DiffuseRT: predicting likely anatomical deformations of patients undergoing radiotherapy.

Objective. Predicting potential deformations of patients can improve radiotherapy treatment planning. Here, we introduce new deep-learning models that predict likely anatomical changes during radiotherapy for head and neck cancer patients.Approach. Denoising diffusion probabilistic models (DDPMs) were developed to generate fraction-specific anatomical changes based on a reference cone-beam CT (CBCT), the fraction number and the dose distribution delivered. Three distinct DDPMs were developed: (1) theimage modelwas trained to directly generate likely future CBCTs, (2) the deformable vector field (DVF) model was trained to generate DVFs that deform a reference CBCT and (3) thehybrid modelwas trained similarly to the DVF model, but without relying on an external deformable registration algorithm. The models were trained on 9 patients with longitudinal CBCT images (224 CBCTs) and evaluated on 5 patients (152 CBCTs).Results. The generated images mainly exhibited random positioning shifts and small anatomical changes for early fractions. For later fractions, all models predicted weight losses in accordance with the training data. The distributions of volume and position changes of the body, esophagus, and parotids generated with the image and hybrid models were more similar to the ground truth distribution than the DVF model, evident from the lower Wasserstein distance achieved with the image (0.33) and hybrid model (0.30) compared to the DVF model (0.36). Generating several images for the same fraction did not yield the expected variability since the ground truth anatomical changes were only in 76% of the fractions within the 95% bounds predicted with the best model. Using the generated images for robust optimization of simplified proton therapy plans improved the worst-case clinical target volume V95 with 7% compared to optimizing with 3 mm set-up robustness while maintaining a similar integral dose.Significance. The newly developed DDPMs generate distributions similar to the real anatomical changes and have the potential to be used for robust anatomical optimization.

Robust optimization strategies for contour uncertainties in online adaptive radiation therapy.

Objective.Online adaptive radiation therapy requires fast and automated contouring of daily scans for treatment plan re-optimization. However, automated contouring is imperfect and introduces contour uncertainties. This work aims at developing and comparing robust optimization strategies accounting for such uncertainties.Approach.A deep-learning method was used to predict the uncertainty of deformable image registration, and to generate a finite set of daily contour samples. Ten optimization strategies were compared: two baseline methods, five methods that convert contour samples into voxel-wise probabilities, and three methods accounting explicitly for contour samples as scenarios in robust optimization. Target coverage and organ-at-risk (OAR) sparing were evaluated robustly for simplified proton therapy plans for five head-and-neck cancer patients.Results.We found that explicitly including target contour uncertainty in robust optimization provides robust target coverage with better OAR sparing than the baseline methods, without increasing the optimization time. Although OAR doses first increased when increasing target robustness, this effect could be prevented by additionally including robustness to OAR contour uncertainty. Compared to the probability-based methods, the scenario-based methods spared the OARs more, but increased integral dose and required more computation time.Significance.This work proposed efficient and beneficial strategies to mitigate contour uncertainty in treatment plan optimization. This facilitates the adoption of automatic contouring in online adaptive radiation therapy and, more generally, enables mitigation also of other sources of contour uncertainty in treatment planning.

Deep learning based uncertainty prediction of deformable image registration for contour propagation and dose accumulation in online adaptive radiotherapy.

Objective.Online adaptive radiotherapy aims to fully leverage the advantages of highly conformal therapy by reducing anatomical and set-up uncertainty, thereby alleviating the need for robust treatments. This requires extensive automation, among which is the use of deformable image registration (DIR) for contour propagation and dose accumulation. However, inconsistencies in DIR solutions between different algorithms have caused distrust, hampering its direct clinical use. This work aims to enable the clinical use of DIR by developing deep learning methods to predict DIR uncertainty and propagating it into clinically usable metrics.Approach.Supervised and unsupervised neural networks were trained to predict the Gaussian uncertainty of a given deformable vector field (DVF). Since both methods rely on different assumptions, their predictions differ and were further merged into a combined model. The resulting normally distributed DVFs can be directly sampled to propagate the uncertainty into contour and accumulated dose uncertainty.Main results.The unsupervised and combined models can accurately predict the uncertainty in the manually annotated landmarks on the DIRLAB dataset. Furthermore, for 5 patients with lung cancer, the propagation of the predicted DVF uncertainty into contour uncertainty yielded for both methods anexpected calibration errorof less than 3%. Additionally, theprobabilisticly accumulated dose volume histograms(DVH) encompass well the accumulated proton therapy doses using 5 different DIR algorithms. It was additionally shown that the unsupervised model can be used for different DIR algorithms without the need for retraining.Significance.Our work presents first-of-a-kind deep learning methods to predict the uncertainty of the DIR process. The methods are fast, yield high-quality uncertainty estimates and are useable for different algorithms and applications. This allows clinics to use DIR uncertainty in their workflows without the need to change their DIR implementation.

