Automated Monte Carlo Simulation of Proton Therapy Treatment Plans.

Simulations of clinical proton radiotherapy treatment plans using general purpose Monte Carlo codes have been proven to be a valuable tool for basic research and clinical studies. They have been used to benchmark dose calculation methods, to study radiobiological effects, and to develop new technologies such as in vivo range verification methods. Advancements in the availability of computational power have made it feasible to perform such simulations on large sets of patient data, resulting in a need for automated and consistent simulations. A framework called MCAUTO was developed for this purpose. Both passive scattering and pencil beam scanning delivery are supported. The code handles the data exchange between the treatment planning system and the Monte Carlo system, which requires not only transfer of plan and imaging information but also translation of institutional procedures, such as output factor definitions. Simulations are performed on a high-performance computing infrastructure. The simulation methods were designed to use the full capabilities of Monte Carlo physics models, while also ensuring consistency in the approximations that are common to both pencil beam and Monte Carlo dose calculations. Although some methods need to be tailored to institutional planning systems and procedures, the described procedures show a general road map that can be easily translated to other systems.

Fractionated Lung IMPT Treatments: Sensitivity to Setup Uncertainties and Motion Effects Based on Single-Field Homogeneity.

Treatment uncertainties in radiotherapy are either systematic or random. This study evaluates the sensitivity of fractionated intensity-modulated proton therapy (IMPT) lung treatments to systematic and random setup uncertainties. Treatments in which single-field homogeneity was restricted to within ±20% (IMPT20%) were compared to full IMPT (IMPTfull) for 10 patients with lung cancer. Four-dimensional Monte Carlo calculations were performed using patient computed tomography geometries with ±5 mm systematic or random setup uncertainties applied over a 35 × 2.5Gy(RBE) treatment course. Fifty fractionated courses were simulated for each patient using both IMPT delivery methods with random setup uncertainties applied each fraction and for 3 energy-dependent spot sizes (big spots, σ≈18-9 mm; intermediate spots, σ≈11-5 mm; and small spots, σ≈4-2 mm). These results were compared to Monte Carlo recalculations of the original treatment plan assuming zero setup uncertainty. Results are presented as the difference in equivalent uniform dose (ΔEUD), V95 (ΔV95), and target dose homogeneity (ΔD1-D99). Over the whole patient cohort, the ΔEUD was 2.0 ± 0.5 (big spots), 1.9 ± 0.7 (intermediate spots), and 1.3 ± 0.4 (small spots) times more sensitive to ±5 mm systematic setup uncertainties in IMPTfull compared to IMPT20% IMPTfull is 1.9 ± 0.9 (big spots), 2.1 ± 1.1 (intermediate spots), and 1.5 ± 0.6 (small spots) times more sensitive to random setup uncertainties than IMPT20% over a fractionated treatment course. The ΔV95 is at least 1.4 times more sensitive to systematic and random setup uncertainties for IMPTfull for all spot sizes considered. The ΔD1-D99 values coincided within uncertainty limits for both IMPT delivery methods for the 3 spot sizes considered, with higher mean values always observed for IMPTfull The paired t-test indicated that variations observed between IMPTfull and IMPT20% were significantly different for the majority of scenarios. Significantly larger variations were observed in ΔEUD and ΔV95 in IMPTfull lung treatments in addition to higher mean ΔD1-D99 The steep intra-target dose gradients in IMPTfull make it more susceptible to systematic and random setup uncertainties.

Motion mitigation for lung cancer patients treated with active scanning proton therapy.

PURPOSE: Motion interplay can affect the tumor dose in scanned proton beam therapy. This study assesses the ability of rescanning and gating to mitigate interplay effects during lung treatments. METHODS: The treatments of five lung cancer patients [48 Gy(RBE)/4fx] with varying tumor size (21.1-82.3 cm(3)) and motion amplitude (2.9-30.6 mm) were simulated employing 4D Monte Carlo. The authors investigated two spot sizes (σ ∼ 12 and ∼ 3 mm), three rescanning techniques (layered, volumetric, breath-sampled volumetric) and respiratory gating with a 30% duty cycle. RESULTS: For 4/5 patients, layered rescanning 6/2 times (for the small/large spot size) maintains equivalent uniform dose within the target >98% for a single fraction. Breath sampling the timing of rescanning is ∼ 2 times more effective than the same number of continuous rescans. Volumetric rescanning is sensitive to synchronization effects, which was observed in 3/5 patients, though not for layered rescanning. For the large spot size, rescanning compared favorably with gating in terms of time requirements, i.e., 2x-rescanning is on average a factor ∼ 2.6 faster than gating for this scenario. For the small spot size however, 6x-rescanning takes on average 65% longer compared to gating. Rescanning has no effect on normal lung V20 and mean lung dose (MLD), though it reduces the maximum lung dose by on average 6.9 ± 2.4/16.7 ± 12.2 Gy(RBE) for the large and small spot sizes, respectively. Gating leads to a similar reduction in maximum dose and additionally reduces V20 and MLD. Breath-sampled rescanning is most successful in reducing the maximum dose to the normal lung. CONCLUSIONS: Both rescanning (2-6 times, depending on the beam size) as well as gating was able to mitigate interplay effects in the target for 4/5 patients studied. Layered rescanning is superior to volumetric rescanning, as the latter suffers from synchronization effects in 3/5 patients studied. Gating minimizes the irradiated volume of normal lung more efficiently, while breath-sampled rescanning is superior in reducing maximum doses to organs at risk.

