Time is NTCP: Should we maximize patient throughput or perform online adaptation on proton therapy systems?

BACKGROUND: Compared to conventional radiotherapy (XT), proton therapy (PT) may improve normal tissue complication probabilities (NTCP). However, PT typically requires higher adaptation rates due to an increased sensitivity to anatomical changes. Systematic online adaptation may address this issue, but it requires additional replanning time, decreasing patient throughput. Therefore, less patients would benefit in such case from PT for a given machine capacity, with results in worse NTCP. AIM: To investigate the trade-off between PT patient throughput and NTCP gain as a function of the time needed for adaptation. METHODS: A retrospective database of 14 lung patients with two repeated 4DCTs was used to compare NTCP values between XT and PT for NTCP2ym (2-year mortality), NTCPdysphagia and NTCPpneumonitis. Four scenarios were considered for PT: no adaptation using clinical robustness parameters (4D robust optimization, 3 % range error and PTV-equivalent setup errors); systematic online adaptation with clinical robustness parameters; setup errors reduced to 4 mm and to 2 mm. Dose was accumulated on the planning CT. The number of patients treated with PT depended on the extra time needed for adaptation, assuming an 8-hours capacity (assuming 14 patients a day; thus minimum 34.2 min per treatment session if there is no or instantaneous adaptation). RESULTS: Baseline NTCP gains (PT against XT without adaptation) equaled 6.9 %, 6.1 %, and 7.7 % for NTCP2ym, NTCPdysphagia and NTCPpneumonitis, respectively. Using instantaneous online adaptation and setup errors of 2 mm, the overall gains were then 10.7 %, 13.6 % and 12.4 %. Taking into account loss of capacity, 13.7 min was the maximum extra-time allowed to complete adaptation and maintain an advantage on all three metrics for the 2-mm setup error scenario. CONCLUSION: This study highlights the critical importance of keeping short online adaptation times when using systems with limited capacity like PT.

Robustness evaluation of pencil beam scanning proton therapy treatment planning: A systematic review.

Compared to conventional radiotherapy using X-rays, proton therapy, in principle, allows better conformity of the dose distribution to target volumes, at the cost of greater sensitivity to physical, anatomical, and positioning uncertainties. Robust planning, both in terms of plan optimization and evaluation, has gained high visibility in publications on the subject and is part of clinical practice in many centers. However, there is currently no consensus on the methods and parameters to be used for robust optimization or robustness evaluation. We propose to overcome this deficiency by following the modified Delphi consensus method. This method first requires a systematic review of the literature. We performed this review using the PubMed and Web Of Science databases, via two different experts. Potential conflicts were resolved by a third expert. We then explored the different methods before focusing on clinical studies that evaluate robustness on a significant number of patients. Many robustness assessment methods are proposed in the literature. Some are more successful than others and their implementation varies between centers. Moreover, they are not all statistically or mathematically equivalent. The most sophisticated and rigorous methods have seen more limited application due to the difficulty of their implementation and their lack of widespread availability.

Dose mimicking based strategies for online adaptive proton therapy of head and neck cancer.

Objective.To compare a not adapted (NA) robust planning strategy with three fully automated online adaptive proton therapy (OAPT) workflows based on the same optimization method: dose mimicking (DM). The added clinical value and limitations of the OAPT methods are investigated for head and neck cancer (HNC) patients.Approach.The three OAPT strategies aimed at compensating for inter-fractional anatomical changes by mimiking different dose distributions on corrected cone beam CT images (corrCBCTs). Order by complexity, the OAPTs were: (1) online adaptive dose restoration (OADR) where the approved clinical dose on the planning-CT (pCT) was mimicked, (2) online adaptation using DM of the deformed clinical dose from the pCT to corrCBCTs (OADEF), and (3) online adaptation applying DM to a predicted dose on corrCBCTs (OAML). Adaptation was only applied in fractions where the target coverage criteria were not met (D98% < 95% of the prescribed dose). For 10 HNC patients, the accumulated dose distributions over the 35 fractions were calculated for NA, OADR, OADEF, and OAML.Main results.Higher target coverage was observed for all OAPT strategies compared to no adaptation. OADEF and OAML outperformed both NA and OADR and were comparable in terms of target coverage to initial clinical plans. However, only OAML provided comparable NTCP values to those from the clinical dose without statistically significant differences. When the NA initial plan was evaluated on corrCBCTs, 51% of fractions needed adaptation. The adaptation rate decreased significantly to 25% when the last adapted plan with OADR was selected for delivery, to 16% with OADEF, and to 21% with OAML. The reduction was even greater when the best plan among previously generated adapted plans (instead of the last one) was selected.Significance. The implemented OAPT strategies provided superior target coverage compared to no adaptation, higher OAR sparing, and fewer required adaptations.

