Quantifying image distortion in MRI for Radiotherapy treatment planning

量化 MRI 中的图像失真以制定放射治疗计划

• 批准号: 2879643
• 金额: --
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2879643
• 关键词: Quantifying; image; distortion; MRI; Radiotherapy

MRI is a key medical imaging modality. It provides high quality 3D images with unique soft tissue contrast which are useful across a huge range of clinical applications including imaging tumours and for surgical planning. One key application is in radiotherapy, where MRI is increasingly used to plan the delivery of radiation to the site of a tumour while minimising the dose to neighbouring, healthy tissue. Compared to more traditional approaches using CT, MRI provides improved tissue contrast and quantitative imaging biomarker definition (making the tumour easier to delineate) for targeting and treatment monitoring, and also removes the need to expose the patient to Ionising radiation during imaging.One very important consideration, however, is spatial distortion in the MR images. The presence of a patient in the scanner distorts the applied magnetic field and means that images contain small errors in the size, shape, and position of tissue features. This means that the errors and uncertainties in radiation delivery cannot be fully quantified, meaning that very conservative estimates must be used instead of the careful approaches applied elsewhere in the treatment planning pipeline.This PhD aims to develop a detailed understanding of MR image distortion to fully quantify its effects and incorporate them into the treatment planning pipeline. The project is partly based on carefully building and imaging test objects (also known as phantoms) which distort the field in a controlled way, building from simple, easily understood objects to more complex objects which are more representative of the geometry and biomarker characteristics of organs such as the brain, and partly on modelling the physics behind image distortion. The aim is to quantitatively characterise the distortion field and to incorporate this into Radiotherapy audits. There is scope to include physics-based modelling, statistics, and other advanced approaches such as AI to inform treatment planning and monitoring with the most complete and accurate description of image distortion possible.The supervision team comprises experts in MRI, modelling, and measurement science. It is in partnership with a leading MRI phantom manufacturer who bring knowledge of advanced materials and manufacturing capabilities. We also work closely with teams who provide radiotherapy audits nationally across the UK. The successful applicant would gain experience across practical imaging, advanced modelling, image analysis, and measurement science and would have the opportunity to emphasize their own strengths and interests in completing the work.The project will cover:1. Development of susceptibility-matched materials, including evaluation of manufacturability and associated uncertainties in manufacturing2. Design and characterization of 3D printed distortion phantoms of a range of complexities Including mimics of key physical properties3. MRI scanning of test objects and volunteers4. Simulation of phantoms and applied field and pulse sequences5. Assessing the performance of image distortion correction algorithms, quantifying errors in reconstruction6. Quantification of image-based uncertainties due to field distortion effects and processing

MRI是一种重要的医学成像方式。它提供具有独特软组织对比度的高质量3D图像，可用于各种临床应用，包括肿瘤成像和手术规划。一个关键的应用是在放射治疗中，MRI越来越多地用于计划将辐射输送到肿瘤部位，同时最大限度地减少对邻近健康组织的剂量。与使用CT的传统方法相比，MRI提供了更好的组织对比度和定量成像生物标志物定义（使肿瘤更容易描绘），用于靶向和治疗监测，并且还消除了在成像期间将患者暴露于电离辐射的需要。扫描仪中存在患者会使施加的磁场发生扭曲，这意味着图像在组织特征的大小、形状和位置方面存在微小误差。这意味着辐射输送中的误差和不确定性不能完全量化，这意味着必须使用非常保守的估计，而不是在治疗计划管道中其他地方应用的谨慎方法。该博士旨在详细了解MR图像失真，以充分量化其影响，并将其纳入治疗计划管道。该项目部分基于仔细构建和成像测试对象（也称为幻影），这些对象以受控的方式扭曲场，从简单，易于理解的对象构建到更复杂的对象，这些对象更能代表大脑等器官的几何形状和生物标志物特征，部分基于对图像失真背后的物理建模。其目的是定量分析畸变场，并将其纳入放射治疗审核。我们的项目包括基于物理的建模、统计和其他先进方法，如人工智能，以最完整、最准确地描述图像失真，为治疗计划和监测提供信息。监督团队由MRI、建模和测量科学方面的专家组成。它与领先的MRI体模制造商合作，后者带来了先进材料和制造能力的知识。我们还与在英国全国范围内提供放射治疗审核的团队密切合作。成功的申请人将获得实践成像，先进建模，图像分析和测量科学的经验，并有机会强调自己的优势和兴趣完成工作。该项目将包括：1.开发可制造性匹配的材料，包括评估可制造性和制造中的相关不确定性2。设计和表征一系列复杂的3D打印变形幻影，包括模拟关键物理特性3。测试对象和志愿者的MRI扫描模拟幻象和施加的场和脉冲序列5.评估图像失真校正算法的性能，量化重建中的误差6.由于场失真效应和处理引起的基于图像的不确定性的量化