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 has already been shown to be safe, and we envision the 13C metabolic imaging markers to be incorporated into a state-of-the-art multi-parametric MRI to reduce the current overdiagnosis of indolent tumors while enabling the early detection of aggressive RCCs, and help safely select patients for active surveillance.

Public Health Relevance

There has been a significant increase in incidentally discovered localized renal tumors, and it remains a challenge to reliably and noninvasively differentiate benign tumors from renal cancers or differentiate low grade from high grade renal cancers. In this study, we will apply a powerful imaging technology, hyperpolarized 13C metabolic MRI, to renal tumors for the first time to address an unmet need for noninvasive predictors of tumor aggressiveness. Successful completion of this work will aid in future management of patients with renal tumors by reducing the current overdiagnosis and treatment of indolent tumors while enabling early detection of aggressive renal cancers that require timely surgery.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
1R01CA249909-01A1
Application #
10068269
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Zhang, Huiming
Project Start
2021-01-01
Project End
2025-12-31
Budget Start
2021-01-01
Budget End
2021-12-31
Support Year
1
Fiscal Year
2021
Total Cost
Indirect Cost
Name
University of California San Francisco
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94143