# Dynamic Nuclear Polarization MR Spectroscopic Imaging for Diagnosis and Treatment Response Assessment in Hepatocellular Carcinoma

> **NIH NIH R01** · UNIVERSITY OF PENNSYLVANIA · 2022 · $580,459

## Abstract

Hepatocellular carcinoma (HCC) is the most rapidly rising cause of cancer mortality in the United States. The
majority of patients with HCC present with incurable disease at diagnosis and, despite the approval of targeted
therapies, life expectancy remains less than 20 months. The diagnosis of HCC as well as its response to
treatment rely primarily on imaging biomarkers which have replaced tissue-based methods. Recent studies
demonstrate that the dismal prognosis for these patients issues, at least in part, from deficiencies of current
clinical imaging paradigms in diagnosing HCC as well as in identifying residual or recurrent HCC after treatment.
Clinical imaging paradigms for HCC diagnosis and the assessment of treatment response are based on anatomic
imaging features that often fail to identify HCCs or provide functional measures of response to targeted therapies.
Indeed, the sensitivity of standard-of-care (SOC) contrast-enhanced (CE) MRI for small HCCs can be as low as
20%. Similarly, SOC imaging provides inadequate assessments of response to therapies. Addressing this
deficiency requires the development of new imaging paradigms that provide functional measures of HCC biology
to improve accuracy, sensitivity and specificity as well as inform the application of therapeutics.
The development of novel functional imaging strategies for HCC has been limited by the absence of
methodologies that can tailor imaging probe selection to the relevant HCC biology as well as a dearth of
representative animal models. Using genome editing and metabolomics, our laboratory has demonstrated the
fundamental dependence of HCC cells on lactate dehydrogenase and NADPH-dependent reductases to be
promising imaging targets for Dynamic Nuclear Polarization 13Carbon Magnetic Resonance Spectroscopic
Imaging (DNP-13C-MRSI), an emerging imaging technology. The proposed project will build on this prior work to
study the ability of DNP-13C-MRSI to: 1) improve the accuracy of diagnosis and treatment response assessment
of HCC following SOC therapies as compared to conventional imaging and 2) inform treatment selection.
We hypothesize that DNP-13C-MRSI provides a unique technology through which to leverage fundamental
enzymatic dependencies of HCC cells and enable functional molecular imaging for diagnosis and treatment
response assessment. To test this hypothesis the proposed project will use unique animal models of HCC
developed in our lab to pursue three aims: (1) to optimize a DNP-13C-MRSI pulse sequence that enables
sensitive, accurate and reproducible measurements of regional pyruvate metabolism in autochthonous HCCs
at high spatial resolution; (2) to determine the sensitivity, specificity and accuracy of DNP-13C-MRSI of HP 1-13C-
pyruvate uptake and metabolism for identifying HCCs; and (3) to determine the accuracy of DNP-13C-MRSI of
HP 1-13C-pyruvate and/or 1-13C-dehydroascorbic acid (DHA) for identifying and characterizing residual
disease/local recurrence following ...

## Key facts

- **NIH application ID:** 10367551
- **Project number:** 1R01CA258715-01A1
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Terence P Gade
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $580,459
- **Award type:** 1
- **Project period:** 2022-01-05 → 2026-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10367551

## Citation

> US National Institutes of Health, RePORTER application 10367551, Dynamic Nuclear Polarization MR Spectroscopic Imaging for Diagnosis and Treatment Response Assessment in Hepatocellular Carcinoma (1R01CA258715-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10367551. Licensed CC0.

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