Advances in image acquisition and filtering for MRI neuroimaging at 7 tesla

Performing magnetic resonance imaging at high magnetic field strength promises many improvements over low fields that are of direct benefit in functional neuroimaging. This includes the possibility of improved signal-to-noise levels, and increased BOLD functional contrast and spatial specificity. However, human MRI at 7T and above suffers from unique engineering challenges that limit the achievable gains. In this thesis, three technological developments are introduced, all of which address separate issues associated with functional magnetic resonance neuroimaging at very high magnetic field strengths. First, the image homogeneity problem is addressed by investigating methods of RF shimming — modifying the excitation portion of the MRI experiment for use with multi-channel RF coils. It is demonstrated that in 2D MRI experiments, shimming on a slice-by slice basis allows utilization of an extra degree of freedom available from the slice dimension, resulting in significant gains in image homogeneity and reduced RF power requirements. After acceptable images are available, we move to address complications of high field imaging that manifest in the fMRI time series. In the second paper, the increased physiological noise present in BOLD time series at high field is addressed with a unique data-driven noise regressor scheme based upon information in the phase component of the MRI signal. It is demonstrated that this method identifies and removes a significant portion of physiological signals, and performs as good or better than other popular data driven methods that use only the magnitude signal information. Lastly, the BOLD phase signal is again leveraged to address the confounding role of veins in resting state BOLD fMRI experiments. The phase regressor technique (previously developed by Dr. Menon) is modified and applied to resting state fMRI to remove macro vascular contributions in the datasets, leading to changes in spatial extent and connectivity of common resting state networks on single subjects and at the group level

Effects of phase regression on high-resolution functional MRI of the primary visual cortex

High-resolution functional MRI studies have become a powerful tool to non-invasively probe the sub-millimeter functional organization of the human cortex. Advances in MR hardware, imaging techniques and sophisticated post-processing methods have allowed high resolution fMRI to be used in both the clinical and academic neurosciences. However, consensus within the community regarding the use of gradient echo (GE) or spin echo (SE) based acquisition remains largely divided. On one hand, GE provides a high temporal signal-to-noise ratio (tSNR) technique sensitive to both the macro- and micro-vascular signal while SE based methods are more specific to microvasculature but suffer from lower tSNR and specific absorption rate limitations, especially at high field and with short repetition times. Fortunately, the phase of the GE-EPI signal is sensitive to vessel size and this provides a potential avenue to reduce the macrovascular weighting of the signal (phase regression, Menon 2002). In order to determine the efficacy of this technique at high-resolution, phase regression was applied to GE-EPI timeseries and compared to SE-EPI to determine if GE-EPI\u27s specificity to the microvascular compartment improved. To do this, functional data was collected from seven subjects on a neuro-optimized 7 T system at 800 μm isotropic resolution with both GE-EPI and SE-EPI while observing an 8 Hz contrast reversing checkerboard. Phase data from the GE-EPI was used to create a microvasculature-weighted time series (GE-EPI-PR). Anatomical imaging (MP2RAGE) was also collected to allow for surface segmentation so that the functional results could be projected onto a surface. A multi-echo gradient echo sequence was collected and used to identify venous vasculature. The GE-EPI-PR surface activation maps showed a high qualitative similarity with SE-EPI and also produced laminar activity profiles similar to SE-EPI. When the GE-EPI and GE-EPI-PR distributions were compared to SE-EPI it was shown that GE-EPI-PR had similar distribution characteristics to SE-EPI (p \u3c 0.05) across the top 60% of cortex. Furthermore, it was shown that GE-EPI-PR has a higher contrast-to-noise ratio (0.5 ± 0.2, mean ± std. dev. across layers) than SE-EPI (0.27 ± 0.07) demonstrating the technique has higher sensitivity than SE-EPI. Taken together this evidence suggests phase regression is a useful method in low SNR studies such as high-resolution fMRI

