily available. Because fMRI has excellent spatial resolution but poor temporal resolution, this method can only be used to identify the spatial location of brain activity associated with a given cognitive process (and reveals virtually nothing about the time course of brain activity). By contrast, event-related potential (ERP) recording, a method that is used much less frequently than fMRI, has excellent temporal resolution and thus can track rapid temporal modulations in neural activity. Unfortunately, ERPs are under utilized in Cognitive Neuroscience because data acquisition techniques are not readily available and low density ERP recording has poor spatial resolution. In an effort to foster the increased use of ERPs in Cognitive Neuroscience, the present article details key techniques involved in high density ERP data acquisition. Critically, high density ERPs offer the promise of excellent temporal resolution and good spatial resolution (or excellent spatial resolution if coupled with fMRI), which is necessary to capture the spatial-temporal dynamics of human brain function.

High-field fMRI unveils orientation columns in humans.

PubMed

Yacoub, Essa; Harel, Noam; Ugurbil, Kâmil

2008-07-29

Functional (f)MRI has revolutionized the field of human brain research. fMRI can noninvasively map the spatial architecture of brain function via localized increases in blood flow after sensory or cognitive stimulation. Recent advances in fMRI have led to enhanced sensitivity and spatial accuracy of the measured signals, indicating the possibility of detecting small neuronal ensembles that constitute fundamental computational units in the brain, such as cortical columns. Orientation columns in visual cortex are perhaps the best known example of such a functional organization in the brain. They cannot be discerned via anatomical characteristics, as with ocular dominance columns. Instead, the elucidation of their organization requires functional imaging methods. However, because of insufficient sensitivity, spatial accuracy, and image resolution of the available mapping techniques, thus far, they have not been detected in humans. Here, we demonstrate, by using high-field (7-T) fMRI, the existence and spatial features of orientation- selective columns in humans. Striking similarities were found with the known spatial features of these columns in monkeys. In addition, we found that a larger number of orientation columns are devoted to processing orientations around 90 degrees (vertical stimuli with horizontal motion), whereas relatively similar fMRI signal changes were observed across any given active column. With the current proliferation of high-field MRI systems and constant evolution of fMRI techniques, this study heralds the exciting prospect of exploring unmapped and/or unknown columnar level functional organizations in the human brain.

State of the art MRI in head and neck cancer.

PubMed

Dai, Y L; King, A D

2018-01-01

Head and neck cancer affects more than 11,000 new patients per year in the UK 1 and imaging has an important role in the diagnosis, treatment planning, and assessment, and post-treatment surveillance of these patients. The anatomical detail produced by magnetic resonance imaging (MRI) is ideally suited to staging and follow-up of primary tumours and cervical nodal metastases in the head and neck; however, anatomical images have limitations in cancer imaging and so increasingly functional-based MRI techniques, which provide molecular, metabolic, and physiological information, are being incorporated into MRI protocols. This article reviews the state of the art of these functional MRI techniques with emphasis on those that are most relevant to the current management of patients with head and neck cancer. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Advantages in functional imaging of the brain.

PubMed

Mier, Walter; Mier, Daniela

2015-01-01

As neuronal pathologies cause only minor morphological alterations, molecular imaging techniques are a prerequisite for the study of diseases of the brain. The development of molecular probes that specifically bind biochemical markers and the advances of instrumentation have revolutionized the possibilities to gain insight into the human brain organization and beyond this-visualize structure-function and brain-behavior relationships. The review describes the development and current applications of functional brain imaging techniques with a focus on applications in psychiatry. A historical overview of the development of functional imaging is followed by the portrayal of the principles and applications of positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), two key molecular imaging techniques that have revolutionized the ability to image molecular processes in the brain. We conclude that the juxtaposition of PET and fMRI in hybrid PET/MRI scanners enhances the significance of both modalities for research in neurology and psychiatry and might pave the way for a new area of personalized medicine.

Fusing DTI and FMRI Data: A Survey of Methods and Applications

PubMed Central

Zhu, Dajiang; Zhang, Tuo; Jiang, Xi; Hu, Xintao; Chen, Hanbo; Yang, Ning; Lv, Jinglei; Han, Junwei; Guo, Lei; Liu, Tianming

2014-01-01

The relationship between brain structure and function has been one of the centers of research in neuroimaging for decades. In recent years, diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) techniques have been widely available and popular in cognitive and clinical neurosciences for examining the brain’s white matter (WM) micro-structures and gray matter (GM) functions, respectively. Given the intrinsic integration of WM/GM and the complementary information embedded in DTI/fMRI data, it is natural and well-justified to combine these two neuroimaging modalities together to investigate brain structure and function and their relationships simultaneously. In the past decade, there have been remarkable achievements of DTI/fMRI fusion methods and applications in neuroimaging and human brain mapping community. This survey paper aims to review recent advancements on methodologies and applications in incorporating multimodal DTI and fMRI data, and offer our perspectives on future research directions. We envision that effective fusion of DTI/fMRI techniques will play increasingly important roles in neuroimaging and brain sciences in the years to come. PMID:24103849

Clinical utility of resting-state functional connectivity magnetic resonance imaging for mood and cognitive disorders.

PubMed

Takamura, T; Hanakawa, T

2017-07-01

Although functional magnetic resonance imaging (fMRI) has long been used to assess task-related brain activity in neuropsychiatric disorders, it has not yet become a widely available clinical tool. Resting-state fMRI (rs-fMRI) has been the subject of recent attention in the fields of basic and clinical neuroimaging research. This method enables investigation of the functional organization of the brain and alterations of resting-state networks (RSNs) in patients with neuropsychiatric disorders. Rs-fMRI does not require participants to perform a demanding task, in contrast to task fMRI, which often requires participants to follow complex instructions. Rs-fMRI has a number of advantages over task fMRI for application with neuropsychiatric patients, for example, although applications of task fMR to participants for healthy are easy. However, it is difficult to apply these applications to patients with psychiatric and neurological disorders, because they may have difficulty in performing demanding cognitive task. Here, we review the basic methodology and analysis techniques relevant to clinical studies, and the clinical applications of the technique for examining neuropsychiatric disorders, focusing on mood disorders (major depressive disorder and bipolar disorder) and dementia (Alzheimer's disease and mild cognitive impairment).

Functional Magnetic Resonance Imaging and Functional Near-Infrared Spectroscopy: Insights from Combined Recording Studies

PubMed Central

Scarapicchia, Vanessa; Brown, Cassandra; Mayo, Chantel; Gawryluk, Jodie R.

2017-01-01

Although blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) is a widely available, non-invasive technique that offers excellent spatial resolution, it remains limited by practical constraints imposed by the scanner environment. More recently, functional near infrared spectroscopy (fNIRS) has emerged as an alternative hemodynamic-based approach that possesses a number of strengths where fMRI is limited, most notably in portability and higher tolerance for motion. To date, fNIRS has shown promise in its ability to shed light on the functioning of the human brain in populations and contexts previously inaccessible to fMRI. Notable contributions include infant neuroimaging studies and studies examining full-body behaviors, such as exercise. However, much like fMRI, fNIRS has technical constraints that have limited its application to clinical settings, including a lower spatial resolution and limited depth of recording. Thus, by combining fMRI and fNIRS in such a way that the two methods complement each other, a multimodal imaging approach may allow for more complex research paradigms than is feasible with either technique alone. In light of these issues, the purpose of the current review is to: (1) provide an overview of fMRI and fNIRS and their associated strengths and limitations; (2) review existing combined fMRI-fNIRS recording studies; and (3) discuss how their combined use in future research practices may aid in advancing modern investigations of human brain function. PMID:28867998

Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI.

PubMed

Chu, Shu-Hsien; Parhi, Keshab K; Lenglet, Christophe

2018-03-16

A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.

Functional Cardiac Magnetic Resonance Imaging (MRI) in the Assessment of Myocardial Viability and Perfusion

PubMed Central

2003-01-01

Executive Summary Objective The objective of this health technology policy assessment was to determine the effectiveness safety and cost-effectiveness of using functional cardiac magnetic resonance imaging (MRI) for the assessment of myocardial viability and perfusion in patients with coronary artery disease and left ventricular dysfunction. Results Functional MRI has become increasingly investigated as a noninvasive method for assessing myocardial viability and perfusion. Most patients in the published literature have mild to moderate impaired LV function. It is possible that the severity of LV dysfunction may be an important factor that can alter the diagnostic accuracy of imaging techniques. There is some evidence of comparable or better performance of functional cardiac MRI for the assessment of myocardial viability and perfusion compared with other imaging techniques. However limitations to most of the studies included: Functional cardiac MRI studies that assess myocardial viability and perfusion have had small sample sizes. Some studies assessed myocardial viability/perfusion in patients who had already undergone revascularization, or excluded patients with a prior MI (Schwitter et al., 2001). Lack of explicit detail of patient recruitment. Patients with LVEF >35%. Interstudy variability in post MI imaging time(including acute or chronic MI), when patients with a prior MI were included. Poor interobserver agreement (kappa statistic) in the interpretation of the results. Traditionally, 0.80 is considered “good”. Cardiac MRI measurement of myocardial perfusion to as an adjunct tool to help diagnose CAD (prior to a definitive coronary angiography) has also been examined in some studies, with methodological limitations, yielding comparable results. Many studies examining myocardial viability and perfusion report on the accuracy of imaging methods with limited data on long-term patient outcome and management. Kim et al. (2000) revealed that the transmural extent of hyperenhancement was significantly related to the likelihood of improvement in contractility after revascularization. However, the LVEF in the patient population was 43% prior to revascularization. It is important to know whether the technique has the same degree of accuracy in patients who have more severe LV dysfunction and who would most benefit from an assessment of myocardial viability. “Substantial” viability used as a measure of a patient’s ability to recover after revascularization has not been definitively reported (how much viability is enough?). Patients with severe LV dysfunction are more likely to have mixtures of surviving myocardium, including normal, infarcted, stunned and hibernating myocardium (Cowley et al., 1999). This may lead to a lack of homogeneity of response to testing and to revascularization and contribute to inter- and intra-study differences. There is a need for a large prospective study with adequate follow-up time for patients with CAD and LV dysfunction (LVEF<35%) comparing MRI and an alternate imaging technique. There is some evidence that MRI has comparable sensitivity, specificity and accuracy to PET for determining myocardial viability. However, there is a lack of evidence comparing the accuracy of these two techniques to predict LV function recovery. In addition, some studies refer to PET as the gold standard for the assessment of myocardial viability. Therefore, PET may be an ideal noninvasive imaging comparator to MRI for a prospective study with follow-up. To date, there is a lack of cost-effectiveness analyses (or any economic analyses) of functional cardiac MRI versus an alternate noninvasive imaging method for the assessment of myocardial viability/perfusion. Conclusion There is some evidence that the accuracy of functional cardiac MRI compares favourably with alternate imaging techniques for the assessment of myocardial viability and perfusion. There is insufficient evidence whether functional cardiac MRI can better select which patients [who have CAD and severe LV dysfunction (LVEF <35%)] may benefit from revascularization compared with an alternate noninvasive imaging technology. There is insufficient evidence whether functional cardiac MRI can better select which patients should proceed to invasive coronary angiography for the definitive diagnosis of CAD, compared with an alternate noninvasive imaging technology. There is a need for a large prospective (potentially multicentre) study with adequate follow-up time for patients with CAD and LV dysfunction (LVEF<35%) comparing MRI and PET. Since longer follow-up time may be associated with restenosis or graft occlusion, it has been suggested to have serial measurements after revascularization (Cowley et al., 1999). PMID:23074446

Ridding fMRI data of motion-related influences: Removal of signals with distinct spatial and physical bases in multiecho data.

PubMed

Power, Jonathan D; Plitt, Mark; Gotts, Stephen J; Kundu, Prantik; Voon, Valerie; Bandettini, Peter A; Martin, Alex

2018-02-27

"Functional connectivity" techniques are commonplace tools for studying brain organization. A critical element of these analyses is to distinguish variance due to neurobiological signals from variance due to nonneurobiological signals. Multiecho fMRI techniques are a promising means for making such distinctions based on signal decay properties. Here, we report that multiecho fMRI techniques enable excellent removal of certain kinds of artifactual variance, namely, spatially focal artifacts due to motion. By removing these artifacts, multiecho techniques reveal frequent, large-amplitude blood oxygen level-dependent (BOLD) signal changes present across all gray matter that are also linked to motion. These whole-brain BOLD signals could reflect widespread neural processes or other processes, such as alterations in blood partial pressure of carbon dioxide (pCO 2 ) due to ventilation changes. By acquiring multiecho data while monitoring breathing, we demonstrate that whole-brain BOLD signals in the resting state are often caused by changes in breathing that co-occur with head motion. These widespread respiratory fMRI signals cannot be isolated from neurobiological signals by multiecho techniques because they occur via the same BOLD mechanism. Respiratory signals must therefore be removed by some other technique to isolate neurobiological covariance in fMRI time series. Several methods for removing global artifacts are demonstrated and compared, and were found to yield fMRI time series essentially free of motion-related influences. These results identify two kinds of motion-associated fMRI variance, with different physical mechanisms and spatial profiles, each of which strongly and differentially influences functional connectivity patterns. Distance-dependent patterns in covariance are nearly entirely attributable to non-BOLD artifacts.

Comprehensive Review on Magnetic Resonance Imaging in Alzheimer's Disease.

PubMed

Dona, Olga; Thompson, Jeff; Druchok, Cheryl

2016-01-01

Alzheimer's disease (AD) is the most common cause of dementia in the elderly. However, definitive diagnosis of AD is only achievable postmortem and currently relies on clinical neurological evaluation. Magnetic resonance imaging (MRI) can evaluate brain changes typical of AD, including brain atrophy, presence of amyloid β (Aβ) plaques, and functional and biochemical abnormalities. Structural MRI (sMRI) has historically been used to assess the inherent brain atrophy present in AD. However, new techniques have recently emerged that have refined sMRI into a more precise tool to quantify the thickness and volume of AD-sensitive cerebral structures. Aβ plaques, a defining pathology of AD, are widely believed to contribute to the progressive cognitive decline in AD, but accurate assessment is only possible on autopsy. In vivo MRI of plaques, although currently limited to mouse models of AD, is a very promising technique. Measuring changes in activation and connectivity in AD-specific regions of the brain can be performed with functional MRI (fMRI). To help distinguish AD from diseases with similar symptoms, magnetic resonance spectroscopy (MRS) can be used to look for differing metabolite concentrations in vivo. Together, these MR techniques, evaluating various brain changes typical of AD, may help to provide a more definitive diagnosis and ease the assessment of the disease over time, noninvasively.

MRI Guided Brain Stimulation without the Use of a Neuronavigation System

PubMed Central

Vaghefi, Ehsan; Byblow, Winston D.; Stinear, Cathy M.; Thompson, Benjamin

2015-01-01

A key issue in the field of noninvasive brain stimulation (NIBS) is the accurate localization of scalp positions that correspond to targeted cortical areas. The current gold standard is to combine structural and functional brain imaging with a commercially available “neuronavigation” system. However, neuronavigation systems are not commonplace outside of specialized research environments. Here we describe a technique that allows for the use of participant-specific functional and structural MRI data to guide NIBS without a neuronavigation system. Surface mesh representations of the head were generated using Brain Voyager and vectors linking key anatomical landmarks were drawn on the mesh. Our technique was then used to calculate the precise distances on the scalp corresponding to these vectors. These calculations were verified using actual measurements of the head and the technique was used to identify a scalp position corresponding to a brain area localized using functional MRI. PMID:26413537

Intraoperative visualisation of functional structures facilitates safe frameless stereotactic biopsy in the motor eloquent regions of the brain.

PubMed

Zhang, Jia-Shu; Qu, Ling; Wang, Qun; Jin, Wei; Hou, Yuan-Zheng; Sun, Guo-Chen; Li, Fang-Ye; Yu, Xin-Guang; Xu, Ban-Nan; Chen, Xiao-Lei

2017-12-20

For stereotactic brain biopsy involving motor eloquent regions, the surgical objective is to enhance diagnostic yield and preserve neurological function. To achieve this aim, we implemented functional neuro-navigation and intraoperative magnetic resonance imaging (iMRI) into the biopsy procedure. The impact of this integrated technique on the surgical outcome and postoperative neurological function was investigated and evaluated. Thirty nine patients with lesions involving motor eloquent structures underwent frameless stereotactic biopsy assisted by functional neuro-navigation and iMRI. Intraoperative visualisation was realised by integrating anatomical and functional information into a navigation framework to improve biopsy trajectories and preserve eloquent structures. iMRI was conducted to guarantee the biopsy accuracy and detect intraoperative complications. The perioperative change of motor function and biopsy error before and after iMRI were recorded, and the role of functional information in trajectory selection and the relationship between the distance from sampling site to nearby eloquent structures and the neurological deterioration were further analyzed. Functional neuro-navigation helped modify the original trajectories and sampling sites in 35.90% (16/39) of cases to avoid the damage of eloquent structures. Even though all the lesions were high-risk of causing neurological deficits, no significant difference was found between preoperative and postoperative muscle strength. After data analysis, 3mm was supposed to be the safe distance for avoiding transient neurological deterioration. During surgery, the use of iMRI significantly reduced the biopsy errors (p = 0.042) and potentially increased the diagnostic yield from 84.62% (33/39) to 94.87% (37/39). Moreover, iMRI detected intraoperative haemorrhage in 5.13% (2/39) of patients, all of them benefited from the intraoperative strategies based on iMRI findings. Intraoperative visualisation of functional structures could be a feasible, safe and effective technique. Combined with intraoperative high-field MRI, it contributed to enhance the biopsy accuracy and lower neurological complications in stereotactic brain biopsy involving motor eloquent areas.

Biology and therapy of fibromyalgia. Functional magnetic resonance imaging findings in fibromyalgia

PubMed Central

Williams, David A; Gracely, Richard H

2006-01-01

Techniques in neuroimaging such as functional magnetic resonance imaging (fMRI) have helped to provide insights into the role of supraspinal mechanisms in pain perception. This review focuses on studies that have applied fMRI in an attempt to gain a better understanding of the mechanisms involved in the processing of pain associated with fibromyalgia. This article provides an overview of the nociceptive system as it functions normally, reviews functional brain imaging methods, and integrates the existing literature utilizing fMRI to study central pain mechanisms in fibromyalgia. PMID:17254318

Functional MRI in the Investigation of Blast-Related Traumatic Brain Injury

PubMed Central

Graner, John; Oakes, Terrence R.; French, Louis M.; Riedy, Gerard

2012-01-01

This review focuses on the application of functional magnetic resonance imaging (fMRI) to the investigation of blast-related traumatic brain injury (bTBI). Relatively little is known about the exact mechanisms of neurophysiological injury and pathological and functional sequelae of bTBI. Furthermore, in mild bTBI, standard anatomical imaging techniques (MRI and computed tomography) generally fail to show focal lesions and most of the symptoms present as subjective clinical functional deficits. Therefore, an objective test of brain functionality has great potential to aid in patient diagnosis and provide a sensitive measurement to monitor disease progression and treatment. The goal of this review is to highlight the relevant body of blast-related TBI literature and present suggestions and considerations in the development of fMRI studies for the investigation of bTBI. The review begins with a summary of recent bTBI publications followed by discussions of various elements of blast-related injury. Brief reviews of some fMRI techniques that focus on mental processes commonly disrupted by bTBI, including working memory, selective attention, and emotional processing, are presented in addition to a short review of resting state fMRI. Potential strengths and weaknesses of these approaches as regards bTBI are discussed. Finally, this review presents considerations that must be made when designing fMRI studies for bTBI populations, given the heterogeneous nature of bTBI and its high rate of comorbidity with other physical and psychological injuries. PMID:23460082

Real-time magnetic resonance imaging of cardiac function and flow—recent progress

PubMed Central

Zhang, Shuo; Joseph, Arun A.; Voit, Dirk; Schaetz, Sebastian; Merboldt, Klaus-Dietmar; Unterberg-Buchwald, Christina; Hennemuth, Anja; Lotz, Joachim

2014-01-01

Cardiac structure, function and flow are most commonly studied by ultrasound, X-ray and magnetic resonance imaging (MRI) techniques. However, cardiovascular MRI is hitherto limited to electrocardiogram (ECG)-synchronized acquisitions and therefore often results in compromised quality for patients with arrhythmias or inabilities to comply with requested protocols—especially with breath-holding. Recent advances in the development of novel real-time MRI techniques now offer dynamic imaging of the heart and major vessels with high spatial and temporal resolution, so that examinations may be performed without the need for ECG synchronization and during free breathing. This article provides an overview of technical achievements, physiological validations, preliminary patient studies and translational aspects for a future clinical scenario of cardiovascular MRI in real time. PMID:25392819

Comparative studies of brain activation with MEG and functional MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

George, J.S.; Aine, C.J.; Sanders, J.A.

The past two years have witnessed the emergence of MRI as a functional imaging methodology. Initial demonstrations involved the injection of a paramagnetic contrast agent and required ultrafast echo planar imaging capability to adequately resolve the passage of the injected bolus. By measuring the local reduction in image intensity due to magnetic susceptibility, it was possible to calculate blood volume, which changes as a function of neural activation. Later developments have exploited endogenous contrast mechanisms to monitor changes in blood volume or in venous blood oxygen content. Recently, we and others have demonstrated that it is possible to make suchmore » measurements in a clinical imager, suggesting that the large installed base of such machines might be utilized for functional imaging. Although it is likely that functional MRI (fMRI) will subsume some of the clinical and basic neuroscience applications now touted for MEG, it is also clear that these techniques offer different largely complementary, capabilities. At the very least, it is useful to compare and cross-validate the activation maps produced by these techniques. Such studies will be valuable as a check on results of neuromagnetic distributed current reconstructions and will allow better characterization of the relationship between neurophysiological activation and associated hemodynamic changes. A more exciting prospect is the development of analyses that combine information from the two modalities to produce a better description of underlying neural activity than is possible with either technique in isolation. In this paper we describe some results from initial comparative studies and outline several techniques that can be used to treat MEG and fMRI data within a unified computational framework.« less

MR measures of renal perfusion, oxygen bioavailability and total renal blood flow in a porcine model: noninvasive regional assessment of renal function.

PubMed

Wentland, Andrew L; Artz, Nathan S; Fain, Sean B; Grist, Thomas M; Djamali, Arjang; Sadowski, Elizabeth A

2012-01-01

Magnetic resonance imaging (MRI) may be a useful adjunct to current methods of evaluating renal function. MRI is a noninvasive imaging modality that has the ability to evaluate the kidneys regionally, which is lacking in current clinical methods. Other investigators have evaluated renal function with MRI-based measurements, such as with techniques to measure cortical and medullary perfusion, oxygen bioavailability and total renal blood flow (TRBF). However, use of all three techniques simultaneously, and therefore the relationships between these MRI-derived functional parameters, have not been reported previously. To evaluate the ability of these MRI techniques to track changes in renal function, we scanned 11 swine during a state of hyperperfusion with acetylcholine and a saline bolus and subsequently scanned during a state of hypoperfusion with the prolonged use of isoflurane anesthesia. For each time point, measurements of perfusion, oxygen bioavailability and TRBF were acquired. Measurements of perfusion and oxygen bioavailability were compared with measurements of TRBF for all swine across all time points. Cortical perfusion, cortical oxygen bioavailability, medullary oxygen bioavailability and TRBF significantly increased with the acetylcholine challenge. Cortical perfusion, medullary perfusion, cortical oxygen bioavailability and TRBF significantly decreased during isoflurane anesthesia. Cortical perfusion (Spearman's correlation coefficient = 0.68; P < 1 × 10(-6)) and oxygen bioavailability (Spearman's correlation coefficient = -0.60; P < 0.0001) correlated significantly with TRBF, whereas medullary perfusion and oxygen bioavailability did not correlate with TRBF. Our results demonstrate expected changes given the pharmacologically induced changes in renal function. Maintenance of the medullary oxygen bioavailability in low blood flow states may reflect the autoregulation particular to this region of the kidney. The ability to non-invasively measure all three parameters of kidney function in a single MRI examination and to evaluate the relationships between these functional parameters is potentially useful for evaluating the state of the human kidneys in situ in future studies.

Anatomo-clinical overlapping maps (AnaCOM): a new method to create anatomo-functional maps from neuropsychological tests and structural MRI scan of subjects with brain lesions

NASA Astrophysics Data System (ADS)

Kinkingnehun, Serge R. J.; du Boisgueheneuc, Foucaud; Golmard, Jean-Louis; Zhang, Sandy X.; Levy, Richard; Dubois, Bruno

2004-04-01

We have developed a new technique to analyze correlations between brain anatomy and its neurological functions. The technique is based on the anatomic MRI of patients with brain lesions who are administered neuropsychological tests. Brain lesions of the MRI scans are first manually segmented. The MRI volumes are then normalized to a reference map, using the segmented area as a mask. After normalization, the brain lesions of the MRI are segmented again in order to redefine the border of the lesions in the context of the normalized brain. Once the MRI is segmented, the patient's score on the neuropsychological test is assigned to each voxel in the lesioned area, while the rest of the voxels of the image are set to 0. Subsequently, the individual patient's MRI images are superimposed, and each voxel is reassigned the average score of the patients who have a lesion at that voxel. A threshold is applied to remove regions having less than three overlaps. This process leads to an anatomo-functional map that links brain areas to functional loss. Other maps can be created to aid in analyzing the functional maps, such as one that indicates the 95% confidence interval of the averaged scores for each area. This anatomo-clinical overlapping map (AnaCOM) method was used to obtain functional maps from patients with lesions in the superior frontal gyrus. By finding particular subregions more responsible for a particular deficit, this method can generate new hypotheses to be tested by conventional group methods.

The role of magnetic resonance imaging techniques in evaluation and management of the idiopathic inflammatory myopathies.

PubMed

Day, Jessica; Patel, Sandy; Limaye, Vidya

2017-04-01

Magnetic resonance imaging (MRI) is an important tool in the evaluation of neuromuscular disorders. MRI accurately demonstrates muscle oedema, atrophy, subcutaneous pathology and fatty infiltration and also highlights the distribution of muscle involvement. This review examines the role of MRI in evaluation of the idiopathic inflammatory myopathies (IIMs), a heterogeneous group of autoimmune conditions characterised by muscle inflammation and a variety of extra-muscular manifestations. MRI has a clear role in aiding diagnosis of these conditions, guiding muscle biopsy, differentiating subtypes of IIM using a pattern-based approach, and monitoring disease activity in a longitudinal fashion. Whole body MRI is an emerging technique that offers several advantages over regional MRI, but is not currently widely available. We will also consider newer MRI techniques which provide detailed information regarding the metabolism, function and structure of muscle, although their use is restricted to research purposes at present. Copyright © 2017 Elsevier Inc. All rights reserved.

Neural and Behavioral Sequelae of Blast-Related Traumatic Brain Injury

DTIC Science & Technology

2012-11-01

testing and advanced MRI techniques [task-activated functional MRI (fMRI) and diffusion tensor imaging ( DTI )] to gain a comprehensive understanding of... DTI fiber tracking) and neurobehavioral testing (computerized assessment and standard neuropsychological testing) on 60 chronic trauma patients: 15...data analysis. 15. SUBJECT TERMS Blast-related traumatic brain injury (TBI), fMRI, DTI , cognition 16. SECURITY CLASSIFICATION OF: 17. LIMITATION

Lying about Facial Recognition: An fMRI Study

ERIC Educational Resources Information Center

Bhatt, S.; Mbwana, J.; Adeyemo, A.; Sawyer, A.; Hailu, A.; VanMeter, J.

2009-01-01

Novel deception detection techniques have been in creation for centuries. Functional magnetic resonance imaging (fMRI) is a neuroscience technology that non-invasively measures brain activity associated with behavior and cognition. A number of investigators have explored the utilization and efficiency of fMRI in deception detection. In this study,…

Added Value of Assessing Adnexal Masses with Advanced MRI Techniques

PubMed Central

Thomassin-Naggara, I.; Balvay, D.; Rockall, A.; Carette, M. F.; Ballester, M.; Darai, E.; Bazot, M.

2015-01-01

This review will present the added value of perfusion and diffusion MR sequences to characterize adnexal masses. These two functional MR techniques are readily available in routine clinical practice. We will describe the acquisition parameters and a method of analysis to optimize their added value compared with conventional images. We will then propose a model of interpretation that combines the anatomical and morphological information from conventional MRI sequences with the functional information provided by perfusion and diffusion weighted sequences. PMID:26413542

A feature-based approach to combine functional MRI, structural MRI and EEG brain imaging data.

PubMed

Calhoun, V; Adali, T; Liu, J

2006-01-01

The acquisition of multiple brain imaging types for a given study is a very common practice. However these data are typically examined in separate analyses, rather than in a combined model. We propose a novel methodology to perform joint independent component analysis across image modalities, including structural MRI data, functional MRI activation data and EEG data, and to visualize the results via a joint histogram visualization technique. Evaluation of which combination of fused data is most useful is determined by using the Kullback-Leibler divergence. We demonstrate our method on a data set composed of functional MRI data from two tasks, structural MRI data, and EEG data collected on patients with schizophrenia and healthy controls. We show that combining data types can improve our ability to distinguish differences between groups.

Identification of discrete functional subregions of the human periaqueductal gray

PubMed Central

Satpute, Ajay B.; Wager, Tor D.; Cohen-Adad, Julien; Bianciardi, Marta; Choi, Ji-Kyung; Buhle, Jason T.; Wald, Lawrence L.; Barrett, Lisa Feldman

2013-01-01

The midbrain periaqueductal gray (PAG) region is organized into distinct subregions that coordinate survival-related responses during threat and stress [Bandler R, Keay KA, Floyd N, Price J (2000) Brain Res 53 (1):95–104]. To examine PAG function in humans, researchers have relied primarily on functional MRI (fMRI), but technological and methodological limitations have prevented researchers from localizing responses to different PAG subregions. We used high-field strength (7-T) fMRI techniques to image the PAG at high resolution (0.75 mm isotropic), which was critical for dissociating the PAG from the greater signal variability in the aqueduct. Activation while participants were exposed to emotionally aversive images segregated into subregions of the PAG along both dorsal/ventral and rostral/caudal axes. In the rostral PAG, activity was localized to lateral and dorsomedial subregions. In caudal PAG, activity was localized to the ventrolateral region. This shifting pattern of activity from dorsal to ventral PAG along the rostrocaudal axis mirrors structural and functional neurobiological observations in nonhuman animals. Activity in lateral and ventrolateral subregions also grouped with distinct emotional experiences (e.g., anger and sadness) in a factor analysis, suggesting that each subregion participates in distinct functional circuitry. This study establishes the use of high-field strength fMRI as a promising technique for revealing the functional architecture of the PAG. The techniques developed here also may be extended to investigate the functional roles of other brainstem nuclei. PMID:24082116

Neural basis of exertional fatigue in the heat: A review of magnetic resonance imaging methods.

PubMed

Tan, X R; Low, I C C; Stephenson, M C; Soong, T W; Lee, J K W

2018-03-01

The central nervous system, specifically the brain, is implicated in the development of exertional fatigue under a hot environment. Diverse neuroimaging techniques have been used to visualize the brain activity during or after exercise. Notably, the use of magnetic resonance imaging (MRI) has become prevalent due to its excellent spatial resolution and versatility. This review evaluates the significance and limitations of various brain MRI techniques in exercise studies-brain volumetric analysis, functional MRI, functional connectivity MRI, and arterial spin labeling. The review aims to provide a summary on the neural basis of exertional fatigue and proposes future directions for brain MRI studies. A systematic literature search was performed where a total of thirty-seven brain MRI studies associated with exercise, fatigue, or related physiological factors were reviewed. The findings suggest that with moderate dehydration, there is a decrease in total brain volume accompanied with expansion of ventricular volume. With exercise fatigue, there is increased activation of sensorimotor and cognitive brain areas, increased thalamo-insular activation and decreased interhemispheric connectivity in motor cortex. Under passive hyperthermia, there are regional changes in cerebral perfusion, a reduction in local connectivity in functional brain networks and an impairment to executive function. Current literature suggests that the brain structure and function are influenced by exercise, fatigue, and related physiological perturbations. However, there is still a dearth of knowledge and it is hoped that through understanding of MRI advantages and limitations, future studies will shed light on the central origin of exertional fatigue in the heat. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training

PubMed Central

Sherwood, Matthew S.; Diller, Emily E.; Ey, Elizabeth; Ganapathy, Subhashini; Nelson, Jeremy T.; Parker, Jason G.

2017-01-01

Neurologic disorders are characterized by abnormal cellular-, molecular-, and circuit-level functions in the brain. New methods to induce and control neuroplastic processes and correct abnormal function, or even shift functions from damaged tissue to physiologically healthy brain regions, hold the potential to dramatically improve overall health. Of the current neuroplastic interventions in development, neurofeedback training (NFT) from functional Magnetic Resonance Imaging (fMRI) has the advantages of being completely non-invasive, non-pharmacologic, and spatially localized to target brain regions, as well as having no known side effects. Furthermore, NFT techniques, initially developed using fMRI, can often be translated to exercises that can be performed outside of the scanner without the aid of medical professionals or sophisticated medical equipment. In fMRI NFT, the fMRI signal is measured from specific regions of the brain, processed, and presented to the participant in real-time. Through training, self-directed mental processing techniques, that regulate this signal and its underlying neurophysiologic correlates, are developed. FMRI NFT has been used to train volitional control over a wide range of brain regions with implications for several different cognitive, behavioral, and motor systems. Additionally, fMRI NFT has shown promise in a broad range of applications such as the treatment of neurologic disorders and the augmentation of baseline human performance. In this article, we present an fMRI NFT protocol developed at our institution for modulation of both healthy and abnormal brain function, as well as examples of using the method to target both cognitive and auditory regions of the brain. PMID:28872110

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training.

PubMed

Sherwood, Matthew S; Diller, Emily E; Ey, Elizabeth; Ganapathy, Subhashini; Nelson, Jeremy T; Parker, Jason G

2017-08-24

Neurologic disorders are characterized by abnormal cellular-, molecular-, and circuit-level functions in the brain. New methods to induce and control neuroplastic processes and correct abnormal function, or even shift functions from damaged tissue to physiologically healthy brain regions, hold the potential to dramatically improve overall health. Of the current neuroplastic interventions in development, neurofeedback training (NFT) from functional Magnetic Resonance Imaging (fMRI) has the advantages of being completely non-invasive, non-pharmacologic, and spatially localized to target brain regions, as well as having no known side effects. Furthermore, NFT techniques, initially developed using fMRI, can often be translated to exercises that can be performed outside of the scanner without the aid of medical professionals or sophisticated medical equipment. In fMRI NFT, the fMRI signal is measured from specific regions of the brain, processed, and presented to the participant in real-time. Through training, self-directed mental processing techniques, that regulate this signal and its underlying neurophysiologic correlates, are developed. FMRI NFT has been used to train volitional control over a wide range of brain regions with implications for several different cognitive, behavioral, and motor systems. Additionally, fMRI NFT has shown promise in a broad range of applications such as the treatment of neurologic disorders and the augmentation of baseline human performance. In this article, we present an fMRI NFT protocol developed at our institution for modulation of both healthy and abnormal brain function, as well as examples of using the method to target both cognitive and auditory regions of the brain.

Calibrated LCD/TFT stimulus presentation for visual psychophysics in fMRI.

PubMed

Strasburger, H; Wüstenberg, T; Jäncke, L

2002-11-15

Standard projection techniques using liquid crystal (LCD) or thin-film transistor (TFT) technology show drastic distortions in luminance and contrast characteristics across the screen and across grey levels. Common luminance measurement and calibration techniques are not applicable in the vicinity of MRI scanners. With the aid of a fibre optic, we measured screen luminances for the full space of screen position and image grey values and on that basis developed a compensation technique that involves both luminance homogenisation and position-dependent gamma correction. By the technique described, images displayed to a subject in functional MRI can be specified with high precision by a matrix of desired luminance values rather than by local grey value.

New trend of MRI diagnosis based on the function and metabolism in the central nervous system.

PubMed

Harada, Masafumi

2006-08-01

The movement of a subject is a major problem in MRI experiments and diagnosis. At first, this review introduces a new technology named the "Propeller Technique" which can improve the motion artifact by changing the data sampling method in the K trajectory. Our experience of a case who underwent measurement by Propeller technique is reported and the effect of this technique is explained. One of the recent hot topics is the appearance of the clinical 3T MR instrument, with its characteristic differences from that at 1.5T. The advantage of 3T is that it facilitates the evaluation of functional and metabolic information using MR spectroscopy (MRS) and functional MRI. The application of proton MRS in clinical cases is shown and the standard method to use proton MRS in a clinical setting is demonstrated. Furthermore, the new techniques, which can measure important metabolites in small amount such as neurotransmitters, was developed using a high signal to noise ratio and frequency resolution, which are advantages of 3T.

SEOM-SERAM-SEMNIM guidelines on the use of functional and molecular imaging techniques in advanced non-small-cell lung cancer.

PubMed

Fernández Pérez, G; Sánchez Escribano, R; García Vicente, A M; Luna Alcalá, A; Ceballos Viro, J; Delgado Bolton, R C; Vilanova Busquets, J C; Sánchez Rovira, P; Fierro Alanis, M P; García Figueiras, R; Alés Martínez, J E

2018-05-25

Imaging in oncology is an essential tool for patient management but its potential is being profoundly underutilized. Each of the techniques used in the diagnostic process also conveys functional information that can be relevant in treatment decision making. New imaging algorithms and techniques enhance our knowledge about the phenotype of the tumor and its potential response to different therapies. Functional imaging can be defined as the one that provides information beyond the purely morphological data, and include all the techniques that make it possible to measure specific physiological functions of the tumor, whereas molecular imaging would include techniques that allow us to measure metabolic changes. Functional and molecular techniques included in this document are based on multi-detector computed tomography (CT), 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET), magnetic resonance imaging (MRI), and hybrid equipments, integrating PET with CT (PET/CT) or MRI (PET-MRI). Lung cancer is one of the most frequent and deadly tumors although survival is increasing thanks to advances in diagnostic methods and new treatments. This increased survival poises challenges in terms of proper follow-up and definitions of response and progression, as exemplified by immune therapy-related pseudoprogression. In this consensus document, the use of functional and molecular imaging techniques will be addressed to exploit their current potential and explore future applications in the diagnosis, evaluation of response and detection of recurrence of advanced NSCLC. Copyright © 2018 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

Neural and Behavioral Sequelae of Blast-Related Traumatic Brain Injury

DTIC Science & Technology

2012-09-01

fMRI, DTI , cognition 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON USAMRMC a...techniques [task-activated functional MRI (fMRI) and diffusion tensor imaging ( DTI )] to gain a comprehensive understanding of the neural changes...orthopedic injuries. We accomplished this goal by conducting advanced neuroimaging (task-activated fMRI and DTI fiber tracking) and neurobehavioral

The Potential for an Enhanced Role for MRI in Radiation-therapy Treatment Planning

PubMed Central

Metcalfe, P.; Liney, G. P.; Holloway, L.; Walker, A.; Barton, M.; Delaney, G. P.; Vinod, S.; Tomé, W.

2013-01-01

The exquisite soft-tissue contrast of magnetic resonance imaging (MRI) has meant that the technique is having an increasing role in contouring the gross tumor volume (GTV) and organs at risk (OAR) in radiation therapy treatment planning systems (TPS). MRI-planning scans from diagnostic MRI scanners are currently incorporated into the planning process by being registered to CT data. The soft-tissue data from the MRI provides target outline guidance and the CT provides a solid geometric and electron density map for accurate dose calculation on the TPS computer. There is increasing interest in MRI machine placement in radiotherapy clinics as an adjunct to CT simulators. Most vendors now offer 70 cm bores with flat couch inserts and specialised RF coil designs. We would refer to these devices as MR-simulators. There is also research into the future application of MR-simulators independent of CT and as in-room image-guidance devices. It is within the background of this increased interest in the utility of MRI in radiotherapy treatment planning that this paper is couched. The paper outlines publications that deal with standard MRI sequences used in current clinical practice. It then discusses the potential for using processed functional diffusion maps (fDM) derived from diffusion weighted image sequences in tracking tumor activity and tumor recurrence. Next, this paper reviews publications that describe the use of MRI in patient-management applications that may, in turn, be relevant to radiotherapy treatment planning. The review briefly discusses the concepts behind functional techniques such as dynamic contrast enhanced (DCE), diffusion-weighted (DW) MRI sequences and magnetic resonance spectroscopic imaging (MRSI). Significant applications of MR are discussed in terms of the following treatment sites: brain, head and neck, breast, lung, prostate and cervix. While not yet routine, the use of apparent diffusion coefficient (ADC) map analysis indicates an exciting future application for functional MRI. Although DW-MRI has not yet been routinely used in boost adaptive techniques, it is being assessed in cohort studies for sub-volume boosting in prostate tumors. PMID:23617289

Resting-state functional magnetic resonance imaging for surgical planning in pediatric patients: a preliminary experience.

PubMed

Roland, Jarod L; Griffin, Natalie; Hacker, Carl D; Vellimana, Ananth K; Akbari, S Hassan; Shimony, Joshua S; Smyth, Matthew D; Leuthardt, Eric C; Limbrick, David D

2017-12-01

OBJECTIVE Cerebral mapping for surgical planning and operative guidance is a challenging task in neurosurgery. Pediatric patients are often poor candidates for many modern mapping techniques because of inability to cooperate due to their immature age, cognitive deficits, or other factors. Resting-state functional MRI (rs-fMRI) is uniquely suited to benefit pediatric patients because it is inherently noninvasive and does not require task performance or significant cooperation. Recent advances in the field have made mapping cerebral networks possible on an individual basis for use in clinical decision making. The authors present their initial experience translating rs-fMRI into clinical practice for surgical planning in pediatric patients. METHODS The authors retrospectively reviewed cases in which the rs-fMRI analysis technique was used prior to craniotomy in pediatric patients undergoing surgery in their institution. Resting-state analysis was performed using a previously trained machine-learning algorithm for identification of resting-state networks on an individual basis. Network maps were uploaded to the clinical imaging and surgical navigation systems. Patient demographic and clinical characteristics, including need for sedation during imaging and use of task-based fMRI, were also recorded. RESULTS Twenty patients underwent rs-fMRI prior to craniotomy between December 2013 and June 2016. Their ages ranged from 1.9 to 18.4 years, and 12 were male. Five of the 20 patients also underwent task-based fMRI and one underwent awake craniotomy. Six patients required sedation to tolerate MRI acquisition, including resting-state sequences. Exemplar cases are presented including anatomical and resting-state functional imaging. CONCLUSIONS Resting-state fMRI is a rapidly advancing field of study allowing for whole brain analysis by a noninvasive modality. It is applicable to a wide range of patients and effective even under general anesthesia. The nature of resting-state analysis precludes any need for task cooperation. These features make rs-fMRI an ideal technology for cerebral mapping in pediatric neurosurgical patients. This review of the use of rs-fMRI mapping in an initial pediatric case series demonstrates the feasibility of utilizing this technique in pediatric neurosurgical patients. The preliminary experience presented here is a first step in translating this technique to a broader clinical practice.

Visualizing Transcranial Direct Current Stimulation (tDCS) in vivo using Magnetic Resonance Imaging

NASA Astrophysics Data System (ADS)

Jog, Mayank Anant

Transcranial Direct Current Stimulation (tDCS) is a low-cost, non-invasive neuromodulation technique that has been shown to treat clinical symptoms as well as improve cognition. However, no techniques exist at the time of research to visualize tDCS currents in vivo. This dissertation presents the theoretical framework and experimental implementations of a novel MRI technique that enables non-invasive visualization of the tDCS electric current using magnetic field mapping. The first chapter establishes the feasibility of measuring magnetic fields induced by tDCS currents. The following chapter discusses the state of the art implementation that can measure magnetic field changes in individual subjects undergoing concurrent tDCS/MRI. The final chapter discusses how the developed technique was integrated with BOLD fMRI-an established MRI technique for measuring brain function. By enabling a concurrent measurement of the tDCS current induced magnetic field as well as the brain's hemodynamic response to tDCS, our technique opens a new avenue to investigate tDCS mechanisms and improve targeting.

Recording event-related activity under hostile magnetic resonance environment: Is multimodal EEG/ERP-MRI recording possible?

PubMed

Karakaş, H M; Karakaş, S; Ozkan Ceylan, A; Tali, E T

2009-08-01

Event-related potentials (ERPs) have high temporal resolution, but insufficient spatial resolution; the converse is true for the functional imaging techniques. The purpose of the study was to test the utility of a multimodal EEG/ERP-MRI technique which combines electroencephalography (EEG) and magnetic resonance imaging (MRI) for a simultaneously high temporal and spatial resolution. The sample consisted of 32 healthy young adults of both sexes. Auditory stimuli were delivered according to the active and passive oddball paradigms in the MRI environment (MRI-e) and in the standard conditions of the electrophysiology laboratory environment (Lab-e). Tasks were presented in a fixed order. Participants were exposed to the recording environments in a counterbalanced order. EEG data were preprocessed for MRI-related artifacts. Source localization was made using a current density reconstruction technique. The ERP waveforms for the MRI-e were morphologically similar to those for the Lab-e. The effect of the recording environment, experimental paradigm and electrode location were analyzed using a 2x2x3 analysis of variance for repeated measures. The ERP components in the two environments showed parametric variations and characteristic topographical distributions. The calculated sources were in line with the related literature. The findings indicated effortful cognitive processing in MRI-e. The study provided preliminary data on the feasibility of the multimodal EEG/ERP-MRI technique. It also indicated lines of research that are to be pursued for a decisive testing of this technique and its implementation to clinical practice.

Non-invasive regime for language lateralization in right- and left-handers by means of functional MRI and dichotic listening.

PubMed

Hund-Georgiadis, Margret; Lex, Ulrike; Friederici, Angela D; von Cramon, D Yves

2002-07-01

Language lateralization was assessed by two independent functional techniques, fMRI and a dichotic listening test (DLT), in an attempt to establish a reliable and non-invasive protocol of dominance determination. This should particularly address the high intraindividual variability of language lateralization and allow decision-making in individual cases. Functional MRI of word classification tasks showed robust language lateralization in 17 right-handers and 17 left-handers in terms of activation in the inferior frontal gyrus. The DLT was introduced as a complementary tool to MR mapping for language dominance assessment, providing information on perceptual language processing located in superior temporal cortices. The overall agreement of lateralization assessment between the two techniques was 97.1%. Conflicting results were found in one subject, and diverging indices in ten further subjects. Increasing age, non-familial sinistrality, and a non-dominant writing hand were identified as the main factors explaining the observed mismatch between the two techniques. This finding stresses the concept of an intrahemispheric distribution of language function that is obviously associated with certain behavioral characteristics.

Functional network alterations and their structural substrate in drug-resistant epilepsy

PubMed Central

Caciagli, Lorenzo; Bernhardt, Boris C.; Hong, Seok-Jun; Bernasconi, Andrea; Bernasconi, Neda

2014-01-01

The advent of MRI has revolutionized the evaluation and management of drug-resistant epilepsy by allowing the detection of the lesion associated with the region that gives rise to seizures. Recent evidence indicates marked chronic alterations in the functional organization of lesional tissue and large-scale cortico-subcortical networks. In this review, we focus on recent methodological developments in functional MRI (fMRI) analysis techniques and their application to the two most common drug-resistant focal epilepsies, i.e., temporal lobe epilepsy related to mesial temporal sclerosis and extra-temporal lobe epilepsy related to focal cortical dysplasia. We put particular emphasis on methodological developments in the analysis of task-free or “resting-state” fMRI to probe the integrity of intrinsic networks on a regional, inter-regional, and connectome-wide level. In temporal lobe epilepsy, these techniques have revealed disrupted connectivity of the ipsilateral mesiotemporal lobe, together with contralateral compensatory reorganization and striking reconfigurations of large-scale networks. In cortical dysplasia, initial observations indicate functional alterations in lesional, peri-lesional, and remote neocortical regions. While future research is needed to critically evaluate the reliability, sensitivity, and specificity, fMRI mapping promises to lend distinct biomarkers for diagnosis, presurgical planning, and outcome prediction. PMID:25565942

MRI tools for assessment of microstructure and nephron function of the kidney.

PubMed

Xie, Luke; Bennett, Kevin M; Liu, Chunlei; Johnson, G Allan; Zhang, Jeff Lei; Lee, Vivian S

2016-12-01

MRI can provide excellent detail of renal structure and function. Recently, novel MR contrast mechanisms and imaging tools have been developed to evaluate microscopic kidney structures including the tubules and glomeruli. Quantitative MRI can assess local tubular function and is able to determine the concentrating mechanism of the kidney noninvasively in real time. Measuring single nephron function is now a near possibility. In parallel to advancing imaging techniques for kidney microstructure is a need to carefully understand the relationship between the local source of MRI contrast and the underlying physiological change. The development of these imaging markers can impact the accurate diagnosis and treatment of kidney disease. This study reviews the novel tools to examine kidney microstructure and local function and demonstrates the application of these methods in renal pathophysiology. Copyright © 2016 the American Physiological Society.

EEG-Informed fMRI: A Review of Data Analysis Methods

PubMed Central

Abreu, Rodolfo; Leal, Alberto; Figueiredo, Patrícia

2018-01-01

The simultaneous acquisition of electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review the methodologies that are currently available to address the challenges at each step of the data analysis pipeline. We start by surveying methods for pre-processing both EEG and fMRI data. On the EEG side, we focus on the correction for several MR-induced artifacts, particularly the gradient and pulse artifacts, as well as other sources of EEG artifacts. On the fMRI side, we consider image artifacts induced by the presence of EEG hardware inside the MR scanner, and the contamination of the fMRI signal by physiological noise of non-neuronal origin, including a review of several approaches to model and remove it. We then provide an overview of the approaches specifically employed for the integration of EEG and fMRI when using EEG to predict the blood oxygenation level dependent (BOLD) fMRI signal, the so-called EEG-informed fMRI integration strategy, the most commonly used strategy in EEG-fMRI research. Finally, we systematically review methods used for the extraction of EEG features reflecting neuronal phenomena of interest. PMID:29467634

Dynamic MRI to quantify musculoskeletal motion: A systematic review of concurrent validity and reliability, and perspectives for evaluation of musculoskeletal disorders.

PubMed

Borotikar, Bhushan; Lempereur, Mathieu; Lelievre, Mathieu; Burdin, Valérie; Ben Salem, Douraied; Brochard, Sylvain

2017-01-01

To report evidence for the concurrent validity and reliability of dynamic MRI techniques to evaluate in vivo joint and muscle mechanics, and to propose recommendations for their use in the assessment of normal and impaired musculoskeletal function. The search was conducted on articles published in Web of science, PubMed, Scopus, Academic search Premier, and Cochrane Library between 1990 and August 2017. Studies that reported the concurrent validity and/or reliability of dynamic MRI techniques for in vivo evaluation of joint or muscle mechanics were included after assessment by two independent reviewers. Selected articles were assessed using an adapted quality assessment tool and a data extraction process. Results for concurrent validity and reliability were categorized as poor, moderate, or excellent. Twenty articles fulfilled the inclusion criteria with a mean quality assessment score of 66% (±10.4%). Concurrent validity and/or reliability of eight dynamic MRI techniques were reported, with the knee being the most evaluated joint (seven studies). Moderate to excellent concurrent validity and reliability were reported for seven out of eight dynamic MRI techniques. Cine phase contrast and real-time MRI appeared to be the most valid and reliable techniques to evaluate joint motion, and spin tag for muscle motion. Dynamic MRI techniques are promising for the in vivo evaluation of musculoskeletal mechanics; however results should be evaluated with caution since validity and reliability have not been determined for all joints and muscles, nor for many pathological conditions.

[One decade of functional imaging in schizophrenia research. From visualisation of basic information processing steps to molecular-genetic oriented imaging].

PubMed

Tost, H; Meyer-Lindenberg, A; Ruf, M; Demirakça, T; Grimm, O; Henn, F A; Ende, G

2005-02-01

Modern neuroimaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET) have contributed tremendously to our current understanding of psychiatric disorders in the context of functional, biochemical and microstructural alterations of the brain. Since the mid-nineties, functional MRI has provided major insights into the neurobiological correlates of signs and symptoms in schizophrenia. The current paper reviews important fMRI studies of the past decade in the domains of motor, visual, auditory, attentional and working memory function. Special emphasis is given to new methodological approaches, such as the visualisation of medication effects and the functional characterisation of risk genes.

Renal volume assessed by magnetic resonance imaging volumetry correlates with renal function in living kidney donors pre- and postdonation: a retrospective cohort study.

PubMed

Lange, Daniel; Helck, Andreas; Rominger, Axel; Crispin, Alexander; Meiser, Bruno; Werner, Jens; Fischereder, Michael; Stangl, Manfred; Habicht, Antje

2018-07-01

Renal function of potential living kidney donors is routinely assessed with scintigraphy. Kidney anatomy is evaluated by imaging techniques such as magnetic resonance imaging (MRI). We evaluated if a MRI-based renal volumetry is a good predictor of kidney function pre- and postdonation. We retrospectively analyzed the renal volume (RV) in a MRI of 100 living kidney donors. RV was correlated with the tubular excretion rate (TER) of MAG3-scintigraphy, a measured creatinine clearance (CrCl), and the estimated glomerular filtration rate (eGFR) by Cockcroft-Gault (CG), CKD-EPI, and modification of diet in renal disease (MDRD) formula pre- and postdonation during a follow-up of 3 years. RV correlated significantly with the TER (total: r = 0.6735, P < 0.0001). Correlation between RV and renal function was the highest for eGFR by CG (r = 0.5595, P < 0.0001), in comparison with CrCl, MDRD-GFR, and CKD-EPI-GFR predonation. RV significantly correlated with CG-GFR postdonation and predicted CG-GFR until 3 years after donation. MRI renal volumetry might be an alternative technique for the evaluation of split renal function and prediction of renal function postdonation in living kidney donors. © 2018 Steunstichting ESOT.

Structural and functional network connectivity breakdown in Alzheimer’s disease studied with magnetic resonance imaging techniques.

PubMed

Filippi, Massimo; Agosta, Federica

2011-01-01

Patients with Alzheimer’s disease (AD) experience a brain network breakdown, reflecting disconnection at both the structural and functional system level. Resting-state (RS) functional MRI (fMRI) studies demonstrated that the regional coherence of the fMRI signal is significantly altered in patients with AD and amnestic mild cognitive impairment. Diffusion tensor (DT) MRI has made it possible to track fiber bundle projections across the brain, revealing a substantially abnormal interplay of “critical” white matter tracts in these conditions. The observed agreement between the results of RS fMRI and DT MRI tractography studies in healthy individuals is encouraging and offers interesting hypotheses to be tested in patients with AD, a MCI, and other dementias in order to improve our understanding of their pathobiology in vivo. In this review,we describe the major findings obtained in AD using RS fMRI and DT MRI tractography, and discuss how the relationship between structure and function of the brain networks in AD may be better understood through the application of MR-based technology. This research endeavor holds a great promise in clarifying the mechanisms of cognitive decline in complex chronic neurodegenerative disorders.

Dynamics of the brain: Mathematical models and non-invasive experimental studies

NASA Astrophysics Data System (ADS)

Toronov, V.; Myllylä, T.; Kiviniemi, V.; Tuchin, V. V.

2013-10-01

Dynamics is an essential aspect of the brain function. In this article we review theoretical models of neural and haemodynamic processes in the human brain and experimental non-invasive techniques developed to study brain functions and to measure dynamic characteristics, such as neurodynamics, neurovascular coupling, haemodynamic changes due to brain activity and autoregulation, and cerebral metabolic rate of oxygen. We focus on emerging theoretical biophysical models and experimental functional neuroimaging results, obtained mostly by functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS). We also included our current results on the effects of blood pressure variations on cerebral haemodynamics and simultaneous measurements of fast processes in the brain by near-infrared spectroscopy and a very novel functional MRI technique called magnetic resonance encephalography. Based on a rapid progress in theoretical and experimental techniques and due to the growing computational capacities and combined use of rapidly improving and emerging neuroimaging techniques we anticipate during next decade great achievements in the overall knowledge of the human brain.

The contributions of resting state and task-based functional connectivity studies to our understanding of adolescent brain network maturation.

PubMed

Stevens, Michael C

2016-11-01

This review summarizes functional magnetic resonance imaging (fMRI) research done over the past decade that examined changes in the function and organization of brain networks across human adolescence. Its over-arching goal is to highlight how both resting state functional connectivity (rs-fcMRI) and task-based functional connectivity (t-fcMRI) have jointly contributed - albeit in different ways - to our understanding of the scope and types of network organization changes that occur from puberty until young adulthood. These two approaches generally have tested different types of hypotheses using different analysis techniques. This has hampered the convergence of findings. Although much has been learned about system-wide changes to adolescents' neural network organization, if both rs-fcMRI and t-fcMRI approaches draw upon each other's methodology and ask broader questions, it will produce a more detailed connectome-informed theory of adolescent neurodevelopment to guide physiological, clinical, and other lines of research. Copyright © 2016 Elsevier Ltd. All rights reserved.

Early myocardial dysfunction in streptozotocin-induced diabetic mice: a study using in vivo magnetic resonance imaging (MRI)

PubMed Central

Yu, Xichun; Tesiram, Yasvir A; Towner, Rheal A; Abbott, Andrew; Patterson, Eugene; Huang, Shijun; Garrett, Marion W; Chandrasekaran, Suresh; Matsuzaki, Satoshi; Szweda, Luke I; Gordon, Brian E; Kem, David C

2007-01-01

Background Diabetes is associated with a cardiomyopathy that is independent of coronary artery disease or hypertension. In the present study we used in vivo magnetic resonance imaging (MRI) and echocardiographic techniques to examine and characterize early changes in myocardial function in a mouse model of type 1 diabetes. Methods Diabetes was induced in 8-week old C57BL/6 mice with two intraperitoneal injections of streptozotocin. The blood glucose levels were maintained at 19–25 mmol/l using intermittent low dosages of long acting insulin glargine. MRI and echocardiography were performed at 4 weeks of diabetes (age of 12 weeks) in diabetic mice and age-matched controls. Results After 4 weeks of hyperglycemia one marker of mitochondrial function, NADH oxidase activity, was decreased to 50% of control animals. MRI studies of diabetic mice at 4 weeks demonstrated significant deficits in myocardial morphology and functionality including: a decreased left ventricular (LV) wall thickness, an increased LV end-systolic diameter and volume, a diminished LV ejection fraction and cardiac output, a decreased LV circumferential shortening, and decreased LV peak ejection and filling rates. M-mode echocardiographic and Doppler flow studies of diabetic mice at 4 weeks showed a decreased wall thickening and increased E/A ratio, supporting both systolic and diastolic dysfunction. Conclusion Our study demonstrates that MRI interrogation can identify the onset of diabetic cardiomyopathy in mice with its impaired functional capacity and altered morphology. The MRI technique will lend itself to repetitive study of early changes in cardiac function in small animal models of diabetic cardiomyopathy. PMID:17309798

PyMVPA: A python toolbox for multivariate pattern analysis of fMRI data.

PubMed

Hanke, Michael; Halchenko, Yaroslav O; Sederberg, Per B; Hanson, Stephen José; Haxby, James V; Pollmann, Stefan

2009-01-01

Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. Here we introduce a Python-based, cross-platform, and open-source software toolbox, called PyMVPA, for the application of classifier-based analysis techniques to fMRI datasets. PyMVPA makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages. We present the framework in this paper and provide illustrative examples on its usage, features, and programmability.

PyMVPA: A Python toolbox for multivariate pattern analysis of fMRI data

PubMed Central

Hanke, Michael; Halchenko, Yaroslav O.; Sederberg, Per B.; Hanson, Stephen José; Haxby, James V.; Pollmann, Stefan

2009-01-01

Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. Here we introduce a Python-based, cross-platform, and open-source software toolbox, called PyMVPA, for the application of classifier-based analysis techniques to fMRI datasets. PyMVPA makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine-learning packages. We present the framework in this paper and provide illustrative examples on its usage, features, and programmability. PMID:19184561

Advanced MRI in Multiple Sclerosis: Current Status and Future Challenges

PubMed Central

Fox, Robert J.; Beall, Erik; Bhattacharyya, Pallab; Chen, Jacqueline; Sakaie, Ken

2011-01-01

Synopsis Magnetic resonance imaging (MRI) has rapidly become a leading research tool in the study of multiple sclerosis (MS). Conventional imaging is useful in diagnosis and management of the inflammatory stages of MS, but has limitations in describing the degree of tissue injury as well as the cause of progressive disability seen in the later stages of disease. Advanced MRI techniques hold promise to fill this void. Magnetization transfer imaging is a widely available technique that can characterize demyelination and may be useful in measuring putative remyelinating therapies. Diffusion tensor imaging describes the three-dimensional diffusion of water and holds promise in characterizing neurodegeneration and putative neuroprotective therapies. Spectroscopy measures the imbalance of cellular metabolites and could help unravel the pathogenesis of neurodegeneration in MS. Functional (f) MRI can be used to understand the functional consequences of MS injury, including the impact on cortical function and compensatory mechanisms. These imaging tools hold great promise to increase our understanding of MS pathogenesis and provide greater insight into the efficacy of new MS therapies. PMID:21439446

Fast-GPU-PCC: A GPU-Based Technique to Compute Pairwise Pearson's Correlation Coefficients for Time Series Data-fMRI Study.

PubMed

Eslami, Taban; Saeed, Fahad

2018-04-20

Functional magnetic resonance imaging (fMRI) is a non-invasive brain imaging technique, which has been regularly used for studying brain’s functional activities in the past few years. A very well-used measure for capturing functional associations in brain is Pearson’s correlation coefficient. Pearson’s correlation is widely used for constructing functional network and studying dynamic functional connectivity of the brain. These are useful measures for understanding the effects of brain disorders on connectivities among brain regions. The fMRI scanners produce huge number of voxels and using traditional central processing unit (CPU)-based techniques for computing pairwise correlations is very time consuming especially when large number of subjects are being studied. In this paper, we propose a graphics processing unit (GPU)-based algorithm called Fast-GPU-PCC for computing pairwise Pearson’s correlation coefficient. Based on the symmetric property of Pearson’s correlation, this approach returns N ( N − 1 ) / 2 correlation coefficients located at strictly upper triangle part of the correlation matrix. Storing correlations in a one-dimensional array with the order as proposed in this paper is useful for further usage. Our experiments on real and synthetic fMRI data for different number of voxels and varying length of time series show that the proposed approach outperformed state of the art GPU-based techniques as well as the sequential CPU-based versions. We show that Fast-GPU-PCC runs 62 times faster than CPU-based version and about 2 to 3 times faster than two other state of the art GPU-based methods.

Neuroimaging in epilepsy.

PubMed

Sidhu, Meneka Kaur; Duncan, John S; Sander, Josemir W

2018-05-17

Epilepsy neuroimaging is important for detecting the seizure onset zone, predicting and preventing deficits from surgery and illuminating mechanisms of epileptogenesis. An aspiration is to integrate imaging and genetic biomarkers to enable personalized epilepsy treatments. The ability to detect lesions, particularly focal cortical dysplasia and hippocampal sclerosis, is increased using ultra high-field imaging and postprocessing techniques such as automated volumetry, T2 relaxometry, voxel-based morphometry and surface-based techniques. Statistical analysis of PET and single photon emission computer tomography (STATISCOM) are superior to qualitative analysis alone in identifying focal abnormalities in MRI-negative patients. These methods have also been used to study mechanisms of epileptogenesis and pharmacoresistance.Recent language fMRI studies aim to localize, and also lateralize language functions. Memory fMRI has been recommended to lateralize mnemonic function and predict outcome after surgery in temporal lobe epilepsy. Combinations of structural, functional and post-processing methods have been used in multimodal and machine learning models to improve the identification of the seizure onset zone and increase understanding of mechanisms underlying structural and functional aberrations in epilepsy.

Enhanced Thalamic Functional Connectivity with No fMRI Responses to Affected Forelimb Stimulation in Stroke-Recovered Rats.

PubMed

Shim, Woo H; Suh, Ji-Yeon; Kim, Jeong K; Jeong, Jaeseung; Kim, Young R

2016-01-01

Neurological recovery after stroke has been extensively investigated to provide better understanding of neurobiological mechanism, therapy, and patient management. Recent advances in neuroimaging techniques, particularly functional MRI (fMRI), have widely contributed to unravel the relationship between the altered neural function and stroke-affected brain areas. As results of previous investigations, the plastic reorganization and/or gradual restoration of the hemodynamic fMRI responses to neural stimuli have been suggested as relevant mechanisms underlying the stroke recovery process. However, divergent study results and modality-dependent outcomes have clouded the proper interpretation of variable fMRI signals. Here, we performed both evoked and resting state fMRI (rs-fMRI) to clarify the link between the fMRI phenotypes and post-stroke functional recovery. The experiments were designed to examine the altered neural activity within the contra-lesional hemisphere and other undamaged brain regions using rat models with large unilateral stroke, which despite the severe injury, exhibited nearly full recovery at ∼6 months after stroke. Surprisingly, both blood oxygenation level-dependent and blood volume-weighted (CBVw) fMRI activities elicited by electrical stimulation of the stroke-affected forelimb were completely absent, failing to reveal the neural origin of the behavioral recovery. In contrast, the functional connectivity maps showed highly robust rs-fMRI activity concentrated in the contra-lesional ventromedial nucleus of thalamus (VM). The negative finding in the stimuli-induced fMRI study using the popular rat middle cerebral artery model denotes weak association between the fMRI hemodynamic responses and neurological improvement. The results strongly caution the indiscreet interpretation of stroke-affected fMRI signals and demonstrate rs-fMRI as a complementary tool for efficiently characterizing stroke recovery.

Magnetic resonance imaging for diagnosis of early Alzheimer's disease.

PubMed

Colliot, O; Hamelin, L; Sarazin, M

2013-10-01

A major challenge for neuroimaging is to contribute to the early diagnosis of Alzheimer's disease (AD). In particular, magnetic resonance imaging (MRI) allows detecting different types of structural and functional abnormalities at an early stage of the disease. Anatomical MRI is the most widely used technique and provides local and global measures of atrophy. The recent diagnostic criteria of "mild cognitive impairment due to AD" include hippocampal atrophy, which is considered a marker of neuronal injury. Advanced image analysis techniques generate automatic and reproducible measures both in the hippocampus and throughout the whole brain. Recent modalities such as diffusion-tensor imaging and resting-state functional MRI provide additional measures that could contribute to the early diagnosis but require further validation. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Imaging techniques in the management of chronic kidney disease: current developments and future perspectives.

PubMed

Herget-Rosenthal, Stefan

2011-05-01

The measurement of both renal function and structure is critical in clinical nephrology to detect, stage, and monitor chronic kidney disease (CKD). Current imaging modalities especially ultrasound (US), computed tomography, and magnetic resonance imaging (MRI) provide adequate information on structural changes but little on functional impairment in CKD. Although not yet considered first-line procedures for evaluating patients with renal disease, new US and MR imaging techniques may permit the assessment of renal function in the near future. Combined with established imaging techniques, contrast-enhanced US, dynamic contrast-enhanced MRI, blood oxygen level dependency MRI, or diffusion-weighted imaging may provide rapid, accurate, simultaneous, and noninvasive imaging of the structure of kidneys, macrovascular and microvascular renal perfusion, oxygenation, and glomerular filtration rate. Recent developments in molecular imaging indicate that pathophysiological pathways of renal diseases such as apoptosis, coagulation, fibrosis, and ischemia will be visualized at the tissue level. These major advances in imaging and developments in hardware and software could enable comprehensive imaging of renal structure and function in four dimensions (three dimensions plus time), and imaging is expected to play an increasing role in the management of CKD. Copyright © 2011 Elsevier Inc. All rights reserved.

[Functional neuro-navigation and intraoperative magnetic resonance imaging for the resection of gliomas involving eloquent language structures].

PubMed

Chen, Xiao-lei; Xu, Bai-nan; Wang, Fei; Meng, Xiang-hui; Zhang, Jun; Jiang, Jin-li; Yu, Xin-guang; Zhou, Ding-biao

2011-08-01

To explore the clinical value of functional neuro-navigation and high-field-strength intraoperative magnetic resonance imaging (iMRI) for the resection of intracerebral gliomas involving eloquent language structures. From April 2009 to April 2010, 48 patients with intracerebral gliomas involving eloquent language structures, were operated with functional neuro-navigation and iMRI. Blood oxygen level dependent functional MRI (BOLD-fMRI) was used to depict both Broca and Wernicke cortex, while diffusion tensor imaging (DTI) based fiber tracking was used to delineate arcuate fasciculus. The reconstructed language structures were integrated into a navigation system, so that intra-operative microscopic-based functional neuro-navigation could be achieved. iMRI was used to update the images for both language structures and residual tumors. All patients were evaluated for language function pre-operatively and post-operatively upon short-term and long-term follow-up. In all patients, functional neuro-navigation and iMRI were successfully achieved. In 38 cases (79.2%), gross total resection was accomplished, while in the rest 10 cases (20.8%), subtotal resection was achieved. Only 1 case (2.1%) developed long-term (more than 3 months) new language function deficits at post-operative follow-up. No peri-operative mortality was recorded. With functional neuro-navigation and iMRI, the eloquent structures for language can be precisely located, while the resection size can be accurately evaluated intra-operatively. This technique is safe and helpful for preservation of language function.

DCE-MRI: a review and applications in veterinary oncology.

PubMed

Boss, M Keara; Muradyan, N; Thrall, D E

2013-06-01

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is a functional imaging technique that assesses the physiology of tumour tissue by exploiting abnormal tumour microvasculature. Advances made through DCE-MRI include improvement in the diagnosis of cancer, optimization of treatment choices, assessment of treatment efficacy and non-invasive identification of prognostic information. DCE-MRI enables quantitative assessment of tissue vessel density, integrity, and permeability, and this information can be applied to study of angiogenesis, hypoxia and the evaluation of various biomarkers. Reproducibility of DCE-MRI results is important in determining the significance of observed changes in the parameters. As improvements are made towards the utility of DCE-MRI and interpreting biologic associations, the technique will be applied more frequently in the study of cancer in animals. Given the importance of tumour perfusion with respect to tumour oxygenation and drug delivery, the use of DCE-MRI is a convenient and powerful way to gain basic information about a tumour. © 2011 John Wiley & Sons Ltd.

Dynamic MRI to quantify musculoskeletal motion: A systematic review of concurrent validity and reliability, and perspectives for evaluation of musculoskeletal disorders

PubMed Central

Lempereur, Mathieu; Lelievre, Mathieu; Burdin, Valérie; Ben Salem, Douraied; Brochard, Sylvain

2017-01-01

Purpose To report evidence for the concurrent validity and reliability of dynamic MRI techniques to evaluate in vivo joint and muscle mechanics, and to propose recommendations for their use in the assessment of normal and impaired musculoskeletal function. Materials and methods The search was conducted on articles published in Web of science, PubMed, Scopus, Academic search Premier, and Cochrane Library between 1990 and August 2017. Studies that reported the concurrent validity and/or reliability of dynamic MRI techniques for in vivo evaluation of joint or muscle mechanics were included after assessment by two independent reviewers. Selected articles were assessed using an adapted quality assessment tool and a data extraction process. Results for concurrent validity and reliability were categorized as poor, moderate, or excellent. Results Twenty articles fulfilled the inclusion criteria with a mean quality assessment score of 66% (±10.4%). Concurrent validity and/or reliability of eight dynamic MRI techniques were reported, with the knee being the most evaluated joint (seven studies). Moderate to excellent concurrent validity and reliability were reported for seven out of eight dynamic MRI techniques. Cine phase contrast and real-time MRI appeared to be the most valid and reliable techniques to evaluate joint motion, and spin tag for muscle motion. Conclusion Dynamic MRI techniques are promising for the in vivo evaluation of musculoskeletal mechanics; however results should be evaluated with caution since validity and reliability have not been determined for all joints and muscles, nor for many pathological conditions. PMID:29232401

Software Toolbox for Low-Frequency Conductivity and Current Density Imaging Using MRI.

PubMed

Sajib, Saurav Z K; Katoch, Nitish; Kim, Hyung Joong; Kwon, Oh In; Woo, Eung Je

2017-11-01

Low-frequency conductivity and current density imaging using MRI includes magnetic resonance electrical impedance tomography (MREIT), diffusion tensor MREIT (DT-MREIT), conductivity tensor imaging (CTI), and magnetic resonance current density imaging (MRCDI). MRCDI and MREIT provide current density and isotropic conductivity images, respectively, using current-injection phase MRI techniques. DT-MREIT produces anisotropic conductivity tensor images by incorporating diffusion weighted MRI into MREIT. These current-injection techniques are finding clinical applications in diagnostic imaging and also in transcranial direct current stimulation (tDCS), deep brain stimulation (DBS), and electroporation where treatment currents can function as imaging currents. To avoid adverse effects of nerve and muscle stimulations due to injected currents, conductivity tensor imaging (CTI) utilizes B1 mapping and multi-b diffusion weighted MRI to produce low-frequency anisotropic conductivity tensor images without injecting current. This paper describes numerical implementations of several key mathematical functions for conductivity and current density image reconstructions in MRCDI, MREIT, DT-MREIT, and CTI. To facilitate experimental studies of clinical applications, we developed a software toolbox for these low-frequency conductivity and current density imaging methods. This MR-based conductivity imaging (MRCI) toolbox includes 11 toolbox functions which can be used in the MATLAB environment. The MRCI toolbox is available at http://iirc.khu.ac.kr/software.html . Its functions were tested by using several experimental datasets, which are provided together with the toolbox. Users of the toolbox can focus on experimental designs and interpretations of reconstructed images instead of developing their own image reconstruction softwares. We expect more toolbox functions to be added from future research outcomes. Low-frequency conductivity and current density imaging using MRI includes magnetic resonance electrical impedance tomography (MREIT), diffusion tensor MREIT (DT-MREIT), conductivity tensor imaging (CTI), and magnetic resonance current density imaging (MRCDI). MRCDI and MREIT provide current density and isotropic conductivity images, respectively, using current-injection phase MRI techniques. DT-MREIT produces anisotropic conductivity tensor images by incorporating diffusion weighted MRI into MREIT. These current-injection techniques are finding clinical applications in diagnostic imaging and also in transcranial direct current stimulation (tDCS), deep brain stimulation (DBS), and electroporation where treatment currents can function as imaging currents. To avoid adverse effects of nerve and muscle stimulations due to injected currents, conductivity tensor imaging (CTI) utilizes B1 mapping and multi-b diffusion weighted MRI to produce low-frequency anisotropic conductivity tensor images without injecting current. This paper describes numerical implementations of several key mathematical functions for conductivity and current density image reconstructions in MRCDI, MREIT, DT-MREIT, and CTI. To facilitate experimental studies of clinical applications, we developed a software toolbox for these low-frequency conductivity and current density imaging methods. This MR-based conductivity imaging (MRCI) toolbox includes 11 toolbox functions which can be used in the MATLAB environment. The MRCI toolbox is available at http://iirc.khu.ac.kr/software.html . Its functions were tested by using several experimental datasets, which are provided together with the toolbox. Users of the toolbox can focus on experimental designs and interpretations of reconstructed images instead of developing their own image reconstruction softwares. We expect more toolbox functions to be added from future research outcomes.

Magnetic resonance imaging based functional imaging in paediatric oncology.

PubMed

Manias, Karen A; Gill, Simrandip K; MacPherson, Lesley; Foster, Katharine; Oates, Adam; Peet, Andrew C

2017-02-01

Imaging is central to management of solid tumours in children. Conventional magnetic resonance imaging (MRI) is the standard imaging modality for tumours of the central nervous system (CNS) and limbs and is increasingly used in the abdomen. It provides excellent structural detail, but imparts limited information about tumour type, aggressiveness, metastatic potential or early treatment response. MRI based functional imaging techniques, such as magnetic resonance spectroscopy, diffusion and perfusion weighted imaging, probe tissue properties to provide clinically important information about metabolites, structure and blood flow. This review describes the role of and evidence behind these functional imaging techniques in paediatric oncology and implications for integrating them into routine clinical practice. Copyright © 2016 Elsevier Ltd. All rights reserved.

Estimation of gas and tissue lung volumes by MRI: functional approach of lung imaging.

PubMed

Qanadli, S D; Orvoen-Frija, E; Lacombe, P; Di Paola, R; Bittoun, J; Frija, G

1999-01-01

The purpose of this work was to assess the accuracy of MRI for the determination of lung gas and tissue volumes. Fifteen healthy subjects underwent MRI of the thorax and pulmonary function tests [vital capacity (VC) and total lung capacity (TLC)] in the supine position. MR examinations were performed at inspiration and expiration. Lung volumes were measured by a previously validated technique on phantoms. Both individual and total lung volumes and capacities were calculated. MRI total vital capacity (VC(MRI)) was compared with spirometric vital capacity (VC(SP)). Capacities were correlated to lung volumes. Tissue volume (V(T)) was estimated as the difference between the total lung volume at full inspiration and the TLC. No significant difference was seen between VC(MRI) and VC(SP). Individual capacities were well correlated (r = 0.9) to static volume at full inspiration. The V(T) was estimated to be 836+/-393 ml. This preliminary study demonstrates that MRI can accurately estimate lung gas and tissue volumes. The proposed approach appears well suited for functional imaging of the lung.

Correlation between brain circuit segregation and obesity.

PubMed

Chao, Seh-Huang; Liao, Yin-To; Chen, Vincent Chin-Hung; Li, Cheng-Jui; McIntyre, Roger S; Lee, Yena; Weng, Jun-Cheng

2018-01-30

Obesity is a major public health problem. Herein, we aim to identify the correlation between brain circuit segregation and obesity using multimodal functional magnetic resonance imaging (fMRI) techniques and analysis. Twenty obese patients (BMI=37.66±5.07) and 30 healthy controls (BMI=22.64±3.45) were compared using neuroimaging and assessed for symptoms of anxiety and depression using the Hospital Anxiety and Depression Scale (HADS). All participants underwent resting-state fMRI (rs-fMRI) and T1-weighted imaging using a 1.5T MRI. Multimodal MRI techniques and analyses were used to assess obese patients, including the functional connectivity (FC), amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), graph theoretical analysis (GTA), and voxel-based morphometry (VBM). Correlations between brain circuit segregation and obesity were also calculated. In the VBM, obese patients showed altered gray matter volumes in the amygdala, thalamus and putamen. In the FC, the obesity group showed increased functional connectivity in the bilateral anterior cingulate cortex and decreased functional connectivity in the frontal gyrus of default mode network. The obesity group also exhibited altered ALFF and ReHo in the prefrontal cortex and precuneus. In the GTA, the obese patients showed a significant decrease in local segregation and a significant increase in global integration, suggesting a shift toward randomization in their functional networks. Our results may provide additional evidence for potential structural and functional imaging markers for clinical diagnosis and future research, and they may improve our understanding of the underlying pathophysiology of obesity. Copyright © 2017 Elsevier B.V. All rights reserved.

Real-time fMRI: a tool for local brain regulation.

PubMed

Caria, Andrea; Sitaram, Ranganatha; Birbaumer, Niels

2012-10-01

Real-time fMRI permits simultaneous measurement and observation of brain activity during an ongoing task. One of the most challenging applications of real-time fMRI in neuroscientific and clinical research is the possibility of acquiring volitional control of localized brain activity using real-time fMRI-based neurofeedback protocols. Real-time fMRI allows the experimenter to noninvasively manipulate brain activity as an independent variable to observe the effects on behavior. Real-time fMRI neurofeedback studies demonstrated that learned control of the local brain activity leads to specific changes in behavior. Here, the authors describe the implementation and application of real-time fMRI with particular emphasis on the self-regulation of local brain activity and the investigation of brain-function relationships. Real-time fMRI represents a promising new approach to cognitive neuroscience that could complement traditional neuroimaging techniques by providing more causal insights into the functional role of circumscribed brain regions in behavior.

Variability comparison of simultaneous brain near-infrared spectroscopy (NIRS) and functional MRI (fMRI) during visual stimulation

PubMed Central

Minati, Ludovico; Visani, Elisa; Dowell, Nick G; Medford, Nick; Critchley, Hugo D

2011-01-01

Brain near-infrared spectroscopy (NIRS) is emerging as a potential alternative to functional MRI (fMRI). To date, no study has explicitly compared the two techniques in terms of measurement variability, a key parameter dictating attainable statistical power. Here, NIRS and fMRI were simultaneously recorded during event-related visual stimulation. Inter-subject coefficients of variation (CVs) for peak response amplitude were considerably larger for NIRS than fMRI, but inter-subject CVs for response latency and intra-subject CVs for response amplitude were overall comparable. Our results may represent an optimistic estimate of the CVs of NIRS measurements, as optode positioning was guided by structural MRI, which is normally unavailable. We conclude that fMRI may be preferable to NIRS for group comparisons, but NIRS is equally powerful when comparing conditions within participants. The discrepancy between inter- and intra-subject CVs is likely related to variability in head anatomy and tissue properties which may be better accounted for by emerging NIRS technology. PMID:21780948

Semi-supervised clustering for parcellating brain regions based on resting state fMRI data

NASA Astrophysics Data System (ADS)

Cheng, Hewei; Fan, Yong

2014-03-01

Many unsupervised clustering techniques have been adopted for parcellating brain regions of interest into functionally homogeneous subregions based on resting state fMRI data. However, the unsupervised clustering techniques are not able to take advantage of exiting knowledge of the functional neuroanatomy readily available from studies of cytoarchitectonic parcellation or meta-analysis of the literature. In this study, we propose a semi-supervised clustering method for parcellating amygdala into functionally homogeneous subregions based on resting state fMRI data. Particularly, the semi-supervised clustering is implemented under the framework of graph partitioning, and adopts prior information and spatial consistent constraints to obtain a spatially contiguous parcellation result. The graph partitioning problem is solved using an efficient algorithm similar to the well-known weighted kernel k-means algorithm. Our method has been validated for parcellating amygdala into 3 subregions based on resting state fMRI data of 28 subjects. The experiment results have demonstrated that the proposed method is more robust than unsupervised clustering and able to parcellate amygdala into centromedial, laterobasal, and superficial parts with improved functionally homogeneity compared with the cytoarchitectonic parcellation result. The validity of the parcellation results is also supported by distinctive functional and structural connectivity patterns of the subregions and high consistency between coactivation patterns derived from a meta-analysis and functional connectivity patterns of corresponding subregions.

