Quantification of proton dose calculation accuracy in the lung

Technical note: Radiological clinical equivalence for phantom materials in carbon ion therapy

PURPOSE

As carbon ion radiotherapy increases in use, there are limited phantom materials for heterogeneous or anthropomorphic phantom measurements. This work characterized the radiological clinical equivalence of several phantom materials in a therapeutic carbon ion beam.

METHODS

Eight materials were tested for radiological material-equivalence in a carbon ion beam. The materials were computed tomography (CT)-scanned to obtain Hounsfield unit (HU) values, then irradiated in a monoenergetic carbon ion beam to determine relative linear stopping power (RLSP). The corresponding HU and RLSP for each phantom material were compared to clinical carbon ion calibration curves. For absorbed dose comparison, ion chamber measurements were made in the center of a carbon ion spread-out Bragg peak (SOBP) in water and in the phantom material, evaluating whether the material perturbed the absorbed dose measurement beyond what was predicted by the HU-RLSP relationship.

RESULTS

Polyethylene, solid water (Gammex and Sun Nuclear), Blue Water (Standard Imaging), and Techtron HPV had measured RLSP values that agreed within ±4.2% of RLSP values predicted by the clinical calibration curve. Measured RLSP for acrylic was 7.2% different from predicted. The agreement for balsa wood and cork varied between samples. Ion chamber measurements in the phantom materials were within 0.1% of ion chamber measurements in water for most materials (solid water, Blue Water, polyethylene, and acrylic), and within 1.9% for the rest of the materials (balsa wood, cork, and Techtron HPV).

CONCLUSIONS

Several phantom materials (Blue Water, polyethylene, solid water [Gammex and Sun Nuclear], and Techtron HPV) are suitable for heterogeneous phantom measurements for carbon ion therapy. Low density materials should be carefully characterized due to inconsistencies between samples.

A systematic approach for calibrating a Monte Carlo code to a treatment planning system for obtaining dose, LET, variable proton RBE and out-of-field dose

Objective. While integration of variable relative biological effectiveness (RBE) has not reached full clinical implementation, the importance of having the ability to recalculate proton treatment plans in a flexible, dedicated Monte Carlo (MC) code cannot be understated . Here we provide a step-wise method for calibrating dose from a MC code to a treatment planning system (TPS), to obtain required parameters for calculating linear energy transfer (LET), variable RBE and in general enabling clinical realistic research studies beyond the capabilities of a TPS.Approach. Initially, Pristine Bragg peaks (PBP) were calculated in both the Eclipse TPS and the FLUKA MC code. A rearranged Bortfeld energy-range relation was applied to the initial energy of the beam to fine-tune the range of the MC code at 80% dose level distal to the PBP. The energy spread was adapted by dividing the TPS range by the MC range for dose level 80%-20% distal to the PBP. Density and relative proton stopping power were adjusted by comparing the TPS and MC for different Hounsfield units. To find the relationship of dose per primary particle from the MC to dose per monitor unit in the TPS, integration was applied to the area of the Bragg curve. The calibration was validated for spread-out Bragg peaks (SOBP) in water and patient treatment plans. Following the validation, variable RBE were calculated using established models.Main results.The PBPs ranges were within ±0.3mm threshold, and a maximum of 5.5% difference for the SOBPs was observed. The patient validation showed excellent dose agreement between the TPS and MC, with the greatest differences for the lung tumor patient.Significance. Aprocedure for calibrating a MC code to a TPS was developed and validated. The procedure enables MC-based calculation of dose, LET, variable RBE, advanced (secondary) particle tracking and more from treatment plans.

Millisecond speed deep learning based proton dose calculation with Monte Carlo accuracy

Objective.Next generation online and real-time adaptive radiotherapy workflows require precise particle transport simulations in sub-second times, which is unfeasible with current analytical pencil beam algorithms (PBA) or Monte Carlo (MC) methods. We present a deep learning based millisecond speed dose calculation algorithm (DoTA) accurately predicting the dose deposited by mono-energetic proton pencil beams for arbitrary energies and patient geometries.Approach.Given the forward-scattering nature of protons, we frame 3D particle transport as modeling a sequence of 2D geometries in the beam's eye view. DoTA combines convolutional neural networks extracting spatial features (e.g. tissue and density contrasts) with a transformer self-attention backbone that routes information between the sequence of geometry slices and a vector representing the beam's energy, and is trained to predict low noise MC simulations of proton beamlets using 80 000 different head and neck, lung, and prostate geometries.Main results.Predicting beamlet doses in 5 ± 4.9 ms with a very high gamma pass rate of 99.37 ± 1.17% (1%, 3 mm) compared to the ground truth MC calculations, DoTA significantly improves upon analytical pencil beam algorithms both in precision and speed. Offering MC accuracy 100 times faster than PBAs for pencil beams, our model calculates full treatment plan doses in 10-15 s depending on the number of beamlets (800-2200 in our plans), achieving a 99.70 ± 0.14% (2%, 2 mm) gamma pass rate across 9 test patients.Significance.Outperforming all previous analytical pencil beam and deep learning based approaches, DoTA represents a new state of the art in data-driven dose calculation and can directly compete with the speed of even commercial GPU MC approaches. Providing the sub-second speed required for adaptive treatments, straightforward implementations could offer similar benefits to other steps of the radiotherapy workflow or other modalities such as helium or carbon treatments.

Experimental validation of 4D log file-based proton dose reconstruction for interplay assessment considering amplitude-sorted 4DCTs

PURPOSE

The unpredictable interplay between dynamic proton therapy delivery and target motion in the thorax can lead to severe dose distortions. A fraction-wise four-dimensional (4D) dose reconstruction workflow allows for the assessment of the applied dose after patient treatment while considering the actual beam delivery sequence extracted from machine log files, the recorded breathing pattern and the geometric information from a 4D computed tomography scan (4DCT). Such an algorithm capable of accounting for amplitude-sorted 4DCTs was implemented and its accuracy as well as its sensitivity to input parameter variations was experimentally evaluated.

METHODS

An anthropomorphic thorax phantom with a movable insert containing a target surrogate and a radiochromic film was irradiated with a monoenergetic field for various 1D target motion forms (sin, sin4) and peak-to-peak amplitudes (5/10/15/20/30 mm). The measured characteristic film dose distributions were compared to the respective sections in the 4D reconstructed doses using a 2D γ-analysis (3mm, 3%); γ-pass rates were derived for different dose grid resolutions (1mm/3mm) and deformable image registrations (DIR, automatic/manual) applied during the 4D dose reconstruction process. In an additional analysis, the sensitivity of reconstructed dose distributions against potential asynchronous timing of the motion and machine log files was investigated for both a monoenergetic field and more realistic 4D robustly optimized fields by artificially introduced offsets of ± 1/5/25/50/250 ms. The resulting dose distributions with asynchronized log files were compared to those with synchronized log files by means of a 3D γ-analysis (1mm, 1%) and the evaluation of absolute dose differences.

RESULTS

The induced characteristic interplay patterns on the films were well reproduced by the 4D dose reconstruction with 2D γ-pass rates ≥95% for almost all cases with motion magnitudes ≤15 mm. In general, the 2D γ-pass rates showed a significant decrease for larger motion amplitudes and increase when using a finer dose grid resolution but were not affected by the choice of motion form (sin, sin4). There was also a trend, though not statistically significant, towards the manually defined DIR for better quality of the reconstructed dose distributions in the area imaged by the film. The 4D dose reconstruction results for the monoenergetic as well as the 4D robustly optimized fields were robust against small asynchronies between motion and machine log files of up to 5 ms, which is in the order of potential network latencies.

CONCLUSIONS

We have implemented a 4D log file-based proton dose reconstruction that accounts for amplitude-sorted 4DCTs. Its accuracy was proven to be clinically acceptable for target motion magnitudes of up to 15 mm. Particular attention should be paid to the synchronization of the log file generating systems as the reconstructed dose distribution may vary with log file asynchronies larger than those caused by realistic network delays. This article is protected by copyright. All rights reserved.

Report of AAPM Task Group 290: Respiratory motion management for particle therapy

Dose uncertainty induced by respiratory motion remains a major concern for treating thoracic and abdominal lesions using particle beams. This Task Group report reviews the impact of tumor motion and dosimetric considerations in particle radiotherapy, current motion‐management techniques, and limitations for different particle‐beam delivery modes (i.e., passive scattering, uniform scanning, and pencil‐beam scanning). Furthermore, the report provides guidance and risk analysis for quality assurance of the motion‐management procedures to ensure consistency and accuracy, and discusses future development and emerging motion‐management strategies. This report supplements previously published AAPM report TG76, and considers aspects of motion management that are crucial to the accurate and safe delivery of particle‐beam therapy. To that end, this report produces general recommendations for commissioning and facility‐specific dosimetric characterization, motion assessment, treatment planning, active and passive motion‐management techniques, image guidance and related decision‐making, monitoring throughout therapy, and recommendations for vendors. Key among these recommendations are that: (1) facilities should perform thorough planning studies (using retrospective data) and develop standard operating procedures that address all aspects of therapy for any treatment site involving respiratory motion; (2) a risk‐based methodology should be adopted for quality management and ongoing process improvement.