Evaluation of the clinical value of automatic online dose restoration for adaptive proton therapy of head and neck cancer.

INTRODUCTION: Intensity modulated proton therapy (IMPT) is highly sensitive to anatomical variations which can cause inadequate target coverage during treatment. This study compares not-adapted (NA) robust plans to two adaptive IMPT methods - a fully-offline adaptive (FOA) and a simplified automatic online adaptive strategy (dose restoration (DR)) to determine the benefit of DR, in head and neck cancer (HNC). MATERIAL/METHODS: Robustly optimized clinical IMPT doses in planning-CTs (pCTs) were available for a cohort of 10 HNC patients. During robust re-optimization, DR used isodose contours, generated from the clinical dose on pCTs, and patient specific objectives to reproduce the clinical dose in every repeated-CT(rCT). For each rCT(n = 50), NA, DR and FOA plans were robustly evaluated. RESULTS: An improvement in DVH-metrics and robustness was seen for DR and FOA plans compared to NA plans. For NA plans, 74%(37/50) of rCTs did not fulfill the CTV coverage criteria (D98%>95%Dprescription). DR improved target coverage, target homogeneity and variability on critical risk organs such as the spinal cord. After DR, 52%(26/50) of rCTs met all clinical goals. Because of large anatomical changes and/or inaccurate patient repositioning, 48%(24/50) of rCTs still needed full offline adaptation to ensure an optimal treatment since dose restoration was not able to re-establish the initial plan quality. CONCLUSION: Robust optimization together with fully-automatized DR avoided offline adaptation in 52% of the cases. Implementation of dose restoration in clinical routine could ensure treatment plan optimality while saving valuable human and material resources to radiotherapy departments.

Development and validation of an automatic commissioning tool for the Monte Carlo dose engine in myQA iON.

Independent dose verification with Monte Carlo (MC) simulations is an important feature of proton therapy quality assurance (QA). However, clinical integration of such tools often generates an additional and complex workload for medical physicists. The preparation of the necessary clinical inputs, such as the machine beam model, should therefore be automated. In this work, a methodology for automatic MC commissioning has been devised, validated, and developed into a MATLAB tool for the users of myQA iON, the recent QA platform of IBA Dosimetry. With this workflow, all necessary parameters can easily be tuned using dedicated optimization methods. For the geometrical beam parameters (phase space), the assumption of a single or double Gaussian is made. To model the energy spectrum, a Gaussian function is assumed and parameters are optimized using either MC simulations or a library of pre-computed Bragg peaks. For the absolute dose calibration, commissioning fields can be reproduced with the dose engine to retrieve the necessary parameters. We discuss in a first time the tool efficiency and show that one can optimize all parameters in less than 4 min per energy with excellent accuracy. We then validate a beam model obtained with the tool by simulating homogeneous spread-out Bragg peaks (SOBPs) and patient QA plans previously measured in water. An average range agreement of 0.29 ± 0.34 mm is achieved for the SOBPs while 3%/3 mm local gamma passing rates reach 99.3% on average over all 62 measured patient QA planes, which is well within clinical tolerances.

Development of robustness evaluation strategies for enabling statistically consistent reporting.