What is feasible with imaging human brain function and connectivity using functional magnetic resonance imaging.

PubMed

Ugurbil, Kamil

2016-10-05

When we consider all of the methods we employ to detect brain function, from electrophysiology to optical techniques to functional magnetic resonance imaging (fMRI), we do not really have a 'golden technique' that meets all of the needs for studying the brain. We have methods, each of which has significant limitations but provide often complimentary information. Clearly, there are many questions that need to be answered about fMRI, which unlike other methods, allows us to study the human brain. However, there are also extraordinary accomplishments or demonstration of the feasibility of reaching new and previously unexpected scales of function in the human brain. This article reviews some of the work we have pursued, often with extensive collaborations with other co-workers, towards understanding the underlying mechanisms of the methodology, defining its limitations, and developing solutions to advance it. No doubt, our knowledge of human brain function has vastly expanded since the introduction of fMRI. However, methods and instrumentation in this dynamic field have evolved to a state that discoveries about the human brain based on fMRI principles, together with information garnered at a much finer spatial and temporal scale through other methods, are poised to significantly accelerate in the next decade.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. © 2016 The Author(s).

Clinical applications of advanced magnetic resonance imaging techniques for arthritis evaluation

PubMed Central

Martín Noguerol, Teodoro; Luna, Antonio; Gómez Cabrera, Marta; Riofrio, Alexie D

2017-01-01

Magnetic resonance imaging (MRI) has allowed a comprehensive evaluation of articular disease, increasing the detection of early cartilage involvement, bone erosions, and edema in soft tissue and bone marrow compared to other imaging techniques. In the era of functional imaging, new advanced MRI sequences are being successfully applied for articular evaluation in cases of inflammatory, infectious, and degenerative arthropathies. Diffusion weighted imaging, new fat suppression techniques such as DIXON, dynamic contrast enhanced-MRI, and specific T2 mapping cartilage sequences allow a better understanding of the physiopathological processes that underlie these different arthropathies. They provide valuable quantitative information that aids in their differentiation and can be used as potential biomarkers of articular disease course and treatment response. PMID:28979849

Various diffusion magnetic resonance imaging techniques for pancreatic cancer

PubMed Central

Tang, Meng-Yue; Zhang, Xiao-Ming; Chen, Tian-Wu; Huang, Xiao-Hua

2015-01-01

Pancreatic cancer is one of the most common malignant tumors and remains a treatment-refractory cancer with a poor prognosis. Currently, the diagnosis of pancreatic neoplasm depends mainly on imaging and which methods are conducive to detecting small lesions. Compared to the other techniques, magnetic resonance imaging (MRI) has irreplaceable advantages and can provide valuable information unattainable with other noninvasive or minimally invasive imaging techniques. Advances in MR hardware and pulse sequence design have particularly improved the quality and robustness of MRI of the pancreas. Diffusion MR imaging serves as one of the common functional MRI techniques and is the only technique that can be used to reflect the diffusion movement of water molecules in vivo. It is generally known that diffusion properties depend on the characterization of intrinsic features of tissue microdynamics and microstructure. With the improvement of the diffusion models, diffusion MR imaging techniques are increasingly varied, from the simplest and most commonly used technique to the more complex. In this review, the various diffusion MRI techniques for pancreatic cancer are discussed, including conventional diffusion weighted imaging (DWI), multi-b DWI based on intra-voxel incoherent motion theory, diffusion tensor imaging and diffusion kurtosis imaging. The principles, main parameters, advantages and limitations of these techniques, as well as future directions for pancreatic diffusion imaging are also discussed. PMID:26753059

An image warping technique for rodent brain MRI-histology registration based on thin-plate splines with landmark optimization

NASA Astrophysics Data System (ADS)

Liu, Yutong; Uberti, Mariano; Dou, Huanyu; Mosley, R. Lee; Gendelman, Howard E.; Boska, Michael D.

2009-02-01

Coregistration of in vivo magnetic resonance imaging (MRI) with histology provides validation of disease biomarker and pathobiology studies. Although thin-plate splines are widely used in such image registration, point landmark selection is error prone and often time-consuming. We present a technique to optimize landmark selection for thin-plate splines and demonstrate its usefulness in warping rodent brain MRI to histological sections. In this technique, contours are drawn on the corresponding MRI slices and images of histological sections. The landmarks are extracted from the contours by equal spacing then optimized by minimizing a cost function consisting of the landmark displacement and contour curvature. The technique was validated using simulation data and brain MRI-histology coregistration in a murine model of HIV-1 encephalitis. Registration error was quantified by calculating target registration error (TRE). The TRE of approximately 8 pixels for 20-80 landmarks without optimization was stable at different landmark numbers. The optimized results were more accurate at low landmark numbers (TRE of approximately 2 pixels for 50 landmarks), while the accuracy decreased (TRE approximately 8 pixels for larger numbers of landmarks (70- 80). The results demonstrated that registration accuracy decreases with the increasing landmark numbers offering more confidence in MRI-histology registration using thin-plate splines.

Whole body MRI: Improved Lesion Detection and Characterization With Diffusion Weighted Techniques

PubMed Central

Attariwala, Rajpaul; Picker, Wayne

2013-01-01

Diffusion-weighted imaging (DWI) is an established functional imaging technique that interrogates the delicate balance of water movement at the cellular level. Technological advances enable this technique to be applied to whole-body MRI. Theory, b-value selection, common artifacts and target to background for optimized viewing will be reviewed for applications in the neck, chest, abdomen, and pelvis. Whole-body imaging with DWI allows novel applications of MRI to aid in evaluation of conditions such as multiple myeloma, lymphoma, and skeletal metastases, while the quantitative nature of this technique permits evaluation of response to therapy. Persisting signal at high b-values from restricted hypercellular tissue and viscous fluid also permits applications of DWI beyond oncologic imaging. DWI, when used in conjunction with routine imaging, can assist in detecting hemorrhagic degradation products, infection/abscess, and inflammation in colitis, while aiding with discrimination of free fluid and empyema, while limiting the need for intravenous contrast. DWI in conjunction with routine anatomic images provides a platform to improve lesion detection and characterization with findings rivaling other combined anatomic and functional imaging techniques, with the added benefit of no ionizing radiation. PMID:23960006

Associations of resting-state fMRI functional connectivity with flow-BOLD coupling and regional vasculature.

PubMed

Tak, Sungho; Polimeni, Jonathan R; Wang, Danny J J; Yan, Lirong; Chen, J Jean

2015-04-01

There has been tremendous interest in applying functional magnetic resonance imaging-based resting-state functional connectivity (rs-fcMRI) measurements to the study of brain function. However, a lack of understanding of the physiological mechanisms of rs-fcMRI limits their ability to interpret rs-fcMRI findings. In this work, the authors examine the regional associations between rs-fcMRI estimates and dynamic coupling between the blood oxygenation level-dependent (BOLD) and cerebral blood flow (CBF), as well as resting macrovascular volume. Resting-state BOLD and CBF data were simultaneously acquired using a dual-echo pseudocontinuous arterial spin labeling (pCASL) technique, whereas macrovascular volume fraction was estimated using time-of-flight MR angiography. Functional connectivity within well-known functional networks—including the default mode, frontoparietal, and primary sensory-motor networks—was calculated using a conventional seed-based correlation approach. They found the functional connectivity strength to be significantly correlated with the regional increase in CBF-BOLD coupling strength and inversely proportional to macrovascular volume fraction. These relationships were consistently observed within all functional networks considered. Their findings suggest that highly connected networks observed using rs-fcMRI are not likely to be mediated by common vascular drainage linking distal cortical areas. Instead, high BOLD functional connectivity is more likely to reflect tighter neurovascular connections, attributable to neuronal pathways.

Functional Imaging of the Lungs with Gas Agents

PubMed Central

Kruger, Stanley J.; Nagle, Scott K.; Couch, Marcus J.; Ohno, Yoshiharu; Albert, Mitchell; Fain, Sean B.

2015-01-01

This review focuses on the state-of-the-art of the three major classes of gas contrast agents used in magnetic resonance imaging (MRI) – hyperpolarized (HP) gas, molecular oxygen, and fluorinated gas – and their application to clinical pulmonary research. During the past several years there has been accelerated development of pulmonary MRI. This has been driven in part by concerns regarding ionizing radiation using multi-detector computed tomography (CT). However, MRI also offers capabilities for fast multi-spectral and functional imaging using gas agents that are not technically feasible with CT. Recent improvements in gradient performance and radial acquisition methods using ultra-short echo time (UTE) have contributed to advances in these functional pulmonary MRI techniques. Relative strengths and weaknesses of the main functional imaging methods and gas agents are compared and applications to measures of ventilation, diffusion, and gas exchange are presented. Functional lung MRI methods using these gas agents are improving our understanding of a wide range of chronic lung diseases, including chronic obstructive pulmonary disease (COPD), asthma, and cystic fibrosis (CF) in both adults and children. PMID:26218920

Connectivity changes after laser ablation: Resting-state fMRI.

PubMed

Boerwinkle, Varina L; Vedantam, Aditya; Lam, Sandi; Wilfong, Angus A; Curry, Daniel J

2018-05-01

Resting-state functional magnetic resonance imaging (rsfMRI) is emerging as a useful tool in the multimodal assessment of patients with epilepsy. In pediatric patients who cannot perform task-based fMRI, rsfMRI may present an adjunct and alternative. Although changes in brain activation during task-based fMRI have been described after surgery for epilepsy, there is limited data on the role of postoperative rsfMRI. In this short review, we discuss the role of postoperative rsfMRI after laser ablation of seizure foci. By establishing standardized anesthesia protocols and imaging parameters, we have been able to perform serial rsfMRI at postoperative follow-up. The development of in-house software that can merge rsfMRI images to surgical navigation systems has allowed us to enhance the clinical applications of this technique. Resting-state fMRI after laser ablation has the potential to identify changes in connectivity, localize new seizure foci, and guide antiepileptic therapy. In our experience, rsfMRI complements conventional MR imaging and task-based fMRI for the evaluation of patients with seizure recurrence after laser ablation, and represents a potential noninvasive biomarker for functional connectivity. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Functional feature embedded space mapping of fMRI data.

PubMed

Hu, Jin; Tian, Jie; Yang, Lei

2006-01-01

We have proposed a new method for fMRI data analysis which is called Functional Feature Embedded Space Mapping (FFESM). Our work mainly focuses on the experimental design with periodic stimuli which can be described by a number of Fourier coefficients in the frequency domain. A nonlinear dimension reduction technique Isomap is applied to the high dimensional features obtained from frequency domain of the fMRI data for the first time. Finally, the presence of activated time series is identified by the clustering method in which the information theoretic criterion of minimum description length (MDL) is used to estimate the number of clusters. The feasibility of our algorithm is demonstrated by real human experiments. Although we focus on analyzing periodic fMRI data, the approach can be extended to analyze non-periodic fMRI data (event-related fMRI) by replacing the Fourier analysis with a wavelet analysis.

The Use of Functional MRI to Study Appetite Control in the CNS

PubMed Central

De Silva, Akila; Salem, Victoria; Matthews, Paul M.; Dhillo, Waljit S.

2012-01-01

Functional magnetic resonance imaging (fMRI) has provided the opportunity to safely investigate the workings of the human brain. This paper focuses on its use in the field of human appetitive behaviour and its impact in obesity research. In the present absence of any safe or effective centrally acting appetite suppressants, a better understanding of how appetite is controlled is vital for the development of new antiobesity pharmacotherapies. Early functional imaging techniques revealed an attenuation of brain reward area activity in response to visual food stimuli when humans are fed—in other words, the physiological state of hunger somehow increases the appeal value of food. Later studies have investigated the action of appetite modulating hormones on the fMRI signal, showing how the attenuation of brain reward region activity that follows feeding can be recreated in the fasted state by the administration of anorectic gut hormones. Furthermore, differences in brain activity between obese and lean individuals have provided clues about the possible aetiology of overeating. The hypothalamus acts as a central gateway modulating homeostatic and nonhomeostatic drives to eat. As fMRI techniques constantly improve, functional data regarding the role of this small but hugely important structure in appetite control is emerging. PMID:22719753

Subcortical pathways serving cortical language sites: initial experience with diffusion tensor imaging fiber tracking combined with intraoperative language mapping.

PubMed

Henry, Roland G; Berman, Jeffrey I; Nagarajan, Srikantan S; Mukherjee, Pratik; Berger, Mitchel S

2004-02-01

The combination of mapping functional cortical neurons by intraoperative cortical stimulation and axonal architecture by diffusion tensor MRI fiber tracking can be used to delineate the pathways between functional regions. In this study the authors investigated the feasibility of combining these techniques to yield connectivity associated with motor speech and naming. Diffusion tensor MRI fiber tracking provides maps of axonal bundles and was combined with intraoperative mapping of eloquent cortex for a patient undergoing brain tumor surgery. Tracks from eight stimulated sites in the inferior frontal cortex including mouth motor, speech arrest, and anomia were generated from the diffusion tensor MRI data. The regions connected by the fiber tracking were compared to foci from previous functional imaging reports on language tasks. Connections were found between speech arrest, mouth motor, and anomia sites and the SMA proper and cerebral peduncle. The speech arrest and a mouth motor site were also seen to connect to the putamen via the external capsule. This is the first demonstration of delineation of subcortical pathways using diffusion tensor MRI fiber tracking with intraoperative cortical stimulation. The combined techniques may provide improved preservation of eloquent regions during neurological surgery, and may provide access to direct connectivity information between functional regions of the brain.

Subcortical pathways serving cortical language sites: initial experience with diffusion tensor imaging fiber tracking combined with intraoperative language mapping

PubMed Central

Henry, Roland G.; Berman, Jeffrey I.; Nagarajan, Srikantan S.; Mukherjee, Pratik; Berger, Mitchel S.

2014-01-01

The combination of mapping functional cortical neurons by intraoperative cortical stimulation and axonal architecture by diffusion tensor MRI fiber tracking can be used to delineate the pathways between functional regions. In this study the authors investigated the feasibility of combining these techniques to yield connectivity associated with motor speech and naming. Diffusion tensor MRI fiber tracking provides maps of axonal bundles and was combined with intraoperative mapping of eloquent cortex for a patient undergoing brain tumor surgery. Tracks from eight stimulated sites in the inferior frontal cortex including mouth motor, speech arrest, and anomia were generated from the diffusion tensor MRI data. The regions connected by the fiber tracking were compared to foci from previous functional imaging reports on language tasks. Connections were found between speech arrest, mouth motor, and anomia sites and the SMA proper and cerebral peduncle. The speech arrest and a mouth motor site were also seen to connect to the putamen via the external capsule. This is the first demonstration of delineation of subcortical pathways using diffusion tensor MRI fiber tracking with intraoperative cortical stimulation. The combined techniques may provide improved preservation of eloquent regions during neurological surgery, and may provide access to direct connectivity information between functional regions of the brain. PMID:14980564

Syntactic Processing in Bilinguals: An fNIRS Study

ERIC Educational Resources Information Center

Scherer, Lilian Cristine; Fonseca, Rochele Paz; Amiri, Mahnoush; Adrover-Roig, Daniel; Marcotte, Karine; Giroux, Francine; Senhadji, Noureddine; Benali, Habib; Lesage, Frederic; Ansaldo, Ana Ines

2012-01-01

The study of the neural basis of syntactic processing has greatly benefited from neuroimaging techniques. Research on syntactic processing in bilinguals has used a variety of techniques, including mainly functional magnetic resonance imaging (fMRI) and event-related potentials (ERP). This paper reports on a functional near-infrared spectroscopy…

Correlation between resting state fMRI total neuronal activity and PET metabolism in healthy controls and patients with disorders of consciousness.

PubMed

Soddu, Andrea; Gómez, Francisco; Heine, Lizette; Di Perri, Carol; Bahri, Mohamed Ali; Voss, Henning U; Bruno, Marie-Aurélie; Vanhaudenhuyse, Audrey; Phillips, Christophe; Demertzi, Athena; Chatelle, Camille; Schrouff, Jessica; Thibaut, Aurore; Charland-Verville, Vanessa; Noirhomme, Quentin; Salmon, Eric; Tshibanda, Jean-Flory Luaba; Schiff, Nicholas D; Laureys, Steven

2016-01-01

The mildly invasive 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established imaging technique to measure 'resting state' cerebral metabolism. This technique made it possible to assess changes in metabolic activity in clinical applications, such as the study of severe brain injury and disorders of consciousness. We assessed the possibility of creating functional MRI activity maps, which could estimate the relative levels of activity in FDG-PET cerebral metabolic maps. If no metabolic absolute measures can be extracted, our approach may still be of clinical use in centers without access to FDG-PET. It also overcomes the problem of recognizing individual networks of independent component selection in functional magnetic resonance imaging (fMRI) resting state analysis. We extracted resting state fMRI functional connectivity maps using independent component analysis and combined only components of neuronal origin. To assess neuronality of components a classification based on support vector machine (SVM) was used. We compared the generated maps with the FDG-PET maps in 16 healthy controls, 11 vegetative state/unresponsive wakefulness syndrome patients and four locked-in patients. The results show a significant similarity with ρ = 0.75 ± 0.05 for healthy controls and ρ = 0.58 ± 0.09 for vegetative state/unresponsive wakefulness syndrome patients between the FDG-PET and the fMRI based maps. FDG-PET, fMRI neuronal maps, and the conjunction analysis show decreases in frontoparietal and medial regions in vegetative patients with respect to controls. Subsequent analysis in locked-in syndrome patients produced also consistent maps with healthy controls. The constructed resting state fMRI functional connectivity map points toward the possibility for fMRI resting state to estimate relative levels of activity in a metabolic map.

Biological intervertebral disc replacement: an in vivo model and comparison of two surgical techniques to approach the rat caudal disc

PubMed Central

Gebhard, Harry; James, Andrew R.; Bowles, Robby D.; Dyke, Jonathan P.; Saleh, Tatianna; Doty, Stephen P.; Bonassar, Lawrence J.; Härtl, Roger

2011-01-01

Study design: Prospective randomized animal study. Objective: To determine a surgical technique for reproducible and functional intervertebral disc replacement in an orthotopic animal model. Methods: The caudal 3/4 intervertebral disc (IVD) of the rat tail was approached by two surgical techniques: blunt dissection, stripping and retracting (Technique 1) or incising and repairing (Technique 2) the dorsal longitudinal tendons. The intervertebral disc was dissected and removed, and then either discarded or reinserted. Outcome measures were perioperative complications, spontaneous tail movement, 7T MRI (T1- and T2-sequences for measurement of disc space height (DSH) and disc hydration). Microcomputed tomographic imaging (micro CT) was additionally performed postmortem. Results: No vascular injuries occurred and no systemic or local infections were observed over the course of 1 month. Tail movements were maintained. With tendon retraction (Technique 1) gross loss of DSH occurred with both discectomy and reinsertion. Tendon division (Technique 2) maintained DSH with IVD reinsertion but not without. The DSH was demonstrated on MRI measurement. A new scoring system to assess IVD appearances was described. Conclusions: The rat tail model, with a tendon dividing surgical technique, can function as an orthotopic animal model for IVD research. Mechanical stimulation is maintained by preserved tail movements. 7T MRI is a feasible modality for longitudinal monitoring for the rat caudal disc. PMID:22956934

A Hitchhiker's Guide to Functional Magnetic Resonance Imaging

PubMed Central

Soares, José M.; Magalhães, Ricardo; Moreira, Pedro S.; Sousa, Alexandre; Ganz, Edward; Sampaio, Adriana; Alves, Victor; Marques, Paulo; Sousa, Nuno

2016-01-01

Functional Magnetic Resonance Imaging (fMRI) studies have become increasingly popular both with clinicians and researchers as they are capable of providing unique insights into brain functions. However, multiple technical considerations (ranging from specifics of paradigm design to imaging artifacts, complex protocol definition, and multitude of processing and methods of analysis, as well as intrinsic methodological limitations) must be considered and addressed in order to optimize fMRI analysis and to arrive at the most accurate and grounded interpretation of the data. In practice, the researcher/clinician must choose, from many available options, the most suitable software tool for each stage of the fMRI analysis pipeline. Herein we provide a straightforward guide designed to address, for each of the major stages, the techniques, and tools involved in the process. We have developed this guide both to help those new to the technique to overcome the most critical difficulties in its use, as well as to serve as a resource for the neuroimaging community. PMID:27891073

Modelling passive diastolic mechanics with quantitative MRI of cardiac structure and function.

PubMed

Wang, Vicky Y; Lam, H I; Ennis, Daniel B; Cowan, Brett R; Young, Alistair A; Nash, Martyn P

2009-10-01

The majority of patients with clinically diagnosed heart failure have normal systolic pump function and are commonly categorized as suffering from diastolic heart failure. The left ventricle (LV) remodels its structure and function to adapt to pathophysiological changes in geometry and loading conditions, which in turn can alter the passive ventricular mechanics. In order to better understand passive ventricular mechanics, a LV finite element (FE) model was customized to geometric data segmented from in vivo tagged magnetic resonance images (MRI) data and myofibre orientation derived from ex vivo diffusion tensor MRI (DTMRI) of a canine heart using nonlinear finite element fitting techniques. MRI tissue tagging enables quantitative evaluation of cardiac mechanical function with high spatial and temporal resolution, whilst the direction of maximum water diffusion in each voxel of a DTMRI directly corresponds to the local myocardial fibre orientation. Due to differences in myocardial geometry between in vivo and ex vivo imaging, myofibre orientations were mapped into the geometric FE model using host mesh fitting (a free form deformation technique). Pressure recordings, temporally synchronized to the tagging data, were used as the loading constraints to simulate the LV deformation during diastole. Simulation of diastolic LV mechanics allowed us to estimate the stiffness of the passive LV myocardium based on kinematic data obtained from tagged MRI. Integrated physiological modelling of this kind will allow more insight into mechanics of the LV on an individualized basis, thereby improving our understanding of the underlying structural basis of mechanical dysfunction under pathological conditions.

Multimodal MRI for early diabetic mild cognitive impairment: study protocol of a prospective diagnostic trial.

PubMed

Yu, Ying; Sun, Qian; Yan, Lin-Feng; Hu, Yu-Chuan; Nan, Hai-Yan; Yang, Yang; Liu, Zhi-Cheng; Wang, Wen; Cui, Guang-Bin

2016-08-24

Type 2 diabetes mellitus (T2DM) is a risk factor for dementia. Mild cognitive impairment (MCI), an intermediary state between normal cognition and dementia, often occurs during the prodromal diabetic stage, making early diagnosis and intervention of MCI very important. Latest neuroimaging techniques revealed some underlying microstructure alterations for diabetic MCI, from certain aspects. But there still lacks an integrated multimodal MRI system to detect early neuroimaging changes in diabetic MCI patients. Thus, we intended to conduct a diagnostic trial using multimodal MRI techniques to detect early diabetic MCI that is determined by the Montreal Cognitive Assessment (MoCA). In this study, healthy controls, prodromal diabetes and diabetes subjects (53 subjects/group) aged 40-60 years will be recruited from the physical examination center of Tangdu Hospital. The neuroimaging and psychometric measurements will be repeated at a 0.5 year-interval for 2.5 years' follow-up. The primary outcome measures are 1) Microstructural and functional alterations revealed with multimodal MRI scans including structure magnetic resonance imaging (sMRI), resting state functional magnetic resonance imaging (rs-fMRI), diffusion kurtosis imaging (DKI), and three-dimensional pseudo-continuous arterial spin labeling (3D-pCASL); 2) Cognition evaluation with MoCA. The second outcome measures are obesity, metabolic characteristics, lifestyle and quality of life. The study will provide evidence for the potential use of multimodal MRI techniques with psychometric evaluation in diagnosing MCI at prodromal diabetic stage so as to help decision making in early intervention and improve the prognosis of T2DM. This study has been registered to ClinicalTrials.gov ( NCT02420470 ) on April 2, 2015 and published on July 29, 2015.

Oncologic PET/MRI, part 1: tumors of the brain, head and neck, chest, abdomen, and pelvis.

PubMed

Buchbender, Christian; Heusner, Till A; Lauenstein, Thomas C; Bockisch, Andreas; Antoch, Gerald

2012-06-01

In oncology, staging forms the basis for prognostic consideration and directly influences patient care by determining the therapeutic approach. Cross-sectional imaging techniques, especially when combined with PET information, play an important role in cancer staging. With the recent introduction of integrated whole-body PET/MRI into clinical practice, a novel metabolic-anatomic imaging technique is now available. PET/MRI seems to be highly accurate in T-staging of tumor entities for which MRI has traditionally been favored, such as squamous cell carcinomas of the head and neck. By adding functional MRI to PET, PET/MRI may further improve diagnostic accuracy in the differentiation of scar tissue from recurrence of tumors such as rectal cancer. This hypothesis will have to be assessed in future studies. With regard to N-staging, PET/MRI does not seem to provide a considerable benefit as compared with PET/CT but provides similar N-staging accuracy when applied as a whole-body staging approach. M-staging will benefit from MRI accuracy in the brain and the liver. The purpose of this review is to summarize the available first experiences with PET/MRI and to outline the potential value of PET/MRI in oncologic applications for which data on PET/MRI are still lacking.

An Improved Framework for Confound Regression and Filtering for Control of Motion Artifact in the Preprocessing of Resting-State Functional Connectivity Data

PubMed Central

Satterthwaite, Theodore D.; Elliott, Mark A.; Gerraty, Raphael T.; Ruparel, Kosha; Loughead, James; Calkins, Monica E.; Eickhoff, Simon B.; Hakonarson, Hakon; Gur, Ruben C.; Gur, Raquel E.; Wolf, Daniel H.

2013-01-01

Several recent reports in large, independent samples have demonstrated the influence of motion artifact on resting-state functional connectivity MRI (rsfc-MRI). Standard rsfc-MRI preprocessing typically includes regression of confounding signals and band-pass filtering. However, substantial heterogeneity exists in how these techniques are implemented across studies, and no prior study has examined the effect of differing approaches for the control of motion-induced artifacts. To better understand how in-scanner head motion affects rsfc-MRI data, we describe the spatial, temporal, and spectral characteristics of motion artifacts in a sample of 348 adolescents. Analyses utilize a novel approach for describing head motion on a voxelwise basis. Next, we systematically evaluate the efficacy of a range of confound regression and filtering techniques for the control of motion-induced artifacts. Results reveal that the effectiveness of preprocessing procedures on the control of motion is heterogeneous, and that improved preprocessing provides a substantial benefit beyond typical procedures. These results demonstrate that the effect of motion on rsfc-MRI can be substantially attenuated through improved preprocessing procedures, but not completely removed. PMID:22926292

Spatially Regularized Machine Learning for Task and Resting-state fMRI

PubMed Central

Song, Xiaomu; Panych, Lawrence P.; Chen, Nan-kuei

2015-01-01

Background Reliable mapping of brain function across sessions and/or subjects in task- and resting-state has been a critical challenge for quantitative fMRI studies although it has been intensively addressed in the past decades. New Method A spatially regularized support vector machine (SVM) technique was developed for the reliable brain mapping in task- and resting-state. Unlike most existing SVM-based brain mapping techniques, which implement supervised classifications of specific brain functional states or disorders, the proposed method performs a semi-supervised classification for the general brain function mapping where spatial correlation of fMRI is integrated into the SVM learning. The method can adapt to intra- and inter-subject variations induced by fMRI nonstationarity, and identify a true boundary between active and inactive voxels, or between functionally connected and unconnected voxels in a feature space. Results The method was evaluated using synthetic and experimental data at the individual and group level. Multiple features were evaluated in terms of their contributions to the spatially regularized SVM learning. Reliable mapping results in both task- and resting-state were obtained from individual subjects and at the group level. Comparison with Existing Methods A comparison study was performed with independent component analysis, general linear model, and correlation analysis methods. Experimental results indicate that the proposed method can provide a better or comparable mapping performance at the individual and group level. Conclusions The proposed method can provide accurate and reliable mapping of brain function in task- and resting-state, and is applicable to a variety of quantitative fMRI studies. PMID:26470627

New insights into lung diseases using hyperpolarized gas MRI.

PubMed

Flors, L; Altes, T A; Mugler, J P; de Lange, E E; Miller, G W; Mata, J F; Ruset, I C; Hersman, F W

2015-01-01

Hyperpolarized (HP) gases are a new class of contrast agents that permit to obtain high temporal and spatial resolution magnetic resonance images (MRI) of the lung airspaces. HP gas MRI has become important research tool not only for morphological and functional evaluation of normal pulmonary physiology but also for regional quantification of pathologic changes occurring in several lung diseases. The purpose of this work is to provide an introduction to MRI using HP noble gases, describing both the basic principles of the technique and the new information about lung disease provided by clinical studies with this method. The applications of the technique in normal subjects, smoking related lung disease, asthma, and cystic fibrosis are reviewed. Copyright © 2014 SERAM. Published by Elsevier España, S.L.U. All rights reserved.

Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion

PubMed Central

Power, Jonathan D; Barnes, Kelly A; Snyder, Abraham Z; Schlaggar, Bradley L; Petersen, Steven E

2011-01-01

Here, we demonstrate that subject motion produces substantial changes in the timecourses of resting state functional connectivity MRI (rs-fcMRI) data despite compensatory spatial registration and regression of motion estimates from the data. These changes cause systematic but spurious correlation structures throughout the brain. Specifically, many long-distance correlations are decreased by subject motion, whereas many short-distance correlations are increased. These changes in rs-fcMRI correlations do not arise from, nor are they adequately countered by, some common functional connectivity processing steps. Two indices of data quality are proposed, and a simple method to reduce motion-related effects in rs-fcMRI analyses is demonstrated that should be flexibly implementable across a variety of software platforms. We demonstrate how application of this technique impacts our own data, modifying previous conclusions about brain development. These results suggest the need for greater care in dealing with subject motion, and the need to critically revisit previous rs-fcMRI work that may not have adequately controlled for effects of transient subject movements. PMID:22019881

fMRI during natural sleep as a method to study brain function during early childhood.

PubMed

Redcay, Elizabeth; Kennedy, Daniel P; Courchesne, Eric

2007-12-01

Many techniques to study early functional brain development lack the whole-brain spatial resolution that is available with fMRI. We utilized a relatively novel method in which fMRI data were collected from children during natural sleep. Stimulus-evoked responses to auditory and visual stimuli as well as stimulus-independent functional networks were examined in typically developing 2-4-year-old children. Reliable fMRI data were collected from 13 children during presentation of auditory stimuli (tones, vocal sounds, and nonvocal sounds) in a block design. Twelve children were presented with visual flashing lights at 2.5 Hz. When analyses combined all three types of auditory stimulus conditions as compared to rest, activation included bilateral superior temporal gyri/sulci (STG/S) and right cerebellum. Direct comparisons between conditions revealed significantly greater responses to nonvocal sounds and tones than to vocal sounds in a number of brain regions including superior temporal gyrus/sulcus, medial frontal cortex and right lateral cerebellum. The response to visual stimuli was localized to occipital cortex. Furthermore, stimulus-independent functional connectivity MRI analyses (fcMRI) revealed functional connectivity between STG and other temporal regions (including contralateral STG) and medial and lateral prefrontal regions. Functional connectivity with an occipital seed was localized to occipital and parietal cortex. In sum, 2-4 year olds showed a differential fMRI response both between stimulus modalities and between stimuli in the auditory modality. Furthermore, superior temporal regions showed functional connectivity with numerous higher-order regions during sleep. We conclude that the use of sleep fMRI may be a valuable tool for examining functional brain organization in young children.

Maintenance and Representation of Mind Wandering during Resting-State fMRI.

PubMed

Chou, Ying-Hui; Sundman, Mark; Whitson, Heather E; Gaur, Pooja; Chu, Mei-Lan; Weingarten, Carol P; Madden, David J; Wang, Lihong; Kirste, Imke; Joliot, Marc; Diaz, Michele T; Li, Yi-Ju; Song, Allen W; Chen, Nan-Kuei

2017-01-12

Major advances in resting-state functional magnetic resonance imaging (fMRI) techniques in the last two decades have provided a tool to better understand the functional organization of the brain both in health and illness. Despite such developments, characterizing regulation and cerebral representation of mind wandering, which occurs unavoidably during resting-state fMRI scans and may induce variability of the acquired data, remains a work in progress. Here, we demonstrate that a decrease or decoupling in functional connectivity involving the caudate nucleus, insula, medial prefrontal cortex and other domain-specific regions was associated with more sustained mind wandering in particular thought domains during resting-state fMRI. Importantly, our findings suggest that temporal and between-subject variations in functional connectivity of above-mentioned regions might be linked with the continuity of mind wandering. Our study not only provides a preliminary framework for characterizing the maintenance and cerebral representation of different types of mind wandering, but also highlights the importance of taking mind wandering into consideration when studying brain organization with resting-state fMRI in the future.

Functional magnetic resonance imaging: basic principles and application in the neurosciences.

PubMed

Labbé Atenas, T; Ciampi Díaz, E; Cruz Quiroga, J P; Uribe Arancibia, S; Cárcamo Rodríguez, C

2018-03-12

Functional magnetic resonance imaging (fMRI) is an advanced tool for the study of brain functions in healthy subjects and in neuropsychiatric patients. This tool makes it possible to identify and locate specific phenomena related to neuronal metabolism and activity. Starting with the detection of changes in the blood supply to a region that participates in a function, more complex approaches have been developed to study the dynamics of neuronal networks. Studies examining the brain at rest or involved in different tasks have provided evidence related to the onset, development, and/or response to treatment in various diseases. The diversity of the possible artifacts associated with image registration as well as the complexity of the analytical experimental designs has generated abundant debate about the technique behind fMRI. This article aims to introduce readers to the fundamentals underlying fMRI, to explain how fMRI studies are interpreted, and to discuss fMRI's contributions to the study of the mechanisms underlying diverse diseases of the nervous system. Copyright © 2018 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

Optogenetic Functional MRI

PubMed Central

Lin, Peter; Fang, Zhongnan; Liu, Jia; Lee, Jin Hyung

2016-01-01

The investigation of the functional connectivity of precise neural circuits across the entire intact brain can be achieved through optogenetic functional magnetic resonance imaging (ofMRI), which is a novel technique that combines the relatively high spatial resolution of high-field fMRI with the precision of optogenetic stimulation. Fiber optics that enable delivery of specific wavelengths of light deep into the brain in vivo are implanted into regions of interest in order to specifically stimulate targeted cell types that have been genetically induced to express light-sensitive trans-membrane conductance channels, called opsins. fMRI is used to provide a non-invasive method of determining the brain's global dynamic response to optogenetic stimulation of specific neural circuits through measurement of the blood-oxygen-level-dependent (BOLD) signal, which provides an indirect measurement of neuronal activity. This protocol describes the construction of fiber optic implants, the implantation surgeries, the imaging with photostimulation and the data analysis required to successfully perform ofMRI. In summary, the precise stimulation and whole-brain monitoring ability of ofMRI are crucial factors in making ofMRI a powerful tool for the study of the connectomics of the brain in both healthy and diseased states. PMID:27167840

Functional MRI during Hippocampal Deep Brain Stimulation in the Healthy Rat Brain.

PubMed

Van Den Berge, Nathalie; Vanhove, Christian; Descamps, Benedicte; Dauwe, Ine; van Mierlo, Pieter; Vonck, Kristl; Keereman, Vincent; Raedt, Robrecht; Boon, Paul; Van Holen, Roel

2015-01-01

Deep Brain Stimulation (DBS) is a promising treatment for neurological and psychiatric disorders. The mechanism of action and the effects of electrical fields administered to the brain by means of an electrode remain to be elucidated. The effects of DBS have been investigated primarily by electrophysiological and neurochemical studies, which lack the ability to investigate DBS-related responses on a whole-brain scale. Visualization of whole-brain effects of DBS requires functional imaging techniques such as functional Magnetic Resonance Imaging (fMRI), which reflects changes in blood oxygen level dependent (BOLD) responses throughout the entire brain volume. In order to visualize BOLD responses induced by DBS, we have developed an MRI-compatible electrode and an acquisition protocol to perform DBS during BOLD fMRI. In this study, we investigate whether DBS during fMRI is valuable to study local and whole-brain effects of hippocampal DBS and to investigate the changes induced by different stimulation intensities. Seven rats were stereotactically implanted with a custom-made MRI-compatible DBS-electrode in the right hippocampus. High frequency Poisson distributed stimulation was applied using a block-design paradigm. Data were processed by means of Independent Component Analysis. Clusters were considered significant when p-values were <0.05 after correction for multiple comparisons. Our data indicate that real-time hippocampal DBS evokes a bilateral BOLD response in hippocampal and other mesolimbic structures, depending on the applied stimulation intensity. We conclude that simultaneous DBS and fMRI can be used to detect local and whole-brain responses to circuit activation with different stimulation intensities, making this technique potentially powerful for exploration of cerebral changes in response to DBS for both preclinical and clinical DBS.

Functional MRI during Hippocampal Deep Brain Stimulation in the Healthy Rat Brain

PubMed Central

Van Den Berge, Nathalie; Vanhove, Christian; Descamps, Benedicte; Dauwe, Ine; van Mierlo, Pieter; Vonck, Kristl; Keereman, Vincent; Raedt, Robrecht; Boon, Paul; Van Holen, Roel

2015-01-01

Deep Brain Stimulation (DBS) is a promising treatment for neurological and psychiatric disorders. The mechanism of action and the effects of electrical fields administered to the brain by means of an electrode remain to be elucidated. The effects of DBS have been investigated primarily by electrophysiological and neurochemical studies, which lack the ability to investigate DBS-related responses on a whole-brain scale. Visualization of whole-brain effects of DBS requires functional imaging techniques such as functional Magnetic Resonance Imaging (fMRI), which reflects changes in blood oxygen level dependent (BOLD) responses throughout the entire brain volume. In order to visualize BOLD responses induced by DBS, we have developed an MRI-compatible electrode and an acquisition protocol to perform DBS during BOLD fMRI. In this study, we investigate whether DBS during fMRI is valuable to study local and whole-brain effects of hippocampal DBS and to investigate the changes induced by different stimulation intensities. Seven rats were stereotactically implanted with a custom-made MRI-compatible DBS-electrode in the right hippocampus. High frequency Poisson distributed stimulation was applied using a block-design paradigm. Data were processed by means of Independent Component Analysis. Clusters were considered significant when p-values were <0.05 after correction for multiple comparisons. Our data indicate that real-time hippocampal DBS evokes a bilateral BOLD response in hippocampal and other mesolimbic structures, depending on the applied stimulation intensity. We conclude that simultaneous DBS and fMRI can be used to detect local and whole-brain responses to circuit activation with different stimulation intensities, making this technique potentially powerful for exploration of cerebral changes in response to DBS for both preclinical and clinical DBS. PMID:26193653

Neuroimaging Techniques: a Conceptual Overview of Physical Principles, Contribution and History

NASA Astrophysics Data System (ADS)

Minati, Ludovico

2006-06-01

This paper is meant to provide a brief overview of the techniques currently used to image the brain and to study non-invasively its anatomy and function. After a historical summary in the first section, general aspects are outlined in the second section. The subsequent six sections survey, in order, computed tomography (CT), morphological magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), diffusion-tensor magnetic resonance imaging (DWI/DTI), positron emission tomography (PET), and electro- and magneto-encephalography (EEG/MEG) based imaging. Underlying physical principles, modelling and data processing approaches, as well as clinical and research relevance are briefly outlined for each technique. Given the breadth of the scope, there has been no attempt to be comprehensive. The ninth and final section outlines some aspects of active research in neuroimaging.

A general dual-bolus approach for quantitative DCE-MRI.

PubMed

Kershaw, Lucy E; Cheng, Hai-Ling Margaret

2011-02-01

To present a dual-bolus technique for quantitative dynamic contrast-enhanced MRI (DCE-MRI) and show that it can give an arterial input function (AIF) measurement equivalent to that from a single-bolus protocol. Five rabbits were imaged using a dual-bolus technique applicable for high-resolution DCE-MRI, incorporating a time resolved imaging of contrast kinetics (TRICKS) sequence for rapid temporal sampling. AIFs were measured from both the low-dose prebolus and the high-dose main bolus in the abdominal aorta. In one animal, TRICKS and fast spoiled gradient echo (FSPGR) acquisitions were compared. The scaled prebolus AIF was shown to match the main bolus AIF, with 95% confidence intervals overlapping for fits of gamma-variate functions to the first pass and linear fits to the washout phase, with the exception of one case. The AIFs measured using TRICKS and FSPGR were shown to be equivalent in one animal. The proposed technique can capture even the rapid circulation kinetics in the rabbit aorta, and the scaled prebolus AIF is equivalent to the AIF from a high-dose injection. This allows separate measurements of the AIF and tissue uptake curves, meaning that each curve can then be acquired using a protocol tailored to its specific requirements. Copyright © 2011 Elsevier Inc. All rights reserved.

Using fMRI to Study Conceptual Change: Why and How?

ERIC Educational Resources Information Center

Masson, Steve; Potvin, Patrice; Riopel, Martin; Foisy, Lorie-Marlene Brault; Lafortune, Stephanie

2012-01-01

Although the use of brain imaging techniques, such as functional magnetic resonance imaging (fMRI) is increasingly common in educational research, only a few studies regarding science learning have so far taken advantage of this technology. This paper aims to facilitate the design and implementation of brain imaging studies relating to science…

Kinematic MRI study of upper-airway biomechanics using electrical muscle stimulation

NASA Astrophysics Data System (ADS)

Brennick, Michael J.; Margulies, Susan S.; Ford, John C.; Gefter, Warren B.; Pack, Allan I.

1997-05-01

We have developed a new and powerful method to study the movement and function of upper airway muscles. Our method is to use direct electrical stimulation of individual upper airway muscles, while performing state of the art high resolution magnetic resonance imaging (MRI). We have adapted a paralyzed isolated UA cat model so that positive or negative static pressure in the UA can be controlled at specific levels while electrical muscle stimulation is applied during MRI. With these techniques we can assess the effect of muscle stimulation on airway cross-sectional area compliance and soft tissue motion. We are reporting the preliminary results and MRI techniques which have enabled us to examine changes in airway dimensions which result form electrical stimulation of specific upper airway dilator muscles. The results of this study will be relevant to the development of new clinical treatments for obstructive sleep apnea by providing new information as to exactly how upper airway muscles function to dilate the upper airway and the strength of stimulation required to prevent the airway obstruction when overall muscle tone may not be sufficient to maintain regular breathing.

Disrupted Cerebro-cerebellar Intrinsic Functional Connectivity in Young Adults with High-functioning Autism Spectrum Disorder: A Data-driven, Whole-brain, High Temporal Resolution fMRI Study.

PubMed

Arnold Anteraper, Sheeba; Guell, Xavier; D'Mello, Anila; Joshi, Neha; Whitfield-Gabrieli, Susan; Joshi, Gagan

2018-06-13

To examine the resting-state functional-connectivity (RsFc) in young adults with high-functioning autism spectrum disorder (HF-ASD) using state-of-the-art fMRI data acquisition and analysis techniques. Simultaneous multi-slice, high temporal resolution fMRI acquisition; unbiased whole-brain connectome-wide multivariate pattern analysis (MVPA) techniques for assessing RsFc; and post-hoc whole-brain seed-to-voxel analyses using MVPA results as seeds. MVPA revealed two clusters of abnormal connectivity in the cerebellum. Whole-brain seed-based functional connectivity analyses informed by MVPA-derived clusters showed significant under connectivity between the cerebellum and social, emotional, and language brain regions in the HF-ASD group compared to healthy controls. The results we report are coherent with existing structural, functional, and RsFc literature in autism, extend previous literature reporting cerebellar abnormalities in the neuropathology of autism, and highlight the cerebellum as a potential target for therapeutic, diagnostic, predictive, and prognostic developments in ASD. The description of functional connectivity abnormalities using whole-brain, data-driven analyses as reported in the present study may crucially advance the development of ASD biomarkers, targets for therapeutic interventions, and neural predictors for measuring treatment response.

Timed function tests, motor function measure, and quantitative thigh muscle MRI in ambulant children with Duchenne muscular dystrophy: A cross-sectional analysis.

PubMed

Schmidt, Simone; Hafner, Patricia; Klein, Andrea; Rubino-Nacht, Daniela; Gocheva, Vanya; Schroeder, Jonas; Naduvilekoot Devasia, Arjith; Zuesli, Stephanie; Bernert, Guenther; Laugel, Vincent; Bloetzer, Clemens; Steinlin, Maja; Capone, Andrea; Gloor, Monika; Tobler, Patrick; Haas, Tanja; Bieri, Oliver; Zumbrunn, Thomas; Fischer, Dirk; Bonati, Ulrike

2018-01-01

The development of new therapeutic agents for the treatment of Duchenne muscular dystrophy has put a focus on defining outcome measures most sensitive to capture treatment effects. This cross-sectional analysis investigates the relation between validated clinical assessments such as the 6-minute walk test, motor function measure and quantitative muscle MRI of thigh muscles in ambulant Duchenne muscular dystrophy patients, aged 6.5 to 10.8 years (mean 8.2, SD 1.1). Quantitative muscle MRI included the mean fat fraction using a 2-point Dixon technique, and transverse relaxation time (T2) measurements. All clinical assessments were highly significantly inter-correlated with p < 0.001. The strongest correlation with the motor function measure and its D1-subscore was shown by the 6-minute walk test. Clinical assessments showed no correlation with age. Importantly, quantitative muscle MRI values significantly correlated with all clinical assessments with the extensors showing the strongest correlation. In contrast to the clinical assessments, quantitative muscle MRI values were highly significantly correlated with age. In conclusion, the motor function measure and timed function tests measure disease severity in a highly comparable fashion and all tests correlated with quantitative muscle MRI values quantifying fatty muscle degeneration. Copyright © 2017 Elsevier B.V. All rights reserved.

Functional MRI detects perfusion impairment in renal allografts with delayed graft function.

PubMed

Hueper, Katja; Gueler, Faikah; Bräsen, Jan Hinrich; Gutberlet, Marcel; Jang, Mi-Sun; Lehner, Frank; Richter, Nicolas; Hanke, Nils; Peperhove, Matti; Martirosian, Petros; Tewes, Susanne; Vo Chieu, Van Dai; Großhennig, Anika; Haller, Hermann; Wacker, Frank; Gwinner, Wilfried; Hartung, Dagmar

2015-06-15

Delayed graft function (DGF) after kidney transplantation is not uncommon, and it is associated with long-term allograft impairment. Our aim was to compare renal perfusion changes measured with noninvasive functional MRI in patients early after kidney transplantation to renal function and allograft histology in biopsy samples. Forty-six patients underwent MRI 4-11 days after transplantation. Contrast-free MRI renal perfusion images were acquired using an arterial spin labeling technique. Renal function was assessed by estimated glomerular filtration rate (eGFR), and renal biopsies were performed when indicated within 5 days of MRI. Twenty-six of 46 patients had DGF. Of these, nine patients had acute rejection (including borderline), and eight had other changes (e.g., tubular injury or glomerulosclerosis). Renal perfusion was significantly lower in the DGF group compared with the group with good allograft function (231 ± 15 vs. 331 ± 15 ml·min(-1)·100 g(-1), P < 0.001). Living donor allografts exhibited significantly higher perfusion values compared with deceased donor allografts (P < 0.001). Renal perfusion significantly correlated with eGFR (r = 0.64, P < 0.001), resistance index (r = -0.57, P < 0.001), and cold ischemia time (r = -0.48, P < 0.01). Furthermore, renal perfusion impairment early after transplantation predicted inferior renal outcome and graft loss. In conclusion, noninvasive functional MRI detects renal perfusion impairment early after kidney transplantation in patients with DGF. Copyright © 2015 the American Physiological Society.

Characterizing the functional MRI response using Tikhonov regularization.

PubMed

Vakorin, Vasily A; Borowsky, Ron; Sarty, Gordon E

2007-09-20

The problem of evaluating an averaged functional magnetic resonance imaging (fMRI) response for repeated block design experiments was considered within a semiparametric regression model with autocorrelated residuals. We applied functional data analysis (FDA) techniques that use a least-squares fitting of B-spline expansions with Tikhonov regularization. To deal with the noise autocorrelation, we proposed a regularization parameter selection method based on the idea of combining temporal smoothing with residual whitening. A criterion based on a generalized chi(2)-test of the residuals for white noise was compared with a generalized cross-validation scheme. We evaluated and compared the performance of the two criteria, based on their effect on the quality of the fMRI response. We found that the regularization parameter can be tuned to improve the noise autocorrelation structure, but the whitening criterion provides too much smoothing when compared with the cross-validation criterion. The ultimate goal of the proposed smoothing techniques is to facilitate the extraction of temporal features in the hemodynamic response for further analysis. In particular, these FDA methods allow us to compute derivatives and integrals of the fMRI signal so that fMRI data may be correlated with behavioral and physiological models. For example, positive and negative hemodynamic responses may be easily and robustly identified on the basis of the first derivative at an early time point in the response. Ultimately, these methods allow us to verify previously reported correlations between the hemodynamic response and the behavioral measures of accuracy and reaction time, showing the potential to recover new information from fMRI data. 2007 John Wiley & Sons, Ltd

A multimodal MRI dataset of professional chess players.

PubMed

Li, Kaiming; Jiang, Jing; Qiu, Lihua; Yang, Xun; Huang, Xiaoqi; Lui, Su; Gong, Qiyong

2015-01-01

Chess is a good model to study high-level human brain functions such as spatial cognition, memory, planning, learning and problem solving. Recent studies have demonstrated that non-invasive MRI techniques are valuable for researchers to investigate the underlying neural mechanism of playing chess. For professional chess players (e.g., chess grand masters and masters or GM/Ms), what are the structural and functional alterations due to long-term professional practice, and how these alterations relate to behavior, are largely veiled. Here, we report a multimodal MRI dataset from 29 professional Chinese chess players (most of whom are GM/Ms), and 29 age matched novices. We hope that this dataset will provide researchers with new materials to further explore high-level human brain functions.

New magnetic resonance imaging methods in nephrology

PubMed Central

Zhang, Jeff L.; Morrell, Glen; Rusinek, Henry; Sigmund, Eric; Chandarana, Hersh; Lerman, Lilach O.; Prasad, Pottumarthi Vara; Niles, David; Artz, Nathan; Fain, Sean; Vivier, Pierre H.; Cheung, Alfred K.; Lee, Vivian S.

2013-01-01

Established as a method to study anatomic changes, such as renal tumors or atherosclerotic vascular disease, magnetic resonance imaging (MRI) to interrogate renal function has only recently begun to come of age. In this review, we briefly introduce some of the most important MRI techniques for renal functional imaging, and then review current findings on their use for diagnosis and monitoring of major kidney diseases. Specific applications include renovascular disease, diabetic nephropathy, renal transplants, renal masses, acute kidney injury and pediatric anomalies. With this review, we hope to encourage more collaboration between nephrologists and radiologists to accelerate the development and application of modern MRI tools in nephrology clinics. PMID:24067433

Functional magnetic resonance imaging (FMRI) with auditory stimulation in songbirds.

PubMed

Van Ruijssevelt, Lisbeth; De Groof, Geert; Van der Kant, Anne; Poirier, Colline; Van Audekerke, Johan; Verhoye, Marleen; Van der Linden, Annemie

2013-06-03

The neurobiology of birdsong, as a model for human speech, is a pronounced area of research in behavioral neuroscience. Whereas electrophysiology and molecular approaches allow the investigation of either different stimuli on few neurons, or one stimulus in large parts of the brain, blood oxygenation level dependent (BOLD) functional Magnetic Resonance Imaging (fMRI) allows combining both advantages, i.e. compare the neural activation induced by different stimuli in the entire brain at once. fMRI in songbirds is challenging because of the small size of their brains and because their bones and especially their skull comprise numerous air cavities, inducing important susceptibility artifacts. Gradient-echo (GE) BOLD fMRI has been successfully applied to songbirds (1-5) (for a review, see (6)). These studies focused on the primary and secondary auditory brain areas, which are regions free of susceptibility artifacts. However, because processes of interest may occur beyond these regions, whole brain BOLD fMRI is required using an MRI sequence less susceptible to these artifacts. This can be achieved by using spin-echo (SE) BOLD fMRI (7,8) . In this article, we describe how to use this technique in zebra finches (Taeniopygia guttata), which are small songbirds with a bodyweight of 15-25 g extensively studied in behavioral neurosciences of birdsong. The main topic of fMRI studies on songbirds is song perception and song learning. The auditory nature of the stimuli combined with the weak BOLD sensitivity of SE (compared to GE) based fMRI sequences makes the implementation of this technique very challenging.

Evaluation of Nonradiative Clinical Imaging Techniques for the Longitudinal Assessment of Tumour Growth in Murine CT26 Colon Carcinoma

PubMed Central

Doan, Bich-Thuy; Latorre Ossa, Heldmuth; Jugé, Lauriane; Gennisson, Jean-Luc; Tanter, Mickaël; Scherman, Daniel; Chabot, Guy G.; Mignet, Nathalie

2013-01-01

Background and Objectives. To determine the most appropriate technique for tumour followup in experimental therapeutics, we compared ultrasound (US) and magnetic resonance imaging (MRI) to characterize ectopic and orthotopic colon carcinoma models. Methods. CT26 tumours were implanted subcutaneously (s.c.) in Balb/c mice for the ectopic model or into the caecum for the orthotopic model. Tumours were evaluated by histology, spectrofluorescence, MRI, and US. Results. Histology of CT26 tumour showed homogeneously dispersed cancer cells and blood vessels. The visualization of the vascular network using labelled albumin showed that CT26 tumours were highly vascularized and disorganized. MRI allowed high-resolution and accurate 3D tumour measurements and provided additional anatomical and functional information. Noninvasive US imaging allowed good delineation of tumours despite an hypoechogenic signal. Monitoring of tumour growth with US could be accomplished as early as 5 days after implantation with a shorter acquisition time (<5 min) compared to MRI. Conclusion. MRI and US afforded excellent noninvasive imaging techniques to accurately follow tumour growth of ectopic and orthotopic CT26 tumours. These two techniques can be appropriately used for tumour treatment followup, with a preference for US imaging, due to its short acquisition time and simplicity of use. PMID:23936648

Cerebellar Functional Parcellation Using Sparse Dictionary Learning Clustering.

PubMed

Wang, Changqing; Kipping, Judy; Bao, Chenglong; Ji, Hui; Qiu, Anqi

2016-01-01

The human cerebellum has recently been discovered to contribute to cognition and emotion beyond the planning and execution of movement, suggesting its functional heterogeneity. We aimed to identify the functional parcellation of the cerebellum using information from resting-state functional magnetic resonance imaging (rs-fMRI). For this, we introduced a new data-driven decomposition-based functional parcellation algorithm, called Sparse Dictionary Learning Clustering (SDLC). SDLC integrates dictionary learning, sparse representation of rs-fMRI, and k-means clustering into one optimization problem. The dictionary is comprised of an over-complete set of time course signals, with which a sparse representation of rs-fMRI signals can be constructed. Cerebellar functional regions were then identified using k-means clustering based on the sparse representation of rs-fMRI signals. We solved SDLC using a multi-block hybrid proximal alternating method that guarantees strong convergence. We evaluated the reliability of SDLC and benchmarked its classification accuracy against other clustering techniques using simulated data. We then demonstrated that SDLC can identify biologically reasonable functional regions of the cerebellum as estimated by their cerebello-cortical functional connectivity. We further provided new insights into the cerebello-cortical functional organization in children.

Measuring functional connectivity using MEG: Methodology and comparison with fcMRI

PubMed Central

Brookes, Matthew J.; Hale, Joanne R.; Zumer, Johanna M.; Stevenson, Claire M.; Francis, Susan T.; Barnes, Gareth R.; Owen, Julia P.; Morris, Peter G.; Nagarajan, Srikantan S.

2011-01-01

Functional connectivity (FC) between brain regions is thought to be central to the way in which the brain processes information. Abnormal connectivity is thought to be implicated in a number of diseases. The ability to study FC is therefore a key goal for neuroimaging. Functional connectivity (fc) MRI has become a popular tool to make connectivity measurements but the technique is limited by its indirect nature. A multimodal approach is therefore an attractive means to investigate the electrodynamic mechanisms underlying hemodynamic connectivity. In this paper, we investigate resting state FC using fcMRI and magnetoencephalography (MEG). In fcMRI, we exploit the advantages afforded by ultra high magnetic field. In MEG we apply envelope correlation and coherence techniques to source space projected MEG signals. We show that beamforming provides an excellent means to measure FC in source space using MEG data. However, care must be taken when interpreting these measurements since cross talk between voxels in source space can potentially lead to spurious connectivity and this must be taken into account in all studies of this type. We show good spatial agreement between FC measured independently using MEG and fcMRI; FC between sensorimotor cortices was observed using both modalities, with the best spatial agreement when MEG data are filtered into the β band. This finding helps to reduce the potential confounds associated with each modality alone: while it helps reduce the uncertainties in spatial patterns generated by MEG (brought about by the ill posed inverse problem), addition of electrodynamic metric confirms the neural basis of fcMRI measurements. Finally, we show that multiple MEG based FC metrics allow the potential to move beyond what is possible using fcMRI, and investigate the nature of electrodynamic connectivity. Our results extend those from previous studies and add weight to the argument that neural oscillations are intimately related to functional connectivity and the BOLD response. PMID:21352925

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

PubMed Central

Shafi, Mouhsin M.; Whitfield-Gabrieli, Susan; Chu, Catherine J.; Pascual-Leone, Alvaro; Chang, Bernard S.

2017-01-01

Resting-state functional connectivity MRI (rs-fcMRI) is a technique that identifies connectivity between different brain regions based on correlations over time in the blood-oxygenation level dependent signal. rs-fcMRI has been applied extensively to identify abnormalities in brain connectivity in different neurologic and psychiatric diseases. However, the relationship among rs-fcMRI connectivity abnormalities, brain electrophysiology and disease state is unknown, in part because the causal significance of alterations in functional connectivity in disease pathophysiology has not been established. Transcranial Magnetic Stimulation (TMS) is a technique that uses electromagnetic induction to noninvasively produce focal changes in cortical activity. When combined with electroencephalography (EEG), TMS can be used to assess the brain's response to external perturbations. Here we provide a protocol for combining rs-fcMRI, TMS and EEG to assess the physiologic significance of alterations in functional connectivity in patients with neuropsychiatric disease. We provide representative results from a previously published study in which rs-fcMRI was used to identify regions with abnormal connectivity in patients with epilepsy due to a malformation of cortical development, periventricular nodular heterotopia (PNH). Stimulation in patients with epilepsy resulted in abnormal TMS-evoked EEG activity relative to stimulation of the same sites in matched healthy control patients, with an abnormal increase in the late component of the TMS-evoked potential, consistent with cortical hyperexcitability. This abnormality was specific to regions with abnormal resting-state functional connectivity. Electrical source analysis in a subject with previously recorded seizures demonstrated that the origin of the abnormal TMS-evoked activity co-localized with the seizure-onset zone, suggesting the presence of an epileptogenic circuit. These results demonstrate how rs-fcMRI, TMS and EEG can be utilized together to identify and understand the physiological significance of abnormal brain connectivity in human diseases. PMID:27911366

Comparison of Clinical Results, Second-Look Arthroscopic Findings, and MRI Findings Between the Transportal and Outside-In Techniques for Double-Bundle Anatomic Anterior Cruciate Ligament Reconstruction: A Prospective, Randomized Controlled Trial With a Minimum 2-Year Follow-up.

PubMed

Kim, Jae Gyoon; Kang, Seung Hoon; Kim, Jun Ho; Lim, Chae Ouk; Wang, Joon Ho

2018-03-01

Although image analysis has shown that the outside-in (OI) technique is associated with different femoral tunnel geometry than the transportal (TP) technique in anatomic anterior cruciate ligament (ACL) reconstruction, it is not known whether clinical results differ between the 2 techniques. To compare clinical results, second-look arthroscopic findings, and magnetic resonance imaging (MRI) findings between the TP and OI techniques in anatomic double-bundle (DB) ACL reconstruction. Randomized controlled trial; Level of evidence, 2. From November 2010 to March 2013, 128 patients were enrolled in this study and were randomly assigned to either the TP group (64 patients) or the OI group (64 patients), and DB ACL reconstructions were performed. At the minimum 2-year follow-up (34.9 ± 10.9 months), 111 patients (86.7%) were evaluated with multiple clinical scores and stability tests (KT-2000 arthrometer, Lachman test, and pivot-shift test). Ninety-three knees were evaluated for graft continuity, graft tension, and synovialization by use of second-look arthroscopy. Seventy-eight knees were evaluated on MRI for graft continuity, femoral graft tunnel healing, and graft signal/noise quotient (SNQ). The primary outcome was KT-2000 arthrometer results. Results were compared between the TP and OI groups. No significant differences were found between the 2 groups in terms of KT-2000 arthrometer results, which was the primary outcome, and other clinical results, with the exception of the postoperative functional test of International Knee Documentation Committee (IKDC) objective score. The ratio of grade A and B on the postoperative functional test of IKDC objective score was significantly larger for the OI group (51/58) than the TP group (36/53) ( P = .005). The second-look arthroscopic findings were not significantly different between the 2 groups in either bundle ( P > .05). In addition, MRI findings did not differ significantly between the 2 groups ( P > .05). With the exception of the functional test of IKDC objective score, we found that clinical results, second-look arthroscopic findings, and MRI findings did not differ significantly between the OI and TP techniques for anatomic ACL reconstruction, although femoral tunnel geometries differed significantly between the 2 techniques.

Detecting nonlinear dynamics of functional connectivity

NASA Astrophysics Data System (ADS)

LaConte, Stephen M.; Peltier, Scott J.; Kadah, Yasser; Ngan, Shing-Chung; Deshpande, Gopikrishna; Hu, Xiaoping

2004-04-01

Functional magnetic resonance imaging (fMRI) is a technique that is sensitive to correlates of neuronal activity. The application of fMRI to measure functional connectivity of related brain regions across hemispheres (e.g. left and right motor cortices) has great potential for revealing fundamental physiological brain processes. Primarily, functional connectivity has been characterized by linear correlations in resting-state data, which may not provide a complete description of its temporal properties. In this work, we broaden the measure of functional connectivity to study not only linear correlations, but also those arising from deterministic, non-linear dynamics. Here the delta-epsilon approach is extended and applied to fMRI time series. The method of delays is used to reconstruct the joint system defined by a reference pixel and a candidate pixel. The crux of this technique relies on determining whether the candidate pixel provides additional information concerning the time evolution of the reference. As in many correlation-based connectivity studies, we fix the reference pixel. Every brain location is then used as a candidate pixel to estimate the spatial pattern of deterministic coupling with the reference. Our results indicate that measured connectivity is often emphasized in the motor cortex contra-lateral to the reference pixel, demonstrating the suitability of this approach for functional connectivity studies. In addition, discrepancies with traditional correlation analysis provide initial evidence for non-linear dynamical properties of resting-state fMRI data. Consequently, the non-linear characterization provided from our approach may provide a more complete description of the underlying physiology and brain function measured by this type of data.

Functional magnetic resonance imaging to determine hemispheric language dominance prior to carotid endarterectomy.

PubMed

Smits, M; Wieberdink, R G; Bakker, S L M; Dippel, D W J

2011-04-01

We describe a left-handed patient with transient aphasia and bilateral carotid stenosis. Computed tomography (CT) arteriography showed a 90% stenosis of the right and 30% stenosis of the left internal carotid artery. Head CT and magnetic resonance imaging (MRI) of the brain showed no recent ischemic changes. As only the symptomatic side would require surgical intervention, and because hemispheric dominance for language in left-handed patients may be either left or right sided, a preoperative assessment of hemispheric dominance was required. We used functional MRI to determine hemispheric dominance for language and hence to establish the indication for carotid endarterectomy surgery. Functional MRI demonstrated right hemispheric dominance for language and right-sided carotid endarterectomy was performed. We propose that the clinical use of functional MRI as a noninvasive imaging technique for the assessment of hemispheric language dominance may be extended to the assessment of hemispheric language dominance prior to carotid endarterectomy. Copyright © 2010 by the American Society of Neuroimaging.

Integration of fMRI, NIROT and ERP for studies of human brain function.

PubMed

Gore, John C; Horovitz, Silvina G; Cannistraci, Christopher J; Skudlarski, Pavel

2006-05-01

Different methods of assessing human brain function possess specific advantages and disadvantages compared to others, but it is believed that combining different approaches will provide greater information than can be obtained from each alone. For example, functional magnetic resonance imaging (fMRI) has good spatial resolution but poor temporal resolution, whereas the converse is true for electrophysiological recordings (event-related potentials or ERPs). In this review of recent work, we highlight a novel approach to combining these modalities in a manner designed to increase information on the origins and locations of the generators of specific ERPs and the relationship between fMRI and ERP signals. Near infrared imaging techniques have also been studied as alternatives to fMRI and can be readily integrated with simultaneous electrophysiological recordings. Each of these modalities may in principle be also used in so-called steady-state acquisitions in which the correlational structure of signals from the brain may be analyzed to provide new insights into brain function.

What can spontaneous fluctuations of the blood oxygenation-level-dependent signal tell us about psychiatric disorders?

PubMed

Fornito, Alex; Bullmore, Edward T

2010-05-01

Resting-state functional MRI (rs-fMRI) is an increasingly popular technique for studying brain dysfunction in psychiatric patients, and is widely assumed to measure intrinsic properties of functional brain organization. Here, we review rs-fMRI studies of psychiatric populations and consider how recent evidence concerning the neuronal basis, behavioural relevance, and the stability of rs-fMRI measures can inform and constrain interpretation of findings obtained using case-control designs. A range of rs-fMRI measures have been applied to different patient groups, although the findings have not always been consistent. The large-scale organization of rs-fMRI networks is robust and reproducible, and rs-fMRI measures show correlations with behavioural phenotypes relevant to psychiatry. However, evidence that such measures are also influenced by preceding psychological states and contexts, as well as individual variations in physiological arousal, may help to explain inconsistent findings in case-control comparisons. rs-fMRI measures show both stable and dynamic properties, the nature of which are only beginning to be uncovered. As such, interpreting significant differences between patients and controls on rs-fMRI measures as evidence for alterations in intrinsic functional brain organization should be done cautiously. Better understanding of the relationship between stable and transient aspects of spontaneous brain dynamics will be necessary to constrain interpretation of case-control studies and inform pathophysiological models.

International Veterinary Epilepsy Task Force recommendations for a veterinary epilepsy-specific MRI protocol.

PubMed

Rusbridge, Clare; Long, Sam; Jovanovik, Jelena; Milne, Marjorie; Berendt, Mette; Bhatti, Sofie F M; De Risio, Luisa; Farqhuar, Robyn G; Fischer, Andrea; Matiasek, Kaspar; Muñana, Karen; Patterson, Edward E; Pakozdy, Akos; Penderis, Jacques; Platt, Simon; Podell, Michael; Potschka, Heidrun; Stein, Veronika M; Tipold, Andrea; Volk, Holger A

2015-08-28

Epilepsy is one of the most common chronic neurological diseases in veterinary practice. Magnetic resonance imaging (MRI) is regarded as an important diagnostic test to reach the diagnosis of idiopathic epilepsy. However, given that the diagnosis requires the exclusion of other differentials for seizures, the parameters for MRI examination should allow the detection of subtle lesions which may not be obvious with existing techniques. In addition, there are several differentials for idiopathic epilepsy in humans, for example some focal cortical dysplasias, which may only apparent with special sequences, imaging planes and/or particular techniques used in performing the MRI scan. As a result, there is a need to standardize MRI examination in veterinary patients with techniques that reliably diagnose subtle lesions, identify post-seizure changes, and which will allow for future identification of underlying causes of seizures not yet apparent in the veterinary literature.There is a need for a standardized veterinary epilepsy-specific MRI protocol which will facilitate more detailed examination of areas susceptible to generating and perpetuating seizures, is cost efficient, simple to perform and can be adapted for both low and high field scanners. Standardisation of imaging will improve clinical communication and uniformity of case definition between research studies. A 6-7 sequence epilepsy-specific MRI protocol for veterinary patients is proposed and further advanced MR and functional imaging is reviewed.

Defining Functional Areas in Individual Human Brains using Resting Functional Connectivity MRI

PubMed Central

Cohen, Alexander L.; Fair, Damien A.; Dosenbach, Nico U.F.; Miezin, Francis M.; Dierker, Donna; Van Essen, David C.; Schlaggar, Bradley L.; Petersen, Steven E.

2009-01-01

The cerebral cortex is anatomically organized at many physical scales starting at the level of single neurons and extending up to functional systems. Current functional magnetic resonance imaging (fMRI) studies often focus at the level of areas, networks, and systems. Except in restricted domains, (e.g. topographically-organized sensory regions), it is difficult to determine area boundaries in the human brain using fMRI. The ability to delineate functional areas non-invasively would enhance the quality of many experimental analyses allowing more accurate across-subject comparisons of independently identified functional areas. Correlations in spontaneous BOLD activity, often referred to as resting state functional connectivity (rs-fcMRI), are especially promising as a way to accurately localize differences in patterns of correlated activity across large expanses of cortex. In the current report, we applied a novel set of image analysis tools to explore the utility of rs-fcMRI for defining wide-ranging functional area boundaries. We find that rs-fcMRI patterns show sharp transitions in correlation patterns and that these putative areal boundaries can be reliably detected in individual subjects as well as in group data. Additionally, combining surface-based analysis techniques with image processing algorithms allows automated mapping of putative areal boundaries across large expanses of cortex without the need for prior information about a region’s function or topography. Our approach reliably produces maps of bounded regions appropriate in size and number for putative functional areas. These findings will hopefully stimulate further methodological refinements and validations. PMID:18367410

Nitroxide-Based Macromolecular Contrast Agents with Unprecedented Transverse Relaxivity and Stability for Magnetic Resonance Imaging of Tumors

PubMed Central

2017-01-01

Metal-free magnetic resonance imaging (MRI) agents could overcome the established toxicity associated with metal-based agents in some patient populations and enable new modes of functional MRI in vivo. Herein, we report nitroxide-functionalized brush-arm star polymer organic radical contrast agents (BASP-ORCAs) that overcome the low contrast and poor in vivo stability associated with nitroxide-based MRI contrast agents. As a consequence of their unique nanoarchitectures, BASP-ORCAs possess per-nitroxide transverse relaxivities up to ∼44-fold greater than common nitroxides, exceptional stability in highly reducing environments, and low toxicity. These features combine to provide for accumulation of a sufficient concentration of BASP-ORCA in murine subcutaneous tumors up to 20 h following systemic administration such that MRI contrast on par with metal-based agents is observed. BASP-ORCAs are, to our knowledge, the first nitroxide MRI contrast agents capable of tumor imaging over long time periods using clinical high-field 1H MRI techniques. PMID:28776023

Phosphorus-31 MRI of bones using quadratic echo line-narrowing

NASA Astrophysics Data System (ADS)

Frey, Merideth; Barrett, Sean; Insogna, Karl; Vanhouten, Joshua

2012-02-01

There is a great need to probe the internal composition of bone on the sub-0.1 mm length scale, both to study normal features and to look for signs of disease. Despite the obvious importance of the mineral fraction to the biomechanical properties of skeletal tissue, few non-destructive techniques are available to evaluate changes in its chemical structure and functional microarchitecture on the interior of bones. MRI would be an excellent candidate, but bone is a particularly challenging tissue to study given the relatively low water density and wider linewidths of its solid components. Recent fundamental research in quantum computing gave rise to a new NMR pulse sequence - the quadratic echo - that can be used to narrow the broad NMR spectrum of solids. This offers a new route to do high spatial resolution, 3D ^31P MRI of bone that complements conventional MRI and x-ray based techniques to study bone physiology and structure. We have used our pulse sequence to do 3D ^31P MRI of ex vivo bones with a spatial resolution of (sub-450 μm)^3, limited only by the specifications of a conventional 4 Tesla liquid-state MRI system. We will describe our plans to push this technique towards the factor of 1000 increase in spatial resolution imposed by fundamental limits.

Mapping of cortical language function by functional magnetic resonance imaging and repetitive navigated transcranial magnetic stimulation in 40 healthy subjects.

PubMed

Sollmann, Nico; Ille, Sebastian; Boeckh-Behrens, Tobias; Ringel, Florian; Meyer, Bernhard; Krieg, Sandro M

2016-07-01

Functional magnetic resonance imaging (fMRI) is considered to be the standard method regarding non-invasive language mapping. However, repetitive navigated transcranial magnetic stimulation (rTMS) gains increasing importance with respect to that purpose. However, comparisons between both methods are sparse. We performed fMRI and rTMS language mapping of the left hemisphere in 40 healthy, right-handed subjects in combination with the tasks that are most commonly used in the neurosurgical context (fMRI: word-generation = WGEN task; rTMS: object-naming = ON task). Different rTMS error rate thresholds (ERTs) were calculated, and Cohen's kappa coefficient and the cortical parcellation system (CPS) were used for systematic comparison of the two techniques. Overall, mean kappa coefficients were low, revealing no distinct agreement. We found the highest agreement for both techniques when using the 2-out-of-3 rule (CPS region defined as language positive in terms of rTMS if at least 2 out of 3 stimulations led to a naming error). However, kappa for this threshold was only 0.24 (kappa of <0, 0.01-0.20, 0.21-0.40, 0.41-0.60, 0.61-0.80 and 0.81-0.99 indicate less than chance, slight, fair, moderate, substantial and almost perfect agreement, respectively). Because of the inherent differences in the underlying physiology of fMRI and rTMS, the different tasks used and the impossibility of verifying the results via direct cortical stimulation (DCS) in the population of healthy volunteers, one must exercise caution in drawing conclusions about the relative usefulness of each technique for language mapping. Nevertheless, this study yields valuable insights into these two mapping techniques for the most common language tasks currently used in neurosurgical practice.

Mapping brain activity in gradient-echo functional MRI using principal component analysis

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Singh, Manbir; Don, Manuel

1997-05-01

The detection of sites of brain activation in functional MRI has been a topic of immense research interest and many technique shave been proposed to this end. Recently, principal component analysis (PCA) has been applied to extract the activated regions and their time course of activation. This method is based on the assumption that the activation is orthogonal to other signal variations such as brain motion, physiological oscillations and other uncorrelated noises. A distinct advantage of this method is that it does not require any knowledge of the time course of the true stimulus paradigm. This technique is well suited to EPI image sequences where the sampling rate is high enough to capture the effects of physiological oscillations. In this work, we propose and apply tow methods that are based on PCA to conventional gradient-echo images and investigate their usefulness as tools to extract reliable information on brain activation. The first method is a conventional technique where a single image sequence with alternating on and off stages is subject to a principal component analysis. The second method is a PCA-based approach called the common spatial factor analysis technique (CSF). As the name suggests, this method relies on common spatial factors between the above fMRI image sequence and a background fMRI. We have applied these methods to identify active brain ares during visual stimulation and motor tasks. The results from these methods are compared to those obtained by using the standard cross-correlation technique. We found good agreement in the areas identified as active across all three techniques. The results suggest that PCA and CSF methods have good potential in detecting the true stimulus correlated changes in the presence of other interfering signals.

Recent neuroimaging techniques in mild traumatic brain injury.

PubMed

Belanger, Heather G; Vanderploeg, Rodney D; Curtiss, Glenn; Warden, Deborah L

2007-01-01

Mild traumatic brain injury (TBI) is characterized by acute physiological changes that result in at least some acute cognitive difficulties and typically resolve by 3 months postinjury. Because the majority of mild TBI patients have normal structural magnetic resonance imaging (MRI)/computed tomography (CT) scans, there is increasing attention directed at finding objective physiological correlates of persistent cognitive and neuropsychiatric symptoms through experimental neuroimaging techniques. The authors review studies utilizing these techniques in patients with mild TBI; these techniques may provide more sensitive assessment of structural and functional abnormalities following mild TBI. Particular promise is evident with fMRI, PET, and SPECT scanning, as demonstrated by associations between brain activation and clinical outcomes.

Application of Independent Component Analysis for the Data Mining of Simultaneous EEG-fMRI: Preliminary Experience on Sleep Onset

PubMed Central

Lee, Jong-Hwan; Oh, Sungsuk; Jolesz, Ferenc A.; Park, Hyunwook; Yoo, Seung-Schik

2010-01-01

The simultaneous acquisition of electroencephalogram (EEG) and functional MRI (fMRI) signals is potentially advantageous because of the superior resolution that is achieved in both the temporal and spatial domains, respectively. However, ballistocardiographic artifacts along with the ocular artifacts are a major obstacle for the detection of the EEG signatures of interest. Since the sources corresponding to these artifacts are independent from those producing the EEG signatures, we applied the Infomax-based independent component analysis (ICA) technique to separate the EEG signatures from the artifacts. The isolated EEG signatures were further utilized to model the canonical hemodynamic response functions (HRFs). Subsequently, the brain areas from which these EEG signatures originated were identified as locales of activation patterns from the analysis of fMRI data. Upon the identification and subsequent evaluation of brain areas generating interictal epileptic discharge (IED) spikes from an epileptic subject, the presented method was successfully applied to detect the theta- and alpha-rhythms that are sleep onset related EEG signatures along with the subsequent neural circuitries from a sleep deprived volunteer. These results suggest that the ICA technique may be useful for the preprocessing of simultaneous EEG-fMRI acquisitions, especially when a reference paradigm is unavailable. PMID:19922343

Application of independent component analysis for the data mining of simultaneous Eeg-fMRI: preliminary experience on sleep onset.

PubMed

Lee, Jong-Hwan; Oh, Sungsuk; Jolesz, Ferenc A; Park, Hyunwook; Yoo, Seung-Schik

2009-01-01

The simultaneous acquisition of electroencephalogram (EEG) and functional MRI (fMRI) signals is potentially advantageous because of the superior resolution that is achieved in both the temporal and spatial domains, respectively. However, ballistocardiographic artifacts along with ocular artifacts are a major obstacle for the detection of the EEG signatures of interest. Since the sources corresponding to these artifacts are independent from those producing the EEG signatures, we applied the Infomax-based independent component analysis (ICA) technique to separate the EEG signatures from the artifacts. The isolated EEG signatures were further utilized to model the canonical hemodynamic response functions (HRFs). Subsequently, the brain areas from which these EEG signatures originated were identified as locales of activation patterns from the analysis of fMRI data. Upon the identification and subsequent evaluation of brain areas generating interictal epileptic discharge (IED) spikes from an epileptic subject, the presented method was successfully applied to detect the theta and alpha rhythms that are sleep onset-related EEG signatures along with the subsequent neural circuitries from a sleep-deprived volunteer. These results suggest that the ICA technique may be useful for the preprocessing of simultaneous EEG-fMRI acquisitions, especially when a reference paradigm is unavailable.

MRI measurements of Blood-Brain Barrier function in dementia: A review of recent studies.

PubMed

Raja, Rajikha; Rosenberg, Gary A; Caprihan, Arvind

2018-05-15

Blood-brain barrier (BBB) separates the systemic circulation and the brain, regulating transport of most molecules to protect the brain microenvironment. Multiple structural and functional components preserve the integrity of the BBB. Several imaging modalities are available to study disruption of the BBB. However, the subtle changes in BBB leakage that occurs in vascular cognitive impairment and Alzheimer's disease have been less well studied. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is the most widely adopted non-invasive imaging technique for evaluating BBB breakdown. It is used as a significant marker for a wide variety of diseases with large permeability leaks, such as brain tumors and multiple sclerosis, to more subtle disruption in chronic vascular disease and dementia. DCE-MRI analysis of BBB includes both model-free parameters and quantitative parameters using pharmacokinetic modelling. We review MRI studies of BBB breakdown in dementia. The challenges in measuring subtle BBB changes and the state of the art techniques are initially examined. Subsequently, a systematic review comparing methodologies from recent in-vivo MRI studies is presented. Various factors related to subtle BBB permeability measurement such as DCE-MRI acquisition parameters, arterial input assessment, T 1 mapping and data analysis methods are reviewed with the focus on finding the optimal technique. Finally, the reported BBB permeability values in dementia are compared across different studies and across various brain regions. We conclude that reliable measurement of low-level BBB permeability across sites remains a difficult problem and a standardization of the methodology for both data acquisition and quantitative analysis is required. This article is part of the Special Issue entitled 'Cerebral Ischemia'. Copyright © 2017 Elsevier Ltd. All rights reserved.

Pharmacological MRI in animal models: a useful tool for 5-HT research?

PubMed

Martin, Chris; Sibson, Nicola R

2008-11-01

Pharmacological magnetic resonance imaging (phMRI) offers the potential to provide novel insights into the functioning of neurotransmitter systems and drug action in the central nervous system. To date, much of the neuropharmacological research that has applied phMRI techniques has focused on the dopaminergic system with relatively few studies into serotonergic function. In this article, we discuss the current capabilities of, and future potential for phMRI to address fundamental questions in serotonergic research using animal models. Firstly we review existing literature on the application of phMRI to the serotonergic system by exploring 3 broad research themes: (i) the functional anatomy of the serotonergic system; (ii) drug-receptor targeting and distribution; and (iii) disease models and drug development. Subsequently, we discuss the interpretation of phMRI data in terms of neuropharmacological action with a focus on issues specific to neuroimaging studies of the serotonergic system. Unlike other neuroimaging approaches such as positron emission tomography, phMRI methods do not currently offer sensitivity to markers of specific pharmacological action. However, they can provide in vivo markers of the neuropharmacological modulation of neuronal activity across the whole brain with unparalleled spatial and temporal resolution. Furthermore, due to the non-invasive nature of MRI, these markers are readily translatable to human studies. Whilst there are a number of constraints and limitations to phMRI methods that necessitate careful data interpretation, we argue that phMRI could become a valuable research tool in neuropharmacological studies of the serotonergic system.

