Physiological basis and image processing in functional magnetic resonance imaging: Neuronal and motor activity in brain

Functional magnetic resonance imaging (fMRI) is recently developing as imaging modality used for mapping hemodynamics of neuronal and motor event related tissue blood oxygen level dependence (BOLD) in terms of brain activation. Image processing is performed by segmentation and registration methods. Segmentation algorithms provide brain surface-based analysis, automated anatomical labeling of cortical fields in magnetic resonance data sets based on oxygen metabolic state. Registration algorithms provide geometric features using two or more imaging modalities to assure clinically useful neuronal and motor information of brain activation. This review article summarizes the physiological basis of fMRI signal, its origin, contrast enhancement, physical factors, anatomical labeling by segmentation, registration approaches with examples of visual and motor activity in brain. Latest developments are reviewed for clinical applications of fMRI along with other different neurophysiological and imaging modalities

Assessment of White Matter Hyperintensity, Cerebral Blood Flow, and Cerebral Oxygenation in Older Subjects Stratified by Cerebrovascular Risk

Objective: Cerebrovascular disease (CVD) is the fifth most common cause of mortality in the United States. Diagnosis of CVD at an early stage is critical for optimal intervention designed to prevent ongoing and future brain injury. CVD is commonly associated with abnormalities of the cerebral microvasculature leading to tissue dysfunction, neuronal injury and death, and resultant clinical symptoms, which in turn, further impacts cerebral autoregulation (CA). This series of studies aims to test the hypothesis that white matter hyperintensities (WMH) and cerebral hemodynamics (quantified by magnetic resonance imaging (MRI) and an by innovative hybrid near-infrared diffuse optical instrument) can be used as biomarkers to distinguish cognitively healthy older subjects with high or low risk for developing CVD. Methods: Using functional MRI, WMH and cerebral blood flow (CBF) were quantified in 26 cognitively healthy older subjects (age: 77.8 ± 6.8 years). In a follow-up study, significant variability in WMH quantification methodology was addressed, with sources of variability identified in selecting image center of gravity, software compatibility, thresholding techniques, and manual editing procedures. Accordingly, post-acquisition processing methods were optimized to develop a standardized protocol with less than 0.5% inter-rater variance. Using a novel laboratory-made hybrid near-infrared spectroscopy/diffuse correlation spectroscopy (NIRS/DCS) and a finger plethysmograph, low-frequency oscillations (LFOs) of CBF, cerebral oxygenation, and main arterial pressure (MAP) were simultaneously measured before, during, and after 70° head-up-tilting (HUT). Gains (associated with CAs) to magnify LFOs were determined by transfer function analyses with MAP as the input and cerebral hemodynamic parameters as the outputs. In a follow-up study, a fast software correlator for DCS and a parallel detection technique for NIRS/DCS were adapted to improve the sampling rate of hybrid optical measurements. In addition, a new DCS probe was developed to measure CBF at the occipital lobe, which represents a novel application of the NIRS/DCS technique. Results: MRI measurements demonstrate that deep WMH (dWMH) and periventricular WMH (pWMH) volumetric measures are associated with reduced regional cortical CBF in patients at high-risk of CVD. Moreover, CBF in white matter (WM) was reduced in regions demonstrating both pWMH and dWMHs. NIRS/DCS optical measurements demonstrate that at resting baseline, LFO gains in the high-risk group were relatively lower compared to the low-risk group. The lower baseline gains in the high-risk group may be attributed to compensatory mechanisms that allow the maintenance of a stronger steady-state CA. However, HUT resulted in smaller gain reductions in the high-risk group compared to the low-risk group, suggesting weaker dynamic CA in association with increased CVD risks. A noteworthy finding in these experiments was that CVD risk more strongly influenced CBF than cerebral oxygenation. Conclusions: Regional WMH volumes, cortical and WM CBF values, and LFO gains of cerebral hemodynamics demonstrate specific associations with CA and may serve as important potential biomarkers for early diagnosis of CVD. The high spatial resolution, large penetration depth, and variety of imaging-sequences afforded by MRI make it an appealing imaging modality for evaluation of CVD, although MRI is costly, time-limited, and requires transfer of subjects from bed to imaging facility. In contrast, low-cost, portable, mobile diffuse optical technologies provide a complementary alternative for early screening of CVD, that can further allow continuous monitoring of disease attenuation or progression at the subject’s bedside. Thus, development of both methodologies is essential for progress in our future understanding of CVD as a major contributor to the morbidity and mortality associated with CVD today

Brain segmentation using endogenous contrast mechanism using breath holding fMRI signal for tissue characterization