Robustness evaluation of proton therapy treatment plans is essential for ensuring safe treatment delivery. However, available evaluation procedures feature a limited exploration of the actual robustness of the plan and generally do not provide confidence levels. This study compared established and more sophisticated robustness evaluation procedures, with quantified confidence levels. We have evaluated several robustness evaluation methods for 5 bilateral head-and-neck patients optimized considering spot scanning delivery and with a conventional CTV-to-PTV margin of 4 mm. Method (1) good practice scenario selection (GPSS) (e.g. +/- 4 mm setup error 3% range uncertainty); (2) statistically sound scenario selection (SSSS) either only on or both on and inside isoprobability hypersurface encompassing 90% of the possible errors; (3) statistically sound dosimetric selection (SSDS). In the last method, the 90% best plans were selected according to either target coverage quantified by D 95 (SSDS_D 95) or to an approximation of the final objective function (OF) used during treatment optimization (SSDS_OF). For all methods, we have considered systematic setup and systematic range errors. A mix of systematic and random setup errors were also simulated for SSDS, but keeping the same conventional margin of 4 mm. All robustness evaluations have been performed using the fast Monte Carlo dose engine MCsquare. Both SSSS strategies yielded on average very similar results. SSSS and GPSS yield comparable values for target coverage (within 0.5 Gy). The most noticeable differences were found for the CTV between GPSS, on the one hand, and SSDS_D 95 and SSDS_OF, on the other hand (average worst-case D 98 were 2.8 and 2.0 Gy larger than for GPSS, respectively). Simulating explicitly random errors in SSDS improved almost all DVH metrics. We have observed that the width of DVH-bands and the confidence levels depend on the method chosen to sample the scenarios. Statistically sound estimation of the robustness of the plan in the dosimetric space may provide an improved insight on the actual robustness of the plan for a given confidence level.

Impact of machine log-files uncertainties on the quality assurance of proton pencil beam scanning treatment delivery.

Irradiation log-files store useful information about the plan delivery, and together with independent Monte Carlo dose engine calculations can be used to reduce the time needed for patient-specific quality assurance (PSQA). Nonetheless, machine log-files carry an uncertainty associated to the measurement of the spot position and intensity that can influence the correct evaluation of the quality of the treatment delivery. This work addresses the problem of the inclusion of these uncertainties for the final verification of the treatment delivery. Dedicated measurements performed in an IBA Proteus Plus gantry with a pencil beam scanning (PBS) dedicated nozzle have been carried out to build a 'room-dependent' model of the spot position uncertainties. The model has been obtained through interpolation of the look-up tables describing the systematic and random uncertainties, and it has been tested for a clinical case of a brain cancer patient irradiated in a dry-run. The delivered dose has been compared with the planned dose with the inclusion of the errors obtained applying the model. Our results suggest that the accuracy of the treatment delivery is higher than the spot position uncertainties obtained from the log-file records. The comparison in terms of DVHs shows that the log-reconstructed dose is compatible with the planned dose within the 95% confidence interval obtained applying our model. The initial mean dose difference between the calculated dose to the patient based on the plan and recorded data is around 1%. The difference is essentially due to the log-file uncertainties and it can be removed with a correct treatment of these errors. In conclusion our new PSQA protocol allows for a fast verification of the dose delivered after every treatment fraction through the use of machine log-files and an independent Monte Carlo dose engine. Moreover, the inclusion of log-file uncertainties in the dose calculation allows for a correct evaluation of the quality of the treatment plan delivery.

Experimental assessment of proton dose calculation accuracy in inhomogeneous media.