A historical overview of magnetic resonance imaging, focusing on technological innovations.

PubMed

Ai, Tao; Morelli, John N; Hu, Xuemei; Hao, Dapeng; Goerner, Frank L; Ager, Bryan; Runge, Val M

2012-12-01

Magnetic resonance imaging (MRI) has now been used clinically for more than 30 years. Today, MRI serves as the primary diagnostic modality for many clinical problems. In this article, historical developments in the field of MRI will be discussed with a focus on technological innovations. Topics include the initial discoveries in nuclear magnetic resonance that allowed for the advent of MRI as well as the development of whole-body, high field strength, and open MRI systems. Dedicated imaging coils, basic pulse sequences, contrast-enhanced, and functional imaging techniques will also be discussed in a historical context. This article describes important technological innovations in the field of MRI, together with their clinical applicability today, providing critical insights into future developments.

Emerging MRI Methods in Translational Cardiovascular Research

PubMed Central

Vandsburger, Moriel H; Epstein, Frederick H

2011-01-01

Cardiac magnetic resonance imaging (CMR) has become a reference standard modality for imaging of left ventricular (LV) structure and function, and, using late gadolinium enhancement, for imaging myocardial infarction. Emerging CMR techniques enable a more comprehensive examination of the heart, making CMR an excellent tool for use in translational cardiovascular research. Specifically, emerging CMR methods have been developed to measure the extent of myocardial edema, changes in ventricular mechanics, changes in tissue composition as a result of fibrosis, and changes in myocardial perfusion as a function of both disease and infarct healing. New CMR techniques also enable the tracking of labeled cells, molecular imaging of biomarkers of disease, and changes in calcium flux in cardiomyocytes. In addition, MRI can quantify blood flow velocity and wall shear stress in large blood vessels. Almost all of these techniques can be applied in both pre-clinical and clinical settings, enabling both the techniques themselves and the knowledge gained using such techniques in pre-clinical research to be translated from the lab bench to the patient bedside. PMID:21452060

Diffusion Tensor Imaging and Resting-State Functional MRI-Scanning in 5- and 6-Year-Old Children: Training Protocol and Motion Assessment

PubMed Central

Theys, Catherine; Wouters, Jan; Ghesquière, Pol

2014-01-01

Advanced Magnetic Resonance Imaging (MRI) techniques such as Diffusion Tensor Imaging (DTI) and resting-state functional MRI (rfMRI) are widely used to study structural and functional neural connectivity. However, as these techniques are highly sensitive to motion artifacts and require a considerable amount of time for image acquisition, successful acquisition of these images can be challenging to complete with certain populations. This is especially true for young children. This paper describes a new approach termed the ‘submarine protocol’, designed to prepare 5- and 6-year-old children for advanced MRI scanning. The submarine protocol aims to ensure that successful scans can be acquired in a time- and resource-efficient manner, without the need for sedation. This manuscript outlines the protocol and details its outcomes, as measured through the number of children who completed the scanning procedure and analysis of the degree of motion present in the acquired images. Seventy-six children aged between 5.8 and 6.9 years were trained using the submarine protocol and subsequently underwent DTI and rfMRI scanning. After completing the submarine protocol, 75 of the 76 children (99%) completed their DTI-scan and 72 children (95%) completed the full 35-minute scan session. Results of diffusion data, acquired in 75 children, showed that the motion in 60 of the scans (80%) did not exceed the threshold for excessive motion. In the rfMRI scans, this was the case for 62 of the 71 scans (87%). When placed in the context of previous studies, the motion data of the 5- and 6-year-old children reported here were as good as, or better than those previously reported for groups of older children (i.e., 8-year-olds). Overall, this study shows that the submarine protocol can be used successfully to acquire DTI and rfMRI scans in 5 and 6-year-old children, without the need for sedation or lengthy training procedures. PMID:24718364

A hybrid method for classifying cognitive states from fMRI data.

PubMed

Parida, S; Dehuri, S; Cho, S-B; Cacha, L A; Poznanski, R R

2015-09-01

Functional magnetic resonance imaging (fMRI) makes it possible to detect brain activities in order to elucidate cognitive-states. The complex nature of fMRI data requires under-standing of the analyses applied to produce possible avenues for developing models of cognitive state classification and improving brain activity prediction. While many models of classification task of fMRI data analysis have been developed, in this paper, we present a novel hybrid technique through combining the best attributes of genetic algorithms (GAs) and ensemble decision tree technique that consistently outperforms all other methods which are being used for cognitive-state classification. Specifically, this paper illustrates the combined effort of decision-trees ensemble and GAs for feature selection through an extensive simulation study and discusses the classification performance with respect to fMRI data. We have shown that our proposed method exhibits significant reduction of the number of features with clear edge classification accuracy over ensemble of decision-trees.

[Initial diagnosis of Parkinson's disease - neuroradiological diagnosis].

PubMed

Orimo, Satoshi

2013-01-01

Brain MRI is essential for differentiating Parkinson's disease (PD) from other parkinsonian syndromes. The purpose of performing brain MRI is not to make a diagnosis of PD but is to exclude other parkinsonian syndromes. Recently, several new MRI techniques such as voxel based morphometry, relaxometry, magnetization transfer, spectroscopy, tractography, and functional MRI have been introduced in the diagnosis of PD. Neuromelanin imaging is one of the new techniques and can be useful to make an initial diagnosis of PD. MIBG myocardial scintigraphy is a sensitive imaging tool to differentiate PD from other parkinsonian syndromes and is one of the good tools to make an initial diagnosis of PD. Brain perfusion imaging is sometimes useful to make an initial diagnosis of PD, because reduced brain perfusion area can be detected before brain MRI detects morphological changes of the brain. Dopamine transporter imaging, not available in Japan, is a sensitive tool to detect very early parkinsonism and is useful to make an initial diagnosis of PD. However, it is difficult to differentiate PD from other parkinsonian syndromes.

Functional Magnetic Resonance Imaging

ERIC Educational Resources Information Center

Voos, Avery; Pelphrey, Kevin

2013-01-01

Functional magnetic resonance imaging (fMRI), with its excellent spatial resolution and ability to visualize networks of neuroanatomical structures involved in complex information processing, has become the dominant technique for the study of brain function and its development. The accessibility of in-vivo pediatric brain-imaging techniques…

Multiparametric Magnetic Resonance Imaging of the Prostate for Tumour Detection and Local Staging: Imaging in 1.5T and Histopathologic Correlation.

PubMed

Loggitsi, Dimitra; Gyftopoulos, Anastasios; Economopoulos, Nikolaos; Apostolaki, Aikaterini; Kalogeropoulos, Theodoros; Thanos, Anastasios; Alexopoulou, Efthimia; Kelekis, Nikolaos L

2017-11-01

The study sought to prospectively evaluate which technique among T2-weighted images, dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), diffusion-weighted (DW) MRI, or a combination of the 2, is best suited for prostate cancer detection and local staging. Twenty-seven consecutive patients with biopsy-proven adenocarcinoma of the prostate underwent MRI on a 1.5T scanner with a surface phased-array coil prior radical prostatectomy. Combined anatomical and functional imaging was performed with the use of T2-weighted sequences, DCE MRI, and DW MRI. We compared the imaging results with whole mount histopathology. For the multiparametric approach, significantly higher sensitivity values, that is, 53% (95% confidence interval [CI]: 41.0-64.1) were obtained as compared with each modality alone or any combination of the 3 modalities (P < .05). The specificity for this multiparametric approach, being 90.3% (95% CI: 86.3-93.3) was not significantly higher (P < .05) as compared with the values of the combination of T2+DCE MRI, DW+DCE MRI, or DCE MRI alone. Among the 3 techniques, DCE had the best performance for tumour detection in both the peripheral and the transition zone. High negative predictive value rates (>86%) were obtained for both tumour detection and local staging. The combination of T2-weighted sequences, DCE MRI, and DW MRI yields higher diagnostic performance for tumour detection and local staging than can any of these techniques alone or even any combination of them. Copyright © 2017 Canadian Association of Radiologists. Published by Elsevier Inc. All rights reserved.

Multivariate analysis of fMRI time series: classification and regression of brain responses using machine learning.

PubMed

Formisano, Elia; De Martino, Federico; Valente, Giancarlo

2008-09-01

Machine learning and pattern recognition techniques are being increasingly employed in functional magnetic resonance imaging (fMRI) data analysis. By taking into account the full spatial pattern of brain activity measured simultaneously at many locations, these methods allow detecting subtle, non-strictly localized effects that may remain invisible to the conventional analysis with univariate statistical methods. In typical fMRI applications, pattern recognition algorithms "learn" a functional relationship between brain response patterns and a perceptual, cognitive or behavioral state of a subject expressed in terms of a label, which may assume discrete (classification) or continuous (regression) values. This learned functional relationship is then used to predict the unseen labels from a new data set ("brain reading"). In this article, we describe the mathematical foundations of machine learning applications in fMRI. We focus on two methods, support vector machines and relevance vector machines, which are respectively suited for the classification and regression of fMRI patterns. Furthermore, by means of several examples and applications, we illustrate and discuss the methodological challenges of using machine learning algorithms in the context of fMRI data analysis.

Real-time functional magnetic resonance imaging neurofeedback in motor neurorehabilitation.

PubMed

Linden, David E J; Turner, Duncan L

2016-08-01

Recent developments in functional magnetic resonance imaging (fMRI) have catalyzed a new field of translational neuroscience. Using fMRI to monitor the aspects of task-related changes in neural activation or brain connectivity, investigators can offer feedback of simple or complex neural signals/patterns back to the participant on a quasireal-time basis [real-time-fMRI-based neurofeedback (rt-fMRI-NF)]. Here, we introduce some background methodology of the new developments in this field and give a perspective on how they may be used in neurorehabilitation in the future. The development of rt-fMRI-NF has been used to promote self-regulation of activity in several brain regions and networks. In addition, and unlike other noninvasive techniques, rt-fMRI-NF can access specific subcortical regions and in principle any region that can be monitored using fMRI including the cerebellum, brainstem and spinal cord. In Parkinson's disease and stroke, rt-fMRI-NF has been demonstrated to alter neural activity after the self-regulation training was completed and to modify specific behaviours. Future exploitation of rt-fMRI-NF could be used to induce neuroplasticity in brain networks that are involved in certain neurological conditions. However, currently, the use of rt-fMRI-NF in randomized, controlled clinical trials is in its infancy.

Current Trends in Intraoperative Optical Imaging for Functional Brain Mapping and Delineation of Lesions of Language Cortex

PubMed Central

Prakash, Neal; Uhleman, Falk; Sheth, Sameer A.; Bookheimer, Susan; Martin, Neil; Toga, Arthur W.

2009-01-01

Resection of a cerebral arteriovenous malformation (AVM), epileptic focus, or glioma, ideally has a prerequisite of microscopic delineation of the lesion borders in relation to the normal gray and white matter that mediate critical functions. Currently, Wada testing and functional magnetic resonance imaging (fMRI) are used for preoperative mapping of critical function, whereas electrical stimulation mapping (ESM) is used for intraoperative mapping. For lesion delineation, MRI and positron emission tomography (PET) are used preoperatively, whereas microscopy and histological sectioning are used intraoperatively. However, for lesions near eloquent cortex, these imaging techniques may lack sufficient resolution to define the relationship between the lesion and language function, and thus not accurately determine which patients will benefit from neurosurgical resection of the lesion without iatrogenic aphasia. Optical techniques such as intraoperative optical imaging of intrinsic signals (iOIS) show great promise for the precise functional mapping of cortices, as well as delineation of the borders of AVMs, epileptic foci, and gliomas. Here we first review the physiology of neuroimaging, and then progress towards the validation and justification of using intraoperative optical techniques, especially in relation to neurosurgical planning of resection AVMs, epileptic foci, and gliomas near or in eloquent cortex. We conclude with a short description of potential novel intraoperative optical techniques. PMID:18786643

Novel frontiers in ultra-structural and molecular MRI of the brain.

PubMed

Duyn, Jeff H; Koretsky, Alan P

2011-08-01

Recent developments in the MRI of the brain continue to expand its use in basic and clinical neuroscience. This review highlights some areas of recent progress. Higher magnetic field strengths and improved signal detectors have allowed improved visualization of the various properties of the brain, facilitating the anatomical definition of function-specific areas and their connections. For example, by sensitizing the MRI signal to the magnetic susceptibility of tissue, it is starting to become possible to reveal the laminar structure of the cortex and identify millimeter-scale fiber bundles. Using exogenous contrast agents, and innovative ways to manipulate contrast, it is becoming possible to highlight specific fiber tracts and cell populations. These techniques are bringing us closer to understanding the evolutionary blueprint of the brain, improving the detection and characterization of disease, and help to guide treatment. Recent MRI techniques are leading to more detailed and more specific contrast in the study of the brain.

The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments.

PubMed

Gorgolewski, Krzysztof J; Auer, Tibor; Calhoun, Vince D; Craddock, R Cameron; Das, Samir; Duff, Eugene P; Flandin, Guillaume; Ghosh, Satrajit S; Glatard, Tristan; Halchenko, Yaroslav O; Handwerker, Daniel A; Hanke, Michael; Keator, David; Li, Xiangrui; Michael, Zachary; Maumet, Camille; Nichols, B Nolan; Nichols, Thomas E; Pellman, John; Poline, Jean-Baptiste; Rokem, Ariel; Schaefer, Gunnar; Sochat, Vanessa; Triplett, William; Turner, Jessica A; Varoquaux, Gaël; Poldrack, Russell A

2016-06-21

The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this problem, we have developed the Brain Imaging Data Structure (BIDS), a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations.

The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments

PubMed Central

Gorgolewski, Krzysztof J.; Auer, Tibor; Calhoun, Vince D.; Craddock, R. Cameron; Das, Samir; Duff, Eugene P.; Flandin, Guillaume; Ghosh, Satrajit S.; Glatard, Tristan; Halchenko, Yaroslav O.; Handwerker, Daniel A.; Hanke, Michael; Keator, David; Li, Xiangrui; Michael, Zachary; Maumet, Camille; Nichols, B. Nolan; Nichols, Thomas E.; Pellman, John; Poline, Jean-Baptiste; Rokem, Ariel; Schaefer, Gunnar; Sochat, Vanessa; Triplett, William; Turner, Jessica A.; Varoquaux, Gaël; Poldrack, Russell A.

2016-01-01

The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this problem, we have developed the Brain Imaging Data Structure (BIDS), a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations. PMID:27326542

MRI-guided focused ultrasound surgery in musculoskeletal diseases: the hot topics

PubMed Central

Napoli, Alessandro; Sacconi, Beatrice; Battista, Giuseppe; Guglielmi, Giuseppe; Catalano, Carlo; Albisinni, Ugo

2016-01-01

MRI-guided focused ultrasound surgery (MRgFUS) is a minimally invasive treatment guided by the most sophisticated imaging tool available in today's clinical practice. Both the imaging and therapeutic sides of the equipment are based on non-ionizing energy. This technique is a very promising option as potential treatment for several pathologies, including musculoskeletal (MSK) disorders. Apart from clinical applications, MRgFUS technology is the result of long, heavy and cumulative efforts exploring the effects of ultrasound on biological tissues and function, the generation of focused ultrasound and treatment monitoring by MRI. The aim of this article is to give an updated overview on a “new” interventional technique and on its applications for MSK and allied sciences. PMID:26607640

State-of-the-art pancreatic MRI.

PubMed

Sandrasegaran, Kumaresan; Lin, Chen; Akisik, Fatih M; Tann, Mark

2010-07-01

The purpose of this article is to discuss the most current techniques used for pancreatic imaging, highlighting the advantages and disadvantages of state-of-the-art and emerging pulse sequences and their application to pancreatic disease. Given the technologic advances of the past decade, pancreatic MRI protocols have evolved. Most sequences can now be performed in one or a few breath-holds; 3D sequences with thin, contiguous slices offer improved spatial resolution; and better fat and motion suppression allow improved contrast resolution and image quality. The diagnostic potential of MRCP is now almost as good as ERCP, with pancreatic MRI as the main imaging technique to investigate biliopancreatic pain, chronic pancreatitis, and cystic pancreatic tumors at many institutions. In addition, functional information is provided with secretin-enhanced MRCP.

Compressed Sensing for fMRI: Feasibility Study on the Acceleration of Non-EPI fMRI at 9.4T

PubMed Central

Kim, Seong-Gi; Ye, Jong Chul

2015-01-01

Conventional functional magnetic resonance imaging (fMRI) technique known as gradient-recalled echo (GRE) echo-planar imaging (EPI) is sensitive to image distortion and degradation caused by local magnetic field inhomogeneity at high magnetic fields. Non-EPI sequences such as spoiled gradient echo and balanced steady-state free precession (bSSFP) have been proposed as an alternative high-resolution fMRI technique; however, the temporal resolution of these sequences is lower than the typically used GRE-EPI fMRI. One potential approach to improve the temporal resolution is to use compressed sensing (CS). In this study, we tested the feasibility of k-t FOCUSS—one of the high performance CS algorithms for dynamic MRI—for non-EPI fMRI at 9.4T using the model of rat somatosensory stimulation. To optimize the performance of CS reconstruction, different sampling patterns and k-t FOCUSS variations were investigated. Experimental results show that an optimized k-t FOCUSS algorithm with acceleration by a factor of 4 works well for non-EPI fMRI at high field under various statistical criteria, which confirms that a combination of CS and a non-EPI sequence may be a good solution for high-resolution fMRI at high fields. PMID:26413503

MRI-negative temporal lobe epilepsy-What do we know?

PubMed

Muhlhofer, Wolfgang; Tan, Yee-Leng; Mueller, Susanne G; Knowlton, Robert

2017-05-01

Temporal lobe epilepsy (TLE) is the most common focal epilepsy in adults. TLE has a high chance of becoming medically refractory, and as such, is frequently considered for further evaluation and surgical intervention. Up to 30% of TLE cases, however, can have normal ("nonlesional" or negative) magnetic resonance imaging (MRI) results, which complicates the presurgical workup and has been associated with worse surgical outcomes. Helped by contributions from advanced imaging techniques and electrical source localization, the number of surgeries performed on MRI-negative TLE has increased over the last decade. Thereby new epidemiologic, clinical, electrophysiologic, neuropathologic, and surgical data of MRI-negative TLE has emerged, showing characteristics that are distinct from those of lesional TLE. This review article summarizes what we know today about MRI-negative TLE, and discusses the comprehensive assessment of patients with MRI-negative TLE in a structured and systematic approach. It also includes a concise description of the most recent developments in structural and functional imaging, and highlights postprocessing imaging techniques that have been shown to add localization value in MRI-negative epilepsies. We evaluate surgical outcomes of MRI-negative TLE, identify prognostic makers of postoperative seizure freedom, and discuss strategies for optimizing the selection of surgical candidates in this group. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Does functional MRI detect activation in white matter? A review of emerging evidence, issues, and future directions

PubMed Central

Gawryluk, Jodie R.; Mazerolle, Erin L.; D'Arcy, Ryan C. N.

2014-01-01

Functional magnetic resonance imaging (fMRI) is a non-invasive technique that allows for visualization of activated brain regions. Until recently, fMRI studies have focused on gray matter. There are two main reasons white matter fMRI remains controversial: (1) the blood oxygen level dependent (BOLD) fMRI signal depends on cerebral blood flow and volume, which are lower in white matter than gray matter and (2) fMRI signal has been associated with post-synaptic potentials (mainly localized in gray matter) as opposed to action potentials (the primary type of neural activity in white matter). Despite these observations, there is no direct evidence against measuring fMRI activation in white matter and reports of fMRI activation in white matter continue to increase. The questions underlying white matter fMRI activation are important. White matter fMRI activation has the potential to greatly expand the breadth of brain connectivity research, as well as improve the assessment and diagnosis of white matter and connectivity disorders. The current review provides an overview of the motivation to investigate white matter fMRI activation, as well as the published evidence of this phenomenon. We speculate on possible neurophysiologic bases of white matter fMRI signals, and discuss potential explanations for why reports of white matter fMRI activation are relatively scarce. We end with a discussion of future basic and clinical research directions in the study of white matter fMRI. PMID:25152709

Preclinical Magnetic Resonance Imaging and Spectroscopy Studies of Memory, Aging, and Cognitive Decline

PubMed Central

Febo, Marcelo; Foster, Thomas C.

2016-01-01

Neuroimaging provides for non-invasive evaluation of brain structure and activity and has been employed to suggest possible mechanisms for cognitive aging in humans. However, these imaging procedures have limits in terms of defining cellular and molecular mechanisms. In contrast, investigations of cognitive aging in animal models have mostly utilized techniques that have offered insight on synaptic, cellular, genetic, and epigenetic mechanisms affecting memory. Studies employing magnetic resonance imaging and spectroscopy (MRI and MRS, respectively) in animal models have emerged as an integrative set of techniques bridging localized cellular/molecular phenomenon and broader in vivo neural network alterations. MRI methods are remarkably suited to longitudinal tracking of cognitive function over extended periods permitting examination of the trajectory of structural or activity related changes. Combined with molecular and electrophysiological tools to selectively drive activity within specific brain regions, recent studies have begun to unlock the meaning of fMRI signals in terms of the role of neural plasticity and types of neural activity that generate the signals. The techniques provide a unique opportunity to causally determine how memory-relevant synaptic activity is processed and how memories may be distributed or reconsolidated over time. The present review summarizes research employing animal MRI and MRS in the study of brain function, structure, and biochemistry, with a particular focus on age-related cognitive decline. PMID:27468264

Arterial Spin Labeling (ASL) fMRI: advantages, theoretical constrains, and experimental challenges in neurosciences.

PubMed

Borogovac, Ajna; Asllani, Iris

2012-01-01

Cerebral blood flow (CBF) is a well-established correlate of brain function and therefore an essential parameter for studying the brain at both normal and diseased states. Arterial spin labeling (ASL) is a noninvasive fMRI technique that uses arterial water as an endogenous tracer to measure CBF. ASL provides reliable absolute quantification of CBF with higher spatial and temporal resolution than other techniques. And yet, the routine application of ASL has been somewhat limited. In this review, we start by highlighting theoretical complexities and technical challenges of ASL fMRI for basic and clinical research. While underscoring the main advantages of ASL versus other techniques such as BOLD, we also expound on inherent challenges and confounds in ASL perfusion imaging. In closing, we expound on several exciting developments in the field that we believe will make ASL reach its full potential in neuroscience research.

Technological challenges in Magnetic Resonance Imaging: enhancing sensitivity, moving to quantitative imaging and searching for disease biomarkers

NASA Astrophysics Data System (ADS)

Retico, A.

2018-02-01

Diagnostic imaging based on the Nuclear Magnetic Resonance phenomenon has increasingly spread in the recent few decades, mainly owing to its exquisite capability in depicting a contrast between soft tissues, to its generally non-invasive nature, and to the priceless advantage of using non-ionizing radiation. Magnetic Resonance (MR)-based acquisition techniques allow gathering information on the structure (through Magnetic Resonance Imaging— MRI), the metabolic composition (through Magnetic Resonance Spectroscopy—MRS), and the functioning (through functional MRI —fMRI) of the human body. MR investigations are the methods of choice for studying the brain in vivo, including anatomy, structural wiring and functional connectivity, in healthy and pathological conditions. Alongside the efforts of the clinical research community in extending the acquisition protocols to allow the exploration of a large variety of pathologies affecting diverse body regions, some relevant technological improvements are on the way to maximize the impact of MR in medical diagnostic. The development of MR scanners operating at ultra-high magnetic field (UHF) strength (>= 7 tesla), is pushing forward the spatial resolution of MRI and the spectral resolution of MRS, and it is increasing the specificity of fMRI to grey matter signal. UHF MR systems are currently in use for research purposes only; nevertheless, UHF technological advances are positively affecting MR investigations at clinical field strengths. To overcome the current major limitation of MRI, which is mostly based on contrast between tissues rather than on absolute measurements of physical quantities, a new acquisition modality is under development, which is referred as Magnetic Resonance Fingerprinting technique. Finally, as neuroimaging data acquired worldwide are reaching the typical size of Big Data, dedicated technical solutions are required to mine large amount of information and to identify specific biomarkers of pathological conditions.

Ultra high spatial and temporal resolution breast imaging at 7T.

PubMed

van de Bank, B L; Voogt, I J; Italiaander, M; Stehouwer, B L; Boer, V O; Luijten, P R; Klomp, D W J

2013-04-01

There is a need to obtain higher specificity in the detection of breast lesions using MRI. To address this need, Dynamic Contrast-Enhanced (DCE) MRI has been combined with other structural and functional MRI techniques. Unfortunately, owing to time constraints structural images at ultra-high spatial resolution can generally not be obtained during contrast uptake, whereas the relatively low spatial resolution of functional imaging (e.g. diffusion and perfusion) limits the detection of small lesions. To be able to increase spatial as well as temporal resolution simultaneously, the sensitivity of MR detection needs to increase as well as the ability to effectively accelerate the acquisition. The required gain in signal-to-noise ratio (SNR) can be obtained at 7T, whereas acceleration can be obtained with high-density receiver coil arrays. In this case, morphological imaging can be merged with DCE-MRI, and other functional techniques can be obtained at higher spatial resolution, and with less distortion [e.g. Diffusion Weighted Imaging (DWI)]. To test the feasibility of this concept, we developed a unilateral breast coil for 7T. It comprises a volume optimized dual-channel transmit coil combined with a 30-channel receive array coil. The high density of small coil elements enabled efficient acceleration in any direction to acquire ultra high spatial resolution MRI of close to 0.6 mm isotropic detail within a temporal resolution of 69 s, high spatial resolution MRI of 1.5 mm isotropic within an ultra high temporal resolution of 6.7 s and low distortion DWI at 7T, all validated in phantoms, healthy volunteers and a patient with a lesion in the right breast classified as Breast Imaging Reporting and Data System (BI-RADS) IV. Copyright © 2012 John Wiley & Sons, Ltd.

Correction for the T1 Effect Incorporating Flip Angle Estimated by Kalman Filter in Cardiac-Gated Functional MRI

PubMed Central

Shin, Jaemin; Ahn, Sinyeob; Hu, Xiaoping

2015-01-01

Purpose To develop an improved and generalized technique for correcting T1-related signal fluctuations (T1 effect) in cardiac-gated functional magnetie resonance imaging (fMRI) data with flip angle estimation. Theory and Methods Spatial maps of flip angle and T1 are jointly estimated from cardiac-gated time series using a Kalman filter. These maps are subsequently used for removing the T1 effect in the presence of B1 inhomogeneity. The new technique was compared with a prior technique that uses T1 only while assuming a homogeneous flip angle of 90°. The robustness of the new technique is demonstrated with simulated and experimental data. Results Simulation results revealed that the new method led to increased temporal signal-to-noise ratio across a large range of flip angles, T1s, and stimulus onset asynchrony means compared to the T1 only approach. With the experimental data, the new approach resulted in higher average gray matter temporal signal-to-noise ratio of seven subjects (84 vs. 48). The new approach also led to a higher statistical score of activation in the lateral geniculate nucleus (P < 0.002). Conclusion The new technique is able to remove the T1 effect robustly and is a promising tool for improving the ability to map activation in fMRI, especially in subcortical regions. PMID:23390029

Superparamagnetic iron oxide nanoparticle-labeled cells as an effective vehicle for tracking the GFP gene marker using magnetic resonance imaging

PubMed Central

Zhang, Z; Mascheri, N; Dharmakumar, R; Fan, Z; Paunesku, T; Woloschak, G; Li, D

2010-01-01

Background Detection of a gene using magnetic resonance imaging (MRI) is hindered by the magnetic resonance (MR) targeting gene technique. Therefore it may be advantageous to image gene-expressing cells labeled with superparamagnetic iron oxide (SPIO) nanoparticles by MRI. Methods The GFP-R3230Ac (GFP) cell line was incubated for 24 h using SPIO nanoparticles at a concentration of 20 μg Fe/mL. Cell samples were prepared for iron content analysis and cell function evaluation. The labeled cells were imaged using fluorescent microscopy and MRI. Results SPIO was used to label GFP cells effectively, with no effects on cell function and GFP expression. Iron-loaded GFP cells were successfully imaged with both fluorescent microscopy and T2*-weighted MRI. Prussian blue staining showed intracellular iron accumulation in the cells. All cells were labeled (100% labeling efficiency). The average iron content per cell was 4.75±0.11 pg Fe/cell (P<0.05 versus control). Discussion This study demonstrates that the GFP expression of cells is not altered by the SPIO labeling process. SPIO-labeled GFP cells can be visualized by MRI; therefore, GFP, a gene marker, was tracked indirectly with the SPIO-loaded cells using MRI. The technique holds promise for monitoring the temporal and spatial migration of cells with a gene marker and enhancing the understanding of cell- and gene-based therapeutic strategies. PMID:18956269

Fusing EEG and fMRI based on a bottom-up model: inferring activation and effective connectivity in neural masses

PubMed Central

Riera, J; Aubert, E; Iwata, K; Kawashima, R; Wan, X; Ozaki, T

2005-01-01

The elucidation of the complex machinery used by the human brain to segregate and integrate information while performing high cognitive functions is a subject of imminent future consequences. The most significant contributions to date in this field, known as cognitive neuroscience, have been achieved by using innovative neuroimaging techniques, such as electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI), which measure variations in both the time and the space of some interpretable physical magnitudes. Extraordinary maps of cerebral activation involving function-restricted brain areas, as well as graphs of the functional connectivity between them, have been obtained from EEG and fMRI data by solving some spatio-temporal inverse problems, which constitutes a top-down approach. However, in many cases, a natural bridge between these maps/graphs and the causal physiological processes is lacking, leading to some misunderstandings in their interpretation. Recent advances in the comprehension of the underlying physiological mechanisms associated with different cerebral scales have provided researchers with an excellent scenario to develop sophisticated biophysical models that permit an integration of these neuroimage modalities, which must share a common aetiology. This paper proposes a bottom-up approach, involving physiological parameters in a specific mesoscopic dynamic equations system. Further observation equations encapsulating the relationship between the mesostates and the EEG/fMRI data are obtained on the basis of the physical foundations of these techniques. A methodology for the estimation of parameters from fused EEG/fMRI data is also presented. In this context, the concepts of activation and effective connectivity are carefully revised. This new approach permits us to examine and discuss some future prospects for the integration of multimodal neuroimages. PMID:16087446

Biophysical and physiological origins of blood oxygenation level-dependent fMRI signals.

PubMed

Kim, Seong-Gi; Ogawa, Seiji

2012-07-01

After its discovery in 1990, blood oxygenation level-dependent (BOLD) contrast in functional magnetic resonance imaging (fMRI) has been widely used to map brain activation in humans and animals. Since fMRI relies on signal changes induced by neural activity, its signal source can be complex and is also dependent on imaging parameters and techniques. In this review, we identify and describe the origins of BOLD fMRI signals, including the topics of (1) effects of spin density, volume fraction, inflow, perfusion, and susceptibility as potential contributors to BOLD fMRI, (2) intravascular and extravascular contributions to conventional gradient-echo and spin-echo BOLD fMRI, (3) spatial specificity of hemodynamic-based fMRI related to vascular architecture and intrinsic hemodynamic responses, (4) BOLD signal contributions from functional changes in cerebral blood flow (CBF), cerebral blood volume (CBV), and cerebral metabolic rate of O(2) utilization (CMRO(2)), (5) dynamic responses of BOLD, CBF, CMRO(2), and arterial and venous CBV, (6) potential sources of initial BOLD dips, poststimulus BOLD undershoots, and prolonged negative BOLD fMRI signals, (7) dependence of stimulus-evoked BOLD signals on baseline physiology, and (8) basis of resting-state BOLD fluctuations. These discussions are highly relevant to interpreting BOLD fMRI signals as physiological means.

Biophysical and physiological origins of blood oxygenation level-dependent fMRI signals

PubMed Central

Kim, Seong-Gi; Ogawa, Seiji

2012-01-01

After its discovery in 1990, blood oxygenation level-dependent (BOLD) contrast in functional magnetic resonance imaging (fMRI) has been widely used to map brain activation in humans and animals. Since fMRI relies on signal changes induced by neural activity, its signal source can be complex and is also dependent on imaging parameters and techniques. In this review, we identify and describe the origins of BOLD fMRI signals, including the topics of (1) effects of spin density, volume fraction, inflow, perfusion, and susceptibility as potential contributors to BOLD fMRI, (2) intravascular and extravascular contributions to conventional gradient-echo and spin-echo BOLD fMRI, (3) spatial specificity of hemodynamic-based fMRI related to vascular architecture and intrinsic hemodynamic responses, (4) BOLD signal contributions from functional changes in cerebral blood flow (CBF), cerebral blood volume (CBV), and cerebral metabolic rate of O2 utilization (CMRO2), (5) dynamic responses of BOLD, CBF, CMRO2, and arterial and venous CBV, (6) potential sources of initial BOLD dips, poststimulus BOLD undershoots, and prolonged negative BOLD fMRI signals, (7) dependence of stimulus-evoked BOLD signals on baseline physiology, and (8) basis of resting-state BOLD fluctuations. These discussions are highly relevant to interpreting BOLD fMRI signals as physiological means. PMID:22395207

Interactive MR image guidance for neurosurgical and minimally invasive procedures

NASA Astrophysics Data System (ADS)

Wong, Terence Z.; Schwartz, Richard B.; Pergolizzi, Richard S., Jr.; Black, Peter M.; Kacher, Daniel F.; Morrison, Paul R.; Jolesz, Ferenc A.

1999-05-01

Advantages of MR imaging for guidance of minimally invasive procedures include exceptional soft tissue contrast, intrinsic multiplanar imaging capability, and absence of exposure to ionizing radiation. Specialized imaging sequences are available and under development which can further enhance diagnosis and therapy. Flow-sensitive imaging techniques can be used to identify vascular structures. Temperature-sensitive imaging is possible which can provide interactive feedback prior to, during, and following the delivery of thermal energy. Functional MR imaging and dynamic contrast-enhanced MRI sequences can provide additional information for guidance in neurosurgical applications. Functional MR allows mapping of eloquent areas in the brain, so that these areas may be avoided during therapy. Dynamic contrast enhancement techniques can be useful for distinguishing active tumor from tumor necrosis caused by previous radiation therapy. An open-configuration 0.5T MRI system (GE Signa SP) developed at Brigham and Women's Hospital in collaboration with General Electric Medical Systems is described. Interactive navigation systems have been integrated into the MRI system. The imaging system is sited in an operating room environment, and used for image guided neurosurgical procedures (biopsies and tumor excision), as well as minimally invasive thermal therapies. Examples of MR imaging guidance, navigational techniques, and clinical applications are presented.

Intensity-Curvature Measurement Approaches for the Diagnosis of Magnetic Resonance Imaging Brain Tumors.

PubMed

Ciulla, Carlo; Veljanovski, Dimitar; Rechkoska Shikoska, Ustijana; Risteski, Filip A

2015-11-01

This research presents signal-image post-processing techniques called Intensity-Curvature Measurement Approaches with application to the diagnosis of human brain tumors detected through Magnetic Resonance Imaging (MRI). Post-processing of the MRI of the human brain encompasses the following model functions: (i) bivariate cubic polynomial, (ii) bivariate cubic Lagrange polynomial, (iii) monovariate sinc, and (iv) bivariate linear. The following Intensity-Curvature Measurement Approaches were used: (i) classic-curvature, (ii) signal resilient to interpolation, (iii) intensity-curvature measure and (iv) intensity-curvature functional. The results revealed that the classic-curvature, the signal resilient to interpolation and the intensity-curvature functional are able to add additional information useful to the diagnosis carried out with MRI. The contribution to the MRI diagnosis of our study are: (i) the enhanced gray level scale of the tumor mass and the well-behaved representation of the tumor provided through the signal resilient to interpolation, and (ii) the visually perceptible third dimension perpendicular to the image plane provided through the classic-curvature and the intensity-curvature functional.

Intensity-Curvature Measurement Approaches for the Diagnosis of Magnetic Resonance Imaging Brain Tumors

PubMed Central

Ciulla, Carlo; Veljanovski, Dimitar; Rechkoska Shikoska, Ustijana; Risteski, Filip A.

2015-01-01

This research presents signal-image post-processing techniques called Intensity-Curvature Measurement Approaches with application to the diagnosis of human brain tumors detected through Magnetic Resonance Imaging (MRI). Post-processing of the MRI of the human brain encompasses the following model functions: (i) bivariate cubic polynomial, (ii) bivariate cubic Lagrange polynomial, (iii) monovariate sinc, and (iv) bivariate linear. The following Intensity-Curvature Measurement Approaches were used: (i) classic-curvature, (ii) signal resilient to interpolation, (iii) intensity-curvature measure and (iv) intensity-curvature functional. The results revealed that the classic-curvature, the signal resilient to interpolation and the intensity-curvature functional are able to add additional information useful to the diagnosis carried out with MRI. The contribution to the MRI diagnosis of our study are: (i) the enhanced gray level scale of the tumor mass and the well-behaved representation of the tumor provided through the signal resilient to interpolation, and (ii) the visually perceptible third dimension perpendicular to the image plane provided through the classic-curvature and the intensity-curvature functional. PMID:26644943

Non-Inferential Multi-Subject Study of Functional Connectivity during Visual Stimulation.

PubMed

Esposito, F; Cirillo, M; Aragri, A; Caranci, F; Cirillo, L; Di Salle, F; Cirillo, S

2007-01-31

Independent component analysis (ICA) is a powerful technique for the multivariate, non-inferential, data-driven analysis of functional magnetic resonance imaging (fMRI) data-sets. The non-inferential nature of ICA makes this a suitable technique for the study of complex mental states whose temporal evolution would be difficult to describe analytically in terms of classical statistical regressors. Taking advantage of this feature, ICA can extract a number of functional connectivity patterns regardless of the task executed by the subject. The technique is so powerful that functional connectivity patterns can be derived even when the subject is just resting in the scanner, opening the opportunity for functional investigation of the human mind at its basal "default" state, which has been proposed to be altered in several brain disorders. However, one major drawback of ICA consists in the difficulty of managing its results, which are not represented by a single functional image as in inferential studies. This produces the need for a classification of ICA results and exacerbates the difficulty of obtaining group "averaged" functional connectivity patterns, while preserving the interpretation of individual differences. Addressing the subject-level variability in the very same framework of "grouping" appears to be a favourable approach towards the clinical evaluation and application of ICA-based methodologies. Here we present a novel strategy for group-level ICA analyses, namely the self-organizing group-level ICA (sog-ICA), which is used on visual activation fMRI data from a block-design experiment repeated on six subjects. We propose the sog-ICA as a multi-subject analysis tool for grouping ICA data while assessing the similarity and variability of the fMRI results of individual subject decompositions.

The potential of real-time fMRI neurofeedback for stroke rehabilitation: A systematic review.

PubMed

Wang, Tianlu; Mantini, Dante; Gillebert, Celine R

2017-09-18

Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback aids the modulation of neural functions by training self-regulation of brain activity through operant conditioning. This technique has been applied to treat several neurodevelopmental and neuropsychiatric disorders, but its effectiveness for stroke rehabilitation has not been examined yet. Here, we systematically review the effectiveness of rt-fMRI neurofeedback training in modulating motor and cognitive processes that are often impaired after stroke. Based on predefined search criteria, we selected and examined 33 rt-fMRI neurofeedback studies, including 651 healthy individuals and 15 stroke patients in total. The results of our systematic review suggest that rt-fMRI neurofeedback training can lead to a learned modulation of brain signals, with associated changes at both the neural and the behavioural level. However, more research is needed to establish how its use can be optimized in the context of stroke rehabilitation. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Improved application of independent component analysis to functional magnetic resonance imaging study via linear projection techniques.

PubMed

Long, Zhiying; Chen, Kewei; Wu, Xia; Reiman, Eric; Peng, Danling; Yao, Li

2009-02-01

Spatial Independent component analysis (sICA) has been widely used to analyze functional magnetic resonance imaging (fMRI) data. The well accepted implicit assumption is the spatially statistical independency of intrinsic sources identified by sICA, making the sICA applications difficult for data in which there exist interdependent sources and confounding factors. This interdependency can arise, for instance, from fMRI studies investigating two tasks in a single session. In this study, we introduced a linear projection approach and considered its utilization as a tool to separate task-related components from two-task fMRI data. The robustness and feasibility of the method are substantiated through simulation on computer data and fMRI real rest data. Both simulated and real two-task fMRI experiments demonstrated that sICA in combination with the projection method succeeded in separating spatially dependent components and had better detection power than pure model-based method when estimating activation induced by each task as well as both tasks.

Discriminant analysis of resting-state functional connectivity patterns on the Grassmann manifold

NASA Astrophysics Data System (ADS)

Fan, Yong; Liu, Yong; Jiang, Tianzi; Liu, Zhening; Hao, Yihui; Liu, Haihong

2010-03-01

The functional networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive functions and neurological diseases. In this paper, we propose a novel algorithm for discriminant analysis of functional networks encoded by spatial independent components. The functional networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of temporal signals of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based subspace distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional networks that are informative for schizophrenia diagnosis.

Mild cognitive impairment and fMRI studies of brain functional connectivity: the state of the art

PubMed Central

Farràs-Permanyer, Laia; Guàrdia-Olmos, Joan; Peró-Cebollero, Maribel

2015-01-01

In the last 15 years, many articles have studied brain connectivity in Mild Cognitive Impairment patients with fMRI techniques, seemingly using different connectivity statistical models in each investigation to identify complex connectivity structures so as to recognize typical behavior in this type of patient. This diversity in statistical approaches may cause problems in results comparison. This paper seeks to describe how researchers approached the study of brain connectivity in MCI patients using fMRI techniques from 2002 to 2014. The focus is on the statistical analysis proposed by each research group in reference to the limitations and possibilities of those techniques to identify some recommendations to improve the study of functional connectivity. The included articles came from a search of Web of Science and PsycINFO using the following keywords: f MRI, MCI, and functional connectivity. Eighty-one papers were found, but two of them were discarded because of the lack of statistical analysis. Accordingly, 79 articles were included in this review. We summarized some parts of the articles, including the goal of every investigation, the cognitive paradigm and methods used, brain regions involved, use of ROI analysis and statistical analysis, emphasizing on the connectivity estimation model used in each investigation. The present analysis allowed us to confirm the remarkable variability of the statistical analysis methods found. Additionally, the study of brain connectivity in this type of population is not providing, at the moment, any significant information or results related to clinical aspects relevant for prediction and treatment. We propose to follow guidelines for publishing fMRI data that would be a good solution to the problem of study replication. The latter aspect could be important for future publications because a higher homogeneity would benefit the comparison between publications and the generalization of results. PMID:26300802

Imaging brain development: the adolescent brain.

PubMed

Blakemore, Sarah-Jayne

2012-06-01

The past 15 years have seen a rapid expansion in the number of studies using neuroimaging techniques to investigate maturational changes in the human brain. In this paper, I review MRI studies on structural changes in the developing brain, and fMRI studies on functional changes in the social brain during adolescence. Both MRI and fMRI studies point to adolescence as a period of continued neural development. In the final section, I discuss a number of areas of research that are just beginning and may be the subject of developmental neuroimaging in the next twenty years. Future studies might focus on complex questions including the development of functional connectivity; how gender and puberty influence adolescent brain development; the effects of genes, environment and culture on the adolescent brain; development of the atypical adolescent brain; and implications for policy of the study of the adolescent brain. Copyright © 2011 Elsevier Inc. All rights reserved.

Resting-State Functional Connectivity in Autism Spectrum Disorders: A Review

PubMed Central

Hull, Jocelyn V.; Jacokes, Zachary J.; Torgerson, Carinna M.; Irimia, Andrei; Van Horn, John Darrell

2017-01-01

Ongoing debate exists within the resting-state functional MRI (fMRI) literature over how intrinsic connectivity is altered in the autistic brain, with reports of general over-connectivity, under-connectivity, and/or a combination of both. Classifying autism using brain connectivity is complicated by the heterogeneous nature of the condition, allowing for the possibility of widely variable connectivity patterns among individuals with the disorder. Further differences in reported results may be attributable to the age and sex of participants included, designs of the resting-state scan, and to the analysis technique used to evaluate the data. This review systematically examines the resting-state fMRI autism literature to date and compares studies in an attempt to draw overall conclusions that are presently challenging. We also propose future direction for rs-fMRI use to categorize individuals with autism spectrum disorder, serve as a possible diagnostic tool, and best utilize data-sharing initiatives. PMID:28101064

[Research progress of functional magnetic resonance imaging in mechanism studies of tinnitus].

PubMed

Ji, B B; Li, M; Zhang, J N

2018-02-07

Tinnitus is a subjective symptom of phantom sound in the ear or brain without sound or electrical stimulation in the environment. The mechanism of tinnitus is complicated and mostly unclear. Recent studies suggested that the abnormal peripheral auditory input lead to neuroplasticity changes in central nervous system followed by tinnitus. More research concerned on the tinnitus central mechanism. A rapid development of functional magnetic resonance imaging (fMRI) technique made it more widely used in tinnitus central mechanism research. fMRI brought new findings but also presented some shortages in technology and cognition in tinnitus study. This article summarized the outcomes of fMRI research on tinnitus in recent years, exploring its existing problems and application prospects.

Translating state-of-the-art spinal cord MRI techniques to clinical use: A systematic review of clinical studies utilizing DTI, MT, MWF, MRS, and fMRI

PubMed Central

Martin, Allan R.; Aleksanderek, Izabela; Cohen-Adad, Julien; Tarmohamed, Zenovia; Tetreault, Lindsay; Smith, Nathaniel; Cadotte, David W.; Crawley, Adrian; Ginsberg, Howard; Mikulis, David J.; Fehlings, Michael G.

2015-01-01

Background 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. Methods A systematic review of the English literature was conducted using MEDLINE, MEDLINE-in-Progress, Embase, and Cochrane databases to identify all human studies that investigated utility, in terms of diagnosis, correlation with disability, and prediction of outcomes, of these promising techniques in pathologies affecting the spinal cord. Data regarding study design, subject characteristics, MRI methods, clinical measures of impairment, and analysis techniques were extracted and tabulated to identify trends and commonalities. The studies were assessed for risk of bias, and the overall quality of evidence was assessed for each specific finding using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework. Results A total of 6597 unique citations were identified in the database search, and after full-text review of 274 articles, a total of 104 relevant studies were identified for final inclusion (97% from the initial database search). Among these, 69 studies utilized DTI and 25 used MT, with both techniques showing an increased number of publications in recent years. The review also identified 1 MWF study, 11 MRS studies, and 8 fMRI studies. Most of the studies were exploratory in nature, lacking a priori hypotheses and showing a high (72%) or moderately high (20%) risk of bias, due to issues with study design, acquisition techniques, and analysis methods. The acquisitions for each technique varied widely across studies, rendering direct comparisons of metrics invalid. The DTI metric fractional anisotropy (FA) had the strongest evidence of utility, with moderate quality evidence for its use as a biomarker showing correlation with disability in several clinical pathologies, and a low level of evidence that it identifies tissue injury (in terms of group differences) compared with healthy controls. However, insufficient evidence exists to determine its utility as a sensitive and specific diagnostic test or as a tool to predict clinical outcomes. Very low quality evidence suggests that other metrics also show group differences compared with controls, including DTI metrics mean diffusivity (MD) and radial diffusivity (RD), the diffusional kurtosis imaging (DKI) metric mean kurtosis (MK), MT metrics MT ratio (MTR) and MT cerebrospinal fluid ratio (MTCSF), and the MRS metric of N-acetylaspartate (NAA) concentration, although these results were somewhat inconsistent. Conclusions 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. PMID:26862478

Thoracic magnetic resonance imaging: pulmonary thromboembolism.

PubMed

Fink, Christian; Henzler, Thomas; Shirinova, Aysel; Apfaltrer, Paul; Wasser, Klaus

2013-05-01

Ongoing technical developments have substantially improved the potential of magnetic resonance imaging (MRI) in the assessment of the pulmonary circulation. These developments includes improved magnet and hardware design, new k-space sampling techniques (ie, parallel imaging), and alternative contrast materials. With these techniques, not only can pulmonary vessels be visualized by MR angiography with high spatial resolution but also the perfusion of the lungs and its changes in relation to pulmonary thromboembolism (PE) can be assessed. Considering venous thromboembolism as a systemic disease, MR venography might be added for the diagnosis of underlying deep venous thrombosis. A unique advantage of MRI over other imaging tests is its potential to evaluate changes in cardiac function as a result of obstruction of the pulmonary circulation, which may have a significant impact on patient monitoring and treatment. Finally, MRI does not involve radiation, which is advantageous, especially in young patients. Over the years, a number of studies have shown promising results not only for MR angiography but also for MRI of lung perfusion and for MR venography. This review article summarizes and discusses the current evidence on pulmonary MRI for patients with suspected PE.

Magnetic resonance imaging based clinical research in Alzheimer's disease.

PubMed

Fayed, Nicolás; Modrego, Pedro J; Salinas, Gulillermo Rojas; Gazulla, José

2012-01-01

Alzheimer's disease (AD) is the most common cause of dementia in elderly people in western countries. However important goals are unmet in the issue of early diagnosis and the development of new drugs for treatment. Magnetic resonance imaging (MRI) and volumetry of the medial temporal lobe structures are useful tools for diagnosis. Positron emission tomography is one of the most sensitive tests for making an early diagnosis of AD but the cost and limited availability are important caveats for its utilization. The importance of magnetic resonance techniques has increased gradually to the extent that most clinical works based on AD use these techniques as the main aid to diagnosis. However, the accuracy of structural MRI as biomarker of early AD generally reaches an accuracy of 80%, so additional biomarkers should be used to improve predictions. Other structural MRI (diffusion weighted, diffusion-tensor MRI) and functional MRI have also added interesting contribution to the understanding of the pathophysiology of AD. Magnetic resonance spectroscopy has proven useful to monitor progression and response to treatment in AD, as well as a biomarker of early AD in mild cognitive impairment.

Regional Homogeneity

PubMed Central

Jiang, Lili; Zuo, Xi-Nian

2015-01-01

Much effort has been made to understand the organizational principles of human brain function using functional magnetic resonance imaging (fMRI) methods, among which resting-state fMRI (rfMRI) is an increasingly recognized technique for measuring the intrinsic dynamics of the human brain. Functional connectivity (FC) with rfMRI is the most widely used method to describe remote or long-distance relationships in studies of cerebral cortex parcellation, interindividual variability, and brain disorders. In contrast, local or short-distance functional interactions, especially at a scale of millimeters, have rarely been investigated or systematically reviewed like remote FC, although some local FC algorithms have been developed and applied to the discovery of brain-based changes under neuropsychiatric conditions. To fill this gap between remote and local FC studies, this review will (1) briefly survey the history of studies on organizational principles of human brain function; (2) propose local functional homogeneity as a network centrality to characterize multimodal local features of the brain connectome; (3) render a neurobiological perspective on local functional homogeneity by linking its temporal, spatial, and individual variability to information processing, anatomical morphology, and brain development; and (4) discuss its role in performing connectome-wide association studies and identify relevant challenges, and recommend its use in future brain connectomics studies. PMID:26170004

Imaging of respiratory muscles in neuromuscular disease: A review.

PubMed

Harlaar, L; Ciet, P; van der Ploeg, A T; Brusse, E; van der Beek, N A M E; Wielopolski, P A; de Bruijne, M; Tiddens, H A W M; van Doorn, P A

2018-03-01

Respiratory muscle weakness frequently occurs in patients with neuromuscular disease. Measuring respiratory function with standard pulmonary function tests provides information about the contribution of all respiratory muscles, the lungs and airways. Imaging potentially enables the study of different respiratory muscles, including the diaphragm, separately. In this review, we provide an overview of imaging techniques used to study respiratory muscles in neuromuscular disease. We identified 26 studies which included a total of 573 patients with neuromuscular disease. Imaging of respiratory muscles was divided into static and dynamic techniques. Static techniques comprise chest radiography, B-mode (brightness mode) ultrasound, CT and MRI, and are used to assess the position and thickness of the diaphragm and the other respiratory muscles. Dynamic techniques include fluoroscopy, M-mode (motion mode) ultrasound and MRI, used to assess diaphragm motion in one or more directions. We discuss how these imaging techniques relate with spirometric values and whether these can be used to study the contribution of the different respiratory muscles in patients with neuromuscular disease. Copyright © 2017. Published by Elsevier B.V.

Clinical Resting-state fMRI in the Preoperative Setting

PubMed Central

Lee, Megan H.; Miller-Thomas, Michelle M.; Benzinger, Tammie L.; Marcus, Daniel S.; Hacker, Carl D.; Leuthardt, Eric C.; Shimony, Joshua S.

2017-01-01

The purpose of this manuscript is to provide an introduction to resting-state functional magnetic resonance imaging (RS-fMRI) and to review the current application of this new and powerful technique in the preoperative setting using our institute’s extensive experience. RS-fMRI has provided important insights into brain physiology and is an increasingly important tool in the clinical setting. As opposed to task-based functional MRI wherein the subject performs a task while being scanned, RS-fMRI evaluates low-frequency fluctuations in the blood oxygen level dependent (BOLD) signal while the subject is at rest. Multiple resting state networks (RSNs) have been identified, including the somatosensory, language, and visual networks, which are of primary importance for presurgical planning. Over the past 4 years, we have performed over 300 RS-fMRI examinations in the clinical setting and these have been used to localize eloquent somatosensory and language cortices before brain tumor resection. RS-fMRI is particularly useful in this setting for patients who are unable to cooperate with the task-based paradigm, such as young children or those who are sedated, paretic, or aphasic. Although RS-fMRI is still investigational, our experience indicates that this method is ready for clinical application in the presurgical setting. PMID:26848556

Towards neural correlates of auditory stimulus processing: A simultaneous auditory evoked potentials and functional magnetic resonance study using an odd-ball paradigm

PubMed Central

Milner, Rafał; Rusiniak, Mateusz; Lewandowska, Monika; Wolak, Tomasz; Ganc, Małgorzata; Piątkowska-Janko, Ewa; Bogorodzki, Piotr; Skarżyński, Henryk

2014-01-01

Background The neural underpinnings of auditory information processing have often been investigated using the odd-ball paradigm, in which infrequent sounds (deviants) are presented within a regular train of frequent stimuli (standards). Traditionally, this paradigm has been applied using either high temporal resolution (EEG) or high spatial resolution (fMRI, PET). However, used separately, these techniques cannot provide information on both the location and time course of particular neural processes. The goal of this study was to investigate the neural correlates of auditory processes with a fine spatio-temporal resolution. A simultaneous auditory evoked potentials (AEP) and functional magnetic resonance imaging (fMRI) technique (AEP-fMRI), together with an odd-ball paradigm, were used. Material/Methods Six healthy volunteers, aged 20–35 years, participated in an odd-ball simultaneous AEP-fMRI experiment. AEP in response to acoustic stimuli were used to model bioelectric intracerebral generators, and electrophysiological results were integrated with fMRI data. Results fMRI activation evoked by standard stimuli was found to occur mainly in the primary auditory cortex. Activity in these regions overlapped with intracerebral bioelectric sources (dipoles) of the N1 component. Dipoles of the N1/P2 complex in response to standard stimuli were also found in the auditory pathway between the thalamus and the auditory cortex. Deviant stimuli induced fMRI activity in the anterior cingulate gyrus, insula, and parietal lobes. Conclusions The present study showed that neural processes evoked by standard stimuli occur predominantly in subcortical and cortical structures of the auditory pathway. Deviants activate areas non-specific for auditory information processing. PMID:24413019

Changes of Visual Pathway and Brain Connectivity in Glaucoma: A Systematic Review

PubMed Central

Nuzzi, Raffaele; Dallorto, Laura; Rolle, Teresa

2018-01-01

Background: Glaucoma is a leading cause of irreversible blindness worldwide. The increasing interest in the involvement of the cortical visual pathway in glaucomatous patients is due to the implications in recent therapies, such as neuroprotection and neuroregeneration. Objective: In this review, we outline the current understanding of brain structural, functional, and metabolic changes detected with the modern techniques of neuroimaging in glaucomatous subjects. Methods: We screened MEDLINE, EMBASE, CINAHL, CENTRAL, LILACS, Trip Database, and NICE for original contributions published until 31 October 2017. Studies with at least six patients affected by any type of glaucoma were considered. We included studies using the following neuroimaging techniques: functional Magnetic Resonance Imaging (fMRI), resting-state fMRI (rs-fMRI), magnetic resonance spectroscopy (MRS), voxel- based Morphometry (VBM), surface-based Morphometry (SBM), diffusion tensor MRI (DTI). Results: Over a total of 1,901 studies, 56 case series with a total of 2,381 patients were included. Evidence of neurodegenerative process in glaucomatous patients was found both within and beyond the visual system. Structural alterations in visual cortex (mainly reduced cortex thickness and volume) have been demonstrated with SBM and VBM; these changes were not limited to primary visual cortex but also involved association visual areas. Other brain regions, associated with visual function, demonstrated a certain grade of increased or decreased gray matter volume. Functional and metabolic abnormalities resulted within primary visual cortex in all studies with fMRI and MRS. Studies with rs-fMRI found disrupted connectivity between the primary and higher visual cortex and between visual cortex and associative visual areas in the task-free state of glaucomatous patients. Conclusions: This review contributes to the better understanding of brain abnormalities in glaucoma. It may stimulate further speculation about brain plasticity at a later age and therapeutic strategies, such as the prevention of cortical degeneration in patients with glaucoma. Structural, functional, and metabolic neuroimaging methods provided evidence of changes throughout the visual pathway in glaucomatous patients. Other brain areas, not directly involved in the processing of visual information, also showed alterations. PMID:29896087

DOE Office of Scientific and Technical Information (OSTI.GOV)

Minati, Ludovico

This paper is meant to provide a brief overview of the techniques currently used to image the brain and to study non-invasively its anatomy and function. After a historical summary in the first section, general aspects are outlined in the second section. The subsequent six sections survey, in order, computed tomography (CT), morphological magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), diffusion-tensor magnetic resonance imaging (DWI/DTI), positron emission tomography (PET), and electro- and magneto-encephalography (EEG/MEG) based imaging. Underlying physical principles, modelling and data processing approaches, as well as clinical and research relevance are briefly outlined for each technique. Givenmore » the breadth of the scope, there has been no attempt to be comprehensive. The ninth and final section outlines some aspects of active research in neuroimaging.« less

Altered resting-state functional connectivity in post-traumatic stress disorder: a perfusion MRI study

NASA Astrophysics Data System (ADS)

Li, Baojuan; Liu, Jian; Liu, Yang; Lu, Hong-Bing; Yin, Hong

2013-03-01

The majority of studies on posttraumatic stress disorder (PTSD) so far have focused on delineating patterns of activations during cognitive processes. Recently, more and more researches have started to investigate functional connectivity in PTSD subjects using BOLD-fMRI. Functional connectivity analysis has been demonstrated as a powerful approach to identify biomarkers of different brain diseases. This study aimed to detect resting-state functional connectivity abnormities in patients with PTSD using arterial spin labeling (ASL) fMRI. As a completely non-invasive technique, ASL allows quantitative estimates of cerebral blood flow (CBF). Compared with BOLD-fMRI, ASL fMRI has many advantages, including less low-frequency signal drifts, superior functional localization, etc. In the current study, ASL images were collected from 10 survivors in mining disaster with recent onset PTSD and 10 survivors without PTSD. Decreased regional CBF in the right middle temporal gyrus, lingual gyrus, and postcentral gyrus was detected in the PTSD patients. Seed-based resting-state functional connectivity analysis was performed using an area in the right middle temporal gyrus as region of interest. Compared with the non-PTSD group, the PTSD subjects demonstrated increased functional connectivity between the right middle temporal gyrus and the right superior temporal gyrus, the left middle temporal gyrus. Meanwhile, decreased functional connectivity between the right middle temporal gyrus and the right postcentral gyrus, the right superior parietal lobule was also found in the PTSD patients. This is the first study which investigated resting-state functional connectivity in PTSD using ASL images. The results may provide new insight into the neural substrates of PTSD.

PreSurgMapp: a MATLAB Toolbox for Presurgical Mapping of Eloquent Functional Areas Based on Task-Related and Resting-State Functional MRI.

PubMed

Huang, Huiyuan; Ding, Zhongxiang; Mao, Dewang; Yuan, Jianhua; Zhu, Fangmei; Chen, Shuda; Xu, Yan; Lou, Lin; Feng, Xiaoyan; Qi, Le; Qiu, Wusi; Zhang, Han; Zang, Yu-Feng

2016-10-01

The main goal of brain tumor surgery is to maximize tumor resection while minimizing the risk of irreversible postoperative functional sequelae. Eloquent functional areas should be delineated preoperatively, particularly for patients with tumors near eloquent areas. Functional magnetic resonance imaging (fMRI) is a noninvasive technique that demonstrates great promise for presurgical planning. However, specialized data processing toolkits for presurgical planning remain lacking. Based on several functions in open-source software such as Statistical Parametric Mapping (SPM), Resting-State fMRI Data Analysis Toolkit (REST), Data Processing Assistant for Resting-State fMRI (DPARSF) and Multiple Independent Component Analysis (MICA), here, we introduce an open-source MATLAB toolbox named PreSurgMapp. This toolbox can reveal eloquent areas using comprehensive methods and various complementary fMRI modalities. For example, PreSurgMapp supports both model-based (general linear model, GLM, and seed correlation) and data-driven (independent component analysis, ICA) methods and processes both task-based and resting-state fMRI data. PreSurgMapp is designed for highly automatic and individualized functional mapping with a user-friendly graphical user interface (GUI) for time-saving pipeline processing. For example, sensorimotor and language-related components can be automatically identified without human input interference using an effective, accurate component identification algorithm using discriminability index. All the results generated can be further evaluated and compared by neuro-radiologists or neurosurgeons. This software has substantial value for clinical neuro-radiology and neuro-oncology, including application to patients with low- and high-grade brain tumors and those with epilepsy foci in the dominant language hemisphere who are planning to undergo a temporal lobectomy.

Online Reduction of Artifacts in EEG of Simultaneous EEG-fMRI Using Reference Layer Adaptive Filtering (RLAF).

PubMed

Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R

2018-01-01

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) allow us to study the active human brain from two perspectives concurrently. Signal processing based artifact reduction techniques are mandatory for this, however, to obtain reasonable EEG quality in simultaneous EEG-fMRI. Current artifact reduction techniques like average artifact subtraction (AAS), typically become less effective when artifact reduction has to be performed on-the-fly. We thus present and evaluate a new technique to improve EEG quality online. This technique adds up with online AAS and combines a prototype EEG-cap for reference recordings of artifacts, with online adaptive filtering and is named reference layer adaptive filtering (RLAF). We found online AAS + RLAF to be highly effective in improving EEG quality. Online AAS + RLAF outperformed online AAS and did so in particular online in terms of the chosen performance metrics, these being specifically alpha rhythm amplitude ratio between closed and opened eyes (3-45% improvement), signal-to-noise-ratio of visual evoked potentials (VEP) (25-63% improvement), and VEPs variability (16-44% improvement). Further, we found that EEG quality after online AAS + RLAF is occasionally even comparable with the offline variant of AAS at a 3T MRI scanner. In conclusion RLAF is a very effective add-on tool to enable high quality EEG in simultaneous EEG-fMRI experiments, even when online artifact reduction is necessary.

Functional magnetic resonance imaging in a low-field intraoperative scanner.

PubMed

Schulder, Michael; Azmi, Hooman; Biswal, Bharat

2003-01-01

Functional magnetic resonance imaging (fMRI) has been used for preoperative planning and intraoperative surgical navigation. However, most experience to date has been with preoperative images acquired on high-field echoplanar MRI units. We explored the feasibility of acquiring fMRI of the motor cortex with a dedicated low-field intraoperative MRI (iMRI). Five healthy volunteers were scanned with the 0.12-tesla PoleStar N-10 iMRI (Odin Medical Technologies, Israel). A finger-tapping motor paradigm was performed with sequential scans, acquired alternately at rest and during activity. In addition, scans were obtained during breath holding alternating with normal breathing. The same paradigms were repeated using a 3-tesla MRI (Siemens Corp., Allandale, N.J., USA). Statistical analysis was performed offline using cross-correlation and cluster techniques. Data were resampled using the 'jackknife' process. The location, number of activated voxels and degrees of statistical significance between the two scanners were compared. With both the 0.12- and 3-tesla imagers, motor cortex activation was seen in all subjects to a significance of p < 0.02 or greater. No clustered pixels were seen outside the sensorimotor cortex. The resampled correlation coefficients were normally distributed, with a mean of 0.56 for both the 0.12- and 3-tesla scanners (standard deviations 0.11 and 0.08, respectively). The breath holding paradigm confirmed that the expected diffuse activation was seen on 0.12- and 3-tesla scans. Accurate fMRI with a low-field iMRI is feasible. Such data could be acquired immediately before or even during surgery. This would increase the utility of iMRI and allow for updated intraoperative functional imaging, free of the limitations of brain shift. Copyright 2003 S. Karger AG, Basel

Real-Time fMRI in Neuroscience Research and Its Use in Studying the Aging Brain

PubMed Central

Rana, Mohit; Varan, Andrew Q.; Davoudi, Anis; Cohen, Ronald A.; Sitaram, Ranganatha; Ebner, Natalie C.

2016-01-01

Cognitive decline is a major concern in the aging population. It is normative to experience some deterioration in cognitive abilities with advanced age such as related to memory performance, attention distraction to interference, task switching, and processing speed. However, intact cognitive functioning in old age is important for leading an independent day-to-day life. Thus, studying ways to counteract or delay the onset of cognitive decline in aging is crucial. The literature offers various explanations for the decline in cognitive performance in aging; among those are age-related gray and white matter atrophy, synaptic degeneration, blood flow reduction, neurochemical alterations, and change in connectivity patterns with advanced age. An emerging literature on neurofeedback and Brain Computer Interface (BCI) reports exciting results supporting the benefits of volitional modulation of brain activity on cognition and behavior. Neurofeedback studies based on real-time functional magnetic resonance imaging (rtfMRI) have shown behavioral changes in schizophrenia and behavioral benefits in nicotine addiction. This article integrates research on cognitive and brain aging with evidence of brain and behavioral modification due to rtfMRI neurofeedback. We offer a state-of-the-art description of the rtfMRI technique with an eye towards its application in aging. We present preliminary results of a feasibility study exploring the possibility of using rtfMRI to train older adults to volitionally control brain activity. Based on these first findings, we discuss possible implementations of rtfMRI neurofeedback as a novel technique to study and alleviate cognitive decline in healthy and pathological aging. PMID:27803662

Investigation of a calcium-responsive contrast agent in cellular model systems: feasibility for use as a smart molecular probe in functional MRI.

PubMed

Angelovski, Goran; Gottschalk, Sven; Milošević, Milena; Engelmann, Jörn; Hagberg, Gisela E; Kadjane, Pascal; Andjus, Pavle; Logothetis, Nikos K

2014-05-21

Responsive or smart contrast agents (SCAs) represent a promising direction for development of novel functional MRI (fMRI) methods for the eventual noninvasive assessment of brain function. In particular, SCAs that respond to Ca(2+) may allow tracking neuronal activity independent of brain vasculature, thus avoiding the characteristic limitations of current fMRI techniques. Here we report an in vitro proof-of-principle study with a Ca(2+)-sensitive, Gd(3+)-based SCA in an attempt to validate its potential use as a functional in vivo marker. First, we quantified its relaxometric response in a complex 3D cell culture model. Subsequently, we examined potential changes in the functionality of primary glial cells following administration of this SCA. Monitoring intracellular Ca(2+) showed that, despite a reduction in the Ca(2+) level, transport of Ca(2+) through the plasma membrane remained unaffected, while stimulation with ATP induced Ca(2+)-transients suggested normal cellular signaling in the presence of low millimolar SCA concentrations. SCAs merely lowered the intracellular Ca(2+) level. Finally, we estimated the longitudinal relaxation times (T1) for an idealized in vivo fMRI experiment with SCA, for extracellular Ca(2+) concentration level changes expected during intense neuronal activity which takes place upon repetitive stimulation. The values we obtained indicate changes in T1 of around 1-6%, sufficient to be robustly detectable using modern MRI methods in high field scanners. Our results encourage further attempts to develop even more potent SCAs and appropriate fMRI protocols. This would result in novel methods that allow monitoring of essential physiological processes at the cellular and molecular level.

Optimized Design and Analysis of Sparse-Sampling fMRI Experiments

PubMed Central

Perrachione, Tyler K.; Ghosh, Satrajit S.

2013-01-01

Sparse-sampling is an important methodological advance in functional magnetic resonance imaging (fMRI), in which silent delays are introduced between MR volume acquisitions, allowing for the presentation of auditory stimuli without contamination by acoustic scanner noise and for overt vocal responses without motion-induced artifacts in the functional time series. As such, the sparse-sampling technique has become a mainstay of principled fMRI research into the cognitive and systems neuroscience of speech, language, hearing, and music. Despite being in use for over a decade, there has been little systematic investigation of the acquisition parameters, experimental design considerations, and statistical analysis approaches that bear on the results and interpretation of sparse-sampling fMRI experiments. In this report, we examined how design and analysis choices related to the duration of repetition time (TR) delay (an acquisition parameter), stimulation rate (an experimental design parameter), and model basis function (an analysis parameter) act independently and interactively to affect the neural activation profiles observed in fMRI. First, we conducted a series of computational simulations to explore the parameter space of sparse design and analysis with respect to these variables; second, we validated the results of these simulations in a series of sparse-sampling fMRI experiments. Overall, these experiments suggest the employment of three methodological approaches that can, in many situations, substantially improve the detection of neurophysiological response in sparse fMRI: (1) Sparse analyses should utilize a physiologically informed model that incorporates hemodynamic response convolution to reduce model error. (2) The design of sparse fMRI experiments should maintain a high rate of stimulus presentation to maximize effect size. (3) TR delays of short to intermediate length can be used between acquisitions of sparse-sampled functional image volumes to increase the number of samples and improve statistical power. PMID:23616742

Data collection and analysis strategies for phMRI.

PubMed

Mandeville, Joseph B; Liu, Christina H; Vanduffel, Wim; Marota, John J A; Jenkins, Bruce G

2014-09-01

Although functional MRI traditionally has been applied mainly to study changes in task-induced brain function, evolving acquisition methodologies and improved knowledge of signal mechanisms have increased the utility of this method for studying responses to pharmacological stimuli, a technique often dubbed "phMRI". The proliferation of higher magnetic field strengths and the use of exogenous contrast agent have boosted detection power, a critical factor for successful phMRI due to the restricted ability to average multiple stimuli within subjects. Receptor-based models of neurovascular coupling, including explicit pharmacological models incorporating receptor densities and affinities and data-driven models that incorporate weak biophysical constraints, have demonstrated compelling descriptions of phMRI signal induced by dopaminergic stimuli. This report describes phMRI acquisition and analysis methodologies, with an emphasis on data-driven analyses. As an example application, statistically efficient data-driven regressors were used to describe the biphasic response to the mu-opioid agonist remifentanil, and antagonism using dopaminergic and GABAergic ligands revealed modulation of the mesolimbic pathway. Results illustrate the power of phMRI as well as our incomplete understanding of mechanisms underlying the signal. Future directions are discussed for phMRI acquisitions in human studies, for evolving analysis methodologies, and for interpretative studies using the new generation of simultaneous PET/MRI scanners. This article is part of the Special Issue Section entitled 'Neuroimaging in Neuropharmacology'. Copyright © 2014 Elsevier Ltd. All rights reserved.

Adaptive cyclic physiologic noise modeling and correction in functional MRI.

PubMed

Beall, Erik B

2010-03-30

Physiologic noise in BOLD-weighted MRI data is known to be a significant source of the variance, reducing the statistical power and specificity in fMRI and functional connectivity analyses. We show a dramatic improvement on current noise correction methods in both fMRI and fcMRI data that avoids overfitting. The traditional noise model is a Fourier series expansion superimposed on the periodicity of parallel measured breathing and cardiac cycles. Correction using this model results in removal of variance matching the periodicity of the physiologic cycles. Using this framework allows easy modeling of noise. However, using a large number of regressors comes at the cost of removing variance unrelated to physiologic noise, such as variance due to the signal of functional interest (overfitting the data). It is our hypothesis that there are a small variety of fits that describe all of the significantly coupled physiologic noise. If this is true, we can replace a large number of regressors used in the model with a smaller number of the fitted regressors and thereby account for the noise sources with a smaller reduction in variance of interest. We describe these extensions and demonstrate that we can preserve variance in the data unrelated to physiologic noise while removing physiologic noise equivalently, resulting in data with a higher effective SNR than with current corrections techniques. Our results demonstrate a significant improvement in the sensitivity of fMRI (up to a 17% increase in activation volume for fMRI compared with higher order traditional noise correction) and functional connectivity analyses. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Assessing Language Dominance with Functional MRI: The Role of Control Tasks and Statistical Analysis

ERIC Educational Resources Information Center

Dodoo-Schittko, Frank; Rosengarth, Katharina; Doenitz, Christian; Greenlee, Mark W.

2012-01-01

There is a discrepancy between the brain regions revealed by functional neuroimaging techniques and those brain regions where a loss of function, either by lesion or by electrocortical stimulation, induces language disorders. To differentiate between essential and non-essential language-related processes, we investigated the effects of linguistic…

Vessel wall characterization using quantitative MRI: what's in a number?

PubMed

Coolen, Bram F; Calcagno, Claudia; van Ooij, Pim; Fayad, Zahi A; Strijkers, Gustav J; Nederveen, Aart J

2018-02-01

The past decade has witnessed the rapid development of new MRI technology for vessel wall imaging. Today, with advances in MRI hardware and pulse sequences, quantitative MRI of the vessel wall represents a real alternative to conventional qualitative imaging, which is hindered by significant intra- and inter-observer variability. Quantitative MRI can measure several important morphological and functional characteristics of the vessel wall. This review provides a detailed introduction to novel quantitative MRI methods for measuring vessel wall dimensions, plaque composition and permeability, endothelial shear stress and wall stiffness. Together, these methods show the versatility of non-invasive quantitative MRI for probing vascular disease at several stages. These quantitative MRI biomarkers can play an important role in the context of both treatment response monitoring and risk prediction. Given the rapid developments in scan acceleration techniques and novel image reconstruction, we foresee the possibility of integrating the acquisition of multiple quantitative vessel wall parameters within a single scan session.

A three-way parallel ICA approach to analyze links among genetics, brain structure and brain function.

PubMed

Vergara, Victor M; Ulloa, Alvaro; Calhoun, Vince D; Boutte, David; Chen, Jiayu; Liu, Jingyu

2014-09-01

Multi-modal data analysis techniques, such as the Parallel Independent Component Analysis (pICA), are essential in neuroscience, medical imaging and genetic studies. The pICA algorithm allows the simultaneous decomposition of up to two data modalities achieving better performance than separate ICA decompositions and enabling the discovery of links between modalities. However, advances in data acquisition techniques facilitate the collection of more than two data modalities from each subject. Examples of commonly measured modalities include genetic information, structural magnetic resonance imaging (MRI) and functional MRI. In order to take full advantage of the available data, this work extends the pICA approach to incorporate three modalities in one comprehensive analysis. Simulations demonstrate the three-way pICA performance in identifying pairwise links between modalities and estimating independent components which more closely resemble the true sources than components found by pICA or separate ICA analyses. In addition, the three-way pICA algorithm is applied to real experimental data obtained from a study that investigate genetic effects on alcohol dependence. Considered data modalities include functional MRI (contrast images during alcohol exposure paradigm), gray matter concentration images from structural MRI and genetic single nucleotide polymorphism (SNP). The three-way pICA approach identified links between a SNP component (pointing to brain function and mental disorder associated genes, including BDNF, GRIN2B and NRG1), a functional component related to increased activation in the precuneus area, and a gray matter component comprising part of the default mode network and the caudate. Although such findings need further verification, the simulation and in-vivo results validate the three-way pICA algorithm presented here as a useful tool in biomedical data fusion applications. Copyright © 2014 Elsevier Inc. All rights reserved.

Evaluating Dynamic Bivariate Correlations in Resting-state fMRI: A comparison study and a new approach

PubMed Central

Lindquist, Martin A.; Xu, Yuting; Nebel, Mary Beth; Caffo, Brain S.

2014-01-01

To date, most functional Magnetic Resonance Imaging (fMRI) studies have assumed that the functional connectivity (FC) between time series from distinct brain regions is constant across time. However, recently, there has been increased interest in quantifying possible dynamic changes in FC during fMRI experiments, as it is thought this may provide insight into the fundamental workings of brain networks. In this work we focus on the specific problem of estimating the dynamic behavior of pair-wise correlations between time courses extracted from two different regions of the brain. We critique the commonly used sliding-windows technique, and discuss some alternative methods used to model volatility in the finance literature that could also prove useful in the neuroimaging setting. In particular, we focus on the Dynamic Conditional Correlation (DCC) model, which provides a model-based approach towards estimating dynamic correlations. We investigate the properties of several techniques in a series of simulation studies and find that DCC achieves the best overall balance between sensitivity and specificity in detecting dynamic changes in correlations. We also investigate its scalability beyond the bivariate case to demonstrate its utility for studying dynamic correlations between more than two brain regions. Finally, we illustrate its performance in an application to test-retest resting state fMRI data. PMID:24993894

Denoising the Speaking Brain: Toward a Robust Technique for Correcting Artifact-Contaminated fMRI Data under Severe Motion

PubMed Central

Xu, Yisheng; Tong, Yunxia; Liu, Siyuan; Chow, Ho Ming; AbdulSabur, Nuria Y.; Mattay, Govind S.; Braun, Allen R.

2014-01-01

A comprehensive set of methods based on spatial independent component analysis (sICA) is presented as a robust technique for artifact removal, applicable to a broad range of functional magnetic resonance imaging (fMRI) experiments that have been plagued by motion-related artifacts. Although the applications of sICA for fMRI denoising have been studied previously, three fundamental elements of this approach have not been established as follows: 1) a mechanistically-based ground truth for component classification; 2) a general framework for evaluating the performance and generalizability of automated classifiers; 3) a reliable method for validating the effectiveness of denoising. Here we perform a thorough investigation of these issues and demonstrate the power of our technique by resolving the problem of severe imaging artifacts associated with continuous overt speech production. As a key methodological feature, a dual-mask sICA method is proposed to isolate a variety of imaging artifacts by directly revealing their extracerebral spatial origins. It also plays an important role for understanding the mechanistic properties of noise components in conjunction with temporal measures of physical or physiological motion. The potentials of a spatially-based machine learning classifier and the general criteria for feature selection have both been examined, in order to maximize the performance and generalizability of automated component classification. The effectiveness of denoising is quantitatively validated by comparing the activation maps of fMRI with those of positron emission tomography acquired under the same task conditions. The general applicability of this technique is further demonstrated by the successful reduction of distance-dependent effect of head motion on resting-state functional connectivity. PMID:25225001

Denoising the speaking brain: toward a robust technique for correcting artifact-contaminated fMRI data under severe motion.

PubMed

Xu, Yisheng; Tong, Yunxia; Liu, Siyuan; Chow, Ho Ming; AbdulSabur, Nuria Y; Mattay, Govind S; Braun, Allen R

2014-12-01

A comprehensive set of methods based on spatial independent component analysis (sICA) is presented as a robust technique for artifact removal, applicable to a broad range of functional magnetic resonance imaging (fMRI) experiments that have been plagued by motion-related artifacts. Although the applications of sICA for fMRI denoising have been studied previously, three fundamental elements of this approach have not been established as follows: 1) a mechanistically-based ground truth for component classification; 2) a general framework for evaluating the performance and generalizability of automated classifiers; and 3) a reliable method for validating the effectiveness of denoising. Here we perform a thorough investigation of these issues and demonstrate the power of our technique by resolving the problem of severe imaging artifacts associated with continuous overt speech production. As a key methodological feature, a dual-mask sICA method is proposed to isolate a variety of imaging artifacts by directly revealing their extracerebral spatial origins. It also plays an important role for understanding the mechanistic properties of noise components in conjunction with temporal measures of physical or physiological motion. The potentials of a spatially-based machine learning classifier and the general criteria for feature selection have both been examined, in order to maximize the performance and generalizability of automated component classification. The effectiveness of denoising is quantitatively validated by comparing the activation maps of fMRI with those of positron emission tomography acquired under the same task conditions. The general applicability of this technique is further demonstrated by the successful reduction of distance-dependent effect of head motion on resting-state functional connectivity. Copyright © 2014 Elsevier Inc. All rights reserved.

Multimodal assessment of hemispheric lateralization for language and its relevance for behavior.

