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 In particular, the use of an outdated patient anatomy is one of the most significant sources of range inaccuracy, thus affecting the quality of the planned dose distribution.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.

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Intrinsic geometric errors by DIR can influence the clinical evaluation of liver 4D PBS-PT plans. We recommend the use of an error bar for correctly interpreting individual 4D dose distributions.

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Organ motion is a major problem for any dynamic radiotherapy delivery technique, and is particularly so for spot scanned proton therapy. On the other hand, the use of narrow, magnetically deflected proton pencil beams is potentially an ideal delivery technique for tracking tumour motion on-line. At PSI, our new Gantry is equipped with a Beams Eye View (BEV) imaging system which will be able to acquire 2D x-ray images in fluoroscopy mode during treatment delivery. However, besides precisely tracking motion from BEVs, it is also essential to obtain information on the 3D motion vector throughout the whole region of interest, and any sparsely acquired surrogate motion is generally not sufficient to describe the deformable behaviour of the whole volume in three dimensions. In this study, we propose a method by which 3D deformable motions can be estimated from surrogate motions obtained using this monoscopic imaging system. The method assumes that example motions over a number of breathing cycles can be acquired before treatment for each patient using 4DMRI. In this study, for each of 11 different subjects, 100 continuous breathing cycles have been extracted from extended 4DMRI studies in the liver and then subject specific motion models have been built using principle component analysis (PCA). To simulate treatment conditions, a different set of 30 continuous breathing cycles from the same subjects have then been used to generate a set of simulated 4DCT data sets (so-called 4DCT(MRI) data sets), from which time-resolved digitally reconstructed radiographs (DRRs) were calculated using the BEV geometry for three treatment fields respectively. From these DRRs, surrogate motions from fiducial markers or the diaphragm have been used as a predictor to estimate 3D motions in the liver region for each subject. The prediction results have been directly compared to the 'ground truth' motions extracted from the same 30 breath cycles of the originating 4DMRI data set. Averaged over all 11 subjects, and for three field directions, for 99% of predicted positions, median (max) error magnitudes of better than 2.63(5.67) mm can be achieved when fiducial markers was chosen as predictor. Furthermore, three single fields, 4D dose calculations have been performed as a verification tool to evaluate the prediction performance of such a model in the context of scanned proton beam therapy. These show a high similarity between plans considering either PCA predicted motion or ground truth motion, where absolute dose differences of more than 5% (V(dosediff = 5%)) occur for the worst field scenarios in only 3.61% (median) or 15.13% (max) of dose calculation points in the irradiated volume. The magnitude of these dose differences were insignificantly dependent on whether surrogate motions were tracked by monoscopic or stereoscopic imaging systems, or whether fiducial markers or diaphragm were chosen as surrogate. This study has demonstrated that on-line deformable motion reconstruction from sparse surrogate motions is feasible, even when using onl...

Pencil beam scanned (PBS) proton therapy has many advantages over conventional radiotherapy, but its effectiveness for treating mobile tumours remains questionable. Gating dose delivery to the breathing pattern is a well-developed method in conventional radiotherapy for mitigating tumour-motion, but its clinical efficiency for PBS proton therapy is not yet well documented. In this study, the dosimetric benefits and the treatment efficiency of beam gating for PBS proton therapy has been comprehensively evaluated. A series of dedicated 4D dose calculations (4DDC) have been performed on 9 different 4DCT(MRI) liver data sets, which give realistic 4DCT extracting motion information from 4DMRI. The value of 4DCT(MRI) is its capability of providing not only patient geometries and deformable breathing characteristics, but also includes variations in the breathing patterns between breathing cycles. In order to monitor target motion and derive a gating signal, we simulate time-resolved beams' eye view (BEV) x-ray images as an online motion surrogate. 4DDCs have been performed using three amplitude-based gating window sizes (10/5/3 mm) with motion surrogates derived from either pre-implanted fiducial markers or the diaphragm. In addition, gating has also been simulated in combination with up to 19 times rescanning using either volumetric or layered approaches. The quality of the resulting 4DDC plans has been quantified in terms of the plan homogeneity index (HI), total treatment time and duty cycle. Results show that neither beam gating nor rescanning alone can fully retrieve the plan homogeneity of the static reference plan. Especially for variable breathing patterns, reductions of the effective duty cycle to as low as 10% have been observed with the smallest gating rescanning window (3 mm), implying that gating on its own for such cases would result in much longer treatment times. In addition, when rescanning is applied on its own, large differences between volumetric and layered rescanning have been observed as a function of increasing number of re-scans. However, once gating and rescanning is combined, HI to within 2% of the static plan could be achieved in the clinical target volume, with only moderately prolonged treatment times, irrespective of the rescanning strategy used. Moreover, these results are independent of the motion surrogate used. In conclusion, our results suggest image guided beam gating, combined with rescanning, is a feasible, effective and efficient motion mitigation approach for PBS-based liver tumour treatments.