Outcomes of and treatment planning considerations for a hybrid technique delivering proton pencil-beam scanning radiation to women with metal-containing tissue expanders undergoing post-mastectomy radiation

BACKGROUND

Following mastectomy, immediate breast reconstruction often involves the use of temporary tissue expanders (TEs). TEs contain metallic ports (MPs), which complicate proton pencil-beam scanning (PBS) planning. A technique was implemented for delivering PBS post-mastectomy radiation (PMRT) to patients with TEs and MPs.

METHODS

A protocol utilizing a hybrid single- and multi-field optimization (SFO, MFO) technique was developed. Plans were robustly optimized using a Monte Carlo algorithm. A CTV_eval structure including chest wall (CW) and regional nodal (RNI) targets and excluding the TE was evaluated. Organ at risk (OAR) dosimetry and acute toxicities were analyzed.

RESULTS

Twenty-nine women were treated with this technique. A 2-field SFO technique was used superior and inferior to the MP, with a 3 or 4-field MFO technique used at the level of the MP. Virtual blocks were utilized so that beams did not travel through the MP. A port-to-CW distance of 1 cm was required. Patients underwent daily image-guidance to ensure the port remained within a 0.5 cm internal planning volume (ITV). Median RT dose to CTV_eval was 50.4 Gy (45.0-50.4). Median 95% CTV_eval coverage was 99.5% (95-100). Optically stimulated luminescent dosimeter (OSLD) readings were available for 8 patients and correlated to the dose measurements in the treatment planning system (TPS); median OSLD ratio was 0.99 (range, 0.93-1.02).

CONCLUSIONS

Delivering PMRT with PBS for women with metal-containing TEs using a hybrid SFO/MFO technique is feasible, reproducible, and achieves excellent dose distributions. Specialized planning and image-guidance techniques are required to safely utilize this treatment in the clinic.

FRoG dose computation meets Monte Carlo accuracy for proton therapy dose calculation in lung

PURPOSE

To benchmark and evaluate the clinical viability of novel analytical GPU-accelerated and CPU-based Monte Carlo (MC) dose-engines for spot-scanning intensity-modulated-proton-therapy (IMPT) towards the improvement of lung cancer treatment.

METHODS

Nine patient cases were collected from the CNAO clinical experience and The Cancer Imaging Archive-4D-Lung-Database for in-silico study. All plans were optimized with 2 orthogonal beams in RayStation (RS) v.8. Forward calculations were performed with FRoG, an independent dose calculation system using a fast robust approach to the pencil beam algorithm (PBA), RS-MC (CPU for v.8) and general-purpose MC (gp-MC). Dosimetric benchmarks were acquired via irradiation of a lung-like phantom and ionization chambers for both a single-field-uniform-dose (SFUD) and IMPT plans. Dose-volume-histograms, dose-difference and γ-analyses were conducted.

RESULTS

With respect to reference gp-MC, the average dose to the GTV was 1.8% and 2.3% larger for FRoG and the RS-MC treatment planning system (TPS). FRoG and RS-MC showed a local γ-passing rate of ~96% and ~93%. Phantom measurements confirmed FRoG's high accuracywith a deviation < 0.1%.

CONCLUSIONS

Dose calculation performance using the GPU-accelerated analytical PBA, MC-TPS and gp-MC code were well within clinical tolerances. FRoG predictions were in good agreement with both the full gp-MC and experimental data for proton beams optimized for thoracic dose calculations. GPU-accelerated dose-engines like FRoG may alleviate current issues related to deficiencies in current commercial analytical proton beam models. The novel approach to the PBA implemented in FRoG is suitable for either clinical TPS or as an auxiliary dose-engine to support clinical activity for lung patients.

Physics of Particle Beam and Hypofractionated Beam Delivery in NSCLC

The dosimetric advantages of particle therapy lead to significantly reduced integral dose to normal tissues, making it an attractive treatment option for body sites such as the thorax. With reduced normal tissue dose comes the potential for dose escalation, toxicity reduction, or hypofractionation. While proton and heavy ion therapy have been used extensively for NSCLC, there are challenges in planning and delivery compared with X-ray-based radiation therapy. Particularly, range uncertainties compounded by breathing motion have to be considered. This article summarizes the current state of particle therapy for NSCLC with a specific focus on the impact of dosimetric uncertainties in planning and delivery.

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.

Improving Proton Dose Calculation Accuracy by Using Deep Learning

Introduction

Pencil beam (PB) dose calculation is fast but inaccurate due to the approximations when dealing with inhomogeneities. Monte Carlo (MC) dose calculation is the most accurate method but it is time consuming. The aim of this study was to develop a deep learning model that can boost the accuracy of PB dose calculation to the level of MC dose by converting PB dose to MC dose for different tumor sites.

Methods

The proposed model uses the PB dose and CT image as inputs to generate the MC dose. We used 290 patients (90 head and neck, 93 liver, 75 prostate and 32 lung) to train, validate, and test the model. For each tumor site, we performed four numerical experiments to explore various combinations of training datasets.

Results

Training the model on data from all tumor sites together and using the dose distribution of each individual beam as input yielded the best performance for all four tumor sites. The average gamma passing rate (1mm/1%) between the converted and the MC dose was 92.8%, 92.7%, 89.7% and 99.6% for head and neck, liver, lung, and prostate test patients, respectively. The average dose conversion time for a single field was less than 4 seconds. The trained model can be adapted to new datasets through transfer learning.

Conclusions

Our deep learning-based approach can quickly boost the accuracy of PB dose to that of MC dose. The developed model can be added to the clinical workflow of proton treatment planning to improve dose calculation accuracy.

Retrospective Planning Study of Patients with Superior Sulcus Tumours Comparing Pencil Beam Scanning Protons to Volumetric-Modulated Arc Therapy

AIMS

Twenty per cent of patients with non-small cell lung cancer present with stage III locally advanced disease. Precision radiotherapy with pencil beam scanning (PBS) protons may improve outcomes. However, stage III is a heterogeneous group and accounting for complex tumour motion is challenging. As yet, it remains unclear as to whom will benefit. In our retrospective planning study, we explored if patients with superior sulcus tumours (SSTs) are a select cohort who might benefit from this treatment.

MATERIALS AND METHODS

Patients with SSTs treated with radical radiotherapy using four-dimensional planning computed tomography between 2010 and 2015 were identified. Tumour motion was assessed and excluded if greater than 5 mm. Photon volumetric-modulated arc therapy (VMAT) and PBS proton single-field optimisation plans, with and without inhomogeneity corrections, were generated retrospectively. Robustness analysis was assessed for VMAT and PBS plans involving: (i) 5 mm geometric uncertainty, with an additional 3.5% range uncertainty for proton plans; (ii) verification plans at maximal inhalation and exhalation. Comparative dosimetric and robustness analyses were carried out.

RESULTS

Ten patients were suitable. The mean clinical target volume D95 was 98.1% ± 0.4 (97.5-98.8) and 98.4% ± 0.2 (98.1-98.9) for PBS and VMAT plans, respectively. All normal tissue tolerances were achieved. The same four PBS and VMAT plans failed robustness assessment. Inhomogeneity corrections minimally impacted proton plan robustness and made it worse in one case. The most important factor affecting target coverage and robustness was the clinical target volume entering the spinal canal. Proton plans significantly reduced the mean lung dose (by 21.9%), lung V5, V10, V20 (by 47.9%, 36.4%, 12.1%, respectively), mean heart dose (by 21.4%) and thoracic vertebra dose (by 29.2%) (P < 0.05).

CONCLUSIONS

In this planning study, robust PBS plans were achievable in carefully selected patients. Considerable dose reductions to the lung, heart and thoracic vertebra were possible without compromising target coverage. Sparing these lymphopenia-related organs may be particularly important in this era of immunotherapy.

Comparison of weekly and daily online adaptation for head and neck intensity-modulated proton therapy

The high conformality of intensity-modulated proton therapy (IMPT) dose distributions causes treatment plans to be sensitive to geometrical changes during the course of a fractionated treatment. This can be addressed using adaptive proton therapy (APT). One important question in APT is the frequency of adaptations performed during a fractionated treatment, which is related to the question whether plan adaptation has to be done online or offline. The purpose of this work is to investigate the impact of weekly and daily online IMPT plan adaptation on the treatment quality for head and neck patients. A cohort of ten head and neck patients with daily acquired cone-beam CT (CBCT) images was evaluated retrospectively. Dose tracking of the IMPT treatment was performed for three scenarios: base plan with no adaptation (BP), weekly online adaptation (OA_W), and daily online adaptation (OA_D). Both adaptation schemes used an in-house developed online APT workflow, performing Monte Carlo (MC) dose calculations on scatter-corrected CBCTs. IMPT plan adaptation was achieved by only tuning the weights of a subset of beamlets, based on deformable image registration from the planning CT to each CBCT. Although OA_Dmitigated random delivery errors more effectively than OA_Won a fraction per fraction basis, both OA_Wand OA_Dachieved the clinical goals for all ten patients, while BP failed for six cases. In the high-risk CTV, accumulated values of D_98%ranged between 97.15% and 99.73% of the prescription dose for OA_D, with a median of 98.07%. For OA_W, values between 95.02% and 99.26% were obtained, with a median of 97.61% of the prescription dose. Otherwise, the dose to most organs at risk was similar for all three scenarios. Globally, our results suggest that OA_Wcould be used as an alternative approach to OA_Dfor most patients in order to reduce the clinical workload.