PubMed

Piervincenzi, C; Petrilli, A; Marini, A; Caulo, M; Committeri, G; Sestieri, C

2016-11-15

Although different MRI-based techniques have been proposed to assess the hemispheric lateralization for language (HLL), the agreement across methods, and its relationship with language abilities, are still a matter of debate. In the present study we obtained measures of HLL using both task-evoked activity during the execution of three different protocols and task-free methods of functional [resting state functional connectivity (rs-FC)] and anatomical [diffusion tensor imaging (DTI) tractography] connectivity. Regional analyses focusing on the perisylvian language network were conducted to assess the consistency of HLL across techniques. In addition, following a multimodal approach, we identified macro-factors of lateralization and examined their relationship with language performance. Our findings indicate the existence of a negative relationship between the structural asymmetry of the direct segment of the arcuate fasciculus (AF) and the inter-hemispheric rs-FC of key nodes of the perisylvian network. Instead, despite all the language tasks exhibited a leftward pattern of asymmetry, measures of HLL derived from task-evoked activity did not show a direct relationship with those obtained with the two task-free methods. Furthermore, a robust brain-behavioral relationship was observed only with a specific macro-factor that combined HLL measures derived from all MRI techniques. In particular, general language performance was positively related to more symmetrical structural organization, stronger inter-hemispheric communication at rest but more lateralized activation of Wernicke's territory during production tasks. Our findings, while not supporting the existence of a direct relationship between indices of hemispheric lateralization for language derived from different MRI techniques, indicate that general language performance can be indexed using combined MRI measures. The same approach might prove successful for likewise complex human behaviours. Copyright © 2016 Elsevier Inc. All rights reserved.

Structural Image Analysis of the Brain in Neuropsychology Using Magnetic Resonance Imaging (MRI) Techniques.

PubMed

Bigler, Erin D

2015-09-01

Magnetic resonance imaging (MRI) of the brain provides exceptional image quality for visualization and neuroanatomical classification of brain structure. A variety of image analysis techniques provide both qualitative as well as quantitative methods to relate brain structure with neuropsychological outcome and are reviewed herein. Of particular importance are more automated methods that permit analysis of a broad spectrum of anatomical measures including volume, thickness and shape. The challenge for neuropsychology is which metric to use, for which disorder and the timing of when image analysis methods are applied to assess brain structure and pathology. A basic overview is provided as to the anatomical and pathoanatomical relations of different MRI sequences in assessing normal and abnormal findings. Some interpretive guidelines are offered including factors related to similarity and symmetry of typical brain development along with size-normalcy features of brain anatomy related to function. The review concludes with a detailed example of various quantitative techniques applied to analyzing brain structure for neuropsychological outcome studies in traumatic brain injury.

Emerging MRI and metabolic neuroimaging techniques in mild traumatic brain injury.

PubMed

Lu, Liyan; Wei, Xiaoer; Li, Minghua; Li, Yuehua; Li, Wenbin

2014-01-01

Traumatic brain injury (TBI) is one of the leading causes of death worldwide, and mild traumatic brain injury (mTBI) is the most common traumatic injury. It is difficult to detect mTBI using a routine neuroimaging. Advanced techniques with greater sensitivity and specificity for the diagnosis and treatment of mTBI are required. The aim of this review is to offer an overview of various emerging neuroimaging methodologies that can solve the clinical health problems associated with mTBI. Important findings and improvements in neuroimaging that hold value for better detection, characterization and monitoring of objective brain injuries in patients with mTBI are presented. Conventional computed tomography (CT) and magnetic resonance imaging (MRI) are not very efficient for visualizing mTBI. Moreover, techniques such as diffusion tensor imaging, magnetization transfer imaging, susceptibility-weighted imaging, functional MRI, single photon emission computed tomography, positron emission tomography and magnetic resonance spectroscopy imaging were found to be useful for mTBI imaging.

Radiology of colorectal cancer.

PubMed

Pijl, M E J; Chaoui, A S; Wahl, R L; van Oostayen, J A

2002-05-01

In the past 20 years, the radiology of colorectal cancer has evolved from the barium enema to advanced imaging modalities like phased array magnetic resonance imaging (MRI), virtual colonoscopy and positron emission tomography (PET). Nowadays, primary rectal cancers are preferably imaged with transrectal ultrasound or MRI, while barium enema is still the most often used technique for imaging of colonic cancers. Virtual colonoscopy is rapidly evolving and might considerably change the imaging of colorectal cancer in the near future. The use of virtual colonoscopy for screening purposes and imaging of the colon in occlusive cancer or incomplete colonoscopies is currently under evaluation. The main role of PET is in detecting tumour recurrences, both locally and distantly. Techniques to fuse cross-sectional anatomical (computer tomography (CT) and MRI) and functional (PET) images are being developed. Apart from diagnostic imaging, the radiologists has added image-guided minimally invasive treatments of colorectal liver metastases to their arsenal. The radio-frequency ablation technique is now widely available, and can be used during laparotomy or percutaneously in selected cases.

Probabilistic atlases of default mode, executive control and salience network white matter tracts: an fMRI-guided diffusion tensor imaging and tractography study

PubMed Central

Figley, Teresa D.; Bhullar, Navdeep; Courtney, Susan M.; Figley, Chase R.

2015-01-01

Diffusion tensor imaging (DTI) is a powerful MRI technique that can be used to estimate both the microstructural integrity and the trajectories of white matter pathways throughout the central nervous system. This fiber tracking (aka, “tractography”) approach is often carried out using anatomically-defined seed points to identify white matter tracts that pass through one or more structures, but can also be performed using functionally-defined regions of interest (ROIs) that have been determined using functional MRI (fMRI) or other methods. In this study, we performed fMRI-guided DTI tractography between all of the previously defined nodes within each of six common resting-state brain networks, including the: dorsal Default Mode Network (dDMN), ventral Default Mode Network (vDMN), left Executive Control Network (lECN), right Executive Control Network (rECN), anterior Salience Network (aSN), and posterior Salience Network (pSN). By normalizing the data from 32 healthy control subjects to a standard template—using high-dimensional, non-linear warping methods—we were able to create probabilistic white matter atlases for each tract in stereotaxic coordinates. By investigating all 198 ROI-to-ROI combinations within the aforementioned resting-state networks (for a total of 6336 independent DTI tractography analyses), the resulting probabilistic atlases represent a comprehensive cohort of functionally-defined white matter regions that can be used in future brain imaging studies to: (1) ascribe DTI or other white matter changes to particular functional brain networks, and (2) compliment resting state fMRI or other functional connectivity analyses. PMID:26578930

Functional connectivity analysis of resting-state fMRI networks in nicotine dependent patients

NASA Astrophysics Data System (ADS)

Smith, Aria; Ehtemami, Anahid; Fratte, Daniel; Meyer-Baese, Anke; Zavala-Romero, Olmo; Goudriaan, Anna E.; Schmaal, Lianne; Schulte, Mieke H. J.

2016-03-01

Brain imaging studies identified brain networks that play a key role in nicotine dependence-related behavior. Functional connectivity of the brain is dynamic; it changes over time due to different causes such as learning, or quitting a habit. Functional connectivity analysis is useful in discovering and comparing patterns between functional magnetic resonance imaging (fMRI) scans of patients' brains. In the resting state, the patient is asked to remain calm and not do any task to minimize the contribution of external stimuli. The study of resting-state fMRI networks have shown functionally connected brain regions that have a high level of activity during this state. In this project, we are interested in the relationship between these functionally connected brain regions to identify nicotine dependent patients, who underwent a smoking cessation treatment. Our approach is on the comparison of the set of connections between the fMRI scans before and after treatment. We applied support vector machines, a machine learning technique, to classify patients based on receiving the treatment or the placebo. Using the functional connectivity (CONN) toolbox, we were able to form a correlation matrix based on the functional connectivity between different regions of the brain. The experimental results show that there is inadequate predictive information to classify nicotine dependent patients using the SVM classifier. We propose other classification methods be explored to better classify the nicotine dependent patients.

MR-guided endovascular interventions: a comprehensive review on techniques and applications.

PubMed

Kos, Sebastian; Huegli, Rolf; Bongartz, Georg M; Jacob, Augustinus L; Bilecen, Deniz

2008-04-01

The magnetic resonance (MR) guidance of endovascular interventions is probably one of the greatest challenges of clinical MR research. MR angiography is not only an imaging tool for the vasculature but can also simultaneously depict high tissue contrast, including the differentiation of the vascular wall and perivascular tissues, as well as vascular function. Several hurdles had to be overcome to allow MR guidance for endovascular interventions. MR hardware and sequence design had to be developed to achieve acceptable patient access and to allow real-time or near real-time imaging. The development of interventional devices, both applicable and safe for MR imaging (MRI), was also mandatory. The subject of this review is to summarize the latest developments in real-time MRI hardware, MRI, visualization tools, interventional devices, endovascular tracking techniques, actual applications and safety issues.

Advanced MR Imaging of the Placenta: Exploring the in utero placenta-brain connection

PubMed Central

Andescavage, Nickie Niforatos; DuPlessis, Adre; Limperopoulos, Catherine

2015-01-01

The placenta is a vital organ necessary for the healthy neurodevelopment of the fetus. Despite the known associations between placental dysfunction and neurologic impairment, there is a paucity of tools available to reliably assess in vivo placental health and function. Existing clinical tools for placental assessment remain insensitive in predicting and assessing placental well-being. Advanced MRI techniques hold significant promise for the dynamic, non-invasive, real-time assessment of placental health and identification of early placental-based disorders. In this review, we summarize the available clinical tools for placental assessment including ultrasound, Doppler, and conventional MRI. We then explore the emerging role of advanced placental MR imaging techniques for supporting the developing fetus, appraise the strengths and limitations of quantitative MRI in identifying early markers of placental dysfunction for improved pregnancy monitoring and fetal outcomes. PMID:25765905

Measurement of the distribution of ventilation-perfusion ratios in the human lung with proton MRI: comparison with the multiple inert-gas elimination technique.

PubMed

Sá, Rui Carlos; Henderson, A Cortney; Simonson, Tatum; Arai, Tatsuya J; Wagner, Harrieth; Theilmann, Rebecca J; Wagner, Peter D; Prisk, G Kim; Hopkins, Susan R

2017-07-01

We have developed a novel functional proton magnetic resonance imaging (MRI) technique to measure regional ventilation-perfusion (V̇ A /Q̇) ratio in the lung. We conducted a comparison study of this technique in healthy subjects ( n = 7, age = 42 ± 16 yr, Forced expiratory volume in 1 s = 94% predicted), by comparing data measured using MRI to that obtained from the multiple inert gas elimination technique (MIGET). Regional ventilation measured in a sagittal lung slice using Specific Ventilation Imaging was combined with proton density measured using a fast gradient-echo sequence to calculate regional alveolar ventilation, registered with perfusion images acquired using arterial spin labeling, and divided on a voxel-by-voxel basis to obtain regional V̇ A /Q̇ ratio. LogSDV̇ and LogSDQ̇, measures of heterogeneity derived from the standard deviation (log scale) of the ventilation and perfusion vs. V̇ A /Q̇ ratio histograms respectively, were calculated. On a separate day, subjects underwent study with MIGET and LogSDV̇ and LogSDQ̇ were calculated from MIGET data using the 50-compartment model. MIGET LogSDV̇ and LogSDQ̇ were normal in all subjects. LogSDQ̇ was highly correlated between MRI and MIGET (R = 0.89, P = 0.007); the intercept was not significantly different from zero (-0.062, P = 0.65) and the slope did not significantly differ from identity (1.29, P = 0.34). MIGET and MRI measures of LogSDV̇ were well correlated (R = 0.83, P = 0.02); the intercept differed from zero (0.20, P = 0.04) and the slope deviated from the line of identity (0.52, P = 0.01). We conclude that in normal subjects, there is a reasonable agreement between MIGET measures of heterogeneity and those from proton MRI measured in a single slice of lung. NEW & NOTEWORTHY We report a comparison of a new proton MRI technique to measure regional V̇ A /Q̇ ratio against the multiple inert gas elimination technique (MIGET). The study reports good relationships between measures of heterogeneity derived from MIGET and those derived from MRI. Although currently limited to a single slice acquisition, these data suggest that single sagittal slice measures of V̇ A /Q̇ ratio provide an adequate means to assess heterogeneity in the normal lung. Copyright © 2017 the American Physiological Society.

Statistical segmentation of multidimensional brain datasets

NASA Astrophysics Data System (ADS)

Desco, Manuel; Gispert, Juan D.; Reig, Santiago; Santos, Andres; Pascau, Javier; Malpica, Norberto; Garcia-Barreno, Pedro

2001-07-01

This paper presents an automatic segmentation procedure for MRI neuroimages that overcomes part of the problems involved in multidimensional clustering techniques like partial volume effects (PVE), processing speed and difficulty of incorporating a priori knowledge. The method is a three-stage procedure: 1) Exclusion of background and skull voxels using threshold-based region growing techniques with fully automated seed selection. 2) Expectation Maximization algorithms are used to estimate the probability density function (PDF) of the remaining pixels, which are assumed to be mixtures of gaussians. These pixels can then be classified into cerebrospinal fluid (CSF), white matter and grey matter. Using this procedure, our method takes advantage of using the full covariance matrix (instead of the diagonal) for the joint PDF estimation. On the other hand, logistic discrimination techniques are more robust against violation of multi-gaussian assumptions. 3) A priori knowledge is added using Markov Random Field techniques. The algorithm has been tested with a dataset of 30 brain MRI studies (co-registered T1 and T2 MRI). Our method was compared with clustering techniques and with template-based statistical segmentation, using manual segmentation as a gold-standard. Our results were more robust and closer to the gold-standard.

Uses, misuses, new uses and fundamental limitations of magnetic resonance imaging in cognitive science

PubMed Central

2016-01-01

When blood oxygenation level-dependent (BOLD) contrast functional magnetic resonance imaging (fMRI) was discovered in the early 1990s, it provoked an explosion of interest in exploring human cognition, using brain mapping techniques based on MRI. Standards for data acquisition and analysis were rapidly put in place, in order to assist comparison of results across laboratories. Recently, MRI data acquisition capabilities have improved dramatically, inviting a rethink of strategies for relating functional brain activity at the systems level with its neuronal substrates and functional connections. This paper reviews the established capabilities of BOLD contrast fMRI, the perceived weaknesses of major methods of analysis, and current results that may provide insights into improved brain modelling. These results have inspired the use of in vivo myeloarchitecture for localizing brain activity, individual subject analysis without spatial smoothing and mapping of changes in cerebral blood volume instead of BOLD activation changes. The apparent fundamental limitations of all methods based on nuclear magnetic resonance are also discussed. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574303

Brain–heart interactions: challenges and opportunities with functional magnetic resonance imaging at ultra-high field

PubMed Central

Raven, Erika P.; Duyn, Jeff H.

2016-01-01

Magnetic resonance imaging (MRI) at ultra-high field (UHF) strengths (7 T and above) offers unique opportunities for studying the human brain with increased spatial resolution, contrast and sensitivity. However, its reliability can be compromised by factors such as head motion, image distortion and non-neural fluctuations of the functional MRI signal. The objective of this review is to provide a critical discussion of the advantages and trade-offs associated with UHF imaging, focusing on the application to studying brain–heart interactions. We describe how UHF MRI may provide contrast and resolution benefits for measuring neural activity of regions involved in the control and mediation of autonomic processes, and in delineating such regions based on anatomical MRI contrast. Limitations arising from confounding signals are discussed, including challenges with distinguishing non-neural physiological effects from the neural signals of interest that reflect cardiorespiratory function. We also consider how recently developed data analysis techniques may be applied to high-field imaging data to uncover novel information about brain–heart interactions. PMID:27044994

Brain-heart interactions: challenges and opportunities with functional magnetic resonance imaging at ultra-high field.

PubMed

Chang, Catie; Raven, Erika P; Duyn, Jeff H

2016-05-13

Magnetic resonance imaging (MRI) at ultra-high field (UHF) strengths (7 T and above) offers unique opportunities for studying the human brain with increased spatial resolution, contrast and sensitivity. However, its reliability can be compromised by factors such as head motion, image distortion and non-neural fluctuations of the functional MRI signal. The objective of this review is to provide a critical discussion of the advantages and trade-offs associated with UHF imaging, focusing on the application to studying brain-heart interactions. We describe how UHF MRI may provide contrast and resolution benefits for measuring neural activity of regions involved in the control and mediation of autonomic processes, and in delineating such regions based on anatomical MRI contrast. Limitations arising from confounding signals are discussed, including challenges with distinguishing non-neural physiological effects from the neural signals of interest that reflect cardiorespiratory function. We also consider how recently developed data analysis techniques may be applied to high-field imaging data to uncover novel information about brain-heart interactions. © 2016 The Author(s).

Uses, misuses, new uses and fundamental limitations of magnetic resonance imaging in cognitive science.

PubMed

Turner, Robert

2016-10-05

When blood oxygenation level-dependent (BOLD) contrast functional magnetic resonance imaging (fMRI) was discovered in the early 1990s, it provoked an explosion of interest in exploring human cognition, using brain mapping techniques based on MRI. Standards for data acquisition and analysis were rapidly put in place, in order to assist comparison of results across laboratories. Recently, MRI data acquisition capabilities have improved dramatically, inviting a rethink of strategies for relating functional brain activity at the systems level with its neuronal substrates and functional connections. This paper reviews the established capabilities of BOLD contrast fMRI, the perceived weaknesses of major methods of analysis, and current results that may provide insights into improved brain modelling. These results have inspired the use of in vivo myeloarchitecture for localizing brain activity, individual subject analysis without spatial smoothing and mapping of changes in cerebral blood volume instead of BOLD activation changes. The apparent fundamental limitations of all methods based on nuclear magnetic resonance are also discussed.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. © 2016 The Authors.

Magnetic Resonance Imaging of Gel-cast Ceramic Composites

DOE R&D Accomplishments Database

Dieckman, S. L.; Balss, K. M.; Waterfield, L. G.; Jendrzejczyk, J. A.; Raptis, A. C.

1997-01-16

Magnetic resonance imaging (MRI) techniques are being employed to aid in the development of advanced near-net-shape gel-cast ceramic composites. MRI is a unique nondestructive evaluation tool that provides information on both the chemical and physical properties of materials. In this effort, MRI imaging was performed to monitor the drying of porous green-state alumina - methacrylamide-N.N`-methylene bisacrylamide (MAM-MBAM) polymerized composite specimens. Studies were performed on several specimens as a function of humidity and time. The mass and shrinkage of the specimens were also monitored and correlated with the water content.

[Functional magnetic resonance imaging: a critical analysis of its technical, statistical and theoretical implications in human neuroscience].

PubMed

González-García, C; Tudela, P; Ruz, M

2014-04-01

The use of functional magnetic resonance imaging (fMRI) has represented an important step forward for the neurosciences. Nevertheless, it has also been subject to rather a lot of criticism. To study the most widespread criticism against fMRI, so that researchers who are starting to use it may know the different elements that must be taken into account to be able to take a suitable approach to this technique. The fact that fMRI allows brain activity to be observed makes it a very attractive and useful tool, and its use has grown exponentially since the last decade of the 20th century. At the same time, criticism against its use has become especially fierce. Most of this scepticism can be classified into aspects related with the technique and physiology, the analysis of data and their theoretical interpretation. In this study we will review the main arguments defended in each of these three areas, as well as looking at whether they are well-founded or not. Additionally, this work is also intended as a reference for novel researchers when it comes to identifying elements that must be taken into account as they approach fMRI. Despite the fact that fMRI is one of the most interesting options for observing the brain available today, its correct utilisation requires a great deal of control and knowledge. Even so, today most of the criticism it receives no longer has any solid foundation on which to stand.

Hybrid two-dimensional navigator correction: a new technique to suppress respiratory-induced physiological noise in multi-shot echo-planar functional MRI

PubMed Central

Barry, Robert L.; Klassen, L. Martyn; Williams, Joy M.; Menon, Ravi S.

2008-01-01

A troublesome source of physiological noise in functional magnetic resonance imaging (fMRI) is due to the spatio-temporal modulation of the magnetic field in the brain caused by normal subject respiration. fMRI data acquired using echo-planar imaging is very sensitive to these respiratory-induced frequency offsets, which cause significant geometric distortions in images. Because these effects increase with main magnetic field, they can nullify the gains in statistical power expected by the use of higher magnetic fields. As a study of existing navigator correction techniques for echo-planar fMRI has shown that further improvements can be made in the suppression of respiratory-induced physiological noise, a new hybrid two-dimensional (2D) navigator is proposed. Using a priori knowledge of the slow spatial variations of these induced frequency offsets, 2D field maps are constructed for each shot using spatial frequencies between ±0.5 cm−1 in k-space. For multi-shot fMRI experiments, we estimate that the improvement of hybrid 2D navigator correction over the best performance of one-dimensional navigator echo correction translates into a 15% increase in the volume of activation, 6% and 10% increases in the maximum and average t-statistics, respectively, for regions with high t-statistics, and 71% and 56% increases in the maximum and average t-statistics, respectively, in regions with low t-statistics due to contamination by residual physiological noise. PMID:18024159

Whole-brain functional magnetic resonance imaging mapping of acute nociceptive responses induced by formalin in rats using atlas registration-based event-related analysis.

PubMed

Shih, Yen-Yu I; Chen, You-Yin; Chen, Chiao-Chi V; Chen, Jyh-Cheng; Chang, Chen; Jaw, Fu-Shan

2008-06-01

Nociceptive neuronal activation in subcortical regions has not been well investigated in functional magnetic resonance imaging (fMRI) studies. The present report aimed to use the blood oxygenation level-dependent (BOLD) fMRI technique to map nociceptive responses in both subcortical and cortical regions by employing a refined data processing method, the atlas registration-based event-related (ARBER) analysis technique. During fMRI acquisition, 5% formalin (50 mul) was injected into the left hindpaw to induce nociception. ARBER was then used to normalize the data among rats, and images were analyzed using automatic selection of the atlas-based region of interest. It was found that formalin-induced nociceptive processing increased BOLD signals in both cortical and subcortical regions. The cortical activation was distributed over the cingulate, motor, somatosensory, insular, and visual cortices, and the subcortical activation involved the caudate putamen, hippocampus, periaqueductal gray, superior colliculus, thalamus, and hypothalamus. With the aid of ARBER, the present study revealed a detailed activation pattern that possibly indicated the recruitment of various parts of the nociceptive system. The results also demonstrated the utilization of ARBER in establishing an fMRI-based whole-brain nociceptive map. The formalin induced nociceptive images may serve as a template of central nociceptive responses, which can facilitate the future use of fMRI in evaluation of new drugs and preclinical therapies for pain. (c) 2008 Wiley-Liss, Inc.

fMRI Brain-Computer Interface: A Tool for Neuroscientific Research and Treatment

PubMed Central

Sitaram, Ranganatha; Caria, Andrea; Veit, Ralf; Gaber, Tilman; Rota, Giuseppina; Kuebler, Andrea; Birbaumer, Niels

2007-01-01

Brain-computer interfaces based on functional magnetic resonance imaging (fMRI-BCI) allow volitional control of anatomically specific regions of the brain. Technological advancement in higher field MRI scanners, fast data acquisition sequences, preprocessing algorithms, and robust statistical analysis are anticipated to make fMRI-BCI more widely available and applicable. This noninvasive technique could potentially complement the traditional neuroscientific experimental methods by varying the activity of the neural substrates of a region of interest as an independent variable to study its effects on behavior. If the neurobiological basis of a disorder (e.g., chronic pain, motor diseases, psychopathy, social phobia, depression) is known in terms of abnormal activity in certain regions of the brain, fMRI-BCI can be targeted to modify activity in those regions with high specificity for treatment. In this paper, we review recent results of the application of fMRI-BCI to neuroscientific research and psychophysiological treatment. PMID:18274615

Development of an MR-compatible SPECT system (MRSPECT) for simultaneous data acquisition.

PubMed

Hamamura, Mark J; Ha, Seunghoon; Roeck, Werner W; Muftuler, L Tugan; Wagenaar, Douglas J; Meier, Dirk; Patt, Bradley E; Nalcioglu, Orhan

2010-03-21

In medical imaging, single-photon emission computed tomography (SPECT) can provide specific functional information while magnetic resonance imaging (MRI) can provide high spatial resolution anatomical information as well as complementary functional information. In this study, we developed a miniaturized dual-modality SPECT/MRI (MRSPECT) system and demonstrated the feasibility of simultaneous SPECT and MRI data acquisition, with the possibility of whole-body MRSPECT systems through suitable scaling of components. For our MRSPECT system, a cadmium-zinc-telluride (CZT) nuclear radiation detector was interfaced with a specialized radiofrequency (RF) coil and placed within a whole-body 4 T MRI system. Various phantom experiments characterized the interaction between the SPECT and MRI hardware components. The metallic components of the SPECT hardware altered the B(0) field and generated a non-uniform reduction in the signal-to-noise ratio (SNR) of the MR images. The presence of a magnetic field generated a position shift and resolution loss in the nuclear projection data. Various techniques were proposed to compensate for these adverse effects. Overall, our results demonstrate that accurate, simultaneous SPECT and MRI data acquisition is feasible, justifying the further development of MRSPECT for either small-animal imaging or whole-body human systems by using appropriate components.

Development of an MR-compatible SPECT system (MRSPECT) for simultaneous data acquisition

NASA Astrophysics Data System (ADS)

Hamamura, Mark J.; Ha, Seunghoon; Roeck, Werner W.; Tugan Muftuler, L.; Wagenaar, Douglas J.; Meier, Dirk; Patt, Bradley E.; Nalcioglu, Orhan

2010-03-01

In medical imaging, single-photon emission computed tomography (SPECT) can provide specific functional information while magnetic resonance imaging (MRI) can provide high spatial resolution anatomical information as well as complementary functional information. In this study, we developed a miniaturized dual-modality SPECT/MRI (MRSPECT) system and demonstrated the feasibility of simultaneous SPECT and MRI data acquisition, with the possibility of whole-body MRSPECT systems through suitable scaling of components. For our MRSPECT system, a cadmium-zinc-telluride (CZT) nuclear radiation detector was interfaced with a specialized radiofrequency (RF) coil and placed within a whole-body 4 T MRI system. Various phantom experiments characterized the interaction between the SPECT and MRI hardware components. The metallic components of the SPECT hardware altered the B0 field and generated a non-uniform reduction in the signal-to-noise ratio (SNR) of the MR images. The presence of a magnetic field generated a position shift and resolution loss in the nuclear projection data. Various techniques were proposed to compensate for these adverse effects. Overall, our results demonstrate that accurate, simultaneous SPECT and MRI data acquisition is feasible, justifying the further development of MRSPECT for either small-animal imaging or whole-body human systems by using appropriate components.

The physics of functional magnetic resonance imaging (fMRI)

NASA Astrophysics Data System (ADS)

Buxton, Richard B.

2013-09-01

Functional magnetic resonance imaging (fMRI) is a methodology for detecting dynamic patterns of activity in the working human brain. Although the initial discoveries that led to fMRI are only about 20 years old, this new field has revolutionized the study of brain function. The ability to detect changes in brain activity has a biophysical basis in the magnetic properties of deoxyhemoglobin, and a physiological basis in the way blood flow increases more than oxygen metabolism when local neural activity increases. These effects translate to a subtle increase in the local magnetic resonance signal, the blood oxygenation level dependent (BOLD) effect, when neural activity increases. With current techniques, this pattern of activation can be measured with resolution approaching 1 mm3 spatially and 1 s temporally. This review focuses on the physical basis of the BOLD effect, the imaging methods used to measure it, the possible origins of the physiological effects that produce a mismatch of blood flow and oxygen metabolism during neural activation, and the mathematical models that have been developed to understand the measured signals. An overarching theme is the growing field of quantitative fMRI, in which other MRI methods are combined with BOLD methods and analyzed within a theoretical modeling framework to derive quantitative estimates of oxygen metabolism and other physiological variables. That goal is the current challenge for fMRI: to move fMRI from a mapping tool to a quantitative probe of brain physiology.

The physics of functional magnetic resonance imaging (fMRI)

PubMed Central

Buxton, Richard B

2015-01-01

Functional magnetic resonance imaging (fMRI) is a methodology for detecting dynamic patterns of activity in the working human brain. Although the initial discoveries that led to fMRI are only about 20 years old, this new field has revolutionized the study of brain function. The ability to detect changes in brain activity has a biophysical basis in the magnetic properties of deoxyhemoglobin, and a physiological basis in the way blood flow increases more than oxygen metabolism when local neural activity increases. These effects translate to a subtle increase in the local magnetic resonance signal, the blood oxygenation level dependent (BOLD) effect, when neural activity increases. With current techniques, this pattern of activation can be measured with resolution approaching 1 mm3 spatially and 1 s temporally. This review focuses on the physical basis of the BOLD effect, the imaging methods used to measure it, the possible origins of the physiological effects that produce a mismatch of blood flow and oxygen metabolism during neural activation, and the mathematical models that have been developed to understand the measured signals. An overarching theme is the growing field of quantitative fMRI, in which other MRI methods are combined with BOLD methods and analyzed within a theoretical modeling framework to derive quantitative estimates of oxygen metabolism and other physiological variables. That goal is the current challenge for fMRI: to move fMRI from a mapping tool to a quantitative probe of brain physiology. PMID:24006360

Spatiotemporal characteristics and vascular sources of neural-specific and -nonspecific fMRI signals at submillimeter columnar resolution

PubMed Central

Moon, Chan Hong; Fukuda, Mitsuhiro; Kim, Seong-Gi

2012-01-01

The neural specificity of hemodynamic-based functional magnetic resonance imaging (fMRI) signals are dependent on both the vascular regulation and the sensitivity of the applied fMRI technique to different types and sizes of blood vessels. In order to examine the specificity of MRI-detectable hemodynamic responses, submillimeter blood oxygenation-level dependent (BOLD) and cerebral blood volume (CBV) fMRI studies were performed in a well-established cat orientation column model at 9.4 Tesla. Neural-nonspecific and -specific signals were separated by comparing the fMRI responses of orthogonal orientation stimuli. The BOLD response was dominantly neural-nonspecific, mostly originating from pial and intracortical emerging veins, and thus was highly correlated with baseline blood volume. Uneven baseline CBV may displace or distort small functional domains in high-resolution BOLD maps. The CBV response in the parenchyma exhibited dual spatiotemporal characteristics, a fast and early neural-nonspecific response (with 4.3-s time constant) and a slightly slower and delayed neural-specific response (with 9.4-s time constant). The nonspecific CBV signal originates from early-responding arteries and arterioles, while the specific CBV response, which is not correlated with baseline blood volume, arises from late-responding microvessels including small pre-capillary arterioles and capillaries. Our data indicate that although the neural specificity of CBV fMRI signals is dependent on stimulation duration, high-resolution functional maps can be obtained from steady-state CBV studies. PMID:22960251

The physics of functional magnetic resonance imaging (fMRI).

PubMed

Buxton, Richard B

2013-09-01

Functional magnetic resonance imaging (fMRI) is a methodology for detecting dynamic patterns of activity in the working human brain. Although the initial discoveries that led to fMRI are only about 20 years old, this new field has revolutionized the study of brain function. The ability to detect changes in brain activity has a biophysical basis in the magnetic properties of deoxyhemoglobin, and a physiological basis in the way blood flow increases more than oxygen metabolism when local neural activity increases. These effects translate to a subtle increase in the local magnetic resonance signal, the blood oxygenation level dependent (BOLD) effect, when neural activity increases. With current techniques, this pattern of activation can be measured with resolution approaching 1 mm(3) spatially and 1 s temporally. This review focuses on the physical basis of the BOLD effect, the imaging methods used to measure it, the possible origins of the physiological effects that produce a mismatch of blood flow and oxygen metabolism during neural activation, and the mathematical models that have been developed to understand the measured signals. An overarching theme is the growing field of quantitative fMRI, in which other MRI methods are combined with BOLD methods and analyzed within a theoretical modeling framework to derive quantitative estimates of oxygen metabolism and other physiological variables. That goal is the current challenge for fMRI: to move fMRI from a mapping tool to a quantitative probe of brain physiology.

Functional Imaging and Related Techniques: An Introduction for Rehabilitation Researchers

PubMed Central

Crosson, Bruce; Ford, Anastasia; McGregor, Keith M.; Meinzer, Marcus; Cheshkov, Sergey; Li, Xiufeng; Walker-Batson, Delaina; Briggs, Richard W.

2010-01-01

Functional neuroimaging and related neuroimaging techniques are becoming important tools for rehabilitation research. Functional neuroimaging techniques can be used to determine the effects of brain injury or disease on brain systems related to cognition and behavior and to determine how rehabilitation changes brain systems. These techniques include: functional magnetic resonance imaging (fMRI), positron emission tomography (PET), electroencephalography (EEG), magnetoencephalography (MEG), near infrared spectroscopy (NIRS), and transcranial magnetic stimulation (TMS). Related diffusion weighted magnetic resonance imaging techniques (DWI), including diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI), can quantify white matter integrity. With the proliferation of these imaging techniques in rehabilitation research, it is critical that rehabilitation researchers, as well as consumers of rehabilitation research, become familiar with neuroimaging techniques, what they can offer, and their strengths and weaknesses The purpose to this review is to provide such an introduction to these neuroimaging techniques. PMID:20593321

MRI of the lung: state of the art.

PubMed

Wielpütz, Mark; Kauczor, Hans-Ulrich

2012-01-01

Magnetic resonance imaging (MRI) of the lung is technically challenging due to the low proton density and fast signal decay of the lung parenchyma itself. Additional challenges consist of tissue loss, hyperinflation, and hypoxic hypoperfusion, e.g., in emphysema, a so-called "minus-pathology". However, pathological changes resulting in an increase of tissue ("plus-pathology"), such as atelectases, nodules, infiltrates, mucus, or pleural effusion, are easily depicted with high diagnostic accuracy. Although MRI is inferior or at best equal to multi-detector computed tomography (MDCT) for the detection of subtle morphological features, MRI now offers an increasing spectrum of functional imaging techniques such as perfusion assessment and measurement of ventilation and respiratory mechanics that are superior to what is possible with MDCT. Without putting patients at risk with ionizing radiation, repeated examinations allow for the evaluation of the course of lung disease and monitoring of the therapeutic response through quantitative imaging, providing a level of functional detail that cannot be obtained by any other single imaging modality. As such, MRI will likely be used for clinical applications beyond morphological imaging for many lung diseases. In this article, we review the technical aspects and protocol suggestions for chest MRI and discuss the role of MRI in the evaluation of nodules and masses, airway disease, respiratory mechanics, ventilation, perfusion and hemodynamics, and pulmonary vasculature.

Imaging Agonist-Induced D2/D3 Receptor Desensitization and Internalization In Vivo with PET/fMRI.

PubMed

Sander, Christin Y; Hooker, Jacob M; Catana, Ciprian; Rosen, Bruce R; Mandeville, Joseph B

2016-04-01

This study investigated the dynamics of dopamine receptor desensitization and internalization, thereby proposing a new technique for non-invasive, in vivo measurements of receptor adaptations. The D2/D3 agonist quinpirole, which induces receptor internalization in vitro, was administered at graded doses in non-human primates while imaging with simultaneous positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). A pronounced temporal divergence between receptor occupancy and fMRI signal was observed: occupancy remained elevated while fMRI responded transiently. Analogous experiments with an antagonist (prochlorperazine) and a lower-affinity agonist (ropinirole) exhibited reduced temporal dissociation between occupancy and function, consistent with a mechanism of desensitization and internalization that depends upon drug efficacy and affinity. We postulated a model that incorporates internalization into a neurovascular-coupling relationship. This model yielded in vivo desensitization/internalization rates (0.2/min for quinpirole) consistent with published in vitro measurements. Overall, these results suggest that simultaneous PET/fMRI enables characterization of dynamic neuroreceptor adaptations in vivo, and may offer a first non-invasive method for assessing receptor desensitization and internalization.

Imaging Agonist-Induced D2/D3 Receptor Desensitization and Internalization In Vivo with PET/fMRI

PubMed Central

Sander, Christin Y; Hooker, Jacob M; Catana, Ciprian; Rosen, Bruce R; Mandeville, Joseph B

2016-01-01

This study investigated the dynamics of dopamine receptor desensitization and internalization, thereby proposing a new technique for non-invasive, in vivo measurements of receptor adaptations. The D2/D3 agonist quinpirole, which induces receptor internalization in vitro, was administered at graded doses in non-human primates while imaging with simultaneous positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). A pronounced temporal divergence between receptor occupancy and fMRI signal was observed: occupancy remained elevated while fMRI responded transiently. Analogous experiments with an antagonist (prochlorperazine) and a lower-affinity agonist (ropinirole) exhibited reduced temporal dissociation between occupancy and function, consistent with a mechanism of desensitization and internalization that depends upon drug efficacy and affinity. We postulated a model that incorporates internalization into a neurovascular-coupling relationship. This model yielded in vivo desensitization/internalization rates (0.2/min for quinpirole) consistent with published in vitro measurements. Overall, these results suggest that simultaneous PET/fMRI enables characterization of dynamic neuroreceptor adaptations in vivo, and may offer a first non-invasive method for assessing receptor desensitization and internalization. PMID:26388148

A regularized clustering approach to brain parcellation from functional MRI data

NASA Astrophysics Data System (ADS)

Dillon, Keith; Wang, Yu-Ping

2017-08-01

We consider a data-driven approach for the subdivision of an individual subject's functional Magnetic Resonance Imaging (fMRI) scan into regions of interest, i.e., brain parcellation. The approach is based on a computational technique for calculating resolution from inverse problem theory, which we apply to neighborhood selection for brain connectivity networks. This can be efficiently calculated even for very large images, and explicitly incorporates regularization in the form of spatial smoothing and a noise cutoff. We demonstrate the reproducibility of the method on multiple scans of the same subjects, as well as the variations between subjects.

QUANTITATIVE MAGNETIC RESONANCE IMAGING OF ARTICULAR CARTILAGE AND ITS CLINICAL APPLICATIONS

PubMed Central

Li, Xiaojuan; Majumdar, Sharmila

2013-01-01

Cartilage is one of the most essential tissues for healthy joint function and is compromised in degenerative and traumatic joint diseases. There have been tremendous advances during the past decade using quantitative MRI techniques as a non-invasive tool for evaluating cartilage, with a focus on assessing cartilage degeneration during osteoarthritis (OA). In this review, after a brief overview of cartilage composition and degeneration, we discuss techniques that grade and quantify morphologic changes as well as the techniques that quantify changes in the extracellular matrix. The basic principles, in vivo applications, advantages and challenges for each technique are discussed. Recent studies using the OA Initiative (OAI) data are also summarized. Quantitative MRI provides non-invasive measures of cartilage degeneration at the earliest stages of joint degeneration, which is essential for efforts towards prevention and early intervention in OA. PMID:24115571

Neuronavigation. Principles. Surgical technique.

PubMed Central

Ivanov, Marcel; Vlad Ciurea, Alexandru

2009-01-01

Neuronavigation and stereotaxy are techniques designed to help neurosurgeons precisely localize different intracerebral pathological processes by using a set of preoperative images (CT, MRI, fMRI, PET, SPECT etc.). The development of computer assisted surgery was possible only after a significant technological progress, especially in the area of informatics and imagistics. The main indications of neuronavigation are represented by the targeting of small and deep intracerebral lesions and choosing the best way to treat them, in order to preserve the neurological function. Stereotaxis also allows lesioning or stimulation of basal ganglia for the treatment of movement disorders. These techniques can bring an important amount of confort both to the patient and to the neurosurgeon. Neuronavigation was introduced in Romania around 2003, in four neurosurgical centers. We present our five-years experience in neuronavigation and describe the main principles and surgical techniques. PMID:20108488

A fast multiparameter MRI approach for acute stroke assessment on a 3T clinical scanner: preliminary results in a non-human primate model with transient ischemic occlusion.

PubMed

Zhang, Xiaodong; Tong, Frank; Li, Chun-Xia; Yan, Yumei; Nair, Govind; Nagaoka, Tsukasa; Tanaka, Yoji; Zola, Stuart; Howell, Leonard

2014-04-01

Many MRI parameters have been explored and demonstrated the capability or potential to evaluate acute stroke injury, providing anatomical, microstructural, functional, or neurochemical information for diagnostic purposes and therapeutic development. However, the application of multiparameter MRI approach is hindered in clinic due to the very limited time window after stroke insult. Parallel imaging technique can accelerate MRI data acquisition dramatically and has been incorporated in modern clinical scanners and increasingly applied for various diagnostic purposes. In the present study, a fast multiparameter MRI approach including structural T1-weighted imaging (T1W), T2-weighted imaging (T2W), diffusion tensor imaging (DTI), T2-mapping, proton magnetic resonance spectroscopy, cerebral blood flow (CBF), and magnetization transfer (MT) imaging, was implemented and optimized for assessing acute stroke injury on a 3T clinical scanner. A macaque model of transient ischemic stroke induced by a minimal interventional approach was utilized for evaluating the multiparameter MRI approach. The preliminary results indicate the surgical procedure successfully induced ischemic occlusion in the cortex and/or subcortex in adult macaque monkeys (n=4). Application of parallel imaging technique substantially reduced the scanning duration of most MRI data acquisitions, allowing for fast and repeated evaluation of acute stroke injury. Hence, the use of the multiparameter MRI approach with up to five quantitative measures can provide significant advantages in preclinical or clinical studies of stroke disease.

Pharmacological MRI (phMRI) of the Human Central Nervous System.

PubMed

Lanfermann, H; Schindler, C; Jordan, J; Krug, N; Raab, P

2015-10-01

Pharmacological magnetic resonance imaging (phMRI) of the central nervous system (CNS) addresses the increasing demands in the biopharma industry for new methods that can accurately predict, as early as possible, whether novel CNS agents will be effective and safe. Imaging of physiological and molecular-level function can provide a more direct measure of a drug mechanism of action, enabling more predictive measures of drug activity. The availability of phMRI of the nervous system within the professional infrastructure of the Clinical Research Center (CRC) Hannover as proof of concept center ensures that advances in basic science progress swiftly into benefits for patients. Advanced standardized MRI techniques including quantitative MRI, kurtosis determination, functional MRI, and spectroscopic imaging of the entire brain are necessary for phMRI. As a result, MR scanners will evolve into high-precision measuring instruments for assessment of desirable and undesirable effects of drugs as the basic precondition for individually tailored therapy. The CRC's Imaging Unit with high-end large-scale equipment will allow the following unique opportunities: for example, identification of MR-based biomarkers to assess the effect of drugs (surrogate parameters), establishment of normal levels and reference ranges for MRI-based biomarkers, evaluation of the most relevant MRI sequences for drug monitoring in outpatient care. Another very important prerequisite for phMRI is the MHH Core Facility as the scientific and operational study unit of the CRC partner Hannover Medical School. This unit is responsible for the study coordination, conduction, complete study logistics, administration, and application of the quality assurance system based on required industry standards.

TWave: High-Order Analysis of Functional MRI

PubMed Central

Barnathan, Michael; Megalooikonomou, Vasileios; Faloutsos, Christos; Faro, Scott; Mohamed, Feroze B.

2011-01-01

The traditional approach to functional image analysis models images as matrices of raw voxel intensity values. Although such a representation is widely utilized and heavily entrenched both within neuroimaging and in the wider data mining community, the strong interactions among space, time, and categorical modes such as subject and experimental task inherent in functional imaging yield a dataset with “high-order” structure, which matrix models are incapable of exploiting. Reasoning across all of these modes of data concurrently requires a high-order model capable of representing relationships between all modes of the data in tandem. We thus propose to model functional MRI data using tensors, which are high-order generalizations of matrices equivalent to multidimensional arrays or data cubes. However, several unique challenges exist in the high-order analysis of functional medical data: naïve tensor models are incapable of exploiting spatiotemporal locality patterns, standard tensor analysis techniques exhibit poor efficiency, and mixtures of numeric and categorical modes of data are very often present in neuroimaging experiments. Formulating the problem of image clustering as a form of Latent Semantic Analysis and using the WaveCluster algorithm as a baseline, we propose a comprehensive hybrid tensor and wavelet framework for clustering, concept discovery, and compression of functional medical images which successfully addresses these challenges. Our approach reduced runtime and dataset size on a 9.3 GB finger opposition motor task fMRI dataset by up to 98% while exhibiting improved spatiotemporal coherence relative to standard tensor, wavelet, and voxel-based approaches. Our clustering technique was capable of automatically differentiating between the frontal areas of the brain responsible for task-related habituation and the motor regions responsible for executing the motor task, in contrast to a widely used fMRI analysis program, SPM, which only detected the latter region. Furthermore, our approach discovered latent concepts suggestive of subject handedness nearly 100x faster than standard approaches. These results suggest that a high-order model is an integral component to accurate scalable functional neuroimaging. PMID:21729758

Functional Magnetic Resonance Imaging and Spectroscopic Imaging of the Brain: Application of fMRI and fMRS to Reading Disabilities and Education.

ERIC Educational Resources Information Center

Richards, Todd L.

2001-01-01

This tutorial/review covers functional brain-imaging methods and results used to study language and reading disabilities. Although the emphasis is on magnetic resonance imaging and functional magnetic resonance spectroscopy, other imaging techniques are also discussed including positron emission tomography, electroencephalography,…

Dipy, a library for the analysis of diffusion MRI data.

PubMed

Garyfallidis, Eleftherios; Brett, Matthew; Amirbekian, Bagrat; Rokem, Ariel; van der Walt, Stefan; Descoteaux, Maxime; Nimmo-Smith, Ian

2014-01-01

Diffusion Imaging in Python (Dipy) is a free and open source software project for the analysis of data from diffusion magnetic resonance imaging (dMRI) experiments. dMRI is an application of MRI that can be used to measure structural features of brain white matter. Many methods have been developed to use dMRI data to model the local configuration of white matter nerve fiber bundles and infer the trajectory of bundles connecting different parts of the brain. Dipy gathers implementations of many different methods in dMRI, including: diffusion signal pre-processing; reconstruction of diffusion distributions in individual voxels; fiber tractography and fiber track post-processing, analysis and visualization. Dipy aims to provide transparent implementations for all the different steps of dMRI analysis with a uniform programming interface. We have implemented classical signal reconstruction techniques, such as the diffusion tensor model and deterministic fiber tractography. In addition, cutting edge novel reconstruction techniques are implemented, such as constrained spherical deconvolution and diffusion spectrum imaging (DSI) with deconvolution, as well as methods for probabilistic tracking and original methods for tractography clustering. Many additional utility functions are provided to calculate various statistics, informative visualizations, as well as file-handling routines to assist in the development and use of novel techniques. In contrast to many other scientific software projects, Dipy is not being developed by a single research group. Rather, it is an open project that encourages contributions from any scientist/developer through GitHub and open discussions on the project mailing list. Consequently, Dipy today has an international team of contributors, spanning seven different academic institutions in five countries and three continents, which is still growing.

Dipy, a library for the analysis of diffusion MRI data

PubMed Central

Garyfallidis, Eleftherios; Brett, Matthew; Amirbekian, Bagrat; Rokem, Ariel; van der Walt, Stefan; Descoteaux, Maxime; Nimmo-Smith, Ian

2014-01-01

Diffusion Imaging in Python (Dipy) is a free and open source software project for the analysis of data from diffusion magnetic resonance imaging (dMRI) experiments. dMRI is an application of MRI that can be used to measure structural features of brain white matter. Many methods have been developed to use dMRI data to model the local configuration of white matter nerve fiber bundles and infer the trajectory of bundles connecting different parts of the brain. Dipy gathers implementations of many different methods in dMRI, including: diffusion signal pre-processing; reconstruction of diffusion distributions in individual voxels; fiber tractography and fiber track post-processing, analysis and visualization. Dipy aims to provide transparent implementations for all the different steps of dMRI analysis with a uniform programming interface. We have implemented classical signal reconstruction techniques, such as the diffusion tensor model and deterministic fiber tractography. In addition, cutting edge novel reconstruction techniques are implemented, such as constrained spherical deconvolution and diffusion spectrum imaging (DSI) with deconvolution, as well as methods for probabilistic tracking and original methods for tractography clustering. Many additional utility functions are provided to calculate various statistics, informative visualizations, as well as file-handling routines to assist in the development and use of novel techniques. In contrast to many other scientific software projects, Dipy is not being developed by a single research group. Rather, it is an open project that encourages contributions from any scientist/developer through GitHub and open discussions on the project mailing list. Consequently, Dipy today has an international team of contributors, spanning seven different academic institutions in five countries and three continents, which is still growing. PMID:24600385

[Language Functions in the Frontal Association Area: Brain Mechanisms That Create Language].

PubMed

Yamamoto, Kayako; Sakai, Kuniyoshi L

2016-11-01

Broca's area is known to be critically involved in language processing for more than 150 years. Recent neuroimaging techniques, including functional magnetic resonance imaging (fMRI) and diffusion MRI, enabled the subdivision of Broca's area based on both functional and anatomical aspects. Networks among the frontal association areas, especially the left inferior frontal gyrus (IFG), and other cortical regions in the temporal/parietal association areas, are also important for language-related information processing. Here, we review how neuroimaging studies, combined with research paradigms based on theoretical linguistics, have contributed to clarifying the critical roles of the left IFG in syntactic processing and those of language-related networks, including cortical and cerebellar regions.

MRI-based dynamic tracking of an untethered ferromagnetic microcapsule navigating in liquid

NASA Astrophysics Data System (ADS)

Dahmen, Christian; Belharet, Karim; Folio, David; Ferreira, Antoine; Fatikow, Sergej

2016-04-01

The propulsion of ferromagnetic objects by means of MRI gradients is a promising approach to enable new forms of therapy. In this work, necessary techniques are presented to make this approach work. This includes path planning algorithms working on MRI data, ferromagnetic artifact imaging and a tracking algorithm which delivers position feedback for the ferromagnetic objects, and a propulsion sequence to enable interleaved magnetic propulsion and imaging. Using a dedicated software environment, integrating path-planning methods and real-time tracking, a clinical MRI system is adapted to provide this new functionality for controlled interventional targeted therapeutic applications. Through MRI-based sensing analysis, this article aims to propose a framework to plan a robust pathway to enhance the navigation ability to reach deep locations in the human body. The proposed approaches are validated with different experiments.

Revealing topological organization of human brain functional networks with resting-state functional near infrared spectroscopy.

PubMed

Niu, Haijing; Wang, Jinhui; Zhao, Tengda; Shu, Ni; He, Yong

2012-01-01

The human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics. We utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques. Our results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.

Compressively sampled MR image reconstruction using generalized thresholding iterative algorithm

NASA Astrophysics Data System (ADS)

Elahi, Sana; kaleem, Muhammad; Omer, Hammad

2018-01-01

Compressed sensing (CS) is an emerging area of interest in Magnetic Resonance Imaging (MRI). CS is used for the reconstruction of the images from a very limited number of samples in k-space. This significantly reduces the MRI data acquisition time. One important requirement for signal recovery in CS is the use of an appropriate non-linear reconstruction algorithm. It is a challenging task to choose a reconstruction algorithm that would accurately reconstruct the MR images from the under-sampled k-space data. Various algorithms have been used to solve the system of non-linear equations for better image quality and reconstruction speed in CS. In the recent past, iterative soft thresholding algorithm (ISTA) has been introduced in CS-MRI. This algorithm directly cancels the incoherent artifacts produced because of the undersampling in k -space. This paper introduces an improved iterative algorithm based on p -thresholding technique for CS-MRI image reconstruction. The use of p -thresholding function promotes sparsity in the image which is a key factor for CS based image reconstruction. The p -thresholding based iterative algorithm is a modification of ISTA, and minimizes non-convex functions. It has been shown that the proposed p -thresholding iterative algorithm can be used effectively to recover fully sampled image from the under-sampled data in MRI. The performance of the proposed method is verified using simulated and actual MRI data taken at St. Mary's Hospital, London. The quality of the reconstructed images is measured in terms of peak signal-to-noise ratio (PSNR), artifact power (AP), and structural similarity index measure (SSIM). The proposed approach shows improved performance when compared to other iterative algorithms based on log thresholding, soft thresholding and hard thresholding techniques at different reduction factors.

Capturing neuroplastic changes after bimanual intensive rehabilitation in children with unilateral spastic cerebral palsy: A combined DTI, TMS and fMRI pilot study

PubMed Central

Bleyenheuft, Yannick; Dricot, Laurence; Gilis, Nathalie; Kuo, Hsing-Ching; Grandin, Cécile; Bleyenheuft, Corinne; Gordon, Andrew M.; Friel, Kathleen M.

2016-01-01

Intensive rehabilitation interventions have been shown to be efficacious in improving upper extremity function in children with unilateral spastic cerebral palsy (USCP). These interventions are based on motor learning principles and engage children in skillful movements. Improvements in upper extremity function are believed to be associated with neuroplastic changes. However, these neuroplastic changes have not been well-described in children with cerebral palsy, likely due to challenges in defining and implementing the optimal tools and tests in children. Here we documented the implementation of three different neurological assessments (diffusion tensor imaging-DTI, transcranial magnetic stimulation-TMS and functional magnetic resonance imaging-fMRI) before and after a bimanual intensive treatment (HABIT-ILE) in two children with USCP presenting differential corticospinal developmental reorganization (ipsilateral and contralateral). The aim of the study was to capture neurophysiological changes and to document the complementary relationship between these measures, the potential measurable changes and the feasibility of applying these techniques in children with USCP. Independent of cortical reorganization, both children showed increases in activation and size of the motor areas controlling the affected hand, quantified with different techniques. In addition, fMRI provided additional unexpected changes in the reward circuit while using the affected hand. PMID:26183338

Memory assessment in patients with temporal lobe epilepsy to predict memory impairment after surgery: A systematic review.

PubMed

Parra-Díaz, P; García-Casares, N

2017-04-19

Given that surgical treatment of refractory mesial temporal lobe epilepsy may cause memory impairment, determining which patients are eligible for surgery is essential. However, there is little agreement on which presurgical memory assessment methods are best able to predict memory outcome after surgery and identify those patients with a greater risk of surgery-induced memory decline. We conducted a systematic literature review to determine which presurgical memory assessment methods best predict memory outcome. The literature search of PubMed gathered articles published between January 2005 and December 2015 addressing pre- and postsurgical memory assessment in mesial temporal lobe epilepsy patients by means of neuropsychological testing, functional MRI, and other neuroimaging techniques. We obtained 178 articles, 31 of which were included in our review. Most of the studies used neuropsychological tests and fMRI; these methods are considered to have the greatest predictive ability for memory impairment. Other less frequently used techniques included the Wada test and FDG-PET. Current evidence supports performing a presurgical assessment of memory function using both neuropsychological tests and functional MRI to predict memory outcome after surgery. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Optimized design and analysis of sparse-sampling FMRI experiments.

PubMed

Perrachione, Tyler K; Ghosh, Satrajit S

2013-01-01

Sparse-sampling is an important methodological advance in functional magnetic resonance imaging (fMRI), in which silent delays are introduced between MR volume acquisitions, allowing for the presentation of auditory stimuli without contamination by acoustic scanner noise and for overt vocal responses without motion-induced artifacts in the functional time series. As such, the sparse-sampling technique has become a mainstay of principled fMRI research into the cognitive and systems neuroscience of speech, language, hearing, and music. Despite being in use for over a decade, there has been little systematic investigation of the acquisition parameters, experimental design considerations, and statistical analysis approaches that bear on the results and interpretation of sparse-sampling fMRI experiments. In this report, we examined how design and analysis choices related to the duration of repetition time (TR) delay (an acquisition parameter), stimulation rate (an experimental design parameter), and model basis function (an analysis parameter) act independently and interactively to affect the neural activation profiles observed in fMRI. First, we conducted a series of computational simulations to explore the parameter space of sparse design and analysis with respect to these variables; second, we validated the results of these simulations in a series of sparse-sampling fMRI experiments. Overall, these experiments suggest the employment of three methodological approaches that can, in many situations, substantially improve the detection of neurophysiological response in sparse fMRI: (1) Sparse analyses should utilize a physiologically informed model that incorporates hemodynamic response convolution to reduce model error. (2) The design of sparse fMRI experiments should maintain a high rate of stimulus presentation to maximize effect size. (3) TR delays of short to intermediate length can be used between acquisitions of sparse-sampled functional image volumes to increase the number of samples and improve statistical power.

Similarity-Based Fusion of MEG and fMRI Reveals Spatio-Temporal Dynamics in Human Cortex During Visual Object Recognition

PubMed Central

Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2016-01-01

Every human cognitive function, such as visual object recognition, is realized in a complex spatio-temporal activity pattern in the brain. Current brain imaging techniques in isolation cannot resolve the brain's spatio-temporal dynamics, because they provide either high spatial or temporal resolution but not both. To overcome this limitation, we developed an integration approach that uses representational similarities to combine measurements of magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) to yield a spatially and temporally integrated characterization of neuronal activation. Applying this approach to 2 independent MEG–fMRI data sets, we observed that neural activity first emerged in the occipital pole at 50–80 ms, before spreading rapidly and progressively in the anterior direction along the ventral and dorsal visual streams. Further region-of-interest analyses established that dorsal and ventral regions showed MEG–fMRI correspondence in representations later than early visual cortex. Together, these results provide a novel and comprehensive, spatio-temporally resolved view of the rapid neural dynamics during the first few hundred milliseconds of object vision. They further demonstrate the feasibility of spatially unbiased representational similarity-based fusion of MEG and fMRI, promising new insights into how the brain computes complex cognitive functions. PMID:27235099

A wavelet-based statistical analysis of FMRI data: I. motivation and data distribution modeling.

PubMed

Dinov, Ivo D; Boscardin, John W; Mega, Michael S; Sowell, Elizabeth L; Toga, Arthur W

2005-01-01

We propose a new method for statistical analysis of functional magnetic resonance imaging (fMRI) data. The discrete wavelet transformation is employed as a tool for efficient and robust signal representation. We use structural magnetic resonance imaging (MRI) and fMRI to empirically estimate the distribution of the wavelet coefficients of the data both across individuals and spatial locations. An anatomical subvolume probabilistic atlas is used to tessellate the structural and functional signals into smaller regions each of which is processed separately. A frequency-adaptive wavelet shrinkage scheme is employed to obtain essentially optimal estimations of the signals in the wavelet space. The empirical distributions of the signals on all the regions are computed in a compressed wavelet space. These are modeled by heavy-tail distributions because their histograms exhibit slower tail decay than the Gaussian. We discovered that the Cauchy, Bessel K Forms, and Pareto distributions provide the most accurate asymptotic models for the distribution of the wavelet coefficients of the data. Finally, we propose a new model for statistical analysis of functional MRI data using this atlas-based wavelet space representation. In the second part of our investigation, we will apply this technique to analyze a large fMRI dataset involving repeated presentation of sensory-motor response stimuli in young, elderly, and demented subjects.

Biocytin-Derived MRI Contrast Agent for Longitudinal Brain Connectivity Studies

PubMed Central

2011-01-01

To investigate the connectivity of brain networks noninvasively and dynamically, we have developed a new strategy to functionalize neuronal tracers and designed a biocompatible probe that can be visualized in vivo using magnetic resonance imaging (MRI). Furthermore, the multimodal design used allows combined ex vivo studies with microscopic spatial resolution by conventional histochemical techniques. We present data on the functionalization of biocytin, a well-known neuronal tract tracer, and demonstrate the validity of the approach by showing brain networks of cortical connectivity in live rats under MRI, together with the corresponding microscopic details, such as fibers and neuronal morphology under light microscopy. We further demonstrate that the developed molecule is the first MRI-visible probe to preferentially trace retrograde connections. Our study offers a new platform for the development of multimodal molecular imaging tools of broad interest in neuroscience, that capture in vivo the dynamics of large scale neural networks together with their microscopic characteristics, thereby spanning several organizational levels. PMID:22860157

Longitudinal 2-point dixon muscle magnetic resonance imaging in becker muscular dystrophy.

PubMed

Bonati, Ulrike; Schmid, Maurice; Hafner, Patricia; Haas, Tanja; Bieri, Oliver; Gloor, Monika; Fischmann, Arne; Fischer, Dirk

2015-06-01

Quantitative MRI techniques detect disease progression in myopathies more sensitively than muscle function measures or conventional MRI. To date, only conventional MRI data using visual rating scales are available for measurement of disease progression in Becker muscular dystrophy (BMD). In 3 patients with BMD (mean age 36.8 years), the mean fat fraction (MFF) of the thigh muscles was assessed by MRI at baseline and at 1-year follow-up using a 2-point Dixon approach (2PD). The motor function measurement scale (MFM) was used for clinical assessment. The mean MFF of all muscles at baseline was 61.6% (SD 7.6). It increased by 3.7% to 65.3% (SD 4.7) at follow-up. The severity of muscle involvement varied between various muscle groups. As in other myopathies, 2PD can quantify fatty muscle degeneration in BMD and can detect disease progression in a small sample size and at relatively short imaging intervals. © 2015 Wiley Periodicals, Inc.

CT, MRI and PET imaging in peritoneal malignancy

PubMed Central

Sahdev, Anju; Reznek, Rodney H.

2011-01-01

Abstract Imaging plays a vital role in the evaluation of patients with suspected or proven peritoneal malignancy. Nevertheless, despite significant advances in imaging technology and protocols, assessment of peritoneal pathology remains challenging. The combination of complex peritoneal anatomy, an extensive surface area that may host tumour deposits and the considerable overlap of imaging appearances of various peritoneal diseases often makes interpretation difficult. Contrast-enhanced multidetector computed tomography (MDCT) remains the most versatile tool in the imaging of peritoneal malignancy. However, conventional and emerging magnetic resonance imaging (MRI) and positron emission tomography (PET)/CT techniques offer significant advantages over MDCT in detection and surveillance. This article reviews established and new techniques in CT, MRI and PET imaging in both primary and secondary peritoneal malignancies and provides an overview of peritoneal anatomy, function and modes of disease dissemination with illustration of common sites and imaging features of peritoneal malignancy. PMID:21865109

Deep brain stimulation with a pre-existing cochlear implant: Surgical technique and outcome.

PubMed

Eddelman, Daniel; Wewel, Joshua; Wiet, R Mark; Metman, Leo V; Sani, Sepehr

2017-01-01

Patients with previously implanted cranial devices pose a special challenge in deep brain stimulation (DBS) surgery. We report the implantation of bilateral DBS leads in a patient with a cochlear implant. Technical nuances and long-term interdevice functionality are presented. A 70-year-old patient with advancing Parkinson's disease and a previously placed cochlear implant for sensorineural hearing loss was referred for placement of bilateral DBS in the subthalamic nucleus (STN). Prior to DBS, the patient underwent surgical removal of the subgaleal cochlear magnet, followed by stereotactic MRI, frame placement, stereotactic computed tomography (CT), and merging of imaging studies. This technique allowed for successful computational merging, MRI-guided targeting, and lead implantation with acceptable accuracy. Formal testing and programming of both the devices were successful without electrical interference. Successful DBS implantation with high resolution MRI-guided targeting is technically feasible in patients with previously implanted cochlear implants by following proper precautions.

Characterization of the resting-state brain network topology in the 6-hydroxydopamine rat model of Parkinson’s disease

PubMed Central

Simmons, Camilla; Mesquita, Michel B.; Wood, Tobias C.; Williams, Steve C. R.; Vernon, Anthony C.; Cash, Diana

2017-01-01

Resting-state functional MRI (rsfMRI) is an imaging technology that has recently gained attention for its ability to detect disruptions in functional brain networks in humans, including in patients with Parkinson’s disease (PD), revealing early and widespread brain network abnormalities. This methodology is now readily applicable to experimental animals offering new possibilities for cross-species translational imaging. In this context, we herein describe the application of rsfMRI to the unilaterally-lesioned 6-hydroxydopamine (6-OHDA) rat, a robust experimental model of the dopamine depletion implicated in PD. Using graph theory to analyse the rsfMRI data, we were able to provide meaningful and translatable measures of integrity, influence and segregation of the underlying functional brain architecture. Specifically, we confirm that rats share a similar functional brain network topology as observed in humans, characterised by small-worldness and modularity. Interestingly, we observed significantly reduced functional connectivity in the 6-OHDA rats, primarily in the ipsilateral (lesioned) hemisphere as evidenced by significantly lower node degree, local efficiency and clustering coefficient in the motor, orbital and sensorimotor cortices. In contrast, we found significantly, and bilaterally, increased thalamic functional connectivity in the lesioned rats. The unilateral deficits in the cortex are consistent with the unilateral nature of this model and further support the validity of the rsfMRI technique in rodents. We thereby provide a methodological framework for the investigation of brain networks in other rodent experimental models of PD, as well as of animal models in general, for cross-comparison with human data. PMID:28249008

SU-D-207A-04: Use of Gradient Echo Plural Contrast Imaging (GEPCI) in MR-Guided Radiation Therapy: A Feasibility Study Targeting Brain Treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai, B; Rao, Y; Tsien, C

Purpose: To implement the Gradient Echo Plural Contrast Imaging(GEPCI) technique in MRI-simulation for radiation therapy and assess the feasibility of using GEPCI images with advanced inhomogeneity correction in MRI-guided radiotherapy for brain treatment. Methods: An optimized multigradient-echo GRE sequence (TR=50ms;TE1=4ms;delta-TE=4ms;flip angle=300,11 Echoes) was developed to generate both structural (T1w and T2*w) and functional MRIs (field and susceptibility maps) from a single acquisition. One healthy subject (Subject1) and one post-surgical brain cancer patient (Subject2) were scanned on a Philips Ingenia 1.5T MRI used for radiation therapy simulation. Another healthy subject (Subject3) was scanned on a 0.35T MRI-guided radiotherapy (MR-IGRT) system (ViewRay).more » A voxel spread function (VSF) was used to correct the B0 inhomogeneities caused by surgical cavities and edema for Subject2. GEPCI images and standard radiotherapy planning MRIs for this patient were compared focusing the delineation of radiotherapy target region. Results: GEPCI brain images were successfully derived from all three subjects with scan times of <7 minutes. The images derived for Subjects1&2 demonstrated that GEPCI can be applied and combined into radiotherapy MRI simulation. Despite low field, T1-weighted and R2* images were successfully reconstructed for Subject3 and were satisfactory for contour and target delineation. The R2* distribution of grey matter (center=12,FWHM=4.5) and white matter (center=14.6, FWHM=2) demonstrated the feasibility for tissue segmentation and quantification. The voxel spread function(VSF) corrected surgical site related inhomogeneities for Subject2. R2* and quantitative susceptibility map(QSM) images for Subject2 can be used to quantitatively assess the brain structure response to radiation over the treatment course. Conclusion: We implemented the GEPCI technique in MRI-simulation and in MR-IGRT system for radiation therapy. The images demonstrated that it is feasible to adopt this technique in radiotherapy for structural delineation. The preliminary data also enable the opportunity for quantitative assessment of radiation response of the target region and normal tissue.« less

What is feasible with imaging human brain function and connectivity using functional magnetic resonance imaging

PubMed Central

2016-01-01

When we consider all of the methods we employ to detect brain function, from electrophysiology to optical techniques to functional magnetic resonance imaging (fMRI), we do not really have a ‘golden technique’ that meets all of the needs for studying the brain. We have methods, each of which has significant limitations but provide often complimentary information. Clearly, there are many questions that need to be answered about fMRI, which unlike other methods, allows us to study the human brain. However, there are also extraordinary accomplishments or demonstration of the feasibility of reaching new and previously unexpected scales of function in the human brain. This article reviews some of the work we have pursued, often with extensive collaborations with other co-workers, towards understanding the underlying mechanisms of the methodology, defining its limitations, and developing solutions to advance it. No doubt, our knowledge of human brain function has vastly expanded since the introduction of fMRI. However, methods and instrumentation in this dynamic field have evolved to a state that discoveries about the human brain based on fMRI principles, together with information garnered at a much finer spatial and temporal scale through other methods, are poised to significantly accelerate in the next decade. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574313

Functional connectivity density mapping: comparing multiband and conventional EPI protocols.

PubMed

Cohen, Alexander D; Tomasi, Dardo; Shokri-Kojori, Ehsan; Nencka, Andrew S; Wang, Yang

2018-06-01

Functional connectivity density mapping (FCDM) is a newly developed data-driven technique that quantifies the number of local and global functional connections for each voxel in the brain. In this study, we evaluated reproducibility, sensitivity, and specificity of both local functional connectivity density (lFCD) and global functional connectivity density (gFCD). We compared these metrics using the human connectome project (HCP) compatible high-resolution (2 mm isotropic, TR = 0.8 s) multiband (MB), and more typical, lower resolution (3.5 mm isotropic, TR = 2.0 s) single-band (SB) resting state functional MRI (rs-fMRI) acquisitions. Furthermore, in order to be more clinically feasible, only rs-fMRI scans that lasted seven minutes were tested. Subjects were scanned twice within a two-week span. We found sensitivity and specificity increased and reproducibility either increased or did not change for the MB compared to the SB acquisitions. The MB scans also showed improved gray matter/white matter contrast compared to the SB scans. The lFCD and gFCD patterns were similar across MB and SB scans and confined predominantly to gray matter. We also observed a strong spatial correlation of FCD between MB and SB scans indicating the two acquisitions provide similar information. These findings indicate high-resolution MB acquisitions improve the quality of FCD data, and seven minute rs-fMRI scan can provide robust FCD measurements.

The Aging Lung: Clinical and Imaging Findings and the Fringe of Physiological State.

PubMed

Schröder, T H; Storbeck, B; Rabe, K F; Weber, C

2015-06-01

Since aspects of demographic transition have become an essential part of socioeconomic, medical and health-care research in the last decades, it is vital for the radiologist to discriminate between normal ageing related effects and abnormal imaging findings in the elderly. This article reviews functional and structural aspects of the ageing lung and focuses on typical ageing related radiological patterns. • The physiological aging process of the thoracic organs shows typical structural and functional aspects.• Mild interstitial fibrosis and focal parenchymal abnormalities like septal thickening can be diagnosed frequently - whereas a clinical correlate is often lacking.• With increasing patient age, the influence by various intrinsic and extrinsic factors (including comorbidities of the patient, and drug inhalation toxicants) also increases.• A growing spectrum of imaging techniques (including functional cardiopulmonary MRI, MRI spectroscopy, hybrid-techniques) is confronted by rare empiric data in the very old people (aging 80 years and older). © Georg Thieme Verlag KG Stuttgart · New York.

Hybrid imaging in foot and ankle disorders.

PubMed

García Jiménez, R; García-Gómez, F J; Noriega Álvarez, E; Calvo Morón, C; Martín-Marcuartu, J J

Disorders of the foot and ankle are some of the most frequent ones affecting the musculoskeletal system and have a great impact on patients' quality of life. Accurate diagnosis is an important clinical challenge because of the complex anatomy and function of the foot, that make it difficult to locate the source of the pain by routine clinical examination. In the study of foot pathology, anatomical imaging (radiography, magnetic resonance imaging [MRI], ultrasound and computed tomography [CT]) and functional imaging (bone scan, positron emission tomography [PET] and MRI) techniques have been used. Hybrid imaging combines the advantages of morphological and functional studies in a synergistic way, helping the clinician manage complex problems. In this article we delve into the anatomy and biomechanics of the foot and ankle and describe the potential indications for the current hybrid techniques available for the study of foot and ankle disease. Copyright © 2017 Elsevier España, S.L.U. y SEMNIM. All rights reserved.

Canonical Correlation Analysis for Feature-Based Fusion of Biomedical Imaging Modalities and Its Application to Detection of Associative Networks in Schizophrenia.

PubMed

Correa, Nicolle M; Li, Yi-Ou; Adalı, Tülay; Calhoun, Vince D

2008-12-01

Typically data acquired through imaging techniques such as functional magnetic resonance imaging (fMRI), structural MRI (sMRI), and electroencephalography (EEG) are analyzed separately. However, fusing information from such complementary modalities promises to provide additional insight into connectivity across brain networks and changes due to disease. We propose a data fusion scheme at the feature level using canonical correlation analysis (CCA) to determine inter-subject covariations across modalities. As we show both with simulation results and application to real data, multimodal CCA (mCCA) proves to be a flexible and powerful method for discovering associations among various data types. We demonstrate the versatility of the method with application to two datasets, an fMRI and EEG, and an fMRI and sMRI dataset, both collected from patients diagnosed with schizophrenia and healthy controls. CCA results for fMRI and EEG data collected for an auditory oddball task reveal associations of the temporal and motor areas with the N2 and P3 peaks. For the application to fMRI and sMRI data collected for an auditory sensorimotor task, CCA results show an interesting joint relationship between fMRI and gray matter, with patients with schizophrenia showing more functional activity in motor areas and less activity in temporal areas associated with less gray matter as compared to healthy controls. Additionally, we compare our scheme with an independent component analysis based fusion method, joint-ICA that has proven useful for such a study and note that the two methods provide complementary perspectives on data fusion.

Hemispheric asymmetries in dorsal language pathway white-matter tracts: A magnetic resonance imaging tractography and functional magnetic resonance imaging study.

PubMed

Silva, Guilherme; Citterio, Alberto

2017-10-01

Introduction Previous studies have shown that the arcuate fasciculus has a leftward asymmetry in right-handers that could be correlated with the language lateralisation defined by functional magnetic resonance imaging. Nonetheless, information about the asymmetry of the other fibres that constitute the dorsal language pathway is scarce. Objectives This study investigated the asymmetry of the white-matter tracts involved in the dorsal language pathway through the diffusion tensor imaging (DTI) technique, in relation to language hemispheric dominance determined by task-dependent functional magnetic resonance imaging (fMRI). Methods We selected 11 patients (10 right-handed) who had been studied with task-dependent fMRI for language areas and DTI and who had no language impairment or structural abnormalities that could compromise magnetic resonance tractography of the fibres involved in the dorsal language pathway. Laterality indices (LI) for fMRI and for the volumes of each tract were calculated. Results In fMRI, all the right-handers had left hemispheric lateralisation, and the ambidextrous subject presented right hemispheric dominance. The arcuate fasciculus LI was strongly correlated with fMRI LI ( r = 0.739, p = 0.009), presenting the same lateralisation of fMRI in seven subjects (including the right hemispheric dominant). It was not asymmetric in three cases and had opposite lateralisation in one case. The other tracts presented predominance for rightward lateralisation, especially superior longitudinal fasciculus (SLF) II/III (nine subjects), but their LI did not correlate (directly or inversely) with fMRI LI. Conclusion The fibres that constitute the dorsal language pathway have an asymmetric distribution in the cerebral hemispheres. Only the asymmetry of the arcuate fasciculus is correlated with fMRI language lateralisation.

Method for multimodal analysis of independent source differences in schizophrenia: combining gray matter structural and auditory oddball functional data.

PubMed

Calhoun, V D; Adali, T; Giuliani, N R; Pekar, J J; Kiehl, K A; Pearlson, G D

2006-01-01

The acquisition of both structural MRI (sMRI) and functional MRI (fMRI) data for a given study is a very common practice. However, these data are typically examined in separate analyses, rather than in a combined model. We propose a novel methodology to perform independent component analysis across image modalities, specifically, gray matter images and fMRI activation images as well as a joint histogram visualization technique. Joint independent component analysis (jICA) is used to decompose a matrix with a given row consisting of an fMRI activation image resulting from auditory oddball target stimuli and an sMRI gray matter segmentation image, collected from the same individual. We analyzed data collected on a group of schizophrenia patients and healthy controls using the jICA approach. Spatially independent joint-components are estimated and resulting components were further analyzed only if they showed a significant difference between patients and controls. The main finding was that group differences in bilateral parietal and frontal as well as posterior temporal regions in gray matter were associated with bilateral temporal regions activated by the auditory oddball target stimuli. A finding of less patient gray matter and less hemodynamic activity for target detection in these bilateral anterior temporal lobe regions was consistent with previous work. An unexpected corollary to this finding was that, in the regions showing the largest group differences, gray matter concentrations were larger in patients vs. controls, suggesting that more gray matter may be related to less functional connectivity in the auditory oddball fMRI task. Hum Brain Mapp, 2005. (c) 2005 Wiley-Liss, Inc.

Design of Multishell Sampling Schemes with Uniform Coverage in Diffusion MRI

PubMed Central

Caruyer, Emmanuel; Lenglet, Christophe; Sapiro, Guillermo; Deriche, Rachid

2017-01-01

Purpose In diffusion MRI, a technique known as diffusion spectrum imaging reconstructs the propagator with a discrete Fourier transform, from a Cartesian sampling of the diffusion signal. Alternatively, it is possible to directly reconstruct the orientation distribution function in q-ball imaging, providing so-called high angular resolution diffusion imaging. In between these two techniques, acquisitions on several spheres in q-space offer an interesting trade-off between the angular resolution and the radial information gathered in diffusion MRI. A careful design is central in the success of multishell acquisition and reconstruction techniques. Methods The design of acquisition in multishell is still an open and active field of research, however. In this work, we provide a general method to design multishell acquisition with uniform angular coverage. This method is based on a generalization of electrostatic repulsion to multishell. Results We evaluate the impact of our method using simulations, on the angular resolution in one and two bundles of fiber configurations. Compared to more commonly used radial sampling, we show that our method improves the angular resolution, as well as fiber crossing discrimination. Discussion We propose a novel method to design sampling schemes with optimal angular coverage and show the positive impact on angular resolution in diffusion MRI. PMID:23625329

Real-time myocardium segmentation for the assessment of cardiac function variation

NASA Astrophysics Data System (ADS)

Zoehrer, Fabian; Huellebrand, Markus; Chitiboi, Teodora; Oechtering, Thekla; Sieren, Malte; Frahm, Jens; Hahn, Horst K.; Hennemuth, Anja

2017-03-01

Recent developments in MRI enable the acquisition of image sequences with high spatio-temporal resolution. Cardiac motion can be captured without gating and triggering. Image size and contrast relations differ from conventional cardiac MRI cine sequences requiring new adapted analysis methods. We suggest a novel segmentation approach utilizing contrast invariant polar scanning techniques. It has been tested with 20 datasets of arrhythmia patients. The results do not differ significantly more between automatic and manual segmentations than between observers. This indicates that the presented solution could enable clinical applications of real-time MRI for the examination of arrhythmic cardiac motion in the future.

The potential role of MRI in veterinary clinical cardiology.

PubMed

Gilbert, Stephen H; McConnell, Fraser J; Holden, Arun V; Sivananthan, Mohan U; Dukes-McEwan, Joanna

2010-02-01

Over the last decade, magnetic resonance imaging (MRI) has become established as a useful referral diagnostic method in veterinary medicine that is widely used in small animal brain and spinal diseases, aural, nasal and orbital disorders, planning soft tissue surgery, oncology and small animal and equine orthopaedics. The use of MRI in these disciplines has grown due to its unparalleled capability to image soft tissue structures. This has been exploited in human cardiology where, despite the inherent difficulties in imaging a moving, contractile structure, cardiac MRI (CMRI) has become the optimal technique for the morphological assessment and quantification of ventricular function. Both CMRI hardware and software systems have developed rapidly in the last 10 years but although several preliminary veterinary CMRI studies have been reported, the technique's growth has been limited and is currently used primarily in clinical research. A review of published studies is presented with a description of CMRI technology and the potential of CMRI is discussed along with some of the reasons for its limited usage. Copyright (c) 2008 Elsevier Ltd. All rights reserved.

Passive Ventricular Mechanics Modelling Using MRI of Structure and Function

PubMed Central

Wang, V.Y.; Lam, H.I.; Ennis, D.B.; Young, A.A.; Nash, M.P.

2009-01-01

Patients suffering from dilated cardiomyopathy or myocardial infarction can develop left ventricular (LV) diastolic impairment. The LV remodels its structure and function to adapt to pathophysiological changes in geometry and loading conditions and this remodeling process can alter the passive ventricular mechanics. In order to better understand passive ventricular mechanics, a LV finite element model was developed to incorporate physiological and mechanical information derived from in vivo magnetic resonance imaging (MRI) tissue tagging, in vivo LV cavity pressure recording and ex vivo diffusion tensor MRI (DTMRI) of a canine heart. MRI tissue tagging enables quantitative evaluation of cardiac mechanical function with high spatial and temporal resolution, whilst the direction of maximum water diffusion (the primary eigenvector) in each voxel of a DTMRI directly correlates with the myocardial fibre orientation. This model was customized to the geometry of the canine LV during diastasis by fitting the segmented epicardial and endocardial surface data from tagged MRI using nonlinear finite element fitting techniques. Myofibre orientations, extracted from DTMRI of the same heart, were incorporated into this geometric model using a free form deformation methodology. Pressure recordings, temporally synchronized to the tissue tagging MRI data, were used to simulate the LV deformation during diastole. Simulation of the diastolic LV mechanics allowed us to estimate the stiffness of the passive LV myocardium based on kinematic data obtained from tagged MRI. This integrated physiological model will allow more insight into the regional passive diastolic mechanics of the LV on an individualized basis, thereby improving our understanding of the underlying structural basis of mechanical dysfunction in pathological conditions. PMID:18982680

A receptor-based model for dopamine-induced fMRI signal

PubMed Central

Mandeville, Joseph. B.; Sander, Christin Y. M.; Jenkins, Bruce G.; Hooker, Jacob M.; Catana, Ciprian; Vanduffel, Wim; Alpert, Nathaniel M.; Rosen, Bruce R.; Normandin, Marc D.

2013-01-01

This report describes a multi-receptor physiological model of the fMRI temporal response and signal magnitude evoked by drugs that elevate synaptic dopamine in basal ganglia. The model is formulated as a summation of dopamine’s effects at D1-like and D2-like receptor families, which produce functional excitation and inhibition, respectively, as measured by molecular indicators like adenylate cyclase or neuroimaging techniques like fMRI. Functional effects within the model are described in terms of relative changes in receptor occupancies scaled by receptor densities and neuro-vascular coupling constants. Using literature parameters, the model reconciles many discrepant observations and interpretations of pre-clinical data. Additionally, we present data showing that amphetamine stimulation produces fMRI inhibition at low doses and a biphasic response at higher doses in the basal ganglia of non-human primates (NHP), in agreement with model predictions based upon the respective levels of evoked dopamine. Because information about dopamine release is required to inform the fMRI model, we simultaneously acquired PET 11C-raclopride data in several studies to evaluate the relationship between raclopride displacement and assumptions about dopamine release. At high levels of dopamine release, results suggest that refinements of the model will be required to consistently describe the PET and fMRI data. Overall, the remarkable success of the model in describing a wide range of preclinical fMRI data indicate that this approach will be useful for guiding the design and analysis of basic science and clinical investigations and for interpreting the functional consequences of dopaminergic stimulation in normal subjects and in populations with dopaminergic neuroadaptations. PMID:23466936

Visual assessment of brain magnetic resonance imaging detects injury to cognitive regulatory sites in patients with heart failure.