PURPOSE: Proton therapy with Pencil Beam Scanning (PBS) has the potential to improve radiotherapy treatments. Unfortunately, its promises are jeopardized by the sensitivity of the dose distributions to uncertainties, including dose calculation accuracy in inhomogeneous media. Monte Carlo dose engines (MC) are expected to handle heterogeneities better than analytical algorithms like the pencil-beam convolution algorithm (PBA). In this study, an experimental phantom has been devised to maximize the effect of heterogeneities and to quantify the capability of several dose engines (MC and PBA) to handle these. METHODS: An inhomogeneous phantom made of water surrounding a long insert of bone tissue substitute (1×10×10 cm3) was irradiated with a mono-energetic PBS field (10×10 cm2). A 2D ion chamber array (MatriXX, IBA Dosimetry GmbH) lied right behind the bone. The beam energy was such that the expected range of the protons exceeded the detector position in water and did not attain it in bone. The measurement was compared to the following engines: Geant4.9.5, PENH, MCsquare, as well as the MC and PBA algorithms of RayStation (RaySearch Laboratories AB). RESULTS: For a γ-index criteria of 2%/2mm, the passing rates are 93.8% for Geant4.9.5, 97.4% for PENH, 93.4% for MCsquare, 95.9% for RayStation MC, and 44.7% for PBA. The differences in γ-index passing rates between MC and RayStation PBA calculations can exceed 50%. CONCLUSION: The performance of dose calculation algorithms in highly inhomogeneous media was evaluated in a dedicated experiment. MC dose engines performed overall satisfactorily while large deviations were observed with PBA as expected.

[Robust treatment planning in proton therapy]. / Planification de traitement robuste en protonthérapie.

The concentration of the dose delivered by protons at the end of their path, the Bragg peak, has the potential to improve external radiotherapy treatments. Unfortunately, the main strength of the protons, their finite range, is also their greatest weakness. Any uncertainty on the range may lead to inadequate target coverage or excessive toxicity. The uncertainties have multiple origins and include, among others, ballistic errors, morphological modifications or inaccurate estimations of the physical quantities necessary to predict the proton range. Uncertainties have been part of daily practice in conventional radiotherapy with X-rays for a long time. However, dose distributions delivered with X-rays are much less sensitive to uncertainties than the ones delivered with protons. This relative insensitivity enabled the management of uncertainties through safety margins using a simple formalism. The conditions of validity of this formalism are much more restrictive for proton therapy, leading to the need of developing new tools and adapted strategies to manage accurately these uncertainties. The objective of this paper is to present a vision for the management of uncertainties in proton therapy in the continuity of formalisms established for X-rays. The latter are first summarized before discussing the necessary developments in order to consistently apply them to protons.

Potential pitfalls of the PTV concept in dose-to-medium planning optimization.

In typical treatment planning of 3D IMRT, the incident energy fluence is optimized to achieve a homogeneous dose distribution to the PTV. The PTV includes the tumour but also healthy tissues that may have a different dose response for the same incident energy fluence, like bony structures included in the PTV (mandibles in head and neck tumours or femoral bones in sarcomas). Dose to medium optimization compensates for this heterogeneous response, leading to a non-homogeneous energy fluence in the PTV and a non-homogeneous dose in the CTV in the presence of geometric errors. We illustrate qualitatively this statement in a cylindrical geometry where the PTV includes a CTV (7cm diameter) made of water surrounded by ICRU compact bone (1.2cm thickness); such configuration was chosen to exaggerate the aforementioned effect. Optimization was performed assuming dose equals photon energy fluence times mass energy absorption coefficient. Bone has a 4% lower dose response in a 6 MV flattening filter free spectrum. After optimization either in medium or assuming everything as water composition, the geometry was shifted by 1.2cm and dose recomputed. As expected, compensating for the under-response of the bone material during optimization in medium leads to an overdosage of the CTV when patient geometric errors are taken into account. Optimization in dose assuming everything as water composition leads to a uniform coverage. Robust optimization or forcing a uniform atomic composition in the PTV margin may resolve this incompatibility between the PTV concept and dose to medium optimization.

Detection of mixed-range proton pencil beams with a prompt gamma slit camera.

