Pencil beam scanning proton therapy allows the delivery of highly conformal dose distributions by delivering several thousand pencil beams. These beams have to be individually optimised and accurately delivered requiring a significant quality assurance workload. In this work we describe a toolkit for independent dose calculations developed at Paul Scherrer Institut which allows for dose reconstructions at several points in the treatment workflow. Quality assurance based on reconstructed dose distributions was shown to be favourable to pencil beam by pencil beam comparisons for the detection of delivery uncertainties and estimation of their effects. Furthermore the dose reconstructions were shown to have a sensitivity of the order of or higher than the measurements currently employed in the clinical verification procedures. The design of the independent dose calculation tool allows for a high modifiability of the dose calculation parameters (e.g. depth dose profiles, angular spatial distributions) allowing for a safe environment outside of the clinical treatment planning system for investigating the effect of such parameters on the resulting dose distributions and thus distinguishing between different contributions to measured dose deviations. The presented system could potentially reduce the amount of patient-specific quality assurance measurements which currently constitute a bottleneck in the clinical workflow.

Pencil beam scanning (PBS) proton therapy requires the delivery of many thousand proton beams, each modulated for position, energy and monitor units, to provide a highly conformal patient treatment. The quality of the treatment is dependent on the delivery accuracy of each beam and at each fraction. In this work we describe the use of treatment log files, which are a record of the machine parameters for a given field delivery on a given fraction, to investigate the integrity of treatment delivery compared to the nominal planned dose. The dosimetry-relevant log file parameters are used to reconstruct the 3D dose distribution on the patient anatomy, using a TPS-independent dose calculation system. The analysis was performed for patients treated at Paul Scherrer Institute on Gantry 2, both for individual fields and per series (or plan), and delivery quality was assessed by determining the percentage of voxels in the log file dose distribution within  +/-  1% of the nominal dose. It was seen that, for all series delivered, the mean pass rate is 96.4%. Furthermore, this work establishes a correlation between the delivery quality of a field and the beam position accuracy. This correlation is evident for all delivered fields regardless of individual patient or plan characteristics. We have also detailed further usefulness of log file analysis within our clinical workflow. In summary, we have highlighted that the integrity of PBS treatment delivery is dependent on daily machine performance and is specifically highly correlated with the accuracy of beam position. We believe this information will be useful for driving machine performance improvements in the PBS field.

For radiotherapy, it is crucial to guarantee that the delivered dose matches the planned dose. Therefore, patient specific quality assurance (QA) of absolute dose distributions is necessary. Here, we investigate the potential of replacing patient specific QA for pencil beam scanned proton therapy with Monte Carlo simulations. First, the set-up of the automated Monte Carlo model is presented with an emphasis on the absolute dose validation. Second, the absolute dose results obtained from the Monte Carlo simulation for a comprehensive set of patient fields are compared to patient specific QA measurements. Absolute doses measured with the Farmer chamber are shown to be 1.4% higher than the doses measured with the Semiflex chamber. For single energy layers, Monte Carlo simulated doses are 2.1%  ±  0.4% lower than the ones measured with the ionization chamber and 1.1%  ±  1.0% lower than measurements compared to patient field verification measurements. After rescaling to account for this 1.1% discrepancy, 98 fields (94.2%) agree within 2% to measurements, the maximum difference being 2.3%. In conclusion, an automated, easy-to-use Monte Carlo calculation system has been set up. This system reproduced patient specific QA results over a wide range of cases, showing that the time consuming measurements could be reduced or even replaced using Monte Carlo simulations without jeopardizing treatment quality.

Patient specific verification (PSV) measurements for pencil beam scanning (PBS) proton therapy are resource-consuming and necessitate substantial beam time outside of clinical hours. As such, efforts to safely reduce the PSV-bottleneck in the clinical work-flow are of great interest. Here, capabilities of current PSV methods to ensure the treatment integrity were investigated and compared to an alternative approach of reconstructing the dose distribution directly from the machine control- or delivery log files with the help of an independent dose calculation (IDC). Scenarios representing a wide range of delivery or work-flow failures were identified (e.g. error in spot position, air gap or pre-absorber setting) and machine files were altered accordingly. This yielded 21 corrupted treatment files, which were delivered and measured with our clinical PSV protocol. IDC machine- and log file checks were also conducted and their sensitivity at detecting the errors compared to the measurements. Although some of the failure scenarios induced clinically relevant dose deviations in the patient geometry, the PSV measurement protocol only detected one out of 21 error scenarios. However, 11 and all 21 error scenarios were detected using dose reconstructions based on the log and machine files respectively. Our data suggests that, although commonly used in particle therapy centers, PSV measurements do a poor job detecting data transfer failures and imperfect delivery machine performance. Machine- and log-file IDCs have been shown to successfully detect erroneous work-flows and to represent a reliable addition to the QA procedure, with the potential to replace PSV.