Gary H. Glover - US grants

The purpose of this project is to develop radial k-space Magnetic Resonance (MR) techniques to improve imaging of cancerous tumors in the abdomen. While MR has been widely embraced as the method of choice for neurological diagnostic imaging applications, it has not received universal acceptance in abdominal applications because the images are frequently contaminated by severe respiratory motion artifacts. In many cases these artifacts render the diagnosis equivocal inasmuch as contrast differences in liver, kidney and adrenal masses can be subtle. This proposal describes a unique approach to enhanced tumor visualization which diminishes the deleterious effects of physiological movement of abdominal structures. Unlike other MRI approaches that rely on corrections to conventional acquisition methods, or on rapid data acquisition for suppression of motion blurring and ghosting, the proposed effort allows conventional TR/TE and SNR choices, and thus provides proven diagnostic imaging contrast characteristics. In the new approach proposed here, radial projection reconstruction (PR) k-space trajectories are shown to have fundamentally superior characteristics relative to those of spinwarp methods with regard to motion artifacts. The plan will carry out a thorough investigation of the tradeoffs of various radial trajectory alternatives, develop a phantom system and quantitative metric for comparison of these techniques, and investigate additional correction schemes which may be employed during reconstruction. The clinical efficacy of these methods will be evaluated in a study of 60 patients with abdominal cancer. The techniques will address the major present limitations of PR imaging: residual streaks from view inconsistencies, off-resonance blurring, motion blurring, and capability for non-axial scan planes. This research will result in the development of superior techniques for MR imaging of abdominal tumors.

Introduction: High speed fMRI is desirable since it allows (1) dynamically imaging functional events; (2) reducing motion artifacts. Partial k-space (PK) imaging increases speed by collecting fewer phase encodes while preserving spatial resolution. PK can also be used in the readout direction to reduce echo time, leading to reduced flow and/or susceptibility dephasing. This study examines the feasibility of PK fMRI technique. Method: MR data were acquired on a GE 1.5 T scanner. Motor cortex activation images were obtained by running a GRE-EPI (single 4mm slice, TR/TE/FOV = 375ms/40ms/240mm, 4 shots, 160 frames in 240s, 128x128 matrix, finger apposition alternated between the left and right hands every 20s) and a 2D spiral sequence (8 slices of 3mm thickness, TR/TE/FA/FOV = 640ms/40ms/ 63o/240mm, 4 interleaves, 100 frames in 256s, resting state alternated with right hand finger tapping every 20s). The spiral data were regridded onto a 128x128 Fourier grid so that PK simulation could be carried out. PK reconstruction was performed using the homodyne approach. Results: The PK activation patterns are highly similar to that of FK. Although PK images have reduced SNR than the FK images, they don't have reduced spatial resolution nor significant ringing or blurring. Discussion and Conclusions: Our results demonstrate the feasibility of PK fMRI technique. A 2D PK technique can save nearly 1/2 scan time, while a 3D PK scan can obtain close to 4 times higher temporal resolution. The time savings can be used to collect more frames to increase statistical power or to cover more slices. The reduced time for each time frame allows using longer TR, leading to improved CNR and/or inflow charateristics. The same time per frame can be used to increase spatial resolution if so desired. Considering that PK imaging techniques are widely available, it represents a promising approach for brain functional mapping.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The FIRST (Functional Imaging Research Schizophrenia Testbed) Biomedical Informatics Research Network (fBIRN) program is the first-ever large scale, multi-center fMRI study of schizophrenia (http://www.nbirn.net). The fBIRN project will pool fMRI data from each of the 11 participating sites to enable the acquisition of a large and diverse study population in a modest time period. Our Center has been responsible for the calibration and quality assurance aspects important for multi-center fMRI trials, and G. Glover chairs the Calibration Working Group within the fBIRN. This subproject is a study of the use of breath holding (BH) to calibrate and mitigate the confounding effects of hemodynamic differences between subjects, thereby reducing variance and improving the ability to pool data across large populations. Previous activities have developed the basic method, which is in current use by the consortium.

Abstract Not Provided.

