Real-Time Volumetric Imaging for Lung Cancer Radiotherapy

肺癌放射治疗的实时体积成像

• 批准号: 8921946
• 负责人: Ruijiang Li
• 金额: $ 24.22万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-02 至 2017-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8921946
• 关键词: Accounting; Address; Adopted; Affect; Algorithms; Anatomy; Award; Breathing; Cancer Patient; Clinical; Data; Data Set; Dose; Future; Goals; Grouping; Image; Imaging Device; Imaging Techniques; Intervention; Knowledge; Lead; Lifting; Linear Accelerator Radiotherapy Systems; Liver; Lung; Lung Neoplasms; Malignant neoplasm of lung; Medical; Mentors; Methodology; Methods; Modeling; Morphologic artifacts; Motion; Nature; Normal tissue morphology; Outcome Study; Pancreas; Pathology; Patients; Performance; Phase; Positioning Attribute; Process; Quality of life; Radiation; Radiation therapy; Research; Research Personnel; Research Project Grants; Research Training; Respiration; Rotation; Safety; Series; Site; Statistical Models; Techniques; Therapeutic; Time; Toxic effect; Training; Universities; Work; X-Ray Computed Tomography; base; cancer radiation therapy; career; career development; clinically significant; digital; flexibility; image guided; image reconstruction; imaging modality; imaging system; improved; innovation; lung volume; medical schools; meetings; parallel computer; programs; reconstruction; research and development; respiratory; signal processing; simulation; time use; tool; treatment duration; tumor

Interfraction anatomic changes and intrafraction respiratory motion are the major limiting factors for escalating radiation dose and improving local control in lung cancer radiotherapy. The advent of on-board x-ray imaging device mounted on the medical linear accelerator (LINAC) has provided a tool to obtain valuable anatomic information of the patient in the treatment position. However, due to the slow rotating nature of the on-board imaging system (~1 min per rotation), obtaining volumetric information in real time is extremely challenging. Existing methods have relied on grouping many projections acquired over multiple breathing cycles for several minutes to reconstruct one static anatomy. Further, due to the fact that lung cancer patients tend to breathe irregularly, the reconstructed images are often heavily contaminated by breathing motion artifacts. The goal of this research project is to develop innovative real-time volumetric imaging methods that are able to reconstruct the dynamic patient anatomy in real time (~0.1 s) using a single x-ray projection during dose delivery. This bold goal is made practical by three integral components: effective use of an accurate patient-specific lung motion model, advanced compressed sensing techniques for image reconstruction, and a massively parallel and yet affordable computing platform based on graphics processing units (GPU). During the mentored K99 phase, the candidate will draw on his signal processing and statistical modeling expertise to improve and optimize the patient-specific lung motion model while gaining knowledge in lung patient anatomy and pathology, and to quantitatively evaluate the lung motion model and interpret the clinical significance of the results. During the independent R00 phase, a real-time volumetric imaging method which captures both interfraction anatomical changes and intrafraction breathing motion, will be developed, implemented, and evaluated through systematic phantom and patient studies. Successful completion of this project will overcome a critical barrier to the urgently needed real-time volumetric image guidance in lung cancer radiotherapy and afford a powerful way for us to safely escalate the radiation dose and improve local control of lung cancer. This project fits perfectly with the candidate’s long-term career goal of establishing a high-quality independent research program to develop state-of-the-art x-ray imaging techniques, which will provide real-time image guidance for cancer radiotherapy and ultimately improve the therapeutic ratio and enhance the quality of life for cancer patients. Career development and research training will be an integral component during the mentored phase of this project. This training will be further supplemented with formal coursework at Stanford University School of Medicine, as well as participation in research seminars and scientific meetings. The training and research contributions supported by this K99/R00 award will substantially enhance the candidate’s career and serve to establish him as a successful independent investigator in the near future.

分次间的解剖变化和分次内的呼吸运动是呼吸强度升高的主要限制因素。 提高肺癌放疗的局部控制。机载X射线成像的出现 安装在医用直线加速器（LINAC）上的装置提供了一种工具， 患者在治疗位置的信息。然而，由于船上的缓慢旋转性质， 成像系统（每次旋转约1分钟），真实的时间获得体积信息是极具挑战性的。 现有的方法依赖于对在多个呼吸周期内获得的许多投影进行分组， 重建一个静态解剖结构此外，由于肺癌患者倾向于呼吸 不规则的是，重建的图像经常被呼吸运动伪影严重污染。的目标 该研究项目旨在开发创新的实时体积成像方法， 在剂量输送期间使用单个X射线投影以真实的时间（~0.1 s）动态观察患者解剖结构。这个大胆 通过三个组成部分实现目标：有效使用准确的患者特异性肺运动 模型，用于图像重建的先进压缩传感技术，以及一个大规模并行但 基于图形处理单元（GPU）的经济实惠的计算平台。在辅导K99阶段， 候选人将利用他的信号处理和统计建模专业知识，以改善和优化 患者特定的肺部运动模型，同时获得肺部患者解剖学和病理学知识， 定量评估肺运动模型并解释结果的临床意义。期间 独立R 00相位，一种实时体积成像方法， 变化和分次内呼吸运动，将通过系统的 体模和患者研究。该项目的成功完成将克服一个关键的障碍， 实时容积图像引导技术是肺癌放疗中急需的一种新技术， 我们可以安全地增加辐射剂量，改善肺癌的局部控制。这个项目完全符合 候选人的长期职业目标，建立一个高质量的独立研究计划，以发展 最先进的X射线成像技术，将为癌症放射治疗提供实时图像指导 并最终提高癌症患者的治疗率和生活质量。职业生涯 发展和研究培训将是该项目辅导阶段的一个组成部分。 该培训将进一步补充斯坦福大学医学院的正式课程， 以及参加研究研讨会和科学会议。培训和研究贡献 在K99/R 00奖项的支持下，将大大提高候选人的职业生涯，并有助于建立他 成为一名成功的独立调查员