Dosimetric comparison of autocontouring techniques for online adaptive proton therapy.

Objective.Anatomical and daily set-up uncertainties impede high precision delivery of proton therapy. With online adaptation, the daily plan is reoptimized on an image taken shortly before the treatment, reducing these uncertainties and, hence, allowing a more accurate delivery. This reoptimization requires target and organs-at-risk (OAR) contours on the daily image, which need to be delineated automatically since manual contouring is too slow. Whereas multiple methods for autocontouring exist, none of them are fully accurate, which affects the daily dose. This work aims to quantify the magnitude of this dosimetric effect for four contouring techniques.Approach.Plans reoptimized on automatic contours are compared with plans reoptimized on manual contours. The methods include rigid and deformable registration (DIR), deep-learning based segmentation and patient-specific segmentation.Main results.It was found that independently of the contouring method, the dosimetric influence of usingautomaticOARcontoursis small (<5% prescribed dose in most cases), with DIR yielding the best results. Contrarily, the dosimetric effect of using theautomatic target contourwas larger (>5% prescribed dose in most cases), indicating that manual verification of that contour remains necessary. However, when compared to non-adaptive therapy, the dose differences caused by automatically contouring the target were small and target coverage was improved, especially for DIR.Significance.The results show that manual adjustment of OARs is rarely necessary and that several autocontouring techniques are directly usable. Contrarily, manual adjustment of the target is important. This allows prioritizing tasks during time-critical online adaptive proton therapy and therefore supports its further clinical implementation.

A motion model-guided 4D dose reconstruction for pencil beam scanned proton therapy.

Objective.4D dose reconstruction in proton therapy with pencil beam scanning (PBS) typically relies on a single pre-treatment 4DCT (p4DCT). However, breathing motion during the fractionated treatment can vary considerably in both amplitude and frequency. We present a novel 4D dose reconstruction method combining delivery log files with patient-specific motion models, to account for the dosimetric effect of intra- and inter-fractional breathing variability.Approach.Correlation between an external breathing surrogate and anatomical deformations of the p4DCT is established using principal component analysis. Using motion trajectories of a surface marker acquired during the dose delivery by an optical tracking system, deformable motion fields are retrospectively reconstructed and used to generate time-resolved synthetic 4DCTs ('5DCTs') by warping a reference CT. For three abdominal/thoracic patients, treated with respiratory gating and rescanning, example fraction doses were reconstructed using the resulting 5DCTs and delivery log files. The motion model was validated beforehand using leave-one-out cross-validation (LOOCV) with subsequent 4D dose evaluations. Moreover, besides fractional motion, fractional anatomical changes were incorporated as proof of concept.Main results.For motion model validation, the comparison of 4D dose distributions for the original 4DCT and predicted LOOCV resulted in 3%/3 mm gamma pass rates above 96.2%. Prospective gating simulations on the p4DCT can overestimate the target dose coverage V95%by up to 2.1% compared to 4D dose reconstruction based on observed surrogate trajectories. Nevertheless, for the studied clinical cases treated with respiratory-gating and rescanning, an acceptable target coverage was maintained with V95%remaining above 98.8% for all studied fractions. For these gated treatments, larger dosimetric differences occurred due to CT changes than due to breathing variations.Significance.To gain a better estimate of the delivered dose, a retrospective 4D dose reconstruction workflow based on motion data acquired during PBS proton treatments was implemented and validated, thus considering both intra- and inter-fractional motion and anatomy changes.