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Renewal of the NCRR Center for Advanced Magnetic Resonance Technology is proposed. Magnetic resonance instrument manufacturers Introduce new technology in their products based on marketing and other factors that often preclude the timely availability of cutting edge research capabilities for investigators. To fill this gap, the Center will develop and make available innovative technologies in five core research areas of magnetic resonance imaging and spectroscopy (MRI/MRS): (1) image reconstruction, fast imaging and RF pulse design methods, (2) MR hardware, (3) body imaging methods, (4) neuroimaging methods, and (5) MR spectroscopy methods. In each of these areas, we will capitalize on the extensive experience in Stanford's Radiology and Electrical Engineering departments to improve and expand imaging technology for use in basic research and clinical care, and to provide cutting edge opportunities for biomedical research with MRI.. Over the past five years, the Center has been motivated by and has served a wide base of extramurally sponsored collaborators and service users from leading medical and research institutions. We will continue to nurture these collaborations and mutually enrich our research and development efforts. Examples of collaborative projects today are the development and use of advanced functional MRI imaging methods in neurosciences and clinical applications and studies of breast cancer with efficient MRS methods. We will continue to train students and postdoctoral fellows to be the future leaders in MR, to publish extensively, and to provide educational opportunities to the scientific and medical communities we serve. New technology and technological capabilities developed at the Center and as part of our extensive collateral research will be disseminated rapidly for widespread use in the national research community. Publications, conference presentations, annual reports and the internet will continue to form the backbone of our dissemination efforts.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Introduction: BOLD fMRI suffers from signal dropout in frontal-orbital and lateral parietal/temporal regions from susceptibility differences between air and tissue induces intravoxel dephasing. By decreasing the slice thickness, dephasing is reduced and signal is regained, but at the expense of signal to noise ratio (SNR) in magnetically uniform regions of the brain (1). Here we introduce a novel solution: the use of Hadamard-encoding to simultaneously excite pairs of subslices that are subsequently combined incoherently using UNFOLD (2) to gain signal in dropout regions at no loss of SNR efficiency in uniform regions. Methods: Alternately applying sine- and cosine-modulated Hadamard pulses (3) in a dynamic acquisition, two sub-slices of half the desired slice thickness are excited in-phase and out-of-phase (Fig. 1). Assuming there is a phase shift of [unreadable] between subslices because of the susceptibility-induced gradients, the resulting complex-valued time series contains magnitude components , where [unreadable]i are the magnitudes of the subslice signals, and the sign alternates with time frame t because of the alternating excitation. Squaring y(t) and taking its Fourier transform, one finds a component Y1 with spectrum centered at DC corresponding to the term and a second component Y2 centered at the Nyquist frequency corresponding to (Fig. 2). Applying an UNFOLD filter H(w) to remove the Nyquist component, inverse transforming and taking the square root yields a reconstructed timeseries , i.e. the square root of the sum of squares of the two subslices. The influence of the intravoxel dephasing component [unreadable] is thereby removed. The Hadamard method was implemented in a spiral-in/out pulse sequence (4). 60 2 mm thick subslices were acquired for 128 time frames. Timeseries corresponding to 4 mm slices were obtained from the magnitude reconstructed images as above using a two-point boxcar filter ( ). Functional data were obtained at 3T using a breath hold task to elicit activation in most of the brain (5). These scans were compared to a similar conventional method. To read about other projects ongoing at the Lucas Center, please visit http://rsl.stanford.edu/ (Lucas Annual Report and ISMRM 2011 Abstracts)

The purpose of this Technical Research and Development (TR&D) Project is the development and dissemination of technical tools for MR imaging pulse sequence development. This includes RF pulse design, pulse sequence waveform and acquisition design, and image reconstruction algorithms and software. Most of this technology is originally developed in either NIH or industrial supported projects. This TR&D provides the support for the refinement of these technologies, and translation into more general, widely useable toolboxes and software. In addition, data sets are provided, so that other investigators can reproduce the results from the original papers, and directly compare their work to our algorithms. This greatly expands the universe of investigators that can contribute to MR imaging research. The response has been tremendous, with many hundreds to thousands of downloads for each software package. For example, the sparse reconstruction matlab code has been downloaded 1840 times in the last year and half, and the paper describing these algorithms is the most downloaded paper over the last five years in Magnetic Resonance in Medicine, the leading journal for MR imaging research.

