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Abstract: Over the past four decades, MRI engineering has been characterized by the pursuit of higher magnetic field strengths, measured in Tesla (T), to achieve improved signal-to-noise ratios (SNR) and greater spatial resolution. However, the push for higher field strengths significantly increases system complexity, necessitating the use of large, expensive superconducting magnets that require extensive liquid helium cooling and substantial infrastructure investment. Additionally, the higher field strengths have introduced new imaging and patient safety concerns. In recent years, there has been a resurgence of interest in mid-to-low field strength MRI systems (<1T). Advances in hardware technology now allow these lower field systems to produce image quality that rivals that of high-field MRIs, while mitigating issues related to cost, infrastructure, and complexity. This talk will discuss a notable instance of leveraging this trend: Synaptive Medical's introduction of Canada's first FDA-approved high-performance 0.5T MRI scanner in 2019. This scanner delivers image quality comparable to the traditional 1.5T systems, which are the standard-of-care for routine imaging, but with the benefits of a helium-free magnet, enhanced compactness, and adaptability to a variety of settings. Moreover, the 0.5T MRI offers significant safety advantages, particularly for imaging patients with implanted medical devices—a concern for as many as 58% of inpatients—thereby simplifying clinical workflows and MRI safety evaluations. The talk will explore the speaker’s experience with development of the early 0.5T systems and the potential of their integration into clinical practice, illustrated by examples from UHN Toronto Western Hospital and ongoing research at UHN Toronto General.
Bio: Dr. Ian Connell serves as the Director of Medical Engineering at the University Health Network (UHN), Assistant Professor at the University of Toronto, and Director of Engineering at UHN's Centre for Digital Therapeutics. He is also a Scientist with the KITE Research Institute and CRANIA, a collaborative group of neurosurgeons, radiologists, and scientists committed to enhancing imaging and image-guided interventions for neurological diseases. Dr. Connell has amassed over a decade of experience as an engineer-scientist specializing in the development of MRI hardware and software within the private sector, with a particular emphasis on mid-field systems. Previously, as a Senior Scientist at Synaptive Medical, Dr. Connell led the design of numerous hardware subsystems, including gradients, shim coils, RF coils, amplifiers, and associated electronics. His contributions also encompassed passive magnet shimming, the design and approval of custom electromagnetic simulation software, and general MRI electronics. Furthermore, he played a lead role in the successful FDA submission in 2019 for the Synaptive 0.5T MRI. Currently, at UHN, Dr. Connell oversees a wide array of biomedical engineering responsibilities related to imaging, surgery, and hospital operations. In addition to his operational roles, he also acts as a Principal Investigator, leading substantial research groups totalling of over 50 research staff and trainees.
Abstract: Scientists using MR spectroscopy are rapidly coming up with new contrast mechanisms, most of which are dependent on combining multiple “dynamic” measurements. Endogenous and exogenous metabolite traces are being followed across time, the spectrum is being edited in more combinations to reveal small metabolites, and diffusion MRS is revealing cell-type-specific microstructure. However, tools to analyse this new data are missing, and so is spatial resolution, with dynamic MRS often limited to anatomically non-specific 2x2x2 cm blocks of tissue. This talk will cover efforts to address both, exploring new open-source MRS analysis tools, and then time-resolved MRSI approaches.
Bio: Will Clarke is the MR Spectroscopist at the Wellcome Centre for Integrative Neuroimaging (aka FMRIB), at the University of Oxford. Will is best known for being the developer of FSL-MRS, and a collection of open-science tools for MRS: spec2nii, NIfTI-MRS and the FSLeyes plugin. Recently awarded a Wellcome Career Development Award, he’s now establishing his own group at Oxford developing new functional MRSI methods – working across acquisition, reconstruction, and analysis. Will trained as a chemist and started his MR journey in cardiovascular 31P MRS. He then moved to WIN to work on neuroimaging at 7 T, before finally combining the two to work on 1H MRS of the brain.