Patient-specific neural networks for contour propagation in online adaptive radiotherapy.

Objective.fast and accurate contouring of daily 3D images is a prerequisite for online adaptive radiotherapy. Current automatic techniques rely either on contour propagation with registration or deep learning (DL) based segmentation with convolutional neural networks (CNNs). Registration lacks general knowledge about the appearance of organs and traditional methods are slow. CNNs lack patient-specific details and do not leverage the known contours on the planning computed tomography (CT). This works aims to incorporate patient-specific information into CNNs to improve their segmentation accuracy.Approach.patient-specific information is incorporated into CNNs by retraining them solely on the planning CT. The resulting patient-specific CNNs are compared to general CNNs and rigid and deformable registration for contouring of organs-at-risk and target volumes in the thorax and head-and-neck regions.Results.patient-specific fine-tuning of CNNs significantly improves contour accuracy compared to standard CNNs. The method further outperforms rigid registration and a commercial DL segmentation software and yields similar contour quality as deformable registration (DIR). It is additionally 7-10 times faster than DIR.Significance.patient-specific CNNs are a fast and accurate contouring technique, enhancing the benefits of adaptive radiotherapy.

Characterization of LiF:Mg,Ti thermoluminescence detectors in low-LET proton beams at ultra-high dose rates.

Objective.This work aims at characterizing LiF:Mg,Ti thermoluminescence detectors (TLDs) for dosimetry of a 250 MeV proton beam delivered at ultra-high dose rates (UHDR). Possible dose rate effects in LiF:Mg,Ti, as well as its usability for dosimetry of narrow proton beams are investigated.Approach.LiF:Mg,Ti (TLD-100TMMicrocubes, 1 mm × 1 mm × 1 mm) was packaged in matrices of 5 × 5 detectors. The center of each matrix was irradiated with single-spot low-LET (energy >244 MeV) proton beam in the (1-4500) Gy s-1average dose rates range. A beam reconstruction procedure was applied to the detectors irradiated at the highest dose rate (Gaussian beam sigma <2 mm) to correct for volumetric averaging effects. Reference dosimetry was carried out with a diamond detector and radiochromic films. The delivered number of protons was measured by a Faraday cup, which was employed to normalize the detector responses.Main results.The lateral beam spread obtained from the beam reconstruction agreed with the one derived from the radiochromic film measurements. No dose rates effects were observed in LiF:Mg,Ti for the investigated dose rates within 3% (k= 1). On average, the dose response of the TLDs agreed with the reference detectors within their uncertainties. The largest deviation (-5%) was measured at 4500 Gy s-1.Significance.The dose rate independence of LiF:Mg,Ti TLDs makes them suitable for dosimetry of UHDR proton beams. Additionally, the combination of a matrix of TLDs and the beam reconstruction can be applied to determine the beam profile of narrow proton beams.

Limitations of phase-sorting based pencil beam scanned 4D proton dose calculations under irregular motion.

Objective.4D dose calculation (4DDC) for pencil beam scanned (PBS) proton therapy is typically based on phase-sorting of individual pencil beams onto phases of a single breathing cycle 4DCT. Understanding the dosimetric limitations and uncertainties of this approach is essential, especially for the realistic treatment scenario with irregular free breathing motion.Approach.For three liver and three lung cancer patient CTs, the deformable multi-cycle motion from 4DMRIs was used to generate six synthetic 4DCT(MRI)s, providing irregular motion (11/15 cycles for liver/lung; tumor amplitudes ∼4-18 mm). 4DDCs for two-field plans were performed, with the temporal resolution of the pencil beam delivery (4-200 ms) or with 8 phases per breathing cycle (500-1000 ms). For the phase-sorting approach, the tumor center motion was used to determine the phase assignment of each spot. The dose was calculated either using the full free breathing motion or individually repeating each single cycle. Additionally, the use of an irregular surrogate signal prior to 4DDC on a repeated cycle was simulated. The CTV volume with absolute dose differences >5% (Vdosediff>5%) and differences in CTVV95%andD5%-D95%compared to the free breathing scenario were evaluated.Main results.Compared to 4DDC considering the full free breathing motion with finer spot-wise temporal resolution, 4DDC based on a repeated single 4DCT resulted inVdosediff>5%of on average 34%, which resulted in an overestimation ofV95%up to 24%. However, surrogate based phase-sorting prior to 4DDC on a single cycle 4DCT, reduced the averageVdosediff>5%to 16% (overestimationV95%up to 19%). The 4DDC results were greatly influenced by the choice of reference cycle (Vdosediff>5%up to 55%) and differences due to temporal resolution were much smaller (Vdosediff>5%up to 10%).Significance.It is important to properly consider motion irregularity in 4D dosimetric evaluations of PBS proton treatments, as 4DDC based on a single 4DCT can lead to an underestimation of motion effects.

