Deuterium metabolic imaging of the human abdomen at clinical field strength

Abstract

Background The Warburg effect is a hallmark of cancer and is characterized by increased glucose consumption and lactate formation. Deuterium metabolic imaging (DMI) is an emerging non-invasive MRI method for probing this metabolic reprogramming in the field of neuroimaging. Here we show the feasibility of the technique for abdominal imaging using a routine 3 T MRI system, which has previously presented significant technical challenges. Purpose This study aimed to translate abdominal DMI to clinical field strength by optimizing the radiofrequency coil setup, the administered dose of deuterium (²H)-labelled glucose, and the data processing pipeline for quantitative characterization of DMI signals over time in the kidney and liver, establishing a basis for routine clinical studies in the future. Materials and Methods Five healthy volunteers were recruited and imaged on 2 or 3 occasions, with different ²H-glucose doses (totalling 13 DMI scan sessions). DMI was performed at 3 T using a flexible 20 x 30 cm^{2 2}H-tuned transmit-receive surface coil. We have defined three novel quantitative parameters as metrics of metabolism and compared these between doses and organs. Results The careful positioning of a dedicated surface coil minimized unwanted gastric signals while maintaining excellent hepatic and renal measurements. The timecourses derived from the liver and kidney were reproducible and comparable across different doses, with a trend towards lower quantitative measurements with decreasing dose. An increase in the ²H-water signal over time particularly in the liver, could be used as an indirect measure of metabolism. Conclusion DMI of the human abdomen is feasible using a routine MRI system and the metabolism measured in the kidney and liver can serve as a reference for future clinical studies. The ²H-glucose dose can be reduced from 0.75 to 0.25 g/kg to minimize gastric signal without substantially affecting the reliability of organ quantification.