With increasing availability of proton and particle therapy centers for tumor treatment, the need for in vivo range verification methods comes more into the focus. Imaging of prompt gamma rays emitted during the treatment is one of the possibilities currently under investigation. A knife-edge shaped slit camera was recently proposed for this task and measurements proved the feasibility of range deviation detection in homogeneous and inhomogeneous targets. In the present paper, we concentrate on laterally inhomogeneous materials, which lead to range mixing situations when crossed by one pencil beam: different sections of the beam have different ranges. We chose exemplative cases from clinical irradiation and assembled idealized tissue equivalent targets. One-dimensional emission profiles were obtained by measuring the prompt gamma emission with the slit camera. It could be shown that the resulting range deviations can be detected by evaluation of the measured data with a previously developed range deviation detection algorithm. The retrieved value, however, strongly depends on the target composition, and is not necessarily in direct relation to the ranges of both parts of the beam. By combining the range deviation detection with an analysis of the slope of the distal edge of the measured prompt gamma profile, the origin of the detected range deviation, i.e. the mixed range of the beam, is also identified. It could be demonstrated that range mixed prompt gamma profiles exhibit less steep distal slopes than profiles from beams traversing laterally homogeneous material. For future application of the slit camera to patient irradiation with double scattered proton beams, situations similar to the range mixing cases are present and results could possibly apply.

Analytical computation of prompt gamma ray emission and detection for proton range verification.

A prompt gamma (PG) slit camera prototype recently demonstrated that Bragg Peak position in a clinical proton scanned beam could be measured with 1-2 mm accuracy by comparing an expected PG detection profile to a measured one. The computation of the expected PG detection profile in the context of a clinical framework is challenging but must be solved before clinical implementation. Obviously, Monte Carlo methods (MC) can simulate the expected PG profile but at prohibitively long calculation times. We implemented a much faster method that is based on analytical processing of precomputed MC data that would allow practical evaluation of this range monitoring approach in clinical conditions. Reference PG emission profiles were generated with MC simulations (PENH) in targets consisting of either (12)C, (14)N, (16)O, (31)P or (40)Ca, with 10% of (1)H. In a given geometry, the local PG emission can then be derived by adding the contribution of each element, according to the local energy of the proton obtained by continuous slowing down approximation and the local composition. The actual incident spot size is taken into account using an optical model fitted to measurements and by super sampling the spot with several rays (up to 113). PG transport in the patient/camera geometries and the detector response are modelled by convolving the PG production profile with a transfer function. The latter is interpolated from a database of transfer functions fitted to MC data (PENELOPE) generated for a photon source in a cylindrical phantom with various radiuses and a camera placed at various positions. As a benchmark, the analytical model was compared to MC and experiments in homogeneous and heterogeneous phantoms. Comparisons with MC were also performed in a thoracic CT. For all cases, the analytical model reproduced the prediction of the position of the Bragg peak computed with MC within 1 mm for the camera in nominal configuration. When compared to measurements, the shape of the profiles was well reproduced and agreement for the estimation of the position of the Bragg peak was within 2.7 mm on average (1.4 mm standard deviation). On a non-optimized MATLAB code, computation time with the analytical model is between 0.3 to 10 s depending on the number of rays simulated per spot. The analytical model can be further used to determine which spots are the best candidates to evaluate the range in clinical conditions and eventually correct for over- and under-shoots depending on the acquired PG profiles.

Measurement of prompt gamma profiles in inhomogeneous targets with a knife-edge slit camera during proton irradiation.

Proton and ion beam therapies become increasingly relevant in radiation therapy. To fully exploit the potential of this irradiation technique and to achieve maximum target volume conformality, the verification of particle ranges is highly desirable. Many research activities focus on the measurement of the spatial distributions of prompt gamma rays emitted during irradiation. A passively collimating knife-edge slit camera is a promising option to perform such measurements. In former publications, the feasibility of accurate detection of proton range shifts in homogeneous targets could be shown with such a camera. We present slit camera measurements of prompt gamma depth profiles in inhomogeneous targets. From real treatment plans and their underlying CTs, representative beam paths are selected and assembled as one-dimensional inhomogeneous targets built from tissue equivalent materials. These phantoms have been irradiated with monoenergetic proton pencil beams. The accuracy of range deviation estimation as well as the detectability of range shifts is investigated in different scenarios. In most cases, range deviations can be detected within less than 2 mm. In close vicinity to low-density regions, range detection is challenging. In particular, a minimum beam penetration depth of 7 mm beyond a cavity is required for reliable detection of a cavity filling with the present setup. Dedicated data post-processing methods may be capable of overcoming this limitation.

