Quantitative Steady-State and Dynamic Metabolic MRI for Evaluating Patients with Glioma

项目摘要 加州大学旧金山分校和GE团队将通过开发 一套硬件和软件工具，可提供改进的成像自动处方策略 序列，以减少操作员差异，提供更广泛的病变覆盖范围，并使改进 序列比较。我们还将简化和简化对结果数据的处理和解释 通过使用我们的开源、兼容DICOM的软件包SIVIC。这将包括一些功能以便于 评估来自系列成像检查的数据，以及扩展可用于 解决更复杂类型的代谢成像数据的分析。另一个关键组成部分是 建议将完善成像和组织采集工作流程，并整合收集的定量数据 临床环境中的生物标记物。

Project Summary The UCSF and GE team will address the limitations of current MR metabolic imaging approaches by developing a package of hardware and software tools to provide improved strategies for automatic prescription of imaging sequences to reduce operator differences, provide more extensive coverage of the lesion and enable improved serial comparisons. We will also simplify and streamline the processing and interpretation of the resulting data by using our open source, DICOM compatible software package, SIVIC. This will include features to facilitate the assessment of data from serial imaging examinations, as well as expanding the algorithms available to address the analysis of more complex types of metabolic imaging data. A further critical component of the proposal will be to refine the imaging and tissue acquisition workflow and integration of collected quantitative biomarkers in the clinical setting.