Abstract: The presentation will cover several topics including development of optimised multi-modal neuroimaging protocols, the conundrum of head coil selection and its impact on data acquisition, high-resolution ASL, and advances in MRI of DBS patients. There might be a spattering of 7 T research.
Bio: I have a multidisciplinary background, primarily in biomedical engineering, neurophysiology, cognitive & clinical neurosciences. I received a PhD in 2019 for my thesis on ‘Laminar fMRI at ultra-high fields’ at Maastricht University, The Netherlands, followed by a post-doc at Maastricht University on advanced fMRI methods using 7 and 9.4 T (human scanners). Since 2021, I am a senior post-doc in the BRAIN-TO Lab at UHN led by Dr. Kamil Uludag and I work on developing novel MRI acquisition, processing and analysis methods for neuroscience applications.
Abstract: CNS tuberculosis is one of the most devastating and severe forms of tuberculosis (TB) accounting for 5-10% of extrapulmonary TB , with high morbidity and mortality in 50% of patients. In resource limited countries in sub-Saharan Africa, the widespread availability of cross sectional imaging can be a challenge. Al improvement in the techniques of machine learning (ML) and deep learning (DL) in neuroradiology has primarily focused on neuro-oncology, stroke imaging and hemorrhage. This talk will focus on the question of exploring the role of Al in neuroimaging in low and middle income countries (MIC) and how well it will fare in the setting of images obtained from the low-field magnets at Tikur Anbessa Specialized Hospital. Specifically, the performance of promising ML and DL methods for detecting and characterizing CNS TB lesions will be discussed.
Bio: Dr. Amal Saleh is an Associate Professor of Radiology and a Neuroradiologist at the School of Medicine, College of Health Sciences, Addis Ababa University. She is the Dean of the School of Medicine at Addis Ababa University, the President of the Council of Medical Schools in Ethiopia and the Vice President of the Ethiopian Medical Association. She previously served as the President of the Radiological Society of Ethiopia and the Neuroradiology unit head as well as Chair of the Department of Radiology.
Abstract: The use of multiple transmission channels, referred to as parallel radio-frequency transmission (pTx), offers numerous advantages across various applications. These benefits include enhanced B1-field homogeneity, spatially selective excitation, decreased global specific absorption rate (SAR), and minimized artifacts related to implants and implant coupling. In this presentation, I will be focusing on the capabilities of pTx, with a primary emphasis on its safe mode application in the presence of brain implants.
Bio: I am a graduate student who joined Simon Graham’s lab in 2020 following the completion of my MSc degree in Medical Physics at Macquarie University in Sydney, Australia. My research centers around Parallel Radiofrequency Transmission (pTx) for ensuring the safety of MRI scans in patients with deep brain stimulation (DBS) implants. Specifically, my project focuses on the application of the pTx approach to suppress localized heating resulting from the coupling between the MR environment and DBS implants, while maintaining adequate spatial homogeneity of the transmission magnetic field.
Abstract: A brief overview of saturation transfer MRI including magnetization transfer (MT) and chemical exchange saturation transfer (CEST) will be presented, along with results from pre-clinical studies that use MT and CEST to assess the aggressiveness and prognosis of solid tumours. These studies involve using saturation transfer MRI to investigate the microstructural and metabolic properties of prostate tumors, validated with histopathology.
Bio: Wilfred is a research associate at Sunnybrook Research Institute. He obtained his Phil at the University of Oxford in white matter modelling using diffusion MRI, and also worked in hyperpolarized helium-3 and carbon-13 imaging. His current research includes using chemical exchange saturation transfer and magnetization transfer to investigate human and pre-clinical tumours.
