Abstract #3939

Laplace Inversion for Kinetic Analysis of Hyperpolarized 13C Data Without a Priori Knowledge Using a Hybrid Maximum Entropy Method (MEM)/ Non-Linear Least Square (NLS)

Erika Mariotti¹, Fiona Shaughnessy¹, Rodolfo A. Medina¹, Joel T. Dunn¹, Richard Southworth¹, Thomas R. Eykyn¹,²

¹Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom; ²CRUK and EPSRC Cancer Imaging Centre, Royal Marsden NHS Trust, The Institute of Cancer Research, Sutton, Surrey, United Kingdom

To obtain information on the underlying metabolic activities, hyperpolarized data are usually fit using kinetic models to derive rates. In this work, we show the feasibility of analysing hyperpolarized data without prior assumptions of a model and, at the same time, overcoming the multiple local minimum problem by applying a hybrid Maximum-Entropy/NonLinear-Least-Squares (MEM/NLS) method4 to hyperpolarized 13C data both in vitro in whole blood and ex vivo in the isolated rat heart.