Magnetic Field Distribution and Signal Decay in Functional MRI in Very High Fields (up to 9.4 T) Using Monte Carlo Diffusion Modeling

Extravascular signal decay rate R2 or R2∗ as a function of blood oxygenation, geometry, and field strength was calculated using a Monte Carlo (MC) algorithm for a wider parameter range than hitherto by others. The relaxation rates of gradient-recalled-echo (GRE) and Hahn-spin-echo (HSE) imaging in the presence of blood vessels (ranging from capillaries to veins) have been computed for a wide range of field strengths up to 9.4T and 50% blood deoxygenation. The maximum HSE decay was found to be shifted to lower radii in higher compared to lower field strengths. For GRE, however, the relaxation rate was greatest for large vessels at any field strength. In addition, assessments of computational reliability have been carried out by investigating the influence of the time step, the Monte Carlo step procedure, boundary conditions, the number of angles between the vessel and the exterior field B0, the influence of neighboring vessels having the same orientation as the central vessel, and the number of proton spins. The results were compared with those obtained from a field distribution of the vessel computed by an analytic formula describing the field distribution of an ideal object (an infinitely long cylinder). It was found that the time step is not critical for values equal to or lower than 200 microseconds. The choice of the MC step procedure (three-dimensional Gaussian diffusion, constant one- or three-dimensional diffusion step) also failed to influence the results significantly; in contrast, the free boundary conditions, as well as taking too few angles into account, did introduce errors. Next neighbor vessels with the same orientation as the main vessel did not contribute significantly to signal decay. The total number of particles simulated was also found to play a minor role in computing R2/ R2∗

Dependence of the magnetic resonance signal on the magnetic susceptibility of blood studied with models based on real microvascular networks

PURPOSE: The primary goal of this study was to estimate the value of beta , the exponent in the power law relating changes of the transverse relaxation rate and intra-extravascular local magnetic susceptibility differences as Delta R 2 * proportional, variant ( Delta chi ) beta. The secondary objective was to evaluate any differences that might exist in the value of beta obtained using a deoxyhemoglobin-weighted Delta chi distribution versus a constant Delta chi distribution assumed in earlier computations. The third objective was to estimate the value of beta that is relevant for methods based on susceptibility contrast agents with a concentration of Delta chi higher than that used for BOLD fMRI calculations. METHODS: Our recently developed model of real microvascular anatomical networks is used to extend the original simplified Monte-Carlo simulations to compute beta from the first principles. RESULTS: Our results show that beta = 1 for most BOLD fMRI measurements of real vascular networks, as opposed to earlier predictions of beta = 1 .5 using uniform Delta chi distributions. For perfusion or fMRI methods based on contrast agents, which generate larger values for Delta chi , beta = 1 for B 0 </= 9.4 T, whereas at 14 T beta can drop below 1 and the variation across subjects is large, indicating that a lower concentration of contrast agent with a lower value of Delta chi is desired for experiments at high B0. CONCLUSION: These results improve our understanding of the relationship between R2 (*) and the underlying microvascular properties. The findings will help to infer the cerebral metabolic rate of oxygen and cerebral blood volume from BOLD and perfusion MRI, respectively.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6435380/Accepted manuscrip

Biophysical Simulation of the Functional Magnetic Resonance Signal Formation in Realistic Neurovascular Networks

