Accurate Target Delineation and Motion Tracking to Improve IMRT Effectiveness

准确的目标描绘和运动跟踪可提高 IMRT 有效性

• 批准号: 7259200
• 负责人: Xiaodong Wu
• 金额: $ 14.48万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-07-19 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7259200
• 关键词: 3-Dimensional; Abdomen; Address; Algorithms; Appointment; Area; Arts; Automobile Driving; Biomedical Computing; Breathing; Class; Clinical; Complex; Computers; Data; Detection; Dose; Effectiveness; Engineering; Environment; Financial compensation; Foundations; Graph; Group Meetings; Healthcare; Human; Image; Intensity-Modulated Radiotherapy; Interobserver Variability; Ionizing radiation; Iowa; Joints; K-Series Research Career Programs; Knowledge; Localized; Malignant Neoplasms; Malignant neoplasm of thorax; Manuals; Maps; Measurable; Measures; Medical Computer Science; Medical Imaging; Mentors; Methods; Modality; Modeling; Motion; Movement; NIH Program Announcements; Nature; Normal tissue morphology; Organ; Phase; Plant Roots; Procedures; Public Health; Radiation; Radiation Oncology; Radiation therapy; Research; Research Personnel; Research Project Grants; Science; Shapes; Software Tools; Solutions; Source; Stomach; Structure; Surface; Survival Rate; System; Techniques; Technology; Testing; Time; Tissues; Treatment Effectiveness; Treatment Efficacy; Tubular formation; Universities; Upper arm; Weight; Work; base; cancer therapy; career; clinical application; design; experience; imaging Segmentation; improved; interest; multidisciplinary; neoplastic cell; novel; optical imaging; research clinical testing; response; symposium; tool; treatment planning; tumor

DESCRIPTION (provided by applicant): The proposed K25 career development award will allow the candidate to become an independent and successful researcher in the emerging multidisciplinary biomedical computing area armed with a unique set of knowledge and breadth of experience both in computational and biomedical sciences. The University of Iowa with a well-rooted multidisciplinary culture, has newly established the Center of Excellence in Image-Guided Radiation Therapy, a world-class radiation therapy facility. In this excellent environment, the candidate, having a joint appointment at Departments of Electrical & Computer Engineering and Radiation Oncology, will develop his research career through (i) taking courses in radiation therapy and medical imaging; (ii) presenting research results at the most pertinent medical and computer science conferences; (iii) attending research group meetings and clinical evaluation and planning meetings at the Center. The research project of the candidate is to develop novel algorithms, methods, and software tools that make use of the latest advances in computer science and medical imaging for accurate target definition and motion tracking, thus improving the treatment effectiveness of Intensity-Modulate Radiation Therapy (IMRT). Target delineation and intra-fraction organ motion are two major sources that compromise the treatment effectiveness of IMRT. The computational feasibility is accomplished by formulating the target delineation and motion tracking problems as computing an optimal closed set in a weighted directed graph. The novel features of our method will be designed with a continuing focus on the global optimality of the solution. We hypothesize that advanced graph algorithmic and geometric techniques enable accurate target delineation and precise tracking of internal tumor/organ motion, thus improving IMRT effectiveness. The specific aims of the proposed research are as follows: 1) Develop and validate a method for the optimal delineation of single and multiple interacting surfaces in volumetric image data; surfaces with terrain-like, tubular, and closed shapes as well as those with complex topologies will be included. 2) Develop and validate a method for tracking optimal organ motion over the treatment course using 4-D image data. 3) Develop and validate a method for accurate tissue voxel mapping which enables to transfer a 3-D treatment plan at one motion phase to all other phases to form a 4-D treatment plan. Public Health Relevance: We expect the clinical applications of the proposed approaches will have a measurable improvement on IMRT treatment effectiveness, leading to a better local tumor control and a significant increase of cancer survival rate.

描述（由申请人提供）：拟议的K25职业发展奖将使候选人成为新兴的多学科生物医学计算领域的独立和成功的研究人员，并拥有具有独特的计算和生物医学科学经验的独特知识和广度。爱荷华大学具有良好的多学科文化，新建立了图像引导放射疗法卓越中心，这是世界一流的放射治疗设施。在这种出色的环境中，候选人在电气和计算机工程和放射肿瘤学部门联合任命，将通过（i）参加放射治疗和医学成像课程来发展其研究生涯； （ii）在最相关的医学和计算机科学会议上介绍研究结果； （iii）参加中心的研究小组会议以及临床评估和计划会议。 候选人的研究项目是开发新颖的算法，方法和软件工具，这些工具利用计算机科学和医学成像方面的最新进展，以进行准确的目标定义和运动跟踪，从而提高了强度 - 调节放射治疗（IMRT）的治疗有效性。目标描绘和分数内器官运动是损害IMRT治疗有效性的两个主要来源。计算可行性是通过制定目标描述和运动跟踪问题来实现的，因为计算加权有向图中的最佳封闭设置。我们方法的新颖特征将以不断的关注解决方案的全球最优性进行设计。我们假设先进的图算法和几何技术可以准确地划分和内部肿瘤/器官运动的精确跟踪，从而提高IMRT效率。拟议研究的具体目的如下： 1）开发和验证一种在体积图像数据中最佳描述单个和多个相互作用表面的方法；将包括具有地形，管状和闭合形状以及具有复杂拓扑的表面。 2）开发和验证一种使用4-D图像数据在治疗过程中跟踪最佳器官运动的方法。 3）开发和验证一种用于精确组织体素映射的方法，该方法使一个运动阶段的3-D治疗计划可以将3-D治疗计划转移到所有其他阶段，以形成4-D治疗计划。 公共卫生相关性：我们预计拟议方法的临床应用将对IMRT治疗效率有了可衡量的改善，从而导致更好的局部肿瘤控制和癌症存活率的显着提高。