# Translating Hyperpolarized 13C Metabolic MRI to Predict Renal Tumor Aggressiveness

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2022 · $590,068

## Abstract

Project summary:
This project aims to clinically translate hyperpolarized (HP) 13C pyruvate MRI as an innovative metabolic imaging
approach for noninvasive prediction of renal tumor aggressiveness, an unmet clinical need. Our study is in direct
response to PAR 19-264 that supports “The optimization, application and validation of emerging imaging or
biomarker approaches targeted specifically for clinical application”, with the goals to “reduce overdiagnosis”, and
“identify lethal cancers from non-lethal disease”. Our project is motivated by the rising incidence of renal tumors,
largely due to the increased utilization of imaging with incidental discovery of many localized tumors. These
include both benign renal tumors and malignant renal cell carcinomas (RCCs). Current imaging or biopsies
cannot reliably differentiate between benign tumors, low grade RCCs, and high grade RCCs. The diagnostic
ambiguity has led to an overdiagnosis of many indolent tumors which are unnecessarily treated by surgery with
surgical risks, and importantly, increased risk of chronic kidney disease and associated cardiovascular disease.
Notably, the increased detection of RCCs has not translated into a decrease in cancer specific death. Therefore,
there is a significant unmet need for novel imaging markers that can improve the risk stratification of
localized renal tumors to guide patient management. HP 13C MRI is an emerging imaging technology that
allows real-time pathway-specific investigation of metabolic processes that were previously inaccessible by
imaging. Our pre-clinical data in orthotopic RCC tumor models have shown that HP 13C pyruvate MRI can
quantitatively map the increased pyruvate-to-lactate metabolism via the lactate dehydrogenase pathway, an
imageable biomarker which is strongly linked to the presence of RCC and its aggressiveness. We have also
demonstrated the feasibility of acquiring dynamic HP 13C pyruvate MRI of renal tumors in patients, with excellent
metabolic contrast between tumor and normal kidney. Building upon these promising preliminary data, we now
propose to investigate for the first time the value of HP 13C pyruvate MRI for risk stratifying localized renal tumors.
Aim 1- we will optimize the MRI acquisition strategies for renal tumor metabolic evaluation. Aim 2- we will
investigate the value of HP 13C pyruvate MRI for differentiating between benign tumors, low grade RCCs, and
high grade RCCs. We will also compare HP 13C data to advanced 1H MRI and radiomics analyses, and develop
multi-parametric model to assess whether it can improve the prediction. Aim 3- we will determine the repeatability
of HP 13C pyruvate MRI of renal tumors, and evaluate new analysis methods to further improve the robustness
of metabolism quantification. Successful completion of this project will provide the first data on the value of HP
13C pyruvate MRI in predicting renal tumor aggressiveness, and will pave the way for future larger clinical studies.
HP 13C pyruvate ...

## Key facts

- **NIH application ID:** 10318924
- **Project number:** 5R01CA249909-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Peder Eric Zufall Larson
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $590,068
- **Award type:** 5
- **Project period:** 2021-01-01 → 2025-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10318924

## Citation

> US National Institutes of Health, RePORTER application 10318924, Translating Hyperpolarized 13C Metabolic MRI to Predict Renal Tumor Aggressiveness (5R01CA249909-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10318924. Licensed CC0.

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