Log file based Monte Carlo calculations for proton pencil beam scanning therapy

Beam delivery characteristics of the Hitachi carbon ion scanning system at Osaka Heavy Ion Medical Accelerator in Kansai (HIMAK)

BACKGROUND

Using the pencil beam raster scanning method employed at most carbon beam treatment facilities, spots can be moved without interrupting the beam, allowing for the delivery of a dose between spots (move dose). This technique is also known as Dose-Driven-Continuous-Scanning (DDCS). To minimize its impact on HIMAK patient dosimetry, there's an upper limit to the move dose. Spots within a layer are grouped into sets, or "break points," allowing continuous irradiation. The beam is turned off when transitioning between sets or at the end of a treatment layer or spill. The control system beam-off is accomplished by turning off the RF Knockout (RFKO) extraction and after a brief delay the High Speed Steering Magnet (HSST) redirects the beam transport away from isocenter to a beam dump.

PURPOSE

The influence of the move dose and beam on/off control on the dose distribution and irradiation time was evaluated by measurements never before reported and modelled for Hitachi Carbon DDCS.

METHOD

We conducted fixed-point and scanning irradiation experiments at three different energies, both with and without breakpoints. For fixed-point irradiation, we utilized a 2D array detector and an oscilloscope to measure beam intensity over time. The oscilloscope data enabled us to confirm beam-off and beam-on timing due to breakpoints, as well as the relative timing of the RFKO signal, HSST signal, and dose monitor (DM) signals. From these measurements, we analyzed and modelled the temporal characteristics of the beam intensity. We also developed a model for the spot shape and amplitude at isocenter occurring after the beam-off signal which we called flap dose and its dependence on beam intensity. In the case of scanning irradiation, we measured move doses using the 2D array detector and compared these measurements with our model.

RESULT

We observed that the most dominant time variation of the beam intensity was at 1 kHz and its harmonic frequencies. Our findings revealed that the derived beam intensity cannot reach the preset beam intensity when each spot belongs to different breakpoints. The beam-off time due to breakpoints was approximately 100 ms, while the beam rise time and fall time (tdecay ) were remarkably fast, about 10 ms and 0.2 ms, respectively. Moreover, we measured the time lag (tdelay ) of approximately 0.2 ms between the RFKO and HSST signals. Since tdelay ≈ tdecay at HIMAK then the HSST is activated after the residual beam intensity, resulting in essentially zero flap dose at isocenter from the HSST. Our measurements of the move dose demonstrated excellent agreement with the modelled move dose.

CONCLUSION

We conducted the first move dose measurement for a Hitachi Carbon synchrotron, and our findings, considering beam on/off control details, indicate that Hitachi's carbon synchrotron provides a stable beam at HIMAK. Our work suggests that measuring both move dose and flap dose should be part of the commissioning process and possibly using our model in the Treatment Planning System (TPS) for new facilities with treatment delivery control systems with higher beam intensities and faster beam-off control.

Monte Carlo simulation-based patient-specific QA using machine log files for line-scanning proton radiation therapy

BACKGROUND

Quality assurance (QA) is a prerequisite for safe and accurate pencil-beam proton therapy. Conventional measurement-based patient-specific QA (pQA) can only verify limited aspects of patient treatment and is labor-intensive. Thus, a better method is needed to ensure the integrity of the treatment plan.

PURPOSE

Line scanning, which involves continuous and rapid delivery of pencil beams, is a state-of-the-art proton therapy technique. Machine performance in delivering scanning protons is dependent on the complexity of the beam modulations. Moreover, it contributes to patient treatment accuracy. A Monte Carlo (MC) simulation-based QA method that reflects the uncertainty related to the machine during scanning beam delivery was developed and verified for clinical applications to pQA.

