1. Quality assurance for MRI-only radiation therapy: A voxel-wise population-based methodology for image and dose assessment of synthetic CT generation methods
- Author
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Hilda Chourak, Anaïs Barateau, Safaa Tahri, Capucine Cadin, Caroline Lafond, Jean-Claude Nunes, Adrien Boue-Rafle, Mathias Perazzi, Peter B. Greer, Jason Dowling, Renaud de Crevoisier, and Oscar Acosta
- Subjects
quality assurance ,voxel-wise analysis ,population-based evaluation ,synthetic CT assessment ,dosimetric assessment ,MRI-only radiation therapy ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
The quality assurance 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 customized interpatient 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 and a generative adversarial network. The 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 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 the regions where discrepancies were significant. The cumulative histograms of the mean absolute dose error per volume of tissue were computed to give a quantitative indication of the error for each generation method. Accurate interpatient registration was achieved, with mean Dice scores higher than 0.91 for all organs. The proposed method produces three-dimensional maps that precisely show the location of the major discrepancies for both sCT generation methods, 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.
- Published
- 2022
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