LAUSR

DNP increases the signal of carbon-13 molecules on MR scans (>10,000-fold), enabling real-time, dynamic quantitation of tissue metabolism in vivo with significant clinical potential. 13C quantification of metabolism is affected by confounding factors (T1 signal decay, flip angle, and metabolite escape), which necessitates metabolic modelling. Here, we have assessed a mathematical model that requires minimal information on confounding factors to measure metabolic rates with reliability. Four healthy male volunteers (age; 24 ± 1.4 years; BMI; 23 ± 0.4 kg/m2) were recruited. Sterile hyperpolarized 13C pyruvate was safely produced using a clinical DNP polariser (SPINlab GE-Healthcare) and administered intravenously to volunteers performing in-bore plantar-flexion exercise to increase muscle pyruvate flux. 13C MR scans of the calf muscle were collected during exercise and used to test our model against 5000 computer simulations using randomised kinetic constants and confounding factors. The signal of metabolites was used to extract the kinetic constants of hyperpolarised-13C pyruvate conversion to lactate (KpL), alanine (KpA), and bicarbonate (KpB) with reproducibility and satisfactory signal-to-noise ratio (8.2 ± 1.8×102 s−1, 2.3 ± 2.1×102 s−1 to 2.1 ± 1.3 x103 s−1, respectively; mean ± SD). Model predictions were in statistical agreement with the kinetic constants used in the simulations. Our metabolic model could be used to measure metabolic conversion of hyperpolarised-13C metabolites in the context of surgery, where postoperative insulin resistance is well-known to be linked to stress-induced upregulation of pyruvate dehydrogenase inhibitor.