METHODS

Herein, a tool for particle simulation (TOPAS) for nozzle modeling was used, and the code was commissioned against the measurements. To acquire the beam delivery uncertainty for each plan, patient plans were delivered. Furthermore, log files recorded every 60 μs by the monitors downstream of the nozzle were exported from the treatment control system. The spot positions and monitor unit (MU) counts in the log files were converted to dipole magnet strengths and number of particles, respectively, and entered into the TOPAS. For the 68 clinical cases, MC simulations were performed in a solid water phantom, and two-dimensional (2D) absolute dose distributions at 20-mm depth were measured using an ionization chamber array (Octavius 1500, PTW, Freiburg, Germany). Consequently, the MC-simulated 2D dose distributions were compared with the measured data, and the dose distributions in the pre-treatment QA plan created with RayStation (RaySearch Laboratories, Stockholm, Sweden). Absolute dose comparisons were made using gamma analysis with 3%/3 mm and 2%/2 mm criteria for 47 clinical cases without considering daily machine output variation in the MC simulation and 21 cases with daily output variation, respectively. All cases were analyzed with 90% or 95% of passing rate thresholds.

RESULTS

For 47 clinical cases not considering daily output variations, the absolute gamma passing rates compared with the pre-treatment QA plan were 99.71% and 96.97%, and the standard deviations (SD) were 0.70% and 3.78% with the 3%/3 mm or 2%/2 mm criteria, respectively. Compared with the measurements, the passing rate of 2%/2 mm gamma criterion was 96.76% with 3.99% of SD. For the 21 clinical cases compared with pre-treatment QA plan data and measurements considering daily output variations, the 2%/2 mm absolute gamma analysis result was 98.52% with 1.43% of SD and 97.67% with 2.72% of SD, respectively. With a 95% passing rate threshold of 2%/2 mm criterion, the false-positive and false-negative were 21.8% and 8.3% for without and with considering output variation, respectively. With a 90% threshold, the false-positive and false-negative reduced to 11.4% and 0% for without and with considering output variation, respectively.

CONCLUSIONS

A log-file-based MC simulation method for patient QA of line-scanning proton therapy was successfully developed. The proposed method exhibited clinically acceptable accuracy, thereby exhibiting a potential to replace the measurement-based dosimetry QA method with a 90% gamma passing rate threshold when applying the 2%/2 mm criterion.

A fast analytical dose calculation approach for MRI-guided proton therapy

Objective.Magnetic resonance (MR) is an innovative technology for online image guidance in conventional radiotherapy and is also starting to be considered for proton therapy as well. For MR-guided therapy, particularly for online plan adaptations, fast dose calculation is essential. Monte Carlo (MC) simulations, however, which are considered the gold standard for proton dose calculations, are very time-consuming. To address the need for an efficient dose calculation approach for MRI-guided proton therapy, we have developed a fast GPU-based modification of an analytical dose calculation algorithm incorporating beam deflections caused by magnetic fields.Approach.Proton beams (70-229 MeV) in orthogonal magnetic fields (0.5/1.5 T) were simulated using TOPAS-MC and central beam trajectories were extracted to generate look-up tables (LUTs) of incremental rotation angles as a function of water-equivalent depth. Beam trajectories are then reconstructed using these LUTs for the modified ray casting dose calculation. The algorithm was validated against MC in water, different materials and for four example patient cases, whereby it has also been fully incorporated into a treatment plan optimisation regime.Main results.Excellent agreement between analytical and MC dose distributions could be observed with sub-millimetre range deviations and differences in lateral shifts <2 mm even for high densities (1000 HU). 2%/2 mm gamma pass rates were comparable to the 0 T scenario and above 94.5% apart for the lung case. Further, comparable treatment plan quality could be achieved regardless of magnetic field strength.Significance.A new method for accurate and fast proton dose calculation in magnetic fields has been developed and successfully implemented for treatment plan optimisation.

Large anatomical changes in head-and-neck cancers – a dosimetric comparison of online and offline adaptive proton therapy

Purpose

This work evaluates an online adaptive (OA) workflow for head-and-neck (H&N) intensity-modulated proton therapy (IMPT) and compares it with full offline replanning (FOR) in patients with large anatomical changes.

