Distinguishing Closely Related Pancreatic Cancer Subtypes In Vivo by 13C Glucose MRI without Hyperpolarization

Abstract

Metabolic differences between patients and within the tumor itself can be an important determinant in cancer treatment outcome. However, methods for determining these differences non-invasively in vivo have been lacking. Using pancreatic ductal adenocarcinoma as a model, we demonstrate that tumor xenografts with a similar genetic background can be distinguished by their differing rates of metabolism, as detected by imaging of uniformly 13C labeled glucose tracers using a newly developed technique using tensor decomposition for noise suppression to bring the signal to a detectable level without hyperpolarization of the tracer. Using this method, cancer subtypes that appeared to exhibit similar metabolic profiles by other techniques that measured steady state metabolism can be distinguished.