Dataset Information

Simultaneous Metabolic and Perfusion Imaging Using Hyperpolarized ¹³C MRI Can Evaluate Early and Dose-Dependent Response to Radiation Therapy in a Prostate Cancer Mouse Model.

ABSTRACT:

Purpose

To investigate use of a novel imaging approach, hyperpolarized (HP) ¹³C magnetic resonance imaging (MRI) for simultaneous metabolism and perfusion assessment, to evaluate early and dose-dependent response to radiation therapy (RT) in a prostate cancer mouse model.

Methods and materials

Transgenic Adenocarcinoma of Mouse Prostate (TRAMP) mice (n = 18) underwent single-fraction RT (4-14 Gy steep dose across the tumor) and were imaged serially at pre-RT baseline and 1, 4, and 7 days after RT using HP ¹³C MRI with combined [1-¹³C]pyruvate (metabolic active agent) and [¹³C]urea (perfusion agent), coupled with conventional multiparametric ¹H MRI including T2-weighted, dynamic contrast-enhanced, and diffusion-weighted imaging. Tumor tissues were collected 4 and 7 days after RT for biological correlative studies.

Results

We found a significant decrease in HP pyruvate-to-lactate conversion in tumors responding to RT, with concomitant significant increases in HP pyruvate-to-alanine conversion and HP urea signal; the opposite changes were observed in tumors resistant to RT. Moreover, HP lactate change was dependent on radiation dose; tumor regions treated with higher radiation doses (10-14 Gy) exhibited a greater decrease in HP lactate signal than low-dose regions (4-7 Gy) as early as 1 day post-RT, consistent with lactate dehydrogenase enzyme activity and expression data. We also found that HP [¹³C]urea MRI provided assessments of tumor perfusion similar to those provided by ¹H dynamic contrast-enhanced MRI in this animal model. However, apparent diffusion coefficien , a conventional ¹H MRI functional biomarker, did not exhibit statistically significant changes within 7 days after RT.

Conclusion

These results demonstrate the ability of HP ¹³C MRI to monitor radiation-induced physiologic changes in a timely and dose-dependent manner, providing the basic science premise for further clinical investigation and translation.

SUBMITTER: Qin H

PROVIDER: S-EPMC7381368 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Modern oncology aims at patient-specific therapy approaches, which triggered the development of biomedical imaging techniques to synergistically address tumor biology at the cellular and molecular level. PET/MR is a new hybrid modality that allows acquisition of high-resolution anatomic images and quantification of functional and metabolic information at the same time. Key steps of the Warburg effect-one of the hallmarks of tumors-can be measured non-invasively with this emerging technique. The aim of this study was to quantify and compare simultaneously imaged augmented glucose uptake and LDH activity in a subcutaneous breast cancer model in rats (MAT-B-III) and to study the effect of varying tumor cellularity on image-derived metabolic information. Methods: For this purpose, we established and validated a multimodal imaging workflow for a clinical PET/MR system including proton magnetic resonance (MR) imaging to acquire accurate morphologic information and diffusion-weighted imaging (DWI) to address tumor cellularity. Metabolic data were measured with dynamic [18F]FDG-PET and hyperpolarized (HP) 13C-pyruvate MR spectroscopic imaging (MRSI). We applied our workflow in a longitudinal study and analyzed the effect of growth dependent variations of cellular density on glycolytic parameters. Results: Tumors of similar cellularity with similar apparent diffusion coefficients (ADC) showed a significant positive correlation of FDG uptake and pyruvate-to-lactate exchange. Longitudinal DWI data indicated a decreasing tumor cellularity with tumor growth, while ADCs exhibited a significant inverse correlation with PET standard uptake values (SUV). Similar but not significant trends were observed with HP-13C-MRSI, but we found that partial volume effects and point spread function artifacts are major confounders for the quantification of 13C-data when the spatial resolution is limited and major blood vessels are close to the tumor. Nevertheless, analysis of longitudinal data with varying tumor cellularity further detected a positive correlation between quantitative PET and 13C-data. Conclusions: Our workflow allows the quantification of simultaneously acquired PET, MRSI and DWI data in rodents on a clinical PET/MR scanner. The correlations and findings suggest that a major portion of consumed glucose is metabolized by aerobic glycolysis in the investigated tumor model. Furthermore, we conclude that variations in cell density affect PET and 13C-data in a similar manner and correlations of longitudinal metabolic data appear to reflect both biochemical processes and tumor cellularity.