ESTRO 2022 - Abstract Book

S551

Abstract book

ESTRO 2022

OC-0623 First-in-human clinical translation of oxygen-enhanced MRI onto an MR Linac

M. Dubec 1,2 , A. Datta 1,3 , A. Clough 4 , D.L. Buckley 2,5 , R.A. Little 1 , M. Berks 1 , S. Cheung 1 , C. Eccles 1,4 , D. Higgins 6 , J.H. Naish 7,8 , J.C. Matthews 9 , M. van Herk 1 , R.G. Bristow 1,10 , G.J. Parker 11,8 , P. Hoskin 1,10,12 , A. McPartlin 10 , A. Choudhury 13,10 , J.P. O'Connor 1,3,14 1 University of Manchester, Division of Cancer Sciences, Manchester, United Kingdom; 2 The Christie NHS Foundation Trust, Christie Medical Physics and Engineering, Manchester, United Kingdom; 3 The Christie NHS Foundation Trust, Radiology, Manchester, United Kingdom; 4 The Christie NHS Foundation Trust, Radiotherapy, Manchester, United Kingdom; 5 Biomedical Imaging, University of Leeds, Leeds, United Kingdom; 6 Philips UK&I, MR Clinical Science, Farnborough, United Kingdom; 7 University of Manchester NHS Foundation Trust, MCMR, Manchester, United Kingdom; 8 Bioxydyn Ltd, Bioxydyn, Manchester, United Kingdom; 9 University of Manchester, Neuroscience and Experimental Psychology , Manchester, United Kingdom; 10 The Christie NHS Foundation Trust, Clinical Oncology, Manchester, United Kingdom; 11 University College London, Centre for Medical Image Computing, London, United Kingdom; 12 Mount Vernon, Radiotherapy, London, United Kingdom; 13 University of Manchester, Division of Cancer Sciences , Manchester, United Kingdom; 14 Institute of Cancer Research, Radiotherapy and Imaging, London, United Kingdom Purpose or Objective MR Linac (MRL) systems enable delivery of radiotherapy with on-line MRI. Functional imaging on the MRL permits identification, mapping and tracking of tumour sub-regions, with the potential to introduce biologically adaptive radiotherapy (Datta 2018 ClinOnc). Here we report the first application of oxygen-enhanced MRI (OE-MRI) on an MRL to identify and map tumour hypoxia. Materials and Methods A dynamic 3D inversion recovery turbo field echo (IR-TFE) OE-MRI sequence was developed on a Philips Ingenia 1.5T MR system (MRSim) in 12 healthy volunteers and 4 patients with treatment naïve head and neck (H&N) carcinoma. This protocol was modified and implemented on an Elekta-Philips 1.5T MRL with different receive coils and required modification of repetition and echo times due to hardware differences. Other hardware fitting steps included retrofitting of gas delivery in the MRL bunker; installation of gas ports, delivery tubing and MR conditional blender providing 15 l/min; and installation of a contrast agent power injector for dynamic contrast-enhanced (DCE)-MRI. Participants were recruited after providing written informed consent on a local ethics approved protocol. MRL OE-MRI was acquired in 4 healthy volunteers and a patient with H&N carcinoma. T 1 measurement was carried out using an IR-TFE sequence with multiple TIs and a dynamic IR-TFE series during delivery of medical air (volumes 1-25), followed by 100% oxygen (volumes 26-70) and back to medical air (volumes 71-91). Analysis was carried out in MATLAB (Mathworks). Native T 1 maps enabled conversion of signal change to Δ R 1 (where Δ R 1 = R 1,O2 – R 1,air ). In all volunteers, Δ R 1 was calculated in the nasal concha (NC). Patient tumour volumes were delineated on T 1 post contrast images and Δ R 1 measurements obtained. Perfused tumour voxels (DCE signal increase p<0.05) were classified as oxygen enhancing (Oxy-E) (OE signal increase p<0.05; suggesting normoxia) or oxygen refractory (Oxy-R) (suggesting hypoxia). Results Volunteer NC Δ R 1 was 0.059 ± 0.027 s -1 (p < 0.001, group Δ R 1 change) and 0.065 ± 0.030 (p < 0.001) on the MRSim and MRL respectively (Figure 1a-b). There was no significant difference in NC Δ R 1 between the groups on the two systems (p=0.6, unpaired t-test). Patient tumour mean Δ R 1 = 0.031 ± 0.035 (p < 0.001) (n=5 patients) on the MRSim and Δ R 1 = 0.035 ± 0.011 (p < 0.001) (n = 1 patient) on the MRL (Figure 1c-d). Hypoxia maps showed distinct ‘hypoxic’ and ‘normoxic’ tumour sub-regions and are presented with the tumour Δ R 1 map in figure 2.