Abstract #0180

Quantitative Biomarkers of Cancer from Metabolic Activity Decomposition Using Stimulated-Echoes and Hyperpolarized Carbon-13 MR

Christine M. Leon¹,², Peder EZ Larson¹, Adam B. Kerr³, Robert Bok¹, John M. Pauly³, John Kurhanewicz¹, Daniel B. Vigneron¹

¹Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States; ²UC Berkeley | UCSF Graduate Group in Bioengineering, University of California, Berkeley and University of California, San Francisco , San Francisco, CA, United States; ³Department of Electrical Engineering, Stanford University, Stanford, CA, United States

We propose a new and robust method for quantification of dynamic data. Using Metabolic Activity Decomposition, we investigated real-time conversion parameters as biomarkers of cancer. ex vivo enzyme experiments validated the technique, allowing for direct observation of real-time conversion, which can only be due to the LDH enzyme. Conventional modeling yields four unknowns but only two equations, an underdetermined system of equations. Using Metabolic Activity Decomposition, twice the amount of information can be obtained from a same acquisition providing a well-conditioned system. Moreover, fitting in vivo data with MAD-STEAM yielded K_Pyr→Lac values that robustly distinguished tumor versus normal (p-value=0.009)