Does higher sampling rate (multiband + SENSE) improve group statistics - An example from social neuroscience block design at 3T

Multiband (MB) or Simultaneous multi-slice (SMS) acquisition schemes allow the acquisition of MRI signals from more than one spatial coordinate at a time. Commercial availability has brought this technique within the reach of many neuroscientists and psychologists. Most early evaluation of the performance of MB acquisition employed resting state fMRI or the most basic tasks. In this study, we tested whether the advantages of using MB acquisition schemes generalize to group analyses using a cognitive task more representative of typical cognitive neuroscience applications. Twenty-three subjects were scanned on a Philips 3 ​T scanner using five sequences, up to eight-fold acceleration with MB-factors 1 to 4, SENSE factors up to 2 and corresponding TRs of 2.45s down to 0.63s, while they viewed (i) movie blocks showing complex actions with hand object interactions and (ii) control movie blocks without hand object interaction. Data were processed using a widely used analysis pipeline implemented in SPM12 including the unified segmentation and canonical HRF modelling. Using random effects group-level, voxel-wise analysis we found that all sequences were able to detect the basic action observation network known to be recruited by our task. The highest t-values were found for sequences with MB4 acceleration. For the MB1 sequence, a 50% bigger voxel volume was needed to reach comparable t-statistics. The group-level t-values for resting state networks (RSNs) were also highest for MB4 sequences. Here the MB1 sequence with larger voxel size did not perform comparable to the MB4 sequence. Altogether, we can thus recommend the use of MB4 (and SENSE 1.5 or 2) on a Philips scanner when aiming to perform group-level analyses using cognitive block design fMRI tasks and voxel sizes in the range of cortical thickness (e.g. 2.7 ​mm isotropic). While results will not be dramatically changed by the use of multiband, our results suggest that MB will bring a moderate but significant benefit

Calibrated BOLD using direct measurement of changes in venous oxygenation

Calibration of the BOLD signal is potentially of great value in providing a closer measure of the underlying changes in brain function related to neuronal activity than the BOLD signal alone, but current approaches rely on an assumed relationship between cerebral blood volume (CBV) and cerebral blood flow (CBF). This is poorly characterised in humans and does not reflect the predominantly venous nature of BOLD contrast, whilst this relationship may vary across brain regions and depend on the structure of the local vascular bed. This work demonstrates a new approach to BOLD calibration which does not require an assumption about the relationship between cerebral blood volume and cerebral blood flow. This method involves repeating the same stimulus both at normoxia and hyperoxia, using hyperoxic BOLD contrast to estimate the relative changes in venous blood oxygenation and venous CBV. To do this the effect of hyperoxia on venous blood oxygenation has to be calculated, which requires an estimate of basal oxygen extraction fraction, and this can be estimated from the phase as an alternative to using a literature estimate. Additional measurement of the relative change in CBF, combined with the blood oxygenation change can be used to calculate the relative change in CMRO2 due to the stimulus. CMRO2 changes of 18 ± 8% in response to a motor task were measured without requiring the assumption of a CBV/CBF coupling relationship, and are in agreement with previous approaches

Phase imaging for reducing macrovascular signal contributions in high-resolution fMRI