Bio: James Stewart graduated with a PhD from the Institute of Biomaterials and Biomedical Engineering at the University of Toronto in 2018 where his thesis focused on improving the accuracy and dosimetric heterogeneity of preclinical irradiation studies. Since then, he has worked as a programmer and researcher in the department of Medical Physics at the Sunnybrook Odette Cancer Institute with a focus on MR-guided central nervous system radiotherapy. James has previously been employed in a research capacity at the Princess Margaret Cancer Centre, exploring adaptive radiotherapy strategies for cervix cancer, and at the Spatial-Temporal Targeting and Amplification of Radiation Response (STAR) centre, where he developed automated algorithms for intracellular and intravascular tracking of inventive therapeutics.
Abstract: Quantitative MRI provides many benefits over traditional qualitative imaging: reproducible tissue characterization, diagnosis of diffuse disease, the potential for earlier disease detection, and more. The standard approach to quantitative MRI of moving organs (e.g., the heart or abdominal organs) has been to “freeze” motion using a complicated mixture of ECG triggering and repeated breath holds. That approach is difficult, unreliable, and most importantly, unsuitable for patients with irregular heartbeats or trouble breath-holding, preventing the wide clinical adoption of quantitative MR in many areas. This seminar describes a new class of approaches to quantitative imaging, which redesign the MR imaging process around the concept of multiple time dimensions. Rather than trying to avoid motion, these approaches “multitask”, capturing motion alongside multiple simultaneous tissue processes for quantification—each of which is assigned its own time dimension. This allows fast, accurate, and repeatable motion-resolved quantitative imaging, and enables non-ECG, free-breathing quantification of multiple tissue parameters at once.
Bio: Anthony G. Christodoulou, PhD, is an Associate Professor of Biomedical Sciences and the Director of Magnetic Resonance Technology Innovations for the Biomedical Imaging Research Institute at Cedars-Sinai Medical Center, and faculty in Medicine and Bioengineering at the University of California, Los Angeles. He received his doctorate in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign and his bachelor’s and master’s degrees in Electrical Engineering from the University of Southern California. Prof. Christodoulou's research laboratory develops and translates novel MRI techniques through innovations in MR physics, machine learning, and image reconstruction. His group's primary research focus is on multidimensional quantitative imaging methods for the diagnosis, risk prediction, and treatment monitoring of cardiovascular diseases and cancer. Prof. Christodoulou is an Executive Board member of the SMRA, a Fellow of the SCMR, and a member of the ISMRM, IEEE, and AHA.
Robust, high-fidelity image reconstruction from noisy, sub-sampled training data with self-supervised learning
Abstract: MRI's temporal resolution is hindered by an inherently slow data acquisition process. To address this, there has been substantial research attention on methods that aim to reconstruct high quality images from sub-sampled, accelerated acquisitions. In recent years, reconstructing sub-sampled acquisitions with neural networks has emerged as the state of the art. Most such methods assume that a fully sampled, high SNR dataset exists and use fully-supervised training, however, such training data may not be readily available and can be difficult or even infeasible to acquire in practice. In this talk, Charles will discuss self-supervised training methods, where the training data is itself sub-sampled. He will present his recent work which analytically justifies one such method, Self-Supervised Learning via Data Undersampling (SSDU), and proposes modifications and extensions that substantially improve its reconstruction quality and robustness to measurement noise and training hyperparameters.
Bio: Dr. Charles Millard is a post-doctoral researcher working in the magnetic resonance physics group at the Wellcome Centre For Integrative Neuroimaging, University of Oxford. His work focuses on methods for image reconstruction from sub-sampled acquisitions with compressed sensing and deep learning. Currently, he is developing self-supervised methods, where a neural network is trained to reconstruct images from sub-sampled examples only. Charles completed his doctorate at the University of Oxford in 2022.
