Core Laboratory for Advanced PET and MRI image analysis

摘要：本提案的目的是为NCI的具体目标提供技术先进的支持-- 华盛顿大学附属于NCI定量成像的医学成像资助项目 网络(QIN)和NCTN ECOG-ACRIN合作小组。我的医学成像生涯始于#年在威斯康星州大学 1985年，我有幸与迈克尔·格雷厄姆博士和亚历克斯·斯宾塞博士一起工作，他们为 定量分析和临床肿瘤学。我早期在PET成像方面的工作围绕着 管理动物成像项目，一个完整的生化实验室和一个新生的人类PET胶质瘤成像项目。 随着PET计划项目(P01-CA042045，Ka Krohn，PI)的发展，我们过渡到 人体成像和临床试验研究，使用大量PET探索不同的生化途径 放射性示踪剂。我开发了对运动图像数据的分区建模分析的热忱，最初是 詹姆斯·巴辛瓦特博士、迈克尔·格雷厄姆博士和芬巴尔·奥沙利文博士的指导，以及后来的合作 与托尼·希尔兹博士、大卫·曼科夫博士、珍妮特·埃里博士、汉娜·林登博士和保罗·基纳汉博士一起，他们都得到了 NCI拨款。我目前是成像核心实验室的主任，也是Paul Kinahan的U01基金的成员。我有过 负责参加QINI图像分析工作组，PET扩展规划 成像项目、成像方案以及为新实验设计数据分析方法。我是大四学生 我们整个计划的贡献者，以及数据管理的新方法的提供者，量化 放射学和肿瘤学中众多癌症项目的图像分析和数据模拟。由于成本的原因 关于成像、辐射剂量和其他问题，我个人的雄心是提取尽可能多的定量 使用PET放射性示踪剂进行精心设计和执行的癌症成像研究以及 先进的磁共振方法。我的职业目标是提供独立的，但协作的，支持特定的 与威斯康星大学、秦皇岛大学和ECOG-ACRIN合作，为医学成像项目提供NCI补助金的目的。另外，我还有 国家认可为ACRIN-UW PET核心实验室经理，ECOG-ACRIN负责人成员和 颈部、实验成像科学和脑肿瘤委员会，NIH-癌症委员会的关键成员 影像计划的秦氏工作组。我为动态成像开发的创新协议是 在从动态PET中提取定量信息方面有了实质性的改进，现在是全国 临床试验标准。我经常在国内和国际上展示我的先进的PET成像结果 科学会议(EORTC、SNMMI、WMIC、ACRIN和QIN/NCI)，每年出版/审查手稿 医学杂志。综上所述，我开发了一个全国公认的PET图像分析先进实验室， 资金完全来自NCI拨款，为期30年。NCI共享我的劳动力所获得的总体收益 NCI资助的项目将对现有的和新的调查人员产生影响，为他们提供量化的 使用稳健、可重复和经过验证的方法分析PET/CT和MRI图像数据的方法。

ABSTRACT: The goal of this proposal is to provide technically-advanced support for the specific aims of NCI- funded projects for medical imaging affiliated with the University of Washington, the NCI Quantitative Imaging Network (QIN), and the NCTN ECOG-ACRIN cooperative group. My medical imaging career began at UW in 1985, where I was fortunate to work with Drs. Michael Graham and Alex Spence, who laid the foundation for quantitative analysis and clinical oncology, respectively. My early work in PET imaging revolved around managing animal imaging projects, a full biochemistry lab and a nascent human PET glioma imaging program. As PET imaging developed under the PET Program Project (P01-CA042045, KA Krohn, PI), we transitioned to human imaging and clinical trials research, probing different biochemical pathways using numerous PET radiotracers. I developed an avidity for compartmental modeling analysis of kinetic image data, initially with guidance from Drs. James Bassingwaithe, Michael Graham and Finbarr O'Sullivan, and later in collaboration with Drs. Tony Shields, David Mankoff, Janet Eary, Hannah Linden and Paul Kinahan, all of them funded by NCI grants. I am currently Director of the Imaging Core lab and a member of Paul Kinahan's U01 grant. I have responsibility for participating in the image analysis working groups of the QIN, extended planning of PET imaging projects, imaging protocols and designing data analysis methods for new experiments. I am a senior contributor to our overall program as well as a provider of novel approaches to data management, quantitative image analysis and data simulations for numerous cancer projects in Radiology and Oncology. Due to the cost of imaging, the radiation dose and other issues, my personal ambition is to extract as much quantitative information as possible from well-designed and executed cancer imaging studies using PET radiotracers and advanced MR methods. My career goal is to provide independent, but collaborative, support for the specific aims of NCI grants for medical imaging projects at with UW, the QIN and ECOG-ACRIN. Additionally, I have national recognition as manager of the ACRIN-UW PET Core Lab, member of the ECOG-ACRIN Head and Neck, Experimental Imaging Sciences and Brain Tumor Committees, and a key member of the NIH-Cancer Imaging Program's QIN Working Groups. The innovative protocols I developed for dynamic imaging are a substantial improvement for extracting quantitative information from dynamic PET, and are now a national clinical trials standard. I routinely present my advanced PET imaging results at national and international scientific meetings (EORTC, SNMMI, WMIC, ACRIN and QIN/NCI) and publish/review manuscripts annually in medical journals. In summary, I have developed a nationally recognized advanced lab for PET image analysis, funded entirely through NCI grants for 30 years. The overall benefit NCI receives for sharing my labor across NCI funded projects will have an impact on current and new investigators, providing them with quantitative methods of analysis for PET/CT and MRI image data using robust, repeatable and validated methods.