Motion robust quantitative MRI of the brain at 7T

1)对研究背景的简要描述，包括潜在的影响本项目将研究运动对7T时大脑的定量磁共振成像的影响。在与西门子的合作中，我们之前已经证明，运动是有问题的，不仅是因为编码错误，还因为位置相关的发送和接收字段(1，2)。消除这些问题将有利于寻求识别神经变性的板层特异性特征的临床研究，包括对亨廷顿病、家族性阿尔茨海默病、帕金森和癫痫的研究。2)目的和目标时间1年：学生将完成他们的研究硕士学位，教授的模块包括医学成像和人工智能，以及一个独立的研究项目，将评估低等级重建的效用。第2年：学生将开始自己的博士学位，并通过回顾数据的获取方式和定义最大限度地减少采集时间的最佳采样方案，从而最大限度地减少扫描中运动的风险，来建立上一年的工作同时保持图像质量。学生还将开始制定包含对比度特定的发射和接收场效应的数据的生成模型，以允许扫描之间的运动。第三年：学生将评估采样方案如何在不同对比度之间改变，并用于联合重建，以进一步降低扫描内运动敏感度，同时确保多参数图的准确和可重复性量化。产生式模型将被训练以学习数据的协方差结构，从而它将能够在新数据中输入数值。第4年：产生式模型将用于补偿扫描间和扫描内运动，以产生最终的可部署协议。将撰写论文并完成所有出版物(如果尚未完成)。3)研究方法的新颖性该项目将利用定量MRI由多个采集组成的事实，并建立这些数据及其协方差的生成模型，以利用这提供的冗余。4)与EPSRC的战略和研究领域保持一致本项目的目标有可能在转变医疗保健方面产生世界级的影响；提高高场磁共振成像的质量和能力，这些解决方案也可以应用于低场磁共振成像。5)参与该项目的任何公司或合作者将与西门子医疗保健公司密切合作，西门子医疗保健公司是该项目的部分资金来源。Papp D，Callaghan MF，Meyer H，Buckley C，Weiskopf N。通过考虑接收线圈灵敏度影响，修正定量R1映射中的扫描间运动伪影。医学中的磁共振。2016；76(5)：1478-1485。DOI：10.1002/mrm.260582。首页--期刊主要分类--期刊细介绍--期刊题录与文摘--期刊详细文摘内容校正7T时定量R1映射中的扫描间运动伪影。医学中的磁共振。2022；88(1)：280-291。DOI：10.1002/mrm.29216“

1) Brief Description of the context of the research including potential impactThis project will be addressing the effects of motion on quantitative MRI of the brain at 7T. In collaboration with Siemens, we have previously shown that motion is problematic not only because of encoding errors, but also because of position-dependent transmit and receive fields (1,2). Eliminating these problems would benefit clinical studies that seek to identify laminar-specific signatures of neurodegeneration, including such studies of Huntington's Disease, familial Alzheimer's Disease, Parkinson's and Epilepsy running locally.2) Aims and ObjectivesTimelineYear 1: The student will have completed their Master of Research with taught modules encompassing medical imaging and AI, as well as a self-contained research project that will assess the utility of low rank reconstructions.Year 2: The student will commence the PhD itself and build on the work from the previous year by revisiting how the data are acquired and define optimal sampling schemes that minimise acquisition times, and therefore the risk of intra-scan motion, while preserving image quality. The student will also start to formulate the generative model of the data incorporating contrast-specific transmit and receive field effects that allow for inter-scan motion. An updated protocol will be deployed.Year 3: The student will assess how sampling schemes might change across contrasts and be used in a joint reconstruction to further mitigate intra-scan motion-sensitivity while ensuring accurate and reproducible quantification of multi-parameter maps. The generative model will be trained to learn the covariance structure of the data such that it would then be able to impute values in novel data.Year 4: The generative model will be used to compensate for for inter- and intra-scan motion to produce a final deployable protocol. The thesis will be written and all publications finalised (if not already completed).3) Novelty of Research MethodologyThe project will exploit the fact that quantitative MRI is comprised of multiple acquisition and establish a generative model of these data, and their covariance, in order to exploit the redundancy that this affords.4)Alignment to EPSRC's strategies and research areasThe objectives of this project have the potential to have a world-class impact in transforming healthcare; enhancing quality and capabilities of the high-field MRI, where these solutions can be applied to lower-field MRI as well.5)Any companies or collaborators involvedThe project will be conducted in close collaboration with Siemens Healthineers, who are part-funding the studentship.References1. Papp D, Callaghan MF, Meyer H, Buckley C, Weiskopf N. Correction of inter-scan motion artifacts in quantitative R1 mapping by accounting for receive coil sensitivity effects. Magnetic Resonance in Medicine. 2016;76(5):1478-1485. doi:10.1002/mrm.260582. Balbastre Y, Aghaeifar A, Corbin N, Brudfors M, Ashburner J, Callaghan MF. Correcting inter-scan motion artifacts in quantitative R1 mapping at 7T. Magnetic Resonance in Medicine. 2022;88(1):280-291. doi:10.1002/mrm.29216"