The use of hyperpolarised C pyruvate for nononcological neurological applications has not been widespread so far, possibly due to delivery issues limiting the visibility of metabolites. First proof-of-concept results have indicated that metabolism can be detected in human brain, and this may supersede the results obtained in preclinical settings. One major difference between the experimental setups is that preclinical MRI/MRS routinely uses anaesthesia, which alters both haemodynamics and metabolism. Here, we used hyperpolarised [1- C]pyruvate to compare brain metabolism in awake rats and under isoflurane, urethane or medetomidine anaesthesia. Spectroscopic [1- C]pyruvate time courses measured sequentially showed that pyruvate-to-bicarbonate and pyruvate-to-lactate labelling rates were lower in isoflurane animals than awake animals. An increased bicarbonate-to-lactate ratio was observed in the medetomidine group compared with other groups. The study shows that hyperpolarised [1- C]pyruvate experiments can be performed in awake rats, thus avoiding anaesthesia-related issues. The results suggest that haemodynamics probably dominate the observed pyruvate-to-metabolite labelling rates and area-under-time course ratios of referenced to pyruvate. On the other hand, the results obtained with medetomidine suggest that the ratios are also modulated by the underlying cerebral metabolism. However, the ratios between intracellular metabolites were unchanged in awake compared with isoflurane-anaesthetised rats.
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http://dx.doi.org/10.1002/nbm.4635 | DOI Listing |
J Magn Reson
January 2025
UC Berkeley - UCSF Graduate Program in Bioengineering, 1700 4th St, San Francisco, CA 94158, USA; Radiology and Biomedical Imaging, University of California, San Francisco, 1700 4th St, San Francisco, CA 94158, USA.
Fitting rate constants to Hyperpolarized [1-C]Pyruvate (HP C13) MRI data is a promising approach for quantifying metabolism in vivo. Current methods typically fit each voxel of the dataset using a least-squares objective. With these methods, each voxel is considered independently, and the spatial relationships are not considered during fitting.
View Article and Find Full Text PDFAnal Chem
January 2025
Institute for Bioengineering of Catalonia (IBEC), Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain.
Nuclear magnetic resonance (NMR) spectroscopy is a valuable diagnostic tool limited by low sensitivity due to low nuclear spin polarization. Hyperpolarization techniques, such as dissolution dynamic nuclear polarization, significantly enhance sensitivity, enabling real-time tracking of cellular metabolism. However, traditional high-field NMR systems and bioreactor platforms pose challenges, including the need for specialized equipment and fixed sample volumes.
View Article and Find Full Text PDFIEEE Access
November 2024
University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
The achievable spatial resolution of C metabolic images acquired with hyperpolarized C-pyruvate is worse than H images typically by an order of magnitude due to the rapidly decaying hyperpolarized signals and the low gyromagnetic ratio of C. This study is to develop and characterize a volumetric patch-based super-resolution reconstruction algorithm that enhances spatial resolution C cardiac MRI by utilizing structural information from H MRI. The reconstruction procedure comprises anatomical segmentation from high-resolution H MRI, calculation of a patch-based weight matrix, and iterative reconstruction of high-resolution multi-slice C MRI.
View Article and Find Full Text PDFNMR Biomed
January 2025
The MR Research Centre, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
Mild traumatic brain injuries (TBIs) are frequent in the European population. The pathophysiological changes after TBI include metabolic changes, but these are not observable using current clinical tools. We aimed to evaluate multinuclear MRI as a mean of assessing these changes.
View Article and Find Full Text PDFOncogene
December 2024
Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.
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