CAMRT will continue to provide training and educational opportunities to students of biomedical imaging who are enrolled at or visiting Stanford and to members of the scientific, medical and public community who use our facilities. CAMRT also actively engages in training and educational activities of the extramural community. We will continue to publish articles in peer-reviewed journals on our technical advances and collaborative research results, and to have a substantial presence at national and international meetings. We will continue to disseminate information about the center through our web site and annual reports. We will maintain our role in providing software and other tools by electronic form. Our investigators are highly regarded in the international community; this visibility is synergistic with requests for dissemination.

This TRD, Magnetic Resonance Spectroscopy (MRS) and Multinuclear Imaging, has been actively involved in the development and evaluation of in vivo MRS and spectroscopic imaging (MRSI) technology for both protons (1H) and other nuclei from the founding of the CAMRTS P41 Research Resource Center in 1995 to the present. While some of our recent metabolic imaging studies involved a variety of organs including kidney, heart, and liver, our primary effort during the prior funding cycle was on the development of novel methods for measuring brain neurotransmitter levels and neurometabolic processes. Under this competitive renewal, we propose to build upon our successes in brain imaging technology with important refinements needed to translate hyperpolarized 13C MRSI techniques from animal to human applications, improve 1H MRS measures of steady-state neurotransmitter levels, and provide previously unavailable regional measures of neuroenergetic and neurotransmitter cycling rates throughout the human brain. These choices are based on meeting the current and future needs of collaborative projects ?Metabolic Therapy of GBM guided by MRS of hyperpolarized 13C-pyruvate? (PI: Lawrence Recht, Stanford University), ?1H MRS of GABA, Glu, and Gln? [PI: Brian Wandell, Stanford University), and Neuroimaging of Alcoholism (PI: Adolf Pfefferbaum, SRI International). Specifically, in vivo MRSI offers non-invasive identification, visualization, and quantification of brain biochemical markers and neurotransmitters, the assessment of abnormalities in injured or diseased brain tissue, the longitudinal monitoring of degenerative diseases, and the early evaluation of therapeutic interventions. 1H MRS is able to measure steady-state levels of GABA, glutamate (Glu), and glutamine (Glu), and infusion of 13C labeled substrates permits the measurement of tricarboxylic acid (TCA) cycle and neurotransmitter cycling rates. Furthermore, the ongoing development of hyperpolarized agents, i.e., MRIvisible compounds whose magnetization is four orders of magnitude higher than that normally achieved at in vivo temperatures, presents unprecedented opportunities to noninvasively monitor critical dynamic metabolic processes under both normal and pathologic conditions. New MRS technology will be developed in accordance with the following Specific Aims: 1) to develop optimized pulse sequences and hardware for clinical hyperpolarized 13C studies of the human brain and glioma treatment response, 2) to develop improved 1H MRS GABA, Glu, and Gln editing methods to robustly measure steady-state neurotransmitter levels throughout the human brain free from overlapping macromolecular resonances that limit current methods, and 3) to develop indirect-detection 1H-13C techniques to measure TCA and Glu/Gln cycling rates throughout the human brain.

From its inception, CAMRT has developed innovative neuroimaging methodology for use by our collaborators and service users as well as the community at large through dissemination and training. When we started doing fMRI research in 1993, our scanner did not have EPI-capable gradients, and we were forced to innovate. We found that spiral trajectories being developed by our colleagues in EE were highly efficient, and enabled us to collect excellent timeseries images with several shots instead of the 64 or more needed with conventional Cartesian methods. Thus, when CAMRT began in 1995 we continued to evolve innovative acquisition and analysis techniques, such as real-time fMRI and sparsely sampled acquisitions, driven by collaborators in the neurosciences and other cognitive biomedical fields. We demonstrated strong advantages to our spiral sequences over the more ubiquitous EPI techniques, and they are in use for tens of thousands of scans/year in our center and elsewhere. We became highly regarded by the extramural community for our technology (our top 5 fMRI papers in Google Scholar together have over 3000 citations), and have disseminated broadly. Building on our sound record of impact in fMRI and other neuroimaging methods for cognitive exploration, and motivated by investigators asking increasingly complex questions about the brain, we propose to develop fMRI acquisition techniques with higher spatiotemporal resolution, introduce highly novel array methods for neuromodulation of brain networks using both TMS and tDCS, and augment our DTI technology with new susceptibility weighted methods. These goals are highly consistent with the Grand Challenges in Neuroimaging identified by an NSF Workshop called in response to the BRAIN research initiative introduced by President Obama in 2013. We will also maintain our support of outside investigators through dissemination of pulse sequences, reconstruction methods and other software, and continue to train students and our users in state of the art neuroimaging technology.