Abstract: Dynamic Positron Emission Tomography (dPET) is a known approach used with 18F-FDG in characterizing tumors. Nevertheless, the development of new radiopharmaceutical tracers has widened the use of dPET to other clinical applications, such as hypoxia. Indeed, a radiopharmaceutical tracer, such as 18F-fluoroazomycin arabinoside (18F-FAZA) appears to be suitable for studying hypoxia using dPET to distinguish between hypoxic and normal tissues. Here, we explore the first attempt to use this approach in Critical Limb Ischemia (CLI).
Bio:
Adam started his career in medical imaging in 2008. He collaborated with Robarts Research Institute scientists in achieving the first human 129-Xe Hyperpolarized lung imaging in Canada, paving the way to a better understanding of lung functions, and in particular, COPD diseases. Shortly after, he developed the technique and tools to measure the tissue sodium concentration in prostate which can be correlated to cancer stages, as a part of a multiparametric study.
When the first PET/MRI scanner came to Canada, he spearheaded, in collaboration with a team of scientists at Lawson Research Institute, the development of the world’s first transparent-to-PET, high-density radiofrequency resonators, particularly for brain imaging. Thereafter, at Western University he furthered his research to improve hybrid PET/MRI cardiovascular imaging by improving the attenuation correction coefficient.
Now as a scientist at UHN, he is collaborating with fellow scientists and doctors, in different studies to understand hypoxia through kinetic modelling of the PET uptake. Furthermore, he is collaborating with the PET/MR vendor to improve PET quantification accuracy, by investigating motion / attenuation correction and methods of PET reconstruction techniques
Abstract: Normal fetal development relies on a healthy supply of oxygenated blood. This supply can be disrupted by a variety of conditions including fetal congenital heart disease, placental dysfunction, and fetal anemia. The consequences of inadequate supply range from fetal demise to the injury of critical organs such as the brain, heart and lungs. To better understand fetal cardiovascular physiology in healthy and at-risk pregnancies, we have developed MRI methods to quantify fetal cardiac anatomy, blood flow, blood oxygenation and hematocrit. This information may one-day guide the timing of traditional therapies, such as early delivery, and allow monitoring of emerging therapies that modify the fetal circulation such as maternal oxygen supplementation and surgical correction of fetal cardiovascular anatomy. In this presentation, I will provide a technical overview of fetal cardiovascular MRI and demonstrate application of MRI to animal and human studies of fetal cardiovascular physiology.
Bio: Chris Macgowan obtained his BSc in physics from the University of British Columbia (1993) and his MSc & PhD in medical biophysics from the University of Toronto (1996 & 2000). He was recruited to SickKids in 2000 to support diagnostic imaging and to develop a research program in cardiovascular imaging. He is now a Senior Scientist in the Translational Medicine program of the Research Institute at SickKids, and a Professor in the Departments of Medical Biophysics and Medical Imaging at the University of Toronto. His research involves the development of novel imaging methods to evaluate cardiovascular physiology including quantification of blood flow, blood oxygen saturation, and vascular mechanics in children. Over the last 15 years, his laboratory has focused on measurement of fetal cardiovascular physiology during normal development and in the presence of pathologies such as congenital heart disease and placental insufficiency. He is interested in translating advanced imaging methods into clinical application and collaborates closely with physiologists and clinical investigators in Cardiology and Obstetrics to obtain new insight to the feto-placental circulation. Among his administrative roles, he is scientific director of the research MRI core facility at SickKids, Chair of the ISMRM Placenta and Fetus study group, and organizer of the annual MICCAI Perinatal, Preterm and Paediatric Image Analysis Workshop
Abstract: Heat production and transport is a critical factor in brain metabolism. This presentation will examine the use of temperature sensitive contrast agents for minimally invasive MRI measurement of temperature and heat transport through the blood. Dr. Chris Heyn will provide an introduction to Dr. Sled's talk by providing background of MR thermometry applications..