Influence of the physical data to calibrate TEPCs.

Tissue-equivalent proportional counters (TEPCs) measure distributions of ionisations, produced in the gas cavity by the radiation field which are afterwards converted into distributions of energy imparted by applying a calibration factor. To calibrate the pulse-height spectra, first, a marker point must be identified in the measured spectrum. Then, an accurate value of lineal energy must be assigned to this marker. A common marker that is often used for calibration is the so-called proton-edge (p-edge). It is a distinctive feature of a proton or neutron spectrum which corresponds to the maximum amount of energy that a proton can deposit in the active volume of the detector. A precise method to identify the marker point was applied to identify the p-edge with an uncertainty below 1 %. To evaluate the final uncertainty of the calibration, the uncertainty of the energy value assigned to the p-edge must also be considered. This value can be evaluated using different energy-range tables. This study investigates how the choice of different input databases for calibration purposes influences the calibration. The effect of three different frequently used sets of input data was analysed for pure propane gas and for propane-TE gas mixture.

Feasibility and robustness of dose painting by numbers in proton therapy with contour-driven plan optimization.

PURPOSE: To prove the ability of protons to reproduce a dose gradient that matches a dose painting by numbers (DPBN) prescription in the presence of setup and range errors, by using contours and structure-based optimization in a commercial treatment planning system. METHODS: For two patients with head and neck cancer, voxel-by-voxel prescription to the target volume (GTVPET) was calculated from (18)FDG-PET images and approximated with several discrete prescription subcontours. Treatments were planned with proton pencil beam scanning. In order to determine the optimal plan parameters to approach the DPBN prescription, the effects of the scanning pattern, number of fields, number of subcontours, and use of range shifter were separately tested on each patient. Different constant scanning grids (i.e., spot spacing = Δx = Δy = 3.5, 4, and 5 mm) and uniform energy layer separation [4 and 5 mm WED (water equivalent distance)] were analyzed versus a dynamic and automatic selection of the spots grid. The number of subcontours was increased from 3 to 11 while the number of beams was set to 3, 5, or 7. Conventional PTV-based and robust clinical target volumes (CTV)-based optimization strategies were considered and their robustness against range and setup errors assessed. Because of the nonuniform prescription, ensuring robustness for coverage of GTVPET inevitably leads to overdosing, which was compared for both optimization schemes. RESULTS: The optimal number of subcontours ranged from 5 to 7 for both patients. All considered scanning grids achieved accurate dose painting (1% average difference between the prescribed and planned doses). PTV-based plans led to nonrobust target coverage while robust-optimized plans improved it considerably (differences between worst-case CTV dose and the clinical constraint was up to 3 Gy for PTV-based plans and did not exceed 1 Gy for robust CTV-based plans). Also, only 15% of the points in the GTVPET (worst case) were above 5% of DPBN prescription for robust-optimized plans, while they were more than 50% for PTV plans. Low dose to organs at risk (OARs) could be achieved for both PTV and robust-optimized plans. CONCLUSIONS: DPBN in proton therapy is feasible with the use of a sufficient number subcontours, automatically generated scanning patterns, and no more than three beams are needed. Robust optimization ensured the required target coverage and minimal overdosing, while PTV-approach led to nonrobust plans with excessive overdose. Low dose to OARs can be achieved even in the presence of a high-dose escalation as in DPBN.

Monte Carlo simulations of patient dose perturbations in rotational-type radiotherapy due to a transverse magnetic field: a tomotherapy investigation.