This Technology Research and Development (TR&D) project aims to provide advanced, quantitative body MRI methods that can quickly be integrated into clinical testing or research studies. The development of MRI methods that have clinical impact demands substantial iteration based on feedback from human studies. An integral part of this project is to work closely with numerous collaborations to speed development of highimpact imaging solutions to clinical problems. This proposal is primarily focused on techniques to image cancer, renal function and osteoarthritis-related conditions, though numerous other applications will likely emerge from the broad array of collaborations and service projects. The overall goals of this project are divided into 3 specific aims: (1) to offer a complete quantitative volumetric dynamic contrast-enhanced (DCE) acquisition, reconstruction and post-processing suite that is robust to motion, static and radiofrequency magnetic field variations and the presence of fat, (2) to develop highresolution quantitative diffusion-weighted imaging (DWI) methods that are robust to the challenges of motion in the body, and (3) to disseminate advanced musculoskeletal methods including a 5-minute 3D morphologic (fat and water) and quantitative (T2, T2* and diffusion) imaging method as well as a novel, rapid approach to distortion-corrected imaging near metallic implants. Collaborations will include numerous investigators who lead research projects and clinical services that utilize all methods in the aims. The project will leverage technology development within the Biomedical Technology Resource Center as well as other funded projects, including advanced sampling, compressed sensing, novel motion correction, multiband imaging, rapid steady-state imaging, quantitative signal model fits, and new approaches to imaging near metal. The main focus will be to combine technologies into robust implementations that can be used routinely in research studies and clinical settings.

This TRD, Hardware and High Field, has been in existence since 2010 and has been addressing the demands for increased spatial resolution, sensitivity and speed as well as solving problems of high magnetic field, by developing novel MR hardware. We propose to continue this focus on technology development, particularly focusing our work on solving neuroimaging problems at high field (3T) and ultra-high-field (7T and above). With regard to the latter, it is known that there are still substantial technical innovations needed to make ultrahigh- field MRI routine, stable and consistently superior to the best available clinical MRI systems, in all parts of the body. The technical challenges related to gradient, shim and RF performance, decreased B0 and B1 homogeneity, and increased RF power deposition are the most critical. These challenges are the basis for much of the present research activity in the UHF MRI world, and many creative solutions are being found. But one underlying principle is clear: solving these problems will demand innovation in the design, implementation and application of high-performance hardware sub-subsystems. It is also clear that even at field strengths lower than 7T, many improvements in image quality would be enabled through novel hardware development. From the Human Connectome Project comes a clear demand for increased gradient performance, which is needed both for more efficient diffusion encoding and for faster and higher resolution spatial encoding. Yet body-size gradients have now reached hard amplitude and slew rate limits set by human peripheral nerve stimulation thresholds, and therefore any further increases in gradient performance will require innovation in smaller size gradient coils, most obviously head-size gradients. Along with the demands for better gradients come new requirements for better B0 shimming and B1 / radio frequency performance. In this TRD project, we will pursue projects involving major hardware design, construction and analysis in all three of these principal hardware subsystems of the MR scanner.

The Center for Advanced Magnetic Resonance Technology (CAMRT) has been in existence as a BTRC since 1995, and long ago developed an effective structure to administer the grant. This includes managing our TR&D projects, choosing collaborations, maintaining up-to-date resources, training users and students, disseminating our technology and developing strategic plans and oversight. In this proposed continuation of CAMRT, we will largely maintain this successful structure as is, although for this final funding cycle we have replaced two of our 5 Advisory Board members and made minor adjustments to our governing structure. We also propose a plan for the sunset of CAMRT when funding concludes. Essentially through collaterallysupported effort, we will maintain the dissemination of technology developed in CAMRT as long as it is relevant and continue to train for and provide service use of instrumentation.

