It is recognized that the use of a single plan calculated on an image acquired some time before the treatment is generally insufficient to accurately represent the daily dose to the target and to the organs at risk. This is particularly true for protons, due to the physical finite range. Although this characteristic enables the generation of steep dose gradients, which is essential for highly conformal radiotherapy, it also tightens the dependency of the delivered dose to the range accuracy. In particular, the use of an outdated patient anatomy is one of the most significant sources of range inaccuracy, thus affecting the quality of the planned dose distribution. A plan should be ideally adapted as soon as anatomical variations occur, ideally online. In this review, we describe in detail the different steps of the adaptive workflow and discuss the challenges and corresponding state-of-the art developments in particular for an online adaptive strategy.

Proton therapy with active scanning beam delivery has significant advantages compared to conventional radiotherapy. However, so far only static targets have been treated in this way, since moving targets potentially lead to interplay effects. For 4D treatment planning, information on the target motion is needed to calculate time-resolved dose distributions. In this study, respiratory liver motion has been extracted from 4D CT data using two deformable image registration algorithms. In moderately moving patient cases (mean motion range around 6 mm), the registration error was no more than 3 mm, while it reached 7 mm for larger motions (range around 13 mm). The obtained deformation fields have then been used to calculate different time-resolved 4D treatment plans. Averaged over both motion estimations, interplay effects can increase the D₅-D₉₅ value for the clinical target volume (CTV) from 8.8% in a static plan to 23.4% when motion is considered. It has also been found that the different deformable registration algorithms can provide different motion estimations despite performing similarly for the selected landmarks, which in turn can lead to differing 4D dose distributions. Especially for single-field treatments where no motion mitigation is used, a maximum (mean) dose difference (averaged over three cases) of 32.8% (2.9%) can be observed. However, this registration ambiguity-induced uncertainty can be reduced if rescanning is applied or if the treatment plan consists of multiple fields, where the maximum (mean) difference can decrease to 15.2% (0.57%). Our results indicate the necessity to interpret 4D dose distributions for scanned proton therapy with some caution or with error bars to reflect the uncertainties resulting from the motion estimation. On the other hand, rescanning has been found to be an appropriate motion mitigation technique and, furthermore, has been shown to be a robust approach to also deal with these motion estimation uncertainties.

Tumour tracking with scanned particle beams potentially requires accurate 3D information on both tumour motion and related density variations. We have previously developed a model-based motion reconstruction method, which allows for the prediction of deformable motions from sparsely sampled surrogate motions tracked via an on-board imaging system (Zhang et al (2013 Phys. Med. Biol. 58 8621)). Here, we investigate the potential effectiveness of tumour tracking for scanned proton beam therapy using such an approach to guide scanned beam tracking, together with the effectiveness of 're-tracking' for reducing residual motion effects due to tracking uncertainties. Three different beam tracking strategies (2D, 2D deformable and 3D) have been applied to three different liver motion cases, with mean magnitudes ranging from 10-20 mm. All simulations have been performed using simulated 4DCTs derived from 4DMRI datasets, whereby inter-breath-cycle motion variability is taken into account. The results show that, without beam tracking, large interplay effects are observed for all motion cases, resulting in CTV D5-95 values of 34.9/58.5/79.4% for the three cases, respectively. These can be reduced to 16.9/18.8/29.1% with 2D tracking, to 15.5/17.9/23.3% with 2D deformable tracking and to 15.1/17.8/21.0% with 3D tracking. Clear 'inverse interplay' effects have also been observed in the proximal portion of the field. However, with three-times re-tracking, D5-95 for the largest motions (20 mm) can be reduced to 13.0/12.8% for 2D and 3D tracking, respectively, and 'hot spots' resulting from the 'inverse interplay' effect can be substantially reduced. In summary, we have found that, for motions over 10 mm, tracking alone cannot fully mitigate motion effects, and can lead to substantially increased doses to normal tissues in the entrance path of the field. However, three-times re-tracking substantially improves the effectiveness of all types of beam tracking, with substantial advantages of 3D over 2D re-tracking only being observed for the largest motion scenario investigated.