Ultra-high dose rate dosimetry for pre-clinical experiments with mm-small proton fields.

PURPOSE: To characterize an experimental setup for ultra-high dose rate (UHDR) proton irradiations, and to address the challenges of dosimetry in millimetre-small pencil proton beams. METHODS: At the PSI Gantry 1, high-energy transmission pencil beams can be delivered to biological samples and detectors up to a maximum local dose rate of âˆ¼9000 Gy/s. In the presented setup, a Faraday cup is used to measure the delivered number of protons up to ultra-high dose rates. The response of transmission ion-chambers, as well as of different field detectors, was characterized over a wide range of dose rates using the Faraday cup as reference. RESULTS: The reproducibility of the delivered proton charge was better than 1 % in the proposed experimental setup. EBT3 films, Al2O3:C optically stimulated luminescence detectors and a PTW microDiamond were used to validate the predicted dose. Transmission ionization chambers showed significant volume ion-recombination (>30 % in the tested conditions) which can be parametrized as a function of the maximum proton current density. Over the considered range, EBT3 films, inorganic scintillator-based screens and the PTW microDiamond were demonstrated to be dose rate independent within ±3 %, ±1.8 % and ±1 %, respectively. CONCLUSIONS: Faraday cups are versatile dosimetry instruments that can be used for dose estimation, field detector characterization and on-line dose verification for pre-clinical experiments in UHDR proton pencil beams. Among the tested detectors, the commercial PTW microDiamond was found to be a suitable option to measure real time the dosimetric properties of narrow pencil proton beams for dose rates up to 2.2 kGy/s.

Citizen seismology helps decipher the 2021 Haiti earthquake.

On 14 August 2021, the moment magnitude (Mw) 7.2 Nippes earthquake in Haiti occurred within the same fault zone as its devastating 2010 Mw 7.0 predecessor, but struck the country when field access was limited by insecurity and conventional seismometers from the national network were inoperative. A network of citizen seismometers installed in 2019 provided near-field data critical to rapidly understand the mechanism of the mainshock and monitor its aftershock sequence. Their real-time data defined two aftershock clusters that coincide with two areas of coseismic slip derived from inversions of conventional seismological and geodetic data. Machine learning applied to data from the citizen seismometer closest to the mainshock allows us to forecast aftershocks as accurately as with the network-derived catalog. This shows the utility of citizen science contributing to our understanding of a major earthquake.

Faraday cup for commissioning and quality assurance for proton pencil beam scanning beams at conventional and ultra-high dose rates.

Recently, proton therapy treatments delivered with ultra-high dose rates have been of high scientific interest, and the Faraday cup (FC) is a promising dosimetry tool for such experiments. Different institutes use different FC designs, and either a high voltage guard ring, or the combination of an electric and a magnetic field is employed to minimize the effect of secondary electrons. The authors first investigate these different approaches for beam energies of 70, 150, 230 and 250 MeV, magnetic fields between 0 and 24 mT and voltages between -1000 and 1000 V. When applying a magnetic field, the measured signal is independent of the guard ring voltage, indicating that this setting minimizes the effect of secondary electrons on the reading of the FC. Without magnetic field, applying the negative voltage however decreases the signal by an energy dependent factor up to 1.3% for the lowest energy tested and 0.4% for the highest energy, showing an energy dependent response. Next, the study demonstrates the application of the FC up to ultra-high dose rates. FC measurements with cyclotron currents up to 800 nA (dose rates of up to approximately 1000 Gy s-1) show that the FC is indeed dose rate independent. Then, the FC is applied to commission the primary gantry monitor for high dose rates. Finally, short-term reproducibility of the monitor calibration is quantified within single days, showing a standard deviation of 0.1% (one sigma). In conclusion, the FC is a promising, dose rate independent tool for dosimetry up to ultra-high dose rates. Caution is however necessary when using a FC without magnetic field, as a guard ring with high voltage alone can introduce an energy dependent signal offset.

