Quantitative Imaging to Assess Response in Cancer Therapy Trials

定量成像评估癌症治疗试验中的反应

基本信息

批准号：
8034225
负责人：
JOHN M. BUATTI
金额：
$ 56万
依托单位：
UNIVERSITY OF IOWA
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-04-01 至 2015-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8034225
关键词：
Acetates Address Algorithms Antineoplastic Protocols Beds Bioinformatics Calibration Cancer Patient Cancer Research Network Clinical Clinical Data Clinical Trials Collaborations Commit Communities Community Clinical Oncology Program Complex Computer software Computers Data Data Set Databases Decision Making Development Dopa Drug Kinetics Early treatment Engineering Environment Evaluation Faculty Financial compensation Four-dimensional Funding Future Glioma Goals Head and Neck Cancer Healthcare Human Image Image Analysis Imaging Device Informatics Institutes Iowa Lead Lung Magnetic Resonance Imaging Magnetic Resonance Spectroscopy Malignant Neoplasms Malignant neoplasm of lung Manuals Measurement Measures Metadata Methods Metric Modeling NIH Program Announcements Oncologist Outcome PET/CT scan Participant Phase Phase I Clinical Trials Phase II Clinical Trials Play Positron-Emission Tomography Principal Investigator Procedures Reproducibility Research Research Infrastructure Research Project Grants Scientist Secure Software Tools Specialist Systems Development Technology Testing Tracer Universities Validation Work base bioimaging cancer Biomedical Informatics Grid cancer imaging cancer therapy clinical decision-making clinically relevant design driving force experience head and neck cancer patient image archival system imaging modality improved indexing middleware molecular imaging novel oncology open source programs public-private partnership quality assurance relational database response system architecture tool tool development translational study tumor uptake working group

项目摘要

DESCRIPTION (provided by applicant): At the University of Iowa we have assembled a remarkably strong team of oncologists, clinical imaging specialists, computer scientists, imaging and therapy physicists, bioinformatics specialists, and statisticians, as well as collaboration with NIST and a public/private partnership with Siemens. This group is an ideal team to address the goals of this UOI Program Announcement and contribute robustly to the envisioned Quantitative Imaging Network (QIN). We plan to achieve our goals through: Specific Aim 1: Create an accessible environment for quantitative image analysis tool development and testing using an existing large H&N cancer dataset and caBIG. 1a: We plan to design and deploy a broadly connected informatics system architecture to support a locally networked relational database for development, implementation and validation of shared tools to the QIN through caBIG and the National Cancer Imaging Archive (NCIA). 1b: We will Interface our large PET/CT imaging and clinical outcomes database of pre and post therapy H&N cancer patients as a universally accessible test database that will be shared with the QIN. Specific Aim 2: Develop novel semi-automated tools for quantitative image-based response assessment. 2a: We will design, implement, and validate open source 2D and 3D semi- automated quantitative image analysis tools for tumor definition and quantitative metrics applicable to response assessment. We will also develop and apply advanced decision-support software as well as measurement variability tools so that image analysis tools can be compared and optimally selected for clinical cancer trials. 2b. We will test these image analysis tools on the imaging and clinical data to assess applicability and accessibility by QIN. Specific Aim 3: Establish robust quality procedures and standards for quantitative imaging, working with NIST and the QIN to enhance the quality and reliability of quantitative imaging for clinical decision-making. 3a: Define and validate calibration procedures, tools and standards for PET imaging using a Ge-68 NIST-traceable phantom. 3b: Define and validate robust quality assurance tools and standards for 4D PET/CT 3c: Define similar tools and standards for quantitative imaging response assessment using ACR and GE phantoms for MRI, including MRSI. Specific Aim 4: Adapt and Enhance Quantitative Image-based Response Assessment for Clinical Trials Decision-Support. 3a: In an existing, NCI-funded study of FDG and F-18 fiuorothymidine in head and neck cancer patients. 3b In an existing, NCI-funded study of FDG and C-11 acetate imaging in lung cancer and 3c: In a planned clinical trial of MRSI and F-18 fluorodopa in high-grade gliomas.

描述（由申请人提供）：在爱荷华大学，我们组建了一个非常强大的肿瘤学家，临床成像专家，计算机科学家，成像和治疗物理学家，生物信息学专家以及统计学家，以及与NIST和NIST和公共/////公共////公共/与西门子的私人伙伴关系。该小组是一个理想的团队，可以解决该UOI计划公告的目标，并为设想的定量成像网络（QIN）做出贡献。我们计划通过：特定目标1：创建一个可访问的环境，以使用现有的大型H＆N癌症数据集和Cabig创建可访问的环境，以进行定量图像分析工具开发和测试。 1A：我们计划设计和部署广泛连接的信息学系统体系结构，以支持本地网络的关系数据库，以开发，实施和验证共享工具通过Cabig和国家癌症成像档案（NCIA）向QIN提供共享工具。 1B：我们将在治疗前和治疗后H＆N癌症患者的大型PET/CT成像和临床结果数据库中连接，作为一个可与QIN共享的普遍可访问的测试数据库。特定目的2：开发新型的半自动化工具，用于基于定量图像的响应评估。 2A：我们将设计，实施和验证开源2D和3D半自动化的定量图像分析工具，用于肿瘤定义和适用于响应评估的定量指标。我们还将开发和应用高级决策支持软件以及测量变异性工具，以便可以比较图像分析工具并最佳地选择用于临床癌症试验。 2b。我们将在成像和临床数据上测试这些图像分析工具，以评估QIN的适用性和可访问性。特定目的3：建立稳健的质量程序和标准，以进行定量成像，与NIST和QIN合作，以提高定量成像的质量和可靠性以进行临床决策。 3A：使用可通过GE-68 NIST可跟踪的幻影定义和验证校准程序，工具和标准，用于PET成像。 3B：为4D PET/CT 3C定义并验证稳健的质量保证工具和标准：使用ACR和GE Phantoms对MRI（包括MRSI）定义了类似的定量成像响应评估的工具和标准。特定目标4：适应并增强基于图像的基于图像的响应评估，以进行临床试验决策支持。 3A：在头颈癌患者中，在现有的NCI资助的FDG和F-18 Fiuorothymidine研究中。 3B在肺癌和3C中的FDG和C-11乙酸盐成像的现有，NCI资助的研究中：在高级神经胶质瘤中MRSI和F-18氟da的计划的临床试验中。