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

NIH RePORTER · NIH · R01 · $648,493 · view on reporter.nih.gov ↗

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.

Key facts

NIH application ID
10588189
Project number
5R01CA262630-02
Recipient
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
Principal Investigator
Susan M Chang
Activity code
R01
Funding institute
NIH
Fiscal year
2023
Award amount
$648,493
Award type
5
Project period
2022-03-08 → 2027-02-28