Adaptive radiotherapy: The Elekta Unity MR-linac concept

Abstract

Background and purpose: The promise of the MR-linac is that one can visualize all anatomical changes during the course of radiotherapy and hence adapt the treatment plan in order to always have the optimal treatment. Yet, there is a trade-off to be made between the time spent for adapting the treatment plan against the dosimetric gain. In this work, the various daily plan adaptation methods will be presented and applied on a variety of tumour sites. The aim is to provide an insight in the behavior of the state-of-the-art 1.5 T MRI guided on-line adaptive radiotherapy methods.

Materials and methods: To explore the different available plan adaptation workflows and methods, we have simulated online plan adaptation for five cases with varying levels of inter-fraction motion, regions of interest and target sizes: prostate, rectum, esophagus and lymph node oligometastases (single and multiple target). The plans were evaluated based on the clinical dose constraints and the optimization time was measured.

Results: The time needed for plan adaptation ranged between 17 and 485 s. More advanced plan adaptation methods generally resulted in more plans that met the clinical dose criteria. Violations were often caused by insufficient PTV coverage or, for the multiple lymph node case, a too high dose to OAR in the vicinity of the PTV. With full online replanning it was possible to create plans that met all clinical dose constraints for all cases.

Conclusion: Daily full online replanning is the most robust adaptive planning method for Unity. It is feasible for specific sites in clinically acceptable times. Faster methods are available, but before applying these, the specific use cases should be explored dosimetrically.

Keywords: Adaptive radiotherapy; MR-linac; MRI-guided radiotherapy; Online plan adaptation; Radiotherapy.

Fig. 1

Schematic overview of the differences between the MR-linac Unity “adapt to shape” method in which online plan adaptation is performed on the new patient anatomy and optimized on the daily MRI and adapted contours, and the “adapt to position” method in which online plan adaptation is performed based on the new patient position and optimized on the pre-treatment CT and contours. Using the “adapt to position” method, rigid registration can be performed on the entire image sets, or using a clipbox around a region of interest.

Fig. 2

Schematic overview of the segment changes for the different plan recalculation and reoptimization methods available in the treatment planning software for the 1.5 T MR-linac. A different background color (e.g. red or yellow) in the Beam’s eye view (BEV) indicates a different segment weighting. When performing plan adaptation methods using optimize weights (method D) or optimize weights and shapes (method F) starting with full fluence optimization, the original segments are discarded and new initial plan segmentation is performed. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 3

Recalculation or optimization time required for plan adaptation for the methods available in the adapt to position (ATP) and adapt to shape (ATS) workflows. Method A – F describe: A the original segments, B adapt segments, C optimize weights from segments, D optimize weights from fluence, E optimize weights and shapes from segments and F optimize weights and shapes from fluence, respectively.

Fig. 4

Prostate case with the resulting dose distributions for the adapt to position (ATP) and adapt to shape (ATS) workflows. Method A – F describe: A the original segments, B adapt segments, C optimize weights from segments, D optimize weights from fluence, E optimize weights and shapes from segments and F optimize weights and shapes from fluence, respectively.