Evaluation of continuous beam rescanning versus pulsed beam in pencil beam scanned proton therapy for lung tumours

The treatment of moving targets with pencil beam scanned proton therapy (PBS-PT) may rely on rescanning strategies to smooth out motion induced dosimetric disturbances. PBS-PT machines, such as Proteus®Plus (PPlus) and Proteus®One (POne), deliver a continuous or a pulsed beam, respectively. In PPlus, scaled (or no) rescanning can be applied, while POne implies intrinsic 'rescanning' due to its pulsed delivery. We investigated the efficacy of these PBS-PT delivery types for the treatment of lung tumours. In general, clinically acceptable plans were achieved, and PPlus and POne showed similar effectiveness.

Anthropomorphic lung phantom based validation of in-room proton therapy 4D-CBCT image correction for dose calculation

PURPOSE

Ventilation-induced tumour motion remains a challenge for the accuracy of proton therapy treatments in lung patients. We investigated the feasibility of using a 4D virtual CT (4D-vCT) approach based on deformable image registration (DIR) and motion-aware 4D CBCT reconstruction (MA-ROOSTER) to enable accurate daily proton dose calculation using a gantry-mounted CBCT scanner tailored to proton therapy.

METHODS

Ventilation correlated data of 10 breathing phases were acquired from a porcine ex-vivo functional lung phantom using CT and CBCT. 4D-vCTs were generated by (1) DIR of the mid-position 4D-CT to the mid-position 4D-CBCT (reconstructed with the MA-ROOSTER) using a diffeomorphic Morphons algorithm and (2) subsequent propagation of the obtained mid-position vCT to the individual 4D-CBCT phases. Proton therapy treatment planning was performed to evaluate dose calculation accuracy of the 4D-vCTs. A robust treatment plan delivering a nominal dose of 60Gy was generated on the average intensity image of the 4D-CT for an approximated internal target volume (ITV). Dose distributions were then recalculated on individual phases of the 4D-CT and the 4D-vCT based on the optimized plan. Dose accumulation was performed for 4D-vCT and 4D-CT using DIR of each phase to the mid position, which was chosen as reference. Dose based on the 4D-vCT was then evaluated against the dose calculated on 4D-CT both, phase-by-phase as well as accumulated, by comparing dose volume histogram (DVH) values (D_mean, D_2%, D_98%, D_95%) for the ITV, and by a 3D-gamma index analysis (global, 3%/3mm, 5Gy, 20Gy and 30Gy dose thresholds).

RESULTS

Good agreement was found between the 4D-CT and 4D-vCT-based ITV-DVH curves. The relative differences ((CT-vCT)/CT) between accumulated values of ITV D_mean, D_2%, D_95% and D_98% for the 4D-CT and 4D-vCT-based dose distributions were -0.2%, 0.0%, -0.1% and -0.1%, respectively. Phase specific values varied between -0.5% and 0.2%, -0.2% and 0.5%, -3.5% and 1.5%, and -5.7% and 2.3%. The relative difference of accumulated D_mean over the lungs was 2.3% and D_mean for the phases varied between -5.4% and 5.8%. The gamma pass-rates with 5Gy, 20Gy and 30Gy thresholds for the accumulated doses were 96.7%, 99.6% and 99.9%, respectively. Phase-by-phase comparison yielded pass-rates between 86% and 97%, 88% and 98%, and 94% and 100%.

CONCLUSIONS

Feasibility of the suggested 4D-vCT workflow using proton therapy specific imaging equipment was shown. Results indicate the potential of the method to be applied for daily 4D proton dose estimation.

The impact of 4DCT-ventilation imaging-guided proton therapy on stereotactic body radiotherapy for lung cancer

Functional lung avoidance during radiotherapy can help reduce pulmonary toxicity. This study assessed the potential impact of four-dimensional computed tomography (4DCT)-ventilation imaging-guided proton radiotherapy (PT) on stereotactic body radiotherapy (SBRT) by comparing it with three-dimensional conformal radiotherapy (3D-CRT) and volumetric modulated arc therapy (VMAT), which employ photon beams. Thirteen lung cancer patients who received SBRT with 3D-CRT were included in the study. 4DCT ventilation was calculated using the patients' 4DCT data, deformable image registration, and a density-change-based algorithm. Three functional treatment plans sparing the functional lung regions were developed for each patient using 3D-CRT, VMAT, and PT. The prescribed doses and dose constraints were based on the Radiation Therapy Oncology Group 0618 protocol. We evaluated the region of interest (ROI) and functional map-based dose-function metrics for 4DCT ventilation and the irradiated dose. Using 3D-CRT, VMAT, and PT, the percentages of the functional lung regions that received ≥ 5 Gy (fV5) were 26.0%, 21.9%, and 10.7%, respectively; the fV10 were 14.4%, 11.4%, and 9.0%, respectively; and fV20 were 6.5%, 6.4%, and 6.6%, respectively, and the functional mean lung doses (fMLD) were 5.6 Gy, 5.2 Gy, and 3.8 Gy, respectively. These results indicated that PT resulted in a significant reduction in fMLD, fV5, and fV10, but not fV20. The use of PT reduced the radiation to highly functional lung regions compared with those for 3D-CRT and VMAT while meeting all dose constraints.

DICOM-RT Ion interface to utilize MC simulations in routine clinical workflow for proton pencil beam radiotherapy

To adopt Monte Carlo (MC) simulations as an independent dose calculation method for proton pencil beam radiotherapy, an interface that converts the plan information in DICOM format into MC components such as geometries and beam source is a crucial element. For this purpose, a DICOM-RT Ion interface (https://github.com/topasmc/dicom-interface) has been developed and integrated into the TOPAS MC code to perform such conversions on-the-fly. DICOM-RT objects utilized in this interface include Ion Plan (RTIP), Ion Beams Treatment Record (RTIBTR), CT image, and Dose. Beamline geometries, gantry and patient coordinate systems, and fluence maps are determined from RTIP and/or RTIBTR. In this interface, DICOM information is processed and delivered to a MC engine in two steps. A MC model, which consists of beamline geometries and beam source, to represent a treatment machine is created by a DICOM parser of the interface. The complexities from different DICOM types, various beamline configurations and source models are handled in this step. Next, geometry information and beam source are transferred to TOPAS on-the-fly via the developed TOPAS extensions. This interface with two treatment machines was successfully deployed into our automated MC workflow which provides simulated dose and LET distributions in a patient or a water phantom automatically when a new plan is identified. The developed interface provides novel features such as handling multiple treatment systems based on different DICOM types, DICOM conversions on-the-fly, and flexible sampling methods that significantly reduce the burden of handling DICOM based plan or treatment record information for MC simulations.

Is an analytical dose engine sufficient for intensity modulated proton therapy in lung cancer?

OBJECTIVE

To identify a subgroup of lung cancer plans where the analytical dose calculation (ADC) algorithm may be clinically acceptable compared to Monte Carlo (MC) dose calculation in intensity modulated proton therapy (IMPT).

METHODS

Robust-optimised IMPT plans were generated for 20 patients to a dose of 70 Gy (relative biological effectiveness) in 35 fractions in Raystation. For each case, four plans were generated: three with ADC optimisation using the pencil beam (PB) algorithm followed by a final dose calculation with the following algorithms: PB (PB-PB), MC (PB-MC) and MC normalised to prescription dose (PB-MC scaled). A fourth plan was generated where MC optimisation and final dose calculation was performed (MC-MC). Dose comparison and γ analysis (PB-PB vs PB-MC) at two dose thresholds were performed: 20% (D20) and 99% (D99) with PB-PB plans as reference.

RESULTS

Overestimation of the dose to 99% and mean dose of the clinical target volume was observed in all PB-MC compared to PB-PB plans (median: 3.7 Gy(RBE) (5%) (range: 2.3 to 6.9 Gy(RBE)) and 1.8 Gy(RBE) (3%) (0.5 to 4.6 Gy(RBE))). PB-MC scaled plans resulted in significantly higher CTVD2 compared to PB-PB (median difference: -4 Gy(RBE) (-6%) (-5.3 to -2.4 Gy(RBE)), p ≤ .001). The overall median γ pass rates (3%-3 mm) at D20 and D99 were 93.2% (range:62.2-97.5%) and 71.3 (15.4-92.0%). On multivariate analysis, presence of mediastinal disease and absence of range shifters were significantly associated with high γ pass rates. Median D20 and D99 pass rates with these predictors were 96.0% (95.3-97.5%) and 85.4% (75.1-92.0%). MC-MC achieved similar target coverage and doses to OAR compared to PB-PB plans.

