Motion-Robust Pulse Design for Parallel Transmission Excitation at Ultra-High Field MRI

功能性磁共振成像（fMRI）是最常用的神经元活动图绘制技术，可以评估健康与患病/受伤的大脑功能，并确定大脑的哪些区域处理运动或说话等任务。由于fMRI采集包括对相同体积的重复扫描，以对大脑每个部分中信号的时间变化进行统计分析，因此患者运动会使数据随时间不一致并使分析恶化。运动对于不合作的患者（如帕金森氏症或痴呆症患者）来说尤其成问题。最先进的超高场（UHF）扫描仪为研究神经元活动提供了独特的机会，提高了功能磁共振成像功能映射信号的精度。不幸的是，校正UHF MRI固有的人工对比度变化需要专门设计的成像协议（并行发射RF脉冲）。使用当前的技术，这些脉冲是为静止的患者设计的，当患者移动时会导致不一致的数据项目目标和方法在本研究中，您将开发设计将“冻结”运动的脉冲的技术;即，在功能性MRI扫描期间，当患者可以自由移动时，采集一致的数据。这些运动容忍并行发射脉冲将设计只有一次扫描前，以适应用户指定的范围内的“预期”或“最大”的病人的运动，将只需要简单的调整，而不是计算昂贵的重新设计在扫描过程中。运动对功能磁共振成像分析的影响将被记录，这些脉冲的性能将通过体内实验进行评估。这些结果将指导新型功能磁共振成像协议的开发，并使对痴呆症和帕金森病患者进行UHF功能磁共振成像变得更加可行。您将受益于与物理学和心理学学院的教职员工合作。研究培训该项目位于多学科的接口，并受益于团队物理学和心理学的导师您将开发跨多学科领域的具体和可转移的技能，包括：拥有丰富的MRI和fMRI物理学知识信号处理对患者进行研究fMRI数据采集和分析MRI扫描仪（7 T）、并行传输和运动跟踪硬件计算建模和电磁模拟（Sim 4Life）编程流畅（例如Matlab、C++、Python）实验设计（PsychoPy）MRI序列开发您还将获得博士学院提供的350多个研讨会的支持，以进一步发展研究和专业技能，心理学院和物理学院为博士生提供积极的培训组合，包括教学机会，研讨会和网络活动。该项目的多学科性质和所获得的技能将使学生在研究生涯中取得成功。CUBRIC与西门子医疗保健公司有着紧密的合作关系，并受益于西门子工程师的全职现场工作，这将使学生接触到医疗保健行业的合作。

Patient-motion tolerant functional Magnetic Resonance Imaging at the Ultra-high FieldBackgroundFunctional magnetic resonance imaging (fMRI), the most commonly used technique to map neuronal activity, makes it possible to evaluate how healthy versus diseased/injured brains function and determine which regions of the brain handle tasks like moving or speaking. Because fMRI acquisitions consist of repetitive scanning of the same volume to conduct statistical analysis on the temporal variation of the signal in every part of the brain, patient motion makes data inconsistent over time and deteriorates the analysis. Motion is specifically problematic with uncooperative patients such as patients with Parkinson's or dementia.The state-of-the-art ultra-high field (UHF) scanners provide a unique opportunity to study neuronal activity with increased accuracy of the functional mapping signals for fMRI. Unfortunately, correcting the artificial contrast variations intrinsic to UHF MRI require specifically designed imaging protocols (parallel-transmit RF pulses). With current techniques, these pulses are designed for a stationary patient, leading to inconsistent data when the patient movesProject aims and methodsIn this study, you will develop techniques to design pulses that will 'freeze' motion; ie, acquire consistent data while the patient can freely move during a functional MRI scan. These motion-tolerant parallel-transmit pulses will be designed only once before a scan to accommodate a user-specified range of 'expected' or 'maximum' patient motion, and will require only simple adjustments rather than a computationally expensive redesign during the scan.The effect of motion on fMRI analysis will be documented, and the performance of these pulses will be evaluated via in-vivo experiments. The outcomes will guide the development of novel fMRI imaging protocols and make it more feasible to conduct UHF functional MRI on patients with dementia and Parkinson's.This interdisciplinary project lies at the boundary of engineering, physics and psychology, and you will benefit from working with faculty members from the schools of Physics and Psychology.Research trainingThe project lies at the interface of multiple disciplines and benefits from a team of supervisors from Physics and Psychology. You will develop specific and transferrable skills across multi-disciplinary domains, including:robust knowledge on MRI and fMRI physicssignal processingconducting research with patientsfMRI data acquisition and analysisMRI scanner (7T), parallel-transmit and motion tracking hardwarecomputational modelling and electromagnetic simulations (Sim4Life)programming fluency (e.g. Matlab, C++, Python)experiment design (PsychoPy)MRI sequence development (Siemens IDEA).You will also be supported to attend from over 350 workshops offered through the Doctoral Academy to further develop research and professional skills, and the schools of Psychology and Physics have active portfolios of training for PhD students that include teaching opportunities, seminars and networking events. The multi-disciplinary nature of the project and acquired skills will launch the student on a successful research career.CUBRIC has strong collaborative ties with Siemens Healthcare and benefits from the full-time presence of an on-site Siemens engineer, which will expose the student to academia-industry collaborations.