MRL has fast become the modality of choice for the analysis of the complexity of the human brain. MRJ is a non-invasive method and gives high spatial resolution maps of the brain with soft tissue contrast. Conventional MRI technique modified to be used to image the functionality at high temporal resolution is known as fMRI. In fMRI the BOLD signal we measure is the hemodynamic response to neuronal and vascular changes at rest or in response to a stimulus where the various tissue types will have a different response. While fMRI has been traditionally been used to detect and identify eloquent regions of the cortex corresponding to specific tasks/stimulus, a number of groups have also used tMRI to study cerebrovascular changes and its consequence on the BOLD signal. A number of different perturbation methods including breath holding, hypercapnia, inhalation of various gas mixtures, and injection of acetozolamyde has been used to study spatio-temporal changes in the fMRI signal intensity. Spatiotemporal changes corresponding to changes in cerebral blood flow (CBF), cerebral blood volume (CBV), oxygen extraction fraction (OEF), and other physiological factors are then estimated and differences between diseased regions and healthy regions are then elucidated

Multiparametric Imaging and MR Image Texture Analysis in Brain Tumors

Discrimination of tumor from radiation injured (RI) tissues and differentiation of tumor types using noninvasive imaging is essential for guiding surgical and radiotherapy treatments are some of the challenges that clinicians face in the course of treatment of brain tumors. The first objective in this thesis was to develop a method to discriminate between glioblastoma tumor recurrences and radiation injury using multiparametric characterization of the tissue incorporating conventional magnetic resonance imaging signal intensities and diffusion tensor imaging parameters. Our results show significant correlations in the RI that was missing in the tumor regions. These correlations may aid in differentiating between tumor recurrence and RI. The second objective of was to investigate whether texture based image analysis of routine MR images would provide quantitative information that could be used to differentiate between glioblastoma and metastasis. Our results demonstrate that first-order texture feature of standard deviation and second-order texture features of entropy, inertia, homogeneity, and energy show significant differences between the two groups. The third objective was to investigate whether quantitative measurements of tumor size and appearance on MRI scans acquired prior to helical tomotherapy (HT) type whole brain radiotherapy with simultaneous infield boost treatment could be used to differentiate responder and non-responder patient groups. Our results demonstrated that smaller size lesions may respond better to this type of radiation therapy. Measures of appearance provided limited added value over measures of size for response prediction. Quantitative measurements of rim enhancement and core necrosis performed separately did not provide additional predictive value

Functional Magnetic Resonance Imaging

"Functional Magnetic Resonance Imaging - Advanced Neuroimaging Applications" is a concise book on applied methods of fMRI used in assessment of cognitive functions in brain and neuropsychological evaluation using motor-sensory activities, language, orthographic disabilities in children. The book will serve the purpose of applied neuropsychological evaluation methods in neuropsychological research projects, as well as relatively experienced psychologists and neuroscientists. Chapters are arranged in the order of basic concepts of fMRI and physiological basis of fMRI after event-related stimulus in first two chapters followed by new concepts of fMRI applied in constraint-induced movement therapy; reliability analysis; refractory SMA epilepsy; consciousness states; rule-guided behavioral analysis; orthographic frequency neighbor analysis for phonological activation; and quantitative multimodal spectroscopic fMRI to evaluate different neuropsychological states

Functional brain perfusion evaluation with Arterial Spin Labeling at 3 Tesla

Dissertation submitted in Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa for the degree of Master of Biomedical EngineeringBackground: The new clinically available arterial spin labelling (ASL) sequences present some advantages relatively to the commonly used blood oxygenation level dependent (BOLD) method for functional brain studies using magnetic resonance imaging (MRI), namely the fact of being potentially quantitative and more reproducible. Purpose: The main aim of this work was to evaluate the functional use of a commercial ASL sequence implemented on a 3 Tesla MRI system (Siemens, Verio) in the Imaging Department of Hospital da Luz. The first aim was to obtain a functional validation of this technique by comparison with the BOLD contrast, using a number of different approaches. The second aim was to accomplish perfusion quantification, by resolving some important quantification issues. Materials and Methods: Fifteen adult volunteers participated in a single functional imaging session using three different protocols: one using BOLD and two using ASL. The subjects performed a motor finger tapping task and the data analysis was performed using Siemens Neuro3D and FSL (FMRIB’s Software Library). The location and variability of the activated areas were analysed in MNI (Montereal Neurological Institute) standard space. Results: Topographic agreement between the activated regions obtained by BOLD and ASL was found. However, the results show that inter-subject variability and distance to the hand motor cortex were smaller when measured with ASL as compared with BOLD fMRI. Quantitative studies revealed that ASL allows the calculation of cerebral blood flow (CBF), both at baseline and upon functional activation. Conclusion: The results suggest that the functional imaging protocols using ASL produce comparable results to a conventional BOLD protocol, with the additional advantages of reduced inter-subject variability, better spatial specificity and quantification possibilities