PubMed

Pan, Alan; Kumar, Rajesh; Macey, Paul M; Fonarow, Gregg C; Harper, Ronald M; Woo, Mary A

2013-02-01

Heart failure (HF) patients exhibit depression and executive function impairments that contribute to HF mortality. Using specialized magnetic resonance imaging (MRI) analysis procedures, brain changes appear in areas regulating these functions (mammillary bodies, hippocampi, and frontal cortex). However, specialized MRI procedures are not part of standard clinical assessment for HF (which is usually a visual evaluation), and it is unclear whether visual MRI examination can detect changes in these structures. Using brain MRI, we visually examined the mammillary bodies and frontal cortex for global and hippocampi for global and regional tissue changes in 17 HF and 50 control subjects. Significantly global changes emerged in the right mammillary body (HF 1.18 ± 1.13 vs control 0.52 ± 0.74; P = .024), right hippocampus (HF 1.53 ± 0.94 vs control 0.80 ± 0.86; P = .005), and left frontal cortex (HF 1.76 ± 1.03 vs control 1.24 ± 0.77; P = .034). Comparison of the visual method with specialized MRI techniques corroborates right hippocampal and left frontal cortical, but not mammillary body, tissue changes. Visual examination of brain MRI can detect damage in HF in areas regulating depression and executive function, including the right hippocampus and left frontal cortex. Visual MRI assessment in HF may facilitate evaluation of injury to these structures and the assessment of the impact of potential treatments for this damage. Copyright © 2013 Elsevier Inc. All rights reserved.

Passive ventricular mechanics modelling using MRI of structure and function.

PubMed

Wang, V Y; Lam, H I; Ennis, D B; Young, A A; Nash, M P

2008-01-01

Patients suffering from dilated cardiomyopathy or myocardial infarction can develop left ventricular (LV) diastolic impairment. The LV remodels its structure and function to adapt to pathophysiological changes in geometry and loading conditions and this remodeling process can alter the passive ventricular mechanics. In order to better understand passive ventricular mechanics, a LV finite element model was developed to incorporate physiological and mechanical information derived from in vivo magnetic resonance imaging (MRI) tissue tagging, in vivo LV cavity pressure recording and ex vivo diffusion tensor MRI (DTMRI) of a canine heart. MRI tissue tagging enables quantitative evaluation of cardiac mechanical function with high spatial and temporal resolution, whilst the direction of maximum water diffusion (the primary eigenvector) in each voxel of a DTMRI directly correlates with the myocardial fibre orientation. This model was customized to the geometry of the canine LV during diastasis by fitting the segmented epicardial and endocardial surface data from tagged MRI using nonlinear finite element fitting techniques. Myofibre orientations, extracted from DTMRI of the same heart, were incorporated into this geometric model using a free form deformation methodology. Pressure recordings, temporally synchronized to the tissue tagging MRI data, were used to simulate the LV deformation during diastole. Simulation of the diastolic LV mechanics allowed us to estimate the stiffness of the passive LV myocardium based on kinematic data obtained from tagged MRI. This integrated physiological model will allow more insight into the regional passive diastolic mechanics of the LV on an individualized basis, thereby improving our understanding of the underlying structural basis of mechanical dysfunction in pathological conditions.

Noninvasive studies of human visual cortex using neuromagnetic techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aine, C.J.; George, J.S.; Supek, S.

1990-01-01

The major goals of noninvasive studies of the human visual cortex are: to increase knowledge of the functional organization of cortical visual pathways; and to develop noninvasive clinical tests for the assessment of cortical function. Noninvasive techniques suitable for studies of the structure and function of human visual cortex include magnetic resonance imaging (MRI), positron emission tomography (PET), single photon emission tomography (SPECT), scalp recorded event-related potentials (ERPs), and event-related magnetic fields (ERFs). The primary challenge faced by noninvasive functional measures is to optimize the spatial and temporal resolution of the measurement and analytic techniques in order to effectively characterizemore » the spatial and temporal variations in patterns of neuronal activity. In this paper we review the use of neuromagnetic techniques for this purpose. 8 refs., 3 figs.« less

Family-Based Training Program Improves Brain Function, Cognition, and Behavior in Lower Socioeconomic Status Preschoolers

ERIC Educational Resources Information Center

Pakulak, Eric; Stevens, Courtney; Bell, Theodore A.; Fanning, Jessica; Klein, Scott; Isbell, Elif; Neville, Helen

2013-01-01

Over the course of several years of research, the authors have employed psychophysics, electrophysiological (ERP) and magnetic resonance imaging (MRI) techniques to study the development and neuroplasticity of the human brain. During this time, they observed that different brain systems and related functions display markedly different degrees or…

Rapid and minimum invasive functional brain mapping by real-time visualization of high gamma activity during awake craniotomy.

PubMed

Ogawa, Hiroshi; Kamada, Kyousuke; Kapeller, Christoph; Hiroshima, Satoru; Prueckl, Robert; Guger, Christoph

2014-11-01

Electrocortical stimulation (ECS) is the gold standard for functional brain mapping during an awake craniotomy. The critical issue is to set aside enough time to identify eloquent cortices by ECS. High gamma activity (HGA) ranging between 80 and 120 Hz on electrocorticogram is assumed to reflect localized cortical processing. In this report, we used real-time HGA mapping and functional neuronavigation integrated with functional magnetic resonance imaging (fMRI) for rapid and reliable identification of motor and language functions. Four patients with intra-axial tumors in their dominant hemisphere underwent preoperative fMRI and lesion resection with an awake craniotomy. All patients showed significant fMRI activation evoked by motor and language tasks. During the craniotomy, we recorded electrocorticogram activity by placing subdural grids directly on the exposed brain surface. Each patient performed motor and language tasks and demonstrated real-time HGA dynamics in hand motor areas and parts of the inferior frontal gyrus. Sensitivity and specificity of HGA mapping were 100% compared with ECS mapping in the frontal lobe, which suggested HGA mapping precisely indicated eloquent cortices. We found different HGA dynamics of language tasks in frontal and temporal regions. Specificities of the motor and language-fMRI did not reach 85%. The results of HGA mapping was mostly consistent with those of ECS mapping, although fMRI tended to overestimate functional areas. This novel technique enables rapid and accurate identification of motor and frontal language areas. Furthermore, real-time HGA mapping sheds light on underlying physiological mechanisms related to human brain functions. Copyright © 2014 Elsevier Inc. All rights reserved.

Clustered functional MRI of overt speech production.

PubMed

Sörös, Peter; Sokoloff, Lisa Guttman; Bose, Arpita; McIntosh, Anthony R; Graham, Simon J; Stuss, Donald T

2006-08-01

To investigate the neural network of overt speech production, event-related fMRI was performed in 9 young healthy adult volunteers. A clustered image acquisition technique was chosen to minimize speech-related movement artifacts. Functional images were acquired during the production of oral movements and of speech of increasing complexity (isolated vowel as well as monosyllabic and trisyllabic utterances). This imaging technique and behavioral task enabled depiction of the articulo-phonologic network of speech production from the supplementary motor area at the cranial end to the red nucleus at the caudal end. Speaking a single vowel and performing simple oral movements involved very similar activation of the cortical and subcortical motor systems. More complex, polysyllabic utterances were associated with additional activation in the bilateral cerebellum, reflecting increased demand on speech motor control, and additional activation in the bilateral temporal cortex, reflecting the stronger involvement of phonologic processing.

Enhanced control of dorsolateral prefrontal cortex neurophysiology with real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback training and working memory practice.

PubMed

Sherwood, Matthew S; Kane, Jessica H; Weisend, Michael P; Parker, Jason G

2016-01-01

Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback can be used to train localized, conscious regulation of blood oxygen level-dependent (BOLD) signals. As a therapeutic technique, rt-fMRI neurofeedback reduces the symptoms of a variety of neurologic disorders. To date, few studies have investigated the use of self-regulation training using rt-fMRI neurofeedback to enhance cognitive performance. This work investigates the utility of rt-fMRI neurofeedback as a tool to enhance human cognition by training healthy individuals to consciously control activity in the left dorsolateral prefrontal cortex (DLPFC). A cohort of 18 healthy participants in the experimental group underwent rt-fMRI neurofeedback from the left DLPFC in five training sessions across two weeks while 7 participants in the control group underwent similar training outside the MRI and without rt-fMRI neurofeedback. Working memory (WM) performance was evaluated on two testing days separated by the five rt-fMRI neurofeedback sessions using two computerized tests. We investigated the ability to control the BOLD signal across training sessions and WM performance across the two testing days. The group with rt-fMRI neurofeedback demonstrated a significant increase in the ability to self-regulate the BOLD signal in the left DLPFC across sessions. WM performance showed differential improvement between testing days one and two across the groups with the highest increases observed in the rt-fMRI neurofeedback group. These results provide evidence that individuals can quickly gain the ability to consciously control the left DLPFC, and this training results in improvements of WM performance beyond that of training alone. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Multimodal integration of fMRI and EEG data for high spatial and temporal resolution analysis of brain networks

PubMed Central

Mantini, D.; Marzetti, L.; Corbetta, M.; Romani, G.L.; Del Gratta, C.

2017-01-01

Two major non-invasive brain mapping techniques, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have complementary advantages with regard to their spatial and temporal resolution. We propose an approach based on the integration of EEG and fMRI, enabling the EEG temporal dynamics of information processing to be characterized within spatially well-defined fMRI large-scale networks. First, the fMRI data are decomposed into networks by means of spatial independent component analysis (sICA), and those associated with intrinsic activity and/or responding to task performance are selected using information from the related time-courses. Next, the EEG data over all sensors are averaged with respect to event timing, thus calculating event-related potentials (ERPs). The ERPs are subjected to temporal ICA (tICA), and the resulting components are localized with the weighted minimum norm (WMNLS) algorithm using the task-related fMRI networks as priors. Finally, the temporal contribution of each ERP component in the areas belonging to the fMRI large-scale networks is estimated. The proposed approach has been evaluated on visual target detection data. Our results confirm that two different components, commonly observed in EEG when presenting novel and salient stimuli respectively, are related to the neuronal activation in large-scale networks, operating at different latencies and associated with different functional processes. PMID:20052528

MRI-based methods for quantification of the cerebral metabolic rate of oxygen

PubMed Central

Rodgers, Zachary B; Detre, John A

2016-01-01

The brain depends almost entirely on oxidative metabolism to meet its significant energy requirements. As such, the cerebral metabolic rate of oxygen (CMRO2) represents a key measure of brain function. Quantification of CMRO2 has helped elucidate brain functional physiology and holds potential as a clinical tool for evaluating neurological disorders including stroke, brain tumors, Alzheimer’s disease, and obstructive sleep apnea. In recent years, a variety of magnetic resonance imaging (MRI)-based CMRO2 quantification methods have emerged. Unlike positron emission tomography – the current “gold standard” for measurement and mapping of CMRO2 – MRI is non-invasive, relatively inexpensive, and ubiquitously available in modern medical centers. All MRI-based CMRO2 methods are based on modeling the effect of paramagnetic deoxyhemoglobin on the magnetic resonance signal. The various methods can be classified in terms of the MRI contrast mechanism used to quantify CMRO2: T2*, T2′, T2, or magnetic susceptibility. This review article provides an overview of MRI-based CMRO2 quantification techniques. After a brief historical discussion motivating the need for improved CMRO2 methodology, current state-of-the-art MRI-based methods are critically appraised in terms of their respective tradeoffs between spatial resolution, temporal resolution, and robustness, all of critical importance given the spatially heterogeneous and temporally dynamic nature of brain energy requirements. PMID:27089912

Neuroimaging is a novel tool to understand the impact of environmental chemicals on neurodevelopment.

PubMed

Horton, Megan K; Margolis, Amy E; Tang, Cheuk; Wright, Robert

2014-04-01

The prevalence of childhood neurodevelopmental disorders has been increasing over the last several decades. Prenatal and early childhood exposure to environmental toxicants is increasingly recognized as contributing to the growing rate of neurodevelopmental disorders. Very little information is known about the mechanistic processes by which environmental chemicals alter brain development. We review the recent advances in brain imaging modalities and discuss their application in epidemiologic studies of prenatal and early childhood exposure to environmental toxicants. Neuroimaging techniques (volumetric and functional MRI, diffusor tensor imaging, and magnetic resonance spectroscopy) have opened unprecedented access to study the developing human brain. These techniques are noninvasive and free of ionization radiation making them suitable for research applications in children. Using these techniques, we now understand much about structural and functional patterns in the typically developing brain. This knowledge allows us to investigate how prenatal exposure to environmental toxicants may alter the typical developmental trajectory. MRI is a powerful tool that allows in-vivo visualization of brain structure and function. Used in epidemiologic studies of environmental exposure, it offers the promise to causally link exposure with behavioral and cognitive manifestations and ultimately to inform programs to reduce exposure and mitigate adverse effects of exposure.

White-matter functional networks changes in patients with schizophrenia.

PubMed

Jiang, Yuchao; Luo, Cheng; Li, Xuan; Li, Yingjia; Yang, Hang; Li, Jianfu; Chang, Xin; Li, Hechun; Yang, Huanghao; Wang, Jijun; Duan, Mingjun; Yao, Dezhong

2018-04-13

Resting-state functional MRI (rsfMRI) is a useful technique for investigating the functional organization of human gray-matter in neuroscience and neuropsychiatry. Nevertheless, most studies have demonstrated the functional connectivity and/or task-related functional activity in the gray-matter. White-matter functional networks have been investigated in healthy subjects. Schizophrenia has been hypothesized to be a brain disorder involving insufficient or ineffective communication associated with white-matter abnormalities. However, previous studies have mainly examined the structural architecture of white-matter using MRI or diffusion tensor imaging and failed to uncover any dysfunctional connectivity within the white-matter on rsfMRI. The current study used rsfMRI to evaluate white-matter functional connectivity in a large cohort of ninety-seven schizophrenia patients and 126 healthy controls. Ten large-scale white-matter networks were identified by a cluster analysis of voxel-based white-matter functional connectivity and classified into superficial, middle and deep layers of networks. Evaluation of the spontaneous oscillation of white-matter networks and the functional connectivity between them showed that patients with schizophrenia had decreased amplitudes of low-frequency oscillation and increased functional connectivity in the superficial perception-motor networks. Additionally, we examined the interactions between white-matter and gray-matter networks. The superficial perception-motor white-matter network had decreased functional connectivity with the cortical perception-motor gray-matter networks. In contrast, the middle and deep white-matter networks had increased functional connectivity with the superficial perception-motor white-matter network and the cortical perception-motor gray-matter network. Thus, we presumed that the disrupted association between the gray-matter and white-matter networks in the perception-motor system may be compensated for through the middle-deep white-matter networks, which may be the foundation of the extensively disrupted connections in schizophrenia. Copyright © 2018 Elsevier Inc. All rights reserved.

Tracking brain motion during the cardiac cycle using spiral cine-DENSE MRI

PubMed Central

Zhong, Xiaodong; Meyer, Craig H.; Schlesinger, David J.; Sheehan, Jason P.; Epstein, Frederick H.; Larner, James M.; Benedict, Stanley H.; Read, Paul W.; Sheng, Ke; Cai, Jing

2009-01-01

Cardiac-synchronized brain motion is well documented, but the accurate measurement of such motion on the pixel-by-pixel basis has been hampered by the lack of proper imaging technique. In this article, the authors present the implementation of an autotracking spiral cine displacement-encoded stimulation echo (DENSE) magnetic resonance imaging (MRI) technique for the measurement of pulsatile brain motion during the cardiac cycle. Displacement-encoded dynamic MR images of three healthy volunteers were acquired throughout the cardiac cycle using the spiral cine-DENSE pulse sequence gated to the R wave of an electrocardiogram. Pixelwise Lagrangian displacement maps were computed, and 2D displacement as a function of time was determined for selected regions of interests. Different intracranial structures exhibited characteristic motion amplitude, direction, and pattern throughout the cardiac cycle. Time-resolved displacement curves revealed the pathway of pulsatile motion from brain stem to peripheral brain lobes. These preliminary results demonstrated that the spiral cine-DENSE MRI technique can be used to measure cardiac-synchronized pulsatile brain motion on the pixel-by-pixel basis with high temporal∕spatial resolution and sensitivity. PMID:19746774

Magnetic resonance in studies of glaucoma

PubMed Central

Fiedorowicz, Michał; Dyda, Wojciech; Rejdak, Robert; Grieb, Paweł

2011-01-01

Summary Glaucoma is the second leading cause of blindness. It affects retinal ganglion cells and the optic nerve. However, there is emerging evidence that glaucoma also affects other components of the visual pathway and visual cortex. There is a need to employ new methods of in vivo brain evaluation to characterize these changes. Magnetic resonance (MR) techniques are well suited for this purpose. We review data on the MR evaluation of the visual pathway and the use of MR techniques in the study of glaucoma, both in humans and in animal models. These studies demonstrated decreases in optic nerve diameter, localized white matter loss and decrease in visual cortex density. Studies on rats employing manganese-enhanced MRI showed that axonal transport in the optic nerve is affected. Diffusion tensor MRI revealed signs of degeneration of the optic pathway. Functional MRI showed decreased response of the visual cortex after stimulation of the glaucomatous eye. Magnetic resonance spectroscopy demonstrated changes in metabolite levels in the visual cortex in a rat model of glaucoma, although not in glaucoma patients. Further applications of MR techniques in studies of glaucomatous brains are indicated. PMID:21959626

Visualizing the anatomical-functional correlation of the human brain

NASA Astrophysics Data System (ADS)

Chang, YuKuang; Rockwood, Alyn P.; Reiman, Eric M.

1995-04-01

Three-dimensional tomographic images obtained from different modalities or from the same modality at different times provide complementary information. For example, while PET shows brain function, images from MRI identify anatomical structures. In this paper, we investigate the problem of displaying available information about structures and function together. Several steps are described to achieve our goal. These include segmentation of the data, registration, resampling, and display. Segmentation is used to identify brain tissue from surrounding tissues, especially in the MRI data. Registration aligns the different modalities as closely as possible. Resampling arises from the registration since two data sets do not usually correspond and the rendering method is most easily achieved if the data correspond to the same grid used in display. We combine several techniques to display the data. MRI data is reconstructed from 2D slices into 3D structures from which isosurfaces are extracted and represented by approximating polygonalizations. These are then displayed using standard graphics pipelines including shaded and transparent images. PET data measures the qualitative rates of cerebral glucose utilization or oxygen consumption. PET image is best displayed as a volume of luminous particles. The combination of both display methods allows the viewer to compare the functional information contained in the PET data with the anatomically more precise MRI data.

Cardiac Magnetic Resonance Imaging in Ischemic Heart Disease

PubMed Central

Florian, A.; Jurcut, R.; Ginghina, C.; Bogaert, J.

2011-01-01

Cardiac magnetic resonance imaging (MRI) has emerged as a prime player in the clinical and preclinical detection of ischemic heart disease (IHD) as well in the prognosis assessment by offering a comprehensive approach for all spectrums of coronary artery disease (CAD) patients. The aim of this review is to provide the reader a state–of–the art on how the newest cardiac MRI techniques can be used to study IHD patients. In patients with suspected/stable CAD, functional and perfusion imaging both at rest and during vasodilatatory stress (adenosine, dypiridamole)/dobutamine stress can accurately depict ischemic myocardium secondary to significant coronary artery stenosis. In patients with acute MI, MRI is a robust tool for differentiating and sizing the jeopardized and the infarcted myocardium by using a combination of functional, edema, perfusion and Gd contrast imaging. Moreover, important prognostic factors like myocardial salvage, the presence of microvascular obstruction (MVO), post reperfusion myocardial hemorrhage, RV involvement and infarct related complications can be assessed in the same examination. In patients with chronic ischemic cardiomyopathy, the role of the MRI extends from diagnosis by means of Gadolinium contrast scar imaging to therapy and prognosis by functional assessment and viability testing with rest and dobutamine stress imaging. In all the circumstances mentioned, MRI derived information has been proven valuable in every day clinical decision making and prognosis assessment. Thus, MRI is becoming more and more an accepted alternative to other imaging modalities both in the acute and chronic setting. PMID:22514564

Pairwise Classifier Ensemble with Adaptive Sub-Classifiers for fMRI Pattern Analysis.

PubMed

Kim, Eunwoo; Park, HyunWook

2017-02-01

The multi-voxel pattern analysis technique is applied to fMRI data for classification of high-level brain functions using pattern information distributed over multiple voxels. In this paper, we propose a classifier ensemble for multiclass classification in fMRI analysis, exploiting the fact that specific neighboring voxels can contain spatial pattern information. The proposed method converts the multiclass classification to a pairwise classifier ensemble, and each pairwise classifier consists of multiple sub-classifiers using an adaptive feature set for each class-pair. Simulated and real fMRI data were used to verify the proposed method. Intra- and inter-subject analyses were performed to compare the proposed method with several well-known classifiers, including single and ensemble classifiers. The comparison results showed that the proposed method can be generally applied to multiclass classification in both simulations and real fMRI analyses.

Comparison of Dynamic Contrast Enhanced MRI and Quantitative SPECT in a Rat Glioma Model

PubMed Central

Skinner, Jack T.; Yankeelov, Thomas E.; Peterson, Todd E.; Does, Mark D.

2012-01-01

Pharmacokinetic modeling of dynamic contrast enhanced (DCE)-MRI data provides measures of the extracellular volume fraction (ve) and the volume transfer constant (Ktrans) in a given tissue. These parameter estimates may be biased, however, by confounding issues such as contrast agent and tissue water dynamics, or assumptions of vascularization and perfusion made by the commonly used model. In contrast to MRI, radiotracer imaging with SPECT is insensitive to water dynamics. A quantitative dual-isotope SPECT technique was developed to obtain an estimate of ve in a rat glioma model for comparison to the corresponding estimates obtained using DCE-MRI with a vascular input function (VIF) and reference region model (RR). Both DCE-MRI methods produced consistently larger estimates of ve in comparison to the SPECT estimates, and several experimental sources were postulated to contribute to these differences. PMID:22991315

Characterizing Resting-State Brain Function Using Arterial Spin Labeling

PubMed Central

Jann, Kay; Wang, Danny J.J.

2015-01-01

Abstract Arterial spin labeling (ASL) is an increasingly established magnetic resonance imaging (MRI) technique that is finding broader applications in studying the healthy and diseased brain. This review addresses the use of ASL to assess brain function in the resting state. Following a brief technical description, we discuss the use of ASL in the following main categories: (1) resting-state functional connectivity (FC) measurement: the use of ASL-based cerebral blood flow (CBF) measurements as an alternative to the blood oxygen level-dependent (BOLD) technique to assess resting-state FC; (2) the link between network CBF and FC measurements: the use of network CBF as a surrogate of the metabolic activity within corresponding networks; and (3) the study of resting-state dynamic CBF-BOLD coupling and cerebral metabolism: the use of dynamic CBF information obtained using ASL to assess dynamic CBF-BOLD coupling and oxidative metabolism in the resting state. In addition, we summarize some future challenges and interesting research directions for ASL, including slice-accelerated (multiband) imaging as well as the effects of motion and other physiological confounds on perfusion-based FC measurement. In summary, this work reviews the state-of-the-art of ASL and establishes it as an increasingly viable MRI technique with high translational value in studying resting-state brain function. PMID:26106930

Functional magnetic resonance imaging during emotion recognition in social anxiety disorder: an activation likelihood meta-analysis

PubMed Central

Hattingh, Coenraad J.; Ipser, J.; Tromp, S. A.; Syal, S.; Lochner, C.; Brooks, S. J.; Stein, D. J.

2012-01-01

Background: Social anxiety disorder (SAD) is characterized by abnormal fear and anxiety in social situations. Functional magnetic resonance imaging (fMRI) is a brain imaging technique that can be used to demonstrate neural activation to emotionally salient stimuli. However, no attempt has yet been made to statistically collate fMRI studies of brain activation, using the activation likelihood-estimate (ALE) technique, in response to emotion recognition tasks in individuals with SAD. Methods: A systematic search of fMRI studies of neural responses to socially emotive cues in SAD was undertaken. ALE meta-analysis, a voxel-based meta-analytic technique, was used to estimate the most significant activations during emotional recognition. Results: Seven studies were eligible for inclusion in the meta-analysis, constituting a total of 91 subjects with SAD, and 93 healthy controls. The most significant areas of activation during emotional vs. neutral stimuli in individuals with SAD compared to controls were: bilateral amygdala, left medial temporal lobe encompassing the entorhinal cortex, left medial aspect of the inferior temporal lobe encompassing perirhinal cortex and parahippocampus, right anterior cingulate, right globus pallidus, and distal tip of right postcentral gyrus. Conclusion: The results are consistent with neuroanatomic models of the role of the amygdala in fear conditioning, and the importance of the limbic circuitry in mediating anxiety symptoms. PMID:23335892

Neuropsychological assessment of language functions during functional magnetic resonance imaging: development of new tasks. Preliminary report.

PubMed

Fersten, Ewa; Jakuciński, Maciej; Kuliński, Radosław; Koziara, Henryk; Mroziak, Barbara; Nauman, Paweł

2011-01-01

Due to the complex and extended cerebral organization of language functions, the brain regions crucial for speech and language, i.e. eloquent areas, have to be affected by neurooncological surgery. One of the techniques that may be helpful in pre-operative planning of the extent of tumour removal and estimating possible complications seems to be functional magnetic resonance imaging (fMRI). The aim of the study was to develop valid procedures for neuropsychological assessment of various language functions visualisable by fMRI in healthy individuals. In this fMRI study, 10 healthy (with no CNS pathology), right-handed volunteers aged 25-35 were examined using four tasks designed to measure different language functions, and one for short-term memory assessment. A 1.5-T MRI scanner performing ultrafast functional (EPI) sequences with 4-mm slice thickness and 1-mm interslice gap was used to detect the BOLD response to stimuli present-ed in a block design (30-second alternating blocks of activity and rest). The analyses used the SPM software running in a MATLAB environment, and the obtained data were interpreted by means of colour-coded maps superimposed on structural brain scans. For each of the tasks developed for particular language functions, a different area of increased neuronal activity was found. The differential localization of function-related neuronal activity seems interesting and the research worth continuing, since verbal communication failure may result from impairment of any of various language functions, and studies reported in the literature seem to focus on verbal expression only.

Investigating the physiology of brain activation with MRI

NASA Astrophysics Data System (ADS)

Buxton, Richard B.; Uludag, Kamil; Dubowitz, David J.

2004-04-01

Functional magnetic resonance imaging (fMRI) has become a powerful tool for investigating the working human brain based on the blood oxygenation level dependent (BOLD) effect on the MR signal. However, despite the widespread use of fMRI techniques for mapping brain activation, the basic physiological mechanisms underlying the observed signal changes are still poorly understood. Arterial spin labeling (ASL) techniques, which measure cerebral blood flow (CBF) and the BOLD effect simultaneously, provide a useful tool for investigating these physiological questions. In this paper, recent results of studies manipulating the baseline CBF both pharmacologically and physiologically will be discussed. These data are consistent with a feed-forward mechanism of neurovascular coupling, and suggest that the CBF change itself may be a more robust reflection of neural activity changes than the BOLD effect. Consistent with these data, a new thermodynamic hypothesis is proposed for the physiological function of CBF regulation: maintenance of the [O2]/[CO2] concentration ratio at the mitochondria in order to preserve the free energy available from oxidative metabolism. A kinetic model based on this hypothesis provides a reasonable quantitative description of the CBF changes associated with neural activity and altered blood gases (CO2 and O2).

Promise of new imaging technologies for assessing ovarian function.

PubMed

Singh, Jaswant; Adams, Gregg P; Pierson, Roger A

2003-10-15

Advancements in imaging technologies over the last two decades have ushered a quiet revolution in research approaches to the study of ovarian structure and function. The most significant changes in our understanding of the ovary have resulted from the use of ultrasonography which has enabled sequential analyses in live animals. Computer-assisted image analysis and mathematical modeling of the dynamic changes within the ovary has permitted exciting new avenues of research with readily quantifiable endpoints. Spectral, color-flow and power Doppler imaging now facilitate physiologic interpretations of vascular dynamics over time. Similarly, magnetic resonance imaging (MRI) is emerging as a research tool in ovarian imaging. New technologies, such as three-dimensional ultrasonography and MRI, ultrasound-based biomicroscopy and synchrotron-based techniques each have the potential to enhance our real-time picture of ovarian function to the near-cellular level. Collectively, information available in ultrasonography, MRI, computer-assisted image analysis and mathematical modeling heralds a new era in our understanding of the basic processes of female and male reproduction.

Event-related functional MRI: Past, present, and future

PubMed Central

Rosen, Bruce R.; Buckner, Randy L.; Dale, Anders M.

1998-01-01

The past two decades have seen an enormous growth in the field of human brain mapping. Investigators have extensively exploited techniques such as positron emission tomography and MRI to map patterns of brain activity based on changes in cerebral hemodynamics. However, until recently, most studies have investigated equilibrium changes in blood flow measured over time periods upward of 1 min. The advent of high-speed MRI methods, capable of imaging the entire brain with a temporal resolution of a few seconds, allows for brain mapping based on more transient aspects of the hemodynamic response. Today it is now possible to map changes in cerebrovascular parameters essentially in real time, conferring the ability to observe changes in brain state that occur over time periods of seconds. Furthermore, because robust hemodynamic alterations are detectable after neuronal stimuli lasting only a few tens of milliseconds, a new class of task paradigms designed to measure regional responses to single sensory or cognitive events can now be studied. Such “event related” functional MRI should provide for fundamentally new ways to interrogate brain function, and allow for the direct comparison and ultimately integration of data acquired by using more traditional behavioral and electrophysiological methods. PMID:9448240

Potential Audiological and MRI Markers of Tinnitus.

PubMed

Gopal, Kamakshi V; Thomas, Binu P; Nandy, Rajesh; Mao, Deng; Lu, Hanzhang

2017-09-01

Subjective tinnitus, or ringing sensation in the ear, is a common disorder with no accepted objective diagnostic markers. The purpose of this study was to identify possible objective markers of tinnitus by combining audiological and imaging-based techniques. Case-control studies. Twenty adults drawn from our audiology clinic served as participants. The tinnitus group consisted of ten participants with chronic bilateral constant tinnitus, and the control group consisted of ten participants with no history of tinnitus. Each participant with tinnitus was closely matched with a control participant on the basis of age, gender, and hearing thresholds. Data acquisition focused on systematic administration and evaluation of various audiological tests, including auditory-evoked potentials (AEP) and otoacoustic emissions, and magnetic resonance imaging (MRI) tests. A total of 14 objective test measures (predictors) obtained from audiological and MRI tests were subjected to statistical analyses to identify the best predictors of tinnitus group membership. The least absolute shrinkage and selection operator technique for feature extraction, supplemented by the leave-one-out cross-validation technique, were used to extract the best predictors. This approach provided a conservative model that was highly regularized with its error within 1 standard error of the minimum. The model selected increased frontal cortex (FC) functional MRI activity to pure tones matching their respective tinnitus pitch, and augmented AEP wave N₁ amplitude growth in the tinnitus group as the top two predictors of tinnitus group membership. These findings suggest that the amplified responses to acoustic signals and hyperactivity in attention regions of the brain may be a result of overattention among individuals that experience chronic tinnitus. These results suggest that increased functional MRI activity in the FC to sounds and augmented N₁ amplitude growth may potentially be the objective diagnostic indicators of tinnitus. However, due to the small sample size and lack of subgroups within the tinnitus population in this study, more research is needed before generalizing these findings. American Academy of Audiology

Advanced magnetic resonance imaging of the physical processes in human glioblastoma.

PubMed

Kalpathy-Cramer, Jayashree; Gerstner, Elizabeth R; Emblem, Kyrre E; Andronesi, Ovidiu; Rosen, Bruce

2014-09-01

The most common malignant primary brain tumor, glioblastoma multiforme (GBM) is a devastating disease with a grim prognosis. Patient survival is typically less than two years and fewer than 10% of patients survive more than five years. Magnetic resonance imaging (MRI) can have great utility in the diagnosis, grading, and management of patients with GBM as many of the physical manifestations of the pathologic processes in GBM can be visualized and quantified using MRI. Newer MRI techniques such as dynamic contrast enhanced and dynamic susceptibility contrast MRI provide functional information about the tumor hemodynamic status. Diffusion MRI can shed light on tumor cellularity and the disruption of white matter tracts in the proximity of tumors. MR spectroscopy can be used to study new tumor tissue markers such as IDH mutations. MRI is helping to noninvasively explore the link between the molecular basis of gliomas and the imaging characteristics of their physical processes. We, here, review several approaches to MR-based imaging and discuss the potential for these techniques to quantify the physical processes in glioblastoma, including tumor cellularity and vascularity, metabolite expression, and patterns of tumor growth and recurrence. We conclude with challenges and opportunities for further research in applying physical principles to better understand the biologic process in this deadly disease. See all articles in this Cancer Research section, "Physics in Cancer Research." ©2014 American Association for Cancer Research.

Biomedical Investigations with Laser-Polarized Noble Gas Magnetic Resonance

NASA Technical Reports Server (NTRS)

Walsworth, Ronald L.

2003-01-01

We pursued advanced technology development of laser-polarized noble gas nuclear magnetic resonance (NMR) as a novel biomedical imaging tool for ground-based and eventually space-based application. This new multidisciplinary technology enables high-resolution gas-space magnetic resonance imaging (MRI)-e.g., of lung ventilation-as well as studies of tissue perfusion. In addition, laser-polarized noble gases (3He and 129Xe) do not require a large magnetic field for sensitive detection, opening the door to practical MRI at very low magnetic fields with an open, lightweight, and low-power device. We pursued two technology development specific aims: (1) development of low-field (less than 0.01 T) noble gas MRI of humans; and (2) development of functional MRI of the lung using laser-polarized noble gas and related techniques.

The dynamic programming high-order Dynamic Bayesian Networks learning for identifying effective connectivity in human brain from fMRI.

PubMed

Dang, Shilpa; Chaudhury, Santanu; Lall, Brejesh; Roy, Prasun Kumar

2017-06-15

Determination of effective connectivity (EC) among brain regions using fMRI is helpful in understanding the underlying neural mechanisms. Dynamic Bayesian Networks (DBNs) are an appropriate class of probabilistic graphical temporal-models that have been used in past to model EC from fMRI, specifically order-one. High-order DBNs (HO-DBNs) have still not been explored for fMRI data. A fundamental problem faced in the structure-learning of HO-DBN is high computational-burden and low accuracy by the existing heuristic search techniques used for EC detection from fMRI. In this paper, we propose using dynamic programming (DP) principle along with integration of properties of scoring-function in a way to reduce search space for structure-learning of HO-DBNs and finally, for identifying EC from fMRI which has not been done yet to the best of our knowledge. The proposed exact search-&-score learning approach HO-DBN-DP is an extension of the technique which was originally devised for learning a BN's structure from static data (Singh and Moore, 2005). The effectiveness in structure-learning is shown on synthetic fMRI dataset. The algorithm reaches globally-optimal solution in appreciably reduced time-complexity than the static counterpart due to integration of properties. The proof of optimality is provided. The results demonstrate that HO-DBN-DP is comparably more accurate and faster than currently used structure-learning algorithms used for identifying EC from fMRI. The real data EC from HO-DBN-DP shows consistency with previous literature than the classical Granger Causality method. Hence, the DP algorithm can be employed for reliable EC estimates from experimental fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.

Digital photography and 3D MRI-based multimodal imaging for individualized planning of resective neocortical epilepsy surgery.

PubMed

Wellmer, Jörg; von Oertzen, Joachim; Schaller, Carlo; Urbach, Horst; König, Roy; Widman, Guido; Van Roost, Dirk; Elger, Christian E

2002-12-01

Invasive presurgical work up of pharmacoresistant epilepsies presumes integration of multiple diagnostic modalities into a comprehensive picture of seizure onset and eloquent brain areas. During resection, reliable transfer of evaluation results to the patient's individual anatomy must be made. We investigated the value of digital photography-based grid localization in combination with preoperative three-dimensional (3D) magnetic resonance imaging (MRI) for clinical routine. Digital photographs of the exposed cortex were taken before and after grid placement. Location of electrode contacts on the cortex was identified and schematically indicated on native cortex prints. Accordingly, transfer of contact positions to a 3D MRI brain-surface rendering was carried out manually by using the rendering software. Results of the electrophysiologic evaluation were transferred to either electrode contact reproduction and co-registered with imaging-based techniques such as single-photon emission computed tomography (SPECT), positron emission tomography (PET), and functional MRI (fMRI). Digital photography allows precise and highly realistic documentation of electrode contact positions on the individual neocortical surface. Lesions underneath grids can be highlighted by semitransparent MRI surface rendering, and lobar boundaries can be identified. Because of integrating electrode contact positions into the postprocessed 3D MRI data set, imaging-based techniques can be codisplayed with the results of the electrophysiologic evaluation. Comparison with CT/MRI co-registration showed good accuracy of the method. However, grids not sewn to the dura at implantation can become subject to significant displacement. Digital photography in combination with preimplantation 3D MRI allows the generation of reliable tailored resection plans in neocortical epilepsy surgery. The method enhances surgical safety and confidence.

OpenNFT: An open-source Python/Matlab framework for real-time fMRI neurofeedback training based on activity, connectivity and multivariate pattern analysis.

PubMed

Koush, Yury; Ashburner, John; Prilepin, Evgeny; Sladky, Ronald; Zeidman, Peter; Bibikov, Sergei; Scharnowski, Frank; Nikonorov, Artem; De Ville, Dimitri Van

2017-08-01

Neurofeedback based on real-time functional magnetic resonance imaging (rt-fMRI) is a novel and rapidly developing research field. It allows for training of voluntary control over localized brain activity and connectivity and has demonstrated promising clinical applications. Because of the rapid technical developments of MRI techniques and the availability of high-performance computing, new methodological advances in rt-fMRI neurofeedback become possible. Here we outline the core components of a novel open-source neurofeedback framework, termed Open NeuroFeedback Training (OpenNFT), which efficiently integrates these new developments. This framework is implemented using Python and Matlab source code to allow for diverse functionality, high modularity, and rapid extendibility of the software depending on the user's needs. In addition, it provides an easy interface to the functionality of Statistical Parametric Mapping (SPM) that is also open-source and one of the most widely used fMRI data analysis software. We demonstrate the functionality of our new framework by describing case studies that include neurofeedback protocols based on brain activity levels, effective connectivity models, and pattern classification approaches. This open-source initiative provides a suitable framework to actively engage in the development of novel neurofeedback approaches, so that local methodological developments can be easily made accessible to a wider range of users. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A 4-channel 3 Tesla phased array receive coil for awake rhesus monkey fMRI and diffusion MRI experiments.

PubMed

Khachaturian, Mark Haig

2010-01-01

Awake monkey fMRI and diffusion MRI combined with conventional neuroscience techniques has the potential to study the structural and functional neural network. The majority of monkey fMRI and diffusion MRI experiments are performed with single coils which suffer from severe EPI distortions which limit resolution. By constructing phased array coils for monkey MRI studies, gains in SNR and anatomical accuracy (i.e., reduction of EPI distortions) can be achieved using parallel imaging. The major challenges associated with constructing phased array coils for monkeys are the variation in head size and space constraints. Here, we apply phased array technology to a 4-channel phased array coil capable of improving the resolution and image quality of full brain awake monkey fMRI and diffusion MRI experiments. The phased array coil is that can adapt to different rhesus monkey head sizes (ages 4-8) and fits in the limited space provided by monkey stereotactic equipment and provides SNR gains in primary visual cortex and anatomical accuracy in conjunction with parallel imaging and improves resolution in fMRI experiments by a factor of 2 (1.25 mm to 1.0 mm isotropic) and diffusion MRI experiments by a factor of 4 (1.5 mm to 0.9 mm isotropic).

A 4-channel 3 Tesla phased array receive coil for awake rhesus monkey fMRI and diffusion MRI experiments

PubMed Central

Khachaturian, Mark Haig

2010-01-01

Awake monkey fMRI and diffusion MRI combined with conventional neuroscience techniques has the potential to study the structural and functional neural network. The majority of monkey fMRI and diffusion MRI experiments are performed with single coils which suffer from severe EPI distortions which limit resolution. By constructing phased array coils for monkey MRI studies, gains in SNR and anatomical accuracy (i.e., reduction of EPI distortions) can be achieved using parallel imaging. The major challenges associated with constructing phased array coils for monkeys are the variation in head size and space constraints. Here, we apply phased array technology to a 4-channel phased array coil capable of improving the resolution and image quality of full brain awake monkey fMRI and diffusion MRI experiments. The phased array coil is that can adapt to different rhesus monkey head sizes (ages 4–8) and fits in the limited space provided by monkey stereotactic equipment and provides SNR gains in primary visual cortex and anatomical accuracy in conjunction with parallel imaging and improves resolution in fMRI experiments by a factor of 2 (1.25 mm to 1.0 mm isotropic) and diffusion MRI experiments by a factor of 4 (1.5 mm to 0.9 mm isotropic). PMID:21243106

Predictive sparse modeling of fMRI data for improved classification, regression, and visualization using the k-support norm.

PubMed

Belilovsky, Eugene; Gkirtzou, Katerina; Misyrlis, Michail; Konova, Anna B; Honorio, Jean; Alia-Klein, Nelly; Goldstein, Rita Z; Samaras, Dimitris; Blaschko, Matthew B

2015-12-01

We explore various sparse regularization techniques for analyzing fMRI data, such as the ℓ1 norm (often called LASSO in the context of a squared loss function), elastic net, and the recently introduced k-support norm. Employing sparsity regularization allows us to handle the curse of dimensionality, a problem commonly found in fMRI analysis. In this work we consider sparse regularization in both the regression and classification settings. We perform experiments on fMRI scans from cocaine-addicted as well as healthy control subjects. We show that in many cases, use of the k-support norm leads to better predictive performance, solution stability, and interpretability as compared to other standard approaches. We additionally analyze the advantages of using the absolute loss function versus the standard squared loss which leads to significantly better predictive performance for the regularization methods tested in almost all cases. Our results support the use of the k-support norm for fMRI analysis and on the clinical side, the generalizability of the I-RISA model of cocaine addiction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparison of quantitative regional ventilation-weighted fourier decomposition MRI with dynamic fluorinated gas washout MRI and lung function testing in COPD patients.

PubMed

Kaireit, Till F; Gutberlet, Marcel; Voskrebenzev, Andreas; Freise, Julia; Welte, Tobias; Hohlfeld, Jens M; Wacker, Frank; Vogel-Claussen, Jens

2018-06-01

Ventilation-weighted Fourier decomposition-MRI (FD-MRI) has matured as a reliable technique for quantitative measures of regional lung ventilation in recent years, but has yet not been validated in COPD patients. To compare regional fractional lung ventilation obtained by ventilation-weighted FD-MRI with dynamic fluorinated gas washout MRI ( 19 F-MRI) and lung function test parameters. Prospective study. Twenty-seven patients with chronic obstructive pulmonary disease (COPD, median age 61 [54-67] years) were included. For FD-MRI and for 19 F-MRI a spoiled gradient echo sequence was used at 1.5T. FD-MRI coronal slices were acquired in free breathing. Dynamic 19 F-MRI was performed after inhalation of 25-30 L of a mixture of 79% fluorinated gas (C 3 F 8 ) and 21% oxygen via a closed face mask tubing using a dedicated coil tuned to 59.9 MHz. 19 F washout times in numbers of breaths ( 19 F-n breaths ) as well as fractional ventilation maps for both methods (FD-FV, 19 F-FV) were calculated. Slices were matched using a landmark driven algorithm, and only corresponding slices with an overlap of >90% were coregistered for evaluation. The obtained parameters were correlated with each other using Spearman's correlation coefficient (r). FD-FV strongly correlated with 19 F-n breaths on a global (r = -0.72, P < 0.0001) as well as on a lobar level and with lung function test parameters (FD-FV vs. FEV1, r = 0.76, P < 0.0001). There was a small systematic overestimation of FD-FV compared to 19 F-FV (mean difference -0.03 (95% confidence interval [CI]: -0.097; -0.045). Regional ventilation-weighted Fourier decomposition-MRI is a promising noninvasive, radiation-free tool for quantification of regional ventilation in COPD patients. 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1534-1541. © 2017 International Society for Magnetic Resonance in Medicine.

Age and amyloid-related alterations in default network habituation to stimulus repetition

PubMed Central

Vannini, Patrizia; Hedden, Trey; Becker, John A.; Sullivan, Caroline; Putcha, Deepti; Rentz, Dorene; Johnson, Keith A.; Sperling, Reisa. A.

2011-01-01

The neural networks supporting encoding of new information are thought to decline with age, although mnemonic techniques such as repetition may enhance performance in older individuals. Accumulation of amyloid-β, one hallmark pathology of Alzheimer’s disease (AD), may contribute to functional alterations in memory networks measured with functional magnetic resonance imaging (fMRI) prior to onset of cognitive impairment. We investigated the effects of age and amyloid burden on fMRI activity in the default network and hippocampus during repetitive encoding. Older individuals, particularly those with high amyloid burden, demonstrated decreased task-induced deactivation in the posteromedial cortices during initial stimulus presentation and failed to modulate fMRI activity in response to repeated trials, whereas young subjects demonstrated a stepwise decrease in deactivation with repetition. The hippocampus demonstrated similar patterns across the groups, showing task-induced activity that decreased in response to repetition. These findings demonstrate that age and amyloid have dissociable functional effects on specific nodes within a distributed memory network, and suggest that functional brain changes may begin far in advance of symptomatic AD. PMID:21334099

[Methodological aspects of functional neuroimaging at high field strength: a critical review].

PubMed

Scheef, L; Landsberg, M W; Boecker, H

2007-09-01

The last few years have proven that high field magnetic resonance imaging (MRI) is superior in nearly every way to conventional equipment up to 1.5 tesla (T). Following the global success of 3T-scanners in research institutes and medical practices, a new generation of MRI devices with field strengths of 7T and higher is now on the horizon. The introduction of ultra high fields has brought MRI technology closer to the physical limitations and increasingly greater costs are required to achieve this goal. This article provides a critical overview of the advantages and problems of functional neuroimaging using ultra high field strengths. This review is principally limited to T2*-based functional imaging techniques not dependent on contrast agents. The main issues include the significance of high field technology with respect to SNR, CNR, resolution, and sequences, as well as artifacts, noise exposure, and SAR. Of great relevance is the discussion of parallel imaging, which will presumably determine the further development of high and ultra high field strengths. Finally, the importance of high field strengths for functional neuroimaging is explained by selected publications.

[Functional neuroimaging of the brain structures associated with language in healthy individuals and patients with post-stroke aphasia].

PubMed

Alferova, V V; Mayorova, L A; Ivanova, E G; Guekht, A B; Shklovskij, V M

2017-01-01

The introduction of non-invasive functional neuroimaging techniques such as functional magnetic resonance imaging (fMRI), in the practice of scientific and clinical research can increase our knowledge about the organization of cognitive processes, including language, in normal and reorganization of these cognitive functions in post-stroke aphasia. The article discusses the results of fMRI studies of functional organization of the cortex of a healthy adult's brain in the processing of various voice information as well as the main types of speech reorganization after post-stroke aphasia in different stroke periods. The concepts of 'effective' and 'ineffective' brain plasticity in post-stroke aphasia were considered. It was concluded that there was an urgent need for further comprehensive studies, including neuropsychological testing and several complementary methods of functional neuroimaging, to develop a phased treatment plan and neurorehabilitation of patients with post-stroke aphasia.

Pressure Autoregulation Measurement Techniques in Adult Traumatic Brain Injury, Part I: A Scoping Review of Intermittent/Semi-Intermittent Methods.

PubMed

Zeiler, Frederick A; Donnelly, Joseph; Calviello, Leanne; Menon, David K; Smielewski, Peter; Czosnyka, Marek

2017-12-01

The purpose of this study was to perform a systematic, scoping review of commonly described intermittent/semi-intermittent autoregulation measurement techniques in adult traumatic brain injury (TBI). Nine separate systematic reviews were conducted for each intermittent technique: computed tomographic perfusion (CTP)/Xenon-CT (Xe-CT), positron emission tomography (PET), magnetic resonance imaging (MRI), arteriovenous difference in oxygen (AVDO 2 ) technique, thigh cuff deflation technique (TCDT), transient hyperemic response test (THRT), orthostatic hypotension test (OHT), mean flow index (Mx), and transfer function autoregulation index (TF-ARI). MEDLINE ® , BIOSIS, EMBASE, Global Health, Scopus, Cochrane Library (inception to December 2016), and reference lists of relevant articles were searched. A two tier filter of references was conducted. The total number of articles utilizing each of the nine searched techniques for intermittent/semi-intermittent autoregulation techniques in adult TBI were: CTP/Xe-CT (10), PET (6), MRI (0), AVDO 2 (10), ARI-based TCDT (9), THRT (6), OHT (3), Mx (17), and TF-ARI (6). The premise behind all of the intermittent techniques is manipulation of systemic blood pressure/blood volume via either chemical (such as vasopressors) or mechanical (such as thigh cuffs or carotid compression) means. Exceptionally, Mx and TF-ARI are based on spontaneous fluctuations of cerebral perfusion pressure (CPP) or mean arterial pressure (MAP). The method for assessing the cerebral circulation during these manipulations varies, with both imaging-based techniques and TCD utilized. Despite the limited literature for intermittent/semi-intermittent techniques in adult TBI (minus Mx), it is important to acknowledge the availability of such tests. They have provided fundamental insight into human autoregulatory capacity, leading to the development of continuous and more commonly applied techniques in the intensive care unit (ICU). Numerous methods of intermittent/semi-intermittent pressure autoregulation assessment in adult TBI exist, including: CTP/Xe-CT, PET, AVDO 2 technique, TCDT-based ARI, THRT, OHT, Mx, and TF-ARI. MRI-based techniques in adult TBI are yet to be described, with the main focus of MRI techniques on metabolic-based cerebrovascular reactivity (CVR) and not pressure-based autoregulation.

Sparse Multivariate Autoregressive Modeling for Mild Cognitive Impairment Classification

PubMed Central

Li, Yang; Wee, Chong-Yaw; Jie, Biao; Peng, Ziwen

2014-01-01

Brain connectivity network derived from functional magnetic resonance imaging (fMRI) is becoming increasingly prevalent in the researches related to cognitive and perceptual processes. The capability to detect causal or effective connectivity is highly desirable for understanding the cooperative nature of brain network, particularly when the ultimate goal is to obtain good performance of control-patient classification with biological meaningful interpretations. Understanding directed functional interactions between brain regions via brain connectivity network is a challenging task. Since many genetic and biomedical networks are intrinsically sparse, incorporating sparsity property into connectivity modeling can make the derived models more biologically plausible. Accordingly, we propose an effective connectivity modeling of resting-state fMRI data based on the multivariate autoregressive (MAR) modeling technique, which is widely used to characterize temporal information of dynamic systems. This MAR modeling technique allows for the identification of effective connectivity using the Granger causality concept and reducing the spurious causality connectivity in assessment of directed functional interaction from fMRI data. A forward orthogonal least squares (OLS) regression algorithm is further used to construct a sparse MAR model. By applying the proposed modeling to mild cognitive impairment (MCI) classification, we identify several most discriminative regions, including middle cingulate gyrus, posterior cingulate gyrus, lingual gyrus and caudate regions, in line with results reported in previous findings. A relatively high classification accuracy of 91.89 % is also achieved, with an increment of 5.4 % compared to the fully-connected, non-directional Pearson-correlation-based functional connectivity approach. PMID:24595922

Cartilage segmentation of 3D MRI scans of the osteoarthritic knee combining user knowledge and active contours

NASA Astrophysics Data System (ADS)

Lynch, John A.; Zaim, Souhil; Zhao, Jenny; Stork, Alexander; Peterfy, Charles G.; Genant, Harry K.

2000-06-01

A technique for segmentation of articular cartilage from 3D MRI scans of the knee has been developed. It overcomes the limitations of the conventionally used region growing techniques, which are prone to inter- and intra-observer variability, and which can require much manual intervention. We describe a hybrid segmentation method combining expert knowledge with directionally oriented Canny filters, cost functions and cubic splines. After manual initialization, the technique utilized 3 cost functions which aided automated detection of cartilage and its boundaries. Using the sign of the edge strength, and the local direction of the boundary, this technique is more reliable than conventional 'snakes,' and the user had little control over smoothness of boundaries. This means that the automatically detected boundary can conform to the true shape of the real boundary, also allowing reliable detection of subtle local lesions on the normally smooth cartilage surface. Manual corrections, with possible re-optimization were sometimes needed. When compared to the conventionally used region growing techniques, this newly described technique measured local cartilage volume with 3 times better reproducibility, and involved two thirds less human interaction. Combined with the use of 3D image registration, the new technique should also permit unbiased segmentation of followup scans by automated initialization from a baseline segmentation of an earlier scan of the same patient.

Comparison of fMRI paradigms assessing visuospatial processing: Robustness and reproducibility

PubMed Central

Herholz, Peer; Zimmermann, Kristin M.; Westermann, Stefan; Frässle, Stefan; Jansen, Andreas

2017-01-01

The development of brain imaging techniques, in particular functional magnetic resonance imaging (fMRI), made it possible to non-invasively study the hemispheric lateralization of cognitive brain functions in large cohorts. Comprehensive models of hemispheric lateralization are, however, still missing and should not only account for the hemispheric specialization of individual brain functions, but also for the interactions among different lateralized cognitive processes (e.g., language and visuospatial processing). This calls for robust and reliable paradigms to study hemispheric lateralization for various cognitive functions. While numerous reliable imaging paradigms have been developed for language, which represents the most prominent left-lateralized brain function, the reliability of imaging paradigms investigating typically right-lateralized brain functions, such as visuospatial processing, has received comparatively less attention. In the present study, we aimed to establish an fMRI paradigm that robustly and reliably identifies right-hemispheric activation evoked by visuospatial processing in individual subjects. In a first study, we therefore compared three frequently used paradigms for assessing visuospatial processing and evaluated their utility to robustly detect right-lateralized brain activity on a single-subject level. In a second study, we then assessed the test-retest reliability of the so-called Landmark task–the paradigm that yielded the most robust results in study 1. At the single-voxel level, we found poor reliability of the brain activation underlying visuospatial attention. This suggests that poor signal-to-noise ratios can become a limiting factor for test-retest reliability. This represents a common detriment of fMRI paradigms investigating visuospatial attention in general and therefore highlights the need for careful considerations of both the possibilities and limitations of the respective fMRI paradigm–in particular, when being interested in effects at the single-voxel level. Notably, however, when focusing on the reliability of measures of hemispheric lateralization (which was the main goal of study 2), we show that hemispheric dominance (quantified by the lateralization index, LI, with |LI| >0.4) of the evoked activation could be robustly determined in more than 62% and, if considering only two categories (i.e., left, right), in more than 93% of our subjects. Furthermore, the reliability of the lateralization strength (LI) was “fair” to “good”. In conclusion, our results suggest that the degree of right-hemispheric dominance during visuospatial processing can be reliably determined using the Landmark task, both at the group and single-subject level, while at the same time stressing the need for future refinements of experimental paradigms and more sophisticated fMRI data acquisition techniques. PMID:29059201

Rapid Gradient-Echo Imaging

PubMed Central

Hargreaves, Brian

2012-01-01

Gradient echo sequences are widely used in magnetic resonance imaging (MRI) for numerous applications ranging from angiography to perfusion to functional MRI. Compared with spin-echo techniques, the very short repetition times of gradient-echo methods enable very rapid 2D and 3D imaging, but also lead to complicated “steady states.” Signal and contrast behavior can be described graphically and mathematically, and depends strongly on the type of spoiling: fully balanced (no spoiling), gradient spoiling, or RF-spoiling. These spoiling options trade off between high signal and pure T1 contrast while the flip angle also affects image contrast in all cases, both of which can be demonstrated theoretically and in image examples. As with spin-echo sequences, magnetization preparation can be added to gradient-echo sequences to alter image contrast. Gradient echo sequences are widely used for numerous applications such as 3D perfusion imaging, functional MRI, cardiac imaging and MR angiography. PMID:23097185

Future trends in Neuroimaging: Neural processes as expressed within real-life contexts

PubMed Central

Hasson, Uri; Honey, Christopher J.

2012-01-01

Human neuroscience research has changed dramatically with the proliferation and refinement of functional magnetic resonance imaging (fMRI) technologies. The early years of the technique were largely devoted to methods development and validation, and to the coarse-grained mapping of functional topographies. This paper will cover three emerging trends that we believe will be central to fMRI research in the coming decade. In the first section of this paper, we argue in favor of a shift from fine-grained functional labeling toward the characterization of underlying neural processes. In the second section, we examine three methodological developments that have improved our ability to characterize underlying neural processes using fMRI. In the last section, we highlight the trend towards more ecologically valid fMRI experiments, which engage neural circuits in real life conditions. We note that many of our cognitive faculties emerge from interpersonal interactions, and that a complete understanding of the cognitive processes within a single individual's brain cannot be achieved without understanding the interactions among individuals. Looking forward to the future of human fMRI, we conclude that the major constraint on new discoveries will not be related to the spatiotemporal resolution of the BOLD signal, which is constantly improving, but rather to the precision of our hypotheses and the creativity of our methods for testing them. PMID:22348879

[Interest of tricuspid annular displacement (TAD) in evaluation of right ventricular ejection fraction].

PubMed

Hugues, T; Ducreux, D; Bertora, D; Berthier, F; Lemoigne, F; Padovani, B; Gibelin, P

2010-04-01

The ultrasound assessment of RV structure and function is often sub-optimal. The range of excursions of the mitral or tricuspid annulus measured in millimetre by 2D or TM-mode in centimetre per second by DTI-mode echocardiography has been shown to reflect the systolic function of both ventricles. We studied a new technique based on a tissue tracking algorithm that is ultrasound beam angle independent for automated detection of tricuspid annular displacement (TAD) (QLAB, Philips Medical Imaging). Twenty-six patients (pts) referred for magnetic resonance imaging (MRI) and 44 control subjects underwent a complete transthoracic echocardiography. MRI of the right ventricular ejection fraction (RVEF) was correlated by linear regression with TAD. Sixteen pts (61.5%) exhibited right ventricular systolic dysfunction (MRI RVEF<40%). The MRI RVEF was positively correlated with TAD (R(2)=0,65; p<0,0001). A value of TAD <14mm predicted right ventricular dysfunction with a sensitivity of 87.5% and a specificity of 90%. Most of (90%) healthy subjects exhibited TAD values exceeding this cut-off point (mean: 16.9+/-1.64mm; range: 13.3 to 24.8mm). Negative correlation was found between TAD and age (R(2)=0,36; p<0,0001). Our study is the first to correlate TAD with MRI RVEF. TAD is a simple, rapid, and non-invasive tool for right ventricular systolic function assessment.

Multiparametric prostate MRI: technical conduct, standardized report and clinical use.

PubMed

Manfredi, Matteo; Mele, Fabrizio; Garrou, Diletta; Walz, Jochen; Fütterer, Jurgen J; Russo, Filippo; Vassallo, Lorenzo; Villers, Arnauld; Emberton, Mark; Valerio, Massimo

2018-02-01

Multiparametric prostate MRI (mp-MRI) is an emerging imaging modality for diagnosis, characterization, staging, and treatment planning of prostate cancer (PCa). The technique, results reporting, and its role in clinical practice have been the subject of significant development over the last decade. Although mp-MRI is not yet routinely used in the diagnostic pathway, almost all urological guidelines have emphasized the potential role of mp-MRI in several aspects of PCa management. Moreover, new MRI sequences and scanning techniques are currently under evaluation to improve the diagnostic accuracy of mp-MRI. This review presents an overview of mp-MRI, summarizing the technical applications, the standardized reporting systems used, and their current roles in various stages of PCa management. Finally, this critical review also reports the main limitations and future perspectives of the technique.

Capturing neuroplastic changes after bimanual intensive rehabilitation in children with unilateral spastic cerebral palsy: A combined DTI, TMS and fMRI pilot study.

PubMed

Bleyenheuft, Yannick; Dricot, Laurence; Gilis, Nathalie; Kuo, Hsing-Ching; Grandin, Cécile; Bleyenheuft, Corinne; Gordon, Andrew M; Friel, Kathleen M

2015-01-01

Intensive rehabilitation interventions have been shown to be efficacious in improving upper extremity function in children with unilateral spastic cerebral palsy (USCP). These interventions are based on motor learning principles and engage children in skillful movements. Improvements in upper extremity function are believed to be associated with neuroplastic changes. However, these neuroplastic changes have not been well-described in children with cerebral palsy, likely due to challenges in defining and implementing the optimal tools and tests in children. Here we documented the implementation of three different neurological assessments (diffusion tensor imaging-DTI, transcranial magnetic stimulation-TMS and functional magnetic resonance imaging-fMRI) before and after a bimanual intensive treatment (HABIT-ILE) in two children with USCP presenting differential corticospinal developmental reorganization (ipsilateral and contralateral). The aim of the study was to capture neurophysiological changes and to document the complementary relationship between these measures, the potential measurable changes and the feasibility of applying these techniques in children with USCP. Independent of cortical reorganization, both children showed increases in activation and size of the motor areas controlling the affected hand, quantified with different techniques. In addition, fMRI provided additional unexpected changes in the reward circuit while using the affected hand. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Whole-brain high in-plane resolution fMRI using accelerated EPIK for enhanced characterisation of functional areas at 3T

PubMed Central

Yun, Seong Dae

2017-01-01

The relatively high imaging speed of EPI has led to its widespread use in dynamic MRI studies such as functional MRI. An approach to improve the performance of EPI, EPI with Keyhole (EPIK), has been previously presented and its use in fMRI was verified at 1.5T as well as 3T. The method has been proven to achieve a higher temporal resolution and smaller image distortions when compared to single-shot EPI. Furthermore, the performance of EPIK in the detection of functional signals was shown to be comparable to that of EPI. For these reasons, we were motivated to employ EPIK here for high-resolution imaging. The method was optimised to offer the highest possible in-plane resolution and slice coverage under the given imaging constraints: fixed TR/TE, FOV and acceleration factors for parallel imaging and partial Fourier techniques. The performance of EPIK was evaluated in direct comparison to the optimised protocol obtained from EPI. The two imaging methods were applied to visual fMRI experiments involving sixteen subjects. The results showed that enhanced spatial resolution with a whole-brain coverage was achieved by EPIK (1.00 mm × 1.00 mm; 32 slices) when compared to EPI (1.25 mm × 1.25 mm; 28 slices). As a consequence, enhanced characterisation of functional areas has been demonstrated in EPIK particularly for relatively small brain regions such as the lateral geniculate nucleus (LGN) and superior colliculus (SC); overall, a significantly increased t-value and activation area were observed from EPIK data. Lastly, the use of EPIK for fMRI was validated with the simulation of different types of data reconstruction methods. PMID:28945780

Integration of Functional Magnetic Resonance Imaging and Magnetoencephalography Functional Maps Into a CyberKnife Planning System: Feasibility Study for Motor Activity Localization and Dose Planning.

PubMed

De Martin, Elena; Duran, Dunja; Ghielmetti, Francesco; Visani, Elisa; Aquino, Domenico; Marchetti, Marcello; Sebastiano, Davide Rossi; Cusumano, Davide; Bruzzone, Maria Grazia; Panzica, Ferruccio; Fariselli, Laura

2017-12-01

Magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) provide noninvasive localization of eloquent brain areas for presurgical planning. The aim of this study is the integration of MEG and fMRI maps into a CyberKnife (CK) system to optimize dose planning. Four patients with brain metastases in the motor area underwent functional imaging study of the hand motor cortex before radiosurgery. MEG data were acquired during a visually cued hand motor task. Motor activations were identified also using an fMRI block-designed paradigm. MEG and fMRI maps were then integrated into a CK system and contoured as organs at risk for treatment planning optimization. The integration of fMRI data into the CK system was achieved for all patients by means of a standardized protocol. We also implemented an ad hoc pipeline to convert the MEG signal into a DICOM standard, to make sure that it was readable by our CK treatment planning system. Inclusion of the activation areas into the optimization plan allowed the creation of treatment plans that reduced the irradiation of the motor cortex yet not affecting the brain peripheral dose. The availability of advanced neuroimaging techniques is playing an increasingly important role in radiosurgical planning strategy. We successfully imported MEG and fMRI activations into a CK system. This additional information can improve dose sparing of eloquent areas, allowing a more comprehensive investigation of the related dose-volume constraints that in theory could translate into a gain in tumor local control, and a reduction of neurological complications. Copyright © 2017 Elsevier Inc. All rights reserved.

Neuronal current magnetic resonance imaging of evoked potentials and neural oscillations

NASA Astrophysics Data System (ADS)

Jiang, Xia

Despite its great success, the current functional magnetic resonance imaging (MRI) technique relies on changes in cerebral hemodynamic parameters to infer the underlying neural activities, and as a result is limited in its spatial and temporal resolutions. In this dissertation, we discuss the feasibility of neuronal current MRI (nc-MRI), a novel technique in which the small magnetic field changes caused by neuronal electrical activities are directly measured by MRI. Two studies are described. In the first study, we investigated the feasibility of detecting the magnetic field produced by sensory evoked potentials. To eliminate the blood-oxygen-level-dependent (BOLD) effect on the MRI signal, which confounded most previous studies, an octopus visual system model was developed, which, for the first time, allowed for an in vivo investigation of nc-MRI in a BOLD-free environment. Electrophysiological responses were measured in the octopus retina and optical lobe to guide the nc-MRI acquisition. Our results indicated that no nc-MRI signal change related to neuronal activation could be detected at 0.2°/0.2% threshold for signal phase/magnitude respectively, while robust electrophysiological responses were recorded. In the second study, we discuss the feasibility of detecting neural oscillations with MRI, Based on previous studies, a novel approach was proposed in which an external oscillatory field was exploited as the excitation pulse under a spin-locked condition. This approach has the advantages of increased sensitivity and lowered physiological noise. Successful detection of sub-nanotesla field was demonstrated in phantom. Our results suggest that evoked potentials are too weak for nc-MRI detection with the current hardware, and that previous positive findings were likely due to hemodynamic confounders. On the other hand, oscillatory magnetic field can be efficiently detected in phantom. Given the stronger equivalent current dipoles produced by neural oscillations compared to evoked potentials, they might be a more promising candidate for future nc-MRI studies.

A new contrast media for functional MR urography: Gd-MAG3.

PubMed

Algin, Oktay

2011-07-01

Tc-99m-MAG3 (tubular agent) provides high imaging quality and extraction efficiency; and has become one of the most widely used agent for scintigraphic examinations of urinary system pathologies and renal transplants. Recently, it was reported that functional magnetic resonance urography (FMRU) can be sufficient in detection of urinary tract obstruction, renal artery stenosis, calculation of kidney functions and evaluation of renal transplants. However the pharmacokinetics of magnetic resonance (MR) contrast-media used in FMRU and Tc-99m-MAG3 differs from each other. This may cause discordant results between the FMRU and most of the scintigraphic studies. To our knowledge, there is no contrast-media which is specific for FMRU. A kidney specific contrast material can be developed for FMRU studies as well. MAG3 is a good candidate for this chelation. In conclusion, MR imaging (MRI) will be the most useful and important technique for morphologic-functional evaluation of urinary system. FMRU examinations performed with MAG3 chelated gadolinium can be sufficient for the complete evaluation of urinary tract even in patients with impaired renal functions ("all in one MRI"). MRI has some important advantages including no risk for radiation exposure, high temporal and spatial resolution, no need for nephrotoxic contrast agent; besides being a fast and feasible technique. Gadolinium-containing contrast agents may cause a life-threatening adverse reaction known as nephrogenic systemic fibrosis in patients with severe renal impairment, but Gd-MAG3 may reduce the risk of nephrogenic systemic fibrosis due to its higher extraction capacity and other features. Copyright © 2011 Elsevier Ltd. All rights reserved.

The use of magnetic resonance imaging for studying female sexual function: A review.

PubMed

Vaccaro, Christine M

2015-04-01

Many would agree that there are two quintessential sexual organs in the female: the clitoris and the brain. Using non-invasive techniques of magnetic resonance imaging (MRI), investigators have gained insight into the mental and physical factors involved in female sexual function. Since only the external clitoral glans is easily accessible for direct measurement, the complete anatomy of the clitoris (including the internal components-paired corpora, crura, and bulbs) has only recently been described, with MRI providing the most sensitive way of distinguishing among the various soft tissue planes. Average sizes of clitoral structures and average distances between the clitoral complex and other pelvic landmarks have been measured. These measurements have been correlated with female sexual function: a longer distance between the clitoral complex and the vaginal lumen correlates with poorer sexual function, consistent with prior imaging studies. However, whether clitoral size influences function is debatable, so further studies are needed. Physiological investigations have demonstrated that female arousal disorder is unlikely to be due to inadequate genital engorgement. Some consider the brain to be the ultimate sexual organ, and several recent studies have used functional MRI (fMRI) to reveal sexual excitability in the brain. The normal sexual response requires deactivation of the frontal lobe and activation of the instinctual limbic system of the midbrain. As MR technology continues to improve, the mysteries of female sexuality will be further unraveled. © 2015 Wiley Periodicals, Inc.

Functional overestimation due to spatial smoothing of fMRI data.

PubMed

Liu, Peng; Calhoun, Vince; Chen, Zikuan

2017-11-01

Pearson correlation (simply correlation) is a basic technique for neuroimage function analysis. It has been observed that the spatial smoothing may cause functional overestimation, which however remains a lack of complete understanding. Herein, we present a theoretical explanation from the perspective of correlation scale invariance. For a task-evoked spatiotemporal functional dataset, we can extract the functional spatial map by calculating the temporal correlations (tcorr) of voxel timecourses against the task timecourse. From the relationship between image noise level (changed through spatial smoothing) and the tcorr map calculation, we show that the spatial smoothing causes a noise reduction, which in turn smooths the tcorr map and leads to a spatial expansion on neuroactivity blob estimation. Through numerical simulations and subject experiments, we show that the spatial smoothing of fMRI data may overestimate activation spots in the correlation functional map. Our results suggest a small spatial smoothing (with a smoothing kernel with a full width at half maximum (FWHM) of no more than two voxels) on fMRI data processing for correlation-based functional mapping COMPARISON WITH EXISTING METHODS: In extreme noiselessness, the correlation of scale-invariance property defines a meaningless binary tcorr map. In reality, a functional activity blob in a tcorr map is shaped due to the spoilage of image noise on correlative responses. We may reduce data noise level by smoothing processing, which poses a smoothing effect on correlation. This logic allows us to understand the noise dependence and the smoothing effect of correlation-based fMRI data analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Magnetic resonance imaging and spectroscopy of the murine cardiovascular system.

PubMed

Akki, Ashwin; Gupta, Ashish; Weiss, Robert G

2013-03-01

Magnetic resonance imaging (MRI) has emerged as a powerful and reliable tool to noninvasively study the cardiovascular system in clinical practice. Because transgenic mouse models have assumed a critical role in cardiovascular research, technological advances in MRI have been extended to mice over the last decade. These have provided critical insights into cardiac and vascular morphology, function, and physiology/pathophysiology in many murine models of heart disease. Furthermore, magnetic resonance spectroscopy (MRS) has allowed the nondestructive study of myocardial metabolism in both isolated hearts and in intact mice. This article reviews the current techniques and important pathophysiological insights from the application of MRI/MRS technology to murine models of cardiovascular disease.

Magnetic resonance imaging and spectroscopy of the murine cardiovascular system

PubMed Central

Akki, Ashwin; Gupta, Ashish

2013-01-01

Magnetic resonance imaging (MRI) has emerged as a powerful and reliable tool to noninvasively study the cardiovascular system in clinical practice. Because transgenic mouse models have assumed a critical role in cardiovascular research, technological advances in MRI have been extended to mice over the last decade. These have provided critical insights into cardiac and vascular morphology, function, and physiology/pathophysiology in many murine models of heart disease. Furthermore, magnetic resonance spectroscopy (MRS) has allowed the nondestructive study of myocardial metabolism in both isolated hearts and in intact mice. This article reviews the current techniques and important pathophysiological insights from the application of MRI/MRS technology to murine models of cardiovascular disease. PMID:23292717

Visual analysis of variance: a tool for quantitative assessment of fMRI data processing and analysis.

PubMed

McNamee, R L; Eddy, W F

2001-12-01

Analysis of variance (ANOVA) is widely used for the study of experimental data. Here, the reach of this tool is extended to cover the preprocessing of functional magnetic resonance imaging (fMRI) data. This technique, termed visual ANOVA (VANOVA), provides both numerical and pictorial information to aid the user in understanding the effects of various parts of the data analysis. Unlike a formal ANOVA, this method does not depend on the mathematics of orthogonal projections or strictly additive decompositions. An illustrative example is presented and the application of the method to a large number of fMRI experiments is discussed. Copyright 2001 Wiley-Liss, Inc.

A longitudinal model for functional connectivity networks using resting-state fMRI.

PubMed

Hart, Brian; Cribben, Ivor; Fiecas, Mark

2018-06-04

Many neuroimaging studies collect functional magnetic resonance imaging (fMRI) data in a longitudinal manner. However, the current fMRI literature lacks a general framework for analyzing functional connectivity (FC) networks in fMRI data obtained from a longitudinal study. In this work, we build a novel longitudinal FC model using a variance components approach. First, for all subjects' visits, we account for the autocorrelation inherent in the fMRI time series data using a non-parametric technique. Second, we use a generalized least squares approach to estimate 1) the within-subject variance component shared across the population, 2) the baseline FC strength, and 3) the FC's longitudinal trend. Our novel method for longitudinal FC networks seeks to account for the within-subject dependence across multiple visits, the variability due to the subjects being sampled from a population, and the autocorrelation present in fMRI time series data, while restricting the number of parameters in order to make the method computationally feasible and stable. We develop a permutation testing procedure to draw valid inference on group differences in the baseline FC network and change in FC over longitudinal time between a set of patients and a comparable set of controls. To examine performance, we run a series of simulations and apply the model to longitudinal fMRI data collected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Overall, we found no difference in the global FC network between Alzheimer's disease patients and healthy controls, but did find differing local aging patterns in the FC between the left hippocampus and the posterior cingulate cortex. Copyright © 2018 Elsevier Inc. All rights reserved.

Combining self-organizing mapping and supervised affinity propagation clustering approach to investigate functional brain networks involved in motor imagery and execution with fMRI measurements.

PubMed

Zhang, Jiang; Liu, Qi; Chen, Huafu; Yuan, Zhen; Huang, Jin; Deng, Lihua; Lu, Fengmei; Zhang, Junpeng; Wang, Yuqing; Wang, Mingwen; Chen, Liangyin

2015-01-01

Clustering analysis methods have been widely applied to identifying the functional brain networks of a multitask paradigm. However, the previously used clustering analysis techniques are computationally expensive and thus impractical for clinical applications. In this study a novel method, called SOM-SAPC that combines self-organizing mapping (SOM) and supervised affinity propagation clustering (SAPC), is proposed and implemented to identify the motor execution (ME) and motor imagery (MI) networks. In SOM-SAPC, SOM was first performed to process fMRI data and SAPC is further utilized for clustering the patterns of functional networks. As a result, SOM-SAPC is able to significantly reduce the computational cost for brain network analysis. Simulation and clinical tests involving ME and MI were conducted based on SOM-SAPC, and the analysis results indicated that functional brain networks were clearly identified with different response patterns and reduced computational cost. In particular, three activation clusters were clearly revealed, which include parts of the visual, ME and MI functional networks. These findings validated that SOM-SAPC is an effective and robust method to analyze the fMRI data with multitasks.

PET/MRI assessment of the infarcted mouse heart

NASA Astrophysics Data System (ADS)

Buonincontri, Guido; Methner, Carmen; Krieg, Thomas; Hawkes, Robert C.; Adrian Carpenter, T.; Sawiak, Stephen J.

2014-01-01

Heart failure originating from myocardial infarction (MI) is a leading cause of death worldwide. Mouse models of ischaemia and reperfusion injury (I/R) are used to study the effects of novel treatment strategies targeting MI, however staging disease and treatment efficacy is a challenge. Damage and recovery can be assessed on the cellular, tissue or whole-organ scale but these are rarely measured in concert. Here, for the first time, we present data showing measures of injury in infarcted mice using complementary techniques for multi-modal characterisation of the heart. We use in vivo magnetic resonance imaging (MRI) to assess heart function with cine-MRI, hindered perfusion with late gadolinium enhancement imaging and muscular function with displacement encoded with stimulated echoes (DENSE) MRI. These measures are followed by positron emission tomography (PET) with 18-F-fluorodeoxyglucose to assess cellular metabolism. We demonstrate a protocol combining each of these measures for the same animal in the same imaging session and compare how the different markers can be used to quantify cardiac recovery on different scales following injury.

The hippocampal formation participates in novel picture encoding: evidence from functional magnetic resonance imaging.

PubMed Central

Stern, C E; Corkin, S; González, R G; Guimaraes, A R; Baker, J R; Jennings, P J; Carr, C A; Sugiura, R M; Vedantham, V; Rosen, B R

1996-01-01

Considerable evidence exists to support the hypothesis that the hippocampus and related medial temporal lobe structures are crucial for the encoding and storage of information in long-term memory. Few human imaging studies, however, have successfully shown signal intensity changes in these areas during encoding or retrieval. Using functional magnetic resonance imaging (fMRI), we studied normal human subjects while they performed a novel picture encoding task. High-speed echo-planar imaging techniques evaluated fMRI signal changes throughout the brain. During the encoding of novel pictures, statistically significant increases in fMRI signal were observed bilaterally in the posterior hippocampal formation and parahippocampal gyrus and in the lingual and fusiform gyri. To our knowledge, this experiment is the first fMRI study to show robust signal changes in the human hippocampal region. It also provides evidence that the encoding of novel, complex pictures depends upon an interaction between ventral cortical regions, specialized for object vision, and the hippocampal formation and parahippocampal gyrus, specialized for long-term memory. Images Fig. 1 Fig. 3 PMID:8710927

The role of hyperpolarized 129xenon in MR imaging of pulmonary function

PubMed Central

Ebner, Lukas; Kammerman, Jeff; Driehuys, Bastiaan; Schiebler, Mark L.; Cadman, Robert V.; Fain, Sean B.

2016-01-01

In the last two decades, functional imaging of the lungs using hyperpolarized noble gases has entered the clinical stage. Both helium (3 He) and xenon (129Xe) gas have been thoroughly investigated for their ability to assess both the global and regional patterns of lung ventilation. With advances in polarizer technology and the current transition towards the widely available 129Xe gas, this method is ready for translation to the clinic. Currently, hyperpolarized (HP) noble gas lung MRI is limited to selected academic institutions; yet, the promising results from initial clinical trials have drawn the attention of the pulmonary medicine community. HP 129Xe MRI provides not only 3-dimensional ventilation imaging, but also unique capabilities for probing regional lung physiology. In this review article, we aim to (1) provide a brief overview of current ventilation MR imaging techniques, (2) emphasize the role of HP 129Xe MRI within the array of different imaging strategies, (3) discuss the unique imaging possibilities with HP 129Xe MRI, and (4) propose clinical applications. PMID:27707585

Functional Magnetic Resonance Imaging (fMRI), Pre-intraoperative Tractography in Neurosurgery: The Experience of Sant' Andrea Rome University Hospital.

PubMed

D'Andrea, Giancarlo; Trillo', Giuseppe; Picotti, Veronica; Raco, Antonino

2017-01-01

The goal of neurosurgery for cerebral intraparenchymal neoplasms of the eloquent areas is maximal resection with the preservation of normal functions, and minimizing operative risk and postoperative morbidity. Currently, modern technological advances in neuroradiological tools, neuronavigation, and intraoperative magnetic resonance imaging (MRI) have produced great improvements in postoperative morbidity after the surgery of cerebral eloquent areas. The integration of preoperative functional MRI (fMRI), intraoperative MRI (volumetric and diffusion tensor imaging [DTI]), and neuronavigation, defined as "functional neuronavigation" has improved the intraoperative detection of the eloquent areas. We reviewed 142 patients operated between 2004 and 2010 for intraparenchymal neoplasms involving or close to one or more major white matter tracts (corticospinal tract [CST], arcuate fasciculus [AF], optic radiation). All the patients underwent neurosurgery in a BrainSUITE equipped with a 1.5 T MR scanner and were preoperatively studied with fMRI and DTI for tractography for surgical planning. The patients underwent MRI and DTI during surgery after dural opening, after the gross total resection close to the white matter tracts, and at the end of the procedure. We evaluated the impact of fMRI on surgical planning and on the selection of the entry point on the cortical surface. We also evaluated the impact of preoperative and intraoperative DTI, in order to modify the surgical approach, to define the borders of resection, and to correlate this modality with subcortical neurophysiological monitoring. We evaluated the impact of the preoperative fMRI by intraoperative neurophysiological monitoring, performing "neuronavigational" brain mapping, following its data to localize the previously elicited areas after brain shift correction by intraoperative MRI. The mean age of the 142 patients (89 M/53 F) was 59.1 years and the lesion involved the CST in 66 patients (57 %), the language pathways in 24 (21 %), and the optic radiations in 25 (22 %). The integration of tractographic data into the volumetric dataset for neuronavigation was technically possible in all cases. In all patients intraoperative DTI demonstrated a shift of the bundle position caused by the surgical procedure; its dislocation was both outward and inward in the range of +6 mm and -2 mm. We found a high concordance between fMRI/DTI and intraoperative brain mapping; their combination improves the sensitivity of each technique, reducing pitfalls and so defining "functional neuronavigation", increasing the definition of eloquent areas and also reducing the time of surgery.