The human brain is one of the most complex living systems. The scientific study of the brain’s anatomy and neurophysiology are fundamental to understand the basic principles of mental processes such as cognition and behavior. For this reason, in the endeavor to investigate the underlying neural mechanisms that drive these processes, the neuroscientific research has employed all the available technological resources and methodologies from different fields like anatomy, histology, electrophysiology, neurobiology, etc. Likewise, great advances have been provided by neuroimaging techniques such as PET and MRI, in order to comprehend the neural activity and the metabolic reactions that occur in the central nervous system. In particular, functional MRI provides an indirect measurement of the neural activity throughout local hemodynamic changes, thus related to the neurovascular coupling, as a response to a particular task-evoked stimulus. This MR signal behavior modulated by oxygenation level changes is better known as the BOLD signal. Although progress has been done in order to understand the BOLD signal change under well-defined nonrealistic vascular geometries, on the other hand, realistic neurovascular networks might give valuable information to resolve the influence on the BOLD signal evolution from a particular vascular tissue and specific hemodynamic responses. In order to extend the analysis of the BOLD signal change obtained by randomly oriented cylinders and spheres, throughout this thesis, the geometrical features of a realistic neurovascular network as well as the biophysical effects related to the hemodynamic response and thermal motion were investigated by means of Monte Carlo simulations in pursuance to resolve the functional MR signal formation. In the Introduction of this thesis, I made a small recapitulation on the MR physics and spin dynamics; magnetic susceptibility and thermal motion as crucial modulators of the BOLD signal behavior. In addition, a summary of the problem and the aims of the project. Therefore, I described the importance of the use of the Monte Carlo method to calculate the MR signal under nonrealistic vascular models. I summarized the seminal analytical and numerical results that provide important insights to characterize the main parameters that influence the MR signal formation. Finally, I described the importance of the use of realistic neurovascular structures in order to disentangle the specific tissue contribution and the direct impact on the BOLD signal change

Quantifying the Microvascular Origin of BOLD-fMRI from First Principles with Two-Photon Microscopy and an Oxygen-Sensitive Nanoprobe

The blood oxygenation level-dependent (BOLD) contrast is widely used in functional magnetic resonance imaging (fMRI) studies aimed at investigating neuronal activity. However, the BOLD signal reflects changes in blood volume and oxygenation rather than neuronal activity per se. Therefore, understanding the transformation of microscopic vascular behavior into macroscopic BOLD signals is at the foundation of physiologically informed noninvasive neuroimaging. Here, we use oxygen-sensitive two-photon microscopy to measure the BOLD-relevant microvascular physiology occurring within a typical rodent fMRI voxel and predict the BOLD signal from first principles using those measurements. The predictive power of the approach is illustrated by quantifying variations in the BOLD signal induced by the morphological folding of the human cortex. This framework is then used to quantify the contribution of individual vascular compartments and other factors to the BOLD signal for different magnet strengths and pulse sequences.National Institutes of Health (U.S.) (Grant P41RR14075)National Institutes of Health (U.S.) (Grant R01NS067050)National Institutes of Health (U.S.) (Grant R01NS057198)National Institutes of Health (U.S.) (Grant R01EB000790)American Heart Association (Grant 11SDG7600037)Advanced Multimodal NeuroImaging Training Program (R90DA023427

A realistic vascular model for BOLD signal up to 16.4 T

The blood oxygenation level-dependent (BOLD) signal using functional magnetic resonance imaging (fMRI) is currently the most popular imaging method to study brain function non-invasively. The sensitivity of the BOLD signal to different types of MRI sequences and vessel sizes is currently under investigation [1]. Gradient echo (GRE) sequences are known to be sensitive to larger vessels (venules and veins), whereas spin-echo (SE) sequences are generally more sensitive to smaller vessels (venules and capillaries), especially at high magnetic field strength [2, 3]. However, the widely used single vessel model is only an approximation to the realistic vascular distribution. Realistic vascular models have been proposed by Marques and Bowtell [4] and, recently, by Chen et al.[5]. We herein present a realistic vascular model (RVM) where diffusion is accounted for by a Monte-Carlo random walk

On Nature of the Gradient Echo MR Signal and Its Application to Monitoring Multiple Sclerosis

