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

University Of California, San Francisco, San Francisco CA

Investigators

Linked publications & trials

Abstract

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.