Virtual phantom magnetic resonance imaging (ViP MRI) on a clinical MRI platform.

PubMed

Saint-Jalmes, Hervé; Bordelois, Alejandro; Gambarota, Giulio

2018-01-01

The purpose of this study was to implement Virtual Phantom Magnetic Resonance Imaging (ViP MRI), a technique that allows for generating reference signals in MR images using radiofrequency (RF) signals, on a clinical MR system and to test newly designed virtual phantoms. MRI experiments were conducted on a 1.5 T MRI scanner. Electromagnetic modelling of the ViP system was done using the principle of reciprocity. The ViP RF signals were generated using a compact waveform generator (dimensions of 26 cm × 18 cm × 16 cm), connected to a homebuilt 25 mm-diameter RF coil. The ViP RF signals were transmitted to the MRI scanner bore, simultaneously with the acquisition of the signal from the object of interest. Different types of MRI data acquisition (2D and 3D gradient-echo) as well as different phantoms, including the Shepp-Logan phantom, were tested. Furthermore, a uniquely designed virtual phantom - in the shape of a grid - was generated; this newly proposed phantom allows for the investigations of the vendor distortion correction field. High quality MR images of virtual phantoms were obtained. An excellent agreement was found between the experimental data and the inverse cube law, which was the expected functional dependence obtained from the electromagnetic modelling of the ViP system. Short-term time stability measurements yielded a coefficient of variation in the signal intensity over time equal to 0.23% and 0.13% for virtual and physical phantom, respectively. MR images of the virtual grid-shaped phantom were reconstructed with the vendor distortion correction; this allowed for a direct visualization of the vendor distortion correction field. Furthermore, as expected from the electromagnetic modelling of the ViP system, a very compact coil (diameter ~ cm) and very small currents (intensity ~ mA) were sufficient to generate a signal comparable to that of physical phantoms in MRI experiments. The ViP MRI technique was successfully implemented on a clinical MR system. One of the major advantages of ViP MRI over previous approaches is that the generation and transmission of RF signals can be achieved with a self-contained apparatus. As such, the ViP MRI technique is transposable to different platforms (preclinical and clinical) of different vendors. It is also shown here that ViP MRI could be used to generate signals whose characteristics cannot be reproduced by physical objects. This could be exploited to assess MRI system properties, such as the vendor distortion correction field. © 2017 American Association of Physicists in Medicine.

Sci-Fri AM: MRI and Diagnostic Imaging - 05: Comparison of Input Function Measurements from DCE and MOLLI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Majtenyi, Nicholas; Juma, Hanif; Klein, Ran

Dynamic contrast-enhanced (DCE)-MRI is a technique for obtaining tissue hemodynamic information (e.g. tumours). Despite widespread clinical application of DCE-MRI, the technique suffers from a lack of standardization and accuracy, especially with respect to the concentration-versus-time of gadolinium (Gd) in feeding arteries (the input function, IF). MR phase has a linear quantitative relationship with Gd concentration ([Gd]), making it ideal for measuring the first-pass of the IF, but is not considered accurate in the steady-state washout. Modified Look-Locker Inversion Recovery (MOLLI) is a fast and accurate method to measure T1 and has been validated to quantify typical [Gd] ranges experienced inmore » the washout of the IF. Two different methods to measure the IF for DCE-MRI were compared: 1) conventional phase-versus-time (“Phase-only”) and 2) phase-versus-time combined with pre- and post-DCE MOLLI T1 measurements (“Phase+MOLLI”). The IF obtained from Phase+MOLLI was calculated from MOLLI T1 values and known relaxivity, then added to the Phase-only acquisition with the washout IF subtracted. A significant difference was observed between IF values for [Gd] between the Phase-only and Phase+MOLLI acquisitions (P = 0.03). To ensure the IFs from MOLLI T1s were accurate, it was compared to [Gd] obtained from “gold-standard” inversion recovery (IR). MOLLI showed excellent agreement with IR when imaged in static phantoms (r{sup 2} = 0.997, P = 0.001). The Phase+MOLLI IF was more accurate than the Phase-only IF in measuring the washout. The Phase+MOLLI acquisition may therefore provide a DCE-MRI reference standard that could lead to better clinical diagnoses.« less

Identifying Rodent Resting-State Brain Networks with Independent Component Analysis

PubMed Central

Bajic, Dusica; Craig, Michael M.; Mongerson, Chandler R. L.; Borsook, David; Becerra, Lino

2017-01-01

Rodent models have opened the door to a better understanding of the neurobiology of brain disorders and increased our ability to evaluate novel treatments. Resting-state functional magnetic resonance imaging (rs-fMRI) allows for in vivo exploration of large-scale brain networks with high spatial resolution. Its application in rodents affords researchers a powerful translational tool to directly assess/explore the effects of various pharmacological, lesion, and/or disease states on known neural circuits within highly controlled settings. Integration of animal and human research at the molecular-, systems-, and behavioral-levels using diverse neuroimaging techniques empowers more robust interrogations of abnormal/ pathological processes, critical for evolving our understanding of neuroscience. We present a comprehensive protocol to evaluate resting-state brain networks using Independent Component Analysis (ICA) in rodent model. Specifically, we begin with a brief review of the physiological basis for rs-fMRI technique and overview of rs-fMRI studies in rodents to date, following which we provide a robust step-by-step approach for rs-fMRI investigation including data collection, computational preprocessing, and brain network analysis. Pipelines are interwoven with underlying theory behind each step and summarized methodological considerations, such as alternative methods available and current consensus in the literature for optimal results. The presented protocol is designed in such a way that investigators without previous knowledge in the field can implement the analysis and obtain viable results that reliably detect significant differences in functional connectivity between experimental groups. Our goal is to empower researchers to implement rs-fMRI in their respective fields by incorporating technical considerations to date into a workable methodological framework. PMID:29311770

Principal and independent component analysis of concomitant functional near infrared spectroscopy and magnetic resonance imaging data

NASA Astrophysics Data System (ADS)

Schelkanova, Irina; Toronov, Vladislav

2011-07-01

Although near infrared spectroscopy (NIRS) is now widely used both in emerging clinical techniques and in cognitive neuroscience, the development of the apparatuses and signal processing methods for these applications is still a hot research topic. The main unresolved problem in functional NIRS is the separation of functional signals from the contaminations by systemic and local physiological fluctuations. This problem was approached by using various signal processing methods, including blind signal separation techniques. In particular, principal component analysis (PCA) and independent component analysis (ICA) were applied to the data acquired at the same wavelength and at multiple sites on the human or animal heads during functional activation. These signal processing procedures resulted in a number of principal or independent components that could be attributed to functional activity but their physiological meaning remained unknown. On the other hand, the best physiological specificity is provided by broadband NIRS. Also, a comparison with functional magnetic resonance imaging (fMRI) allows determining the spatial origin of fNIRS signals. In this study we applied PCA and ICA to broadband NIRS data to distill the components correlating with the breath hold activation paradigm and compared them with the simultaneously acquired fMRI signals. Breath holding was used because it generates blood carbon dioxide (CO2) which increases the blood-oxygen-level-dependent (BOLD) signal as CO2 acts as a cerebral vasodilator. Vasodilation causes increased cerebral blood flow which washes deoxyhaemoglobin out of the cerebral capillary bed thus increasing both the cerebral blood volume and oxygenation. Although the original signals were quite diverse, we found very few different components which corresponded to fMRI signals at different locations in the brain and to different physiological chromophores.

Biomedical Investigations with Laser-Polarized Noble Gas Magnetic Resonance

NASA Technical Reports Server (NTRS)

Walsworth, Ronald L.

2001-01-01

We are developing laser-polarized noble gas nuclear magnetic resonance (NMR) as a novel biomedical imaging tool for ground-based and eventually space-based application. This emerging multidisciplinary technology enables high-resolution gas-space magnetic resonance imaging (MRI) (e.g., of lung ventilation) as well as studies of tissue perfusion. In addition, laser-polarized noble gases (He-3 and Xe-129) do not require a large magnetic field for sensitive detection, opening the door to practical MRI at very low magnetic fields with an open, lightweight, and low-power device. We are pursuing two specific aims in this research. The first aim is to develop a low-field (< 0.01 T) instrument for noble gas MRI of humans, and the second aim is to develop functional MRI of the lung using laser-polarized Xe-129 and related techniques.

A validation of event-related FMRI comparisons between users of cocaine, nicotine, or cannabis and control subjects.

PubMed

Murphy, Kevin; Dixon, Veronica; LaGrave, Kathleen; Kaufman, Jacqueline; Risinger, Robert; Bloom, Alan; Garavan, Hugh

2006-07-01

Noninvasive brain imaging techniques are a powerful tool for researching the effects of drug abuse on brain activation measures. However, because many drugs have direct vascular effects, the validity of techniques that depend on blood flow measures as a reflection of neuronal activity may be called into question. This may be of particular concern in event-related functional magnetic resonance imaging (fMRI), where current analytic techniques search for a specific shape in the hemodynamic response to neuronal activity. To investigate possible alterations in task-related activation as a result of drug abuse, fMRI scans were conducted on subjects in four groups as they performed a simple event-related finger-tapping task: users of cocaine, nicotine, or cannabis and control subjects. Activation measures, as determined by two different analytic methods, did not differ between the groups. A comparison between an intravenous saline and an intravenous cocaine condition in cocaine users found a similar null result. Further in-depth analyses of the shape of the hemodynamic responses in each group also showed no differences. This study demonstrates that drug groups may be compared with control subjects using event-related fMRI without the need for any post hoc procedures to correct for possible drug-induced cardiovascular alterations. Thus, fMRI activation differences reported between these drug groups can be more confidently interpreted as reflecting neuronal differences.

Delineation of early brain development from fetuses to infants with diffusion MRI and beyond.

PubMed

Ouyang, Minhui; Dubois, Jessica; Yu, Qinlin; Mukherjee, Pratik; Huang, Hao

2018-04-12

Dynamic macrostructural and microstructural changes take place from the mid-fetal stage to 2 years after birth. Delineating structural changes of the brain during early development provides new insights into the complicated processes of both typical development and the pathological mechanisms underlying various psychiatric and neurological disorders including autism, attention deficit hyperactivity disorder and schizophrenia. Decades of histological studies have identified strong spatial and functional maturation gradients in human brain gray and white matter. The recent improvements in magnetic resonance imaging (MRI) techniques, especially diffusion MRI (dMRI), relaxometry imaging, and magnetization transfer imaging (MTI) have provided unprecedented opportunities to non-invasively quantify and map the early developmental changes at whole brain and regional levels. Here, we review the recent advances in understanding early brain structural development during the second half of gestation and the first two postnatal years using modern MR techniques. Specifically, we review studies that delineate the emergence and microstructural maturation of white matter tracts, as well as dynamic mapping of inhomogeneous cortical microstructural organization unique to fetuses and infants. These imaging studies converge into maturational curves of MRI measurements that are distinctive across different white matter tracts and cortical regions. Furthermore, contemporary models offering biophysical interpretations of the dMRI-derived measurements are illustrated to infer the underlying microstructural changes. Collectively, this review summarizes findings that contribute to charting spatiotemporally heterogeneous gray and white matter structural development, offering MRI-based biomarkers of typical brain development and setting the stage for understanding aberrant brain development in neurodevelopmental disorders. Copyright © 2018 Elsevier Inc. All rights reserved.

Advanced flow MRI: emerging techniques and applications

PubMed Central

Markl, M.; Schnell, S.; Wu, C.; Bollache, E.; Jarvis, K.; Barker, A. J.; Robinson, J. D.; Rigsby, C. K.

2016-01-01

Magnetic resonance imaging (MRI) techniques provide non-invasive and non-ionising methods for the highly accurate anatomical depiction of the heart and vessels throughout the cardiac cycle. In addition, the intrinsic sensitivity of MRI to motion offers the unique ability to acquire spatially registered blood flow simultaneously with the morphological data, within a single measurement. In clinical routine, flow MRI is typically accomplished using methods that resolve two spatial dimensions in individual planes and encode the time-resolved velocity in one principal direction, typically oriented perpendicular to the two-dimensional (2D) section. This review describes recently developed advanced MRI flow techniques, which allow for more comprehensive evaluation of blood flow characteristics, such as real-time flow imaging, 2D multiple-venc phase contrast MRI, four-dimensional (4D) flow MRI, quantification of complex haemodynamic properties, and highly accelerated flow imaging. Emerging techniques and novel applications are explored. In addition, applications of these new techniques for the improved evaluation of cardiovascular (aorta, pulmonary arteries, congenital heart disease, atrial fibrillation, coronary arteries) as well as cerebrovascular disease (intra-cranial arteries and veins) are presented. PMID:26944696

Integrated SSFP for functional brain mapping at 7 T with reduced susceptibility artifact

NASA Astrophysics Data System (ADS)

Sun, Kaibao; Xue, Rong; Zhang, Peng; Zuo, Zhentao; Chen, Zhongwei; Wang, Bo; Martin, Thomas; Wang, Yi; Chen, Lin; He, Sheng; Wang, Danny J. J.

2017-03-01

Balanced steady-state free precession (bSSFP) offers an alternative and potentially important tool to the standard gradient-echo echo-planar imaging (GE-EPI) for functional MRI (fMRI). Both passband and transition band based bSSFP have been proposed for fMRI. The applications of these methods, however, are limited by banding artifacts due to the sensitivity of bSSFP signal to off-resonance effects. In this article, a unique case of the SSFP-FID sequence, termed integrated-SSFP or iSSFP, was proposed to overcome the obstacle by compressing the SSFP profile into the width of a single voxel. The magnitude of the iSSFP signal was kept constant irrespective of frequency shift. Visual stimulation studies were performed to demonstrate the feasibility of fMRI using iSSFP at 7 T with flip angles of 4° and 25°, compared to standard bSSFP and gradient echo (GRE) imaging. The signal changes for the complex iSSFP signal in activated voxels were 2.48 ± 0.53 (%) and 2.96 ± 0.87 (%) for flip angles (FA) of 4° and 25° respectively at the TR of 9.88 ms. Simultaneous multi-slice acquisition (SMS) with the CAIPIRIHNA technique was carried out with iSSFP scanning to detect the anterior temporal lobe activation using a semantic processing task fMRI, compared with standard 2D GE-EPI. This study demonstrates the feasibility of iSSFP for fMRI with reduced susceptibility artifacts, while maintaining robust functional contrast at 7 T.

Functional MR imaging of the cervical spinal cord by use of electrical stimulation at LI4 (Hegu).

PubMed

Wang, W D; Kong, K M; Xiao, Y Y; Wang, X J; Liang, B; Qi, W L; Wu, R H

2006-01-01

The purpose is to investigate the cervical spinal cord mapping on electrical stimulation at LI4 (Hegu) by using 'signal enhancement by extravascular water protons' (SEEP)-fMRI, and to establish the response of acupoint-stimulation in spinal cord. Three healthy volunteers were underwent low-frequency electrical stimulation at LI4. Meanwhile, a single-shot fast spin-echo (SSFSE) sequence was used to perform functional MR imaging on a 1.5 T GE Signa MR system. Cord activation was measured both in the sagittal and transverse imaging planes and then analyzed by AFNI (analysis of functional neuroimages) system. In the sagittal view, two subjects had an fMRI response in the cervical spinal cord upon electrical stimulation at LI4. The localizations of the segmental fMRI activation are both at C6 through T1 and C2/3 cervical spinal cord level. In the transverse imaging plane, significant fMRI responses could be measured in the last subjects locating at C6/7 segment, the cross-sectional localization of the activity measured in the spinal cord was most in terms of the ipsilateral posterior direction. It is concluded that the fMRI technique can be used for detecting with activity in the human cervical spinal cord by a single-shot fast spin-echo sequence on a 1.5 T GE clinical system. Investigating the acupoint-stimulation response in the spinal cord using the spinal fMRI will be helpful for the further discussion on the mechanisms of acupuncture to spinal cord diseases.

Structured Illumination Diffuse Optical Tomography for Mouse Brain Imaging

NASA Astrophysics Data System (ADS)

Reisman, Matthew David

As advances in functional magnetic resonance imaging (fMRI) have transformed the study of human brain function, they have also widened the divide between standard research techniques used in humans and those used in mice, where high quality images are difficult to obtain using fMRI given the small volume of the mouse brain. Optical imaging techniques have been developed to study mouse brain networks, which are highly valuable given the ability to study brain disease treatments or development in a controlled environment. A planar imaging technique known as optical intrinsic signal (OIS) imaging has been a powerful tool for capturing functional brain hemodynamics in rodents. Recent wide field-of-view implementations of OIS have provided efficient maps of functional connectivity from spontaneous brain activity in mice. However, OIS requires scalp retraction and is limited to imaging a 2-dimensional view of superficial cortical tissues. Diffuse optical tomography (DOT) is a non-invasive, volumetric neuroimaging technique that has been valuable for bedside imaging of patients in the clinic, but previous DOT systems for rodent neuroimaging have been limited by either sparse spatial sampling or by slow speed. My research has been to develop diffuse optical tomography for whole brain mouse neuroimaging by expanding previous techniques to achieve high spatial sampling using multiple camera views for detection and high speed using structured illumination sources. I have shown the feasibility of this method to perform non-invasive functional neuroimaging in mice and its capabilities of imaging the entire volume of the brain. Additionally, the system has been built with a custom, flexible framework to accommodate the expansion to imaging multiple dynamic contrasts in the brain and populations that were previously difficult or impossible to image, such as infant mice and awake mice. I have contributed to preliminary feasibility studies of these more advanced techniques using OIS, which can now be carried out using the structured illumination diffuse optical tomography technique to perform longitudinal, non-invasive studies of the whole volume of the mouse brain.

Sample-Poor Estimation of Order and Common Signal Subspace with Application to Fusion of Medical Imaging Data

PubMed Central

Levin-Schwartz, Yuri; Song, Yang; Schreier, Peter J.; Calhoun, Vince D.; Adalı, Tülay

2016-01-01

Due to their data-driven nature, multivariate methods such as canonical correlation analysis (CCA) have proven very useful for fusion of multimodal neurological data. However, being able to determine the degree of similarity between datasets and appropriate order selection are crucial to the success of such techniques. The standard methods for calculating the order of multimodal data focus only on sources with the greatest individual energy and ignore relations across datasets. Additionally, these techniques as well as the most widely-used methods for determining the degree of similarity between datasets assume sufficient sample support and are not effective in the sample-poor regime. In this paper, we propose to jointly estimate the degree of similarity between datasets and their order when few samples are present using principal component analysis and canonical correlation analysis (PCA-CCA). By considering these two problems simultaneously, we are able to minimize the assumptions placed on the data and achieve superior performance in the sample-poor regime compared to traditional techniques. We apply PCA-CCA to the pairwise combinations of functional magnetic resonance imaging (fMRI), structural magnetic resonance imaging (sMRI), and electroencephalogram (EEG) data drawn from patients with schizophrenia and healthy controls while performing an auditory oddball task. The PCA-CCA results indicate that the fMRI and sMRI datasets are the most similar, whereas the sMRI and EEG datasets share the least similarity. We also demonstrate that the degree of similarity obtained by PCA-CCA is highly predictive of the degree of significance found for components generated using CCA. PMID:27039696

Exploring brainstem function in multiple sclerosis by combining brainstem reflexes, evoked potentials, clinical and MRI investigations.

PubMed

Magnano, Immacolata; Pes, Giovanni Mario; Pilurzi, Giovanna; Cabboi, Maria Paola; Ginatempo, Francesca; Giaconi, Elena; Tolu, Eusebio; Achene, Antonio; Salis, Antonio; Rothwell, John C; Conti, Maurizio; Deriu, Franca

2014-11-01

To investigate vestibulo-masseteric (VMR), acoustic-masseteric (AMR), vestibulo-collic (VCR) and trigemino-collic (TCR) reflexes in patients with multiple sclerosis (MS); to relate abnormalities of brainstem reflexes (BSRs) to multimodal evoked potentials (EPs), clinical and Magnetic Resonance Imaging (MRI) findings. Click-evoked VMR, AMR and VCR were recorded from active masseter and sternocleidomastoid muscles, respectively; TCR was recorded from active sternocleidomastoid muscles, following electrical stimulation of the infraorbital nerve. EPs and MRI were performed with standard techniques. Frequencies of abnormal BSRs were: VMR 62.1%, AMR 55.1%, VCR 25.9%, TCR 58.6%. Brainstem dysfunction was identified by these tests, combined into a four-reflex battery, in 86.9% of cases, by EPs in 82.7%, MRI in 71.7% and clinical examination in 37.7% of cases. The sensitivity of paired BSRs/EPs (93.3%) was significantly higher than combined MRI/clinical testing (70%) in patients with disease duration ⩽6.4years. BSR alterations significantly correlated with clinical, EP and MRI findings. The four-BSR battery effectively increases the performance of standard EPs in early detection of brainstem impairment, otherwise undetected by clinical examination and neuroimaging. Multiple BSR assessment usefully supplements conventional testing and monitoring of brainstem function in MS, especially in newly diagnosed patients. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project.

PubMed

Bastiani, Matteo; Andersson, Jesper L R; Cordero-Grande, Lucilio; Murgasova, Maria; Hutter, Jana; Price, Anthony N; Makropoulos, Antonios; Fitzgibbon, Sean P; Hughes, Emer; Rueckert, Daniel; Victor, Suresh; Rutherford, Mary; Edwards, A David; Smith, Stephen M; Tournier, Jacques-Donald; Hajnal, Joseph V; Jbabdi, Saad; Sotiropoulos, Stamatios N

2018-05-28

The developing Human Connectome Project is set to create and make available to the scientific community a 4-dimensional map of functional and structural cerebral connectivity from 20 to 44 weeks post-menstrual age, to allow exploration of the genetic and environmental influences on brain development, and the relation between connectivity and neurocognitive function. A large set of multi-modal MRI data from fetuses and newborn infants is currently being acquired, along with genetic, clinical and developmental information. In this overview, we describe the neonatal diffusion MRI (dMRI) image processing pipeline and the structural connectivity aspect of the project. Neonatal dMRI data poses specific challenges, and standard analysis techniques used for adult data are not directly applicable. We have developed a processing pipeline that deals directly with neonatal-specific issues, such as severe motion and motion-related artefacts, small brain sizes, high brain water content and reduced anisotropy. This pipeline allows automated analysis of in-vivo dMRI data, probes tissue microstructure, reconstructs a number of major white matter tracts, and includes an automated quality control framework that identifies processing issues or inconsistencies. We here describe the pipeline and present an exemplar analysis of data from 140 infants imaged at 38-44 weeks post-menstrual age. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

The role of long-range connectivity for the characterization of the functional-anatomical organization of the cortex.

PubMed

Knösche, Thomas R; Tittgemeyer, Marc

2011-01-01

This review focuses on the role of long-range connectivity as one element of brain structure that is of key importance for the functional-anatomical organization of the cortex. In this context, we discuss the putative guiding principles for mapping brain function and structure onto the cortical surface. Such mappings reveal a high degree of functional-anatomical segregation. Given that brain regions frequently maintain characteristic connectivity profiles and the functional repertoire of a cortical area is closely related to its anatomical connections, long-range connectivity may be used to define segregated cortical areas. This methodology is called connectivity-based parcellation. Within this framework, we investigate different techniques to estimate connectivity profiles with emphasis given to non-invasive methods based on diffusion magnetic resonance imaging (dMRI) and diffusion tractography. Cortical parcellation is then defined based on similarity between diffusion tractograms, and different clustering approaches are discussed. We conclude that the use of non-invasively acquired connectivity estimates to characterize the functional-anatomical organization of the brain is a valid, relevant, and necessary endeavor. Current and future developments in dMRI technology, tractography algorithms, and models of the similarity structure hold great potential for a substantial improvement and enrichment of the results of the technique.

Statistical inference of dynamic resting-state functional connectivity using hierarchical observation modeling.

PubMed

Sojoudi, Alireza; Goodyear, Bradley G

2016-12-01

Spontaneous fluctuations of blood-oxygenation level-dependent functional magnetic resonance imaging (BOLD fMRI) signals are highly synchronous between brain regions that serve similar functions. This provides a means to investigate functional networks; however, most analysis techniques assume functional connections are constant over time. This may be problematic in the case of neurological disease, where functional connections may be highly variable. Recently, several methods have been proposed to determine moment-to-moment changes in the strength of functional connections over an imaging session (so called dynamic connectivity). Here a novel analysis framework based on a hierarchical observation modeling approach was proposed, to permit statistical inference of the presence of dynamic connectivity. A two-level linear model composed of overlapping sliding windows of fMRI signals, incorporating the fact that overlapping windows are not independent was described. To test this approach, datasets were synthesized whereby functional connectivity was either constant (significant or insignificant) or modulated by an external input. The method successfully determines the statistical significance of a functional connection in phase with the modulation, and it exhibits greater sensitivity and specificity in detecting regions with variable connectivity, when compared with sliding-window correlation analysis. For real data, this technique possesses greater reproducibility and provides a more discriminative estimate of dynamic connectivity than sliding-window correlation analysis. Hum Brain Mapp 37:4566-4580, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Resting state functional connectivity: its physiological basis and application in neuropharmacology.

PubMed

Lu, Hanbing; Stein, Elliot A

2014-09-01

Brain structures do not work in isolation; they work in concert to produce sensory perception, motivation and behavior. Systems-level network activity can be investigated by resting state magnetic resonance imaging (rsMRI), an emerging neuroimaging technique that assesses the synchrony of the brain's ongoing spontaneous activity. Converging evidence reveals that rsMRI is able to consistently identify distinct spatiotemporal patterns of large-scale brain networks. Dysregulation within and between these networks has been implicated in a number of neurodegenerative and neuropsychiatric disorders, including Alzheimer's disease and drug addiction. Despite wide application of this approach in systems neuroscience, the physiological basis of these fluctuations remains incompletely understood. Here we review physiological studies in electrical, metabolic and hemodynamic fluctuations that are most pertinent to the rsMRI signal. We also review recent applications to neuropharmacology - specifically drug effects on resting state fluctuations. We speculate that the mechanisms governing spontaneous fluctuations in regional oxygenation availability likely give rise to the observed rsMRI signal. We conclude by identifying several open questions surrounding this technique. This article is part of the Special Issue Section entitled 'Neuroimaging in Neuropharmacology'. Published by Elsevier Ltd.

Higher Resolution and Faster MRI of 31Phosphorus in Bone

NASA Astrophysics Data System (ADS)

Frey, Merideth; Barrett, Sean; Sethna, Zachary; Insogna, Karl; Vanhouten, Joshua

2013-03-01

Probing the internal composition of bone on the sub-100 μm length scale is important to study normal features and to look for signs of disease. However, few useful non-destructive techniques are available to evaluate changes in the bone mineral chemical structure and functional micro-architecture on the interior of bones. MRI would be an excellent candidate, but bone is a particularly challenging tissue to study given the relatively low water density, wider linewidths of its solid components leading to low spatial resolution, and the long imaging time compared to conventional 1H MRI. Our lab has recently made advances in obtaining high spatial resolution (sub-400 μm)3 three-dimensional 31Phosphorus MRI of bone through use of the quadratic echo line-narrowing sequence (1). In this talk, we describe our current results using proton decoupling to push this technique even further towards the factor of 1000 increase in spatial resolution imposed by fundamental limits. We also discuss our work to speed up imaging through novel, faster reconstruction algorithms that can reconstruct the desired image from very sparse data sets. (1) M. Frey, et al. PNAS 109: 5190 (2012).

A New Paradigm for Individual Subject Language Mapping: Movie-Watching fMRI.

PubMed

Tie, Yanmei; Rigolo, Laura; Ozdemir Ovalioglu, Aysegul; Olubiyi, Olutayo; Doolin, Kelly L; Mukundan, Srinivasan; Golby, Alexandra J

2015-01-01

Functional MRI (fMRI) based on language tasks has been used in presurgical language mapping in patients with lesions in or near putative language areas. However, if patients have difficulty performing the tasks due to neurological deficits, it leads to unreliable or noninterpretable results. In this study, we investigate the feasibility of using a movie-watching fMRI for language mapping. A 7-minute movie clip with contrasting speech and nonspeech segments was shown to 22 right-handed healthy subjects. Based on all subjects' language functional regions-of-interest, 6 language response areas were defined, within which a language response model (LRM) was derived by extracting the main temporal activation profile. Using a leave-one-out procedure, individuals' language areas were identified as the areas that expressed highly correlated temporal responses with the LRM derived from an independent group of subjects. Compared with an antonym generation task-based fMRI, the movie-watching fMRI generated language maps with more localized activations in the left frontal language area, larger activations in the left temporoparietal language area, and significant activations in their right-hemisphere homologues. Results of 2 brain tumor patients' movie-watching fMRI using the LRM derived from the healthy subjects indicated its ability to map putative language areas; while their task-based fMRI maps were less robust and noisier. These results suggest that it is feasible to use this novel "task-free" paradigm as a complementary tool for fMRI language mapping when patients cannot perform the tasks. Its deployment in more neurosurgical patients and validation against gold-standard techniques need further investigation. Copyright © 2015 by the American Society of Neuroimaging.

Improved sparse decomposition based on a smoothed L0 norm using a Laplacian kernel to select features from fMRI data.

PubMed

Zhang, Chuncheng; Song, Sutao; Wen, Xiaotong; Yao, Li; Long, Zhiying

2015-04-30

Feature selection plays an important role in improving the classification accuracy of multivariate classification techniques in the context of fMRI-based decoding due to the "few samples and large features" nature of functional magnetic resonance imaging (fMRI) data. Recently, several sparse representation methods have been applied to the voxel selection of fMRI data. Despite the low computational efficiency of the sparse representation methods, they still displayed promise for applications that select features from fMRI data. In this study, we proposed the Laplacian smoothed L0 norm (LSL0) approach for feature selection of fMRI data. Based on the fast sparse decomposition using smoothed L0 norm (SL0) (Mohimani, 2007), the LSL0 method used the Laplacian function to approximate the L0 norm of sources. Results of the simulated and real fMRI data demonstrated the feasibility and robustness of LSL0 for the sparse source estimation and feature selection. Simulated results indicated that LSL0 produced more accurate source estimation than SL0 at high noise levels. The classification accuracy using voxels that were selected by LSL0 was higher than that by SL0 in both simulated and real fMRI experiment. Moreover, both LSL0 and SL0 showed higher classification accuracy and required less time than ICA and t-test for the fMRI decoding. LSL0 outperformed SL0 in sparse source estimation at high noise level and in feature selection. Moreover, LSL0 and SL0 showed better performance than ICA and t-test for feature selection. Copyright © 2015 Elsevier B.V. All rights reserved.

A new paradigm for individual subject language mapping: Movie-watching fMRI

PubMed Central

Tie, Yanmei; Rigolo, Laura; Ovalioglu, Aysegul Ozdemir; Olubiyi, Olutayo; Doolin, Kelly L.; Mukundan, Srinivasan; Golby, Alexandra J.

2015-01-01

Background Functional MRI (fMRI) based on language tasks has been used in pre-surgical language mapping in patients with lesions in or near putative language areas. However, if the patients have difficulty performing the tasks due to neurological deficits, it leads to unreliable or non-interpretable results. In this study, we investigate the feasibility of using a movie-watching fMRI for language mapping. Methods A 7-min movie clip with contrasting speech and non-speech segments was shown to 22 right-handed healthy subjects. Based on all subjects' language functional regions-of-interest, six language response areas were defined, within which a language response model (LRM) was derived by extracting the main temporal activation profile. Using a leave-one-out procedure, individuals' language areas were identified as the areas that expressed highly correlated temporal responses with the LRM derived from an independent group of subjects. Results Compared with an antonym generation task-based fMRI, the movie-watching fMRI generated language maps with more localized activations in the left frontal language area, larger activations in the left temporoparietal language area, and significant activations in their right-hemisphere homologues. Results of two brain tumor patients' movie-watching fMRI using the LRM derived from the healthy subjects indicated its ability to map putative language areas; while their task-based fMRI maps were less robust and noisier. Conclusions These results suggest that it is feasible to use this novel “task-free” paradigm as a complementary tool for fMRI language mapping when patients cannot perform the tasks. Its deployment in more neurosurgical patients and validation against gold-standard techniques need further investigation. PMID:25962953

Image-based computational fluid dynamics in blood vessel models: toward developing a prognostic tool to assess cardiovascular function changes in prolonged space flights

NASA Astrophysics Data System (ADS)

Chatzimavroudis, George P.; Spirka, Thomas A.; Setser, Randolph M.; Myers, Jerry G.

2005-04-01

One of NASA"s objectives is to be able to perform a complete pre-flight evaluation of possible cardiovascular changes in astronauts scheduled for prolonged space missions. Blood flow is an important component of cardiovascular function. Lately, attention has focused on using computational fluid dynamics (CFD) to analyze flow with realistic vessel geometries. MRI can provide detailed geometrical information and is the only clinical technique to measure all three spatial velocity components. The objective of this study was to investigate the reliability of MRI-based model reconstruction for CFD simulations. An aortic arch model and a carotid bifurcation model were scanned in a 1.5T MRI scanner. Axial MRI acquisitions provided images for geometry reconstruction using different resolution settings. The vessel walls were identified and the geometry was reconstructed using existing software. The geometry was then imported into a commercial CFD package for meshing and numerical solution. MRI velocity acquisitions provided true inlet boundary conditions for steady flow, as well as three-directional velocity data at several locations. In addition, an idealized version of each geometry was created from the model drawings. Contour and vector plots of the velocity showed identical features between the MRI velocity data, the MRI-based CFD data, and the idealized-geometry CFD data, with mean differences <10%. CFD results from different MRI resolution settings did not show significant differences (<5%). This study showed quantitatively that reliable CFD simulations can be performed in models reconstructed from MRI acquisitions and gives evidence that a future, subject-specific, computational evaluation of the cardiovascular system is possible.

Identifying relevant biomarkers of brain injury from structural MRI: Validation using automated approaches in children with unilateral cerebral palsy

PubMed Central

Dowson, Nicholas; Doecke, James; Fiori, Simona; Bradley, Andrew P.; Boyd, Roslyn N.; Rose, Stephen

2017-01-01

Previous studies have proposed that the early elucidation of brain injury from structural Magnetic Resonance Images (sMRI) is critical for the clinical assessment of children with cerebral palsy (CP). Although distinct aetiologies, including cortical maldevelopments, white and grey matter lesions and ventricular enlargement, have been categorised, these injuries are commonly only assessed in a qualitative fashion. As a result, sMRI remains relatively underexploited for clinical assessments, despite its widespread use. In this study, several automated and validated techniques to automatically quantify these three classes of injury were generated in a large cohort of children (n = 139) aged 5–17, including 95 children diagnosed with unilateral CP. Using a feature selection approach on a training data set (n = 97) to find severity of injury biomarkers predictive of clinical function (motor, cognitive, communicative and visual function), cortical shape and regional lesion burden were most often chosen associated with clinical function. Validating the best models on the unseen test data (n = 42), correlation values ranged between 0.545 and 0.795 (p<0.008), indicating significant associations with clinical function. The measured prevalence of injury, including ventricular enlargement (70%), white and grey matter lesions (55%) and cortical malformations (30%), were similar to the prevalence observed in other cohorts of children with unilateral CP. These findings support the early characterisation of injury from sMRI into previously defined aetiologies as part of standard clinical assessment. Furthermore, the strong and significant association between quantifications of injury observed on structural MRI and multiple clinical scores accord with empirically established structure-function relationships. PMID:28763455

Non-destructive analysis of sensory traits of dry-cured loins by MRI-computer vision techniques and data mining.

PubMed

Caballero, Daniel; Antequera, Teresa; Caro, Andrés; Ávila, María Del Mar; G Rodríguez, Pablo; Perez-Palacios, Trinidad

2017-07-01

Magnetic resonance imaging (MRI) combined with computer vision techniques have been proposed as an alternative or complementary technique to determine the quality parameters of food in a non-destructive way. The aim of this work was to analyze the sensory attributes of dry-cured loins using this technique. For that, different MRI acquisition sequences (spin echo, gradient echo and turbo 3D), algorithms for MRI analysis (GLCM, NGLDM, GLRLM and GLCM-NGLDM-GLRLM) and predictive data mining techniques (multiple linear regression and isotonic regression) were tested. The correlation coefficient (R) and mean absolute error (MAE) were used to validate the prediction results. The combination of spin echo, GLCM and isotonic regression produced the most accurate results. In addition, the MRI data from dry-cured loins seems to be more suitable than the data from fresh loins. The application of predictive data mining techniques on computational texture features from the MRI data of loins enables the determination of the sensory traits of dry-cured loins in a non-destructive way. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Brain-wide pathway for waste clearance captured by contrast-enhanced MRI.

PubMed

Iliff, Jeffrey J; Lee, Hedok; Yu, Mei; Feng, Tian; Logan, Jean; Nedergaard, Maiken; Benveniste, Helene

2013-03-01

The glymphatic system is a recently defined brain-wide paravascular pathway for cerebrospinal fluid (CSF) and interstitial fluid (ISF) exchange that facilitates efficient clearance of solutes and waste from the brain. CSF enters the brain along para-arterial channels to exchange with ISF, which is in turn cleared from the brain along para-venous pathways. Because soluble amyloid β clearance depends on glymphatic pathway function, we proposed that failure of this clearance system contributes to amyloid plaque deposition and Alzheimer's disease progression. Here we provide proof of concept that glymphatic pathway function can be measured using a clinically relevant imaging technique. Dynamic contrast-enhanced MRI was used to visualize CSF-ISF exchange across the rat brain following intrathecal paramagnetic contrast agent administration. Key features of glymphatic pathway function were confirmed, including visualization of para-arterial CSF influx and molecular size-dependent CSF-ISF exchange. Whole-brain imaging allowed the identification of two key influx nodes at the pituitary and pineal gland recesses, while dynamic MRI permitted the definition of simple kinetic parameters to characterize glymphatic CSF-ISF exchange and solute clearance from the brain. We propose that this MRI approach may provide the basis for a wholly new strategy to evaluate Alzheimer's disease susceptibility and progression in the live human brain.

Brain-wide pathway for waste clearance captured by contrast-enhanced MRI

PubMed Central

Iliff, Jeffrey J.; Lee, Hedok; Yu, Mei; Feng, Tian; Logan, Jean; Nedergaard, Maiken; Benveniste, Helene

2013-01-01

The glymphatic system is a recently defined brain-wide paravascular pathway for cerebrospinal fluid (CSF) and interstitial fluid (ISF) exchange that facilitates efficient clearance of solutes and waste from the brain. CSF enters the brain along para-arterial channels to exchange with ISF, which is in turn cleared from the brain along para-venous pathways. Because soluble amyloid β clearance depends on glymphatic pathway function, we proposed that failure of this clearance system contributes to amyloid plaque deposition and Alzheimer’s disease progression. Here we provide proof of concept that glymphatic pathway function can be measured using a clinically relevant imaging technique. Dynamic contrast-enhanced MRI was used to visualize CSF-ISF exchange across the rat brain following intrathecal paramagnetic contrast agent administration. Key features of glymphatic pathway function were confirmed, including visualization of para-arterial CSF influx and molecular size-dependent CSF-ISF exchange. Whole-brain imaging allowed the identification of two key influx nodes at the pituitary and pineal gland recesses, while dynamic MRI permitted the definition of simple kinetic parameters to characterize glymphatic CSF-ISF exchange and solute clearance from the brain. We propose that this MRI approach may provide the basis for a wholly new strategy to evaluate Alzheimer’s disease susceptibility and progression in the live human brain. PMID:23434588

Combined DTI Tractography and Functional MRI Study of the Language Connectome in Healthy Volunteers: Extensive Mapping of White Matter Fascicles and Cortical Activations.

PubMed

Vassal, François; Schneider, Fabien; Boutet, Claire; Jean, Betty; Sontheimer, Anna; Lemaire, Jean-Jacques

2016-01-01

Despite a better understanding of brain language organization into large-scale cortical networks, the underlying white matter (WM) connectivity is still not mastered. Here we combined diffusion tensor imaging (DTI) fiber tracking (FT) and language functional magnetic resonance imaging (fMRI) in twenty healthy subjects to gain new insights into the macroscopic structural connectivity of language. Eight putative WM fascicles for language were probed using a deterministic DTI-FT technique: the arcuate fascicle (AF), superior longitudinal fascicle (SLF), uncinate fascicle (UF), temporo-occipital fascicle, inferior fronto-occipital fascicle (IFOF), middle longitudinal fascicle (MdLF), frontal aslant fascicle and operculopremotor fascicle. Specific measurements (i.e. volume, length, fractional anisotropy) and precise cortical terminations were derived for each WM fascicle within both hemispheres. Connections between these WM fascicles and fMRI activations were studied to determine which WM fascicles are related to language. WM fascicle volumes showed asymmetries: leftward for the AF, temporoparietal segment of SLF and UF, and rightward for the frontoparietal segment of the SLF. The lateralization of the AF, IFOF and MdLF extended to differences in patterns of anatomical connections, which may relate to specific hemispheric abilities. The leftward asymmetry of the AF was correlated to the leftward asymmetry of fMRI activations, suggesting that the lateralization of the AF is a structural substrate of hemispheric language dominance. We found consistent connections between fMRI activations and terminations of the eight WM fascicles, providing a detailed description of the language connectome. WM fascicle terminations were also observed beyond fMRI-confirmed language areas and reached numerous cortical areas involved in different functional brain networks. These findings suggest that the reported WM fascicles are not exclusively involved in language and might be related to other cognitive functions such as visual recognition, spatial attention, executive functions, memory, and processing of emotional and behavioral aspects.

Neuroimaging is a novel tool to understand the impact of environmental chemicals on neurodevelopment

PubMed Central

Horton, Megan K.; Margolis, Amy E.; Tang, Cheuk; Wright, Robert

2014-01-01

Purpose of review The prevalence of childhood neurodevelopmental disorders (ND) has been increasing over the last several decades. Prenatal and early childhood exposure to environmental toxicants is increasingly recognized as contributing to the growing rate of NDs. Very little is known about the mechanistic processes by which environmental chemicals alter brain development. We review recent advances in brain imaging modalities and discuss their application in epidemiologic studies of prenatal and early childhood exposure to environmental toxicants. Recent findings Neuroimaging techniques (volumetric and functional magnetic resonance imaging (MRI), diffusor tensor imaging (DTI), magnetic resonance spectroscopy (MRS)) have opened unprecedented access to study the developing human brain. These techniques are non-invasive and free of ionization radiation making them suitable for research applications in children. Using these techniques, we now understand much about structural and functional patterns in the typically developing brain. This knowledge allows us to investigate how prenatal exposure to environmental toxicants may alter the typical developmental trajectory. Summary MRI is a powerful tool that allows in vivo visualization of brain structure and function. Used in epidemiologic studies of environmental exposure, it offers the promise to causally link exposure with behavioral and cognitive manifestations and ultimately to inform programs to reduce exposure and mitigate adverse effects of exposure. PMID:24535497

Measurements of coherent hemodynamics to enrich the physiological information provided by near-infrared spectroscopy (NIRS) and functional MRI

NASA Astrophysics Data System (ADS)

Sassaroli, Angelo; Tgavalekos, Kristen; Pham, Thao; Krishnamurthy, Nishanth; Fantini, Sergio

2018-02-01

Hemodynamic-based neuroimaging techniques such as functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS) sense hemoglobin concentration in cerebral tissue. The local concentration of hemoglobin, which is differentiated into oxy- and deoxy-hemoglobin by NIRS, features spontaneous oscillations over time scales of 10-100 s in response to a number of local and systemic physiological processes. If one of such processes becomes the dominant source of cerebral hemodynamics, there is a high coherence between this process and the associated hemodynamics. In this work, we report a method to identify such conditions of coherent hemodynamics, which may be exploited to study and quantify microvasculature and microcirculation properties. We discuss how a critical value of significant coherence may depend on the specific data collection scheme (for example, the total acquisition time) and the nature of the hemodynamic data (in particular, oxy- and deoxy-hemoglobin concentrations measured with NIRS show an intrinsic level of correlation that must be taken into account). A frequency-resolved study of coherent hemodynamics is the basis for the new technique of coherent hemodynamics spectroscopy (CHS), which aims to provide measures of cerebral blood flow and cerebral autoregulation. While these concepts apply in principle to both fMRI and NIRS data, in this article we focus on NIRS data.

Regional homogeneity changes in prelingually deafened patients: a resting-state fMRI study

NASA Astrophysics Data System (ADS)

Li, Wenjing; He, Huiguang; Xian, Junfang; Lv, Bin; Li, Meng; Li, Yong; Liu, Zhaohui; Wang, Zhenchang

2010-03-01

Resting-state functional magnetic resonance imaging (fMRI) is a technique that measures the intrinsic function of brain and has some advantages over task-induced fMRI. Regional homogeneity (ReHo) assesses the similarity of the time series of a given voxel with its nearest neighbors on a voxel-by-voxel basis, which reflects the temporal homogeneity of the regional BOLD signal. In the present study, we used the resting state fMRI data to investigate the ReHo changes of the whole brain in the prelingually deafened patients relative to normal controls. 18 deaf patients and 22 healthy subjects were scanned. Kendall's coefficient of concordance (KCC) was calculated to measure the degree of regional coherence of fMRI time courses. We found that regional coherence significantly decreased in the left frontal lobe, bilateral temporal lobes and right thalamus, and increased in the postcentral gyrus, cingulate gyrus, left temporal lobe, left thalamus and cerebellum in deaf patients compared with controls. These results show that the prelingually deafened patients have higher degree of regional coherence in the paleocortex, and lower degree in neocortex. Since neocortex plays an important role in the development of auditory, these evidences may suggest that the deaf persons reorganize the paleocortex to offset the loss of auditory.

Biomedical Applications of Sodium MRI In Vivo

PubMed Central

Madelin, Guillaume; Regatte, Ravinder R.

2013-01-01

In this article, we present an up-to-date overview of the potential biomedical applications of sodium MRI in vivo. Sodium MRI is a subject of increasing interest in translational imaging research as it can give some direct and quantitative biochemical information on the tissue viability, cell integrity and function, and therefore not only help the diagnosis but also the prognosis of diseases and treatment outcomes. It has already been applied in vivo in most of human tissues, such as brain for stroke or tumor detection and therapeutic response, in breast cancer, in articular cartilage, in muscle and in kidney, and it was shown in some studies that it could provide very useful new information not available through standard proton MRI. However, this technique is still very challenging due to the low detectable sodium signal in biological tissue with MRI and hardware/software limitations of the clinical scanners. The article is divided in three parts: (1) the role of sodium in biological tissues, (2) a short review on sodium magnetic resonance, and (3) a review of some studies on sodium MRI on different organs/diseases to date. PMID:23722972

Evaluating effects of methylphenidate on brain activity in cocaine addiction: a machine-learning approach

NASA Astrophysics Data System (ADS)

Rish, Irina; Bashivan, Pouya; Cecchi, Guillermo A.; Goldstein, Rita Z.

2016-03-01

The objective of this study is to investigate effects of methylphenidate on brain activity in individuals with cocaine use disorder (CUD) using functional MRI (fMRI). Methylphenidate hydrochloride (MPH) is an indirect dopamine agonist commonly used for treating attention deficit/hyperactivity disorders; it was also shown to have some positive effects on CUD subjects, such as improved stop signal reaction times associated with better control/inhibition,1 as well as normalized task-related brain activity2 and resting-state functional connectivity in specific areas.3 While prior fMRI studies of MPH in CUDs have focused on mass-univariate statistical hypothesis testing, this paper evaluates multivariate, whole-brain effects of MPH as captured by the generalization (prediction) accuracy of different classification techniques applied to features extracted from resting-state functional networks (e.g., node degrees). Our multivariate predictive results based on resting-state data from3 suggest that MPH tends to normalize network properties such as voxel degrees in CUD subjects, thus providing additional evidence for potential benefits of MPH in treating cocaine addiction.

Interleaved EPI based fMRI improved by multiplexed sensitivity encoding (MUSE) and simultaneous multi-band imaging.

PubMed

Chang, Hing-Chiu; Gaur, Pooja; Chou, Ying-hui; Chu, Mei-Lan; Chen, Nan-kuei

2014-01-01

Functional magnetic resonance imaging (fMRI) is a non-invasive and powerful imaging tool for detecting brain activities. The majority of fMRI studies are performed with single-shot echo-planar imaging (EPI) due to its high temporal resolution. Recent studies have demonstrated that, by increasing the spatial-resolution of fMRI, previously unidentified neuronal networks can be measured. However, it is challenging to improve the spatial resolution of conventional single-shot EPI based fMRI. Although multi-shot interleaved EPI is superior to single-shot EPI in terms of the improved spatial-resolution, reduced geometric distortions, and sharper point spread function (PSF), interleaved EPI based fMRI has two main limitations: 1) the imaging throughput is lower in interleaved EPI; 2) the magnitude and phase signal variations among EPI segments (due to physiological noise, subject motion, and B0 drift) are translated to significant in-plane aliasing artifact across the field of view (FOV). Here we report a method that integrates multiple approaches to address the technical limitations of interleaved EPI-based fMRI. Firstly, the multiplexed sensitivity-encoding (MUSE) post-processing algorithm is used to suppress in-plane aliasing artifacts resulting from time-domain signal instabilities during dynamic scans. Secondly, a simultaneous multi-band interleaved EPI pulse sequence, with a controlled aliasing scheme incorporated, is implemented to increase the imaging throughput. Thirdly, the MUSE algorithm is then generalized to accommodate fMRI data obtained with our multi-band interleaved EPI pulse sequence, suppressing both in-plane and through-plane aliasing artifacts. The blood-oxygenation-level-dependent (BOLD) signal detectability and the scan throughput can be significantly improved for interleaved EPI-based fMRI. Our human fMRI data obtained from 3 Tesla systems demonstrate the effectiveness of the developed methods. It is expected that future fMRI studies requiring high spatial-resolvability and fidelity will largely benefit from the reported techniques.

Auditory Neuroimaging with fMRI and PET

PubMed Central

Talavage, Thomas M.; Gonzalez-Castillo, Javier; Scott, Sophie K.

2013-01-01

For much of the past 30 years, investigations of auditory perception and language have been enhanced or even driven by the use of functional neuroimaging techniques that specialize in localization of central responses. Beginning with investigations using positron emission tomography (PET) and gradually shifting primarily to usage of functional magnetic resonance imaging (fMRI), auditory neuroimaging has greatly advanced our understanding of the organization and response properties of brain regions critical to the perception of and communication with the acoustic world in which we live. As the complexity of the questions being addressed has increased, the techniques, experiments and analyses applied have also become more nuanced and specialized. A brief review of the history of these investigations sets the stage for an overview and analysis of how these neuroimaging modalities are becoming ever more effective tools for understanding the auditory brain. We conclude with a brief discussion of open methodological issues as well as potential clinical applications for auditory neuroimaging. PMID:24076424

Studies in nonlinear optics and functional magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Dai, Tehui

There are two parts in this thesis. The first part will involve a study in the anomalous dispersion phase matched second-harmonic generation, and the second part will be a study in functional magnetic resonance imaging (fMRI) and a biophysical model of the human muscle. In part I, we report on a series of tricyanovinylaniline chromophores for use as dopants in poled poly(methyl methacrylate) waveguides for anomalous-dispersion phase- matched second-harmonic generation. Second-harmonic generation measurements as a function of mode index confirmed anomalous dispersion phase-matching efficiencies as large as 245%/Wcm2 over a propagation length of ~35 μm. The waveguide coupling technique limited the interaction length. The photostability of the chromophores was measured directly and found to agree qualitatively with second-harmonic measurements over time and was found to be improved over previously reported materials. In part II, we designed a system that could record joint force and surface electromyography (EMG) simultaneously with fMRI data. I-Egh quality force and EMG data were obtained at the same time that excellent fMRI brain images were achieved. Using this system we determined the relationship between the fMRI-measured brain activation and the handgrip force, and between the fMRI-measured brain activation and the EMG of finger flexor muscles. We found that in the whole brain and in the majority of motor function-related cortical fields, the degree of muscle activation is directly proportional to the amplitude of the brain signal determined by the fMRI measurement. The similarity in the relationship between muscle output and fMRI signal in a number of brain areas suggests that multiple cortical fields are involved in controlling muscle force. The factors that may contribute to the fMRI signals are discussed. A biophysical twitch force model was developed to predict force response under electrical stimulation. Comparison between experimental and modeled force profiles, peak forces, and force duration shows excellent agreement between the model and the experimental data. It is concluded that the present model allows us to reproduce the main features of muscle activation under stimulation.

Registering and Analyzing Rat fMRI Data in the Stereotaxic Framework by Exploiting Intrinsic Anatomical Features

PubMed Central

Lu, Hanbing; Scholl, Clara A.; Zuo, Yantao; Demny, Steven; Rea, William; Stein, Elliot A.; Yang, Yihong

2009-01-01

The value of analyzing neuroimaging data on a group level has been well established in human studies. However, there is no standard procedure for registering and analyzing fMRI data into common space in rodent functional magnetic resonance imaging (fMRI) studies. An approach for performing rat imaging data analysis in the stereotaxic framework is presented. This method is rooted in the biological observation that the skull shape and size of rat brain are essentially the same as long as their weights are within certain range. Registration is performed using rigid-body transformations without scaling or shearing, preserving the unique properties of the stable shape and size inherent in rat brain structure. Also, it does not require brain tissue masking, and is not biased towards surface coil sensitivity profile. A standard rat brain atlas is used to facilitate the identification of activated areas in common space, allowing accurate region-of-interest (ROI) analysis. This technique is evaluated from a group of rats (n = 11) undergoing routine MRI scans; the registration accuracy is estimated to be within 400 μm. The analysis of fMRI data acquired with an electrical forepaw stimulation model demonstrates the utility of this technique. The method is implemented within the AFNI framework and can be readily extended to other studies. PMID:19608368

Resting state activity in patients with disorders of consciousness

PubMed Central

Soddu, Andrea; Vanhaudenhuyse, Audrey; Demertzi, Athena; Bruno, Marie-Aurélie; Tshibanda, Luaba; Di, Haibo; Boly, Mélanie; Papa, Michele; Laureys, Steven; Noirhomme, Quentin

Summary Recent advances in the study of spontaneous brain activity have demonstrated activity patterns that emerge with no task performance or sensory stimulation; these discoveries hold promise for the study of higher-order associative network functionality. Additionally, such advances are argued to be relevant in pathological states, such as disorders of consciousness (DOC), i.e., coma, vegetative and minimally conscious states. Recent studies on resting state activity in DOC, measured with functional magnetic resonance imaging (fMRI) techniques, show that functional connectivity is disrupted in the task-negative or the default mode network. However, the two main approaches employed in the analysis of resting state functional connectivity data (i.e., hypothesis-driven seed-voxel and data-driven independent component analysis) present multiple methodological difficulties, especially in non-collaborative DOC patients. Improvements in motion artifact removal and spatial normalization are needed before fMRI resting state data can be used as proper biomarkers in severe brain injury. However, we anticipate that such developments will boost clinical resting state fMRI studies, allowing for easy and fast acquisitions and ultimately improve the diagnosis and prognosis in the absence of DOC patients’ active collaboration in data acquisition. PMID:21693087

High-resolution maps of real and illusory tactile activation in primary somatosensory cortex in individual monkeys with functional magnetic resonance imaging and optical imaging.

PubMed

Chen, Li M; Turner, Gregory H; Friedman, Robert M; Zhang, Na; Gore, John C; Roe, Anna W; Avison, Malcolm J

2007-08-22

Although blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has been widely used to explore human brain function, questions remain regarding the ultimate spatial resolution of positive BOLD fMRI, and indeed the extent to which functional maps revealed by positive BOLD correlate spatially with maps obtained with other high-spatial-resolution mapping techniques commonly used in animals, such as optical imaging of intrinsic signal (OIS) and single-unit electrophysiology. Here, we demonstrate that the positive BOLD signal at 9.4T can reveal the fine topography of individual fingerpads in single-condition activation maps in nonhuman primates. These digit maps are similar to maps obtained from the same animal using intrinsic optical imaging. Furthermore, BOLD fMRI reliably resolved submillimeter spatial shifts in activation in area 3b previously identified with OIS (Chen et al., 2003) as neural correlates of the "funneling illusion." These data demonstrate that at high field, high-spatial-resolution topographic maps can be achieved using the positive BOLD signal, weakening previous notions regarding the spatial specificity of the positive BOLD signal.

[Possibilities of modern imaging technologies in early diagnosis of Alzheimer disease].

PubMed

Unschuld, Paul G

2015-04-01

Recent advances in neuroimaging technology and image analysis algorithms have significantly contributed to a better understanding of spatial and temporal aspects of brain change associated with Alzheimer Disease. The current review will demonstrate how functional (fMRI) and structural magnetic resonance imaging (MRI) techniques may be used to identify distinct patterns of brain change associated with disease progression and also increased risk for Alzheimer Disease. Moreover, Positron Emission Tomography (PET) based measures of glucosemetabolism (Fluorodeoxyglucose, FDG) and Amyloid-beta plaque density (11-C-Pittsburgh Compound B, PiB and 18-F) will be reviewed regarding their diagnostic value for assessing the individual degree of Alzheimer -pathology and thus complement the information provided by MRI and other clinical measures.

Optical/MRI Multimodality Molecular Imaging

NASA Astrophysics Data System (ADS)

Ma, Lixin; Smith, Charles; Yu, Ping

2007-03-01

Multimodality molecular imaging that combines anatomical and functional information has shown promise in development of tumor-targeted pharmaceuticals for cancer detection or therapy. We present a new multimodality imaging technique that combines fluorescence molecular tomography (FMT) and magnetic resonance imaging (MRI) for in vivo molecular imaging of preclinical tumor models. Unlike other optical/MRI systems, the new molecular imaging system uses parallel phase acquisition based on heterodyne principle. The system has a higher accuracy of phase measurements, reduced noise bandwidth, and an efficient modulation of the fluorescence diffuse density waves. Fluorescent Bombesin probes were developed for targeting breast cancer cells and prostate cancer cells. Tissue phantom and small animal experiments were performed for calibration of the imaging system and validation of the targeting probes.

Longitudinal assessment of treatment effects on pulmonary ventilation using 1H/3He MRI multivariate templates

NASA Astrophysics Data System (ADS)

Tustison, Nicholas J.; Contrella, Benjamin; Altes, Talissa A.; Avants, Brian B.; de Lange, Eduard E.; Mugler, John P.

2013-03-01

The utitlity of pulmonary functional imaging techniques, such as hyperpolarized 3He MRI, has encouraged their inclusion in research studies for longitudinal assessment of disease progression and the study of treatment effects. We present methodology for performing voxelwise statistical analysis of ventilation maps derived from hyper­ polarized 3He MRI which incorporates multivariate template construction using simultaneous acquisition of IH and 3He images. Additional processing steps include intensity normalization, bias correction, 4-D longitudinal segmentation, and generation of expected ventilation maps prior to voxelwise regression analysis. Analysis is demonstrated on a cohort of eight individuals with diagnosed cystic fibrosis (CF) undergoing treatment imaged five times every two weeks with a prescribed treatment schedule.

Visual feature extraction from voxel-weighted averaging of stimulus images in 2 fMRI studies.

PubMed

Hart, Corey B; Rose, William J

2013-11-01

Multiple studies have provided evidence for distributed object representation in the brain, with several recent experiments leveraging basis function estimates for partial image reconstruction from fMRI data. Using a novel combination of statistical decomposition, generalized linear models, and stimulus averaging on previously examined image sets and Bayesian regression of recorded fMRI activity during presentation of these data sets, we identify a subset of relevant voxels that appear to code for covarying object features. Using a technique we term "voxel-weighted averaging," we isolate image filters that these voxels appear to implement. The results, though very cursory, appear to have significant implications for hierarchical and deep-learning-type approaches toward the understanding of neural coding and representation.

Behavioral, Cognitive and Neural Markers of Asperger Syndrome

PubMed Central

Faridi, Farnaz; Khosrowabadi, Reza

2017-01-01

Asperger syndrome (AS) is a subtype of Autism Spectrum Disorder (ASD) characterized by major problems in social and nonverbal communication, together with limited and repetitive forms of behavior and interests. The linguistic and cognitive development in AS is preserved which help us to differentiate it from other subtypes of ASD. However, significant effects of AS on cognitive abilities and brain functions still need to be researched. Although a clear cut pathology for Asperger has not been identified yet, recent studies have largely focused on brain imaging techniques to investigate AS. In this regard, we carried out a systematic review on behavioral, cognitive, and neural markers (specifically using MRI and fMRI) studies on AS. In this paper, behavior, motor skills and language capabilities of individuals with Asperger are compared to those in healthy controls. In addition, common findings across MRI and fMRI based studies associated with behavior and cognitive disabilities are highlighted. PMID:29167722

Behavioral, Cognitive and Neural Markers of Asperger Syndrome.

PubMed

Faridi, Farnaz; Khosrowabadi, Reza

2017-01-01

Asperger syndrome (AS) is a subtype of Autism Spectrum Disorder (ASD) characterized by major problems in social and nonverbal communication, together with limited and repetitive forms of behavior and interests. The linguistic and cognitive development in AS is preserved which help us to differentiate it from other subtypes of ASD. However, significant effects of AS on cognitive abilities and brain functions still need to be researched. Although a clear cut pathology for Asperger has not been identified yet, recent studies have largely focused on brain imaging techniques to investigate AS. In this regard, we carried out a systematic review on behavioral, cognitive, and neural markers (specifically using MRI and fMRI) studies on AS. In this paper, behavior, motor skills and language capabilities of individuals with Asperger are compared to those in healthy controls. In addition, common findings across MRI and fMRI based studies associated with behavior and cognitive disabilities are highlighted.

Chapter 18: the origins of functional brain imaging in humans.

PubMed

Raichle, Marcus E

2010-01-01

Functional brain imaging in humans as we presently know it began when the experimental strategies of cognitive psychology were combined with modern brain imaging techniques, first positron emission tomography (PET) and then functional magnetic resonance imaging (fMRI), to examine how brain function supports mental activities. This marriage of disciplines and techniques galvanized the field of cognitive neuroscience, which has rapidly expanded to include a broad range of the social sciences as well as basic scientists interested in the neurophysiology, cell biology and genetics of the imaging signals. While much of this work has transpired over the past couple of decades, its roots can be traced back more than a century.

Identifying the arterial input function from dynamic contrast-enhanced magnetic resonance images using an apex-seeking technique

NASA Astrophysics Data System (ADS)

Martel, Anne L.

2004-04-01

In order to extract quantitative information from dynamic contrast-enhanced MR images (DCE-MRI) it is usually necessary to identify an arterial input function. This is not a trivial problem if there are no major vessels present in the field of view. Most existing techniques rely on operator intervention or use various curve parameters to identify suitable pixels but these are often specific to the anatomical region or the acquisition method used. They also require the signal from several pixels to be averaged in order to improve the signal to noise ratio, however this introduces errors due to partial volume effects. We have described previously how factor analysis can be used to automatically separate arterial and venous components from DCE-MRI studies of the brain but although that method works well for single slice images through the brain when the blood brain barrier technique is intact, it runs into problems for multi-slice images with more complex dynamics. This paper will describe a factor analysis method that is more robust in such situations and is relatively insensitive to the number of physiological components present in the data set. The technique is very similar to that used to identify spectral end-members from multispectral remote sensing images.

The effect of ageing on fMRI: Correction for the confounding effects of vascular reactivity evaluated by joint fMRI and MEG in 335 adults.

PubMed

Tsvetanov, Kamen A; Henson, Richard N A; Tyler, Lorraine K; Davis, Simon W; Shafto, Meredith A; Taylor, Jason R; Williams, Nitin; Cam-Can; Rowe, James B

2015-06-01

In functional magnetic resonance imaging (fMRI) research one is typically interested in neural activity. However, the blood-oxygenation level-dependent (BOLD) signal is a composite of both neural and vascular activity. As factors such as age or medication may alter vascular function, it is essential to account for changes in neurovascular coupling when investigating neurocognitive functioning with fMRI. The resting-state fluctuation amplitude (RSFA) in the fMRI signal (rsfMRI) has been proposed as an index of vascular reactivity. The RSFA compares favourably with other techniques such as breath-hold and hypercapnia, but the latter are more difficult to perform in some populations, such as older adults. The RSFA is therefore a candidate for use in adjusting for age-related changes in vascular reactivity in fMRI studies. The use of RSFA is predicated on its sensitivity to vascular rather than neural factors; however, the extent to which each of these factors contributes to RSFA remains to be characterized. The present work addressed these issues by comparing RSFA (i.e., rsfMRI variability) to proxy measures of (i) cardiovascular function in terms of heart rate (HR) and heart rate variability (HRV) and (ii) neural activity in terms of resting state magnetoencephalography (rsMEG). We derived summary scores of RSFA, a sensorimotor task BOLD activation, cardiovascular function and rsMEG variability for 335 healthy older adults in the population-based Cambridge Centre for Ageing and Neuroscience cohort (Cam-CAN; www.cam-can.com). Mediation analysis revealed that the effects of ageing on RSFA were significantly mediated by vascular factors, but importantly not by the variability in neuronal activity. Furthermore, the converse effects of ageing on the rsMEG variability were not mediated by vascular factors. We then examined the effect of RSFA scaling of task-based BOLD in the sensorimotor task. The scaling analysis revealed that much of the effects of age on task-based activation studies with fMRI do not survive correction for changes in vascular reactivity, and are likely to have been overestimated in previous fMRI studies of ageing. The results from the mediation analysis demonstrate that RSFA is modulated by measures of vascular function and is not driven solely by changes in the variance of neural activity. Based on these findings we propose that the RSFA scaling method is articularly useful in large scale and longitudinal neuroimaging studies of ageing, or with frail participants, where alternative measures of vascular reactivity are impractical. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

The effect of ageing on fMRI: Correction for the confounding effects of vascular reactivity evaluated by joint fMRI and MEG in 335 adults

PubMed Central

Henson, Richard N. A.; Tyler, Lorraine K.; Davis, Simon W.; Shafto, Meredith A.; Taylor, Jason R.; Williams, Nitin; Cam‐CAN; Rowe, James B.

2015-01-01

Abstract In functional magnetic resonance imaging (fMRI) research one is typically interested in neural activity. However, the blood‐oxygenation level‐dependent (BOLD) signal is a composite of both neural and vascular activity. As factors such as age or medication may alter vascular function, it is essential to account for changes in neurovascular coupling when investigating neurocognitive functioning with fMRI. The resting‐state fluctuation amplitude (RSFA) in the fMRI signal (rsfMRI) has been proposed as an index of vascular reactivity. The RSFA compares favourably with other techniques such as breath‐hold and hypercapnia, but the latter are more difficult to perform in some populations, such as older adults. The RSFA is therefore a candidate for use in adjusting for age‐related changes in vascular reactivity in fMRI studies. The use of RSFA is predicated on its sensitivity to vascular rather than neural factors; however, the extent to which each of these factors contributes to RSFA remains to be characterized. The present work addressed these issues by comparing RSFA (i.e., rsfMRI variability) to proxy measures of (i) cardiovascular function in terms of heart rate (HR) and heart rate variability (HRV) and (ii) neural activity in terms of resting state magnetoencephalography (rsMEG). We derived summary scores of RSFA, a sensorimotor task BOLD activation, cardiovascular function and rsMEG variability for 335 healthy older adults in the population‐based Cambridge Centre for Ageing and Neuroscience cohort (Cam‐CAN; www.cam-can.com). Mediation analysis revealed that the effects of ageing on RSFA were significantly mediated by vascular factors, but importantly not by the variability in neuronal activity. Furthermore, the converse effects of ageing on the rsMEG variability were not mediated by vascular factors. We then examined the effect of RSFA scaling of task‐based BOLD in the sensorimotor task. The scaling analysis revealed that much of the effects of age on task‐based activation studies with fMRI do not survive correction for changes in vascular reactivity, and are likely to have been overestimated in previous fMRI studies of ageing. The results from the mediation analysis demonstrate that RSFA is modulated by measures of vascular function and is not driven solely by changes in the variance of neural activity. Based on these findings we propose that the RSFA scaling method is articularly useful in large scale and longitudinal neuroimaging studies of ageing, or with frail participants, where alternative measures of vascular reactivity are impractical. Hum Brain Mapp 36:2248–2269, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. PMID:25727740

Functional classification of schizophrenia using feed forward neural networks.

PubMed

Jafri, Madiha J; Calhoun, Vince D

2006-01-01

In medicine, the nature of an illness is often determined through behavioral or biological markers. The process of diagnosis becomes difficult when dealing with mental disorders since they rely primarily on behavioral markers. Schizophrenia is an example of a complex mental disorder that relies on aberrant behavior such as auditory hallucinations, dampening of emotions, paranoia, etc. This research is an attempt to determine a biological marker for schizophrenia through the use of functional magnetic resonance imaging (fMRI). In this paper, we propose a method of classification of schizophrenia and healthy controls, using a neural network approach and functional brain 'modes'estimated from resting state data using independent component analysis. A reliable technique for discriminating schizophrenia based upon fMRI would be a significant advance and may also provide additional information about the biological implications of mental illness.

Graphical programming interface: A development environment for MRI methods.

PubMed

Zwart, Nicholas R; Pipe, James G

2015-11-01

To introduce a multiplatform, Python language-based, development environment called graphical programming interface for prototyping MRI techniques. The interface allows developers to interact with their scientific algorithm prototypes visually in an event-driven environment making tasks such as parameterization, algorithm testing, data manipulation, and visualization an integrated part of the work-flow. Algorithm developers extend the built-in functionality through simple code interfaces designed to facilitate rapid implementation. This article shows several examples of algorithms developed in graphical programming interface including the non-Cartesian MR reconstruction algorithms for PROPELLER and spiral as well as spin simulation and trajectory visualization of a FLORET example. The graphical programming interface framework is shown to be a versatile prototyping environment for developing numeric algorithms used in the latest MR techniques. © 2014 Wiley Periodicals, Inc.

Feature-space-based FMRI analysis using the optimal linear transformation.

PubMed

Sun, Fengrong; Morris, Drew; Lee, Wayne; Taylor, Margot J; Mills, Travis; Babyn, Paul S

2010-09-01

The optimal linear transformation (OLT), an image analysis technique of feature space, was first presented in the field of MRI. This paper proposes a method of extending OLT from MRI to functional MRI (fMRI) to improve the activation-detection performance over conventional approaches of fMRI analysis. In this method, first, ideal hemodynamic response time series for different stimuli were generated by convolving the theoretical hemodynamic response model with the stimulus timing. Second, constructing hypothetical signature vectors for different activity patterns of interest by virtue of the ideal hemodynamic responses, OLT was used to extract features of fMRI data. The resultant feature space had particular geometric clustering properties. It was then classified into different groups, each pertaining to an activity pattern of interest; the applied signature vector for each group was obtained by averaging. Third, using the applied signature vectors, OLT was applied again to generate fMRI composite images with high SNRs for the desired activity patterns. Simulations and a blocked fMRI experiment were employed for the method to be verified and compared with the general linear model (GLM)-based analysis. The simulation studies and the experimental results indicated the superiority of the proposed method over the GLM-based analysis in detecting brain activities.

Three-dimensional histology: tools and application to quantitative assessment of cell-type distribution in rabbit heart

PubMed Central

Burton, Rebecca A.B.; Lee, Peter; Casero, Ramón; Garny, Alan; Siedlecka, Urszula; Schneider, Jürgen E.; Kohl, Peter; Grau, Vicente

2014-01-01

Aims Cardiac histo-anatomical organization is a major determinant of function. Changes in tissue structure are a relevant factor in normal and disease development, and form targets of therapeutic interventions. The purpose of this study was to test tools aimed to allow quantitative assessment of cell-type distribution from large histology and magnetic resonance imaging- (MRI) based datasets. Methods and results Rabbit heart fixation during cardioplegic arrest and MRI were followed by serial sectioning of the whole heart and light-microscopic imaging of trichrome-stained tissue. Segmentation techniques developed specifically for this project were applied to segment myocardial tissue in the MRI and histology datasets. In addition, histology slices were segmented into myocytes, connective tissue, and undefined. A bounding surface, containing the whole heart, was established for both MRI and histology. Volumes contained in the bounding surface (called ‘anatomical volume’), as well as that identified as containing any of the above tissue categories (called ‘morphological volume’), were calculated. The anatomical volume was 7.8 cm3 in MRI, and this reduced to 4.9 cm3 after histological processing, representing an ‘anatomical’ shrinkage by 37.2%. The morphological volume decreased by 48% between MRI and histology, highlighting the presence of additional tissue-level shrinkage (e.g. an increase in interstitial cleft space). The ratio of pixels classified as containing myocytes to pixels identified as non-myocytes was roughly 6:1 (61.6 vs. 9.8%; the remaining fraction of 28.6% was ‘undefined’). Conclusion Qualitative and quantitative differentiation between myocytes and connective tissue, using state-of-the-art high-resolution serial histology techniques, allows identification of cell-type distribution in whole-heart datasets. Comparison with MRI illustrates a pronounced reduction in anatomical and morphological volumes during histology processing. PMID:25362175

Performance of blind source separation algorithms for fMRI analysis using a group ICA method.

PubMed

Correa, Nicolle; Adali, Tülay; Calhoun, Vince D

2007-06-01

Independent component analysis (ICA) is a popular blind source separation technique that has proven to be promising for the analysis of functional magnetic resonance imaging (fMRI) data. A number of ICA approaches have been used for fMRI data analysis, and even more ICA algorithms exist; however, the impact of using different algorithms on the results is largely unexplored. In this paper, we study the performance of four major classes of algorithms for spatial ICA, namely, information maximization, maximization of non-Gaussianity, joint diagonalization of cross-cumulant matrices and second-order correlation-based methods, when they are applied to fMRI data from subjects performing a visuo-motor task. We use a group ICA method to study variability among different ICA algorithms, and we propose several analysis techniques to evaluate their performance. We compare how different ICA algorithms estimate activations in expected neuronal areas. The results demonstrate that the ICA algorithms using higher-order statistical information prove to be quite consistent for fMRI data analysis. Infomax, FastICA and joint approximate diagonalization of eigenmatrices (JADE) all yield reliable results, with each having its strengths in specific areas. Eigenvalue decomposition (EVD), an algorithm using second-order statistics, does not perform reliably for fMRI data. Additionally, for iterative ICA algorithms, it is important to investigate the variability of estimates from different runs. We test the consistency of the iterative algorithms Infomax and FastICA by running the algorithm a number of times with different initializations, and we note that they yield consistent results over these multiple runs. Our results greatly improve our confidence in the consistency of ICA for fMRI data analysis.

Lung volume quantified by MRI reflects extracellular-matrix deposition and altered pulmonary function in bleomycin models of fibrosis: effects of SOM230.

PubMed

Egger, Christine; Gérard, Christelle; Vidotto, Nella; Accart, Nathalie; Cannet, Catherine; Dunbar, Andrew; Tigani, Bruno; Piaia, Alessandro; Jarai, Gabor; Jarman, Elizabeth; Schmid, Herbert A; Beckmann, Nicolau

2014-06-15

Idiopathic pulmonary fibrosis is a progressive and lethal disease, characterized by loss of lung elasticity and alveolar surface area, secondary to alveolar epithelial cell injury, reactive inflammation, proliferation of fibroblasts, and deposition of extracellular matrix. The effects of oropharyngeal aspiration of bleomycin in Sprague-Dawley rats and C57BL/6 mice, as well as of intratracheal administration of ovalbumin to actively sensitized Brown Norway rats on total lung volume as assessed noninvasively by magnetic resonance imaging (MRI) were investigated here. Lung injury and volume were quantified by using nongated or respiratory-gated MRI acquisitions [ultrashort echo time (UTE) or gradient-echo techniques]. Lung function of bleomycin-challenged rats was examined additionally using a flexiVent system. Postmortem analyses included histology of collagen and hydroxyproline assays. Bleomycin induced an increase of MRI-assessed total lung volume, lung dry and wet weights, and hydroxyproline content as well as collagen amount. In bleomycin-treated rats, gated MRI showed an increased volume of the lung in the inspiratory and expiratory phases of the respiratory cycle and a temporary decrease of tidal volume. Decreased dynamic lung compliance was found in bleomycin-challenged rats. Bleomycin-induced increase of MRI-detected lung volume was consistent with tissue deposition during fibrotic processes resulting in decreased lung elasticity, whereas influences by edema or emphysema could be excluded. In ovalbumin-challenged rats, total lung volume quantified by MRI remained unchanged. The somatostatin analog, SOM230, was shown to have therapeutic effects on established bleomycin-induced fibrosis in rats. This work suggests MRI-detected total lung volume as readout for tissue-deposition in small rodent bleomycin models of pulmonary fibrosis. Copyright © 2014 the American Physiological Society.

Functional Magnetic Resonance Imaging Networks Induced by Intracranial Stimulation May Help Defining the Epileptogenic Zone

PubMed Central

Zhang, Myron; Avitsian, Rafi; Bhattacharyya, Pallab; Bulacio, Juan; Cendes, Fernando; Enatsu, Rei; Lowe, Mark; Najm, Imad; Nair, Dileep; Phillips, Michael; Gonzalez-Martinez, Jorge

2014-01-01

Abstract Patients with medically intractable epilepsy often undergo invasive evaluation and surgery, with a 50% success rate. The low success rate is likely due to poor identification of the epileptogenic zone (EZ), the brain area causing seizures. This work introduces a new method using functional magnetic resonance imaging (fMRI) with simultaneous direct electrical stimulation of the brain that could help localize the EZ, performed in five patients with medically intractable epilepsy undergoing invasive evaluation with intracranial depth electrodes. Stimulation occurred in a location near the hypothesized EZ and a location away. Electrical recordings in response to stimulation were recorded and compared to fMRI. Multiple stimulation parameters were varied, like current and frequency. The brain areas showing fMRI response were compared with the areas resected and the success of surgery. Robust fMRI maps of activation networks were easily produced, which also showed a significant but weak positive correlation between quantitative measures of blood-oxygen-level-dependent (BOLD) activity and measures of electrical activity in response to direct electrical stimulation (mean correlation coefficient of 0.38 for all acquisitions that produced a strong BOLD response). For four patients with outcome data at 6 months, successful surgical outcome is consistent with the resection of brain areas containing high local fMRI activity. In conclusion, this method demonstrates the feasibility of simultaneous direct electrical stimulation and fMRI in humans, which allows the study of brain connectivity with high resolution and full spatial coverage. This innovative technique could be used to better define the localization and extension of the EZ in intractable epilepsies, as well as for other functional neurosurgical procedures. PMID:24735069

Evaluation of preprocessing steps to compensate for magnetic field distortions due to body movements in BOLD fMRI

PubMed Central

Barry, Robert L.; Williams, Joy M.; Klassen, L. Martyn; Gallivan, Jason P.; Culham, Jody C.

2009-01-01

Blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is currently the dominant technique for non-invasive investigation of brain functions. One of the challenges with BOLD fMRI, particularly at high fields, is compensation for the effects of spatiotemporally varying magnetic field inhomogeneities (ΔB0) caused by normal subject respiration, and in some studies, movement of the subject during the scan to perform tasks related to the functional paradigm. The presence of ΔB0 during data acquisition distorts reconstructed images and introduces extraneous fluctuations in the fMRI time series that decrease the BOLD contrast-to-noise ratio. Optimization of the fMRI data-processing pipeline to compensate for geometric distortions is of paramount importance to ensure high quality of fMRI data. To investigate ΔB0 caused by subject movement, echo-planar imaging scans were collected with and without concurrent motion of a phantom arm. The phantom arm was constructed and moved by the experimenter to emulate forearm motions while subjects remained still and observed a visual stimulation paradigm. These data were then subjected to eight different combinations of preprocessing steps. The best preprocessing pipeline included navigator correction, a complex phase regressor, and spatial smoothing. The synergy between navigator correction and phase regression reduced geometric distortions better than either step in isolation, and preconditioned the data to make them more amenable to the benefits of spatial smoothing. The combination of these steps provided a 10% increase in t-statistics compared to only navigator correction and spatial smoothing, and reduced the noise and false activations in regions where no legitimate effects would occur. PMID:19695810

Understanding Magnetic Resonance Imaging of Knee Cartilage Repair: A Focus on Clinical Relevance.

PubMed

Hayashi, Daichi; Li, Xinning; Murakami, Akira M; Roemer, Frank W; Trattnig, Siegfried; Guermazi, Ali

2017-06-01

The aims of this review article are (a) to describe the principles of morphologic and compositional magnetic resonance imaging (MRI) techniques relevant for the imaging of knee cartilage repair surgery and their application to longitudinal studies and (b) to illustrate the clinical relevance of pre- and postsurgical MRI with correlation to intraoperative images. First, MRI sequences that can be applied for imaging of cartilage repair tissue in the knee are described, focusing on comparison of 2D and 3D fast spin echo and gradient recalled echo sequences. Imaging features of cartilage repair tissue are then discussed, including conventional (morphologic) MRI and compositional MRI techniques. More specifically, imaging techniques for specific cartilage repair surgery techniques as described above, as well as MRI-based semiquantitative scoring systems for the knee cartilage repair tissue-MR Observation of Cartilage Repair Tissue and Cartilage Repair OA Knee Score-are explained. Then, currently available surgical techniques are reviewed, including marrow stimulation, osteochondral autograft, osteochondral allograft, particulate cartilage allograft, autologous chondrocyte implantation, and others. Finally, ongoing research efforts and future direction of cartilage repair tissue imaging are discussed.

A method to classify schizophrenia using inter-task spatial correlations of functional brain images.

