Chemical exchange saturation transfer MRI in central nervous system tumours on a 1.5 T MR-Linac. (September 2021) - Chan, Rachel W.; Lawrence, Liam S.P.; Oglesby, Ryan T.; Chen, Hanbo; Stewart, James; Theriault, Aimee; Campbell, Mikki; Ruschin, Mark; Myrehaug, Sten; Atenafu, Eshetu G.; Keller, Brian; Chugh, Brige; et al.
Highlights: CEST MRI is feasible on a 1.5 tesla MR-Linac for imaging CNS tumours. Differences were found in CEST signals between tumour and white matter. Detectable signal changes between treatment fractions were observed. Differences in asymmetry were found between high- and low-grade tumours. Abstract: Purpose: To describe the implementation and initial results of using Chemical Exchange Saturation Transfer (CEST) for monitoring patients with central nervous system (CNS) tumours treated using a 1.5 tesla MR-guided radiotherapy system. Methods: CNS patients were treated with up to 30 fractions (total dose up to 60 Gy) using a 1.5 T Elekta Unity MR-Linac. CEST scans were obtained in 54 subjects at one or more time points during treatment. CEST metrics, including the amide magnetization transfer ratio (MTRAmide ), nuclear Overhauser effect (NOE) MTR (MTRNOE ) and asymmetry, were quantified in phantoms and CNS patients. The signal was investigated between tumour and white matter, across time, and across disease categories including high- and low-grade tumours. Results: The gross tumour volume (GTV) exhibited lower MTRAmide and MTRNOE and higher asymmetry compared to contralateral normal appearing white matter. Signal changes in the GTV during fractionated radiotherapy were observed. There were differences between high- and low-grade tumours, with higher CEST asymmetry associated with higher grade disease. Conclusion: CEST MRI using a 1.5 T MR-Linac was demonstrated to be feasible for in vivo imaging of CNS tumours. CEST images showed tumour/white-matter contrast, temporal CEST signal changes, and associations with tumour grade. These results show promise for the eventual goal of using metabolic imaging to inform the design of adaptive radiotherapy protocols.