PURPOSE: Several groups are exploring the integration of magnetic resonance (MR) image guidance with radiotherapy to reduce tumor position uncertainty during photon radiotherapy. The therapeutic gain from reducing tumor position uncertainty using intrafraction MR imaging during radiotherapy could be partially offset if the negative effects of magnetic field-induced dose perturbations are not appreciated or accounted for. The authors hypothesize that a more rotationally symmetric modality such as helical tomotherapy will permit a systematic mediation of these dose perturbations. This investigation offers a unique look at the dose perturbations due to homogeneous transverse magnetic field during the delivery of Tomotherapy(®) Treatment System plans under varying degrees of rotational beamlet symmetry. METHODS: The authors accurately reproduced treatment plan beamlet and patient configurations using the Monte Carlo code geant4. This code has a thoroughly benchmarked electromagnetic particle transport physics package well-suited for the radiotherapy energy regime. The three approved clinical treatment plans for this study were for a prostate, head and neck, and lung treatment. The dose heterogeneity index metric was used to quantify the effect of the dose perturbations to the target volumes. RESULTS: The authors demonstrate the ability to reproduce the clinical dose-volume histograms (DVH) to within 4% dose agreement at each DVH point for the target volumes and most planning structures, and therefore, are able to confidently examine the effects of transverse magnetic fields on the plans. The authors investigated field strengths of 0.35, 0.7, 1, 1.5, and 3 T. Changes to the dose heterogeneity index of 0.1% were seen in the prostate and head and neck case, reflecting negligible dose perturbations to the target volumes, a change from 5.5% to 20.1% was observed with the lung case. CONCLUSIONS: This study demonstrated that the effect of external magnetic fields can be mitigated by exploiting a more rotationally symmetric treatment modality.

Monte Carlo evaluation of the dose calculation algorithm of TomoTherapy for clinical cases in dynamic jaws mode.

PURPOSE: For the TomoTherapy(®) system, longitudinal conformation can be improved by selecting a smaller field width but at the expense of longer treatment time. Recently, the TomoEdge(®) feature has been released with the possibility to move dynamically the jaws at the edges of the target volume, improving longitudinal penumbra and enabling faster treatments. Such delivery scheme requires additional modeling of treatment delivery. Using a previously validated Monte Carlo model (TomoPen), we evaluated the accuracy of the implementation of TomoEdge in the new dose engine of TomoTherapy for 15 clinical cases. METHODS: TomoPen is based on PENELOPE. Particle tracking in the treatment head is performed almost instantaneously by 1) reading a particle from a phase-space file corresponding to the largest field and 2) correcting the weight of the particle depending on the actual jaw and MLC configurations using Monte Carlo pre-generated data. 15 clinical plans (5 head-and-neck, 5 lung and 5 prostate tumors) planned with TomoEdge and with the last release of the treatment planning system (VoLO(®)) were re-computed with TomoPen. The resulting dose-volume histograms were compared. RESULTS: Good agreement was achieved overall, with deviations for the target volumes typically within 2% (D95), excepted for small lung tumors (17 cm(3)) where a maximum deviation of 4.4% was observed for D95. The results were consistent with previously reported values for static field widths. CONCLUSIONS: For the clinical cases considered in the present study, the introduction of TomoEdge did not impact significantly the accuracy of the computed dose distributions.

Metabolic imaging in non-small-cell lung cancer radiotherapy.

Metabolic imaging by positrons emission tomography (PET) offers new perspectives in the field of non-small-cell lung cancer radiation therapy. First, it can be used to refine the way nodal and primary tumour target volumes are selected and delineated, in better agreement with the underlying tumour reality. In addition, the non-invasive spatiotemporal mapping of the tumour biology and the organs at risk function might be further used to steer radiation dose distribution. Delivering higher dose to low responsive tumour area, in a way that better preserves the normal tissue function, should thus reconcile the tumour radiobiological imperatives (maximising tumour local control) with dose related to the treatment safety (minimising late toxicity). By predicting response early in the course of radiation therapy, PET may also participate to better select patients who are believed to benefit most from treatment intensification. Altogether, these technological advances open avenues to in-depth modify the way the treatment plan is designed and the dose is delivered, in better accordance with the radiobiology of individual solid cancers and normal tissues.