High resolution functional MRI allows for the investigation of neural activity within the cortical sheet. One consideration in high resolution fMRI is the choice of which sequence to use during imaging, as all methods come with sensitivity and specificity tradeoffs. The most used fMRI sequence is gradient-echo echo planar imaging (GE-EPI) which has the highest sensitivity but is not specific to microvasculature. GE-EPI results in a signal with pial vessel bias which increases complexity of performing studies targeted at structures within the cortex. This work seeks to explore the use of MRI phase signal as a macrovascular filter to correct this bias. First, an in-house phase combination method was designed and tested on the 7T MRI system. This method, the fitted SVD method, uses a low-resolution singular value decomposition and fitting to a polynomial basis to provide computationally efficient, phase sensitive, coil combination that is insensitive to motion. Second, a direct comparison of GE-EPI, GE-EPI with phase regression (GE-EPI-PR), and spin echo EPI (SE-EPI) was performed in humans completing a visual task. The GE-EPI-PR activation showed higher spatial similarity with SE-EPI than GE-EPI across the cortical surface. GE-EPI-PR produced a similar laminar profile to SE-EPI while maintaining a higher contrast-to-noise ratio across layers, making it a useful method in low SNR studies such as high-resolution fMRI. The final study extended this work to a resting state macaque experiment. Macaques are a common model for laminar fMRI as they allow for simultaneous imaging and electrophysiology. We hypothesized that phase regression could improve spatial specificity of the resting state data. Further analysis showed the phase data contained both system and respiratory artifacts which prevented the technique performing as expected under two physiological cleaning strategies. Future work will have to examine on-scanner physiology correction to obtain a phase timeseries without artifacts to allow for the phase regression technique to be used in macaques. This work demonstrates that phase regression reduces signal contributions from pial vessels and will improve specificity in human layer fMRI studies. This method can be completed easily with complex fMRI data which can be created using our fitted SVD method

Multiparametric measurement of cerebral physiology using calibrated fMRI

The ultimate goal of calibrated fMRI is the quantitative imaging of oxygen metabolism (CMRO2), and this has been the focus of numerous methods and approaches. However, one underappreciated aspect of this quest is that in the drive to measure CMRO2, many other physiological parameters of interest are often acquired along the way. This can significantly increase the value of the dataset, providing greater information that is clinically relevant, or detail that can disambiguate the cause of signal variations. This can also be somewhat of a double-edged sword: calibrated fMRI experiments combine multiple parameters into a physiological model that requires multiple steps, thereby providing more opportunity for error propagation and increasing the noise and error of the final derived values. As with all measurements, there is a trade-off between imaging time, spatial resolution, coverage, and accuracy. In this review, we provide a brief overview of the benefits and pitfalls of extracting multiparametric measurements of cerebral physiology through calibrated fMRI experiments

Expanding the role of functional mri in rehabilitation research

Functional magnetic resonance imaging (fMRI) based on blood oxygenation level dependent (BOLD) contrast has become a universal methodology in functional neuroimaging. However, the BOLD signal consists of a mix of physiological parameters and has relatively poor reproducibility. As fMRI becomes a prominent research tool for rehabilitation studies involving repeated measures of the human brain, more quantitative and stable fMRI contrasts are needed. This dissertation enhances quantitative measures to complement BOLD fMRI. These additional markers, cerebral blood flow (CBF) and cerebral blood volume (CBV) (and hence cerebral metabolic rate of oxygen (CMRO₂) modeling) are more specific imaging markers of neuronal activity than BOLD. The first aim of this dissertation assesses feasibility of complementing BOLD with quantitative fMRI measures in subjects with central visual impairment. Second, image acquisition and analysis are developed to enhance quantitative fMRI by quantifying CBV while simultaneously acquiring CBF and BOLD images. This aim seeks to relax assumptions related to existing methods that are not suitable for patient populations. Finally, CBF acquisition using a low-cost local labeling coil, which improves image quality, is combined with simultaneous acquisition of two types of traditional BOLD contrast. The demonstrated enhancement of CBF, CBV and CMRO₂measures can lead to better characterization of pathophysiology and treatment effects.Ph.D.Committee Chair: Hu, Xiaoping; Committee Member: Benkeser, Paul; Committee Member: Keilholz, Shella; Committee Member: Sathian, Krish; Committee Member: Schuchard, Ronal

Applicability of Quantitative Functional MRI Techniques for Studies of Brain Function at Ultra-High Magnetic Field

