N Koch

Monte Carlo simulations for configuring and testing an analytical proton dose-calculation algorithm

Contemporary treatment planning systems for proton radiotherapy typically use analytical pencil-beam algorithms - which require a comprehensive set of configuration data - to predict the absorbed dose distributions in the patient. In order to reduce the time required to prepare a new proton treatment planning system for clinical use, it was desirable to configure the planning system before measured beam data were available. However, it was not known if the Monte Carlo simulation method was a practical alternative to measuring beam profiles. The purpose of this study was to develop a model of a passively scattered proton therapy unit, to simulate the properties of the proton fields using the Monte Carlo technique and to configure an analytical treatment planning system using the simulated beam data. Additional simulations and treatment plans were calculated in order to validate the pencil-beam predictions against the Monte Carlo simulations using realistic treatment beams. Comparison of dose distributions in a water phantom revealed small dose difference and distances to agreement under the validation conditions. The total simulation time for generating the 768 beam configuration profiles was approximately 6 weeks using 30 nodes in a parallel processing cluster. The results of this study show that it is possible to configure and test a proton treatment planning system prior to the availability of measured proton beam data. The model presented here provided a means to reduce by several months the time required to prepare an analytical treatment planning system for patient treatments.

Monte Carlo simulations of a nozzle for the treatment of ocular tumours with high-energy proton beams.

By the end of 2002, 33 398 patients worldwide had been treated with proton radiotherapy, 10 829 for eye diseases. The dose prediction algorithms used today for ocular proton therapy treatment planning rely on parameterizations of measured proton dose distributions, i.e., broad-beam and pencil-beam techniques, whose predictive capabilities are inherently limited by severe approximations and simplifications in modelling the radiation transport physics. In contrast, the Monte Carlo radiation transport technique can, in principle, provide accurate predictions of the proton treatment beams by taking into account all the physical processes involved, including coulombic energy loss, energy straggling, multiple Coulomb scattering, elastic and nonelastic nuclear interactions, and the transport of secondary particles. It has not been shown, however, whether it is possible to commission a proton treatment planning system by using data exclusively from Monte Carlo simulations of the treatment apparatus and a phantom. In this work, we made benchmark comparisons between Monte Carlo predictions and measurements of an ocular proton treatment beamline. The maximum differences between absorbed dose profiles from simulations and measurements were 6% and 0.6 mm, while typical differences were less than 2% and 0.2 mm. The computation time for the entire virtual commissioning process is less than one day. The study revealed that, after a significant development effort, a Monte Carlo model of a proton therapy apparatus is sufficiently accurate and fast for commissioning a treatment planning system.

Monte Carlo simulations of the dosimetric impact of radiopaque fiducial markers for proton radiotherapy of the prostate

Many clinical studies have demonstrated that implanted radiopaque fiducial markers improve targeting accuracy in external-beam radiotherapy, but little is known about the dose perturbations these markers may cause in patients receiving proton radiotherapy. The objective of this study was to determine what types of implantable markers are visible in setup radiographs and, at the same time, perturb the therapeutic proton dose to the prostate by less than 10%. The radiographic visibility of the markers was assessed by visual inspection of lateral setup radiographs of a pelvic phantom using a kilovoltage x-ray imaging system. The fiducial-induced perturbations in the proton dose were estimated with Monte Carlo simulations. The influence of marker material, size, placement depth and orientation within the pelvis was examined. The radiographic tests confirmed that gold and stainless steel markers were clearly visible and that titanium markers were not. The Monte Carlo simulations revealed that titanium and stainless steel markers minimally perturbed the proton beam, but gold markers cast unacceptably large dose shadows. A 0.9 mm diameter, 3.1 mm long cylindrical stainless steel marker provides good radiographic visibility yet perturbs the proton dose distribution in the prostate by less than 8% when using a parallel opposed lateral beam arrangement.