Monte Carlo tools to supplement experimental microdosimetric spectra.

Tissue-equivalent proportional counters (TEPCs) are widely used in experimental microdosimetry for characterising the radiation quality in radiation protection and radiation therapy environments. Generally, TEPCs are filled with tissue-equivalent gas mixtures, at low gas pressure, to simulate tissue site sizes similar to the cell nucleus (1 or 2 µm). The TEPC response using Monte Carlo (MC) codes can be applied to supplement experimental measurements. Most of general-purpose MC codes currently available recourse to the condensed-history approach to model the electron transport and do not transport low-energy electrons (<1 keV), which can lead to systematic errors, especially in thin layers and in gas-condensed medium interfaces. In this work, a comparison between experimental microdosimetric spectra of (60)Co and (137)Cs radiation at different simulated sizes (from 1.0 to 3.0 µm) in pure propane versus simulated spectra obtained with two general-purpose codes FLUKA and PENELOPE, which include a detailed simulation of electron-photon transport in arbitrary materials, including gases, is presented.

Extension of PENELOPE to protons: simulation of nuclear reactions and benchmark with Geant4.

PURPOSE: Describing the implementation of nuclear reactions in the extension of the Monte Carlo code (MC) PENELOPE to protons (PENH) and benchmarking with Geant4. METHODS: PENH is based on mixed-simulation mechanics for both elastic and inelastic electromagnetic collisions (EM). The adopted differential cross sections for EM elastic collisions are calculated using the eikonal approximation with the Dirac-Hartree-Fock-Slater atomic potential. Cross sections for EM inelastic collisions are computed within the relativistic Born approximation, using the Sternheimer-Liljequist model of the generalized oscillator strength. Nuclear elastic and inelastic collisions were simulated using explicitly the scattering analysis interactive dialin database for (1)H and ICRU 63 data for (12)C, (14)N, (16)O, (31)P, and (40)Ca. Secondary protons, alphas, and deuterons were all simulated as protons, with the energy adapted to ensure consistent range. Prompt gamma emission can also be simulated upon user request. Simulations were performed in a water phantom with nuclear interactions switched off or on and integral depth-dose distributions were compared. Binary-cascade and precompound models were used for Geant4. Initial energies of 100 and 250 MeV were considered. For cases with no nuclear interactions simulated, additional simulations in a water phantom with tight resolution (1 mm in all directions) were performed with FLUKA. Finally, integral depth-dose distributions for a 250 MeV energy were computed with Geant4 and PENH in a homogeneous phantom with, first, ICRU striated muscle and, second, ICRU compact bone. RESULTS: For simulations with EM collisions only, integral depth-dose distributions were within 1%/1 mm for doses higher than 10% of the Bragg-peak dose. For central-axis depth-dose and lateral profiles in a phantom with tight resolution, there are significant deviations between Geant4 and PENH (up to 60%/1 cm for depth-dose distributions). The agreement is much better with FLUKA, with deviations within 3%/3 mm. When nuclear interactions were turned on, agreement (within 6% before the Bragg-peak) between PENH and Geant4 was consistent with uncertainties on nuclear models and cross sections, whatever the material simulated (water, muscle, or bone). CONCLUSIONS: A detailed and flexible description of nuclear reactions has been implemented in the PENH extension of PENELOPE to protons, which utilizes a mixed-simulation scheme for both elastic and inelastic EM collisions, analogous to the well-established algorithm for electrons/positrons. PENH is compatible with all current main programs that use PENELOPE as the MC engine. The nuclear model of PENH is realistic enough to give dose distributions in fair agreement with those computed by Geant4.