Methods

IMPT treatment plans are created retrospectively for a cohort of eight H&N cancer patients that previously required replanning during the course of treatment due to large anatomical changes. Daily cone-beam CTs (CBCT) are acquired and corrected for scatter, resulting in 253 analyzed fractions. To simulate the FOR workflow, nominal plans are created on the planning-CT and delivered until a repeated-CT is acquired; at this point, a new plan is created on the repeated-CT. To simulate the OA workflow, nominal plans are created on the planning-CT and adapted at each fraction using a simple beamlet weight-tuning technique. Dose distributions are calculated on the CBCTs with Monte Carlo for both delivery methods. The total treatment dose is accumulated on the planning-CT.

Results

Daily OA improved target coverage compared to FOR despite using smaller target margins. In the high-risk CTV, the median D₉₈ degradation was 1.1 % and 2.1 % for OA and FOR, respectively. In the low-risk CTV, the same metrics yield 1.3 % and 5.2 % for OA and FOR, respectively. Smaller setup margins of OA reduced the dose to all OARs, which was most relevant for the parotid glands.

Conclusion

Daily OA can maintain prescription doses and constraints over the course of fractionated treatment, even in cases of large anatomical changes, reducing the necessity for manual replanning in H&N IMPT.

Technical note: A method to evaluate the effect of scanning beam delivery error on 3D dose and its utilization on carbon ion radiotherapy for prostate cancer

PURPOSE

To establish a method for evaluating the effect of scanning ion beam delivery error on three-dimensional (3D) dose reconstructed on patients' CT based on log file.

MATERIALS AND METHODS

This study used the MATLAB program to reconstruct the 3D dose on the patient's CT based on the log file (Dose_log ) for treatment delivery accuracy check. In addition, differences between the parameters in the log file and the treatment plan, such as the spot position, spot size, and particle number, were analyzed, as well as their effects on the dose distribution. The accuracy of the dose reconstruction algorithm was verified by comparing dose from TPS (Dose_TPS ) and the dose recalculated based on the treatment plan (Dose_rec ). Twenty treatment plans of ten prostate cancer patients received carbon ion therapy, and their corresponding 160 log files were selected for analysis and treatment delivery accuracy check. The regions with dose higher than 10% of the maximum dose were selected and 2 mm/2% criteria were used for global gamma analysis. Multiple linear regression was used to evaluate the relation between dose deviation and delivery errors.

RESULTS

For the algorithm accuracy verification, the mean relative dose difference is 1.02% ± 0.12%. For prostate cancer patients treated in our facility using carbon ion radiotherapy, the average passing rate of the gamma analysis between the Dose_log and the Dose_TPS was 95.3%. The dose deviation caused by the difference in the spot position and the number of particles was smaller than that caused by the spot size deviation.

CONCLUSION

This study established a 3D dose verification method based on log files to evaluate the accuracy of daily delivered treatment doses. In our facility, the daily delivered dose accuracy of carbon ion therapy for prostate cancer was mainly affected by the spot size deviation in terms of the machine delivery part.

GPU accelerated Monte Carlo scoring of positron emitting isotopes produced during proton therapy for PET verification

Objective.Verification of delivered proton therapy treatments is essential for reaping the many benefits of the modality, with the most widely proposedin vivoverification technique being the imaging of positron emitting isotopes generated in the patient during treatment using positron emission tomography (PET). The purpose of this work is to reduce the computational resources and time required for simulation of patient activation during proton therapy using the GPU accelerated Monte Carlo code FRED, and to validate the predicted activity against the widely used Monte Carlo code GATE.Approach.We implement a continuous scoring approach for the production of positron emitting isotopes within FRED version 5.59.9. We simulate treatment plans delivered to 95 head and neck patients at Centrum Cyklotronowe Bronowice using this GPU implementation, and verify the accuracy using the Monte Carlo toolkit GATE version 9.0.Main results.We report an average reduction in computational time by a factor of 50 when using a local system with 2 GPUs as opposed to a large compute cluster utilising between 200 to 700 CPU threads, enabling simulation of patient activity within an average of 2.9 min as opposed to 146 min. All simulated plans are in good agreement across the two Monte Carlo codes. The two codes agree within a maximum of 0.95σon a voxel-by-voxel basis for the prediction of 7 different isotopes across 472 simulated fields delivered to 95 patients, with the average deviation over all fields being 6.4 × 10^-3σ.Significance.The implementation of activation calculations in the GPU accelerated Monte Carlo code FRED provides fast and reliable simulation of patient activation following proton therapy, allowing for research and development of clinical applications of range verification for this treatment modality using PET to proceed at a rapid pace.