Bio: Dr. Heyn is Section Chief of Neuroradiology, Sunnybrook Health Sciences Centre. Assistant Professor in the Department of Medical Imaging, University of Toronto and Associate Scientist SRI, Physical Sciences Platform. His current research interests are in the evaluation of brain metabolism and blood flow for the diagnosis and management of diseases of the CNS. Dr. Sled is a Senior Scientist at the Hospital for Sick Children and a Professor in Medical Biophysics at the University of Toronto. His research is focused on biomedical imaging technologies and applications in mouse models of disease
Abstract: Neuroimaging MRI biomarkers include volumetric measures, microstructure imaging such as diffusion-weighted imaging and magnetization transfer, and functional MRI. These biomarkers nicely complement clinical indices and provide objective means to monitor disease evolution in patients. While being very popular in the brain, MRI biomarkers have been slow to translate to the spinal cord because of technical challenges: (i) The need for high resolution and the difficulties in harnessing 7T systems, (ii) Susceptibility artifacts and shimming, (iii) The lack of standardized imaging protocol across vendors and (iv) Unmet needs for analyzing spinal cord MRI data. This talk will be organized around these challenges, by proposing cutting-edge solutions and discussing their pros and cons.
Bio: Dr. Cohen-Adad (https://neuro.polymtl.ca/team/faculty/julien-cohen-adad.html) is an Associate Professor at Polytechnique Montreal, Associate Director of the Neuroimaging Functional Unit at the University of Montreal, and Canada Research Chair in Quantitative Magnetic Resonance Imaging. His research focuses on advancing hardware and software methods for MRI to help characterizing pathologies in the central nervous system, with a particular focus in the spinal cord. Dr. Cohen-Adad also dedicates efforts in bringing the community together by developing open source solutions (https://github.com/sponsors/neuropoly).
Abstract: The combination of a MRI scanner with a linear accelerator (linac), known as MR-linac, enables to use MRI to guide radiotherapy on each fraction of the process. The MR-linac has the potential to adapt the delivery of radiation for tumors affected by motion in real-time. However, the slow speed of conventional MRI only enables to perform real-time MRI in 2D, which limits the performance for motion tracking. This talk presents a new approach for real-time 4D MRI called MR SIGnature MAtching (MRSIGMA), which shifts the acquisition and reconstruction burden to an offline learning step to compute a 4D dictionary of 3D motion states and motion signatures that identify each state in a unique way, and an online signature matching step that is able to perform 3D imaging with a total latency of less than 300 ms (including acquisition and reconstruction). The concept of MRSIGMA, real-time implementation on the Elekta Unity MR-linac system and initial validation on patients with pancreatic cancer will be presented.
Bio: Ricardo Otazo is currently the Director of MRI Physics and Member in Physics and Radiology at Memorial Sloan Kettering Cancer Center in New York City. He received his PhD in Engineering from the University of New Mexico in 2007 and was a faculty member in the Department of Radiology at NYU Langone Health before moving to Memorial Sloan Kettering Cancer Center in 2018. Dr. Otazo is a world leader in the development of fast and motion-tolerant MRI techniques using compressed sensing, deep learning and non-cartesian sampling. He is one of the pioneers in the application of compressed sensing for accelerated MRI acquisition and the combination of compressed sensing and non-cartesian acquisition for motion-tolerant body MRI. His more recent interests are the development of artificial intelligence techniques for high-performance MRI and the development of real-time 3D MRI techniques for online adaptive radiotherapy of organs affected by motion using a MR-linac system.
