Metabolic reprogramming is one ofthe defning features of cancer and abnormal metabolism is
associated with many other pathologies. Molecular imaging techniques capable of detecting such
changes have become essential for cancer diagnosis,treatment planning, and surveillance. In particular, 18F-FDG (fuorodeoxyglucose) PET has emerged as an essential imaging modality for cancer because of
its unique ability to detect a disturbed molecular pathway through measurements of glucose uptake.
However, FDG-PET has limitations that restrict its usefulness in certain situations and the information
gained is limited to glucose uptake only.13C magnetic resonance spectroscopy theoretically has certain
advantages over FDG-PET, but its inherent low sensitivity has restricted its use mostly to single
voxel measurements unless dissolution dynamic nuclear polarization (dDNP) is used to increase the
signal, which brings additional complications for clinical use.We show here a new method of imaging
glucose metabolism in vivo by MRI chemical shiftimaging (CSI) experiments thatrelies on a simple,
butrobust and efcient, post-processing procedure by the higher dimensional analog of singular value
decomposition,tensor decomposition. Using this procedure, we achieve an order of magnitude increase
in signalto noise in both dDNP and non-hyperpolarized non-localized experiments without sacrifcing
accuracy. In CSI experiments an approximately 30-fold increase was observed, enough thatthe glucose
to lactate conversion indicative oftheWarburg efect can be imaged without hyper-polarization with a
time resolution of 12s and an overall spatial resolution that compares favorably to 18F-FDG PET.