Abstract
Background and purpose: Daily plan adaptations could take the dose delivered in previous fractions into account. Due to high dose delivered per fraction, low number of fractions, steep dose gradients, and large interfractional organ deformations, this might be particularly important for liver SBRT. This study investigates inter-algorithm variation of interfractional dose accumulation for MR-guided liver SBRT. Materials and methods: We assessed 27 consecutive MR-guided liver SBRT treatments of 67.5 Gy in three (n = 15) or 50 Gy in five fractions (n = 12), both prescribed to the GTV. We calculated fraction doses on daily patient anatomy, warped these doses to the simulation MRI using seven different algorithms, and accumulated the warped doses. Thus, we obtained differences in planned doses and warped or accumulated doses for each algorithm. This enabled us to calculate the inter-algorithm variations in warped doses per fraction and in accumulated doses per treatment course. Results: The four intensity-based algorithms were more consistent with planned PTV dose than affine or contour-based algorithms. The mean (range) variation of the dose difference for PTV D95% due to dose warping by these intensity-based algorithms was 10.4 percentage points (0.3 to 43.7) between fractions and 8.6 (0.3 to 24.9) between accumulated treatment doses. As seen by these ranges, the variation was very dependent on the patient and the fraction being analyzed. Nevertheless, no correlations between patient or plan characteristics on the one hand and inter-algorithm dose warping variation on the other hand was found. Conclusion: Inter-algorithm dose accumulation variation is highly patient- and fraction-dependent for MR-guided liver SBRT. We advise against trusting a single algorithm for dose accumulation in liver SBRT.
Originalsprog | Engelsk |
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Artikelnummer | 109448 |
Tidsskrift | Radiotherapy and Oncology |
Vol/bind | 182 |
Antal sider | 9 |
ISSN | 0167-8140 |
DOI | |
Status | Udgivet - 2023 |
Bibliografisk note
Funding Information:Isak Wahlstedt reports funding from ViewRay and the Danish Comprehensive Cancer Center as well as institutional research and teaching contracts with Varian Medical Systems, Brainlab, and Viewray. Thomas Carlslund at Rigshospitalet is acknowledged for solving several IT- and software-related issues. Rasmus Hvass Hansen at Rigshospitalet is acknowledged for proofreading and for acquiring results for quality assurance of MRIs. Angela Trask and Jorn Verweij at ViewRay are acknowledged for providing information about how to perform calculation of delivered doses with new Monte Carlo dose calculation settings in the MRIdian treatment planning system. Maxim de Smedt, Stefano Sobkowiak, and Michael Duchateau at MIM are acknowledged for their assistance in designing workflows for dose accumulation and for providing information about the MIM algorithms used in this study. Stefan Zepter at Varian is acknowledged for support in building the dose accumulation workflow in Velocity. Jamie McClelland and Bjoern Eiben from University College London are acknowledged for helping us understand the DICOM registrations exported from Velocity.
Funding Information:
Isak Wahlstedt reports funding from ViewRay and the Danish Comprehensive Cancer Center as well as institutional research and teaching contracts with Varian Medical Systems, Brainlab, and Viewray. Claus P. Behrens and Ivan R Vogelius report institutional research and teaching contracts with Varian Medical Systems, Brainlab, and Viewray. Abraham George Smith, Claus E. Andersen, Susanne Nørring Bekke, Kristian Boye, Mette van Overeem Felter, Mirjana Josipovic, Jens Petersen, Signe Lenora Risumlund, and Janita E. van Timmeren report no conflicts of interest.
Publisher Copyright:
© 2022 The Author(s)