Real-time dose reconstruction and dose coverage forecasting using the magnetic resonance linear accelerator
Abstract
Background and purpose: Intrafraction patient motion during radiotherapy treatment affects the delivered dose, thereby, deviating from the planned dose. To monitor the deviation, we propose a workflow capable of performing and displaying real-time dose calculations during treatment with a magnetic resonance linear accelerator (MR-linac). Additionally, the workflow can forecast the accumulated dose and enables evaluation of dose guidance in real time for triggering automatic plan adaptation or intrafraction drift corrections (IDCs). Materials and methods: Information on the treated anatomy, rigid translations or three-dimensional (3D) volumes, and the linac state were collected to perform clinical grade dose calculations. Real-time dose reconstructions and the accumulated dose forecasts were performed for two dynamic scenarios. The first, rigid translations derived from two-dimensional orthogonal MR images where the calculated dose was compared to diode measurements. The second, deformable dose accumulation using deformable image registration, based on 3D MR imaging and compared to a dose film measurement. Results: The real-time dose reconstruction had a maximum standard deviation error of 2.3 % with the measured dose, compared to 13.1 % for the planned dose. The workflow maintained real-time performance using a single graphics processing unit up to 92 % of the time that the beam was on. Finally, dose coverage forecasts were updated every 6.5 s at the start of treatment, with the update frequency increasing towards the end of treatment. Conclusion: We demonstrated the feasibility of displaying real-time delivered dose distributions and forecasted dose coverage using an MR-Linac. This enables triggering automatic plan adaptations or IDCs.
Fields of Study & Subjects
Advanced Radiotherapy Techniques
Radiation Dose and Imaging
Radiation Effects and Dosimetry
Publication details
- Journal / source
- Physics and Imaging in Radiation Oncology
- Publisher
- Elsevier BV
- Volume
- 37
- Pages
- 100910–100910
- Publication date
- 1 January 2026
- Language
- EN