This thesis describes the development, implementation and application of various quantitative functional magnetic resonance imaging (fMRI) approaches at ultra-high magnetic field including the assessment with regards to applicability and reproducibility. Functional MRI (fMRI) commonly uses the blood oxygenation level dependent (BOLD) contrast to detect functionally induced changes in the oxy-deoxyhaemoglobin composition of blood which reflect cerebral neural activity. As these blood oxygenation changes do not only occur at the activation site but also downstream in the draining veins, the spatial specificity of the BOLD signal is limited. Therefore, the focus has moved towards more quantitative fMRI approaches such as arterial spin labelling (ASL), vascular space occupancy (VASO) or calibrated fMRI which measure quantifiable physiologically and physically relevant parameters such as cerebral blood flow (CBF), cerebral blood volume (CBV) or cerebral metabolic rate of oxygen (CMRO2), respectively. In this thesis a novel MRI technique was introduced which allowed the simultaneous acquisition of multiple physiological parameters in order to beneficially utilise their spatial and temporal characteristics. The advantages of ultra-high magnetic field were utilised to achieve higher signal-to-noise and contrast-to-noise ratios compared to lower field strengths. This technique was successfully used to study the spatial and temporal characteristics of CBV, CBF and BOLD in the visual cortex. This technique is the first one that allows simultaneous acquisition of CBV, CBF and BOLD weighted fMRI signals in the human brain at 7 Tesla. Additionally, this thesis presented a calibrated fMRI technique which allowed the quantitative estimation of changes in cerebral oxygen metabolism at ultra-high field. CMRO2 reflects the amount of thermodynamic work due to neural activity and is therefore a significant physical measure in neuroscience. The calibrated fMRI approach presented in this thesis was optimised for the use at ultra-high field by adjusting the MRI parameters as well as implementing a specifically designed radio-frequency (RF) pulse. A biophysical model was used to calibrate the fMRI data based on the simultaneous acquisition of BOLD and CBF weighted MRI signals during a gas-breathing challenge. The reproducibility was assessed across multiple brain regions and compared to that of various physiologically relevant parameters. The results indicate that the degree of intra-subject variation for calibrated fMRI is lower than for the classic BOLD contrast or ASL. Consequently, calibrated fMRI is a viable alternative to classic fMRI contrasts with regards to spatial specificity as well as functional reproducibility. This calibrated fMRI approach was also compared to a novel direct calibration technique which relies on complete venous oxygenation saturation during the calibration scan via a gas-breathing challenge. This thesis introduced several reliable quantitative fMRI approaches at 7 Tesla and the results presented are a step forward to the wider application of quantitative fMRI.:1 Introduction 3 2 Background to Functional Magnetic Resonance Imaging 7 2.1 Magnetic Resonance 7 2.1.1 Quantum Mechanics 7 2.1.2 The Classical Point of View 10 2.1.3 Radio Frequency Pulses 12 2.1.4 Relaxation Effects 13 2.1.5 The Bloch Equations 15 2.2 Magnetic Resonance Imaging 16 2.2.1 Data Acquisition 16 2.2.2 Image Formation 17 2.2.2.1 Slice Selection 17 2.2.2.2 Frequency Encoding 18 2.2.2.3 Phase Encoding 19 2.2.2.4 Mathematics of Image Formation 20 2.2.2.5 Signal Formation 22 2.3 Advanced Imaging Methods 24 2.3.1 Echo-Planar Imaging (EPI) 24 2.3.2 Partial Fourier Acquisition 25 2.3.3 Generalised Autocalibrating