Challenges in glucoCEST MR body imaging at 3 Tesla

Mina Kim; Francisco Torrealdea; Sola Adeleke; Marilena Rega; Vincent Evans; Teresita Beeston; Katerina Soteriou; Stefanie Thust; Aaron Kujawa; Sachi Okuchi; Elizabeth Isaac; Wivijin Piga; Jonathan R Lambert; Asim Afaq; Eleni Demetriou; Pratik Choudhary; King Kenneth Cheung; Sarita Naik; David Atkinson; Shonit Punwani; Xavier Golay

doi:10.21037/qims.2019.10.05

Challenges in glucoCEST MR body imaging at 3 Tesla

Quant Imaging Med Surg. 2019 Oct;9(10):1628-1640. doi: 10.21037/qims.2019.10.05.

Authors

Mina Kim^{1

2}, Francisco Torrealdea³, Sola Adeleke⁴, Marilena Rega⁵, Vincent Evans⁴, Teresita Beeston⁴, Katerina Soteriou⁴, Stefanie Thust², Aaron Kujawa^{1

2}, Sachi Okuchi^{1

2}, Elizabeth Isaac⁴, Wivijin Piga⁴, Jonathan R Lambert⁶, Asim Afaq⁵, Eleni Demetriou^{1

2}, Pratik Choudhary^{7

8}, King Kenneth Cheung⁹, Sarita Naik¹⁰, David Atkinson⁴, Shonit Punwani⁴, Xavier Golay^{1

2}

Affiliations

¹ Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK.
² Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, UK.
³ Medical Physics and Biomedical Engineering, University College Hospital, London, UK.
⁴ UCL Centre for Medical Imaging, London, UK.
⁵ Institute of Nuclear Medicine, University College Hospital, London, UK.
⁶ Department of Haematology, University College London Hospital, London, UK.
⁷ King's College Hospital NHS Foundation Trust, London, UK.
⁸ Department of Diabetes, School of Life Course Sciences, King's College London, London, UK.
⁹ University College London Hospitals NHS Foundation Trust, London, UK.
¹⁰ Department of Diabetes and Endocrinology, University College Hospital, London, UK.

Abstract

Background: The aim of this study was to translate dynamic glucose enhancement (DGE) body magnetic resonance imaging (MRI) based on the glucose chemical exchange saturation transfer (glucoCEST) signal to a 3 T clinical field strength.

Methods: An infusion protocol for intravenous (i.v.) glucose was optimised using a hyperglycaemic clamp to maximise the chances of detecting exchange-sensitive MRI signal. Numerical simulations were performed to define the optimum parameters for glucoCEST measurements with consideration to physiological conditions. DGE images were acquired for patients with lymphomas and prostate cancer injected i.v. with 20% glucose.

Results: The optimised hyperglycaemic clamp infusion based on the DeFronzo method demonstrated higher efficiency and stability of glucose delivery as compared to manual determination of glucose infusion rates. DGE signal sensitivity was found to be dependent on T₂, B₁ saturation power and integration range. Our results show that motion correction and B₀ field inhomogeneity correction are crucial to avoid mistaking signal changes for a glucose response while field drift is a substantial contributor. However, after B₀ field drift correction, no significant glucoCEST signal enhancement was observed in tumour regions of all patients in vivo.

Conclusions: Based on our simulated and experimental results, we conclude that glucose-related signal remains elusive at 3 T in body regions, where physiological movements and strong effects of B₁ ⁺ and B₀ render the originally small glucoCEST signal difficult to detect.

Keywords: Glucose chemical exchange saturation transfer (glucoCEST), body magnetic resonance imaging (body MRI); clinical 3 T; field inhomogeneity; magnetization transfer ratio asymmetry (MTRasym).

Abstract

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