Recently, we developed a post processing denoising algorithms that are based on singular value decomposition and its multidimensional analogue Tucker decomposition. These algorithms allow more than 10-fold improvement in signal to noise ratio in dynamic spectroscopy and more than 50-fold in dynamic spectral imaging studies. Using this technique, we successfully characterize the metabolic profiles of two pancreatic ductal adenocarcinoma xenografts, MiaPaca-2 and Hs766t tumors by injecting 50 mg of 13C6 glucose. This imaging is potentially applicable to human subject and provides even more information than PET or 13C DNP MRI alone.
This abstract and the presentation materials are available to members only; a login is required.