Golden angle radial undersampling to accelerate synthetic CT generation with generative adversarial networks for prostate MR-guided Radiotherapy

Synthetic-computed tomography (sCT) is crucial to enable MR-only radiotherapy and accurate MR-based dose calculations. In this work, we assessed the feasibility of using undersampled golden angle radial acquisition in combination with a conditional adversarial network to accelerate both acquisition and sCT generation for patients with prostate cancer. Golden angle radial acquisitions were simulated for several undersampling factors in a retrospective manner on 3D Cartesian spoiled gradient-echo data that were clinically acquired on fourty patients with prostate cancer. Dose planning demonstrated that accurate MR-based dose calculations were possible up to an undersampling factor 30 resulting in fast (<20s) sCT generation, which is of particular interest for online MR-guided radiotherapy.