Partially Parallel Acquisition (GRAPPA) 25 2.3.4 Inversion Recovery (IR) 26 2.3.5 Adiabatic Inversion 26 2.3.5.1 Hyperbolic Secant (HS) RF pulses 28 2.3.5.2 Time Resampled Frequency Offset Corrected Inversion (tr-FOCI) RF Pulses 28 2.4 Physiological Background 29 2.4.1 Neuronal Activity 30 2.4.2 Energy Metabolism 31 2.4.3 Physiological Changes During Brain Activation 32 2.4.4 The BOLD Contrast 34 2.4.5 Disadvantages of the BOLD Contrast 35 2.5 Arterial Spin Labelling (ASL) 35 2.5.1 Pulsed Arterial Spin Labelling 37 2.5.2 Arterial Spin Labelling at Ultra-High Field 41 2.6 Vascular Space Occupancy (VASO) 42 2.6.1 VASO at Ultra-High Field 44 2.6.2 Slice-Saturation Slab-Inversion (SS-SI) VASO 45 2.7 Calibrated Functional Magnetic Resonance Imaging 47 2.7.1 The Davis Model 47 2.7.2 The Chiarelli Model 50 2.7.3 The Generalised Calibration Model (GCM) 52 3 Materials and Methods 53 3.1 Scanner Setup 53 3.2 Gas Delivery and Physiological Monitoring System 53 3.3 MRI Sequence Developments 55 3.3.1 Tr-FOCI Adiabatic Inversion 55 3.3.2 Optimisation of the PASL FAIR QUIPSSII Sequence Parameters 60 3.3.3 Multi-TE Multi-TI EPI 64 4 Experiment I: Comparison of Direct and Modelled fMRI Calibration 68 4.1 Background Information 68 4.2 Methods 69 4.2.1 Experimental Design 69 4.2.2 Visuo-Motor Task 70 4.2.3 Gas Manipulations 71 4.2.4 Scanning Parameters 71 4.2.5 Data Analysis 72 4.2.6 M-value Modelling 72 4.2.7 Direct M-Value Estimation 73 4.3 Results 74 4.4 Discussion 79 4.4.1 M-value Estimation 79 4.4.2 BOLD Time Courses 82 4.4.3 M-Maps and Single Subject Analysis 82 4.4.4 Effects on CMRO2 Estimation 83 4.4.5 Technical Limitations and Implications for Calibrated fMRI 84 4.5 Conclusion 89 5 Experiment II: Reproducibility of BOLD, ASL and Calibrated fMRI 90 5.1 Background Information 90 5.2 Methods 91 5.2.1 Experimental Design 91 5.2.2 Data Analysis 91 5.2.3 Reproducibility 93 5.2.4 Learning and Habituation Effects 95 5.3 Results 95 5.4 Discussion 101 5.4.1 Breathing Manipulations 102 5.4.2 Functional Reproducibility 107 5.4.3 Habituation Effects on Reproducibility 109 5.4.4 Technical Considerations for Calibrated fMRI 110 5.5 Conclusion 112 6 Experiment III: Simultaneous Acquisition of BOLD, ASL and VASO Signals 113 6.1 Background Information 113 6.2 Methods 114 6.2.1 SS-SI VASO Signal Acquisition 114 6.2.2 ASL and BOLD Signal Acquisition 114 6.2.3 Experimental Design 114 6.2.4 Data Analysis 115 6.3 Results 115 6.4 Discussion 116 6.5 Conclusion 120 7 Conclusion and Outlook 12

Calibrated fMRI for mapping absolute CMRO2: practicalities and prospects

Functional magnetic resonance imaging (fMRI) is an essential workhorse of modern neuroscience, providing valuable insight into the functional organisation of the brain. The physiological mechanisms underlying the blood oxygenation level dependent (BOLD) effect are complex and preclude a straightforward interpretation of the signal. However, by employing appropriate calibration of the BOLD signal, quantitative measurements can be made of important physiological parameters including the the absolute rate of cerebral metabolic oxygen consumption or oxygen metabolism (CMRO2) and oxygen extraction (OEF). The ability to map such fundamental parameters has the potential to greatly expand the utility of fMRI and to broaden its scope of application in clinical research and clinical practice. In this review article we discuss some of the practical issues related to the calibrated-fMRI approach to the measurement of CMRO2. We give an overview of the necessary precautions to ensure high quality data acquisition, and explore some of the pitfalls and challenges that must be considered as it is applied and interpreted in a widening array of diseases and research questions