PubMed

Michael, Andrew M; Calhoun, Vince D; Andreasen, Nancy C; Baum, Stefi A

2008-01-01

The clinical heterogeneity of schizophrenia (scz) and the overlap of self reported and observed symptoms with other mental disorders makes its diagnosis a difficult task. At present no laboratory-based or image-based diagnostic tool for scz exists and such tools are desired to support existing methods for more precise diagnosis. Functional magnetic resonance imaging (fMRI) is currently employed to identify and correlate cognitive processes related to scz and its symptoms. Fusion of multiple fMRI tasks that probe different cognitive processes may help to better understand hidden networks of this complex disorder. In this paper we utilize three different fMRI tasks and introduce an approach to classify subjects based on inter-task spatial correlations of brain activation. The technique was applied to groups of patients and controls and its validity was checked with the leave-one-out method. We show that the classification rate increases when information from multiple tasks are combined.

Preservation of bursal-sided tendon in partial-thickness articular-sided rotator cuff tears: a novel arthroscopic transtendon anatomic repair technique.

PubMed

Shin, Sang-Jin; Jeong, Jae-Hoon; Jeon, Yoon Sang; Kim, Rag Gyu

2016-12-01

The purpose of this study was to introduce a novel arthroscopic transtendon anatomic repair technique that spares the intact bursal-sided tendon in articular-sided partial-thickness rotator cuff tears (PTRCT) and to present shoulder functional outcomes in patients with symptomatic articular-sided PCRCT that involves more than 50 % of its thickness after arthroscopic repair using a novel technique. Eighteen patients with symptomatic articular-sided PCRCT involving more than 50 % of the tendon's thickness underwent arthroscopic repair using a devised technique. The devised technique restores only the torn articular portion of the rotator cuff at the anatomical footprint using a suture anchor, and preserves the integrity of the corresponding bursal-sided tendon by tying knots at the most lateral bursal side on the subacromial space. Clinical and functional outcome using ASES and Constant scores were evaluated. The structural integrity of the rotator cuff was evaluated by MRI at 6 months postoperatively. Pain relief and shoulder functional outcomes were encouraging during the recovery phase after operation. ASES (preoperative 54.0 ± 10.3 to postoperative 92.6 ± 8.0), Constant score (61.2 ± 8.5-88.0 ± 5.3), VAS for pain (4.9 ± 2.6-0.6 ± 0.7) improved significantly after arthroscopic transtendon anatomic repair (p < 0.001). No patients had rotator cuff retears on 6-month MRI. No complications related to surgical procedures had occurred. The devised technique of arthroscopic transtendon repair provided satisfactory functional outcomes without postoperative discomforts. This technique minimizes over-tightening of the articular layer and reduces tension mismatches between the articular and bursal layers, which are considered as important factors for improvement of postoperative shoulder motion.

A comparison study of atlas-based 3D cardiac MRI segmentation: global versus global and local transformations

NASA Astrophysics Data System (ADS)

Daryanani, Aditya; Dangi, Shusil; Ben-Zikri, Yehuda Kfir; Linte, Cristian A.

2016-03-01

Magnetic Resonance Imaging (MRI) is a standard-of-care imaging modality for cardiac function assessment and guidance of cardiac interventions thanks to its high image quality and lack of exposure to ionizing radiation. Cardiac health parameters such as left ventricular volume, ejection fraction, myocardial mass, thickness, and strain can be assessed by segmenting the heart from cardiac MRI images. Furthermore, the segmented pre-operative anatomical heart models can be used to precisely identify regions of interest to be treated during minimally invasive therapy. Hence, the use of accurate and computationally efficient segmentation techniques is critical, especially for intra-procedural guidance applications that rely on the peri-operative segmentation of subject-specific datasets without delaying the procedure workflow. Atlas-based segmentation incorporates prior knowledge of the anatomy of interest from expertly annotated image datasets. Typically, the ground truth atlas label is propagated to a test image using a combination of global and local registration. The high computational cost of non-rigid registration motivated us to obtain an initial segmentation using global transformations based on an atlas of the left ventricle from a population of patient MRI images and refine it using well developed technique based on graph cuts. Here we quantitatively compare the segmentations obtained from the global and global plus local atlases and refined using graph cut-based techniques with the expert segmentations according to several similarity metrics, including Dice correlation coefficient, Jaccard coefficient, Hausdorff distance, and Mean absolute distance error.

Implementation of compressive sensing for preclinical cine-MRI

NASA Astrophysics Data System (ADS)

Tan, Elliot; Yang, Ming; Ma, Lixin; Zheng, Yahong Rosa

2014-03-01

This paper presents a practical implementation of Compressive Sensing (CS) for a preclinical MRI machine to acquire randomly undersampled k-space data in cardiac function imaging applications. First, random undersampling masks were generated based on Gaussian, Cauchy, wrapped Cauchy and von Mises probability distribution functions by the inverse transform method. The best masks for undersampling ratios of 0.3, 0.4 and 0.5 were chosen for animal experimentation, and were programmed into a Bruker Avance III BioSpec 7.0T MRI system through method programming in ParaVision. Three undersampled mouse heart datasets were obtained using a fast low angle shot (FLASH) sequence, along with a control undersampled phantom dataset. ECG and respiratory gating was used to obtain high quality images. After CS reconstructions were applied to all acquired data, resulting images were quantitatively analyzed using the performance metrics of reconstruction error and Structural Similarity Index (SSIM). The comparative analysis indicated that CS reconstructed images from MRI machine undersampled data were indeed comparable to CS reconstructed images from retrospective undersampled data, and that CS techniques are practical in a preclinical setting. The implementation achieved 2 to 4 times acceleration for image acquisition and satisfactory quality of image reconstruction.

Preoperative three-dimensional model creation of magnetic resonance brain images as a tool to assist neurosurgical planning.

PubMed

Spottiswoode, B S; van den Heever, D J; Chang, Y; Engelhardt, S; Du Plessis, S; Nicolls, F; Hartzenberg, H B; Gretschel, A

2013-01-01

Neurosurgeons regularly plan their surgery using magnetic resonance imaging (MRI) images, which may show a clear distinction between the area to be resected and the surrounding healthy brain tissue depending on the nature of the pathology. However, this distinction is often unclear with the naked eye during the surgical intervention, and it may be difficult to infer depth and an accurate volumetric interpretation from a series of MRI image slices. In this work, MRI data are used to create affordable patient-specific 3-dimensional (3D) scale models of the brain which clearly indicate the location and extent of a tumour relative to brain surface features and important adjacent structures. This is achieved using custom software and rapid prototyping. In addition, functionally eloquent areas identified using functional MRI are integrated into the 3D models. Preliminary in vivo results are presented for 2 patients. The accuracy of the technique was estimated both theoretically and by printing a geometrical phantom, with mean dimensional errors of less than 0.5 mm observed. This may provide a practical and cost-effective tool which can be used for training, and during neurosurgical planning and intervention. Copyright © 2013 S. Karger AG, Basel.

Current whole-body MRI applications in the neurofibromatoses

PubMed Central

Fayad, Laura M.; Khan, Muhammad Shayan; Bredella, Miriam A.; Harris, Gordon J.; Evans, D. Gareth; Farschtschi, Said; Jacobs, Michael A.; Chhabra, Avneesh; Salamon, Johannes M.; Wenzel, Ralph; Mautner, Victor F.; Dombi, Eva; Cai, Wenli; Plotkin, Scott R.; Blakeley, Jaishri O.

2016-01-01

Objectives: The Response Evaluation in Neurofibromatosis and Schwannomatosis (REiNS) International Collaboration Whole-Body MRI (WB-MRI) Working Group reviewed the existing literature on WB-MRI, an emerging technology for assessing disease in patients with neurofibromatosis type 1 (NF1), neurofibromatosis type 2 (NF2), and schwannomatosis (SWN), to recommend optimal image acquisition and analysis methods to enable WB-MRI as an endpoint in NF clinical trials. Methods: A systematic process was used to review all published data about WB-MRI in NF syndromes to assess diagnostic accuracy, feasibility and reproducibility, and data about specific techniques for assessment of tumor burden, characterization of neoplasms, and response to therapy. Results: WB-MRI at 1.5T or 3.0T is feasible for image acquisition. Short tau inversion recovery (STIR) sequence is used in all investigations to date, suggesting consensus about the utility of this sequence for detection of WB tumor burden in people with NF. There are insufficient data to support a consensus statement about the optimal imaging planes (axial vs coronal) or 2D vs 3D approaches. Functional imaging, although used in some NF studies, has not been systematically applied or evaluated. There are no comparative studies between regional vs WB-MRI or evaluations of WB-MRI reproducibility. Conclusions: WB-MRI is feasible for identifying tumors using both 1.5T and 3.0T systems. The STIR sequence is a core sequence. Additional investigation is needed to define the optimal approach for volumetric analysis, the reproducibility of WB-MRI in NF, and the diagnostic performance of WB-MRI vs regional MRI. PMID:27527647

Paradoxical correlation between signal in functional magnetic resonance imaging and deoxygenated haemoglobin content in capillaries: a new theoretical explanation

NASA Astrophysics Data System (ADS)

Yamamoto, Toru; Kato, Toshinori

2002-04-01

Signal increases in functional magnetic resonance imaging (fMRI) are believed to be a result of decreased paramagnetic deoxygenated haemoglobin (deoxyHb) content in the neural activation area. However, discrepancies in this canonical blood oxygenation level dependent (BOLD) theory have been pointed out in studies using optical techniques, which directly measure haemoglobin changes. To explain the discrepancies, we developed a new theory bridging magnetic resonance (MR) signal and haemoglobin changes. We focused on capillary influences, which have been neglected in most previous fMRI studies and performed a combined fMRI and near-infrared spectroscopy (NIRS) study using a language task. Paradoxically, both the MR signal and deoxyHb content increased in Broca's area. On the other hand, fMRI activation in the auditory area near large veins correlated with a mirror-image decrease in deoxyHb and increase in oxygenated haemoglobin (oxyHb), in agreement with canonical BOLD theory. All fMRI signal changes correlated consistently with changes in oxyHb, the diamagnetism of which is insensitive to MR. We concluded that the discrepancy with the canonical BOLD theory is caused by the fact that the BOLD theory ignores the effect of the capillaries. Our theory explains the paradoxical phenomena of the oxyHb and deoxyHb contributions to the MR signal and gives a new insight into the precise haemodynamics of activation by analysing fMRI and NIRS data.

Temporal reliability of ultra-high field resting-state MRI for single-subject sensorimotor and language mapping.

PubMed

Branco, Paulo; Seixas, Daniela; Castro, São Luís

2018-03-01

Resting-state fMRI is a well-suited technique to map functional networks in the brain because unlike task-based approaches it requires little collaboration from subjects. This is especially relevant in clinical settings where a number of subjects cannot comply with task demands. Previous studies using conventional scanner fields have shown that resting-state fMRI is able to map functional networks in single subjects, albeit with moderate temporal reliability. Ultra-high resolution (7T) imaging provides higher signal-to-noise ratio and better spatial resolution and is thus well suited to assess the temporal reliability of mapping results, and to determine if resting-state fMRI can be applied in clinical decision making including preoperative planning. We used resting-state fMRI at ultra-high resolution to examine whether the sensorimotor and language networks are reliable over time - same session and one week after. Resting-state networks were identified for all subjects and sessions with good accuracy. Both networks were well delimited within classical regions of interest. Mapping was temporally reliable at short and medium time-scales as demonstrated by high values of overlap in the same session and one week after for both networks. Results were stable independently of data quality metrics and physiological variables. Taken together, these findings provide strong support for the suitability of ultra-high field resting-state fMRI mapping at the single-subject level. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Measuring Pain for Patients Seeking Physical Therapy: Can Functional Magnetic Resonance Imaging (fMRI) Help?

PubMed

Elliott, James M; Owen, Meriel; Bishop, Mark D; Sparks, Cheryl; Tsao, Henry; Walton, David M; Weber, Kenneth A; Wideman, Timothy H

2017-01-01

In the multidisciplinary fields of pain medicine and rehabilitation, advancing techniques such as functional magnetic resonance imaging (fMRI) are used to enhance our understanding of the pain experience. Given that such measures, in some circles, are expected to help us understand the brain in pain, future research in pain measurement is undeniably rich with possibility. However, pain remains intensely personal and represents a multifaceted experience, unique to each individual; no single measure in isolation, fMRI included, can prove or quantify its magnitude beyond the patient self-report. Physical therapists should be aware of cutting-edge advances in measuring the patient's pain experience, and they should work closely with professionals in other disciplines (eg, magnetic resonance physicists, biomedical engineers, radiologists, psychologists) to guide the exploration and development of multimodal pain measurement and management on a patient-by-patient basis. The primary purpose of this perspective article is to provide a brief overview of fMRI and inform physical therapist clinicians of the pros and cons when utilized as a measure of the patient's perception of pain. A secondary purpose is to describe current known factors that influence the quality of fMRI data and its analyses, as well as the potential for future clinical applications relevant to physical therapist practice. Lastly, the interested reader is introduced and referred to existing guidelines and recommendations for reporting fMRI research. © 2017 American Physical Therapy Association.

Diffusion fMRI detects white-matter dysfunction in mice with acute optic neuritis

PubMed Central

Lin, Tsen-Hsuan; Spees, William M.; Chiang, Chia-Wen; Trinkaus, Kathryn; Cross, Anne H.; Song, Sheng-Kwei

2014-01-01

Optic neuritis is a frequent and early symptom of multiple sclerosis (MS). Conventional magnetic resonance (MR) techniques provide means to assess multiple MS-related pathologies, including axonal injury, demyelination, and inflammation. A method to directly and non-invasively probe white-matter function could further elucidate the interplay of underlying pathologies and functional impairments. Previously, we demonstrated a significant 27% activation-associated decrease in the apparent diffusion coefficient of water perpendicular to the axonal fibers (ADC⊥) in normal C57BL/6 mouse optic nerve with visual stimulation using diffusion fMRI. Here we apply this approach to explore the relationship between visual acuity, optic nerve pathology, and diffusion fMRI in the experimental autoimmune encephalomyelitis (EAE) mouse model of optic neuritis. Visual stimulation produced a significant 25% (vs. baseline) ADC⊥ decrease in sham EAE optic nerves, while only a 7% (vs. baseline) ADC⊥ decrease was seen in EAE mice with acute optic neuritis. The reduced activation-associated ADC⊥ response correlated with post-MRI immunohistochemistry determined pathologies (including inflammation, demyelination, and axonal injury). The negative correlation between activation-associated ADC⊥ response and visual acuity was also found when pooling EAE-affected and sham groups under our experimental criteria. Results suggest that reduction in diffusion fMRI directly reflects impaired axonal-activation in EAE mice with optic neuritis. Diffusion fMRI holds promise for directly gauging in vivo white-matter dysfunction or therapeutic responses in MS patients. PMID:24632420

Single slice US-MRI registration for neurosurgical MRI-guided US

NASA Astrophysics Data System (ADS)

Pardasani, Utsav; Baxter, John S. H.; Peters, Terry M.; Khan, Ali R.

2016-03-01

Image-based ultrasound to magnetic resonance image (US-MRI) registration can be an invaluable tool in image-guided neuronavigation systems. State-of-the-art commercial and research systems utilize image-based registration to assist in functions such as brain-shift correction, image fusion, and probe calibration. Since traditional US-MRI registration techniques use reconstructed US volumes or a series of tracked US slices, the functionality of this approach can be compromised by the limitations of optical or magnetic tracking systems in the neurosurgical operating room. These drawbacks include ergonomic issues, line-of-sight/magnetic interference, and maintenance of the sterile field. For those seeking a US vendor-agnostic system, these issues are compounded with the challenge of instrumenting the probe without permanent modification and calibrating the probe face to the tracking tool. To address these challenges, this paper explores the feasibility of a real-time US-MRI volume registration in a small virtual craniotomy site using a single slice. We employ the Linear Correlation of Linear Combination (LC2) similarity metric in its patch-based form on data from MNI's Brain Images for Tumour Evaluation (BITE) dataset as a PyCUDA enabled Python module in Slicer. By retaining the original orientation information, we are able to improve on the poses using this approach. To further assist the challenge of US-MRI registration, we also present the BOXLC2 metric which demonstrates a speed improvement to LC2, while retaining a similar accuracy in this context.

Translating Neurocognitive Models of Auditory-Verbal Hallucinations into Therapy: Using Real-time fMRI-Neurofeedback to Treat Voices

PubMed Central

Fovet, Thomas; Orlov, Natasza; Dyck, Miriam; Allen, Paul; Mathiak, Klaus; Jardri, Renaud

2016-01-01

Auditory-verbal hallucinations (AVHs) are frequent and disabling symptoms, which can be refractory to conventional psychopharmacological treatment in more than 25% of the cases. Recent advances in brain imaging allow for a better understanding of the neural underpinnings of AVHs. These findings strengthened transdiagnostic neurocognitive models that characterize these frequent and disabling experiences. At the same time, technical improvements in real-time functional magnetic resonance imaging (fMRI) enabled the development of innovative and non-invasive methods with the potential to relieve psychiatric symptoms, such as fMRI-based neurofeedback (fMRI-NF). During fMRI-NF, brain activity is measured and fed back in real time to the participant in order to help subjects to progressively achieve voluntary control over their own neural activity. Precisely defining the target brain area/network(s) appears critical in fMRI-NF protocols. After reviewing the available neurocognitive models for AVHs, we elaborate on how recent findings in the field may help to develop strong a priori strategies for fMRI-NF target localization. The first approach relies on imaging-based “trait markers” (i.e., persistent traits or vulnerability markers that can also be detected in the presymptomatic and remitted phases of AVHs). The goal of such strategies is to target areas that show aberrant activations during AVHs or are known to be involved in compensatory activation (or resilience processes). Brain regions, from which the NF signal is derived, can be based on structural MRI and neurocognitive knowledge, or functional MRI information collected during specific cognitive tasks. Because hallucinations are acute and intrusive symptoms, a second strategy focuses more on “state markers.” In this case, the signal of interest relies on fMRI capture of the neural networks exhibiting increased activity during AVHs occurrences, by means of multivariate pattern recognition methods. The fine-grained activity patterns concomitant to hallucinations can then be fed back to the patients for therapeutic purpose. Considering the potential cost necessary to implement fMRI-NF, proof-of-concept studies are urgently required to define the optimal strategy for application in patients with AVHs. This technique has the potential to establish a new brain imaging-guided psychotherapy for patients that do not respond to conventional treatments and take functional neuroimaging to therapeutic applications. PMID:27445865

Evaluation of MRI issues for a new neurological implant, the Sensor Reservoir.

PubMed

Shellock, Frank G; Knebel, Jörg; Prat, Angelina D

2013-09-01

A new neurological implant, the Sensor-Reservoir, was developed to provide a relative measurement of ICP, which permits a noninvasive technique to detect and localize occlusions in ventricular drainage systems and, thus, to identify mechanical damage to shunt valves. The "reservoir" of this device can be used to administer medication or a contrast agent, to extract cerebral spinal fluid (CSF), and with the possibility of directly measuring ICP. The Sensor-Reservoir was evaluated to identify possible MRI-related issues at 1.5-T/64-MHz and 3-T/128-MHz. Standard testing techniques were utilized to evaluate magnetic field interactions (i.e., translational attraction and torque), MRI-related heating, and artifacts at 3-T for the Sensor-Reservoir. In addition, 12 samples of the Sensor-Reservoir underwent testing to determine if the function of these devices was affected by exposures to various MRI conditions at 1.5-T/64-MHz and 3-T/128-MHz. Magnetic field interactions for the Sensor-Reservoir were not substantial. The heating results indicated a highest temperature rise of 1.8 °C, which poses no patient risks. Artifacts were relatively small in relation to the size and shape of the Sensor-Reservoir, but may interfere diagnostically if the area of interest is near the device. All devices were unaffected by exposures to MRI conditions at 1.5-T/64-MHz and 3-T/128-MHz. When specific guidelines are followed, the Sensor-Reservoir is "MR conditional" for patients undergoing MRI examinations at 3-T or less. Copyright © 2013 Elsevier Inc. All rights reserved.

Regional homogeneity changes between heroin relapse and non-relapse patients under methadone maintenance treatment: a resting-state fMRI study.

PubMed

Chang, Haifeng; Li, Wei; Li, Qiang; Chen, Jiajie; Zhu, Jia; Ye, Jianjun; Liu, Jierong; Li, Zhe; Li, Yongbin; Shi, Ming; Wang, Yarong; Wang, Wei

2016-08-18

Methadone maintenance treatment (MMT) is recognized as one of the most effective treatments for heroin addiction but its effect is dimmed by the high incidence of heroin relapse. However, underlying neurobiology mechanism of heroin relapse under MMT is still largely unknown. Here, we took advantage of a resting-state fMRI technique by analysis of regional homogeneity (ReHo), and tried to explore the difference of brain function between heroin relapsers and non-relapsers in MMT. Forty MMT patients were included and received a 12-month follow-up. All patients were given baseline resting-state fMRI scans by using a 3.0 T GE Signa Excite HD whole-body MRI system. Monthly self-report and urine test were used to assess heroin relapse or non-relapse. Subjective craving was measured with visual analog scale. The correlation between ReHo and the degree of heroin relapse was analyzed. Compared with the non-relapsers, ReHo values were increased in the bilateral medial orbitofrontal cortex, right caudate, and right cerebellum of the heroin relapsers while those in the left parahippocampal gyrus, left middle temporal gyrus, right lingual gyrus, and precuneus were decreased in heroin relapsers. Importantly, altered ReHo in the right caudate were positively correlated with heroin relapse rates or subjective craving response. Using the resting-state fMRI technique by analysis of ReHo, we provided the first resting-state fMRI evidence that right caudate may serve as a potential biomarker for heroin relapse prediction and also as a promising target for reducing relapse risk.

Structural and functional evaluation of cortical motor areas in Amyotrophic Lateral Sclerosis.

PubMed

Cosottini, Mirco; Pesaresi, Ilaria; Piazza, Selina; Diciotti, Stefano; Cecchi, Paolo; Fabbri, Serena; Carlesi, Cecilia; Mascalchi, Mario; Siciliano, Gabriele

2012-03-01

The structural and functional data gathered with Magnetic Resonance Imaging (MRI) techniques about the brain cortical motor damage in Amyotrophic Lateral Sclerosis (ALS) are controversial. In fact some structural MRI studies showed foci of gray matter (GM) atrophy in the precentral gyrus, even in the early stage, while others did not. Most functional MRI (fMRI) studies in ALS reported hyperactivation of extra-primary motor cortices, while contradictory results were obtained on the activation of the primary motor cortex. We aimed to investigate the cortical motor circuitries in ALS patients by a combined structural and functional approach. Twenty patients with definite ALS and 16 healthy subjects underwent a structural examination with acquisition of a 3D T1-weighted sequence and fMRI examination during a maximal force handgrip task executed with the right-hand, the left-hand and with both hands simultaneously. The T1-weighted images were analyzed with Voxel-Based Morphometry (VBM) that showed several clusters of reduced cortical GM in ALS patients compared to controls including the pre and postcentral gyri, the superior, middle and inferior frontal gyri, the supplementary motor area, the superior and inferior parietal cortices and the temporal lobe, bilaterally but more extensive on the right side. In ALS patients a significant hypoactivation of the primary sensory motor cortex and frontal dorsal premotor areas as compared to controls was observed. The hypoactivated areas matched with foci of cortical atrophy demonstrated by VBM. The fMRI analysis also showed an enhanced activation in the ventral premotor frontal areas and in the parietal cortex pertaining to the fronto-parietal motor circuit which paralleled with disease progression rate and matched with cortical regions of atrophy. The hyperactivation of the fronto-parietal circuit was asymmetric and prevalent in the left hemisphere. VBM and fMRI identified structural and functional markers of an extended cortical damage within the motor circuit of ALS patients. The functional changes in non-primary motor cortices pertaining to fronto-parietal circuit suggest an over-recruitment of a pre-existing physiological sensory-motor network. However, the concomitant fronto-parietal cortical atrophy arises the possibility that such a hyper-activation reflects cortical hyper-excitability due to loss of inhibitory inter-neurons. Copyright © 2011 Elsevier Inc. All rights reserved.

Inferring functional connectivity in MRI using Bayesian network structure learning with a modified PC algorithm

PubMed Central

Iyer, Swathi; Shafran, Izhak; Grayson, David; Gates, Kathleen; Nigg, Joel; Fair, Damien

2013-01-01

Resting state functional connectivity MRI (rs-fcMRI) is a popular technique used to gauge the functional relatedness between regions in the brain for typical and special populations. Most of the work to date determines this relationship by using Pearson's correlation on BOLD fMRI timeseries. However, it has been recognized that there are at least two key limitations to this method. First, it is not possible to resolve the direct and indirect connections/influences. Second, the direction of information flow between the regions cannot be differentiated. In the current paper, we follow-up on recent work by Smith et al (2011), and apply a Bayesian approach called the PC algorithm to both simulated data and empirical data to determine whether these two factors can be discerned with group average, as opposed to single subject, functional connectivity data. When applied on simulated individual subjects, the algorithm performs well determining indirect and direct connection but fails in determining directionality. However, when applied at group level, PC algorithm gives strong results for both indirect and direct connections and the direction of information flow. Applying the algorithm on empirical data, using a diffusion-weighted imaging (DWI) structural connectivity matrix as the baseline, the PC algorithm outperformed the direct correlations. We conclude that, under certain conditions, the PC algorithm leads to an improved estimate of brain network structure compared to the traditional connectivity analysis based on correlations. PMID:23501054

Neuroimaging and neuromodulation approaches to study eating behavior and prevent and treat eating disorders and obesity.

PubMed

Val-Laillet, D; Aarts, E; Weber, B; Ferrari, M; Quaresima, V; Stoeckel, L E; Alonso-Alonso, M; Audette, M; Malbert, C H; Stice, E

2015-01-01

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. This opens the way to prevention studies using functional and molecular neuroimaging to perform early diagnostics and to phenotype subjects at risk by exploring different neurobehavioral dimensions of the food choices and motivation processes. In the first part of this review, advantages and limitations of neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), pharmacogenetic fMRI and functional near-infrared spectroscopy (fNIRS) will be discussed in the context of recent work dealing with eating behavior, with a particular focus on obesity. In the second part of the review, non-invasive strategies to modulate food-related brain processes and functions will be presented. At the leading edge of non-invasive brain-based technologies is real-time fMRI (rtfMRI) neurofeedback, which is a powerful tool to better understand the complexity of human brain-behavior relationships. rtfMRI, alone or when combined with other techniques and tools such as EEG and cognitive therapy, could be used to alter neural plasticity and learned behavior to optimize and/or restore healthy cognition and eating behavior. Other promising non-invasive neuromodulation approaches being explored are repetitive transcranial magnetic stimulation (rTMS) and transcranial direct-current stimulation (tDCS). Converging evidence points at the value of these non-invasive neuromodulation strategies to study basic mechanisms underlying eating behavior and to treat its disorders. Both of these approaches will be compared in light of recent work in this field, while addressing technical and practical questions. The third part of this review will be dedicated to invasive neuromodulation strategies, such as vagus nerve stimulation (VNS) and deep brain stimulation (DBS). In combination with neuroimaging approaches, these techniques are promising experimental tools to unravel the intricate relationships between homeostatic and hedonic brain circuits. Their potential as additional therapeutic tools to combat pharmacorefractory morbid obesity or acute eating disorders will be discussed, in terms of technical challenges, applicability and ethics. In a general discussion, we will put the brain at the core of fundamental research, prevention and therapy in the context of obesity and eating disorders. 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.

Neuroimaging and neuromodulation approaches to study eating behavior and prevent and treat eating disorders and obesity

PubMed Central

Val-Laillet, D.; Aarts, E.; Weber, B.; Ferrari, M.; Quaresima, V.; Stoeckel, L.E.; Alonso-Alonso, M.; Audette, M.; Malbert, C.H.; Stice, E.

2015-01-01

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. This opens the way to prevention studies using functional and molecular neuroimaging to perform early diagnostics and to phenotype subjects at risk by exploring different neurobehavioral dimensions of the food choices and motivation processes. In the first part of this review, advantages and limitations of neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), pharmacogenetic fMRI and functional near-infrared spectroscopy (fNIRS) will be discussed in the context of recent work dealing with eating behavior, with a particular focus on obesity. In the second part of the review, non-invasive strategies to modulate food-related brain processes and functions will be presented. At the leading edge of non-invasive brain-based technologies is real-time fMRI (rtfMRI) neurofeedback, which is a powerful tool to better understand the complexity of human brain–behavior relationships. rtfMRI, alone or when combined with other techniques and tools such as EEG and cognitive therapy, could be used to alter neural plasticity and learned behavior to optimize and/or restore healthy cognition and eating behavior. Other promising non-invasive neuromodulation approaches being explored are repetitive transcranial magnetic stimulation (rTMS) and transcranial direct-current stimulation (tDCS). Converging evidence points at the value of these non-invasive neuromodulation strategies to study basic mechanisms underlying eating behavior and to treat its disorders. Both of these approaches will be compared in light of recent work in this field, while addressing technical and practical questions. The third part of this review will be dedicated to invasive neuromodulation strategies, such as vagus nerve stimulation (VNS) and deep brain stimulation (DBS). In combination with neuroimaging approaches, these techniques are promising experimental tools to unravel the intricate relationships between homeostatic and hedonic brain circuits. Their potential as additional therapeutic tools to combat pharmacorefractory morbid obesity or acute eating disorders will be discussed, in terms of technical challenges, applicability and ethics. In a general discussion, we will put the brain at the core of fundamental research, prevention and therapy in the context of obesity and eating disorders. 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. PMID:26110109

How Can Neuroscience Enhance Gifted Education?

ERIC Educational Resources Information Center

Newman, Sharlene D.

2009-01-01

With the advent of imaging techniques like functional magnetic resonance imaging (fMRI) over the past couple of decades, the people's understanding of the brain has increased dramatically. One of the newer research frontiers is the discovery of neural underpinnings of individual differences in cognitive ability. This research has the potential to…

Functional connectivity and microstructural white matter changes in phenocopy frontotemporal dementia.

PubMed

Meijboom, R; Steketee, R M E; de Koning, I; Osse, R J; Jiskoot, L C; de Jong, F J; van der Lugt, A; van Swieten, J C; Smits, M

2017-04-01

Phenocopy frontotemporal dementia (phFTD) is a rare and poorly understood clinical syndrome. PhFTD shows core behavioural variant FTD (bvFTD) symptoms without associated cognitive deficits and brain abnormalities on conventional MRI and without progression. In contrast to phFTD, functional connectivity and white matter (WM) microstructural abnormalities have been observed in bvFTD. We hypothesise that phFTD belongs to the same disease spectrum as bvFTD and investigated whether functional connectivity and microstructural WM changes similar to bvFTD are present in phFTD. Seven phFTD patients without progression or alternative psychiatric diagnosis, 12 bvFTD patients and 17 controls underwent resting state functional MRI (rs-fMRI) and diffusion tensor imaging (DTI). Default mode network (DMN) connectivity and WM measures were compared between groups. PhFTD showed subtly increased DMN connectivity and subtle microstructural changes in frontal WM tracts. BvFTD showed abnormalities in similar regions as phFTD, but had lower increased DMN connectivity and more extensive microstructural WM changes. Our findings can be interpreted as neuropathological changes in phFTD and are in support of the hypothesis that phFTD and bvFTD may belong to the same disease spectrum. Advanced MRI techniques, objectively identifying brain abnormalities, would therefore be potentially suited to improve the diagnosis of phFTD. • PhFTD shows brain abnormalities that are similar to bvFTD. • PhFTD shows increased functional connectivity in the parietal default mode network. • PhFTD shows microstructural white matter abnormalities in the frontal lobe. • We hypothesise phFTD and bvFTD may belong to the same disease spectrum.

Resting-State Functional Connectivity in the Infant Brain: Methods, Pitfalls, and Potentiality.

PubMed

Mongerson, Chandler R L; Jennings, Russell W; Borsook, David; Becerra, Lino; Bajic, Dusica

2017-01-01

Early brain development is characterized by rapid growth and perpetual reconfiguration, driven by a dynamic milieu of heterogeneous processes. Postnatal brain plasticity is associated with increased vulnerability to environmental stimuli. However, little is known regarding the ontogeny and temporal manifestations of inter- and intra-regional functional connectivity that comprise functional brain networks. Resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a promising non-invasive neuroinvestigative tool, measuring spontaneous fluctuations in blood oxygen level dependent (BOLD) signal at rest that reflect baseline neuronal activity. Over the past decade, its application has expanded to infant populations providing unprecedented insight into functional organization of the developing brain, as well as early biomarkers of abnormal states. However, many methodological issues of rs-fMRI analysis need to be resolved prior to standardization of the technique to infant populations. As a primary goal, this methodological manuscript will (1) present a robust methodological protocol to extract and assess resting-state networks in early infancy using independent component analysis (ICA), such that investigators without previous knowledge in the field can implement the analysis and reliably obtain viable results consistent with previous literature; (2) review the current methodological challenges and ethical considerations associated with emerging field of infant rs-fMRI analysis; and (3) discuss the significance of rs-fMRI application in infants for future investigations of neurodevelopment in the context of early life stressors and pathological processes. The overarching goal is to catalyze efforts toward development of robust, infant-specific acquisition, and preprocessing pipelines, as well as promote greater transparency by researchers regarding methods used.

Functional brain segmentation using inter-subject correlation in fMRI.

PubMed

Kauppi, Jukka-Pekka; Pajula, Juha; Niemi, Jari; Hari, Riitta; Tohka, Jussi

2017-05-01

The human brain continuously processes massive amounts of rich sensory information. To better understand such highly complex brain processes, modern neuroimaging studies are increasingly utilizing experimental setups that better mimic daily-life situations. A new exploratory data-analysis approach, functional segmentation inter-subject correlation analysis (FuSeISC), was proposed to facilitate the analysis of functional magnetic resonance (fMRI) data sets collected in these experiments. The method provides a new type of functional segmentation of brain areas, not only characterizing areas that display similar processing across subjects but also areas in which processing across subjects is highly variable. FuSeISC was tested using fMRI data sets collected during traditional block-design stimuli (37 subjects) as well as naturalistic auditory narratives (19 subjects). The method identified spatially local and/or bilaterally symmetric clusters in several cortical areas, many of which are known to be processing the types of stimuli used in the experiments. The method is not only useful for spatial exploration of large fMRI data sets obtained using naturalistic stimuli, but also has other potential applications, such as generation of a functional brain atlases including both lower- and higher-order processing areas. Finally, as a part of FuSeISC, a criterion-based sparsification of the shared nearest-neighbor graph was proposed for detecting clusters in noisy data. In the tests with synthetic data, this technique was superior to well-known clustering methods, such as Ward's method, affinity propagation, and K-means ++. Hum Brain Mapp 38:2643-2665, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Resting-State Functional Connectivity in the Infant Brain: Methods, Pitfalls, and Potentiality

PubMed Central

Mongerson, Chandler R. L.; Jennings, Russell W.; Borsook, David; Becerra, Lino; Bajic, Dusica

2017-01-01

Early brain development is characterized by rapid growth and perpetual reconfiguration, driven by a dynamic milieu of heterogeneous processes. Postnatal brain plasticity is associated with increased vulnerability to environmental stimuli. However, little is known regarding the ontogeny and temporal manifestations of inter- and intra-regional functional connectivity that comprise functional brain networks. Resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a promising non-invasive neuroinvestigative tool, measuring spontaneous fluctuations in blood oxygen level dependent (BOLD) signal at rest that reflect baseline neuronal activity. Over the past decade, its application has expanded to infant populations providing unprecedented insight into functional organization of the developing brain, as well as early biomarkers of abnormal states. However, many methodological issues of rs-fMRI analysis need to be resolved prior to standardization of the technique to infant populations. As a primary goal, this methodological manuscript will (1) present a robust methodological protocol to extract and assess resting-state networks in early infancy using independent component analysis (ICA), such that investigators without previous knowledge in the field can implement the analysis and reliably obtain viable results consistent with previous literature; (2) review the current methodological challenges and ethical considerations associated with emerging field of infant rs-fMRI analysis; and (3) discuss the significance of rs-fMRI application in infants for future investigations of neurodevelopment in the context of early life stressors and pathological processes. The overarching goal is to catalyze efforts toward development of robust, infant-specific acquisition, and preprocessing pipelines, as well as promote greater transparency by researchers regarding methods used. PMID:28856131

Breast MRI in community practice: equipment and imaging techniques at facilities in the Breast Cancer Surveillance Consortium.

PubMed

DeMartini, Wendy B; Ichikawa, Laura; Yankaskas, Bonnie C; Buist, Diana; Kerlikowske, Karla; Geller, Berta; Onega, Tracy; Rosenberg, Robert D; Lehman, Constance D

2010-11-01

MRI is increasingly used for the detection of breast carcinoma. Little is known about breast MRI techniques among community practice facilities. The aim of this study was to evaluate equipment and acquisition techniques used by community facilities across the United States, including compliance with minimum standards by the ACRIN® 6667 Trial and the European Society of Breast Imaging. Breast Cancer Surveillance Consortium facilities performing breast MRI were identified and queried by survey regarding breast MRI equipment and technical parameters. Variables included scanner field strength, coil type, acquisition coverage, slice thickness, and the timing of the initial postcontrast sequence. Results were tallied and percentages of facilities meeting ACRIN® and European Society of Breast Imaging standards were calculated. From 23 facilities performing breast MRI, results were obtained from 14 (61%) facilities with 16 MRI scanners reporting 18 imaging parameters. Compliance with equipment recommendations of ≥1.5-T field strength was 94% and of a dedicated breast coil was 100%. Eighty-three percent of acquisitions used bilateral postcontrast techniques, and 78% used slice thickness≤3 mm. The timing of initial postcontrast sequences ranged from 58 seconds to 8 minutes 30 seconds, with 63% meeting recommendations for completion within 4 minutes. Nearly all surveyed facilities met ACRIN and European Society of Breast Imaging standards for breast MRI equipment. The majority met standards for acquisition parameters, although techniques varied, in particular for the timing of initial postcontrast imaging. Further guidelines by the ACR Breast MRI Accreditation Program will be of importance in facilitating standardized and high-quality breast MRI. Copyright © 2010 American College of Radiology. Published by Elsevier Inc. All rights reserved.

SU-E-J-07: A Functional MR Protocol for the Pancreatic Tumor Delineation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andreychenko, A; Heerkens, H; Meijer, G

2014-06-01

Purpose: Pancreatic cancer is one of the cancers with the poorest survival prognosis. At the time of diagnosis most of pancreatic cancers are unresectable and those patients can be treated by radiotherapy. Radiotherapy for pancreatic cancer is limited due to uncertainties in CT-based delineations. MRI provides an excellent soft tissue contrast. Here, an MR protocol is developed to improve delineations for radiotherapy treatment of pancreatic cancer. In a later stage this protocol can also be used for on-line visualization of the pancreas during MRI guided treatments. Methods: Nine pancreatic cancer patients were included. The MR protocol included T2 weighted(T2w), T1more » weighted(T1w), diffusion weighted(DWI) and dynamic contrast enhanced(DCE) techniques. The tumor was delineated on T2w and T1w MRI by an experienced radiation oncologist. Healthy pancreas or pancreatitis (assigned by the oncologist based on T2w) areas were also delineated. Apparent diffusion coefficient(ADC), and area under the curve(AUC)/time to peak(TTP) maps were obtained from DWI and DCE scans, respectively. Results: A clear demarcation of tumor area was visible on b800 DWI images in 5 patients. ADC maps of those patients characterized tumor as an area with restricted water diffusion. Tumor delineations based on solely DCE were possible in 7 patients. In 6 of those patients AUC maps demonstrated tumor heterogeneity: a hypointense area with a hyperintense ring. TTP values clearly discriminated the tumor and the healthy pancreas but could not distinguish tumor and the pancreatitis accurately. Conclusion: MR imaging results in a more pronounced tumor contrast than contrast enhanced CT. The addition of quantitative, functional MRI provides valuable, additional information to the radiation oncologist on the spatial tumor extent by discriminating tumor from the healthy pancreas(TTP, DWI) and characterizing the tumor(ADC). Our findings indicate that tumor delineation in pancreatic cancer can greatly benefit from the addition of MRI and especially functional MR techniques.« less

Blood oxygen level dependent magnetic resonance imaging for detecting pathological patterns in lupus nephritis patients: a preliminary study using a decision tree model.

PubMed

Shi, Huilan; Jia, Junya; Li, Dong; Wei, Li; Shang, Wenya; Zheng, Zhenfeng

2018-02-09

Precise renal histopathological diagnosis will guide therapy strategy in patients with lupus nephritis. Blood oxygen level dependent (BOLD) magnetic resonance imaging (MRI) has been applicable noninvasive technique in renal disease. This current study was performed to explore whether BOLD MRI could contribute to diagnose renal pathological pattern. Adult patients with lupus nephritis renal pathological diagnosis were recruited for this study. Renal biopsy tissues were assessed based on the lupus nephritis ISN/RPS 2003 classification. The Blood oxygen level dependent magnetic resonance imaging (BOLD-MRI) was used to obtain functional magnetic resonance parameter, R2* values. Several functions of R2* values were calculated and used to construct algorithmic models for renal pathological patterns. In addition, the algorithmic models were compared as to their diagnostic capability. Both Histopathology and BOLD MRI were used to examine a total of twelve patients. Renal pathological patterns included five classes III (including 3 as class III + V) and seven classes IV (including 4 as class IV + V). Three algorithmic models, including decision tree, line discriminant, and logistic regression, were constructed to distinguish the renal pathological pattern of class III and class IV. The sensitivity of the decision tree model was better than that of the line discriminant model (71.87% vs 59.48%, P < 0.001) and inferior to that of the Logistic regression model (71.87% vs 78.71%, P < 0.001). The specificity of decision tree model was equivalent to that of the line discriminant model (63.87% vs 63.73%, P = 0.939) and higher than that of the logistic regression model (63.87% vs 38.0%, P < 0.001). The Area under the ROC curve (AUROCC) of the decision tree model was greater than that of the line discriminant model (0.765 vs 0.629, P < 0.001) and logistic regression model (0.765 vs 0.662, P < 0.001). BOLD MRI is a useful non-invasive imaging technique for the evaluation of lupus nephritis. Decision tree models constructed using functions of R2* values may facilitate the prediction of renal pathological patterns.

Minimizing Noise in Pediatric Task-Based functional MRI; Adolescents with Developmental Disabilities and Typical Development

PubMed Central

Fassbender, Catherine; Muhkerjee, Prerona; Schweitzer, Julie B.

2017-01-01

Functional Magnetic Resonance Imaging (fMRI) represents a powerful tool with which to examine brain functioning and development in typically developing pediatric groups as well as children and adolescents with clinical disorders. However, fMRI data can be highly susceptible to misinterpretation due to the effects of excessive levels of noise, often related to head motion. Imaging children, especially with developmental disorders, requires extra considerations related to hyperactivity, anxiety and the ability to perform and maintain attention to the fMRI paradigm. We discuss a number of methods that can be employed to minimize noise, in particular movement-related noise. To this end we focus on strategies prior to, during and following the data acquisition phase employed primarily within our own laboratory. We discuss the impact of factors such as experimental design, screening of potential participants and pre-scan training on head motion in our adolescents with developmental disorders and typical development. We make some suggestions that may minimize noise during data acquisition itself and finally we briefly discuss some current processing techniques that may help to identify and remove noise in the data. Many advances have been made in the field of pediatric imaging, particularly with regard to research involving children with developmental disorders. Mindfulness of issues such as those discussed here will ensure continued progress and greater consistency across studies. PMID:28130195

Comparison of ASL and DCE MRI for the non-invasive measurement of renal blood flow: quantification and reproducibility.

PubMed

Cutajar, Marica; Thomas, David L; Hales, Patrick W; Banks, T; Clark, Christopher A; Gordon, Isky

2014-06-01

To investigate the reproducibility of arterial spin labelling (ASL) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and quantitatively compare these techniques for the measurement of renal blood flow (RBF). Sixteen healthy volunteers were examined on two different occasions. ASL was performed using a multi-TI FAIR labelling scheme with a segmented 3D-GRASE imaging module. DCE MRI was performed using a 3D-FLASH pulse sequence. A Bland-Altman analysis was used to assess repeatability of each technique, and determine the degree of correspondence between the two methods. The overall mean cortical renal blood flow (RBF) of the ASL group was 263 ± 41 ml min(-1) [100 ml tissue](-1), and using DCE MRI was 287 ± 70 ml min(-1) [100 ml tissue](-1). The group coefficient of variation (CVg) was 18 % for ASL and 28 % for DCE-MRI. Repeatability studies showed that ASL was more reproducible than DCE with CVgs of 16 % and 25 % for ASL and DCE respectively. Bland-Altman analysis comparing the two techniques showed a good agreement. The repeated measures analysis shows that the ASL technique has better reproducibility than DCE-MRI. Difference analysis shows no significant difference between the RBF values of the two techniques. Reliable non-invasive monitoring of renal blood flow is currently clinically unavailable. Renal arterial spin labelling MRI is robust and repeatable. Renal dynamic contrast-enhanced MRI is robust and repeatable. ASL blood flow values are similar to those obtained using DCE-MRI.

Hepatic Phospholipidosis Is Associated with Altered Hepatobiliary Function as Assessed by Gadoxetate Dynamic Contrast-enhanced Magnetic Resonance Imaging.

PubMed

Lenhard, Stephen C; Lev, Mally; Webster, Lindsey O; Peterson, Richard A; Goulbourne, Christopher N; Miller, Richard T; Jucker, Beat M

2016-01-01

To determine if amiodarone induces hepatic phospholipidosis (PLD) sufficient to detect changes in hepatobiliary transporter function as assessed by gadoxetate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), rats were orally dosed with vehicle (1% methyl cellulose) or amiodarone (300 mg/kg/day) for 7 consecutive days. Gadoxetate DCE-MRI occurred at baseline, day 7, and following a 2-week washout of amiodarone. At day 7, the gadoxetate washout rate was significantly decreased compared to the vehicle group. Blood chemistry analysis revealed no significant changes in liver enzymes (alanine aminotransferase [ALT]/aspartate aminotransferase [AST]/alkaline phosphatase [ALP]), bilirubin, or bile acids between vehicle or amiodarone groups. Hepatic PLD was confirmed in all rats treated with amiodarone at day 7 by transmission electron microscopy. Following the 2-week washout, there was no ultrastructural evidence of hepatic PLD in rats and the gadoxetate washout rate returned to baseline levels. This is the first study to show the application of gadoxetate DCE-MRI to detect hepatobiliary functional changes associated with PLD and offer a potential new technique with clinical utility in patients suspected of having PLD. These results also suggest PLD itself has functional consequences on hepatobiliary function in the absence of biomarkers of toxicity, given the cause/effect relationship between PLD and function has not been fully established. © The Author(s) 2015.

MRI compatibility of robot actuation techniques--a comparative study.

PubMed

Fischer, Gregory S; Krieger, Axel; Iordachita, Iulian; Csoma, Csaba; Whitcomb, Louis L; Gabor, Fichtinger

2008-01-01

This paper reports an experimental evaluation of the following three different MRI-compatible actuators: a Shinsei ultrasonic motor a Nanomotion ultrasonic motor and a pneumatic cylinder actuator. We report the results of a study comparing the effect of these actuators on the signal to noise ratio (SNR) of MRJ images under a variety of experimental conditions. Evaluation was performed with the controller inside and outside the scanner room and with both 1.5T and 3T MRI scanners. Pneumatic cylinders function with no loss of SNR with controller both inside and outside of the scanner room. The Nanomotion motor performs with moderate loss of SNR when moving during imaging. The Shinsei is unsuitable for motion during imaging. All may be used when motion is appropriately interleaved with imaging cycles.

Bone marrow invasion in multiple myeloma and metastatic disease.

PubMed

Vilanova, J C; Luna, A

2016-04-01

Magnetic resonance imaging (MRI) of the spine is the imaging study of choice for the management of bone marrow disease. MRI sequences enable us to integrate structural and functional information for detecting, staging, and monitoring the response the treatment of multiple myeloma and bone metastases in the spine. Whole-body MRI has been incorporated into different guidelines as the technique of choice for managing multiple myeloma and metastatic bone disease. Normal physiological changes in the yellow and red bone marrow represent a challenge in analyses to differentiate clinically significant findings from those that are not clinically significant. This article describes the findings for normal bone marrow, variants, and invasive processes in multiple myeloma and bone metastases. Copyright © 2015 SERAM. Published by Elsevier España, S.L.U. All rights reserved.

Comparison of 18F-FDG PET/CT and PET/MRI in patients with multiple myeloma

PubMed Central

Sachpekidis, Christos; Hillengass, Jens; Goldschmidt, Hartmut; Mosebach, Jennifer; Pan, Leyun; Schlemmer, Heinz-Peter; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2015-01-01

PET/MRI represents a promising hybrid imaging modality with several potential clinical applications. Although PET/MRI seems highly attractive in the diagnostic approach of multiple myeloma (MM), its role has not yet been evaluated. The aims of this prospective study are to evaluate the feasibility of 18F-FDG PET/MRI in detection of MM lesions, and to investigate the reproducibility of bone marrow lesions detection and quantitative data of 18F-FDG uptake between the functional (PET) component of PET/CT and PET/MRI in MM patients. The study includes 30 MM patients. All patients initially underwent 18F-FDG PET/CT (60 min p.i.), followed by PET/MRI (120 min p.i.). PET/CT and PET/MRI data were assessed and compared based on qualitative (lesion detection) and quantitative (SUV) evaluation. The hybrid PET/MRI system provided good image quality in all cases without artefacts. PET/MRI identified 65 of the 69 lesions, which were detectable with PET/CT (94.2%). Quantitative PET evaluations showed the following mean values in MM lesions: SUVaverage=5.5 and SUVmax=7.9 for PET/CT; SUVaverage=3.9 and SUVmax=5.8 for PET/MRI. Both SUVaverage and SUVmax were significantly higher on PET/CT than on PET/MRI. Spearman correlation analysis demonstrated a strong correlation between both lesional SUVaverage (r=0.744) and lesional SUVmax (r=0.855) values derived from PET/CT and PET/MRI. Regarding detection of myeloma skeletal lesions, PET/MRI exhibited equivalent performance to PET/CT. In terms of tracer uptake quantitation, a significant correlation between the two techniques was demonstrated, despite the statistically significant differences in lesional SUVs between PET/CT and PET/MRI. PMID:26550538

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wendler, J. J., E-mail: johann.wendler@med.ovgu.de; Porsch, M.; Huehne, S.

Irreversible electroporation (IRE) is a novel nonthermal tissue ablation technique by high current application leading to apoptosis without affecting extracellular matrix. Previous results of renal IRE shall be supplemented by functional MRI and differentiated histological analysis of renal parenchyma in a chronic treatment setting. Three swine were treated with two to three multifocal percutaneous IRE of the right kidney. MRI was performed before, 30 min (immediate-term), 7 days (short-term), and 28 days (mid-term) after IRE. A statistical analysis of the lesion surrounded renal parenchyma intensities was made to analyze functional differences depending on renal part, side and posttreatment time. Histologicalmore » follow-up of cortex and medulla was performed after 28 days. A total of eight ablations were created. MRI showed no collateral damage of surrounded tissue. The highest visual contrast between lesions and normal parenchyma was obtained by T2-HR-SPIR-TSE-w sequence of DCE-MRI. Ablation zones showed inhomogeneous necroses with small perifocal edema in the short-term and sharp delimitable scars in the mid-term. MRI showed no significant differences between adjoined renal parenchyma around ablations and parenchyma of untreated kidney. Histological analysis demonstrated complete destruction of cortical glomeruli and tubules, while collecting ducts, renal calyxes, and pelvis of medulla were preserved. Adjoined kidney parenchyma around IRE lesions showed no qualitative differences to normal parenchyma of untreated kidney. This porcine IRE study reveals a multifocal renal ablation, while protecting surrounded renal parenchyma and collecting system over a mid-term period. That offers prevention of renal function ablating centrally located or multifocal renal masses.« less

Diagnosis of pulmonary hypertension from magnetic resonance imaging-based computational models and decision tree analysis.

PubMed

Lungu, Angela; Swift, Andrew J; Capener, David; Kiely, David; Hose, Rod; Wild, Jim M

2016-06-01

Accurately identifying patients with pulmonary hypertension (PH) using noninvasive methods is challenging, and right heart catheterization (RHC) is the gold standard. Magnetic resonance imaging (MRI) has been proposed as an alternative to echocardiography and RHC in the assessment of cardiac function and pulmonary hemodynamics in patients with suspected PH. The aim of this study was to assess whether machine learning using computational modeling techniques and image-based metrics of PH can improve the diagnostic accuracy of MRI in PH. Seventy-two patients with suspected PH attending a referral center underwent RHC and MRI within 48 hours. Fifty-seven patients were diagnosed with PH, and 15 had no PH. A number of functional and structural cardiac and cardiovascular markers derived from 2 mathematical models and also solely from MRI of the main pulmonary artery and heart were integrated into a classification algorithm to investigate the diagnostic utility of the combination of the individual markers. A physiological marker based on the quantification of wave reflection in the pulmonary artery was shown to perform best individually, but optimal diagnostic performance was found by the combination of several image-based markers. Classifier results, validated using leave-one-out cross validation, demonstrated that combining computation-derived metrics reflecting hemodynamic changes in the pulmonary vasculature with measurement of right ventricular morphology and function, in a decision support algorithm, provides a method to noninvasively diagnose PH with high accuracy (92%). The high diagnostic accuracy of these MRI-based model parameters may reduce the need for RHC in patients with suspected PH.

Prospective multicentre study of the clinical and functional outcomes following quadriceps tendon repair with suture anchors.

PubMed

Mille, F; Adam, A; Aubry, S; Leclerc, G; Ghislandi, X; Sergent, P; Garbuio, P

2016-01-01

Quadriceps tendon avulsions are typically treated by reattaching the tendon through bone tunnels, with or without tendon or hardware augmentation. The operated knee joint can be moved right away; however, tendon grafting or tension banding will be required to protect the repair, and the hardware must be removed later on. The goal of this study was to evaluate the clinical and functional outcomes when suture anchors are used to reattached torn quadriceps tendon, and also to assess tendon healing using MRI. Thirteen consecutive patients with avulsed quadriceps tendons were operated and then followed prospectively. The surgical technique consisted of tendon reattachment using at least three anchors, in addition to intratendinous weaving of the sutures. Weight bearing was allowed while using a splint. Rehabilitation was initiated immediately after surgery according to a set protocol. Eleven patients were followed for a mean of 14.7 months. Two retears occurred in patients who did not wear the splint. Eighty-two per cent of patients were satisfied or very satisfied with the outcome. The mean knee flexion was 124.5°. All patients were able to return to their pre-injury activity levels. The mean time for clinical and functional recovery was 3 months. MRI performed 6 months after the surgical repair revealed good tendon healing. This was the first prospective study performed on quadriceps avulsion patients undergoing suture anchor repair. Prior clinical case reports have shown that this method leads to predictable clinical and functional results. Our results were comparable to those in published cases. The procedure is simpler when only suture anchors are used. Tendon healing was observed on MRI in all cases. This simple, reproducible technique is free of the drawbacks associated with the typical repair augmentation.

Effect of phase-encoding direction on group analysis of resting-state functional magnetic resonance imaging.

PubMed

Mori, Yasuo; Miyata, Jun; Isobe, Masanori; Son, Shuraku; Yoshihara, Yujiro; Aso, Toshihiko; Kouchiyama, Takanori; Murai, Toshiya; Takahashi, Hidehiko

2018-05-17

Echo-planar imaging is a common technique used in functional magnetic resonance imaging (fMRI), however it suffers from image distortion and signal loss because of large susceptibility effects that are related to the phase-encoding direction of the scan. Despite this relationship, the majority of neuroimaging studies have not considered the influence of phase-encoding direction. Here, we aimed to clarify how phase-encoding direction can affect the outcome of an fMRI connectivity study of schizophrenia. Resting-state fMRI using anterior to posterior (A-P) and posterior to anterior (P-A) directions was used to examine 25 patients with schizophrenia (SC) and 37 matched healthy controls (HC). We conducted a functional connectivity analysis using independent component analysis and performed three group comparisons: A-P vs. P-A (all participants), SC vs. HC for the A-P and P-A datasets, and the interaction between phase-encoding direction and participant group. The estimated functional connectivity differed between the two phase-encoding directions in areas that were more extensive than those where signal loss has been reported. Although functional connectivity in the SC group was lower than that in the HC group for both directions, the A-P and P-A conditions did not exhibit the same specific pattern of differences. Further, we observed an interaction between participant group and the phase-encoding direction in the left temporo-parietal junction and left fusiform gyrus. Phase-encoding direction can influence the results of functional connectivity studies. Thus, appropriate selection and documentation of phase-encoding direction will be important in future resting-state fMRI studies. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Accuracy of MRI-based Magnetic Susceptibility Measurements

NASA Astrophysics Data System (ADS)

Russek, Stephen; Erdevig, Hannah; Keenan, Kathryn; Stupic, Karl

Magnetic Resonance Imaging (MRI) is increasingly used to map tissue susceptibility to identify microbleeds associated with brain injury and pathologic iron deposits associated with neurologic diseases such as Parkinson's and Alzheimer's disease. Field distortions with a resolution of a few parts per billion can be measured using MRI phase maps. The field distortion map can be inverted to obtain a quantitative susceptibility map. To determine the accuracy of MRI-based susceptibility measurements, a set of phantoms with paramagnetic salts and nano-iron gels were fabricated. The shapes and orientations of features were varied. Measured susceptibility of 1.0 mM GdCl3 solution in water as a function of temperature agreed well with the theoretical predictions, assuming Gd+3 is spin 7/2. The MRI susceptibility measurements were compared with SQUID magnetometry. The paramagnetic susceptibility sits on top of the much larger diamagnetic susceptibility of water (-9.04 x 10-6), which leads to errors in the SQUID measurements. To extract out the paramagnetic contribution using standard magnetometry, measurements must be made down to low temperature (2K). MRI-based susceptometry is shown to be as or more accurate than standard magnetometry and susceptometry techniques.

Neuroimaging in pediatric traumatic head injury: diagnostic considerations and relationships to neurobehavioral outcome.

PubMed

Bigler, E D

1999-08-01

Contemporary neuorimaging techniques in child traumatic brain injury are reviewed, with an emphasis on computerized tomography (CT) and magnetic resonance (MR) imaging. A brief overview of MR spectroscopy (MRS), functional MR imaging (fMRI), single-photon emission computed tomography (SPECT), and magnetoencephalography (MEG) is also provided because these techniques will likely constitute important neuroimaging techniques of the future. Numerous figures are provided to illustrate the multifaceted manner in which traumatic deficits can be imaged and the role of neuroimaging information as it relates to TBI outcome.

A case study of magnetic resonance imaging of cerebrovascular reactivity: a powerful imaging marker for mild traumatic brain injury.

PubMed

Chan, Suk-tak; Evans, Karleyton C; Rosen, Bruce R; Song, Tian-yue; Kwong, Kenneth K

2015-01-01

To use breath-hold functional magnetic resonance imaging (fMRI) to localize the brain regions with impaired cerebrovascular reactivity (CVR) in a female patient diagnosed with mild traumatic brain injury (mTBI). The extent of impaired CVR was evaluated 2 months after concussion. Follow-up scan was performed 1 year post-mTBI using the same breath-hold fMRI technique. Case report. fMRI blood oxygenation dependent level (BOLD) signals were measured under breath-hold challenge in a female mTBI patient 2 months after concussion followed by a second fMRI with breath-hold challenge 1 year later. CVR was expressed as the percentage change of BOLD signals per unit time of breath-hold. In comparison with CVR measurement of normal control subjects, statistical maps of CVR revealed substantial neurovascular deficits and hemispheric asymmetry within grey and white matter in the initial breath-hold fMRI scan. Follow-up breath-hold fMRI performed 1 year post-mTBI demonstrated normalization of CVR accompanied with symptomatic recovery. CVR may serve as an imaging biomarker to detect subtle deficits in both grey and white matter for individual diagnosis of mTBI. The findings encourage further investigation of hypercapnic fMRI as a diagnostic tool for mTBI.

EEG-fMRI Bayesian framework for neural activity estimation: a simulation study

NASA Astrophysics Data System (ADS)

Croce, Pierpaolo; Basti, Alessio; Marzetti, Laura; Zappasodi, Filippo; Del Gratta, Cosimo

2016-12-01

Objective. Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework. Approach. We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF). Main results. First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements. Significance. The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.

EEG-fMRI Bayesian framework for neural activity estimation: a simulation study.

PubMed

Croce, Pierpaolo; Basti, Alessio; Marzetti, Laura; Zappasodi, Filippo; Gratta, Cosimo Del

2016-12-01

Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework. We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF). First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements. The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.

Advanced magnetic resonance imaging in glioblastoma: a review.

PubMed

Shukla, Gaurav; Alexander, Gregory S; Bakas, Spyridon; Nikam, Rahul; Talekar, Kiran; Palmer, Joshua D; Shi, Wenyin

2017-08-01

Glioblastoma, the most common and most rapidly progressing primary malignant tumor of the central nervous system, continues to portend a dismal prognosis, despite improvements in diagnostic and therapeutic strategies over the last 20 years. The standard of care radiographic characterization of glioblastoma is magnetic resonance imaging (MRI), which is a widely utilized examination in the diagnosis and post-treatment management of patients with glioblastoma. Basic MRI modalities available from any clinical scanner, including native T1-weighted (T1w) and contrast-enhanced (T1CE), T2-weighted (T2w), and T2-fluid-attenuated inversion recovery (T2-FLAIR) sequences, provide critical clinical information about various processes in the tumor environment. In the last decade, advanced MRI modalities are increasingly utilized to further characterize glioblastomas more comprehensively. These include multi-parametric MRI sequences, such as dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE), higher order diffusion techniques such as diffusion tensor imaging (DTI), and MR spectroscopy (MRS). Significant efforts are ongoing to implement these advanced imaging modalities into improved clinical workflows and personalized therapy approaches. Functional MRI (fMRI) and tractography are increasingly being used to identify eloquent cortices and important tracts to minimize postsurgical neuro-deficits. A contemporary review of the application of standard and advanced MRI in clinical neuro-oncologic practice is presented here.

Automatic segmentation of left ventricle in cardiac cine MRI images based on deep learning

NASA Astrophysics Data System (ADS)

Zhou, Tian; Icke, Ilknur; Dogdas, Belma; Parimal, Sarayu; Sampath, Smita; Forbes, Joseph; Bagchi, Ansuman; Chin, Chih-Liang; Chen, Antong

2017-02-01

In developing treatment of cardiovascular diseases, short axis cine MRI has been used as a standard technique for understanding the global structural and functional characteristics of the heart, e.g. ventricle dimensions, stroke volume and ejection fraction. To conduct an accurate assessment, heart structures need to be segmented from the cine MRI images with high precision, which could be a laborious task when performed manually. Herein a fully automatic framework is proposed for the segmentation of the left ventricle from the slices of short axis cine MRI scans of porcine subjects using a deep learning approach. For training the deep learning models, which generally requires a large set of data, a public database of human cine MRI scans is used. Experiments on the 3150 cine slices of 7 porcine subjects have shown that when comparing the automatic and manual segmentations the mean slice-wise Dice coefficient is about 0.930, the point-to-curve error is 1.07 mm, and the mean slice-wise Hausdorff distance is around 3.70 mm, which demonstrates the accuracy and robustness of the proposed inter-species translational approach.

Parallel group independent component analysis for massive fMRI data sets.

PubMed

Chen, Shaojie; Huang, Lei; Qiu, Huitong; Nebel, Mary Beth; Mostofsky, Stewart H; Pekar, James J; Lindquist, Martin A; Eloyan, Ani; Caffo, Brian S

2017-01-01

Independent component analysis (ICA) is widely used in the field of functional neuroimaging to decompose data into spatio-temporal patterns of co-activation. In particular, ICA has found wide usage in the analysis of resting state fMRI (rs-fMRI) data. Recently, a number of large-scale data sets have become publicly available that consist of rs-fMRI scans from thousands of subjects. As a result, efficient ICA algorithms that scale well to the increased number of subjects are required. To address this problem, we propose a two-stage likelihood-based algorithm for performing group ICA, which we denote Parallel Group Independent Component Analysis (PGICA). By utilizing the sequential nature of the algorithm and parallel computing techniques, we are able to efficiently analyze data sets from large numbers of subjects. We illustrate the efficacy of PGICA, which has been implemented in R and is freely available through the Comprehensive R Archive Network, through simulation studies and application to rs-fMRI data from two large multi-subject data sets, consisting of 301 and 779 subjects respectively.

Multiparametric imaging of brain hemodynamics and function using gas-inhalation MRI.

PubMed

Liu, Peiying; Welch, Babu G; Li, Yang; Gu, Hong; King, Darlene; Yang, Yihong; Pinho, Marco; Lu, Hanzhang

2017-02-01

Diagnosis and treatment monitoring of cerebrovascular diseases routinely require hemodynamic imaging of the brain. Current methods either only provide part of the desired information or require the injection of multiple exogenous agents. In this study, we developed a multiparametric imaging scheme for the imaging of brain hemodynamics and function using gas-inhalation MRI. The proposed technique uses a single MRI scan to provide simultaneous measurements of baseline venous cerebral blood volume (vCBV), cerebrovascular reactivity (CVR), bolus arrival time (BAT), and resting-state functional connectivity (fcMRI). This was achieved with a novel, concomitant O 2 and CO 2 gas inhalation paradigm, rapid MRI image acquisition with a 9.3min BOLD sequence, and an advanced algorithm to extract multiple hemodynamic information from the same dataset. In healthy subjects, CVR and vCBV values were 0.23±0.03%/mmHg and 0.0056±0.0006%/mmHg, respectively, with a strong correlation (r=0.96 for CVR and r=0.91 for vCBV) with more conventional, separate acquisitions that take twice the scan time. In patients with Moyamoya syndrome, CVR in the stenosis-affected flow territories (typically anterior-cerebral-artery, ACA, and middle-cerebral-artery, MCA, territories) was significantly lower than that in posterior-cerebral-artery (PCA), which typically has minimal stenosis, flow territories (0.12±0.06%/mmHg vs. 0.21±0.05%/mmHg, p<0.001). BAT of the gas bolus was significantly longer (p=0.008) in ACA/MCA territories, compared to PCA, and the maps were consistent with the conventional contrast-enhanced CT perfusion method. FcMRI networks were robustly identified from the gas-inhalation MRI data after factoring out the influence of CO 2 and O 2 on the signal time course. The spatial correspondence between the gas-data-derived fcMRI maps and those using a separate, conventional fcMRI scan was excellent, showing a spatial correlation of 0.58±0.17 and 0.64±0.20 for default mode network and primary visual network, respectively. These findings suggest that advanced gas-inhalation MRI provides reliable measurements of multiple hemodynamic parameters within a clinically acceptable imaging time and is suitable for patient examinations. Copyright © 2016 Elsevier Inc. All rights reserved.

Multiparametric imaging of brain hemodynamics and function using gas-inhalation MRI

PubMed Central

Liu, Peiying; Welch, Babu G.; Li, Yang; Gu, Hong; King, Darlene; Yang, Yihong; Pinho, Marco; Lu, Hanzhang

2016-01-01

Diagnosis and treatment monitoring of cerebrovascular diseases routinely require hemodynamic imaging of the brain. Current methods either only provide part of the desired information or require the injection of multiple exogenous agents. In this study, we developed a multiparametric imaging scheme for the imaging of brain hemodynamics and function using gas-inhalation MRI. The proposed technique uses a single MRI scan to provide simultaneous measurements of baseline venous cerebral blood volume (vCBV), cerebrovascular reactivity (CVR), bolus arrival time (BAT), and resting-state functional connectivity (fcMRI). This was achieved with a novel, concomitant O2 and CO2 gas inhalation paradigm, rapid MRI image acquisition with a 9.3 min BOLD sequence, and an advanced algorithm to extract multiple hemodynamic information from the same dataset. In healthy subjects, CVR and vCBV values were 0.23±0.03 %/mmHg and 0.0056±0.0006 %/mmHg, respectively, with a strong correlation (r=0.96 for CVR and r=0.91 for vCBV) with more conventional, separate acquisitions that take twice the scan time. In patients with Moyamoya syndrome, CVR in the stenosis-affected flow territories (typically anterior-cerebral-artery, ACA, and middle-cerebral-artery, MCA, territories) was significantly lower than that in posterior-cerebral-artery (PCA), which typically has minimal stenosis, flow territories (0.12±0.06 %/mmHg vs. 0.21±0.05 %/mmHg, p<0.001). BAT of the gas bolus was significantly longer (p=0.008) in ACA/MCA territories, compared to PCA, and the maps were consistent with the conventional contrast-enhanced CT perfusion method. FcMRI networks were robustly identified from the gas-inhalation MRI data after factoring out the influence of CO2 and O2 on the signal time course. The spatial correspondence between the gas-data-derived fcMRI maps and those using a separate, conventional fcMRI scan was excellent, showing a spatial correlation of 0.58±0.17 and 0.64±0.20 for default mode network and primary visual network, respectively. These findings suggest that advanced gas-inhalation MRI provides reliable measurements of multiple hemodynamic parameters within a clinically acceptable imaging time and is suitable for patient examinations. PMID:27693197

ALE Meta-Analysis of Schizophrenics Performing the N-Back Task

NASA Astrophysics Data System (ADS)

Harrell, Zachary

2010-10-01

MRI/fMRI has already proven itself as a valuable tool in the diagnosis and treatment of many illnesses of the brain, including cognitive problems. By exploiting the differences in magnetic susceptibility between oxygenated and deoxygenated hemoglobin, fMRI can measure blood flow in various regions of interest within the brain. This can determine the level of brain activity in relation to motor or cognitive functions and provide a metric for tissue damage or illness symptoms. Structural imaging techniques have shown lesions or deficiencies in tissue volumes in schizophrenics corresponding to areas primarily in the frontal and temporal lobes. These areas are currently known to be involved in working memory and attention, which many schizophrenics have trouble with. The ALE (Activation Likelihood Estimation) Meta-Analysis is able to statistically determine the significance of brain area activations based on the post-hoc combination of multiple studies. This process is useful for giving a general model of brain function in relation to a particular task designed to engage the affected areas (such as working memory for the n-back task). The advantages of the ALE Meta-Analysis include elimination of single subject anomalies, elimination of false/extremely weak activations, and verification of function/location hypotheses.

Physiologic noise regression, motion regression, and TOAST dynamic field correction in complex-valued fMRI time series.

PubMed

Hahn, Andrew D; Rowe, Daniel B

2012-02-01

As more evidence is presented suggesting that the phase, as well as the magnitude, of functional MRI (fMRI) time series may contain important information and that there are theoretical drawbacks to modeling functional response in the magnitude alone, removing noise in the phase is becoming more important. Previous studies have shown that retrospective correction of noise from physiologic sources can remove significant phase variance and that dynamic main magnetic field correction and regression of estimated motion parameters also remove significant phase fluctuations. In this work, we investigate the performance of physiologic noise regression in a framework along with correction for dynamic main field fluctuations and motion regression. Our findings suggest that including physiologic regressors provides some benefit in terms of reduction in phase noise power, but it is small compared to the benefit of dynamic field corrections and use of estimated motion parameters as nuisance regressors. Additionally, we show that the use of all three techniques reduces phase variance substantially, removes undesirable spatial phase correlations and improves detection of the functional response in magnitude and phase. Copyright © 2011 Elsevier Inc. All rights reserved.

Control of nucleus accumbens activity with neurofeedback

PubMed Central

Greer, Stephanie M.; Trujillo, Andrew J.; Glover, Gary H.; Knutson, Brian

2014-01-01

The nucleus accumbens (NAcc) plays critical roles in healthy motivation and learning, as well as in psychiatric disorders (including schizophrenia and attention deficit hyperactivity disorder). Thus, techniques that confer control of NAcc activity might inspire new therapeutic interventions. By providing second-to-second temporal resolution of activity in small subcortical regions, functional magnetic resonance imaging (fMRI) can resolve online changes in NAcc activity, which can then be presented as “neurofeedback.” In an fMRI-based neurofeedback experiment designed to elicit NAcc activity, we found that subjects could increase their own NAcc activity, and that display of neurofeedback significantly enhanced their ability to do so. Subjects were not as capable of decreasing their NAcc activity, however, and enhanced control did not persist after subsequent removal of neurofeedback. Further analyses suggested that individuals who recruited positive arousal affect were better able to increase NAcc activity in response to neurofeedback, and that NAcc neurofeedback also elicited functionally correlated activity in the medial prefrontal cortex. Together, these findings suggest that humans can modulate their own NAcc activity and that fMRI-based neurofeedback may augment their efforts. The observed association between positive arousal and effective NAcc control further supports an anticipatory affect account of NAcc function. PMID:24705203

Unmasking Language Lateralization in Human Brain Intrinsic Activity

PubMed Central

McAvoy, Mark; Mitra, Anish; Coalson, Rebecca S.; d'Avossa, Giovanni; Keidel, James L.; Petersen, Steven E.; Raichle, Marcus E.

2016-01-01

Lateralization of function is a fundamental feature of the human brain as exemplified by the left hemisphere dominance of language. Despite the prominence of lateralization in the lesion, split-brain and task-based fMRI literature, surprisingly little asymmetry has been revealed in the increasingly popular functional imaging studies of spontaneous fluctuations in the fMRI BOLD signal (so-called resting-state fMRI). Here, we show the global signal, an often discarded component of the BOLD signal in resting-state studies, reveals a leftward asymmetry that maps onto regions preferential for semantic processing in left frontal and temporal cortex and the right cerebellum and a rightward asymmetry that maps onto putative attention-related regions in right frontal, temporoparietal, and parietal cortex. Hemispheric asymmetries in the global signal resulted from amplitude modulation of the spontaneous fluctuations. To confirm these findings obtained from normal, healthy, right-handed subjects in the resting-state, we had them perform 2 semantic processing tasks: synonym and numerical magnitude judgment and sentence comprehension. In addition to establishing a new technique for studying lateralization through functional imaging of the resting-state, our findings shed new light on the physiology of the global brain signal. PMID:25636911

Continuous functional magnetic resonance imaging reveals dynamic nonlinearities of "dose-response" curves for finger opposition.

PubMed

Berns, G S; Song, A W; Mao, H

1999-07-15

Linear experimental designs have dominated the field of functional neuroimaging, but although successful at mapping regions of relative brain activation, the technique assumes that both cognition and brain activation are linear processes. To test these assumptions, we performed a continuous functional magnetic resonance imaging (MRI) experiment of finger opposition. Subjects performed a visually paced bimanual finger-tapping task. The frequency of finger tapping was continuously varied between 1 and 5 Hz, without any rest blocks. After continuous acquisition of fMRI images, the task-related brain regions were identified with independent components analysis (ICA). When the time courses of the task-related components were plotted against tapping frequency, nonlinear "dose- response" curves were obtained for most subjects. Nonlinearities appeared in both the static and dynamic sense, with hysteresis being prominent in several subjects. The ICA decomposition also demonstrated the spatial dynamics with different components active at different times. These results suggest that the brain response to tapping frequency does not scale linearly, and that it is history-dependent even after accounting for the hemodynamic response function. This implies that finger tapping, as measured with fMRI, is a nonstationary process. When analyzed with a conventional general linear model, a strong correlation to tapping frequency was identified, but the spatiotemporal dynamics were not apparent.

25 years of neuroimaging in amyotrophic lateral sclerosis.

PubMed

Foerster, Bradley R; Welsh, Robert C; Feldman, Eva L

2013-09-01

Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease for which a precise cause has not yet been identified. Standard CT or MRI evaluation does not demonstrate gross structural nervous system changes in ALS, so conventional neuroimaging techniques have provided little insight into the pathophysiology of this disease. Advanced neuroimaging techniques--such as structural MRI, diffusion tensor imaging and proton magnetic resonance spectroscopy--allow evaluation of alterations of the nervous system in ALS. These alterations include focal loss of grey and white matter and reductions in white matter tract integrity, as well as changes in neural networks and in the chemistry, metabolism and receptor distribution in the brain. Given their potential for investigation of both brain structure and function, advanced neuroimaging methods offer important opportunities to improve diagnosis, guide prognosis, and direct future treatment strategies in ALS. In this article, we review the contributions made by various advanced neuroimaging techniques to our understanding of the impact of ALS on different brain regions, and the potential role of such measures in biomarker development.

Functional quantitative susceptibility mapping (fQSM).

PubMed

Balla, Dávid Z; Sanchez-Panchuelo, Rosa M; Wharton, Samuel J; Hagberg, Gisela E; Scheffler, Klaus; Francis, Susan T; Bowtell, Richard

2014-10-15

Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) is a powerful technique, typically based on the statistical analysis of the magnitude component of the complex time-series. Here, we additionally interrogated the phase data of the fMRI time-series and used quantitative susceptibility mapping (QSM) in order to investigate the potential of functional QSM (fQSM) relative to standard magnitude BOLD fMRI. High spatial resolution data (1mm isotropic) were acquired every 3 seconds using zoomed multi-slice gradient-echo EPI collected at 7 T in single orientation (SO) and multiple orientation (MO) experiments, the latter involving 4 repetitions with the subject's head rotated relative to B0. Statistical parametric maps (SPM) were reconstructed for magnitude, phase and QSM time-series and each was subjected to detailed analysis. Several fQSM pipelines were evaluated and compared based on the relative number of voxels that were coincidentally found to be significant in QSM and magnitude SPMs (common voxels). We found that sensitivity and spatial reliability of fQSM relative to the magnitude data depended strongly on the arbitrary significance threshold defining "activated" voxels in SPMs, and on the efficiency of spatio-temporal filtering of the phase time-series. Sensitivity and spatial reliability depended slightly on whether MO or SO fQSM was performed and on the QSM calculation approach used for SO data. Our results present the potential of fQSM as a quantitative method of mapping BOLD changes. We also critically discuss the technical challenges and issues linked to this intriguing new technique. Copyright © 2014 Elsevier Inc. All rights reserved.

MRI in local staging of rectal cancer: an update

PubMed Central

Tapan, Ümit; Özbayrak, Mustafa; Tatlı, Servet

2014-01-01

Preoperative imaging for staging of rectal cancer has become an important aspect of current approach to rectal cancer management, because it helps to select suitable patients for neoadjuvant chemoradiotherapy and determine the appropriate surgical technique. Imaging modalities such as endoscopic ultrasonography, computed tomography, and magnetic resonance imaging (MRI) play an important role in assessing the depth of tumor penetration, lymph node involvement, mesorectal fascia and anal sphincter invasion, and presence of distant metastatic diseases. Currently, there is no consensus on a preferred imaging technique for preoperative staging of rectal cancer. However, high-resolution phased-array MRI is recommended as a standard imaging modality for preoperative local staging of rectal cancer, with excellent soft tissue contrast, multiplanar capability, and absence of ionizing radiation. This review will mainly focus on the role of MRI in preoperative local staging of rectal cancer and discuss recent advancements in MRI technique such as diffusion-weighted imaging and dynamic contrast-enhanced MRI. PMID:25010367

Current whole-body MRI applications in the neurofibromatoses: NF1, NF2, and schwannomatosis.

PubMed

Ahlawat, Shivani; Fayad, Laura M; Khan, Muhammad Shayan; Bredella, Miriam A; Harris, Gordon J; Evans, D Gareth; Farschtschi, Said; Jacobs, Michael A; Chhabra, Avneesh; Salamon, Johannes M; Wenzel, Ralph; Mautner, Victor F; Dombi, Eva; Cai, Wenli; Plotkin, Scott R; Blakeley, Jaishri O

2016-08-16

The Response Evaluation in Neurofibromatosis and Schwannomatosis (REiNS) International Collaboration Whole-Body MRI (WB-MRI) Working Group reviewed the existing literature on WB-MRI, an emerging technology for assessing disease in patients with neurofibromatosis type 1 (NF1), neurofibromatosis type 2 (NF2), and schwannomatosis (SWN), to recommend optimal image acquisition and analysis methods to enable WB-MRI as an endpoint in NF clinical trials. A systematic process was used to review all published data about WB-MRI in NF syndromes to assess diagnostic accuracy, feasibility and reproducibility, and data about specific techniques for assessment of tumor burden, characterization of neoplasms, and response to therapy. WB-MRI at 1.5T or 3.0T is feasible for image acquisition. Short tau inversion recovery (STIR) sequence is used in all investigations to date, suggesting consensus about the utility of this sequence for detection of WB tumor burden in people with NF. There are insufficient data to support a consensus statement about the optimal imaging planes (axial vs coronal) or 2D vs 3D approaches. Functional imaging, although used in some NF studies, has not been systematically applied or evaluated. There are no comparative studies between regional vs WB-MRI or evaluations of WB-MRI reproducibility. WB-MRI is feasible for identifying tumors using both 1.5T and 3.0T systems. The STIR sequence is a core sequence. Additional investigation is needed to define the optimal approach for volumetric analysis, the reproducibility of WB-MRI in NF, and the diagnostic performance of WB-MRI vs regional MRI. © 2016 American Academy of Neurology.

High-resolution MRI in detecting subareolar breast abscess.

PubMed

Fu, Peifen; Kurihara, Yasuyuki; Kanemaki, Yoshihide; Okamoto, Kyoko; Nakajima, Yasuo; Fukuda, Mamoru; Maeda, Ichiro

2007-06-01

Because subareolar breast abscess has a high recurrence rate, a more effective imaging technique is needed to comprehensively visualize the lesions and guide surgery. We performed a high-resolution MRI technique using a microscopy coil to reveal the characteristics and extent of subareolar breast abscess. High-resolution MRI has potential diagnostic value in subareolar breast abscess. This technique can be used to guide surgery with the aim of reducing the recurrence rate.

Functional magnetic resonance imaging of internet addiction in young adults.