CONCLUSION

In the presence of mediastinal involvement and absence of range shifters Raystation ADC may be clinically acceptable in lung IMPT. Otherwise, MC algorithm would be recommended to ensure accuracy of treatment plans.

ADVANCES IN KNOWLEDGE

Although MC algorithm is more accurate compared to ADC in lung IMPT, ADC may be clinically acceptable where there is mediastinal involvement and absence of range shifters.

Validation of the RayStation Monte Carlo dose calculation algorithm using a realistic lung phantom

PURPOSE

Our purposes are to compare the accuracy of RaySearch's analytical pencil beam (APB) and Monte Carlo (MC) algorithms for clinical proton therapy and to present clinical validation data using a novel animal tissue lung phantom.

METHODS

We constructed a realistic lung phantom composed of a rack of lamb resting on a stack of rectangular natural cork slabs simulating lung tissue. The tumor was simulated using 70% lean ground lamb meat inserted in a spherical hole with diameter 40 ± 5 mm carved into the cork slabs. A single-field plan using an anterior beam and a two-field plan using two anterior-oblique beams were delivered to the phantom. Ion chamber array measurements were taken medial and distal to the tumor. Measured doses were compared with calculated RayStation APB and MC calculated doses.

RESULTS

Our lung phantom enabled measurements with the MatriXX PT at multiple depths in the phantom. Using the MC calculations, the 3%/3 mm gamma index pass rates, comparing measured with calculated doses, for the distal planes were 74.5% and 85.3% for the APB and 99.1% and 92% for the MC algorithms. The measured data revealed up to 46% and 30% underdosing within the distal regions of the target volume for the single and the two field plans when APB calculations are used. These discrepancies reduced to less than 18% and 7% respectively using the MC calculations.

CONCLUSIONS

RaySearch Laboratories' Monte Carlo dose calculation algorithm is superior to the pencil-beam algorithm for lung targets. Clinicians relying on the analytical pencil-beam algorithm should be aware of its pitfalls for this site and verify dose prior to delivery. We conclude that the RayStation MC algorithm is reliable and more accurate than the APB algorithm for lung targets and therefore should be used to plan proton therapy for patients with lung cancer.

Comparing 2 Monte Carlo Systems in Use for Proton Therapy Research

Purpose

Several Monte Carlo transport codes are available for medical physics users. To ensure confidence in the accuracy of the codes, they must be continually cross-validated. This study provides comparisons between MC² and Tool for Particle Simulation (TOPAS) simulations, that is, between medical physics applications for Monte Carlo N-Particle Transport Code (MCNPX) and Geant4.

Materials and Methods

Monte Carlo simulations were repeated with 2 wrapper codes: TOPAS (based on Geant4) and MC² (based on MCNPX). Simulations increased in geometrical complexity from a monoenergetic beam incident on a water phantom, to a monoenergetic beam incident on a water phantom with a bone or tissue slab at various depths, to a spread-out Bragg peak incident on a voxelized computed tomography (CT) geometry. The CT geometry cases consisted of head and neck tissue and lung tissue. The results of the simulations were compared with one another through dose or energy deposition profiles, r ₉₀ calculations, and γ-analyses.

Results

Both codes gave very similar results with monoenergetic beams incident on a water phantom. Systematic differences were observed between MC² and TOPAS simulations when using a lung or bone slab in a water phantom, particularly in the r ₉₀ values, where TOPAS consistently calculated r ₉₀ to be deeper by about 0.4%. When comparing the performance of the 2 codes in a CT geometry, the results were still very similar, exemplified by a 3-dimensional γ-analysis pass rate > 95% at the 2%-2-mm criterion for tissues from both head and neck and lung.

Conclusion

Differences between TOPAS and MC² were minor and were not considered clinically relevant.

Dynamic lung phantom commissioning for 4D dose assessment in proton therapy

Anthropomorphic phantoms mimicking organ and tumor motion of patients are essential for end-to-end testing of motion mitigation techniques in ion beam therapy. In this work a commissioning procedure developed with the in-house designed respiratory phantom ARDOS (Advanced Radiation DOSimetry system) is presented. The phantom was tested and benchmarked for 4D dose verification in proton therapy, which included: characterization of the tissue equivalent materials from computed tomography (CT) imaging, assessment of dose calculation accuracy in critical structures of the phantom, and testing various detectors for proton dosimetry in the ARDOS phantom. To prove the validity of the CT calibration curve, measured relative stopping powers (RSP) of the ARDOS materials were compared with values from CTs: original and overwritten with known material parameters. Override of rib- and soft-tissue phantom components improved RSP accuracy while inhomogeneous lung tissue, represented by the balsa wood, was better modelled by the CT Hounsfield units. Monte Carlo (MC) dose calculations were benchmarked against measurements with a reference Farmer chamber embedded in ARDOS material samples showing less than 3% relative dose difference. Differences between MC calculated dose distributions and those calculated by analytical algorithms for the ARDOS geometry were higher than 20% of the prescribed dose, depending on the position in the phantom. Pinpoint ionization chambers and thermoluminescence dosimeters showed differences of up to 5.5% compared to MC dose calculations for all lung setups in the static phantom. They were also able to detect dose distortions due to motion. EBT3 film dosimetry was shown to be suitable for 2D relative dose characterization, which could provide extended information on dose distributions in the penumbra area. The presented methodology and results can be used for drafting general recommendations for dynamic phantom commissioning, which is an essential step towards end-to-end evaluation of motion mitigation techniques in ion beam therapy.

Validation of the RayStation Monte Carlo dose calculation algorithm using realistic animal tissue phantoms

PURPOSE

The aim of this study is to validate the RayStation Monte Carlo (MC) dose algorithm using animal tissue neck phantoms and a water breast phantom.

METHODS

Three anthropomorphic phantoms were used in a clinical setting to test the RayStation MC dose algorithm. We used two real animal necks that were cut to a workable shape while frozen and then thawed before being CT scanned. Secondly, we made a patient breast phantom using a breast prosthesis filled with water and placed on a flat surface. Dose distributions in the animal and breast phantoms were measured using the MatriXX PT device.

RESULTS

The measured doses to the neck and breast phantoms compared exceptionally well with doses calculated by the analytical pencil beam (APB) and MC algorithms. The comparisons between APB and MC dose calculations and MatriXX PT measurements yielded an average depth difference for best gamma agreement of <1 mm for the neck phantoms. For the breast phantom better average gamma pass rates between measured and calculated dose distributions were observed for the MC than for the APB algorithms.

CONCLUSIONS

The MC dose calculations are more accurate than the APB calculations for the static phantoms conditions we evaluated, especially in areas where significant inhomogeneous interfaces are traversed by the beam.

Treatment planning for proton therapy: what is needed in the next 10 years?

Treatment planning is the process where the prescription of the radiation oncologist is translated into a deliverable treatment. With the complexity of contemporary radiotherapy, treatment planning cannot be performed without a computerized treatment planning system. Proton therapy (PT) enables highly conformal treatment plans with a minimum of dose to tissues outside the target volume, but to obtain the most optimal plan for the treatment, there are a multitude of parameters that need to be addressed. In this review areas of ongoing improvements and research in the field of PT treatment planning are identified and discussed. The main focus is on issues of immediate clinical and practical relevance to the PT community highlighting the needs for the near future but also in a longer perspective. We anticipate that the manual tasks performed by treatment planners in the future will involve a high degree of computational thinking, as many issues can be solved much better by e.g. scripting. More accurate and faster dose calculation algorithms are needed, automation for contouring and planning is required and practical tools to handle the variable biological efficiency in PT is urgently demanded just to mention a few of the expected improvements over the coming 10 years.

FLUKA particle therapy tool for Monte Carlo independent calculation of scanned proton and carbon ion beam therapy

While Monte Carlo (MC) codes are considered as the gold standard for dosimetric calculations, the availability of user friendly MC codes suited for particle therapy is limited. Based on the FLUKA MC code and its graphical user interface (GUI) Flair, we developed an easy-to-use tool which enables simple and reliable simulations for particle therapy. In this paper we provide an overview of functionalities of the tool and with the presented clinical, proton and carbon ion therapy examples we demonstrate its reliability and the usability in the clinical environment and show its flexibility for research purposes. The first, easy-to-use FLUKA MC platform for particle therapy with GUI functionalities allows a user with a minimal effort and reduced knowledge about MC details to apply MC at their facility and is expected to enhance the popularity of the MC for both research and clinical quality assurance and commissioning purposes.

