Abstract

Abstract INTRODUCTION Hyperpolarized (HP) 13C MRI is a novel metabolic imaging that allows for real time in vivo probing of pathway-specific metabolic processes relevant to gliomas. The first human brain application reports were published recently. In this study, we characterized longitudinal dynamic and static brain metabolism changes from serial HP 13C and 1H metabolic imaging in a patient with multiply recurrent glioma. METHODS Eight dynamic HP 13C imaging, 1H MRI and MRSI examinations were acquired over a period of 15 months in a patient with multiply recurrent glioma that underwent malignant transformation. The patient was imaged after initial tumor debulking, after chemoradiotherapy, at first recurrence, after re-irradiation and anti-angiogentic therapy, and at second recurrence. Ratios of pyruvate-to-lactate and pyruvate-to-bicarbonate were calculated from HP 13C imaging and choline-to-NAA index (CNI) was derived from 1H MRSI. RESULTS/ DISCUSSION Successful therapies are usually associated with a drop in pyruvate-to-lactate conversion, mediated by different mechanisms from various treatments. We identified three key findings over repeat HP 13C MRIs: 1) a marked response to therapy with a reduction in pyruvate-to-lactate conversion corresponding to associated imaging response to therapy at the primary site of disease. Following chemoradiotherapy, the volume of T2 hyperintensity decreased from 28.21cc to 15.29 cc, and the volume of metabolic abnormality (CNI >3) decreased from 27.84 cc to 10.36 cc. 2) increasing pyruvate-to-lactate conversion in a region of recurrence before morphologic signal abnormality, and 3) a reduction in pyruvate-to-lactate conversion in a recurrent lesion following anti-angiogenic therapy. CONCLUSION Here we show that one can reliably image glioma patients using HP 13C MRI alongside standard of care morphologic and physiologic MRI including diffusion, perfusion, and 1H MRSI. Serial HP 13C MRI can be performed in the neuro-oncologic clinical setting and pyruvate-to-lactate metabolism may be useful to monitor treatment response.

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