PubMed

Sepede, Gianna; Tavino, Margherita; Santacroce, Rita; Fiori, Federica; Salerno, Rosa Maria; Di Giannantonio, Massimo

2016-02-28

To report the results of functional magnetic resonance imaging (fMRI) studies pertaining internet addiction disorder (IAD) in young adults. We conducted a systematic review on PubMed, focusing our attention on fMRI studies involving adult IAD patients, free from any comorbid psychiatric condition. The following search words were used, both alone and in combination: fMRI, internet addiction, internet dependence, functional neuroimaging. The search was conducted on April 20(th), 2015 and yielded 58 records. Inclusion criteria were the following: Articles written in English, patients' age ≥ 18 years, patients affected by IAD, studies providing fMRI results during resting state or cognitive/emotional paradigms. Structural MRI studies, functional imaging techniques other than fMRI, studies involving adolescents, patients with comorbid psychiatric, neurological or medical conditions were excluded. By reading titles and abstracts, we excluded 30 records. By reading the full texts of the 28 remaining articles, we identified 18 papers meeting our inclusion criteria and therefore included in the qualitative synthesis. We found 18 studies fulfilling our inclusion criteria, 17 of them conducted in Asia, and including a total number of 666 tested subjects. The included studies reported data acquired during resting state or different paradigms, such as cue-reactivity, guessing or cognitive control tasks. The enrolled patients were usually males (95.4%) and very young (21-25 years). The most represented IAD subtype, reported in more than 85% of patients, was the internet gaming disorder, or videogame addiction. In the resting state studies, the more relevant abnormalities were localized in the superior temporal gyrus, limbic, medial frontal and parietal regions. When analyzing the task related fmri studies, we found that less than half of the papers reported behavioral differences between patients and normal controls, but all of them found significant differences in cortical and subcortical brain regions involved in cognitive control and reward processing: Orbitofrontal cortex, insula, anterior and posterior cingulate cortex, temporal and parietal regions, brain stem and caudate nucleus. IAD may seriously affect young adults' brain functions. It needs to be studied more in depth to provide a clear diagnosis and an adequate treatment.

Awake Craniotomy with Noninvasive Brain Mapping by 3-Tesla Functional Magnetic Resonance Imaging for Excision of Low-grade Glioma: A Case of a Young Patient from Pakistan.

PubMed

Aleem Bhatti, Atta Ul; Jakhrani, Nasir Khan; Parekh, Maria Adnan

2018-01-01

The past few years have seen increasing support for gross total resection in the management of low-grade gliomas (LGGs), with a greater extent of resection correlated with better overall survival, progression-free survival, and time to malignant transformation. There is consistent evidence in literature supporting extent of safe resection as a good prognostic indicator as well as positively affecting seizure control, symptomatic relief in pressure symptoms, and longer progression-free and total survival. The operative goal in most LGG cases is to maximize the extent of resection for these benefits while avoiding postoperative neurologic deficits. Several advanced invasive and noninvasive surgical techniques such as intraoperative magnetic resonance imaging (MRI), fluorescence-guided surgery, intraoperative functional pathway mapping, and neuronavigation have been developed in an attempt to better achieve maximal safe resection. We present a case of LGG in a young patient with a 5-year history of refractory seizures and gradual onset walking difficulty. Serial MRI brain scans revealed a progressive increase in right frontal tumor size with substantial edema and parafalcine herniation. Noninvasive brain mapping by functional MRI (fMRI) and sleep-awake-sleep type of anesthesia with endotracheal tube insertion was utilized during an awake craniotomy. Histopathology confirmed a Grade II oligodendroglioma, and genetic analysis revealed no codeletion at 1p/19q. Neurological improvement was remarkable in terms of immediate motor improvement, and the patient remained completely seizure free on a single antiepileptic drug. There is no radiologic or clinical evidence of recurrence 6 months postoperatively. This is the first published report of an awake craniotomy for LGG in Pakistan. The contemporary concept of supratotal resection in LGGs advocates generous functional resection even beyond MRI findings rather than mere excision of oncological boundaries. This relatively aggressive approach is only possible with an awake craniotomy, which ensures preservation of functional status and thus less postoperative morbidity and better outcomes. Noninvasive mapping for intracranial space-occupying lesions, including fMRI and blood-oxygen-level dependent (BOLD) imaging modality, is an essential tool in a resource-limited setting such as Pakistan.

Functional magnetic resonance imaging of internet addiction in young adults

PubMed Central

Sepede, Gianna; Tavino, Margherita; Santacroce, Rita; Fiori, Federica; Salerno, Rosa Maria; Di Giannantonio, Massimo

2016-01-01

AIM: To report the results of functional magnetic resonance imaging (fMRI) studies pertaining internet addiction disorder (IAD) in young adults. METHODS: We conducted a systematic review on PubMed, focusing our attention on fMRI studies involving adult IAD patients, free from any comorbid psychiatric condition. The following search words were used, both alone and in combination: fMRI, internet addiction, internet dependence, functional neuroimaging. The search was conducted on April 20th, 2015 and yielded 58 records. Inclusion criteria were the following: Articles written in English, patients’ age ≥ 18 years, patients affected by IAD, studies providing fMRI results during resting state or cognitive/emotional paradigms. Structural MRI studies, functional imaging techniques other than fMRI, studies involving adolescents, patients with comorbid psychiatric, neurological or medical conditions were excluded. By reading titles and abstracts, we excluded 30 records. By reading the full texts of the 28 remaining articles, we identified 18 papers meeting our inclusion criteria and therefore included in the qualitative synthesis. RESULTS: We found 18 studies fulfilling our inclusion criteria, 17 of them conducted in Asia, and including a total number of 666 tested subjects. The included studies reported data acquired during resting state or different paradigms, such as cue-reactivity, guessing or cognitive control tasks. The enrolled patients were usually males (95.4%) and very young (21-25 years). The most represented IAD subtype, reported in more than 85% of patients, was the internet gaming disorder, or videogame addiction. In the resting state studies, the more relevant abnormalities were localized in the superior temporal gyrus, limbic, medial frontal and parietal regions. When analyzing the task related fmri studies, we found that less than half of the papers reported behavioral differences between patients and normal controls, but all of them found significant differences in cortical and subcortical brain regions involved in cognitive control and reward processing: Orbitofrontal cortex, insula, anterior and posterior cingulate cortex, temporal and parietal regions, brain stem and caudate nucleus. CONCLUSION: IAD may seriously affect young adults’ brain functions. It needs to be studied more in depth to provide a clear diagnosis and an adequate treatment. PMID:26981230

Characterization of task-free and task-performance brain states via functional connectome patterns.

PubMed

Zhang, Xin; Guo, Lei; Li, Xiang; Zhang, Tuo; Zhu, Dajiang; Li, Kaiming; Chen, Hanbo; Lv, Jinglei; Jin, Changfeng; Zhao, Qun; Li, Lingjiang; Liu, Tianming

2013-12-01

Both resting state fMRI (R-fMRI) and task-based fMRI (T-fMRI) have been widely used to study the functional activities of the human brain during task-free and task-performance periods, respectively. However, due to the difficulty in strictly controlling the participating subject's mental status and their cognitive behaviors during R-fMRI/T-fMRI scans, it has been challenging to ascertain whether or not an R-fMRI/T-fMRI scan truly reflects the participant's functional brain states during task-free/task-performance periods. This paper presents a novel computational approach to characterizing and differentiating the brain's functional status into task-free or task-performance states, by which the functional brain activities can be effectively understood and differentiated. Briefly, the brain's functional state is represented by a whole-brain quasi-stable connectome pattern (WQCP) of R-fMRI or T-fMRI data based on 358 consistent cortical landmarks across individuals, and then an effective sparse representation method was applied to learn the atomic connectome patterns (ACPs) of both task-free and task-performance states. Experimental results demonstrated that the learned ACPs for R-fMRI and T-fMRI datasets are substantially different, as expected. A certain portion of ACPs from R-fMRI and T-fMRI data were overlapped, suggesting some subjects with overlapping ACPs were not in the expected task-free/task-performance brain states. Besides, potential outliers in the T-fMRI dataset were further investigated via functional activation detections in different groups, and our results revealed unexpected task-performances of some subjects. This work offers novel insights into the functional architectures of the brain. Copyright © 2013 Elsevier B.V. All rights reserved.

Characterization of Task-free and Task-performance Brain States via Functional Connectome Patterns

PubMed Central

Zhang, Xin; Guo, Lei; Li, Xiang; Zhang, Tuo; Zhu, Dajiang; Li, Kaiming; Chen, Hanbo; Lv, Jinglei; Jin, Changfeng; Zhao, Qun; Li, Lingjiang; Liu, Tianming

2014-01-01

Both resting state fMRI (R-fMRI) and task-based fMRI (T-fMRI) have been widely used to study the functional activities of the human brain during task-free and task-performance periods, respectively. However, due to the difficulty in strictly controlling the participating subject's mental status and their cognitive behaviors during R-fMRI/T-fMRI scans, it has been challenging to ascertain whether or not an R-fMRI/T-fMRI scan truly reflects the participant's functional brain states during task-free/task-performance periods. This paper presents a novel computational approach to characterizing and differentiating the brain's functional status into task-free or task-performance states, by which the functional brain activities can be effectively understood and differentiated. Briefly, the brain's functional state is represented by a whole-brain quasi-stable connectome pattern (WQCP) of R-fMRI or T-fMRI data based on 358 consistent cortical landmarks across individuals, and then an effective sparse representation method was applied to learn the atomic connectome patterns (ACP) of both task-free and task-performance states. Experimental results demonstrated that the learned ACPs for R-fMRI and T-fMRI datasets are substantially different, as expected. A certain portion of ACPs from R-fMRI and T-fMRI data were overlapped, suggesting some subjects with overlapping ACPs were not in the expected task-free/task-performance brain states. Besides, potential outliers in the T-fMRI dataset were further investigated via functional activation detections in different groups, and our results revealed unexpected task-performances of some subjects. This work offers novel insights into the functional architectures of the brain. PMID:23938590

Physiological noise in murine solid tumours using T2*-weighted gradient-echo imaging: a marker of tumour acute hypoxia?

PubMed

Baudelet, Christine; Ansiaux, Réginald; Jordan, Bénédicte F; Havaux, Xavier; Macq, Benoit; Gallez, Bernard

2004-08-07

T2*-weighted gradient-echo magnetic resonance imaging (T2*-weighted GRE MRI) was used to investigate spontaneous fluctuations in tumour vasculature non-invasively. FSa fibrosarcomas, implanted intramuscularly (i.m.) in the legs of mice, were imaged at 4.7 T, over a 30 min or 1 h sampling period. On a voxel-by-voxel basis, time courses of signal intensity were analysed using a power spectrum density (PSD) analysis to isolate voxels for which signal changes did not originate from Gaussian white noise or linear drift. Under baseline conditions, the tumours exhibited spontaneous signal fluctuations showing spatial and temporal heterogeneity over the tumour. Statistically significant fluctuations occurred at frequencies ranging from 1 cycle/3 min to 1 cycle/h. The fluctuations were independent of the scanner instabilities. Two categories of signal fluctuations were reported: (i) true fluctuations (TFV), i.e., sequential signal increase and decrease, and (ii) profound drop in signal intensity with no apparent signal recovery (SDV). No temporal correlation between tumour and contralateral muscle fluctuations was observed. Furthermore, treatments aimed at decreasing perfusion-limited hypoxia, such as carbogen combined with nicotinamide and flunarizine, decreased the incidence of tumour T2*-weighted GRE fluctuations. We also tracked dynamic changes in T2* using multiple GRE imaging. Fluctuations of T2* were observed; however, fluctuation maps using PSD analysis could not be generated reliably. An echo-time dependency of the signal fluctuations was observed, which is typical to physiological noise. Finally, at the end of T2*-weighted GRE MRI acquisition, a dynamic contrast-enhanced MRI was performed to characterize the microenvironment in which tumour signal fluctuations occurred in terms of vessel functionality, vascularity and microvascular permeability. Our data showed that TFV were predominantly located in regions with functional vessels, whereas SDV occurred in regions with no contrast enhancement as the result of vessel functional impairment. Furthermore, transient fluctuations appeared to occur preferentially in neoangiogenic hyperpermeable vessels. The present study suggests that spontaneous T2*-weighted GRE fluctuations are very likely to be related to the spontaneous fluctuations in blood flow and oxygenation associated with the pathophysiology of acute hypoxia in tumours. The disadvantage of the T2*-weighted GRE MRI technique is the complexity of signal interpretation with regard to pO2 changes. Compared to established techniques such as intravital microscopy or histological assessments, the major advantage of the MRI technique lies in its capacity to provide simultaneously both temporal and detailed spatial information on spontaneous fluctuations throughout the tumour.

MRI versus breast-specific gamma imaging (BSGI) in newly diagnosed ductal cell carcinoma-in-situ: a prospective head-to-head trial.

PubMed

Keto, Jessica L; Kirstein, Laurie; Sanchez, Diana P; Fulop, Tamara; McPartland, Laura; Cohen, Ilona; Boolbol, Susan K

2012-01-01

Mammography remains the standard imaging technique for the diagnosis of ductal carcinoma-in-situ (DCIS). Functional breast imaging, including breast magnetic resonance imaging (MRI), has known limitations in evaluating DCIS. To date, there are limited data on the utility of breast-specific gamma imaging (BSGI) in DCIS. We sought to prospectively compare the sensitivity of BSGI to MRI in newly diagnosed DCIS patients. Patients with newly diagnosed DCIS from June 1, 2009, through May 31, 2010, underwent a protocol with both breast MRI and BSGI. Each imaging study was read by a separate dedicated breast radiologist. Patients were excluded if excisional biopsy was performed for diagnosis, if their MRI was performed at an outside facility, or if final pathology revealed invasive carcinoma. There were 18 patients enrolled onto the study that had both MRI and BSGI for newly diagnosed DCIS. The sensitivity for MRI was 94% and for BSGI was 89% (P > 0.5, NS). There was one index tumor not seen on either MRI or BSGI, and one index tumor seen on MRI but not visualized on BSGI. Although BSGI has previously been shown to be as sensitive as MRI for detecting known invasive breast carcinoma, this study shows that BSGI is equally as sensitive as MRI at detecting newly diagnosed DCIS. As a result of the limited number of patients enrolled onto the study, larger prospective studies need to be performed to determine the true sensitivity and specificity of BSGI.

Low-Cost High-Performance MRI

NASA Astrophysics Data System (ADS)

Sarracanie, Mathieu; Lapierre, Cristen D.; Salameh, Najat; Waddington, David E. J.; Witzel, Thomas; Rosen, Matthew S.

2015-10-01

Magnetic Resonance Imaging (MRI) is unparalleled in its ability to visualize anatomical structure and function non-invasively with high spatial and temporal resolution. Yet to overcome the low sensitivity inherent in inductive detection of weakly polarized nuclear spins, the vast majority of clinical MRI scanners employ superconducting magnets producing very high magnetic fields. Commonly found at 1.5-3 tesla (T), these powerful magnets are massive and have very strict infrastructure demands that preclude operation in many environments. MRI scanners are costly to purchase, site, and maintain, with the purchase price approaching $1 M per tesla (T) of magnetic field. We present here a remarkably simple, non-cryogenic approach to high-performance human MRI at ultra-low magnetic field, whereby modern under-sampling strategies are combined with fully-refocused dynamic spin control using steady-state free precession techniques. At 6.5 mT (more than 450 times lower than clinical MRI scanners) we demonstrate (2.5 × 3.5 × 8.5) mm3 imaging resolution in the living human brain using a simple, open-geometry electromagnet, with 3D image acquisition over the entire brain in 6 minutes. We contend that these practical ultra-low magnetic field implementations of MRI (<10 mT) will complement traditional MRI, providing clinically relevant images and setting new standards for affordable (<$50,000) and robust portable devices.

Ventilation distribution in rats: Part 2 – A comparison of electrical impedance tomography and hyperpolarised helium magnetic resonance imaging

PubMed Central

2012-01-01

Background Hyperpolarised helium MRI (He3 MRI) is a new technique that enables imaging of the air distribution within the lungs. This allows accurate determination of the ventilation distribution in vivo. The technique has the disadvantages of requiring an expensive helium isotope, complex apparatus and moving the patient to a compatible MRI scanner. Electrical impedance tomography (EIT) a non-invasive bedside technique that allows constant monitoring of lung impedance, which is dependent on changes in air space capacity in the lung. We have used He3MRI measurements of ventilation distribution as the gold standard for assessment of EIT. Methods Seven rats were ventilated in supine, prone, left and right lateral position with 70% helium/30% oxygen for EIT measurements and pure helium for He3 MRI. The same ventilator and settings were used for both measurements. Image dimensions, geometric centre and global in homogeneity index were calculated. Results EIT images were smaller and of lower resolution and contained less anatomical detail than those from He3 MRI. However, both methods could measure positional induced changes in lung ventilation, as assessed by the geometric centre. The global in homogeneity index were comparable between the techniques. Conclusion EIT is a suitable technique for monitoring ventilation distribution and inhomgeneity as assessed by comparison with He3 MRI. PMID:22966835

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Pei-Hsin; Chung, Hsiao-Wen; Tsai, Ping-Huei

Purpose: One of the technical advantages of functional magnetic resonance imaging (fMRI) is its precise localization of changes from neuronal activities. While current practice of fMRI acquisition at voxel size around 3 × 3 × 3 mm{sup 3} achieves satisfactory results in studies of basic brain functions, higher spatial resolution is required in order to resolve finer cortical structures. This study investigated spatial resolution effects on brain fMRI experiments using balanced steady-state free precession (bSSFP) imaging with 0.37 mm{sup 3} voxel volume at 3.0 T. Methods: In fMRI experiments, full and unilateral visual field 5 Hz flashing checkerboard stimulations weremore » given to healthy subjects. The bSSFP imaging experiments were performed at three different frequency offsets to widen the coverage, with functional activations in the primary visual cortex analyzed using the general linear model. Variations of the spatial resolution were achieved by removing outerk-space data components. Results: Results show that a reduction in voxel volume from 3.44 × 3.44 × 2 mm{sup 3} to 0.43 × 0.43 × 2 mm{sup 3} has resulted in an increase of the functional activation signals from (7.7 ± 1.7)% to (20.9 ± 2.0)% at 3.0 T, despite of the threefold SNR decreases in the original images, leading to nearly invariant functional contrast-to-noise ratios (fCNR) even at high spatial resolution. Activation signals aligning nicely with gray matter sulci at high spatial resolution would, on the other hand, have possibly been mistaken as noise at low spatial resolution. Conclusions: It is concluded that the bSSFP sequence is a plausible technique for fMRI investigations at submillimeter voxel widths without compromising fCNR. The reduction of partial volume averaging with nonactivated brain tissues to retain fCNR is uniquely suitable for high spatial resolution applications such as the resolving of columnar organization in the brain.« less

Hyperpolarized Xenon-129 Gas-Exchange Imaging of Lung Microstructure: First Case Studies in Subjects with Obstructive Lung Disease

PubMed Central

Dregely, Isabel; Mugler, John P.; Ruset, Iulian C.; Altes, Talissa A.; Mata, Jaime F.; Miller, G. Wilson; Ketel, Jeffrey; Ketel, Steve; Distelbrink, Jan; Hersman, F.W.; Ruppert, Kai

2011-01-01

Purpose To develop and test a method to non-invasively assess the functional lung microstructure. Materials and Methods The Multiple exchange time Xenon polarization Transfer Contrast technique (MXTC) encodes xenon gas-exchange contrast at multiple delay times permitting two lung-function parameters to be derived: 1) MXTC-F, the long exchange-time depolarization value, which is proportional to the tissue to alveolar-volume ratio and 2) MXTC-S, the square root of the xenon exchange-time constant, which characterizes thickness and composition of alveolar septa. Three healthy volunteers, one asthmatic and two COPD (GOLD stage I and II) subjects were imaged with MXTC MRI. In a subset of subjects, hyperpolarized xenon-129 ADC MRI and CT imaging were also performed. Results The MXTC-S parameter was found to be elevated in subjects with lung disease (p-value = 0.018). In the MXTC-F parameter map it was feasible to identify regional loss of functional tissue in a COPD patient. Further, the MXTC-F map showed excellent regional correlation with CT and ADC (ρ ≥ 0.90) in one COPD subject. Conclusion The functional tissue-density parameter MXTC-F showed regional agreement with other imaging techniques. The newly developed parameter MXTC-S, which characterizes the functional thickness of alveolar septa, has potential as a novel biomarker for regional parenchymal inflammation or thickening. PMID:21509861

Diagnostic accuracy of magnetic resonance imaging techniques for treatment response evaluation in patients with high-grade glioma, a systematic review and meta-analysis.

PubMed

van Dijken, Bart R J; van Laar, Peter Jan; Holtman, Gea A; van der Hoorn, Anouk

2017-10-01

Treatment response assessment in high-grade gliomas uses contrast enhanced T1-weighted MRI, but is unreliable. Novel advanced MRI techniques have been studied, but the accuracy is not well known. Therefore, we performed a systematic meta-analysis to assess the diagnostic accuracy of anatomical and advanced MRI for treatment response in high-grade gliomas. Databases were searched systematically. Study selection and data extraction were done by two authors independently. Meta-analysis was performed using a bivariate random effects model when ≥5 studies were included. Anatomical MRI (five studies, 166 patients) showed a pooled sensitivity and specificity of 68% (95%CI 51-81) and 77% (45-93), respectively. Pooled apparent diffusion coefficients (seven studies, 204 patients) demonstrated a sensitivity of 71% (60-80) and specificity of 87% (77-93). DSC-perfusion (18 studies, 708 patients) sensitivity was 87% (82-91) with a specificity of 86% (77-91). DCE-perfusion (five studies, 207 patients) sensitivity was 92% (73-98) and specificity was 85% (76-92). The sensitivity of spectroscopy (nine studies, 203 patients) was 91% (79-97) and specificity was 95% (65-99). Advanced techniques showed higher diagnostic accuracy than anatomical MRI, the highest for spectroscopy, supporting the use in treatment response assessment in high-grade gliomas. • Treatment response assessment in high-grade gliomas with anatomical MRI is unreliable • Novel advanced MRI techniques have been studied, but diagnostic accuracy is unknown • Meta-analysis demonstrates that advanced MRI showed higher diagnostic accuracy than anatomical MRI • Highest diagnostic accuracy for spectroscopy and perfusion MRI • Supports the incorporation of advanced MRI in high-grade glioma treatment response assessment.

Auditory neuroimaging with fMRI and PET.

PubMed

Talavage, Thomas M; Gonzalez-Castillo, Javier; Scott, Sophie K

2014-01-01

For much of the past 30 years, investigations of auditory perception and language have been enhanced or even driven by the use of functional neuroimaging techniques that specialize in localization of central responses. Beginning with investigations using positron emission tomography (PET) and gradually shifting primarily to usage of functional magnetic resonance imaging (fMRI), auditory neuroimaging has greatly advanced our understanding of the organization and response properties of brain regions critical to the perception of and communication with the acoustic world in which we live. As the complexity of the questions being addressed has increased, the techniques, experiments and analyses applied have also become more nuanced and specialized. A brief review of the history of these investigations sets the stage for an overview and analysis of how these neuroimaging modalities are becoming ever more effective tools for understanding the auditory brain. We conclude with a brief discussion of open methodological issues as well as potential clinical applications for auditory neuroimaging. This article is part of a Special Issue entitled Human Auditory Neuroimaging. Copyright © 2013 Elsevier B.V. All rights reserved.

Concurrent white matter bundles and grey matter networks using independent component analysis.

PubMed

O'Muircheartaigh, Jonathan; Jbabdi, Saad

2018-04-15

Developments in non-invasive diffusion MRI tractography techniques have permitted the investigation of both the anatomy of white matter pathways connecting grey matter regions and their structural integrity. In parallel, there has been an expansion in automated techniques aimed at parcellating grey matter into distinct regions based on functional imaging. Here we apply independent component analysis to whole-brain tractography data to automatically extract brain networks based on their associated white matter pathways. This method decomposes the tractography data into components that consist of paired grey matter 'nodes' and white matter 'edges', and automatically separates major white matter bundles, including known cortico-cortical and cortico-subcortical tracts. We show how this framework can be used to investigate individual variations in brain networks (in terms of both nodes and edges) as well as their associations with individual differences in behaviour and anatomy. Finally, we investigate correspondences between tractography-based brain components and several canonical resting-state networks derived from functional MRI. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Wide-bore 1.5 T MRI-guided deep brain stimulation surgery: initial experience and technique comparison.

PubMed

Sillay, Karl A; Rusy, Deborah; Buyan-Dent, Laura; Ninman, Nancy L; Vigen, Karl K

2014-12-01

We report results of the initial experience with magnetic resonance image (MRI)-guided implantation of subthalamic nucleus (STN) deep brain stimulating (DBS) electrodes at the University of Wisconsin after having employed frame-based stereotaxy with previously available MR imaging techniques and microelectrode recording for STN DBS surgeries. Ten patients underwent MRI-guided DBS implantation of 20 electrodes between April 2011 and March 2013. The procedure was performed in a purpose-built intraoperative MRI suite configured specifically to allow MRI-guided DBS, using a wide-bore (70 cm) MRI system. Trajectory guidance was accomplished with commercially available system consisting of an MR-visible skull-mounted aiming device and a software guidance system processing intraoperatively acquired iterative MRI scans. A total of 10 patients (5 male, 5 female)-representative of the Parkinson Disease (PD) population-were operated on with standard technique and underwent 20 electrode placements under MRI-guided bilateral STN-targeted DBS placement. All patients completed the procedure with electrodes successfully placed in the STN. Procedure time improved with experience. Our initial experience confirms the safety of MRI-guided DBS, setting the stage for future investigations combining physiology and MRI guidance. Further follow-up is required to compare the efficacy of the MRI-guided surgery cohort to that of traditional frame-based stereotaxy. Copyright © 2014 Elsevier B.V. All rights reserved.

SU-D-18C-01: A Novel 4D-MRI Technology Based On K-Space Retrospective Sorting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Y; Yin, F; Cai, J

2014-06-01

Purpose: Current 4D-MRI techniques lack sufficient temporal/spatial resolution and consistent tumor contrast. To overcome these limitations, this study presents the development and initial evaluation of an entirely new framework of 4D-MRI based on k-space retrospective sorting. Methods: An important challenge of the proposed technique is to determine the number of repeated scans(NR) required to obtain sufficient k-space data for 4D-MRI. To do that, simulations using 29 cancer patients' respiratory profiles were performed to derive the relationship between data acquisition completeness(Cp) and NR, also relationship between NR(Cp=95%) and the following factors: total slice(NS), respiratory phase bin length(Lb), frame rate(fr), resolution(R) andmore » image acquisition starting-phase(P0). To evaluate our technique, a computer simulation study on a 4D digital human phantom (XCAT) were conducted with regular breathing (fr=0.5Hz; R=256×256). A 2D echo planer imaging(EPI) MRI sequence were assumed to acquire raw k-space data, with respiratory signal and acquisition time for each k-space data line recorded simultaneously. K-space data was re-sorted based on respiratory phases. To evaluate 4D-MRI image quality, tumor trajectories were measured and compared with the input signal. Mean relative amplitude difference(D) and cross-correlation coefficient(CC) are calculated. Finally, phase-sharing sliding window technique was applied to investigate the feasibility of generating ultra-fast 4D-MRI. Result: Cp increased with NR(Cp=100*[1-exp(-0.19*NR)], when NS=30, Lb=100%/6). NR(Cp=95%) was inversely-proportional to Lb (r=0.97), but independent of other factors. 4D-MRI on XCAT demonstrated highly accurate motion information (D=0.67%, CC=0.996) with much less artifacts than those on image-based sorting 4D-MRI. Ultra-fast 4D-MRI with an apparent temporal resolution of 10 frames/second was reconstructed using the phase-sharing sliding window technique. Conclusions: A novel 4D-MRI technology based on k-space sorting has been successfully developed and evaluated on the digital phantom. Framework established can be applied to a variety of MR sequences, showing great promises to develop the optimal 4D-MRI technique for many radiation therapy applications. NIH (1R21CA165384-01A1)« less

Magnetic Resonance Imaging of Adipose Tissue in Metabolic Dysfunction.

PubMed

Franz, Daniela; Syväri, Jan; Weidlich, Dominik; Baum, Thomas; Rummeny, Ernst J; Karampinos, Dimitrios C

2018-06-06

 Adipose tissue has become an increasingly important tissue target in medicine. It plays a central role in the storage and release of energy throughout the human body and has recently gained interest for its endocrinologic function. Magnetic resonance imaging (MRI) is an established method for quantitative direct evaluation of adipose tissue distribution, and is used increasingly as the modality of choice for metabolic phenotyping. The purpose of this review was the identification and presentation of the currently available literature on MRI of adipose tissue in metabolic dysfunction.  A PubMed (http://www.ncbi.nlm.nih.gov/pubmed) keyword search up to August 2017 without starting date limitation was performed and reference lists of relevant articles were searched.  MRI provides excellent tools for the evaluation of adipose tissue distribution and further characterization of the tissue. Standard as well as newly developed MRI techniques allow a risk stratification for the development of metabolic dysfunction and enable monitoring without the use of ionizing radiation or contrast material.   · Different types of adipose tissue play a crucial role in various types of metabolic dysfunction.. · Magnetic resonance imaging (MRI) is an excellent tool for noninvasive adipose tissue evaluation with respect to distribution, composition and metabolic activity.. · Both standard and newly developed MRI techniques can be used for risk stratification for the development of metabolic dysfunction and allow monitoring without the use of ionizing radiation or contrast material.. · Franz D, Syväri J, Weidlich D et al. Magnetic Resonance Imaging of Adipose Tissue in Metabolic Dysfunction. Fortschr Röntgenstr 2018; DOI: 10.1055/a-0612-8006. © Georg Thieme Verlag KG Stuttgart · New York.

A Comparative Study of Average, Linked Mastoid, and REST References for ERP Components Acquired during fMRI

PubMed Central

Yang, Ping; Fan, Chenggui; Wang, Min; Li, Ling

2017-01-01

In simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) studies, average reference (AR), and digitally linked mastoid (LM) are popular re-referencing techniques in event-related potential (ERP) analyses. However, they may introduce their own physiological signals and alter the EEG/ERP outcome. A reference electrode standardization technique (REST) that calculated a reference point at infinity was proposed to solve this problem. To confirm the advantage of REST in ERP analyses of synchronous EEG-fMRI studies, we compared the reference effect of AR, LM, and REST on task-related ERP results of a working memory task during an fMRI scan. As we hypothesized, we found that the adopted reference did not change the topography map of ERP components (N1 and P300 in the present study), but it did alter the task-related effect on ERP components. LM decreased or eliminated the visual working memory (VWM) load effect on P300, and the AR distorted the distribution of VWM location-related effect at left posterior electrodes as shown in the statistical parametric scalp mapping (SPSM) of N1. ERP cortical source estimates, which are independent of the EEG reference choice, were used as the golden standard to infer the relative utility of different references on the ERP task-related effect. By comparison, REST reference provided a more integrated and reasonable result. These results were further confirmed by the results of fMRI activations and a corresponding EEG-only study. Thus, we recommend the REST, especially with a realistic head model, as the optimal reference method for ERP data analysis in simultaneous EEG-fMRI studies. PMID:28529472

A Comparative Study of Average, Linked Mastoid, and REST References for ERP Components Acquired during fMRI.

PubMed

Yang, Ping; Fan, Chenggui; Wang, Min; Li, Ling

2017-01-01

In simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) studies, average reference (AR), and digitally linked mastoid (LM) are popular re-referencing techniques in event-related potential (ERP) analyses. However, they may introduce their own physiological signals and alter the EEG/ERP outcome. A reference electrode standardization technique (REST) that calculated a reference point at infinity was proposed to solve this problem. To confirm the advantage of REST in ERP analyses of synchronous EEG-fMRI studies, we compared the reference effect of AR, LM, and REST on task-related ERP results of a working memory task during an fMRI scan. As we hypothesized, we found that the adopted reference did not change the topography map of ERP components (N1 and P300 in the present study), but it did alter the task-related effect on ERP components. LM decreased or eliminated the visual working memory (VWM) load effect on P300, and the AR distorted the distribution of VWM location-related effect at left posterior electrodes as shown in the statistical parametric scalp mapping (SPSM) of N1. ERP cortical source estimates, which are independent of the EEG reference choice, were used as the golden standard to infer the relative utility of different references on the ERP task-related effect. By comparison, REST reference provided a more integrated and reasonable result. These results were further confirmed by the results of fMRI activations and a corresponding EEG-only study. Thus, we recommend the REST, especially with a realistic head model, as the optimal reference method for ERP data analysis in simultaneous EEG-fMRI studies.

Performance of Blind Source Separation Algorithms for FMRI Analysis using a Group ICA Method

PubMed Central

Correa, Nicolle; Adali, Tülay; Calhoun, Vince D.

2007-01-01

Independent component analysis (ICA) is a popular blind source separation (BSS) technique that has proven to be promising for the analysis of functional magnetic resonance imaging (fMRI) data. A number of ICA approaches have been used for fMRI data analysis, and even more ICA algorithms exist, however the impact of using different algorithms on the results is largely unexplored. In this paper, we study the performance of four major classes of algorithms for spatial ICA, namely information maximization, maximization of non-gaussianity, joint diagonalization of cross-cumulant matrices, and second-order correlation based methods when they are applied to fMRI data from subjects performing a visuo-motor task. We use a group ICA method to study the variability among different ICA algorithms and propose several analysis techniques to evaluate their performance. We compare how different ICA algorithms estimate activations in expected neuronal areas. The results demonstrate that the ICA algorithms using higher-order statistical information prove to be quite consistent for fMRI data analysis. Infomax, FastICA, and JADE all yield reliable results; each having their strengths in specific areas. EVD, an algorithm using second-order statistics, does not perform reliably for fMRI data. Additionally, for the iterative ICA algorithms, it is important to investigate the variability of the estimates from different runs. We test the consistency of the iterative algorithms, Infomax and FastICA, by running the algorithm a number of times with different initializations and note that they yield consistent results over these multiple runs. Our results greatly improve our confidence in the consistency of ICA for fMRI data analysis. PMID:17540281

Questions and answers on prostate multiparameter magnetic resonance imaging: Everything a urologist should know.

PubMed

Catalá, V; Salas, D; Esquena, S; Mateu, S; Algaba, F; Palou, J; de la Torre, P

2016-01-01

For many years, the detection of prostate cancer (PC) and the management of its therapy have been based primarily on prostate-specific antigen, rectal examination and prostate biopsy. However, these parameters have known limitations. Multiparametric magnetic resonance imaging (mpMRI) for prostate cancer has undergone extensive development in recent years, providing morphological and functional information. The aim of this study is to present an updated review of the scope and limitations of prostatic mpMRI for PC, in the framework of a multidisciplinary vision. We conducted a literature review (in PubMed) of articles referencing "mpMRI/staging/ PC/detection/active surveillance/therapy planning/post-therapy". We included 4 systematic reviews and other articles published in high impact-factor journals within the field of radiology and urology. MpMRI provides morphological and functional information concerning PC. This information is integrated into the Prostate Imaging Report and Date System, classifying the probability of clinically significant carcinoma on a scale from 1 to 5. The usefulness of mpMRI is currently being established for patients with high prostate-specific antigen levels and prior negative prostate biopsy; tumour staging in selected cases; assessment of patients who are candidates for active surveillance; the planning of focal treatments; and the assessment of tumour persistence and recurrence. MpMRI currently fills a relevant role in the diagnosis and therapeutic decision-making of PC. More widespread use of the technique requires a cost/benefit analysis. Copyright © 2015 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

Deformable and rigid registration of MRI and microPET images for photodynamic therapy of cancer in mice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fei Baowei; Wang Hesheng; Muzic, Raymond F. Jr.

2006-03-15

We are investigating imaging techniques to study the tumor response to photodynamic therapy (PDT). Positron emission tomography (PET) can provide physiological and functional information. High-resolution magnetic resonance imaging (MRI) can provide anatomical and morphological changes. Image registration can combine MRI and PET images for improved tumor monitoring. In this study, we acquired high-resolution MRI and microPET {sup 18}F-fluorodeoxyglucose (FDG) images from C3H mice with RIF-1 tumors that were treated with Pc 4-based PDT. We developed two registration methods for this application. For registration of the whole mouse body, we used an automatic three-dimensional, normalized mutual information algorithm. For tumor registration,more » we developed a finite element model (FEM)-based deformable registration scheme. To assess the quality of whole body registration, we performed slice-by-slice review of both image volumes; manually segmented feature organs, such as the left and right kidneys and the bladder, in each slice; and computed the distance between corresponding centroids. Over 40 volume registration experiments were performed with MRI and microPET images. The distance between corresponding centroids of organs was 1.5{+-}0.4 mm which is about 2 pixels of microPET images. The mean volume overlap ratios for tumors were 94.7% and 86.3% for the deformable and rigid registration methods, respectively. Registration of high-resolution MRI and microPET images combines anatomical and functional information of the tumors and provides a useful tool for evaluating photodynamic therapy.« less

Development of an apparatus and methodology for conducting functional magnetic resonance imaging (fMRI) with pharmacological stimuli in conscious rhesus monkeys.

PubMed

Murnane, Kevin Sean; Howell, Leonard Lee

2010-08-15

Functional magnetic resonance imaging (fMRI) is a technique with significant potential to advance our understanding of multiple brain systems. However, when human subjects undergo fMRI studies they are typically conscious whereas pre-clinical fMRI studies typically utilize anesthesia, which complicates comparisons across studies. Therefore, we have developed an apparatus suitable for imaging conscious rhesus monkeys. In order to minimize subject stress and spatial motion, each subject was acclimated to the necessary procedures over several months. The effectiveness of this process was then evaluated, in fully trained subjects, by quantifying objective physiological measures. These physiological metrics were stable both within and across sessions and did not differ from when these same subjects were immobilized using standard primate handling procedures. Subject motion and blood oxygenation level dependent (BOLD) fMRI measurements were then evaluated by scanning subjects under three different conditions: the absence of stimulation, presentation of a visual stimulus, or administration of intravenous (i.v.) cocaine (0.3mg/kg). Spatial motion differed neither by condition nor along the three principal axes. In addition, maximum translational and rotational motion never exceeded one half of the voxel size (0.75 mm) or 1.5 degrees, respectively. Furthermore, the localization of changes in blood oxygenation closely matched those reported in previous studies using similar stimuli. These findings document the feasibility of fMRI data collection in conscious rhesus monkeys using these procedures and allow for the further study of the neural effects of psychoactive drugs. (c) 2010 Elsevier B.V. All rights reserved.

Magnetic Resonance Elastography and Other Magnetic Resonance Imaging Techniques in Chronic Liver Disease: Current Status and Future Directions.

PubMed

Tan, Cher Heng; Venkatesh, Sudhakar Kundapur

2016-09-15

Recent advances in the noninvasive imaging of chronic liver disease have led to improvements in diagnosis, particularly with magnetic resonance imaging (MRI). A comprehensive evaluation of the liver may be performed with the quantification of the degree of hepatic steatosis, liver iron concentration, and liver fibrosis. In addition, MRI of the liver may be used to identify complications of cirrhosis, including portal hypertension, ascites, and the development of hepatocellular carcinoma. In this review article, we discuss the state of the art techniques in liver MRI, namely, magnetic resonance elastography, hepatobiliary phase MRI, and liver fat and iron quantification MRI. The use of these advanced techniques in the management of chronic liver diseases, including nonalcoholic fatty liver disease, will be elaborated.

Magnetic Resonance Elastography and Other Magnetic Resonance Imaging Techniques in Chronic Liver Disease: Current Status and Future Directions

PubMed Central

Tan, Cher Heng; Venkatesh, Sudhakar Kundapur

2016-01-01

Recent advances in the noninvasive imaging of chronic liver disease have led to improvements in diagnosis, particularly with magnetic resonance imaging (MRI). A comprehensive evaluation of the liver may be performed with the quantification of the degree of hepatic steatosis, liver iron concentration, and liver fibrosis. In addition, MRI of the liver may be used to identify complications of cirrhosis, including portal hypertension, ascites, and the development of hepatocellular carcinoma. In this review article, we discuss the state of the art techniques in liver MRI, namely, magnetic resonance elastography, hepatobiliary phase MRI, and liver fat and iron quantification MRI. The use of these advanced techniques in the management of chronic liver diseases, including non-alcoholic fatty liver disease, will be elaborated. PMID:27563019

An optimized workflow for the integration of biological information into radiotherapy planning: experiences with T1w DCE-MRI

NASA Astrophysics Data System (ADS)

Neff, T.; Kiessling, F.; Brix, G.; Baudendistel, K.; Zechmann, C.; Giesel, F. L.; Bendl, R.

2005-09-01

Planning of radiotherapy is often difficult due to restrictions on morphological images. New imaging techniques enable the integration of biological information into treatment planning and help to improve the detection of vital and aggressive tumour areas. This might improve clinical outcome. However, nowadays morphological data sets are still the gold standard in the planning of radiotherapy. In this paper, we introduce an in-house software platform enabling us to combine images from different imaging modalities yielding biological and morphological information in a workflow driven approach. This is demonstrated for the combination of morphological CT, MRI, functional DCE-MRI and PET data. Data of patients with a tumour of the prostate and with a meningioma were examined with DCE-MRI by applying pharmacokinetic two-compartment models for post-processing. The results were compared with the clinical plans for radiation therapy. Generated parameter maps give additional information about tumour spread, which can be incorporated in the definition of safety margins.

Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture

PubMed Central

Meszlényi, Regina J.; Buza, Krisztian; Vidnyánszky, Zoltán

2017-01-01

Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network. PMID:29089883

Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture.

PubMed

Meszlényi, Regina J; Buza, Krisztian; Vidnyánszky, Zoltán

2017-01-01

Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network.

Studies of MRI relaxivities of gadolinium-labeled dendrons

NASA Astrophysics Data System (ADS)

Pan, Hongmu; Daniel, Marie-Christine

2011-05-01

In cancer detection, imaging techniques have a great importance in early diagnosis. The more sensitive the imaging technique and the earlier the tumor can be detected. Contrast agents have the capability to increase the sensitivity in imaging techniques such as magnetic resonance imaging (MRI). Until now, gadolinium-based contrast agents are mainly used for MRI, and show good enhancement. But improvement is needed for detection of smaller tumors at the earliest stage possible. The dendrons complexed with Gd(DOTA) were synthesized and evaluated as a new MRI contrast agent. The longitudinal and transverse relaxation effects were tested and compared with commercial drug Magnevist, Gd(DTPA).

Unwrapping eddy current compensation: improved compensation of eddy current induced baseline shifts in high-resolution phase-contrast MRI at 9.4 Tesla.

PubMed

Espe, Emil K S; Zhang, Lili; Sjaastad, Ivar

2014-10-01

Phase-contrast MRI (PC-MRI) is a versatile tool allowing evaluation of in vivo motion, but is sensitive to eddy current induced phase offsets, causing errors in the measured velocities. In high-resolution PC-MRI, these offsets can be sufficiently large to cause wrapping in the baseline phase, rendering conventional eddy current compensation (ECC) inadequate. The purpose of this study was to develop an improved ECC technique (unwrapping ECC) able to handle baseline phase discontinuities. Baseline phase discontinuities are unwrapped by minimizing the spatiotemporal standard deviation of the static-tissue phase. Computer simulations were used for demonstrating the theoretical foundation of the proposed technique. The presence of baseline wrapping was confirmed in high-resolution myocardial PC-MRI of a normal rat heart at 9.4 Tesla (T), and the performance of unwrapping ECC was compared with conventional ECC. Areas of phase wrapping in static regions were clearly evident in high-resolution PC-MRI. The proposed technique successfully eliminated discontinuities in the baseline, and resulted in significantly better ECC than the conventional approach. We report the occurrence of baseline phase wrapping in PC-MRI, and provide an improved ECC technique capable of handling its presence. Unwrapping ECC offers improved correction of eddy current induced baseline shifts in high-resolution PC-MRI. Copyright © 2013 Wiley Periodicals, Inc.

Language Mapping Using fMRI and Direct Cortical Stimulation for Brain Tumor Surgery

PubMed Central

Brennan, Nicole Petrovich; Peck, Kyung K.; Holodny, Andrei

2016-01-01

Language functional magnetic resonance imaging for neurosurgical planning is a useful but nuanced technique. Consideration of primary and secondary language anatomy, task selection, and data analysis choices all impact interpretation. In the following chapter, we consider practical considerations and nuances alike for language functional magnetic resonance imaging in the support of and comparison with the neurosurgical gold standard, direct cortical stimulation. Pitfalls and limitations are discussed. PMID:26848555

A wavelet-based estimator of the degrees of freedom in denoised fMRI time series for probabilistic testing of functional connectivity and brain graphs.

PubMed

Patel, Ameera X; Bullmore, Edward T

2016-11-15

Connectome mapping using techniques such as functional magnetic resonance imaging (fMRI) has become a focus of systems neuroscience. There remain many statistical challenges in analysis of functional connectivity and network architecture from BOLD fMRI multivariate time series. One key statistic for any time series is its (effective) degrees of freedom, df, which will generally be less than the number of time points (or nominal degrees of freedom, N). If we know the df, then probabilistic inference on other fMRI statistics, such as the correlation between two voxel or regional time series, is feasible. However, we currently lack good estimators of df in fMRI time series, especially after the degrees of freedom of the "raw" data have been modified substantially by denoising algorithms for head movement. Here, we used a wavelet-based method both to denoise fMRI data and to estimate the (effective) df of the denoised process. We show that seed voxel correlations corrected for locally variable df could be tested for false positive connectivity with better control over Type I error and greater specificity of anatomical mapping than probabilistic connectivity maps using the nominal degrees of freedom. We also show that wavelet despiked statistics can be used to estimate all pairwise correlations between a set of regional nodes, assign a P value to each edge, and then iteratively add edges to the graph in order of increasing P. These probabilistically thresholded graphs are likely more robust to regional variation in head movement effects than comparable graphs constructed by thresholding correlations. Finally, we show that time-windowed estimates of df can be used for probabilistic connectivity testing or dynamic network analysis so that apparent changes in the functional connectome are appropriately corrected for the effects of transient noise bursts. Wavelet despiking is both an algorithm for fMRI time series denoising and an estimator of the (effective) df of denoised fMRI time series. Accurate estimation of df offers many potential advantages for probabilistically thresholding functional connectivity and network statistics tested in the context of spatially variant and non-stationary noise. Code for wavelet despiking, seed correlational testing and probabilistic graph construction is freely available to download as part of the BrainWavelet Toolbox at www.brainwavelet.org. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Reward circuit connectivity relates to delay discounting in children with attention-deficit/hyperactivity disorder

PubMed Central

Costa Dias, Taciana G.; Wilson, Vanessa B.; Bathula, Deepti R.; Iyer, Swathi P.; Mills, Kathryn L.; Thurlow, Bria L.; Stevens, Corinne A.; Musser, Erica D.; Carpenter, Samuel D.; Grayson, David S.; Mitchell, Suzanne H.; Nigg, Joel T.; Fair, Damien A.

2012-01-01

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent psychiatric disorder that has poor long-term outcomes and remains a major public health concern. Recent theories have proposed that ADHD arises from alterations in multiple neural pathways. Alterations in reward circuits are hypothesized as one core dysfunction, leading to altered processing of anticipated rewards. The nucleus accumbens (NAcc) is particularly important for reward processes; task-based fMRI studies have found atypical activation of this region while the participants performed a reward task. Understanding how reward circuits are involved with ADHD may be further enhanced by considering how the NAcc interacts with other brain regions. Here we used the technique of resting-state functional connectivity MRI (rs-fcMRI) to examine the alterations in the NAcc interactions and how they relate to impulsive decision making in ADHD. Using rs-fcMRI, this study: examined differences in functional connectivity of the NAcc between children with ADHD and control children; correlated the functional connectivity of NAcc with impulsivity, as measured by a delay discounting task; and combined these two initial segments to identify the atypical NAcc connections that were associated with impulsive decision making in ADHD. We found that functional connectivity of NAcc was atypical in children with ADHD and the ADHD-related increased connectivity between NAcc and the prefrontal cortex was associated with greater impulsivity (steeper delayed-reward discounting). These findings are consistent with the hypothesis that atypical signaling of the NAcc to the prefrontal cortex in ADHD may lead to excessive approach and failure in estimating future consequences; thus, leading to impulsive behavior. PMID:23206930

Tractography-Based Score for Learning Effective Connectivity From Multimodal Imaging Data Using Dynamic Bayesian Networks.

PubMed

Dang, Shilpa; Chaudhury, Santanu; Lall, Brejesh; Roy, Prasun K

2018-05-01

Effective connectivity (EC) is the methodology for determining functional-integration among the functionally active segregated regions of the brain. By definition EC is "the causal influence exerted by one neuronal group on another" which is constrained by anatomical connectivity (AC) (axonal connections). AC is necessary for EC but does not fully determine it, because synaptic communication occurs dynamically in a context-dependent fashion. Although there is a vast emerging evidence of structure-function relationship using multimodal imaging studies, till date only a few studies have done joint modeling of the two modalities: functional MRI (fMRI) and diffusion tensor imaging (DTI). We aim to propose a unified probabilistic framework that combines information from both sources to learn EC using dynamic Bayesian networks (DBNs). DBNs are probabilistic graphical temporal models that learn EC in an exploratory fashion. Specifically, we propose a novel anatomically informed (AI) score that evaluates fitness of a given connectivity structure to both DTI and fMRI data simultaneously. The AI score is employed in structure learning of DBN given the data. Experiments with synthetic-data demonstrate the face validity of structure learning with our AI score over anatomically uninformed counterpart. Moreover, real-data results are cross-validated by performing classification-experiments. EC inferred on real fMRI-DTI datasets is found to be consistent with previous literature and show promising results in light of the AC present as compared to other classically used techniques such as Granger-causality. Multimodal analyses provide a more reliable basis for differentiating brain under abnormal/diseased conditions than the single modality analysis.

An Investigation of the Relationship Between fMRI and ERP Source Localized Measurements of Brain Activity during Face Processing

PubMed Central

Richards, Todd; Webb, Sara Jane; Murias, Michael; Merkle, Kristen; Kleinhans, Natalia M.; Johnson, L. Clark; Poliakov, Andrew; Aylward, Elizabeth; Dawson, Geraldine

2013-01-01

Brain activity patterns during face processing have been extensively explored with functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs). ERP source localization adds a spatial dimension to the ERP time series recordings, which allows for a more direct comparison and integration with fMRI findings. The goals for this study were (1) to compare the spatial descriptions of neuronal activity during face processing obtained with fMRI and ERP source localization using low-resolution electro-magnetic tomography (LORETA), and (2) to use the combined information from source localization and fMRI to explore how the temporal sequence of brain activity during face processing is summarized in fMRI activation maps. fMRI and high-density ERP data were acquired in separate sessions for 17 healthy adult males for a face and object processing task. LORETA statistical maps for the comparison of viewing faces and viewing houses were coregistered and compared to fMRI statistical maps for the same conditions. The spatial locations of face processing-sensitive activity measured by fMRI and LORETA were found to overlap in a number of areas including the bilateral fusiform gyri, the right superior, middle and inferior temporal gyri, and the bilateral precuneus. Both the fMRI and LORETA solutions additionally demon-strated activity in regions that did not overlap. fMRI and LORETA statistical maps of face processing-sensitive brain activity were found to converge spatially primarily at LORETA solution latencies that were within 18 ms of the N170 latency. The combination of data from these techniques suggested that electrical brain activity at the latency of the N170 is highly represented in fMRI statistical maps. PMID:19322649

Quantitative magnetic resonance (MR) neurography for evaluation of peripheral nerves and plexus injuries

PubMed Central

Barousse, Rafael; Socolovsky, Mariano; Luna, Antonio

2017-01-01

Traumatic conditions of peripheral nerves and plexus have been classically evaluated by morphological imaging techniques and electrophysiological tests. New magnetic resonance imaging (MRI) studies based on 3D fat-suppressed techniques are providing high accuracy for peripheral nerve injury evaluation from a qualitative point of view. However, these techniques do not provide quantitative information. Diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI) are functional MRI techniques that are able to evaluate and quantify the movement of water molecules within different biological structures. These techniques have been successfully applied in other anatomical areas, especially in the assessment of central nervous system, and now are being imported, with promising results for peripheral nerve and plexus evaluation. DWI and DTI allow performing a qualitative and quantitative peripheral nerve analysis, providing valuable pathophysiological information about functional integrity of these structures. In the field of trauma and peripheral nerve or plexus injury, several derived parameters from DWI and DTI studies such as apparent diffusion coefficient (ADC) or fractional anisotropy (FA) among others, can be used as potential biomarkers of neural damage providing information about fiber organization, axonal flow or myelin integrity. A proper knowledge of physical basis of these techniques and their limitations is important for an optimal interpretation of the imaging findings and derived data. In this paper, a comprehensive review of the potential applications of DWI and DTI neurographic studies is performed with a focus on traumatic conditions, including main nerve entrapment syndromes in both peripheral nerves and brachial or lumbar plexus. PMID:28932698

A Bayesian spatial model for neuroimaging data based on biologically informed basis functions.

PubMed

Huertas, Ismael; Oldehinkel, Marianne; van Oort, Erik S B; Garcia-Solis, David; Mir, Pablo; Beckmann, Christian F; Marquand, Andre F

2017-11-01

The dominant approach to neuroimaging data analysis employs the voxel as the unit of computation. While convenient, voxels lack biological meaning and their size is arbitrarily determined by the resolution of the image. Here, we propose a multivariate spatial model in which neuroimaging data are characterised as a linearly weighted combination of multiscale basis functions which map onto underlying brain nuclei or networks or nuclei. In this model, the elementary building blocks are derived to reflect the functional anatomy of the brain during the resting state. This model is estimated using a Bayesian framework which accurately quantifies uncertainty and automatically finds the most accurate and parsimonious combination of basis functions describing the data. We demonstrate the utility of this framework by predicting quantitative SPECT images of striatal dopamine function and we compare a variety of basis sets including generic isotropic functions, anatomical representations of the striatum derived from structural MRI, and two different soft functional parcellations of the striatum derived from resting-state fMRI (rfMRI). We found that a combination of ∼50 multiscale functional basis functions accurately represented the striatal dopamine activity, and that functional basis functions derived from an advanced parcellation technique known as Instantaneous Connectivity Parcellation (ICP) provided the most parsimonious models of dopamine function. Importantly, functional basis functions derived from resting fMRI were more accurate than both structural and generic basis sets in representing dopamine function in the striatum for a fixed model order. We demonstrate the translational validity of our framework by constructing classification models for discriminating parkinsonian disorders and their subtypes. Here, we show that ICP approach is the only basis set that performs well across all comparisons and performs better overall than the classical voxel-based approach. This spatial model constitutes an elegant alternative to voxel-based approaches in neuroimaging studies; not only are their atoms biologically informed, they are also adaptive to high resolutions, represent high dimensions efficiently, and capture long-range spatial dependencies, which are important and challenging objectives for neuroimaging data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A novel tablet computer platform for advanced language mapping during awake craniotomy procedures.

PubMed

Morrison, Melanie A; Tam, Fred; Garavaglia, Marco M; Golestanirad, Laleh; Hare, Gregory M T; Cusimano, Michael D; Schweizer, Tom A; Das, Sunit; Graham, Simon J

2016-04-01

A computerized platform has been developed to enhance behavioral testing during intraoperative language mapping in awake craniotomy procedures. The system is uniquely compatible with the environmental demands of both the operating room and preoperative functional MRI (fMRI), thus providing standardized testing toward improving spatial agreement between the 2 brain mapping techniques. Details of the platform architecture, its advantages over traditional testing methods, and its use for language mapping are described. Four illustrative cases demonstrate the efficacy of using the testing platform to administer sophisticated language paradigms, and the spatial agreement between intraoperative mapping and preoperative fMRI results. The testing platform substantially improved the ability of the surgeon to detect and characterize language deficits. Use of a written word generation task to assess language production helped confirm areas of speech apraxia and speech arrest that were inadequately characterized or missed with the use of traditional paradigms, respectively. Preoperative fMRI of the analogous writing task was also assistive, displaying excellent spatial agreement with intraoperative mapping in all 4 cases. Sole use of traditional testing paradigms can be limiting during awake craniotomy procedures. Comprehensive assessment of language function will require additional use of more sophisticated and ecologically valid testing paradigms. The platform presented here provides a means to do so.

Variational Bayesian Parameter Estimation Techniques for the General Linear Model

PubMed Central

Starke, Ludger; Ostwald, Dirk

2017-01-01

Variational Bayes (VB), variational maximum likelihood (VML), restricted maximum likelihood (ReML), and maximum likelihood (ML) are cornerstone parametric statistical estimation techniques in the analysis of functional neuroimaging data. However, the theoretical underpinnings of these model parameter estimation techniques are rarely covered in introductory statistical texts. Because of the widespread practical use of VB, VML, ReML, and ML in the neuroimaging community, we reasoned that a theoretical treatment of their relationships and their application in a basic modeling scenario may be helpful for both neuroimaging novices and practitioners alike. In this technical study, we thus revisit the conceptual and formal underpinnings of VB, VML, ReML, and ML and provide a detailed account of their mathematical relationships and implementational details. We further apply VB, VML, ReML, and ML to the general linear model (GLM) with non-spherical error covariance as commonly encountered in the first-level analysis of fMRI data. To this end, we explicitly derive the corresponding free energy objective functions and ensuing iterative algorithms. Finally, in the applied part of our study, we evaluate the parameter and model recovery properties of VB, VML, ReML, and ML, first in an exemplary setting and then in the analysis of experimental fMRI data acquired from a single participant under visual stimulation. PMID:28966572

fMRI activation patterns in an analytic reasoning task: consistency with EEG source localization

NASA Astrophysics Data System (ADS)

Li, Bian; Vasanta, Kalyana C.; O'Boyle, Michael; Baker, Mary C.; Nutter, Brian; Mitra, Sunanda

2010-03-01

Functional magnetic resonance imaging (fMRI) is used to model brain activation patterns associated with various perceptual and cognitive processes as reflected by the hemodynamic (BOLD) response. While many sensory and motor tasks are associated with relatively simple activation patterns in localized regions, higher-order cognitive tasks may produce activity in many different brain areas involving complex neural circuitry. We applied a recently proposed probabilistic independent component analysis technique (PICA) to determine the true dimensionality of the fMRI data and used EEG localization to identify the common activated patterns (mapped as Brodmann areas) associated with a complex cognitive task like analytic reasoning. Our preliminary study suggests that a hybrid GLM/PICA analysis may reveal additional regions of activation (beyond simple GLM) that are consistent with electroencephalography (EEG) source localization patterns.

Dynamic enhancement MRI of anterior lobe in pituitary dwarfism.

PubMed

Liu, H M; Li, Y W; Tsai, W Y; Su, C T

1995-08-01

We examined 23 patients with pituitary dwarfism by dynamic MRI; with a repetition time of 150 or 50 ms. The time-enhancement difference curves of selected regions in the anterior lobes were plotted. Another 48 patients with no definite clinical pituitary disfunction were examined with the same technique. We found that the intensity of maximum enhancement in both groups was similar, but the time to achieve maximum enhancement was delayed in pituitary dwarfism with or without stalk transection; the time seemed longest with stalk transection. There was little difference in enhancement between patients with multiple hormone deficiency or isolated growth hormone deficiency. Dynamic MRI of the anterior lobes may be an important functional imaging study, and our results imply that poor perfusion is a useful finding in pituitary dwarfism, especially in patients without stalk transection and normal pituitary height.

Imaging pathobiology of carotid atherosclerosis with ultrasmall superparamagnetic particles of iron oxide: an update.

PubMed

Sadat, Umar; Usman, Ammara; Gillard, Jonathan H

2017-07-01

To provide brief overview of the developments regarding use of ultrasmall superparamagnetic particles of iron oxide in imaging pathobiology of carotid atherosclerosis. MRI is a promising technique capable of providing morphological and functional information about atheromatous plaques. MRI using iron oxide particles, called ultrasmall superparamagnetic iron oxide (USPIO) particles, allows detection of macrophages in atherosclerotic tissue. Ferumoxytol has emerged as a new USPIO agent, which has an excellent safety profile. Based on the macrophage-selective properties of ferumoxytol, there is increasing number of recent reports suggesting its effectiveness to detect pathological inflammation. USPIO particles allow magnetic resonance detection of macrophages in atherosclerotic tissue. Ferumoxytol has emerged as a new USPIO agent, with an excellent safety profile. This has the potential to be used for MRI of the pathobiology of atherosclerosis.

Prediction of pork quality parameters by applying fractals and data mining on MRI.

PubMed

Caballero, Daniel; Pérez-Palacios, Trinidad; Caro, Andrés; Amigo, José Manuel; Dahl, Anders B; ErsbØll, Bjarne K; Antequera, Teresa

2017-09-01

This work firstly investigates the use of MRI, fractal algorithms and data mining techniques to determine pork quality parameters non-destructively. The main objective was to evaluate the capability of fractal algorithms (Classical Fractal algorithm, CFA; Fractal Texture Algorithm, FTA and One Point Fractal Texture Algorithm, OPFTA) to analyse MRI in order to predict quality parameters of loin. In addition, the effect of the sequence acquisition of MRI (Gradient echo, GE; Spin echo, SE and Turbo 3D, T3D) and the predictive technique of data mining (Isotonic regression, IR and Multiple linear regression, MLR) were analysed. Both fractal algorithm, FTA and OPFTA are appropriate to analyse MRI of loins. The sequence acquisition, the fractal algorithm and the data mining technique seems to influence on the prediction results. For most physico-chemical parameters, prediction equations with moderate to excellent correlation coefficients were achieved by using the following combinations of acquisition sequences of MRI, fractal algorithms and data mining techniques: SE-FTA-MLR, SE-OPFTA-IR, GE-OPFTA-MLR, SE-OPFTA-MLR, with the last one offering the best prediction results. Thus, SE-OPFTA-MLR could be proposed as an alternative technique to determine physico-chemical traits of fresh and dry-cured loins in a non-destructive way with high accuracy. Copyright © 2017. Published by Elsevier Ltd.

Preclinical In vivo Imaging for Fat Tissue Identification, Quantification, and Functional Characterization.

PubMed

Marzola, Pasquina; Boschi, Federico; Moneta, Francesco; Sbarbati, Andrea; Zancanaro, Carlo

2016-01-01

Localization, differentiation, and quantitative assessment of fat tissues have always collected the interest of researchers. Nowadays, these topics are even more relevant as obesity (the excess of fat tissue) is considered a real pathology requiring in some cases pharmacological and surgical approaches. Several weight loss medications, acting either on the metabolism or on the central nervous system, are currently under preclinical or clinical investigation. Animal models of obesity have been developed and are widely used in pharmaceutical research. The assessment of candidate drugs in animal models requires non-invasive methods for longitudinal assessment of efficacy, the main outcome being the amount of body fat. Fat tissues can be either quantified in the entire animal or localized and measured in selected organs/regions of the body. Fat tissues are characterized by peculiar contrast in several imaging modalities as for example Magnetic Resonance Imaging (MRI) that can distinguish between fat and water protons thank to their different magnetic resonance properties. Since fat tissues have higher carbon/hydrogen content than other soft tissues and bones, they can be easily assessed by Computed Tomography (CT) as well. Interestingly, MRI also discriminates between white and brown adipose tissue (BAT); the latter has long been regarded as a potential target for anti-obesity drugs because of its ability to enhance energy consumption through increased thermogenesis. Positron Emission Tomography (PET) performed with 18 F-FDG as glucose analog radiotracer reflects well the metabolic rate in body tissues and consequently is the technique of choice for studies of BAT metabolism. This review will focus on the main, non-invasive imaging techniques (MRI, CT, and PET) that are fundamental for the assessment, quantification and functional characterization of fat deposits in small laboratory animals. The contribution of optical techniques, which are currently regarded with increasing interest, will be also briefly described. For each technique the physical principles of signal detection will be overviewed and some relevant studies will be summarized. Far from being exhaustive, this review has the purpose to highlight some strategies that can be adopted for the in vivo identification, quantification, and functional characterization of adipose tissues mainly from the point of view of biophysics and physiology.

Fetal MRI: A Technical Update with Educational Aspirations

PubMed Central

Gholipour, Ali; Estroff, Judith A.; Barnewolt, Carol E.; Robertson, Richard L.; Grant, P. Ellen; Gagoski, Borjan; Warfield, Simon K.; Afacan, Onur; Connolly, Susan A.; Neil, Jeffrey J.; Wolfberg, Adam; Mulkern, Robert V.

2015-01-01

Fetal magnetic resonance imaging (MRI) examinations have become well-established procedures at many institutions and can serve as useful adjuncts to ultrasound (US) exams when diagnostic doubts remain after US. Due to fetal motion, however, fetal MRI exams are challenging and require the MR scanner to be used in a somewhat different mode than that employed for more routine clinical studies. Herein we review the techniques most commonly used, and those that are available, for fetal MRI with an emphasis on the physics of the techniques and how to deploy them to improve success rates for fetal MRI exams. By far the most common technique employed is single-shot T2-weighted imaging due to its excellent tissue contrast and relative immunity to fetal motion. Despite the significant challenges involved, however, many of the other techniques commonly employed in conventional neuro- and body MRI such as T1 and T2*-weighted imaging, diffusion and perfusion weighted imaging, as well as spectroscopic methods remain of interest for fetal MR applications. An effort to understand the strengths and limitations of these basic methods within the context of fetal MRI is made in order to optimize their use and facilitate implementation of technical improvements for the further development of fetal MR imaging, both in acquisition and post-processing strategies. PMID:26225129

The potential of multiparametric MRI of the breast

PubMed Central

Pinker, Katja; Helbich, Thomas H

2017-01-01

MRI is an essential tool in breast imaging, with multiple established indications. Dynamic contrast-enhanced MRI (DCE-MRI) is the backbone of any breast MRI protocol and has an excellent sensitivity and good specificity for breast cancer diagnosis. DCE-MRI provides high-resolution morphological information, as well as some functional information about neoangiogenesis as a tumour-specific feature. To overcome limitations in specificity, several other functional MRI parameters have been investigated and the application of these combined parameters is defined as multiparametric MRI (mpMRI) of the breast. MpMRI of the breast can be performed at different field strengths (1.5–7 T) and includes both established (diffusion-weighted imaging, MR spectroscopic imaging) and novel MRI parameters (sodium imaging, chemical exchange saturation transfer imaging, blood oxygen level-dependent MRI), as well as hybrid imaging with positron emission tomography (PET)/MRI and different radiotracers. Available data suggest that multiparametric imaging using different functional MRI and PET parameters can provide detailed information about the underlying oncogenic processes of cancer development and progression and can provide additional specificity. This article will review the current and emerging functional parameters for mpMRI of the breast for improved diagnostic accuracy in breast cancer. PMID:27805423

Automatic Denoising of Functional MRI Data: Combining Independent Component Analysis and Hierarchical Fusion of Classifiers

PubMed Central

Salimi-Khorshidi, Gholamreza; Douaud, Gwenaëlle; Beckmann, Christian F; Glasser, Matthew F; Griffanti, Ludovica; Smith, Stephen M

2014-01-01

Many sources of fluctuation contribute to the fMRI signal, and this makes identifying the effects that are truly related to the underlying neuronal activity difficult. Independent component analysis (ICA) - one of the most widely used techniques for the exploratory analysis of fMRI data - has shown to be a powerful technique in identifying various sources of neuronally-related and artefactual fluctuation in fMRI data (both with the application of external stimuli and with the subject “at rest”). ICA decomposes fMRI data into patterns of activity (a set of spatial maps and their corresponding time series) that are statistically independent and add linearly to explain voxel-wise time series. Given the set of ICA components, if the components representing “signal” (brain activity) can be distinguished form the “noise” components (effects of motion, non-neuronal physiology, scanner artefacts and other nuisance sources), the latter can then be removed from the data, providing an effective cleanup of structured noise. Manual classification of components is labour intensive and requires expertise; hence, a fully automatic noise detection algorithm that can reliably detect various types of noise sources (in both task and resting fMRI) is desirable. In this paper, we introduce FIX (“FMRIB’s ICA-based X-noiseifier”), which provides an automatic solution for denoising fMRI data via accurate classification of ICA components. For each ICA component FIX generates a large number of distinct spatial and temporal features, each describing a different aspect of the data (e.g., what proportion of temporal fluctuations are at high frequencies). The set of features is then fed into a multi-level classifier (built around several different Classifiers). Once trained through the hand-classification of a sufficient number of training datasets, the classifier can then automatically classify new datasets. The noise components can then be subtracted from (or regressed out of) the original data, to provide automated cleanup. On conventional resting-state fMRI (rfMRI) single-run datasets, FIX achieved about 95% overall accuracy. On high-quality rfMRI data from the Human Connectome Project, FIX achieves over 99% classification accuracy, and as a result is being used in the default rfMRI processing pipeline for generating HCP connectomes. FIX is publicly available as a plugin for FSL. PMID:24389422

Dictionary learning and time sparsity in dynamic MRI.

PubMed

Caballero, Jose; Rueckert, Daniel; Hajnal, Joseph V

2012-01-01

Sparse representation methods have been shown to tackle adequately the inherent speed limits of magnetic resonance imaging (MRI) acquisition. Recently, learning-based techniques have been used to further accelerate the acquisition of 2D MRI. The extension of such algorithms to dynamic MRI (dMRI) requires careful examination of the signal sparsity distribution among the different dimensions of the data. Notably, the potential of temporal gradient (TG) sparsity in dMRI has not yet been explored. In this paper, a novel method for the acceleration of cardiac dMRI is presented which investigates the potential benefits of enforcing sparsity constraints on patch-based learned dictionaries and TG at the same time. We show that an algorithm exploiting sparsity on these two domains can outperform previous sparse reconstruction techniques.

Functional Imaging for Prostate Cancer: Therapeutic Implications

PubMed Central

Aparici, Carina Mari; Seo, Youngho

2012-01-01

Functional radionuclide imaging modalities, now commonly combined with anatomical imaging modalities CT or MRI (SPECT/CT, PET/CT, and PET/MRI) are promising tools for the management of prostate cancer particularly for therapeutic implications. Sensitive detection capability of prostate cancer using these imaging modalities is one issue; however, the treatment of prostate cancer using the information that can be obtained from functional radionuclide imaging techniques is another challenging area. There are not many SPECT or PET radiotracers that can cover the full spectrum of the management of prostate cancer from initial detection, to staging, prognosis predictor, and all the way to treatment response assessment. However, when used appropriately, the information from functional radionuclide imaging improves, and sometimes significantly changes, the whole course of the cancer management. The limitations of using SPECT and PET radiotracers with regards to therapeutic implications are not so much different from their limitations solely for the task of detecting prostate cancer; however, the specific imaging target and how this target is reliably imaged by SPECT and PET can potentially make significant impact in the treatment of prostate cancer. Finally, while the localized prostate cancer is considered manageable, there is still significant need for improvement in noninvasive imaging of metastatic prostate cancer, in treatment guidance, and in response assessment from functional imaging including radionuclide-based techniques. In this review article, we present the rationale of using functional radionuclide imaging and the therapeutic implications for each of radionuclide imaging agent that have been studied in human subjects. PMID:22840598

Dynamic fMRI of a decision-making task

NASA Astrophysics Data System (ADS)

Singh, Manbir; Sungkarat, Witaya

2008-03-01

A novel fMRI technique has been developed to capture the dynamics of the evolution of brain activity during complex tasks such as those designed to evaluate the neural basis of decision-making under different situations. A task called the Iowa Gambling Task was used as an example. Six normal human volunteers were studied. The task was presented inside a 3T MRI and a dynamic fMRI study of the approximately 2s period between the beginning and end of the decision-making period was conducted by employing a series of reference functions, separated by 200 ms, designed to capture activation at different time-points within this period. As decision-making culminates with a button-press, the timing of the button press was chosen as the reference (t=0) and corresponding reference functions were shifted backward in steps of 200ms from this point up to the time when motor activity from the previous button press became predominant. SPM was used to realign, high-pass filter (cutoff 200s), normalize to the Montreal Neurological Institute (MNI) Template using a 12 parameter affine/non-linear transformation, 8mm Gaussian smoothing, and event-related General Linear Model analysis for each of the shifted reference functions. The t-score of each activated voxel was then examined to find its peaking time. A random effect analysis (p<0.05) showed prefrontal, parietal and bi-lateral hippocampal activation peaking at different times during the decision making period in the n=6 group study.

Multiparametric or practical quantitative liver MRI: towards millisecond, fat fraction, kilopascal and function era.

PubMed

Unal, Emre; Idilman, Ilkay Sedakat; Karçaaltıncaba, Muşturay

2017-02-01

New advances in liver magnetic resonance imaging (MRI) may enable diagnosis of unseen pathologies by conventional techniques. Normal T1 (550-620 ms for 1.5 T and 700-850 ms for 3 T), T2, T2* (>20 ms), T1rho (40-50 ms) mapping, proton density fat fraction (PDFF) (≤5%) and stiffness (2-3kPa) values can enable differentiation of a normal liver from chronic liver and diffuse diseases. Gd-EOB-DTPA can enable assessment of liver function by using postcontrast hepatobiliary phase or T1 reduction rate (normally above 60%). T1 mapping can be important for the assessment of fibrosis, amyloidosis and copper overload. T1rho mapping is promising for the assessment of liver collagen deposition. PDFF can allow objective treatment assessment in NAFLD and NASH patients. T2 and T2* are used for iron overload determination. MR fingerprinting may enable single slice acquisition and easy implementation of multiparametric MRI and follow-up of patients. Areas covered: T1, T2, T2*, PDFF and stiffness, diffusion weighted imaging, intravoxel incoherent motion imaging (ADC, D, D* and f values) and function analysis are reviewed. Expert commentary: Multiparametric MRI can enable biopsyless diagnosis and more objective staging of diffuse liver disease, cirrhosis and predisposing diseases. A comprehensive approach is needed to understand and overcome the effects of iron, fat, fibrosis, edema, inflammation and copper on MR relaxometry values in diffuse liver disease.

Symmetric Positive 4th Order Tensors & Their Estimation from Diffusion Weighted MRI⋆

PubMed Central

Barmpoutis, Angelos; Jian, Bing; Vemuri, Baba C.; Shepherd, Timothy M.

2009-01-01

In Diffusion Weighted Magnetic Resonance Image (DW-MRI) processing a 2nd order tensor has been commonly used to approximate the diffusivity function at each lattice point of the DW-MRI data. It is now well known that this 2nd-order approximation fails to approximate complex local tissue structures, such as fibers crossings. In this paper we employ a 4th order symmetric positive semi-definite (PSD) tensor approximation to represent the diffusivity function and present a novel technique to estimate these tensors from the DW-MRI data guaranteeing the PSD property. There have been several published articles in literature on higher order tensor approximations of the diffusivity function but none of them guarantee the positive semi-definite constraint, which is a fundamental constraint since negative values of the diffusivity coefficients are not meaningful. In our methods, we parameterize the 4th order tensors as a sum of squares of quadratic forms by using the so called Gram matrix method from linear algebra and its relation to the Hilbert’s theorem on ternary quartics. This parametric representation is then used in a nonlinear-least squares formulation to estimate the PSD tensors of order 4 from the data. We define a metric for the higher-order tensors and employ it for regularization across the lattice. Finally, performance of this model is depicted on synthetic data as well as real DW-MRI from an isolated rat hippocampus. PMID:17633709

4D tumor centroid tracking using orthogonal 2D dynamic MRI: Implications for radiotherapy planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tryggestad, Erik; Flammang, Aaron; Shea, Steven M.

2013-09-15

Purpose: Current pretreatment, 4D imaging techniques are suboptimal in that they sample breathing motion over a very limited “snapshot” in time. Heretofore, long-duration, 4D motion characterization for radiotherapy planning, margin optimization, and validation have been impractical for safety reasons, requiring invasive markers imaged under x-ray fluoroscopy. To characterize 3D tumor motion and associated variability over durations more consistent with treatments, the authors have developed a practical dynamic MRI (dMRI) technique employing two orthogonal planes acquired in a continuous, interleaved fashion.Methods: 2D balanced steady-state free precession MRI was acquired continuously over 9–14 min at approximately 4 Hz in three healthy volunteersmore » using a commercial 1.5 T system; alternating orthogonal imaging planes (sagittal, coronal, sagittal, etc.) were employed. The 2D in-plane pixel resolution was 2 × 2 mm{sup 2} with a 5 mm slice profile. Simultaneous with image acquisition, the authors monitored a 1D surrogate respiratory signal using a device available with the MRI system. 2D template matching-based anatomic feature registration, or tracking, was performed independently in each orientation. 4D feature tracking at the raw frame rate was derived using spline interpolation.Results: Tracking vascular features in the lung for two volunteers and pancreatic features in one volunteer, the authors have successfully demonstrated this method. Registration error, defined here as the difference between the sagittal and coronal tracking result in the SI direction, ranged from 0.7 to 1.6 mm (1σ) which was less than the acquired image resolution. Although the healthy volunteers were instructed to relax and breathe normally, significantly variable respiration was observed. To demonstrate potential applications of this technique, the authors subsequently explored the intrafraction stability of hypothetical tumoral internal target volumes and 3D spatial probability distribution functions. The surrogate respiratory information allowed the authors to show how this technique can be used to study correlations between internal and external (surrogate) information over these prolonged durations. However, compared against the gold standard of the time stamps in the dMRI frames, the temporal synchronization of the surrogate 1D respiratory information was shown to be likely unreliable.Conclusions: The authors have established viability of a novel and practical pretreatment, 4D tumor centroid tracking method employing a commercially available dynamic MRI sequence. Further developments from the vendor are likely needed to provide a reliably synchronized surrogate 1D respiratory signal, which will likely broaden the utility of this method in the pretreatment radiotherapy planning context.« less

TH-EF-BRA-06: A Novel Retrospective 3D K-Space Sorting 4D-MRI Technique Using a Radial K-Space Acquisition MRI Sequence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Y; Subashi, E; Yin, F

Purpose: Current retrospective 4D-MRI provides superior tumor-to-tissue contrast and accurate respiratory motion information for radiotherapy motion management. The developed 4D-MRI techniques based on 2D-MRI image sorting require a high frame-rate of the MR sequences. However, several MRI sequences provide excellent image quality but have low frame-rate. This study aims at developing a novel retrospective 3D k-space sorting 4D-MRI technique using radial k-space acquisition MRI sequences to improve 4D-MRI image quality and temporal-resolution for imaging irregular organ/tumor respiratory motion. Methods: The method is based on a RF-spoiled, steady-state, gradient-recalled sequence with minimal echo time. A 3D radial k-space data acquisition trajectorymore » was used for sampling the datasets. Each radial spoke readout data line starts from the 3D center of Field-of-View. Respiratory signal can be extracted from the k-space center data point of each spoke. The spoke data was sorted based on its self-synchronized respiratory signal using phase sorting. Subsequently, 3D reconstruction was conducted to generate the time-resolved 4D-MRI images. As a feasibility study, this technique was implemented on a digital human phantom XCAT. The respiratory motion was controlled by an irregular motion profile. To validate using k-space center data as a respiratory surrogate, we compared it with the XCAT input controlling breathing profile. Tumor motion trajectories measured on reconstructed 4D-MRI were compared to the average input trajectory. The mean absolute amplitude difference (D) was calculated. Results: The signal extracted from k-space center data matches well with the input controlling respiratory profile of XCAT. The relative amplitude error was 8.6% and the relative phase error was 3.5%. XCAT 4D-MRI demonstrated a clear motion pattern with little serrated artifacts. D of tumor trajectories was 0.21mm, 0.23mm and 0.23mm in SI, AP and ML directions, respectively. Conclusion: A novel retrospective 3D k-space sorting 4D-MRI technique has been developed and evaluated on human digital phantom. NIH (1R21CA165384-01A1)« less

Structural and Functional Magnetic Resonance Imaging of the Cerebellum: Considerations for Assessing Cerebellar Ataxias.

PubMed

Deistung, Andreas; Stefanescu, Maria R; Ernst, Thomas M; Schlamann, Marc; Ladd, Mark E; Reichenbach, Jürgen R; Timmann, Dagmar

2016-02-01

Magnetic resonance imaging (MRI) of the brain is of high interest for diagnosing and understanding degenerative ataxias. Here, we present state-of-the-art MRI methods to characterize structural alterations of the cerebellum and introduce initial experiments to show abnormalities in the cerebellar nuclei. Clinically, T1-weighted MR images are used to assess atrophy of the cerebellar cortex, the brainstem, and the spinal cord, whereas T2-weighted and PD-weighted images are typically employed to depict potential white matter lesions that may be associated with certain types of ataxias. More recently, attention has also focused on the characterization of the cerebellar nuclei, which are discernible on spatially highly resolved iron-sensitive MR images due to their relatively high iron content, including T2 (*)-weighted images, susceptibility-weighted images (SWI), effective transverse relaxation rate (R2 (*)) maps, and quantitative susceptibility maps (QSM). Among these iron-sensitive techniques, QSM reveals the best contrast between cerebellar nuclei and their surroundings. In particular, the gyrification of the dentate nuclei is prominently depicted, even at the clinically widely available field strength of 3 T. The linear relationship between magnetic susceptibility and local iron content allows for determination of iron deposition in cerebellar nuclei non-invasively. The increased signal-to-noise ratio of ultrahigh-field MRI (B0 ≥ 7 T) and advances in spatial normalization methods enable functional MRI (fMRI) at the level of the cerebellar cortex and cerebellar nuclei. Data from initial fMRI studies are presented in three common forms of hereditary ataxias (Friedreich's ataxia, spinocerebellar ataxia type 3, and spinocerebellar ataxia type 6). Characteristic changes in the fMRI signal are discussed in the light of histopathological data and current knowledge of the underlying physiology of the fMRI signal in the cerebellum.