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

开发患者解剖模型以促进纯 MR 治疗计划

基本信息

批准号：
9306036
负责人：
Carri Kaye Glide-Hurst
金额：
$ 30.48万
依托单位：
HENRY FORD HEALTH SYSTEM
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-07-01 至 2021-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9306036
关键词：
3D Print Academia Address Anatomic Models Anatomy Area Atlases Benchmarking Biological Brain Clinic Clinical Collaborations Community Clinical Oncology Program Consensus Data Data Set Development Disease Dose Ensure Evaluation Female Functional Magnetic Resonance Imaging Future Generations Goals Health system Healthcare Hybrids Image Implant Industrialization Industry Magnetic Resonance Imaging Malignant Neoplasms Malignant neoplasm of brain Malignant neoplasm of cervix uteri Malignant neoplasm of prostate Measures Metals Modeling Multi-Institutional Clinical Trial Normal tissue morphology Organ Orthopedics Patient-Focused Outcomes Patients Pelvic Cancer Pelvis Phase Physicians Play Practice Guidelines Process Radiation Radiation Oncology Radiation therapy Research Research Personnel Residual state Resolution Risk Role Scanning Site Techniques Technology Testing Time Toxic effect Translating Translations Tumor Burden Uncertainty Validation Vendor Work X-Ray Computed Tomography base bone clinical practice correctional system cost density design digital dosimetry electron density image guided image guided radiation therapy image processing image reconstruction image registration imaging Segmentation imaging platform imaging system improved innovation innovative technologies interest male multidisciplinary novel patient population population based radiation risk simulation soft tissue standard of care tool treatment planning tumor virtual virtual clinical trial

项目摘要

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.

准确描绘放射治疗计划 (RTP) 中面临风险的目标和器官仍然是一个挑战由于计算机断层扫描 (CT)（RTP 的护理成像标准）缺乏软组织对比度。放射肿瘤学通过将磁共振图像 (MRI) 与 CT 配准解决了这一限制数据集以利用 MRI 提供的卓越软组织对比度。 MRI带来可观的价值通过提高描绘精度来实现 RTP，这反过来又使剂量递增能够改善局部控制同时维持或减少正常组织的毒性。然而，目前 MRI 作为辅助手段的整合 CT 具有显着的缺点，因为它需要图像配准和数据集之间的轮廓传输。这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 MR-only RTP 转化为临床应用，最终目标是改善通过改进治疗计划设计实现患者治疗效果。仅 MR 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，完全规避注册不确定性，并充分利用 MRI 的优势实现高精度 RTP。然而，MRI 通常并不单独使用对于 RTP，主要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剂量计算的在线图像引导和电子密度测绘所需。中心假设是我们的多学科学术/工业的创新技术（亨利·福特医疗系统/飞利浦医疗保健）合作开发将产生几何精确的患者根据跨多个平台/场强的 MRI 数据构建的模型，具有 CT 等效密度，可以在整个 RTP 工作流程中放心使用。在目标 1 中，我们将执行几何变形校正，确定随着解剖结构变化的变形变化，在新颖的模块化中对结果进行基准测试 phantom，并开发图像处理工具包。在目标 2 中，我们将完全自动化 MR 图像分割大脑和男性/女性骨盆，以产生源自新型 MRI 的准确合成 CT 患者模型序列，包括金属植入物的规定，并对模型中的结果进行基准测试。在目标 3 中，我们将进行端到端测试来表征仅 MR RTP 工作流程中的不确定性。我们将执行一个针对大脑和男性/女性骨盆的仅 MR RTP 的虚拟临床试验，并与护理标准进行比较。最终的翻译将包括制定医师-物理学家实践指南、所有翻译的最终用户验证步骤，并将图像处理工具传播到放射肿瘤学界。这项研究将系统地解决限制仅 MR RTP 的主要挑战，并为多机构奠定基础跨 MRI 平台的临床试验。它将支持与 MR 引导 RT、功能 MRI 相关的未来工作生物适应性放疗和针对高肿瘤负荷区域的局部放疗。