| First Author | Chen HY | Year | 2017 |
| Journal | Cancer Res | Volume | 77 |
| Issue | 12 | Pages | 3207-3216 |
| PubMed ID | 28428273 | Mgi Jnum | J:242583 |
| Mgi Id | MGI:5905693 | Doi | 10.1158/0008-5472.CAN-16-2083 |
| Citation | Chen HY, et al. (2017) Assessing Prostate Cancer Aggressiveness with Hyperpolarized Dual-Agent 3D Dynamic Imaging of Metabolism and Perfusion. Cancer Res 77(12):3207-3216 |
| abstractText | New magnetic resonance (MR) molecular imaging techniques offer the potential for noninvasive, simultaneous quantification of metabolic and perfusion parameters in tumors. This study applied a three-dimensional dynamic dual-agent hyperpolarized 13C magnetic resonance spectroscopic imaging approach with 13C-pyruvate and 13C-urea to investigate differences in perfusion and metabolism between low- and high-grade tumors in the transgenic adenocarcinoma of mouse prostate (TRAMP) transgenic mouse model of prostate cancer. Dynamic MR data were corrected for T1 relaxation and RF excitation and modeled to provide quantitative measures of pyruvate to lactate flux (kPL ) and urea perfusion (urea AUC) that correlated with TRAMP tumor histologic grade. kPL values were relatively higher for high-grade TRAMP tumors. The increase in kPL flux correlated significantly with higher lactate dehydrogenase activity and mRNA expression of Ldha, Mct1, and Mct4 as well as with more proliferative disease. There was a significant reduction in perfusion in high-grade tumors that associated with increased hypoxia and mRNA expression of Hif1alpha and Vegf and increased ktrans , attributed to increased blood vessel permeability. In 90% of the high-grade TRAMP tumors, a mismatch in perfusion and metabolism measurements was observed, with low perfusion being associated with increased kPL This perfusion-metabolism mismatch was also associated with metastasis. The molecular imaging approach we developed could be translated to investigate these imaging biomarkers for their diagnostic and prognostic power in future prostate cancer clinical trials. Cancer Res; 77(12); 3207-16. (c)2017 AACR. |