Dosimetric impact of tantalum markers used in the treatment of uveal melanoma with proton beam therapy

Metallic fiducial markers are frequently implanted in patients prior to external-beam radiation therapy to facilitate tumor localization. There is little information in the literature, however, about the perturbations in proton absorbed-dose distribution these objects cause. The aim of this study was to assess the dosimetric impact of perturbations caused by 2.5 mm diameter by 0.2 mm thick tantalum fiducial markers when used in proton therapy for treating uveal melanoma. Absorbed dose perturbations were measured using radiochromic film and confirmed by Monte Carlo simulations of the experiment. Additional Monte Carlo simulations were performed to study the effects of range modulation and fiducial placement location on the magnitude of the dose shadow for a representative uveal melanoma treatment. The simulations revealed that the fiducials caused perturbations in the absorbed-dose distribution, including absorbed-dose shadows of 22% to 82% in a typical proton beam for treating uveal melanoma, depending on the marker depth and orientation. The clinical implication of this study is that implanted fiducials may, in certain circumstances, cause dose shadows that could lower the tumor dose and theoretically compromise local tumor control. To avoid this situation, fiducials should be positioned laterally or distally with respect to the target volume.

Monte Carlo calculations and measurements of absorbed dose per monitor unit for the treatment of uveal melanoma with proton therapy

The treatment of uveal melanoma with proton radiotherapy has provided excellent clinical outcomes. However, contemporary treatment planning systems use simplistic dose algorithms that limit the accuracy of relative dose distributions. Further, absolute predictions of absorbed dose per monitor unit are not yet available in these systems. The purpose of this study was to determine if Monte Carlo methods could predict dose per monitor unit (D/MU) value at the center of a proton spread-out Bragg peak (SOBP) to within 1% on measured values for a variety of treatment fields relevant to ocular proton therapy. The MCNPX Monte Carlo transport code, in combination with realistic models for the ocular beam delivery apparatus and a water phantom, was used to calculate dose distributions and D/MU values, which were verified by the measurements. Measured proton beam data included central-axis depth dose profiles, relative cross-field profiles and absolute D/MU measurements under several combinations of beam penetration ranges and range-modulation widths. The Monte Carlo method predicted D/MU values that agreed with measurement to within 1% and dose profiles that agreed with measurement to within 3% of peak dose or within 0.5 mm distance-to-agreement. Lastly, a demonstration of the clinical utility of this technique included calculations of dose distributions and D/MU values in a realistic model of the human eye. It is possible to predict D/MU values accurately for clinical relevant range-modulated proton beams for ocular therapy using the Monte Carlo method. It is thus feasible to use the Monte Carlo method as a routine absolute dose algorithm for ocular proton therapy.

Calibration of the Gamma Knife Perfexion using TG‐21 and the solid water Leksell dosimetry phantom

PURPOSE To calibrate a Gamma Knife (GK) Perfexion using TG-21 with updated chamber-dependent values for modern microionization chambers in the new solid water Leksell dosimetry phantom. This work illustrates a calibration method using commercially available equipment, instruments, and an established dosimetry protocol that may be adopted at any GK center, thus reducing the interinstitutional variation in GK calibration. The calibration was verified by three third-party dosimetry checks. In addition, measurements of the relative output factors are presented and compared to available data and the new manufacturer-provided relative output factors yet to be released. METHODS An absolute dose calibration based on the TG-21 formalism, utilizing recently reported phantom material and chamber-dependent factors, was performed using a microionization chamber in a spherical solid water phantom. The result was compared to other calibration protocols based on TG-51. Independent verification of the machine output was conducted through M.D. Anderson Dosimetry Services (MDADS), using thermoluminescent dosimeters (TLDs) in an anthropomorphic head phantom; the Radiological Physics Center (RPC), using TLDs in the standard Elekta ABS plastic calibration phantom (gray phantom), included with the GK; and through a collaborative international calibration survey by the University of Pittsburgh Medical Center (UPMC) using alanine dosimeters, also in the gray phantom. The alanine dosimeters were read by the National Institute of Standards and Technology. Finally, Gafchromic EBT film was used to measure relative output factors and these factors were compared to values reported in the literature as well as new values announced for release by Elekta. The films were exposed in the solid water phantom using an included film insert accessory. RESULTS Compared to the TG-21 protocol in the solid water phantom, the modified and unmodified TG-51 calibrations resulted in dose rates which were 1.8% and 1.3% lower, respectively. Ratios of the doses measured by third parties to the dose reported showed excellent agreement. MDADS returned ratios of 1.00 and 0.98 for the two TLDs irradiated. The RPC returned a mean ratio of 0.98 of the dose reported and the UPMC alanine study returned a mean ratio of 1.008. Relative output factors were found to be 0.817 +/- 0.009 and 0.897 +/- 0.008 for the 4 and 8 mm collimators, respectively, which are in excellent agreement with revised Monte Carlo-derived relative output factors Elekta is expected to recommend with the next version of the GK treatment planning software (GAMMAPLAN version 10). CONCLUSIONS The TG-21 dosimetry protocol, performed in a solid water phantom in conjunction with modern dosimeters and phantom material and chamber-dependent factors, can yield an accurate dose measurement in the unique GK treatment geometry. The technique described here can be easily adopted by institutions worldwide since all equipment and instruments used are commercially available, thus reducing the existing interinstitutional variation in GK calibration techniques. Relative output factor measurements made in this same solid water phantom were used to verify the relative output factors provided by Elekta and agreed excellently with output factors expected to be released in conjunction with GAMMAPLAN version 10.