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I will describe a new generation of massively-parallel array coils aimed at improving human MR neuroimaging well as simultaneous imaging and neuromodulation. An overarching goal is to push the limits of MRI resolution and speed, particularly for functional and diffusion MR imaging, enabling non-invasive studies of brain structure and function at finer spatial scales. Specifically, I will discuss the synergistic combination of high-channel count radiofrequency (RF) receive arrays with “B0” shim arrays for accelerating image acquisition while reducing image artifacts (particularly at 7 Tesla and beyond). In addition to new array coils for neuroimaging, we are also developing multi-channel, MR-compatible transcranial magnetic simulation (TMS) coils that allow the electric field to be dynamically steered and reoriented over the cortical surface. This provides new degrees of freedom for probing the activity of multiple brain circuits either simultaneously or sequentially. Bringing together two types of array coils, we are integrating a 48-ch TMS array with a 28-ch RF receive array to provide unprecedented image quality for simultaneous TMS-fMRI experiments. Exploiting these hardware capabilities further, we have begun exploring the use of the current-carrying loops in our TMS coils for MRI applications such as diffusion encoding and B0 shimming. The unifying theme of these hardware subsystems is “local field control” using the many degrees of freedom provided by large arrays to dynamically shape both the B-field and E-field for imaging and neuromodulation, thus extending the utility of MRI and TMS for systems neuroscience.
Jason Stockmann, PhD, is broadly interested in magnetic resonance imaging hardware and acquisition methods for improving data quality for both structural and functional imaging. He has worked on diverse MRI scanners ranging in field strength by two orders of magnitude, from low-field (70 mT) to ultra-high field (7 Tesla). He specializes in synergistic combinations of hardware, pulse sequences, and image reconstruction algorithms that address unmet needs in MRI research, especially for diffusion and functional brain imaging with echo planar imaging (EPI) acquisitions. The major thrust of this work has been to develop multi-coil (MC) shim arrays and associated amplifier hardware and optimization methods to improve magnetic field homogeneity inside the body, thus reducing image distortions and other artifacts. More recently, he and colleagues have applied MC arrays to perform dynamic local field control, creating tailored nonlinear field offsets for (i) improving lipid suppression in spectroscopy, (ii) selectively exciting and imaging target anatomy with increased efficiency, and (iii) providing supplementary spatial encoding.
Dr. Stockmann is also interested in low-field, portable MRI for point-of-care brain imaging. He has contributed to Dr. Lawrence Wald and Dr. Clarissa Cooley’s program to build a lightweight prototype brain scanner based on a Halbach array of permanent magnets (80mT main magnetic field). His primary role in this project has been to design pulse sequences and RF pulses that are robust to extreme field inhomogeneity. He has also helped build a generalized reconstruction framework that incorporates the full signal forward model including field nonlinearity. In parallel with this work, he has developed an interest in open-source hardware for MRI research and education. To this end, he contributed to a team effort by Dr. Wald’s group to build 20 tabletop MRI scanners (0.2 Tesla) for an undergraduate engineering lab course at MIT, at a cost of less than $10K per scanner.
He is strongly committed to open-source science and reproducible research across sites. All of his hardware designs and software are available online or by request.
Magnetic Resonance Imaging offers an enormously flexible tool to answer questions about the human body. The MR scanner itself is a complex device, but knowledge of encoding fields and the deviations from nominal scanner behavior can reduce measurement uncertainty. These measurements and system characterizations can then be used to compensate for deviations in the image acquisition, whether from systematic or physiologic origin. Additionally, the measurement of these field dynamics can enable new implementations of image acquisition techniques which were previously subject to unacceptable levels of distortion or signal loss.
Dr. Weavers completed his PhD in 2014 at the Mayo Clinic, in Rochester, MN where he focused on patient-specific optimizations of parallel imaging parameters as enabled by high performance computing and receiver coil design. From there he spent two and a half years as a post-doc with Dr. Matt Bernstein on the final system design and application of a prototype head-only 3T MRI system. Here Paul contributed to general image quality improvements through implementing field corrections through real-time processing on scanner FPGAs. From there a stint at GE Healthcare in the MR Engineering department taught Paul quite a lot about the realities around MR system design and productization.
Paul joined Skope in 2018, and now leads the global sales, marketing and North American support teams. He focuses quite heavily on ensuring the technical capabilities of a field monitoring system are crystal clear to potential users, and that once the system is delivered it is useful to the researcher.