SWFT-Net: a deep learning framework for efficient fine-tuning spot weights towards adaptive proton therapy

Objective. One critical task for adaptive proton therapy is how to perform spot weight re-tuning and reoptimize plan, both of which are time-consuming and labor intensive. We proposed a deep learning framework (SWFT-Net) to speed up such a task, a starting point for us to move towards online adaptive proton therapy.Approach. For a H&N patient case, a reference intensity modulated proton therapy plan was generated. For data augmentation, spot weights were modified to generate three datasets (DS10, DS30, DS50), corresponding to different levels of weight adjustment. For each dataset, the samples were split into the training and testing groups at a ratio of 8:2 (6400 for training, 1706 for testing). To ease the difficulty of machine learning, the residuals of dose maps and spot weights (i.e. difference relative to a reference) were used as inputs and outputs, respectively. Quantitative analyses were performed in terms of normalized root mean square error (NRMSE) of spot weights, Gamma passing rate and dose difference within the PTV.Main results. The SWFT-Net is able to generate an adapted plan in less than a second with a NVIDIA GeForce RTX 3090 GPU. For the 1706 samples in the testing dataset, the NRMSE is 0.41% (DS10), 1.05% (DS30) and 2.04% (DS50), respectively. Cold/hot spots in the dose maps after adaptation are observed. The mean relative dose difference is 0.64% (DS10), 0.92% (DS30) and 0.88% (DS50), respectively. For all three datasets, the mean Gamma passing rate is consistently over 95% for both 1 mm/1% and 3 mm/3% settings.Significance. The proposed SWFT-Net is a promising tool to help realize adaptive proton therapy. It can be used as an alternative tool to other spot fine-tuning optimization algorithms, likely demonstrating superior performance in terms of speed, accuracy, robustness and minimum human interaction. This study lays down a foundation for us to move further incorporating other factors such as daily anatomical changes and propagated PTVs, and develop a truly online adaptive workflow in proton therapy.

Adaptive proton therapy

Radiation therapy treatments are typically planned based on a single image set, assuming that the patient's anatomy and its position relative to the delivery system remains constant during the course of treatment. Similarly, the prescription dose assumes constant biological dose-response over the treatment course. However, variations can and do occur on multiple time scales. For treatment sites with significant intra-fractional motion, geometric changes happen over seconds or minutes, while biological considerations change over days or weeks. At an intermediate timescale, geometric changes occur between daily treatment fractions. Adaptive radiation therapy is applied to consider changes in patient anatomy during the course of fractionated treatment delivery. While traditionally adaptation has been done off-line with replanning based on new CT images, online treatment adaptation based on on-board imaging has gained momentum in recent years due to advanced imaging techniques combined with treatment delivery systems. Adaptation is particularly important in proton therapy where small changes in patient anatomy can lead to significant dose perturbations due to the dose conformality and finite range of proton beams. This review summarizes the current state-of-the-art of on-line adaptive proton therapy and identifies areas requiring further research.