Multiple Sclerosis is a common disease, affecting 2.5 million people world-wide. The clinical course is heterogeneous, ranging from benign disease in which patients live an almost normal life to severe and devastating disease that may shorten life. Despite much research, a fully effective treatment for MS is still unavailable and diagnostic techniques for monitoring MS disease evolution are much needed. As a non-invasive tool, Magnetic resonance imaging: MRI) plays a key role in MS diagnosis. Numerous MRI techniques have been proposed over the years. Among most widely used are conventional T1-weighted: T1W), T2-weighted: T2W) and FLuid Attenuated Inversion Recovery: FLAIR) imaging techniques. However their results do not correlate well with neurological findings. Several advanced MRI techniques are also used as research tools to study MS. Among them are magnetization transfer contrast imaging: MT), MR spectroscopy: MRS), and Diffusion Tensor Imaging: DTI) but they have not penetrated to clinical arena yet. Gradient Echo Plural Contrast Imaging: GEPCI) developed in our laboratory is a post processing technique based on multi-echo gradient echo sequence. It offers basic contrasts such as T1W images and T2* maps obtained from magnitude of GEPCI signal, and frequency maps obtained from GEPCI signal phase. Phase information of Gradient Echo MR signal has recently attracted much attention of the MR community since it manifests superior gray matter/ white matter contrast and sub-cortical contrast, especially at high field: 7 T) MRI. However the nature of this contrast is under intense debates. Our group proposed a theoretical framework - Generalized Lorentzian Approach - which emphasizes that, contrary to a common-sense intuition, phase contrast in brain tissue is not directly proportional to the tissue bulk magnetic susceptibility but is rather determined by the geometrical arrangement of brain tissue components: lipids, proteins, iron, etc.) at the cellular and sub-cellular levels - brain tissue magnetic architecture . In this thesis we have provide first direct prove of this hypothesis by measurement of phase contrast in isolated optic nerve. We have also provided first quantitative measurements of the contribution to phase contrast from the water-macromolecule exchange effect. Based on our measurement in protein solutions, we demonstrated that the magnitude of exchange effect is 1/2 of susceptibility effect and to the opposite sign. GEPCI technique also offers a scoring method for monitoring Multiple Sclerosis based on the quantitative T2* maps generated from magnitude information of gradient echo signal. Herein we demonstrated a strong agreement between GEPCI quantitative scores and traditional lesion load assessment. We also established a correlation between GEPCI scores and clinical tests for MS patients. We showed that this correlation is stronger than that found between traditional lesion load and clinical tests. Such studies will be carried out for longer period and on MS subjects with broader range of disease severity in the future. We have also demonstrated that the magnitude and phase information available from GEPCI experiment can be combined in multiple ways to generate novel contrasts that can help with visualization of neurological brain abnormalities beyond Multiple Sclerosis. In summary, in this study, we 1) propose novel contrasts for GEPCI from its basic images; 2) investigate the biophysical mechanisms behind phase contrast; 3) evaluate the benefits of quantitative T2* map offered by GEPCI in monitoring disease of Multiple Sclerosis by comparing GEPCI results to clinical standard techniques; 4) apply our theoretical framework - Generalized Lorentzian Approach - to better understand phase contrast in MS lesions

Approaches Toward Combining Positron Emission Tomography with Magnetic Resonance Imaging

Positron emission tomography (PET) and magnetic resonance imaging (MRI) provide complementary information, and there has been a great deal of research effort to combine these two modalities. A major engineering hurdle is that photomultiplier tubes (PMT), used in conventional PET detectors, are sensitive to magnetic field. This thesis explores the design considerations of different ways of combining small animal PMT-based PET systems with MRI through experimentation, modelling and Monte Carlo simulation. A proof-of-principle hybrid PET and field-cycled MRI system was built and the first multimodality images are shown. A Siemens Inveon PET was exposed to magnetic fields of different strengths and the performance is characterized as a function of field magnitude. The results of this experiment established external magnetic field limits and design studies are shown for wide range of approaches to combining the PET system with various configurations of field-cycled MRI and superconducting MRI systems. A sophisticated Monte Carlo PET simulation workflow based on the GATE toolkit was developed to model the Siemens Inveon PET. Simulated PET data were converted to the raw Siemens list-mode format and were processed and reconstructed using the same processing chain as the data measured on the actual scanner. A general GATE add-on was developed to rapidly generate attenuation correction sinograms using the precise detector geometry and attenuation coefficients built into the emission simulation. Emission simulations and the attenuation correction add-on were validated against measured data. Simulations were performed to study the impact of radiofrequency coil components on PET image quality and to test the suitability of various MR-compatible materials for a dual-modality animal bed

Topics in Steady-state MRI Sequences and RF Pulse Optimization.

