Featured Publications
Translation of hyperpolarized [13C, 15N2]urea MRI for novel human brain perfusion studies
Authors: Kim Y, Chen HY, Nickles T, Shkliar I, Dang D, Slater J, Wang C, Gordon JW, Tan CT, Suszczynski C, Maddali S, Gaunt A, Chen R, Villanueva-Meyer J, Xu D, Larson PEZ, Kurhanewicz J, Bok RA, Chang S, Vigneron DB
Conclusions: We successfully developed and optimized a new SOP for the on-site production of sterile hyperpolarized (HP) urea for the first time, following Good Manufacturing Practice (GMP) guidelines. To dissolve solid urea and achieve a DNP-compatible sample with ~9 M urea concentration, lactic acid was used as a solvent due to its similar physical properties to pyruvic acid (i.e., a self-glassing agent). The urea/lactic acid/electron paramagnetic agent (EPA) mixture, sterile water for injection (SWFI) for dissolution, and buffer for neutralization were prepared as described in the Methods section and loaded into a GE Pharmacy Kit. After regulatory approval the sterile HP [13C,15N2]urea probe, enabled unprecedented brain perfusion and BBB integrity MRI measurements.
Multivariate Framework of Metabolism in Advanced Prostate Cancer Using Whole Abdominal and Pelvic Hyperpolarized 13C MRI-A Correlative Study with Clinical Outcomes
Authors: Chen HY, de Kouchkovsky I, Bok RA, Ohliger MA, Wang ZJ, Gebrezgiabhier D, Nickles T, Carvajal L, Gordon JW, Larzon PEZ, Kurhanewicz J, Aggarwal R, Vigneron DB
Conclusions: Risk classifiers derived from select multiparametric HP features were significantly associated with clinically meaningful outcome measures in this small, heterogeneous patient cohort, strongly supporting further investigation into their prognostic values.
Hyperpolarized 13C metabolic imaging of the human abdomen with spatiotemporal denoising
Authors: Nickels TM, Kim Y, Lee PM, Chen HY, Ohliger M, Bok RA, Wang ZJ, Larson PEZ, Vigneron DB, Gordon JW
Purpose: Improving the quality and maintaining the fidelity of large coverage abdominal hyperpolarize (HP) 13C MRI studies with a patch based global-local higher-order singular value decomposition (GL-HOVSD) spatiotemporal denoising approach.
