Log file-based dose reconstruction and accumulation for 4D adaptive pencil beam scanned proton therapy in a clinical treatment planning system: Implementation and proof-of-concept.

BACKGROUND AND PURPOSE: Motion-induced uncertainties hamper the clinical implementation of pencil beam scanning proton therapy (PBS-PT). Prospective pretreatment evaluations only provide multiscenario predictions without giving a clear conclusion for the actual treatment. Therefore, in this proof-of-concept study we present a methodology for a fraction-wise retrospective four-dimensional (4D) dose reconstruction and accumulation aiming at the evaluation of treatment quality during and after treatment. MATERIAL AND METHODS: We implemented an easy-to-use, script-based 4D dose assessment of PBS-PT for patients with moving tumors in a commercially available treatment planning system. This 4D dose accumulation uses treatment delivery log files and breathing pattern records of each fraction as well as weekly repeated 4D-CT scans acquired during the treatment course. The approach was validated experimentally and was executed for an exemplary dataset of a lung cancer patient. RESULTS: The script-based 4D dose reconstruction and accumulation was implemented successfully, requiring minimal user input and a reasonable processing time (around 10 min for a fraction dose assessment). An experimental validation using a dynamic CIRS thorax phantom confirmed the precision of the 4D dose reconstruction methodology. In a proof-of-concept study, the accumulation of 33 reconstructed fraction doses showed a linear increase of D98 values. Projected treatment course D98 values revealed a CTV underdosage after fraction 25. This loss of target coverage was confirmed in a dose volume histogram comparison of the nominal, the projected (after 16 fractions) and the accumulated (after 33 fractions) dose distribution. CONCLUSIONS: The presented method allows for the assessment of the conformity between planned and delivered dose as the treatment course progresses. The implemented approach considers the influence of changing patient anatomy and variations in the breathing pattern. This facilitates treatment quality evaluation and supports decisions regarding plan adaptation. In a next step, this approach will be applied to a larger patient cohort to investigate its capability as 4D quality control and decision support tool for treatment adaptation.

Experimental investigation of irregular motion impact on 4D PET-based particle therapy monitoring.

Particle therapy positron emission tomography (PT-PET) is an in vivo and non-invasive imaging technique to monitor treatment delivery in particle therapy. The inevitable patient respiratory motion during irradiation causes artefacts and inaccurate activity distribution in PET images. Four-dimensional (4D) maximum likelihood expectation maximisation (4D MLEM) allows for a compensation of these effects, but has up to now been restricted to regular motion for PT-PET investigations. However, intra-fractional motion during treatment might differ from that during acquisition of the 4D-planning CT (e.g. amplitude variation, baseline drift) and therefore might induce inaccurate 4D PET reconstruction results. This study investigates the impact of different irregular analytical one-dimensional (1D) motion patterns on PT-PET imaging by means of experiments with a radioactive source and irradiated moving phantoms. Three sorting methods, namely phase sorting, equal amplitude sorting and event-based amplitude sorting, were applied to manage the PET list-mode data. The influence of these sorting methods on the motion compensating algorithm has been analysed. The event-based amplitude sorting showed a superior performance and it is applicable for irregular motions with ⩽ 4 mm amplitude elongation and drift. For motion with 10 mm baseline drift, the normalised root mean square error was as high as 10.5% and a 10 mm range deviation was observed.

Experimental verification of a 4D MLEM reconstruction algorithm used for in-beam PET measurements in particle therapy.

In-beam positron emission tomography (PET) has been proven to be a reliable technique in ion beam radiotherapy for the in situ and non-invasive evaluation of the correct dose deposition in static tumour entities. In the presence of intra-fractional target motion an appropriate time-resolved (four-dimensional, 4D) reconstruction algorithm has to be used to avoid reconstructed activity distributions suffering from motion-related blurring artefacts and to allow for a dedicated dose monitoring. Four-dimensional reconstruction algorithms from diagnostic PET imaging that can properly handle the typically low counting statistics of in-beam PET data have been adapted and optimized for the characteristics of the double-head PET scanner BASTEI installed at GSI Helmholtzzentrum Darmstadt, Germany (GSI). Systematic investigations with moving radioactive sources demonstrate the more effective reduction of motion artefacts by applying a 4D maximum likelihood expectation maximization (MLEM) algorithm instead of the retrospective co-registration of phasewise reconstructed quasi-static activity distributions. Further 4D MLEM results are presented from in-beam PET measurements of irradiated moving phantoms which verify the accessibility of relevant parameters for the dose monitoring of intra-fractionally moving targets. From in-beam PET listmode data sets acquired together with a motion surrogate signal, valuable images can be generated by the 4D MLEM reconstruction for different motion patterns and motion-compensated beam delivery techniques.