A static beam delivery device for fast scanning proton arc-therapy.

Arc-therapy is a dose delivery technique regularly applied in photon radiation therapy, and is currently subject of great interest for proton therapy as well. In this technique, proton beams are aimed at a tumor from different continuous ranges of incident directions (so called 'arcs'). This technique can potentially yield a better dose conformity around the tumor and a very low dose in the surrounding healthy tissue. Currently, proton-arc therapy is performed by rotating a proton gantry around the patient, adapting the normally used dose-delivery method to the arc-specific motion of the gantry. Here we present first results from a feasibility study of the conceptual design of a new static fast beam delivery device/system for proton-arc therapy, which could be used instead of a gantry. In this novel concept, the incident angle of proton beams can be set rapidly by only changing field strengths of small magnets. This device eliminates the motion of the heavy gantry and related hardware. Therefore, a reduction of the total treatment time is expected. In the feasibility study presented here, we concentrate on the concept of the beam transport. Based on several simple, but realistic assumptions and approximations, proton tracking calculations were performed in a 3D magnetic field map, to calculate the beam transport in this device and to investigate and address several beam-optics challenges. We propose and simulate corresponding solutions and discuss their outcomes. To enable the implementation of some usually applied techniques in proton therapy, such as pencil beam scanning, energy modulation and beam shaping, we present and discuss our proposals. Here we present the concept of a new idea to perform fast proton arc-scanning and we report on first results of a feasibility study. Based on these results, we propose several options and next steps in the design.

Update on yesterday's dose-Use of delivery log-files for daily adaptive proton therapy (DAPT).

In daily adaptive proton therapy (DAPT), the treatment plan is re-optimized on a daily basis. It is a straightforward idea to incorporate information from the previous deliveries during the optimization to refine this daily proton delivery. A feedback signal was used to correct for delivery errors and errors from an inaccurate dose calculation used for plan optimization. This feedback signal consisted of a dose distribution calculated with a Monte Carlo algorithm and was based on the spot delivery information from the previous deliveries in the form of log-files. We therefore called the method Update On Yesterday's Dose (UYD). The UYD method was first tested with a simulated DAPT treatment and second with dose measurements using an anthropomorphic phantom. For both, the simulations and the measurements, a better agreement between the delivered and the intended dose distribution could be observed using UYD. Gamma pass rates (1%/1 mm) increased from around 75% to above 90%, when applying the closed-loop correction for the simulations, as well as the measurements. For a DAPT treatment, positioning errors or anatomical changes are incorporated during the optimization and therefore are less dominant in the overall dose uncertainty. Hence, the relevance of algorithm or delivery machine errors even increases compared to standard therapy. The closed-loop process described here is a method to correct for these errors, and potentially further improve DAPT.

Assessing the advantages of CFR-PEEK over titanium spinal stabilization implants in proton therapy-a phantom study.