Experimental validation of daily adaptive proton therapy

Anatomical changes during proton therapy require rapid treatment plan adaption to mitigate the associated dosimetric impact. This in turn requires a highly efficient workflow that minimizes the time between imaging and delivery. At the Paul Scherrer Institute, we have developed an online adaptive workflow, which is specifically designed for treatments in the skull-base/cranium, with the focus set on simplicity and minimizing changes to the conventional workflow. The dosimetric and timing performance of this daily adaptive proton therapy (DAPT) workflow has been experimentally investigated using an in-house developed DAPT software and specifically developed anthropomorphic phantom. After a standard treatment preparation, which includes the generation of a template plan, the treatment can then be adapted each day, based on daily imaging acquired on an in-room CT. The template structures are then rigidly propagated to this CT and the daily plan is fully re-optimized using the same field arrangement, DVH constraints and optimization settings of the template plan. After a dedicated plan QA, the daily plan is delivered. To minimize the time between imaging and delivery, clinically integrated software for efficient execution of all online adaption steps, as well as tools for comprehensive and automated QA checks, have been developed. Film measurements of an end-to-end validation of a multi-fraction DAPT treatment showed high agreement to the calculated doses. Gamma pass rates with a 3%/3 mm criteria were >92% when comparing the measured dose to the template plan. Additionally, a gamma pass rate >99% was found comparing measurements to the Monte Carlo dose of the daily plans reconstructed from the logfile, accumulated over the delivered fractions. With this, we experimentally demonstrate that the described adaptive workflow can be delivered accurately in a timescale similar to a standard delivery.

Anatomic changes in head and neck intensity-modulated proton therapy: Comparison between robust optimization and online adaptation

BACKGROUND/PURPOSE

Setup variations and anatomical changes can severely affect the quality of head and neck intensity-modulated proton therapy (IMPT) treatments. The impact of these changes can be alleviated by increasing the plan's robustness a priori, or by adapting the plan online. This work compares these approaches in the context of head and neck IMPT.

MATERIALS/METHODS

A representative cohort of 10 head and neck squamous cell carcinoma (HNSCC) patients with daily cone-beam computed tomography (CBCT) was evaluated. For each patient, three IMPT plans were created: 1- a classical robust optimization (cRO) plan optimized on the planning CT, 2- an anatomical robust optimization (aRO) plan additionally including the two first daily CBCTs and 3- a plan optimized without robustness constraints, but online-adapted (OA) daily, using a constrained spot intensity re-optimization technique only.

RESULTS

The cumulative dose following OA fulfilled the clinical objective of both the high-risk and low-risk clinical target volumes (CTV) coverage in all 10 patients, compared to 8 for aRO and 4 for cRO. aRO did not significantly increase the dose to most organs at risk compared to cRO, although the integral dose was higher. OA significantly reduced the integral dose to healthy tissues compared to both robust methods, while providing equivalent or superior target coverage.

CONCLUSION

Using a simple spot intensity re-optimization, daily OA can achieve superior target coverage and lower dose to organs at risk than robust optimization methods.

Dosimetric influence of deformable image registration uncertainties on propagated structures for online daily adaptive proton therapy of lung cancer patients

PURPOSE

A major burden of introducing an online daily adaptive proton therapy (DAPT) workflow is the time and resources needed to correct the daily propagated contours. In this study, we evaluated the dosimetric impact of neglecting the online correction of the propagated contours in a DAPT workflow.

MATERIAL AND METHODS

For five NSCLC patients with nine repeated deep-inspiration breath-hold CTs, proton therapy plans were optimised on the planning CT to deliver 60 Gy-RBE in 30 fractions. All repeated CTs were registered with six different clinically used deformable image registration (DIR) algorithms to the corresponding planning CT. Structures were propagated rigidly and with each DIR algorithm and reference structures were contoured on each repeated CT. DAPT plans were optimised with the uncorrected, propagated structures (propagated DAPT doses) and on the reference structures (ideal DAPT doses), non-adapted doses were recalculated on all repeated CTs.

RESULTS

Due to anatomical changes occurring during the therapy, the clinical target volume (CTV) coverage of the non-adapted doses reduces on average by 9.7% (V95) compared to an ideal DAPT doses. For the propagated DAPT doses, the CTV coverage was always restored (average differences in the CTV V95 < 1% compared to the ideal DAPT doses). Hotspots were always reduced with any DAPT approach.