Development and verification of an analytical algorithm to predict absorbed dose distributions in ocular proton therapy using Monte Carlo simulations

Proton beam radiotherapy is an effective and non-invasive treatment for uveal melanoma. Recent research efforts have focused on improving the dosimetric accuracy of treatment planning and overcoming the present limitation of relative analytical dose calculations. Monte Carlo algorithms have been shown to accurately predict dose per monitor unit (D/MU) values, but this has yet to be shown for analytical algorithms dedicated to ocular proton therapy, which are typically less computationally expensive than Monte Carlo algorithms. The objective of this study was to determine if an analytical method could predict absolute dose distributions and D/MU values for a variety of treatment fields like those used in ocular proton therapy. To accomplish this objective, we used a previously validated Monte Carlo model of an ocular nozzle to develop an analytical algorithm to predict three-dimensional distributions of D/MU values from pristine Bragg peaks and therapeutically useful spread-out Bragg peaks (SOBPs). Results demonstrated generally good agreement between the analytical and Monte Carlo absolute dose calculations. While agreement in the proximal region decreased for beams with less penetrating Bragg peaks compared with the open-beam condition, the difference was shown to be largely attributable to edge-scattered protons. A method for including this effect in any future analytical algorithm was proposed. Comparisons of D/MU values showed typical agreement to within 0.5%. We conclude that analytical algorithms can be employed to accurately predict absolute proton dose distributions delivered by an ocular nozzle.

Assessing the usefulness of 18F-fluorodeoxyglucose PET-CT scan after stereotactic body radiotherapy for early-stage non-small cell lung cancer.

BACKGROUND Although stereotactic body radiation therapy (SBRT) is an established treatment option for early-stage lung cancer, there are no guidelines for reassessing patients for local treatment failure or intrathoracic recurrence after treatment. This study reports the sensitivity, specificity, and positive and negative predictive values for 18F-fluorodeoxyglucose (FDG) PET-CT scanning when used to evaluate patients after SBRT. METHODS Charts were reviewed of all patients who received SBRT and a subsequent FDG PET-CT scan at a university hospital over a 5-year period. Pretreatment and 3-month posttreatment tumor characteristics on PET-CT scan and outcome data (adverse events from SBRT, need for repeat biopsy, rate of local treatment failure and recurrent disease, and all-cause mortality) were recorded. RESULTS Eighty-eight patients were included in the study. Fourteen percent of patients (12 of 88) had positive 3-month PET scans. Of the positive results, 67% (eight of 12) were true positives. Eighty-six percent (76 of 88 patients) had negative 3-month FDG PET-CT scans, with 89% (68 of 76) true negatives. FDG PET-CT scan performed 3 months after SBRT for non-small cell lung cancer (NSCLC) had a sensitivity of 50% (95% CI, 0.26-0.75), a specificity of 94% (95% CI, 0.89-1.0), a positive predictive value of 67% (95% CI, 0.4-0.93), and a negative predictive value of 89% (95% CI, 0.83- 0.96). CONCLUSIONS FDG PET-CT scan 3 months after treatment of NSCLC with SBRT was a specific but insensitive test for the detection of recurrence or treatment failure. Serial CT scans should be used for early surveillance following SBRT, whereas FDG PET-CT scans should be reserved to define suspected metastatic disease or to evaluate new abnormalities on CT scan, or for possible reassessment later in the follow-up period after radiation-related inflammation subsides.