Inferring Geodesic Cerebrovascular Graphs: Image Processing, Topological Alignment and Biomarkers Extraction

A vectorial representation of the vascular network that embodies quantitative features - location, direction, scale, and bifurcations - has many potential neuro-vascular applications. Patient-specific models support computer-assisted surgical procedures in neurovascular interventions, while analyses on multiple subjects are essential for group-level studies on which clinical prediction and therapeutic inference ultimately depend. This first motivated the development of a variety of methods to segment the cerebrovascular system. Nonetheless, a number of limitations, ranging from data-driven inhomogeneities, the anatomical intra- and inter-subject variability, the lack of exhaustive ground-truth, the need for operator-dependent processing pipelines, and the highly non-linear vascular domain, still make the automatic inference of the cerebrovascular topology an open problem. In this thesis, brain vessels’ topology is inferred by focusing on their connectedness. With a novel framework, the brain vasculature is recovered from 3D angiographies by solving a connectivity-optimised anisotropic level-set over a voxel-wise tensor field representing the orientation of the underlying vasculature. Assuming vessels joining by minimal paths, a connectivity paradigm is formulated to automatically determine the vascular topology as an over-connected geodesic graph. Ultimately, deep-brain vascular structures are extracted with geodesic minimum spanning trees. The inferred topologies are then aligned with similar ones for labelling and propagating information over a non-linear vectorial domain, where the branching pattern of a set of vessels transcends a subject-specific quantized grid. Using a multi-source embedding of a vascular graph, the pairwise registration of topologies is performed with the state-of-the-art graph matching techniques employed in computer vision. Functional biomarkers are determined over the neurovascular graphs with two complementary approaches. Efficient approximations of blood flow and pressure drop account for autoregulation and compensation mechanisms in the whole network in presence of perturbations, using lumped-parameters analog-equivalents from clinical angiographies. Also, a localised NURBS-based parametrisation of bifurcations is introduced to model fluid-solid interactions by means of hemodynamic simulations using an isogeometric analysis framework, where both geometry and solution profile at the interface share the same homogeneous domain. Experimental results on synthetic and clinical angiographies validated the proposed formulations. Perspectives and future works are discussed for the group-wise alignment of cerebrovascular topologies over a population, towards defining cerebrovascular atlases, and for further topological optimisation strategies and risk prediction models for therapeutic inference. Most of the algorithms presented in this work are available as part of the open-source package VTrails

Investigation of Flow Disturbances and Multi-Directional Wall Shear Stress in the Stenosed Carotid Artery Bifurcation Using Particle Image Velocimetry

Hemodynamics and shear forces are associated with pathological changes in the vascular wall and its function, resulting in the focal development of atherosclerosis. Flow complexities that develop in the presence of established plaques create environments favourable to thrombosis formation and potentially plaque rupture leading to stroke. The carotid artery bifurcation is a common site of atherosclerosis development. Recently, the multi-directional nature of shear stress acting on the endothelial layer has been highlighted as a risk factor for atherogenesis, emphasizing the need for accurate measurements of shear stress magnitude as well direction. In the absence of comprehensive patient specific datasets numerical simulations of hemodynamics are limited by modeling assumptions. The objective of this thesis was to investigate the relative contributions of various factors - including geometry, rheology, pulsatility, and compliance – towards the development of disturbed flow and multi-directional wall shear stress (WSS) parameters related to the development of atherosclerosis An experimental stereoscopic particle image velocimetry (PIV) system was used to measure instantaneous full-field velocity in idealized asymmetrically stenosed carotid artery bifurcation models, enabling the extraction of bulk flow features and turbulence intensity (TI). The velocity data was combined with wall location information segmented from micro computed tomography (CT) to obtain phase-averaged maps of WSS magnitude and direction. A comparison between Newtonian and non-Newtonian blood-analogue fluids demonstrated that the conventional Newtonian viscosity assumption underestimates WSS magnitude while overestimating TI. Studies incorporating varying waveform pulsatility demonstrated that the levels of TI and oscillatory shear index (OSI) depend on the waveform amplitude in addition to the degree of vessel constriction. Local compliance resulted in a dampening of disturbed flow due to volumetric capacity of the upstream vessel, however wall tracking had a negligible effect on WSS prediction. While the degree of stenosis severity was found to have a dominant effect on local hemodynamics, comparable relative differences in metrics of flow and WSS disturbances were found due to viscosity model, waveform pulsatility and local vessel compliance