Evaluation of the ray-casting analytical algorithm for pencil beam scanning proton therapy

For pencil beam scanned (PBS) proton therapy, analytical dose calculation engines are still typically used for the optimisation process, and often for the final evaluation of the plan. Recently however, the suitability of analytical calculations for planning PBS treatments has been questioned. Conceptually, the two main approaches for these analytical dose calculations are the ray-casting (RC) and the pencil-beam (PB) method. In this study, we compare dose distributions and dosimetric indices, calculated on both the clinical dose calculation grid and as a function of dose grid resolution, to Monte Carlo (MC) calculations. The analysis is done using a comprehensive set of clinical plans which represent a wide choice of treatment sites. When analysing dose difference histograms for relative treatment plans, pencil beam calculations with double grid resolution perform best, with on average 97.7%/91.9% (RC), 97.9%/92.7% (RC, double grid resolution), 97.6%/91.0% (PB) and 98.6%/94.0% (PB, double grid resolution) of voxels agreeing within  ±5%/±  3% between the analytical and the MC calculations. Even though these point-to-point dose comparison shows differences between analytical and MC calculations, for all algorithms, clinically relevant dosimetric indices agree within  ±4% for the PTV and within  ±5% for critical organs. While the clinical agreement depends on the treatment site, there is no substantial difference of indices between the different algorithms. The pencil-beam approach however comes at a higher computational cost than the ray-casting calculation. In conclusion, we would recommend using the ray-casting algorithm for fast dose optimization and subsequently combine it with one MC calculation to scale the absolute dose and assure the quality of the treatment plan.

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

Patient specific quality assurance is crucial to guarantee safety in proton pencil beam scanning. In current clinical practice, this requires extensive, time consuming measurements. Additionally, these measurements do not consider the influence of density heterogeneities in the patient and are insensitive to delivery errors. In this work, we investigate the use of log file based Monte Carlo calculations for dose reconstructions in the patient CT, which takes the combined influence of calculational and delivery errors into account. For one example field, 87%/90% of the voxels agree within  ±3% when taking either calculational or delivery uncertainties into account (analytical versus Monte Carlo calculation/Monte Carlo from planned versus Monte Carlo from log file). 78% agree when considering both uncertainties simultaneously (nominal field versus Monte Carlo from log files). We then show the application of the log file based Monte Carlo calculations as a patient specific quality assurance tool for a set of five patients (16 fields) treated for different indications. For all fields, absolute dose scaling factors based on the log file Monte Carlo agree within  ±3% to the measurement based absolute dose scaling. Relative comparison shows that more than 90% of the voxels agree within  ±  5% between the analytical calculated plan and the Monte Carlo based on log files. The log file based Monte Carlo approach is an end-to-end test incorporating all requirements of patient specific quality assurance. It has the potential to reduce the workload and therefore to increase the patient throughput, while simultaneously enabling more accurate dose verification directly in the patient geometry.

A comprehensive dosimetric study of Monte Carlo and pencil-beam algorithms on intensity-modulated proton therapy for breast cancer

PB algorithms are commonly used for proton therapy. Previously reported limitations of the PB algorithm for proton therapy are mainly focused on high-density gradients and small-field dosimetry, the effect of PB algorithms on intensity-modulated proton therapy (IMPT) for breast cancer has yet to be illuminated. In this study, we examined 20 patients with breast cancer and systematically investigated the dosimetric impact of MC and PB algorithms on IMPT. Four plans were generated for each patient: (a) a PB plan that optimized and computed the final dose using a PB algorithm; (b) a MC-recomputed plan that recomputed the final dose of the PB plan using a MC algorithm; (c) a MC-renormalized plan that renormalized the MC-recomputed plan to restore the target coverage; and (d) a MC-optimized plan that optimized and computed the final dose using a MC algorithm. The DVH on CTVs and on organ-at-risks (OARs) from each plan were studied. The Mann-Whitney U-test was used for testing the differences between any two types of plans. We found that PB algorithms significantly overestimated the target dose in breast IMPT plans. The median value of the CTV D99% , D95% , and Dmean dropped by 3.7%, 3.4%, and 2.1%, respectively, of the prescription dose in the MC-recomputed plans compared with the PB plans. The magnitude of the target dose overestimation by the PB algorithm was higher for the breast CTV than for the chest wall CTV. In the MC-renormalized plans, the target dose coverage was comparable with the original PB plans, but renormalization led to a significant increase in target hot spots as well as skin dose. The MC-optimized plans led to sufficient target dose coverage, acceptable target hot spots, and good sparing of skin and other OARs. Utilizing the MC algorithm for both plan optimization and final dose computation in breast IMPT treatment planning is therefore desirable.

Contour-based lung dose prediction for breast proton therapy

PURPOSE

This study evaluates the feasibility of lung dose prediction based on target contour and patient anatomy for breast patients treated with proton therapy.

METHODS

Fifty-two randomly selected patients were included in the cohort, who were treated to 50.4-66.4 Gy(RBE) to the left (36), right (15), or bilateral (1) breast with uniform scanning (32) or pencil beam scanning (20). Anterior-oblique beams were used for each patient. The prescription doses were all scaled to 50.4 Gy(RBE) for the current analysis. Isotropic expansions of the planning target volume of various margins m were retrospectively generated and compared with isodose volumes in the ipsilateral lung. The fractional volume V of each expansion contour within the ipsilateral lung was compared with dose-volume data of clinical plans to establish the relationship between the margin m and dose D for the ipsilateral lung such that VD  = V(m). This relationship enables prediction of dose-volume VD from V(m), which could be derived from contours before any plan is generated, providing a goal of plan quality. Lung V20 Gy( RBE ) and V5 Gy( RBE ) were considered for this pilot study, while the results could be generalized to other dose levels and/or other organs.

RESULTS

The actual V20 Gy( RBE ) ranged from 6% to 23%. No statistically significant difference in V20 Gy( RBE ) was found between breast irradiation and chest wall irradiation (P = 0.8) or between left-side and right-side treatment (P = 0.9). It was found that V(1.1 cm) predicted V20 Gy( RBE ) to within 5% root-mean-square deviation (RMSD) and V(2.2 cm) predicted V5 Gy( RBE ) to within 6% RMSD.

CONCLUSION

A contour-based model was established to predict dose to ipsilateral lung in breast treatment. Clinically relevant accuracy was demonstrated. This model facilitates dose prediction before treatment planning. It could serve as a guide toward realistic clinical goals in the planning stage.

A Monte-Carlo-based and GPU-accelerated 4D-dose calculator for a pencil beam scanning proton therapy system

PURPOSE

The presence of respiratory motion during radiation treatment leads to degradation of the expected dose distribution, both for target coverage and healthy tissue sparing, particularly for techniques like pencil beam scanning proton therapy which have dynamic delivery systems. While tools exist to estimate this degraded four-dimensional (4D) dose, they typically have one or more deficiencies such as not including the particular effects from a dynamic delivery, using analytical dose calculations, and/or using nonphysical dose-accumulation methods. This work presents a clinically useful 4D-dose calculator that addresses each of these shortcomings.

METHODS

To quickly compute the 4D dose, the three main tasks of the calculator were run on graphics processing units (GPUs). These tasks were (a) simulating the delivery of the plan using measured delivery parameters to distribute the plan amongst 4DCT phases characterizing the patient breathing, (b) using an in-house Monte Carlo simulation (MC) dose calculator to determine the dose delivered to each breathing phase, and (c) accumulating the doses from the various breathing phases onto a single phase for evaluation. The accumulation was performed by individually transferring the energy and mass of dose-grid subvoxels, a technique that models the transfer of dose in a more physically realistic manner. The calculator was run on three test cases, with lung, esophagus, and liver targets, respectively, to assess the various uncertainties in the beam delivery simulation as well as to characterize the dose-accumulation technique.

RESULTS

Four-dimensional doses were successfully computed for the three test cases with computation times ranging from 4-6 min on a server with eight NVIDIA Titan X graphics cards; the most time-consuming component was the MC dose engine. The subvoxel-based dose-accumulation technique produced stable 4D-dose distributions at subvoxel scales of 0.5-1.0 mm without impairing the total computation time. The uncertainties in the beam delivery simulation led to moderate variations of the dose-volume histograms for these cases; the variations were reduced by implementing repainting or phase-gating motion mitigation techniques in the calculator.

CONCLUSIONS

A MC-based and GPU-accelerated 4D-dose calculator was developed to estimate the effects of respiratory motion on pencil beam scanning proton therapy treatments. After future validation, the calculator could be used to assess treatment plans and its quick runtime would make it easily usable in a future 4D-robust optimization system.

Validation and application of a fast Monte Carlo algorithm for assessing the clinical impact of approximations in analytical dose calculations for pencil beam scanning proton therapy

PURPOSE

Monte Carlo (MC) dose calculation is generally superior to analytical dose calculation (ADC) used in commercial TPS to model the dose distribution especially for heterogeneous sites, such as lung and head/neck patients. The purpose of this study was to provide a validated, fast, and open-source MC code, MCsquare, to assess the impact of approximations in ADC on clinical pencil beam scanning (PBS) plans covering various sites.