High-density materials, such as titanium, used for spinal stabilization, introduces several critical issues in proton therapy (PT). Artefacts affect both contouring and dose calculation. Subsequently, artefacts need to be corrected which is a time-consuming process. Besides, titanium causes proton interactions that are unaccounted for in dose calculation. The result is a suboptimal treatment plan, and indeed decreased local controls have been reported for these patients. Carbon fiber reinforced polyetheretherketone (CFR-PEEK) implant material, which is of low density, potentially solves these issues. For this study, we designed a unique phantom to compare the effects of titanium and CFR-PEEK implants in PT. The phantom contains four interchangeable spinal inserts representing a native spine, and three different spinal stabilizations consisting of titanium only, CFR-PEEK only, and a combination of titanium and CFR-PEEK. All phantom scenarios received the standard treatment workup. Two planning approaches were investigated: a single field plan and a multi-field optimized plan with spinal cord sparing. For both plans we analyzed the following aspects: total volume of artefacts on CT images, time required for artefact correction, effect of planning CT correction on dose calculation, plan robustness to range and set up uncertainties, and finally the discrepancy between the calculated dose and the delivered dose with Gafchromic® film. The CFR-PEEK implant had a 90% reduction of artefacts on CT images and subsequently severely reduced the time for artefact correction with respect to the titanium-only implant. Furthermore, the CFR-PEEK as opposed to titanium did not influence the robustness of the plan. Finally, the titanium implants led to hardware-related discrepancies between the planned and the measured dose while the CFR-PEEK implant showed good agreement. As opposed to titanium, CFR-PEEK has none to minor effects on PT. The use of CFR-PEEK is expected to optimize treatment and possibly improve outcomes for patients that require spinal stabilization.

Outcomes, Prognostic Factors and Salvage Treatment for Recurrent Chordoma After Pencil Beam Scanning Proton Therapy at the Paul Scherrer Institute.

AIMS: The outcome of chordoma patients with local or distant failure after proton therapy is not well established. We assessed the disease-specific (DSS) and overall survival of patients recurring after proton therapy and evaluated the prognostic factors affecting DSS. MATERIALS AND METHODS: A retrospective analysis was carried out of 71 recurring skull base (n = 36) and extracranial (n = 35) chordoma patients who received adjuvant proton therapy at initial presentation (n = 42; 59%) or after post-surgical recurrence (n = 29; 41%). The median proton therapy dose delivered was 74 GyRBE (range 62-76). The mean age was 55 ± 14.2 years and the male/female ratio was about one. RESULTS: The median time to first failure after proton therapy was 30.8 months (range 3-152). Most patients (n = 59; 83%) presented with locoregional failure only. There were only 12 (17%) distant failures, either with (n = 5) or without (n = 7) synchronous local failure. Eight patients (11%) received no salvage therapy for their treatment failure after proton therapy. Salvage treatments after proton therapy failure included surgery, systemic therapy and additional radiotherapy in 45 (63%), 20 (28%) and eight (11%) patients, respectively. Fifty-three patients (75%) died, most often from disease progression (47 of 53 patients; 89%). The median DSS and overall survival after failure was 3.9 (95% confidence interval 3.1-5.1) and 3.4 (95% confidence interval 2.5-4.4) years, respectively. On multivariate analysis, extracranial location and late failure (≥31 months after proton therapy) were independent favourable prognostic factors for DSS. CONCLUSION: The survival of chordoma patients after a treatment failure following proton therapy is poor, particularly for patients who relapse early or recur in the skull base. Although salvage treatment is administered to most patients with uncontrolled disease, they will ultimately die as a result of disease progression in most cases.

Pencil Beam Scanning Proton Therapy for Paediatric Neuroblastoma with Motion Mitigation Strategy for Moving Target Volumes.

AIMS: More efforts are required to minimise late radiation side-effects for paediatric patients. Pencil beam scanning proton beam therapy (PBS-PT) allows increased sparing of normal tissues while maintaining conformality, but is prone to dose degradation from interplay effects due to respiratory motion. We report our clinical experience of motion mitigation with volumetric rescanning (vRSC) and outcomes of children with neuroblastoma. MATERIALS AND METHODS: Nineteen patients with high-risk (n = 16) and intermediate-risk (n = 3) neuroblastoma received PBS-PT. The median age at PBS-PT was 3.5 years (range 1.2-8.6) and the median PBS-PT dose was 21 Gy (relative biological effectiveness). Most children (89%) were treated under general anaesthesia. Seven patients (37%) underwent four-dimensional computed tomography for motion assessment and were treated with vRSC for motion mitigation. RESULTS: The mean result of maximum organ motion was 2.7 mm (cranial-caudal), 1.2 mm (left-right), 1.0 mm (anterior-posterior). Four anaesthetised children (21%) showing <5 mm motion had four-dimensional dose calculations (4DDC) to guide the number of vRSC. The mean deterioration or improvement to the planning target volume covered by 95% of the prescribed dose compared with static three-dimensional plans were: 4DDC no vRSC, -0.6%; 2 vRSC, +0.3%; 4 vRSC, +0.3%; and 8 vRSC, +0.1%. With a median follow-up of 14.9 months (range 2.7-49.0) there were no local recurrences. The 2-year overall survival was 94% and distant progression-free survival was 76%. Acute grade 2-4 toxicity was 11%. During the limited follow-up time, no late toxicities were observed. CONCLUSIONS: The early outcomes of mainly high-risk patients with neuroblastoma treated with PBS-PT were excellent. With a subset of our cohort undergoing PBS-PT with vRSC we have shown that it is logistically feasible and safe. The clinical relevance of vRSC is debatable in anaesthetised children with small pre-PBS-PT motion of <5 mm.

