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.

分次间解剖变化和分次内呼吸运动是升级的主要限制因素 放射剂量和改善肺癌放射治疗的局部控制。机载 X 射线成像的出现。 安装在医用直线加速器 (LINAC) 上的设备提供了一种获得有价值的解剖学信息的工具 然而，由于机载设备旋转速度慢，因此无法获取处于治疗位置的患者的信息。 成像系统（每次旋转约 1 分钟），实时获取体积信息极具挑战性。 现有方法依赖于对多个呼吸周期中获得的许多预测进行分组 此外，由于肺癌患者倾向于呼吸，因此需要几分钟的时间来重建一个静态解剖结构。 不规则的是，重建的图像常常受到呼吸运动伪影的严重污染。 该研究项目旨在开发创新的实时体积成像方法，能够重建 在剂量输送期间使用单个 X 射线投影实时（~0.1 秒）动态患者解剖结构。 该目标通过三个组成部分得以实现： 有效利用准确的患者特定肺运动 模型、用于图像重建的先进压缩感知技术以及大规模并行且尚未实现的 基于图形处理单元 (GPU) 的经济型计算平台 在 K99 指导阶段， 候选人将利用他的信号处理和统计建模专业知识来改进和优化 患者特定的肺运动模型，同时获得有关肺患者解剖学和病理学的知识，并 定量评估肺运动模型并解释结果的临床意义。 独立的 R00 相位，一种实时体积成像方法，可捕获交叉解剖结构 变化和分次内呼吸运动，将通过系统性的开发、实施和评估 模型和患者研究的成功完成将克服一个关键障碍。 肺癌放射治疗中迫切需要的实时体积图像引导，并为 我们安全地增加辐射剂量并改善肺癌的局部控制。 候选人的长期职业目标是建立高质量的独立研究项目来开发 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 最终提高癌症患者的治疗率并提高生活质量。 开发和研究培训将是该项目指导阶段不可或缺的组成部分。 该培训将得到斯坦福大学医学院的正式课程的进一步补充，如 以及参加研究研讨会和科学会议的培训和研究贡献。 获得 K99/R00 奖项的支持将极大地提升候选人的职业生涯并有助于奠定他的地位 在不久的将来成为一名成功的独立调查员。