biostudies-literatureGoodburn RCancer Research UK28-40https://www.ebi.ac.uk/biostudies/studies/S-EPMC12021324biostudies-literatureUnknown94(1)<h4>Purpose</h4>To measure the gradient system transfer function (GSTF) of an MR-Linac (Elekta Unity, Stockholm, Sweden) using an accessible phantom-based method and to apply trajectory corrections for UTE image reconstruction in the context of MR-guided radiotherapy of lung cancer.<h4>Methods</h4>The first-order GSTF of a 1.5 T, split gradient Elekta Unity MR-Linac was measured using a thin-slice technique to characterize gradient system imperfections for each physical gradient axis (X, Y, Z). Repeatability measurements of the GSTF were performed 48 h apart. The GSTF was applied to trajectory correction in multi-echo UTE image reconstruction (TEs = 0.176, 1.85, 3.52 ms) to allow for UTE-Dixon inputs in the generation of synthetic CT. Images were acquired in an anthropomorphic phantom and Magnetic resonance in medicineGradient system characterization of a 1.5 T MR-Linac with application to 4D UTE imaging for adaptive MR-guided radiotherapy of lung cancer.PMC12021324A26234C33589/A28284Barnes HOelfke UGoodburn RBruijnen TWetscherek ANair PAhmed MLecoeur BfalseGradient system characterization of a 1.5 T MR-Linac with application to 4D UTE imaging for adaptive MR-guided radiotherapy of lung cancer.<h4>Purpose</h4>To measure the gradient system transfer function (GSTF) of an MR-Linac (Elekta Unity, Stockholm, Sweden) using an accessible phantom-based method and to apply trajectory corrections for UTE image reconstruction in the context of MR-guided radiotherapy of lung cancer.<h4>Methods</h4>The first-order GSTF of a 1.5 T, split gradient Elekta Unity MR-Linac was measured using a thin-slice technique to characterize gradient system imperfections for each physical gradient axis (X, Y, Z). Repeatability measurements of the GSTF were performed 48 h apart. The GSTF was applied to trajectory correction in multi-echo UTE image reconstruction (TEs = 0.176, 1.85, 3.52 ms) to allow for UTE-Dixon inputs in the generation of synthetic CT. Images were acquired in an anthropomorphic phantom and 2025-01-01T00:00:00Z2025 Jul2025-07-01T03:05:32.485Z2025-07-01T03:05:32.485ZS-EPMC120213244010679410.1002/mrm.30505