The dependence of interplay effects on the field scan direction in PBS proton therapy.

The literature is controversial about the scan direction dependency of interplay effects in pencil beam scanning (PBS) treatment of moving targets. A directional effect is supported by many simulation studies, whereas the experimental data are mostly limited to simple geometries, not reflecting realistically clinical treatment plans. We have compared increasingly complex treatment fields, from a homogeneous single energy layer to a more modulated lung plan, under identical experimental settings, seeking evidence for differences in motion mitigation due to the selection of primary scanning direction. In total, 120 experimental samples were taken, combining two primary scan directions and three rescanning regimes with different motion scenarios. 4D dose distributions were measured in water with a moving ionisation chamber array and compared to those of a stationary delivery using 2D gamma analysis. Each plan has been verified twice for the same rescanning regime and motion scenario, changing the meandering direction in between to scan perpendicularly to, or along, the target motion. Additionally, machine log files of the lung plan, together with 4DCT data, were used to calculate the dose distribution that such deliveries would have produced in the patient. The primary meandering direction has a clear influence on measured dose distributions when considering a single energy layer. Introducing spot weight modulation and multiple energy layers however, makes the dynamic of interplay more complex and difficult to predict. Overall, gamma (3%/3 mm) differences between scanning along or orthogonal to the target motion follow a normal distribution [Formula: see text] when considering multiple motion scenarios and rescanning regimes. Nevertheless, data spread [Formula: see text] is significant enough such that, for individual experiments and set-ups, a dependency may be observed even if this is not a general result. Patient reconstructed doses follow the same trend, the two primary scan directions producing statistically insignificant differences in dose distributions in terms of conformity or homogeneity. Except for extremely simplified cases of mono-energetic and homogeneous treatment fields, the interplay effect has been found to be only marginally influenced by the choice of the primary scanning direction.

Patient positioning verification for proton therapy using proton radiography.

We present a proof of principle, experimental validation of the potential of proton 'Range Probes' (RP) for patient positioning verification in proton therapy. In this work, we have evaluated experimentally the accuracy of RP by using tissue-like samples and an in-house developed multilayer ionization chamber (MLIC). In addition we build on our previous, simulation based work to present first experimental measurements of RP through anthropomorphic phantoms to detect either rotational or translational positioning errors. For this, a technique has been proposed to characterize the residual integral depth dose curve (RIDDC) after range mixing. This parametrization has been used to evaluate the similarity between Monte Carlo calculated error scenarios of the database and the measured RIDDC, while considering the intrinsic uncertainties of both modalities in order to deduce the positioning error. Finally, the additional dose applied to the patient when using clinical RP with known fluence has been estimated by measuring the local dose of a single RP. In tissue phantoms, the prediction accuracy of the water equivalent path length was 0.70%, with the highest deviations being found in low density samples (up to 5.67%). In addition, the results of the patient positioning verification measurements demonstrated that using carefully selected RPs, 1D translational or rotational errors could be detected with an accuracy of 1 mm and 2°, respectively, and that these would be associated with a low additional dose burden to the patient. In summary, these promising results suggest that the RP method could be a simple, fast and low-dose tool for verifying patient set-up during proton therapy treatment.

Alternatives to patient specific verification measurements in proton therapy: a comparative experimental study with intentional errors.

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.

Validating a Monte Carlo approach to absolute dose quality assurance for proton pencil beam scanning.

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.