Small-tip fast recovery (STFR) is a recently proposed rapid steady-state magnetic resonance imaging (MRI) sequence that has the potential to be an alternative to the popular balanced steady-state free precession (bSSFP) imaging sequence, since they have similar signal level and tissue contrast, but STFR has reduced banding artifacts. In this dissertation, an analytic equation of the steady-state signal for the unspoiled version of STFR is first derived. It is shown that unspoiled-STFR is less sensitive to the inaccuracy in excitation than the previous proposed spoiled-STFR. By combining unspoiled-STFR with jointly designed tip-down and tip-up pulses, a 3D STFR acquisition over 3-4 cm thick 3D ROI with single coil and short RF pulses (1.7 ms) is demonstrated. Then, it is demonstrated that STFR can reliably detect functional MRI signal and the contrast is driven mainly from intra-voxel dephasing, not diffusion, using Monte Carlo simulation, human experiments and test-retest reliability. Following that another version of STFR using a spectral pre-winding pulse instead of the spatially tailored pulse is investigated, leading to less T2* weighting, easier implementation. Multidimensional selective RF pulse is a key part for STFR and many other MRI applications. Two novel RF pulse optimization methods are proposed. First, a minimax formulation that directly controls the maximum excitation error, and an effective optimization algorithm using variable splitting and alternating direction method of multipliers (ADMM). The proposed method reduced the maximum excitation by more than half in all the testing cases. Second, a method that jointly optimizes the excitation k-space trajectory and RF pulse is proposed. The k-space trajectory is parametrized using 2nd-order B-splines, and an interior point algorithm is used to explicitly solve the constrained optimization. An effective initialization method is also suggested. The joint design reduced the NRMSE by more than 30 percent compared to existing methods in inner volume excitation and pre-phasing problem. Using the proposed joint design, rapid inner volume STFR imaging with a 4 ms excitation pulse with single transmit coil is demonstrated. Finally, a regularized Bloch-Siegert B1 map reconstruction method is presented that significantly reduces the noise in estimated B1 maps.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111514/1/sunhao_1.pd

Classification of breast malignancy using optimised advanced diffusion-weighted imaging : and surgical planning for breast tumour resection using MR-guided focused ultrasound

Intravoxel Incoherent Motion Imaging (IVIM) is a non-invasive MR-imaging technique that enables the measurement of cellularity and vascularity using diffusion-weighted (DW)-imaging. IVIM has been applied to various cancer types including breast cancer, and is becoming more popular but lacks standardisation. The quantitative parameters; diffusion, D, perfusion fraction, f, and pseudo micro capillary diffusion, D* are thought to be correlated with tumour physiognomies such as proliferation, angiogenesis and heterogeneity.In Part 1 of this thesis, an optimised clinical b-value protocol is produced using a robust statistical method. This optimised protocol and various fitting methodologies are investigated in healthy volunteers, and then the most precise approach is applied in a clinical trial in patients following diagnosis of breast cancer, before treatment, to correlate IVIM parameters with breast cancer grade, histological type and molecular subtype with statistically significant results supporting IVIM’s potential as a non-invasive biomarker for malignancy. Monte Carlo simulations support this clinical application, where real data mean squared errors due to SNR limitations lie within simulated errors. A computed DW-imaging program is also presented to produce better quality images than acquired high b-value images as an adjunct to the optimised IVIM protocol.In Part 2 of this thesis, MR-guided Focused Ultrasound (MRgFUS) is explored as a means to create a pre-surgical template of thermally induced palpable markers to enable a surgeon to resect occult lesions and potentially reduce positive tumour margin status and local recurrence after breast conserving surgery. A surrogate animal model with pseudo lesion is presented, as well as a clinical tool to plan spot markers around a lesion as seen on MRI