METHODS

First, MCsquare was validated using tissue-mimicking IROC lung phantom measurements as well as benchmarked with the general purpose Monte Carlo TOPAS for patient dose calculation. Then a comparative analysis between MCsquare and ADC was performed for a total of 50 patients with 10 patients per site (including liver, pelvis, brain, head-and-neck, and lung). Differences among TOPAS, MCsquare, and ADC were evaluated using four dosimetric indices based on the dose-volume histogram (target Dmean, D95, homogeneity index, V95), a 3D gamma index analysis (using 3%/3 mm criteria), and estimations of tumor control probability (TCP).

RESULTS

Comparison between MCsquare and TOPAS showed less than 1.8% difference for all of the dosimetric indices/TCP values and resulted in a 3D gamma index passing rate for voxels within the target in excess of 99%. When comparing ADC and MCsquare, the variances of all the indices were found to increase as the degree of tissue heterogeneity increased. In the case of lung, the D95s for ADC were found to differ by as much as 6.5% from the corresponding MCsquare statistic. The median gamma index passing rate for voxels within the target volume decreased from 99.3% for liver to 75.8% for lung. Resulting TCP differences can be large for lung (≤10.5%) and head-and-neck (≤6.2%), while smaller for brain, pelvis and liver (≤1.5%).

CONCLUSIONS

Given the differences found in the analysis, accurate dose calculation algorithms such as Monte Carlo simulations are needed for proton therapy, especially for disease sites with high heterogeneity, such as head-and-neck and lung. The establishment of MCsquare can facilitate patient plan reviews at any institution and can potentially provide unbiased comparison in clinical trials given its accuracy, speed and open-source availability.

Four-dimensional Plan Optimization for the Treatment of Lung Tumors Using Pencil-beam Scanning Proton Radiotherapy

Purpose 

This study aimed to evaluate the effectiveness of four-dimensional (4D) robust optimization for proton pencil-beam scanning (PBS) treatment of lung tumors.

Patients and methods 

In seven patients with lung cancer, proton beam therapy was planned using 4D robust optimization over 4D computed tomography (CT) data sets. The gross target volume (GTV) was contoured based on individual breathing phases, and a 5-mm expansion was used to generate the clinical target volume (CTV) for each phase. The 4D optimization was conducted directly on the 4D CT data set. The robust optimization settings included a CT Hounsfield unit (HU) uncertainty of 4% and a setup uncertainty of 5 mm to obtain the CTV. Additional target dose objectives such as those for the internal target volume (ITV) as well as the organ-at-risk (OAR) dose requirements were placed on the average CT. For comparison, three-dimensional (3D) robust optimization was also performed on the average CT. An additional verification 4D CT was performed to verify plan robustness against inter-fractional variations.

Results 

Target coverages were generally higher for 4D optimized plans. The difference was most pronounced for ITV V70Gy when evaluating individual breathing phases. The 4D optimized plans were shown to be able to maintain the ITV coverage at full prescription, while 3D optimized plans could not. More importantly, this difference in ITV V70Gy between the 4D and 3D optimized plans was also consistently observed when evaluating the verification 4D CT, indicating that the 4D optimized plans were more robust against inter-fractional variations. Less difference was seen between the 4D and 3D optimized plans in the lungs criteria: V5Gy and V20Gy.

Conclusion 

The proton PBS treatment plans optimized directly on the 4D CT were shown to be more robust when compared to those optimized on a regular 3D CT. Robust 4D optimization can improve the target coverage for the proton PBS lung treatments.

Validation and clinical implementation of an accurate Monte Carlo code for pencil beam scanning proton therapy

Monte Carlo (MC)‐based dose calculations are generally superior to analytical dose calculations (ADC) in modeling the dose distribution for proton pencil beam scanning (PBS) treatments. The purpose of this paper is to present a methodology for commissioning and validating an accurate MC code for PBS utilizing a parameterized source model, including an implementation of a range shifter, that can independently check the ADC in commercial treatment planning system (TPS) and fast Monte Carlo dose calculation in opensource platform (MCsquare). The source model parameters (including beam size, angular divergence and energy spread) and protons per MU were extracted and tuned at the nozzle exit by comparing Tool for Particle Simulation (TOPAS) simulations with a series of commissioning measurements using scintillation screen/CCD camera detector and ionization chambers. The range shifter was simulated as an independent object with geometric and material information. The MC calculation platform was validated through comprehensive measurements of single spots, field size factors (FSF) and three‐dimensional dose distributions of spread‐out Bragg peaks (SOBPs), both without and with the range shifter. Differences in field size factors and absolute output at various depths of SOBPs between measurement and simulation were within 2.2%, with and without a range shifter, indicating an accurate source model. TOPAS was also validated against anthropomorphic lung phantom measurements. Comparison of dose distributions and DVHs for representative liver and lung cases between independent MC and analytical dose calculations from a commercial TPS further highlights the limitations of the ADC in situations of highly heterogeneous geometries. The fast MC platform has been implemented within our clinical practice to provide additional independent dose validation/QA of the commercial ADC for patient plans. Using the independent MC, we can more efficiently commission ADC by reducing the amount of measured data required for low dose “halo” modeling, especially when a range shifter is employed.

4D robust optimization including uncertainties in time structures can reduce the interplay effect in proton pencil beam scanning radiation therapy

PURPOSE

Interplay effects in proton radiotherapy can create large distortions in the dose distribution and severely degrade the plan quality. Standard methods to mitigate these effects include abdominal compression, gating, and rescanning. We propose a new method to include the time structures of the delivery and organ motion in the framework of four-dimensional (4D) robust optimization to generate plans that are robust against interplay effects.

METHODS

The method considers multiple scenarios reflecting the uncertainties in the delivery and in the organ motion. In each scenario, the pencil beam scanning spots are distributed to different phases of the breathing cycle according to each individual spot time stamp, and a partial beam dose is calculated for each phase. The partial beam doses are accumulated on a reference phase through deformable image registrations. Minimax optimization is performed to take all scenarios into account simultaneously. For simplicity, the uncertainties in this proof of concept study are limited to variations in the breathing pattern. The method is evaluated for three different nonsmall cell lung cancer patients and compared to plans using conventional 4D robust optimization both with and without rescanning. We assess the ability of the method to mitigate distortions from the interplay effect over multiple evaluation scenarios using 4D dose calculations. This interplay evaluation is performed in an experimentally validated framework, which is independent of the optimization in the plan generation step.

RESULTS

For the three studied patients, 4D optimization including time structures is efficient, especially for large tumor motions, where rescanning of conventional 4D robustly optimized plans is not sufficient to mitigate the interplay effect. The most efficient approach of the new method is achieved when it is combined with rescanning. For the patient with the largest motion, the mean V95% is 99.2% and mean V107% is 3.65% for the best rescanned 4D plan optimized with time structure. This can be compared to conventional 4D optimized plans with mean V95% of 92.7% and mean V107% of 13.1%.

CONCLUSIONS

The current study shows the potential of reducing interplay effects in proton pencil beam scanning radiotherapy by incorporating organ motion and delivery characteristics in a 4D robust optimization.

Clinical Feasibility of Single-Source Dual-spiral 4D Dual-Energy CT for Proton Treatment Planning Within the Thoracic Region

PURPOSE

Single-source dual-spiral dual-energy computed tomography (DECT) provides additional patient information but is prone to motion between the 2 consecutively acquired computed tomography (CT) scans. Here, the clinical applicability of dual-spiral time-resolved DECT (4D-DECT) for proton treatment planning within the thoracic region was evaluated.

METHODS AND MATERIALS

Dual-spiral 4D-DECT scans of 3 patients with lung cancer were acquired. For time-averaged datasets and 4 breathing phases, the geometric conformity of 80 kVp and 140 kVp 4D-DECT scans before image post-processing was assessed by normalized cross correlation (NCC). Additionally, the conformity of the corresponding DECT-derived 58 keV and 79 keV pseudo-monoenergetic CT datasets after image post-processing, including deformable image registration (DIR), was determined. To analyze the reliability of proton dose calculation, clinical (Plan_Clin) and artificial worst-case (Plan_WorstCase, targeting the diaphragm) treatment plans were calculated on 140 kVp and 79 keV datasets and compared with gamma analyses (0.1% dose-difference and 1 mm distance-to-agreement criterion). The applicability of a patient-specific DECT-based prediction of stopping-power ratio (SPR) was investigated and proton range shifts compared with the clinical heuristic CT-number-to-SPR conversion were assessed. Finally, the delineation variability of an experienced radiation oncologist was quantified.

RESULTS

Dual-spiral 4D-DECT scans without DIR showed a high geometric conformity, with an average NCC ± standard deviation of 98.7% ± 1.0% when including all patient voxels or 88.2% ± 7.8% when considering only lung. DIR improved the conformity, leading to an average NCC of 99.9% ± 0.1% and 99.6% ± 0.5%, respectively. Plan_Clin dose distributions on 140 kVp and 79 keV datasets were similar, with an average gamma passing rate of 99.9% (99.2%-100%). The worst-case evaluation still revealed high passing rates (99.3% on average, 92.4% as minimum). Clinically relevant mean range shifts of 2.2% ± 1.2% were determined between patient-specific DECT-based SPR prediction and clinical heuristic CT-number-to-SPR conversion. The intra-observer delineation variability was slightly reduced using additional DECT-derived datasets.

