Abstract: The transition of a healthy cell to a cancer cell starts with the change of energy metabolism long before the cells proliferate uncontrollably and lead to anatomical changes (tumors, metastases) that can be visualized by conventional imaging. In particular, lactate/pyruvate metabolism is considered a hall-mark for cancer (Warburg effect). To detect cancer by metabolic imaging the sensitivity of magnetic resonance imaging (MRI) has to be increased by at least 5 orders of magnitude. This cannot be achieved by increasing the magnetic field strength. Hyperpolarization is currently the only method to achieve the necessary signal-to-noise ratio. The most commonly used method at present is DNP (dynamic nuclear polarization). Clinical studies with a limited number of patients have proven the extraordinary potential of the method. Despite its impressive success in the early detection, staging and treatment monitoring of prostate, breast and pancreatic cancer, DNP-MRI has not yet been investigated in Phase 3 studies and has therefore not yet found its way into clinical practice. The reason for this is that the method requires a very large investment in equipment and time, which does not permit studies with large patient groups.

DNP hyperpolarized MRI of three patients suffering from prostate cancer. The colored areas represent sites with high lactate/pyruvate ratio (Warburg effect) indicating cancerous tissue (S. Nelsen et al. Sci. Trans. Med. 2013, 5, 198ra108)

We take a different, much simpler approach to hyperpolarization. We use the spin order of parahydrogen as the source of hyperpolarization, transfer it to the 13C in 1-position of vinyl pyruvate, hydrolyze the ester and obtain hyperpolarized pyruvate. The process is much faster, simpler and less complex than DNP. We achieve hyperpolarization of up to 30%, which is sufficient for metabolic MRI. Upscaling for even very large patient groups is no problem. We consider the parahydrogen induced hyperpolarization a big step towards clinical translation.

[1] A. N. Pravdivtsev, F. Ellermann, A. Sirbu, A. Brahms, C. Assaf, R. Herges, and J.-B. Hövener, Nature Commun. 2023, 14, 4774.

[2] J. P. Peters et al. Science Adv. 2023, 9, eadd3643.

[3] Startup QuantView 2023, founders: R. Herges, S. Kloth.

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