CONCLUSION

For the patients presented here, a benefit of online DAPT was shown, even if the daily optimisation is based on propagated structures with some residual uncertainties. However, a careful (offline) structure review is necessary and corrections can be included in an offline adaption.

Fast MCsquare-Based Independent Dose Verification Platform for Pencil Beam Scanning Proton Therapy

PURPOSE

To commission MCsquare (a multi-cores CPU-based dose calculation engine) for pencil beam scanning (PBS) proton therapy, integrate it into RayStation treatment plan system (TPS) to create a dedicated platform for fast independent dose verification.

METHOD

A MCsquare-based independent dose verification platform (MC2InRS) was developed to realize automatic dose re-calculation for clinical use, including data preparation, dose calculation, 2D/3D gamma analysis. MCsquare was commissioned based on in-air lateral dose profiles, integrated depth dose, and the absolute dose of different beam energies for Proteus®ONE. MC2InRS was validated with measurement data using various targets and depths in a water phantom. This study also investigated 15 clinical cases to demonstrate the feasibility and effectiveness of MC2InRS platform in clinic practice.

RESULTS

Between simulation and measurement, the distal range differences at 80% (R80) and 20% (R20) dose levels for each energy were below 0.05 mm, and 0.1 mm, respectively, and the absolute dose differences were below 0.5%. 29 out of 36 QA planes reached a 100% gamma passing rate (GPR) for 2%/2mm criteria, and a minimum of 98.3% gamma was obtained in water phantom between simulation and measurement. For the 15 clinical cases investigated, the average 2D GPR (2%/2mm) was 95.4%, 99.3% for MCsquare vs. measurement, MCsquare vs. TPS, respectively. The average 3D GPR (2%/2mm) was 98.9%, 95.3% for MCsquare vs. TPS in water, and computed tomography (CT), respectively.

CONCLUSION

MC2InRS, a fast, independent dose verification platform, has been developed to perform dose verification with high accuracy and efficiency for Pencil Bream Scanning (PBS). Its potential to be applied in routine clinical practice has also been discussed.

Online-adaptive versus robust IMPT for prostate cancer: How much can we gain?

BACKGROUND/PURPOSE

Intensity-modulated proton therapy (IMPT) is highly sensitive to anatomical variations which can cause inadequate target coverage during treatment. Available mitigation techniques include robust treatment planning and online-adaptive IMPT. This study compares a robust planning strategy to two online-adaptive IMPT strategies to determine the benefit of online adaptation.

MATERIALS/METHODS

We derived the robustness settings and safety margins needed to yield adequate target coverage (V_95%≥98%) for >90% of 11 patients in a prostate cancer cohort (88 repeat CTs). For each patient, we also adapted a non-robust prior plan using a simple restoration and a full adaptation method. The restoration uses energy-adaptation followed by a fast spot-intensity re-optimization. The full adaptation uses energy-adaptation followed by the addition of new spots and a range-robust spot-intensity optimization. Dose was prescribed as 55 Gy(RBE) to the low-dose target (lymph nodes and seminal vesicles) with a boost to 74 Gy(RBE) to the high-dose target (prostate). Daily patient set-up was simulated using implanted intra-prostatic markers.

RESULTS

Margins of 4 and 8 mm around the high- and low-dose target regions, a 6 mm setup error and a 3% range error were found to obtain adequate target coverage for all repeat CTs of 10/11 patients (94.3% of all 88 repeat CTs). Both online-adaptive strategies yielded V_95%≥98% and better OAR sparing in 11/11 patients. Median OAR improvements up to 11%-point and 16%-point were observed when moving from robust planning to respectively restoration and full adaption.

CONCLUSION

Both full plan adaptation and simple dose restoration can increase OAR sparing besides better conforming to the target criteria compared to robust treatment planning.

Online daily adaptive proton therapy

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.