CONCLUSIONS

The 79 keV pseudo-monoenergetic CT datasets can be consistently obtained from dual-spiral 4D-DECT and are applicable for dose calculation. Patient-specific DECT-based SPR prediction performed well and potentially reduces range uncertainty in proton therapy of patients with lung cancer.

Clinical examination of proton pencil beam scanning on a moving anthropomorphic lung phantom

The objective of this study was to examine the use of proton pencil beam scanning for the treatment of moving lung tumors. A single-field uniform dose proton pencil beam scanning (PBS) plan was generated for the standard thorax phantom designed by the Imaging and Radiation Oncology Core (IROC) Houston QA Center. Robust optimization, including range and setup uncertainties as well as volumetric repainting, was used for the plan. Patient-specific quality assurance (QA) measurements were performed using both a water tank and a custom heterogeneous QA phantom. A custom moving phantom was used to find the optimal number of volumetric repainting. Both analytical and Monte Carlo (MC) algorithms were used for dose calculation and their accuracies were compared with actual measurements. A single ionization chamber, a 2-dimensional ionization chamber array, thermoluminescent dosimeters (TLDs), and films were used for dose measurements. The optimal number of volumetric repainting was found to be 4 times in our system. The mean dose overestimations on a moving target by analytical and MC algorithms based on a time-averaged computed tomography (CT) image of the phantom were found to be 4.8% and 2.4%, respectively. The mean gamma indexes for analytical and MC algorithms were 91% and 96%, respectively. The MC dose algorithm calculation was found to have a better agreement with measurements compared with the analytical algorithm. When treating moving lung tumors using proton PBS, the techniques of robust optimization, volumetric repainting, and MC dose calculation were found effective. Extra care needs to be taken when an analytical dose calculation algorithm is used.

Effectiveness of different rescanning techniques for scanned proton radiotherapy in lung cancer patients

Non-small cell lung cancer (NSCLC) is a tumour type thought to be well-suited for proton radiotherapy. However, the lung region poses many problems related to organ motion and can for actively scanned beams induce severe interplay effects. In this study we investigate four mitigating rescanning techniques: (1) volumetric rescanning, (2) layered rescanning, (3) breath-sampled (BS) layered rescanning, and (4) continuous breath-sampled (CBS) layered rescanning. The breath-sampled methods will spread the layer rescans over a full breathing cycle, resulting in an improved averaging effect at the expense of longer treatment times. In CBS, we aim at further improving the averaging by delivering as many rescans as possible within one breathing cycle. The interplay effect was evaluated for 4D robustly optimized treatment plans (with and without rescanning) for seven NSCLC patients in the treatment planning system RayStation. The optimization and final dose calculation used a Monte Carlo dose engine to account for the density heterogeneities in the lung region. A realistic treatment delivery time structure given from the IBA ScanAlgo simulation tool served as basis for the interplay evaluation. Both slow (2.0 s) and fast (0.1 s) energy switching times were simulated. For all seven studied patients, rescanning improves the dose conformity to the target. The general trend is that the breath-sampled techniques are superior to layered and volumetric rescanning with respect to both target coverage and variability in dose to OARs. The spacing between rescans in our breath-sampled techniques is set at planning, based on the average breathing cycle length obtained in conjunction with CT acquisition. For moderately varied breathing cycle lengths between planning and delivery (up to 15%), the breath-sampled techniques still mitigate the interplay effect well. This shows the potential for smooth implementation at the clinic without additional motion monitoring equipment.

Advanced Proton Beam Dosimetry Part I: review and performance evaluation of dose calculation algorithms

The accuracy of dose calculation is vital to the quality of care for patients undergoing proton beam therapy (PBT). Currently, the dose calculation algorithms available in commercial treatment planning systems (TPS) in PBT are classified into two classes: pencil beam (PB) and Monte-Carlo (MC) algorithms. PB algorithms are still regarded as the standard of practice in PBT, but they are analytical approximations whereas MC algorithms use random sampling of interaction cross-sections that represent the underlying physics to simulate individual particles trajectories. This article provides a brief review of PB and MC dose calculation algorithms employed in commercial treatment planning systems and their performance comparison in phantoms through simulations and measurements. Deficiencies of PB algorithms are first highlighted by a simplified simulation demonstrating the transport of a single sub-spot of proton beam that is incident at an oblique angle in a water phantom. Next, more typical cases of clinical beams in water phantom are presented and compared to measurements. The inability of PB to correctly predict the range and subsequently distal fall-off is emphasized. Through the presented examples, it is shown how dose errors as high as 30% can result with use of a PB algorithm. These dose errors can be minimized to clinically acceptable levels of less than 5%, if MC algorithm is employed in TPS. As a final illustration, comparison between PB and MC algorithm is made for a clinical beam that is use to deliver uniform dose to a target in a lung section of an anthropomorphic phantom. It is shown that MC algorithm is able to correctly predict the dose at all depths and matched with measurements. For PB algorithm, there is an increasing mismatch with the measured doses with increasing tissue heterogeneity. The findings of this article provide a foundation for the second article of this series to compare MC vs. PB based lung cancer treatment planning.

Considerations when treating lung cancer with passive scatter or active scanning proton therapy

Lung cancer, due to its poor clinical outcomes and significant toxicity associated with standard photon-based radiation, is a disease site that has the potential to greatly benefit from accurate treatment with proton radiation therapy. The potential of proton therapy is the ability to increase the radiation dose to the tumor while simultaneously decreasing the radiation dose to surrounding healthy tissues. For lung cancer treatment, this could mean significant sparing of the uninvolved healthy lung, which is difficult to achieve with external photon beam therapy, or decreasing the heart dose. In treating lung cancer with proton therapy, some additional considerations need to be made compared to treating patients with external photon beam radiation therapy. These include accounting for the finite range of protons in the patient, understanding temporal effects, potential dose discrepancies and choosing an appropriate treatment planning system for the task. One final consideration is differences between the different available proton therapy delivery systems-passive scattered proton therapy (PSPT) and active scanning proton therapy.

Advanced proton beam dosimetry part II: Monte Carlo vs. pencil beam-based planning for lung cancer

BACKGROUND

Proton pencil beam (PB) dose calculation algorithms have limited accuracy within heterogeneous tissues of lung cancer patients, which may be addressed by modern commercial Monte Carlo (MC) algorithms. We investigated clinical pencil beam scanning (PBS) dose differences between PB and MC-based treatment planning for lung cancer patients.

METHODS

With IRB approval, a comparative dosimetric analysis between RayStation MC and PB dose engines was performed on ten patient plans. PBS gantry plans were generated using single-field optimization technique to maintain target coverage under range and setup uncertainties. Dose differences between PB-optimized (PBopt), MC-recalculated (MCrecalc), and MC-optimized (MCopt) plans were recorded for the following region-of-interest metrics: clinical target volume (CTV) V95, CTV homogeneity index (HI), total lung V20, total lung VRX (relative lung volume receiving prescribed dose or higher), and global maximum dose. The impact of PB-based and MC-based planning on robustness to systematic perturbation of range (±3% density) and setup (±3 mm isotropic) was assessed. Pairwise differences in dose parameters were evaluated through non-parametric Friedman and Wilcoxon sign-rank testing.

RESULTS

In this ten-patient sample, CTV V95 decreased significantly from 99-100% for PBopt to 77-94% for MCrecalc and recovered to 99-100% for MCopt (P<10-5). The median CTV HI (D95/D5) decreased from 0.98 for PBopt to 0.91 for MCrecalc and increased to 0.95 for MCopt (P<10-3). CTV D95 robustness to range and setup errors improved under MCopt (ΔD95 =-1%) compared to MCrecalc (ΔD95 =-6%, P=0.006). No changes in lung dosimetry were observed for large volumes receiving low to intermediate doses (e.g., V20), while differences between PB-based and MC-based planning were noted for small volumes receiving high doses (e.g., VRX). Global maximum patient dose increased from 106% for PBopt to 109% for MCrecalc and 112% for MCopt (P<10-3).

CONCLUSIONS

MC dosimetry revealed a reduction in target dose coverage under PB-based planning that was regained under MC-based planning along with improved plan robustness. MC-based optimization and dose calculation should be integrated into clinical planning workflows of lung cancer patients receiving actively scanned proton therapy.

Feasibility study of range-based registration using daily cone beam CT for intensity-modulated proton therapy

PURPOSE

Proton dose coverage is sensitive to proton beam range. The current practice of CT number-based registration for patient positioning focuses on matching the target and is not sufficient for proton therapy because the proton range depends on the medium traversed by the beam. Patient body deformations and anatomical changes result in range deviation in the target. We propose proton range-based registration to minimize the range deviation.

