# MR Fingerprinting based Quantitative Imaging and Analysis Platform (MRF-QIA) for brain tumors. > **NIH NIH R01** · CASE WESTERN RESERVE UNIVERSITY · 2024 · $531,269 ## Abstract Abstract The clinical utility of MR images is largely as a qualitative tool without in-built standardization, which requires subjective interpretation and time-consuming analysis. Importantly, these qualitative MRI approaches have demonstrated poor tissue characterization, and poor center-to- center reproducibility, greatly limiting their use in clinical trials. Availability of a robust quantitative imaging tool with high tissue discriminability can directly impact clinical care by offering actionable information to end-user clinicians. As an example, availability of accurate tumor infiltration maps in Glioblastomas, a highly aggressive brain tumor, can pave the way for novel multisite clinical trials in personalized radiation therapy and neurosurgery for improved outcomes. None of the current MRI techniques offer this capability in an accurate and reproducible manner. MRF is a quantitative imaging scan that can address the limitations of qualitative MRI by providing reproducible and physiologically meaningful measurements of tissue properties. We have also shown that utilizing the underlying physical/physiological bounds of the quantitative MRF values improves the reproducibility of the image analysis techniques. Integration of MRF and advanced quantitative analytics could fundamentally address the well-recognized low-reproducibility in qualitative MRI approaches and allow broad clinical translation. In this proposal, we have established an academic-industrial partnership among MRF developers (CWRU), image analysis and AI experts (UPenn), Brain tumor imaging experts (UHCMC), and leading healthcare company (Siemens) to ensure successful clinical translation of the MRF-QIA into the clinical workflow. We will achieve our goal with the following aims: Aim 1: Establish a high throughput MRF scan and assess multisite performance for FDA approval; Aim 2: Fully integrate the MRF-QIA image analytics software into the clinical system for brain tumor analysis; Aim 3: Clinical validation of the MRF-QIA application for infiltration prediction in Glioblastoma patients. This project will add new capabilities to the clinical flow directly impacting the end-user experience and patient care: 1) FDA approval of MRF product scan will allow any Siemens clinical site to add it to their routine patient scans. 2) The MRF-QIA software will be distributed globally through Siemens Global Digital Market and will be available for broad clinical and multisite research applications. 3) The specialized application for GB infiltration prediction will lead to new clinical trials for planning targeted biopsy, extended resections, and personalized radiotherapy by neurosurgeons and neuro-oncologists to eventually provide targeted treatment plans for GB patients. ## Key facts - **NIH application ID:** 10753556 - **Project number:** 5R01CA269604-02 - **Recipient organization:** CASE WESTERN RESERVE UNIVERSITY - **Principal Investigator:** Chaitra Badve - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $531,269 - **Award type:** 5 - **Project period:** 2023-01-01 → 2027-12-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10753556 ## Citation > US National Institutes of Health, RePORTER application 10753556, MR Fingerprinting based Quantitative Imaging and Analysis Platform (MRF-QIA) for brain tumors. (5R01CA269604-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10753556. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*