[[https://github.com/fahsuanlin/sri_mr_seminars/blob/main/images/mri_seminars_weavers_april2022.pptx]]
“Combined diffusion-relaxometry techniques” and “Improving the sensitivity and specificity of functional magnetic resonance imaging”
Colleen Bailey is an MR physicist working on MRI methods for cancer therapy response. She uses biophysical models to explore the relationship of cellular changes with diffusion and relaxation MRI. These have revealed changes in cellularity and membrane water exchange resulting from cell death following cancer treatment.
Limitations in diffusion MRI, along with new acquisition and reconstruction techniques, have led to renewed interest in combined diffusion-relaxation MRI protocols in the diffusion community. I will present a summary of this history and a recent review paper (doi: 10.1002/mrm.28963), considering what 2D diffusion-relaxation methods can and cannot tell us. The lessons learned are likely to be of broader interest beyond MRI diffusion and get to questions about research studying biological mechanisms versus clinical applications.Speaker 2:
With the training in cognitive neuroscience and human neuroimaging, Dr. Hsin-Ju Lee is currently a postdoctoral researcher at Sunnybrook Research Institute. Hsin-Ju has been focusing on developing and applying neuroimaging tools and psychological tasks to better understand brain functions and dysfunction. Her research projects use the integration of fMRI, EEG, and TMS to study the neural mechanisms supporting executive controls. She also applies these methods to improve the medical and surgical treatments for schizophrenia, attention-deficit hyperactive and epilepsy patients.Presentation Title: Improving the sensitivity and specificity of functional magnetic resonance imaging
Functional magnetic resonance imaging (fMRI) has been used extensively to suggest "active brain areas" in healthy individuals' cognitive processes, emotional states, and perception. This technique has also been applied to help diagnose, assess, and manage neurological and psychiatric disorders. While fMRI benefits from non-invasiveness and relatively high spatial resolution (about 1 mm) for whole-brain imaging, it has limitations in sensitivity and specificity. In this talk, I will present methods to mitigate these fMRI challenges. Specifically, an emerging trend of using complex naturalistic stimuli will be introduced to probe the brain function and dysfunction more sensitively in an ecologically valid setting. Then, I will explain how incorporating electrophysiological measurements, including concurrent electroencephalography (EEG) recording with fMRI and invasive stereo-EEG, discloses fMRI signals closely related to typical and abnormal neural activity. Lastly, I will introduce the use of transcranial magnetic stimulation (TMS) to elucidate causal relationships between brain activity and behaviors. Together, advancements in the experimental paradigm design, multimodal imaging, and the integration of imaging and modulation improve the sensitivity and specificity of fMRI in neuroscience studies and clinical applications.
The goals of this session will be to review the current safety practices and procedures for our research MRI scanners, talk about improvements / updates that should be made to the current SOPs and generally discuss MR safety related to doing research in the magnet.
Two decades of research and development have brought us here, to the point where 7T MR became clinical. This has expanded the application of 7T MR from pure research to translational research and clinical use. In this talk, I will show you examples from these areas that will demonstrate what the title promises.
Robin M. Heidemann, Ph.D. is the Director of Ultra-High Field MR Pre-development at Siemens Healthineers.
Robins ‘MR Life’ began 1999 with his master studies in Physics on parallel MRI at the University of Wuerzburg. It was followed by a PhD working together with Mark Griswold on parallel imaging methods, such as GRAPPA. After this he joined Siemens in Erlangen as an application developer in the Advanced Neuro Imaging Team for two years. He went back to academia to work for five years as a senior research scientist at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig. In this time, he developed new methods, exploring the potential of 7T for ultra-high resolution functional and diffusion MRI. Since 2012 he is a member of the ultra-high field team at Siemens Healthineers. Currently, Robin is the head of the UHF pre-development at Siemens Healthineers, and he is in charge of the UHF global collaboration and application development.