METHODS

The range was calculated from cone beam-computed tomography (CBCT) of the patient on couch, and the range deviation was the difference of the calculated range from that on the initial (day 1) CBCT. In the investigated prostate cases in which the main cause of range deviation was the rotation of femur bones, and in the investigated abdomen cases in which the main cause of range deviation was body growth and anatomic change, our range-based registration was used to obtain the optimal beam angle by minimizing the range deviation. The new angle was limited to be ±5° from that planned to prevent potentially increased dose to the organs at risk. To demonstrate the benefit of range-based registration, we investigated the range at the voxels on the surface of the target volume. The calculation error of range deviation due to CBCT scatter was investigated by using solid water phantoms with different thicknesses. Range-based registration using both CBCTs and CTs was performed in cases of two patients with pelvic rhabdomyosarcoma and one patient with upper abdominal tumor. The range was represented by the water-equivalent thickness to shorten the computation for online application purposes.

RESULTS

In the phantom study, the calculation error of range deviation due to CBCT scatter was within 2 mm for a 1-cm thickness change (the mean range deviation was 0.8 mm). In the CT study of the prostate cases, the range deviation (mean ± root-mean-square deviation) on the contour in each slice was efficiently reduced from 3.6 ± 2.8 mm to 2.1 ± 1.4 mm, with most slices being within 3 mm; in the CT study of the abdomen cases, the range deviation of the whole set was reduced from 4.4 ± 1.9 mm to 3.5 ± 2.1 mm. Both the mean and root-mean-square deviation of the range deviation on each treatment day were decreased. The dose coverage on the target was improved and the dose on the OARs was only slightly changed.

CONCLUSION

Range-based registration can efficiently mitigate range deviation due to patient positioning and anatomical changes. It can shorten patient positioning time and reduce the patient's dose from CBCT.

Technical Note: Defining cyclotron-based clinical scanning proton machines in a FLUKA Monte Carlo system

PURPOSE

Cyclotron-based pencil beam scanning (PBS) proton machines represent nowadays the majority and most affordable choice for proton therapy facilities, however, their representation in Monte Carlo (MC) codes is more complex than passively scattered proton system- or synchrotron-based PBS machines. This is because degraders are used to decrease the energy from the cyclotron maximum energy to the desired energy, resulting in a unique spot size, divergence, and energy spread depending on the amount of degradation. This manuscript outlines a generalized methodology to characterize a cyclotron-based PBS machine in a general-purpose MC code. The code can then be used to generate clinically relevant plans starting from commercial TPS plans.

METHODS

The described beam is produced at the Provision Proton Therapy Center (Knoxville, TN, USA) using a cyclotron-based IBA Proteus Plus equipment. We characterized the Provision beam in the MC FLUKA using the experimental commissioning data. The code was then validated using experimental data in water phantoms for single pencil beams and larger irregular fields. Comparisons with RayStation TPS plans are also presented.

RESULTS

Comparisons of experimental, simulated, and planned dose depositions in water plans show that same doses are calculated by both programs inside the target areas, while penumbrae differences are found at the field edges. These differences are lower for the MC, with a γ(3%-3 mm) index never below 95%.

CONCLUSIONS

Extensive explanations on how MC codes can be adapted to simulate cyclotron-based scanning proton machines are given with the aim of using the MC as a TPS verification tool to check and improve clinical plans. For all the tested cases, we showed that dose differences with experimental data are lower for the MC than TPS, implying that the created FLUKA beam model is better able to describe the experimental beam.

Feasibility of proton pencil beam scanning treatment of free-breathing lung cancer patients

BACKGROUND

The interplay effect might degrade the dose of pencil beam scanning proton therapy to a degree that free-breathing treatment might be impossible without further motion mitigation techniques, which complicate and prolong the treatment. We assessed whether treatment of free-breathing patients without motion mitigation is feasible.

MATERIAL AND METHODS

For 40 lung cancer patients, 4DCT datasets and individual breathing patterns were used to simulate 4D dynamic dose distributions of 3D treatment plans over 33 fractions delivered with an IBA universal nozzle. Evaluation was done by assessing under- and overdosage in the target structure using the parameters V90, V95, V98, D98, D2, V107 and V110. The impact of using beam-specific target volumes and the impact of changes in motion and patient anatomy in control 4DCTs were assessed.

RESULTS

Almost half of the patients had tumour motion amplitudes of less than 5 mm. Under- and overdosage was significantly smaller for patients with tumour motion below 5 mm compared to patients with larger motion (2% vs. 13% average absolute reduction of V95, 2% vs. 8% average increase in V107, p < .01). Simulating a 33-fraction treatment, the dose degradation was reduced but persisted for patients with tumour motion above 5 mm (average ΔV95 of <1% vs. 3%, p < .01). Beam-specific target volumes reduced the dose degradation in a fractionated treatment, but were more relevant for large motion. Repeated 4DCT revealed that changes in tumour motion during treatment might result in unexpected large dose degradations.

CONCLUSION

Tumour motion amplitude is an indicator of dose degradation caused by the interplay effect. Fractionation reduces the dose degradation allowing the unmitigated treatment of patients with small tumour motions of less than 5 mm. The beam-specific target approach improves the dose coverage. The tumour motion and position needs to be assessed during treatment for all patients, to quickly react to possible changes, which might require treatment adaptation.

Density overwrites of internal tumor volumes in intensity modulated proton therapy plans for mobile lung tumors

The purpose of this study was to investigate internal tumor volume density overwrite strategies to minimize intensity modulated proton therapy (IMPT) plan degradation of mobile lung tumors. Four planning paradigms were compared for nine lung cancer patients. Internal gross tumor volume (IGTV) and internal clinical target volume (ICTV) structures were defined encompassing their respective volumes in every 4DCT phase. The paradigms use different planning CT (pCT) created from the average intensity projection (AIP) of the 4DCT, overwriting the density within the IGTV to account for movement. The density overwrites were: (a) constant filling with 100 HU (C100) or (b) 50 HU (C50), (c) maximum intensity projection (MIP) across phases, and (d) water equivalent path length (WEPL) consideration from beam's-eye-view. Plans were created optimizing dose-influence matrices calculated with fast GPU Monte Carlo (MC) simulations in each pCT. Plans were evaluated with MC on the 4DCTs using a model of the beam delivery time structure. Dose accumulation was performed using deformable image registration. Interplay effect was addressed applying 10 times rescanning. Significantly less DVH metrics degradation occurred when using MIP and WEPL approaches. Target coverage ([Formula: see text] Gy(RBE)) was fulfilled in most cases with MIP and WEPL ([Formula: see text] Gy (RBE)), keeping dose heterogeneity low ([Formula: see text] Gy(RBE)). The mean lung dose was kept lowest by the WEPL strategy, as well as the maximum dose to organs at risk (OARs). The impact on dose levels in the heart, spinal cord and esophagus were patient specific. Overall, the WEPL strategy gives the best performance and should be preferred when using a 3D static geometry for lung cancer IMPT treatment planning. Newly available fast MC methods make it possible to handle long simulations based on 4D data sets to perform studies with high accuracy and efficiency, even prior to individual treatment planning.

Performance of a hybrid Monte Carlo-Pencil Beam dose algorithm for proton therapy inverse planning

PURPOSE

Analytical algorithms have a limited accuracy when modeling very heterogeneous tumor sites. This work addresses the performance of a hybrid dose optimizer that combines both Monte Carlo (MC) and pencil beam (PB) dose engines to get the best trade-off between speed and accuracy for proton therapy plans.

METHODS

The hybrid algorithm calculates the optimal spot weights (w) by means of an iterative optimization process where the dose at each iteration is computed by using a precomputed dose influence matrix based on the conventional PB plus a correction term c obtained from a MC simulation. Updates of c can be triggered as often as necessary by calling the MC dose engine with the last corrected values of w as input. In order to analyze the performance of the hybrid algorithm against dose calculation errors, it was applied to a simplistic water phantom for which several test cases with different errors were simulated, including proton range uncertainties. Afterwards, the algorithm was used in three clinical cases (prostate, lung, and brain) and benchmarked against full MC-based optimization. The influence of different stopping criteria in the final results was also investigated.

RESULTS

The hybrid algorithm achieved excellent results provided that the estimated range in a homogeneous material is the same for the two dose engines involved, i.e., PB and MC. For the three patient cases, the hybrid plans were clinically equivalent to those obtained with full MC-based optimization. Only a single update of c was needed in the hybrid algorithm to fulfill the clinical dose constraints, which represents an extra computation time to obtain c that ranged from 1 (brain) to 4 min (lung) with respect to the conventional PB-based optimization, and an estimated average gain factor of 14 with respect to full MC-based optimization.

CONCLUSION

The hybrid algorithm provides an improved trade-off between accuracy and speed. This algorithm can be immediately considered as an option for improving dose calculation accuracy of commercial analytical treatment planning systems, without a significant increase in the computation time (≪5 min) with respect to current PB-based optimization.