Validation of a modern second‐check dosimetry system using a novel verification phantom

Abstract Purpose To evaluate the Mobius second‐check dosimetry system by comparing it to ionization‐chamber dose measurements collected in the recently released Mobius Verification Phantom™ (MVP). For reference, a comparison of these measurements to dose calculated in the primary treatment planning system (TPS), Varian Eclipse with the AcurosXB dose algorithm, is also provided. Finally, patient dose calculated in Mobius is compared directly to Eclipse to demonstrate typical expected results during clinical use of the Mobius system. Methods Seventeen anonymized intensity‐modulated clinical treatment plans were selected for analysis. Dose was recalculated on the MVP in both Eclipse and Mobius. These calculated doses were compared to doses measured using an A1SL ionization‐chamber in the MVP. Dose was measured and analyzed at two different chamber positions for each treatment plan. Mobius calculated dose was then compared directly to Eclipse using the following metrics; target mean dose, target D95%, global 3D gamma pass rate, and target gamma pass rate. Finally, these same metrics were used to analyze the first 36 intensity modulated cases, following clinical implementation of the Mobius system. Results The average difference between Mobius and measurement was 0.3 ± 1.3%. Differences ranged from −3.3 to + 2.2%. The average difference between Eclipse and measurement was −1.2 ± 0.7%. Eclipse vs. measurement differences ranged from −3.0 to −0.1%. For the 17 anonymized pre‐clinical cases, the average target mean dose difference between Mobius and Eclipse was 1.0 ± 1.1%. Average target D95% difference was ‐0.9 ± 2.0%. Average global gamma pass rate, using a criteria of 3%, 2 mm, was 94.4 ± 3.3%, and average gamma pass rate for the target volume only was 80.2 ± 12.3%. Results of the first 36 intensity‐modulated cases, post‐clinical implementation of Mobius, were similar to those seen for the 17 pre‐clinical test cases. Conclusion Mobius correctly calculated dose for each tested intensity modulated treatment plan, agreeing with measurement to within 3.5% for all cases analyzed. The dose calculation accuracy and independence of the Mobius system is sufficient to provide a rigorous second‐check of a modern TPS.

SU‐FF‐T‐25: A Monte‐Carlo Based Dose Engine for Proton Radiotherapy Treatment Planning

Purpose: To develop a fast Monte Carlo (MC)dose engine for protonradiation treatment planning calculations and research studies. Method and Materials: We developed a complete MC simulation system for calculating the dose distributions in patients. The system uses a commercial treatment planning system with an analytical dose algorithm to design the treatment plans. A DICOM‐RT‐ION interface was developed to allow automated data transfer between the treatment planning system and the MC system. The MCmodel included all major components of a passively‐scattered protontreatment unit and a CT‐based patient model. A suite of programs converted the prescriptive data (e.g., range, modulation width, field size) and patient CT data into a MC input file, including coordinate system transformations for arbitrary treatment beam orientations. The radiation transport calculations are performed with the MCNPX Monte Carlo system running on a cluster of 512 64‐bit CPUs. For each treatment field, multiple simulation output files were postprocessed and the resulting MCdose matrix was written to the DICOM‐RT‐ION plan. The plan was then imported into the commercial planning system for visualization. Results: The MC simulations and pencil beam dose distributions are in good agreement for a two‐field prostate plan and a three‐field lung plan. The prostate plan required 1.6 hours and the lung plan required 14 hours using 512 CPUs to achieve < 2 % statistical uncertainty in the total dose at isocenter. The computing time was directly related to the number of voxels in the patient model. Timing studies revealed that the simulation speed for this system scales almost linearly with the inverse number of CPUs. Conclusion: The results of this study strongly suggest that it is feasible to implement a fast and easy‐to‐use MCtreatment planningdose engine with currently available computing technologies and resources.