? DESCRIPTION: (provided by applicant): A renewal of the NIBIB Center for Advanced Magnetic Resonance Technology at Stanford University School of Medicine is proposed. Magnetic resonance instrument manufacturers introduce new technology in their products based on marketing and other factors that often preclude the timely availability of cutting edge research capabilities for investigators. To fill this gap, the Center continues to develop and make available innovative technologies in five related research areas of magnetic resonance imaging and spectroscopy (MRI/MRS): (1) Image Reconstruction, Fast Imaging, and RF Pulse Design, (2) MR hardware and High Field, (3) Body Imaging Methods, (4) Functional/ & Structural Neuroimaging Methods, and (5) MR Spectroscopy & Multinuclear Imaging. In each of these project areas, we will capitalize on the extensive experience in Stanford's Radiology and Electrical Engineering departments to improve and expand imaging technology for use in basic research and clinical care, and to provide cutting edge opportunities for biomedical research with MRI. Over the past five years, the Center has been motivated by and has served a wide base of extramurally sponsored collaborators and service users from leading medical and research institutions. We will continue to nurture these collaborations and mutually enrich our research and development efforts. Examples of collaborative projects today are the development and use of advanced functional MRI imaging methods in neurosciences and the incorporation of sparsely sampled MRI acquisition and reconstruction methods. We will continue to train students and postdoctoral fellows to be the future leaders in MR, to publish extensively, and to provide educational opportunities to the scientific and medical communities we serve. New technology and technological capabilities developed at the Center and as part of our extensive collateral research will be disseminated rapidly for widespread use in the national research community. Publications, conference presentations, annual reports and the internet (http://camrt.stanford.edu/) will continue to form the backbone of our dissemination efforts.

Significance: Chronic pain affects approximately 100 million Americans, costs our society half a trillion dollars per year, and is challenging to treat effectively. Functional magnetic resonance imaging (fMRI) of the brain - and more recently the spinal cord - have advanced our knowledge of the central nervous system (CNS) correlates of pain processing in humans. Additionally, brain fMRI is demonstrating much promise as a potential pain biomarker. Convention has been to perform brain/brainstem and, only more recently, spinal cord imaging separately. But a link between the human brain and spinal cord remains conspicuously missing. To fully characterize abnormal CNS mechanisms of chronic pain and pain modulation, we need to understand the intricate interplay between these structures. Preliminary Data: We have demonstrated successful simultaneous spinal cord-brainstem-brain fMRI by overcoming the magnetic field shimming obstacles. We have also demonstrated the ability to image the CNS correlates of pain and pain modulation. We propose to use this innovative technology of simultaneous spinal cord-brain fMRI to more fully characterize CNS mechanisms of chronic pain and pain modulation, and also to develop improved corticospinal biomarkers of the chronic pain condition fibromyalgia (FM). Specific Aims: In Aim 1, we will enhance our innovative simultaneous spinal cord-brain imaging sequence to minimize the impact of cardiovascular-induced spinal cord motion. We will contrast the optimized sequence against our currently working sequence while characterizing the CNS mechanisms of thermal pain intensity encoding. In Aim 2, we will characterize central sensitization (using pressure pain, temporal summation (TS) of pain, and resting state functional connectivity) and in Aim 3, descending modulation of pain (using conditioned pain modulation (CPM) and emotion reappraisal (ER)). Our preliminary data demonstrates feasibility and early insights into these mechanisms. Finally, in Aim 4, we will use the complete CNS imaging of pain and its modulation within our established multivariate pattern analysis (MVPA) models to better inform mechanistic knowledge and classification procedures. Overall Impact: Successful completion of our aims will advance scientific knowledge of the complex interplay between the spinal cord and brain in chronic pain and pain modulation. Our results and technology will be used to investigate other fields of human CNS research (e.g. motor disorders, spinal cord injury, degenerative conditions, etc). Additionally, we will have advanced development of objective biomarkers of pain. Future directions of this research will apply these CNS biomarkers for neuroprognosis and neuroprediction to help reduce the public health crisis of pain.