Development of Anatomical Patient Models to Facilitate MR-only Treatment Planning

精确描绘放射治疗计划(RTP)的危险靶点和器官仍然是一个挑战。 由于计算机断层扫描(CT)缺乏软组织对比度，这是RTP的标准护理成像。 放射肿瘤学通过将磁共振图像(MRI)与CT配准来解决这一限制 数据集，以利用MRI提供的卓越软组织对比度。核磁共振带来相当大的价值 通过提高描绘的准确性来提高RTP，这反过来又使得剂量递增能够改善局部控制 同时维持或降低正常组织毒性。然而，目前MRI作为附件的整合 CT有很大的缺点，因为它需要图像配准和数据集之间的轮廓转移。这 治疗过程引入了系统的几何不确定性，这些不确定性在整个治疗过程中持续存在，并可能会损害 肿瘤控制。因此，我们建议将仅限MR的RTP转化为临床使用，最终目标是改进 通过改进的治疗计划设计实现患者结果。仅限MR的RTP将消除冗余CT 扫描(减少剂量、患者时间和成本)、简化临床效率、完全避免注册 不确定性，并充分发挥磁共振成像的高精度实时成像的优势。然而，核磁共振并不是常规的单独使用。 对于RTP，很大程度上是由于其已知的空间扭曲、缺乏电子密度以及无法分割骨骼 用于在线图像指导和用于剂量计算的电子密度图。 中心假设是，我们的多学科学术/行业的创新技术 (Henry Ford Health System/飞利浦Healthcare)合作开发将产生几何精度高的患者 基于多个平台/场强的MRI数据构建的模型，其CT等效密度可 在整个RTP工作流程中保密使用。在目标1中，我们将执行几何扭曲 校正，根据变化的解剖结构确定失真可变性，在新的模块化中对结果进行基准测试 Phantom，并开发了一个图像处理工具包。在目标2中，我们将在 大脑和男性/女性骨盆从新型MRI获得准确的合成CT患者模型 序列，包括金属植入物的规定，并在体模中对结果进行基准测试。在《目标3》中，我们将 进行端到端测试，以确定仅限MR的RTP工作流程中的不确定性。我们将表演一场 仅限MR的RTP在脑和男性/女性骨盆的虚拟临床试验并与护理标准进行比较。最终 翻译将包括制定医生-物理学家执业指南、最终用户验证所有翻译 步骤，并将图像处理工具传播到放射肿瘤学社区。这项研究将 系统地解决限制仅限MR的RTP的主要挑战，并为多机构合作奠定基础 跨磁共振平台的临床试验。它将支持未来与MR引导的RT、功能MRI相关的工作 生物适应性放射治疗和肿瘤负荷较高区域的焦点放射治疗。

Accurate delineation of targets and organs at risk for radiation therapy planning (RTP) remains a challenge due to the lack of soft tissue contrast in computed tomography (CT), the standard of care imaging for RTP. Radiation Oncology has addressed this limitation by registering magnetic resonance images (MRI) to CT datasets to take advantage of the superior soft tissue contrast afforded by MRI. MRI brings considerable value to RTP by improving delineation accuracy which, in turn, has enabled dose escalation to improve local control while maintaining or reducing normal tissue toxicities. However, the current integration of MRI as an adjunct to CT has significant drawbacks as it requires image registration and contour transfer between datasets. This process introduces systematic geometric uncertainties that persist throughout treatment and may compromise tumor control. Thus, we propose to translate MR-only RTP into clinical use, with the ultimate goal of improving patient outcomes accomplished via improved treatment plan design. MR-only RTP will eliminate redundant CT scans (reducing dose, patient time, and costs), streamline clinical efficiency, entirely circumvent registration uncertainties, and fully exploit the benefits of MRI for high-precision RTP. Yet, MRI is not routinely used alone for RTP, largely due to its known spatial distortions, lack of electron density, and inability to segment the bone needed for online image guidance and electron density mapping for dose calculation. The central hypothesis is that the innovative technologies that our multi-disciplinary academic/industrial (Henry Ford Health System/Philips Healthcare) collaboration develop will yield geometrically accurate patient models built from MRI data across several platforms/field strengths with CT-equivalent densities that can be used in confidence throughout the entire RTP workflow. In Aim 1, we will perform geometric distortion corrections, determine distortion variability with changing anatomy, benchmark the results in a novel modular phantom, and develop an image processing toolkit. In Aim 2, we will fully automate MR image segmentation in the brain and male/female pelvis to yield accurate synthetic CT patient models derived from novel MRI sequences, including provisions for metal implants, and benchmark the results in phantom. In Aim 3, we will conduct end-to-end testing to characterize the uncertainties in the MR-only RTP workflow. We will perform a virtual clinical trial of MR-only RTP for brain and male/female pelvis and compare to the standard of care. Final translation will include developing physician-physicist practice guidelines, end-user validation of all translational steps, and dissemination of image processing tools into the Radiation Oncology community. This research will systematically address the major challenges limiting MR-only RTP and lay the groundwork for multi-institutional clinical trials across MRI platforms. It will support future work related to MR-guided RT, functional MRI for biologically adaptive RT, and focal RT to areas of high tumor burden.