Accurate measurement of low metabolite concentrations produced by medically important enzymes is commonly obscured by noise during magnetic resonance imaging (MRI). Measuring the turnover rate of low-level metabolites can directly quantify the activity of enzymes of interest, including possible drug targets in cancer and other diseases. Noise can cause the in vivo signal to fall below the limit of detection. A variety of denoising methods have been proposed to enhance spectroscopic peaks, but still fall short for the detection of low-intensity signals. Dynamic nuclear polarization (DNP) is one method that has been critical for boosting weak signals. DNP must be performed near zero absolute temperature, requiring high operating costs. Measurements are limited to imaging immediately after tracer injection, limiting the range of injectable tracers that can be used in vivo. To address these issues, scientists at the National Cancer Institute (NCI) and National Institute of Neurological Disorders and Stroke (NINDS) have invented a unique method for measuring low-abundance metabolites in vivo which does not rely on frequency or spatial domains – but instead works in the kinetic domain. Data processing structure is simpler. True weak spectroscopic peaks can be more easily distinguished from noise. This technology improves the signal-to-noise ratio by an order of magnitude or more and has already been tested in vivo. The denoising software enhances low-metabolic signal without the need for DNP, which was previously thought impossible. The method makes MRI more informative for determining the metabolic activity of key enzymes in serious pathologies, is more dynamic in the range of tracers that can be used, and is generally less expensive. This software is also highly adaptable as it can be added as a plug-in to already existing MRI processing software. The scientists seek co-development parties and/or licensees for their invention.