Quality assurance for MRI-only radiation therapy: A voxel-wise population-based methodology for image and dose assessment of synthetic CT generation methods - Chourak, Hilda; Barateau, Anaïs; Tahri, Safaa; Cadin, Capucine; Lafond, Caroline; Nunes, Jean-Claude; Boue-Rafle, Adrien; Perazzi, Mathias; Greer, Peter B.; Dowling, Jason; de Crevoisier, Renaud; Acosta, Oscar (Frontiers in Oncology, 2022)
Quality assurance (QA) of synthetic-CT (sCT) is crucial for safe clinical transfer to an MRI-only radiotherapy planning workflow. The aim of this work is to propose a population-based process assessing local errors in the generation of sCTs, and their impact on dose distribution. For the analysis to be anatomically meaningful, a customised inter-patient registration method brought the population data to the same coordinate system. Then, the voxel-based process was applied on two sCT generation methods: a bulk-density method (BDM) and a Generative Adversarial Network (GAN). CT and MRI pairs of 39 patients treated by radiotherapy for prostate cancer were used for sCT generation, and 26 of them with delineated structures were selected for the analysis. Voxel-wise errors in sCT compared to CT were assessed for image intensities and dose calculation, and a population-based statistical test was applied to identify regions where discrepancies were significant. Cumulative histograms of mean absolute dose error per volume of tissue were computed to give a quantitative indication of the error for each generation method. Accurate inter-patient registration was achieved, with mean Dice scores higher than 0.91 for all organs. The proposed method produces 3D maps that precisely show the location of the major discrepancies for both sCT generation, highlighting the heterogeneity of image and dose errors for sCT generation methods from MRI across the pelvic anatomy. Hence, this method provides additional information that will assist with both sCT development and quality control for MRI-based planning radiotherapy.