Validation of a GPU-based Monte Carlo code (gPMC) for proton radiation therapy: clinical cases study.

Monte Carlo (MC) methods are recognized as the gold-standard for dose calculation, however they have not replaced analytical methods up to now due to their lengthy calculation times. GPU-based applications allow MC dose calculations to be performed on time scales comparable to conventional analytical algorithms. This study focuses on validating our GPU-based MC code for proton dose calculation (gPMC) using an experimentally validated multi-purpose MC code (TOPAS) and compare their performance for clinical patient cases. Clinical cases from five treatment sites were selected covering the full range from very homogeneous patient geometries (liver) to patients with high geometrical complexity (air cavities and density heterogeneities in head-and-neck and lung patients) and from short beam range (breast) to large beam range (prostate). Both gPMC and TOPAS were used to calculate 3D dose distributions for all patients. Comparisons were performed based on target coverage indices (mean dose, V95, D98, D50, D02) and gamma index distributions. Dosimetric indices differed less than 2% between TOPAS and gPMC dose distributions for most cases. Gamma index analysis with 1%/1 mm criterion resulted in a passing rate of more than 94% of all patient voxels receiving more than 10% of the mean target dose, for all patients except for prostate cases. Although clinically insignificant, gPMC resulted in systematic underestimation of target dose for prostate cases by 1-2% compared to TOPAS. Correspondingly the gamma index analysis with 1%/1 mm criterion failed for most beams for this site, while for 2%/1 mm criterion passing rates of more than 94.6% of all patient voxels were observed. For the same initial number of simulated particles, calculation time for a single beam for a typical head and neck patient plan decreased from 4 CPU hours per million particles (2.8-2.9 GHz Intel X5600) for TOPAS to 2.4 s per million particles (NVIDIA TESLA C2075) for gPMC. Excellent agreement was demonstrated between our fast GPU-based MC code (gPMC) and a previously extensively validated multi-purpose MC code (TOPAS) for a comprehensive set of clinical patient cases. This shows that MC dose calculations in proton therapy can be performed on time scales comparable to analytical algorithms with accuracy comparable to state-of-the-art CPU-based MC codes.

Quantification of proton dose calculation accuracy in the lung.

PURPOSE: To quantify the accuracy of a clinical proton treatment planning system (TPS) as well as Monte Carlo (MC)-based dose calculation through measurements and to assess the clinical impact in a cohort of patients with tumors located in the lung. METHODS AND MATERIALS: A lung phantom and ion chamber array were used to measure the dose to a plane through a tumor embedded in the lung, and to determine the distal fall-off of the proton beam. Results were compared with TPS and MC calculations. Dose distributions in 19 patients (54 fields total) were simulated using MC and compared to the TPS algorithm. RESULTS: MC increased dose calculation accuracy in lung tissue compared with the TPS and reproduced dose measurements in the target to within ±2%. The average difference between measured and predicted dose in a plane through the center of the target was 5.6% for the TPS and 1.6% for MC. MC recalculations in patients showed a mean dose to the clinical target volume on average 3.4% lower than the TPS, exceeding 5% for small fields. For large tumors, MC also predicted consistently higher V5 and V10 to the normal lung, because of a wider lateral penumbra, which was also observed experimentally. Critical structures located distal to the target could show large deviations, although this effect was highly patient specific. Range measurements showed that MC can reduce range uncertainty by a factor of ~2: the average (maximum) difference to the measured range was 3.9 mm (7.5 mm) for MC and 7 mm (17 mm) for the TPS in lung tissue. CONCLUSION: Integration of Monte Carlo dose calculation techniques into the clinic would improve treatment quality in proton therapy for lung cancer by avoiding systematic overestimation of target dose and underestimation of dose to normal lung. In addition, the ability to confidently reduce range margins would benefit all patients by potentially lowering toxicity.

Four-dimensional Monte Carlo simulations demonstrating how the extent of intensity-modulation impacts motion effects in proton therapy lung treatments.

PURPOSE: To compare motion effects in intensity modulated proton therapy (IMPT) lung treatments with different levels of intensity modulation. METHODS: Spot scanning IMPT treatment plans were generated for ten lung cancer patients for 2.5Gy(RBE) and 12Gy(RBE) fractions and two distinct energy-dependent spot sizes (σ ∼8-17 mm and ∼2-4 mm). IMPT plans were generated with the target homogeneity of each individual field restricted to <20% (IMPT20%). These plans were compared to full IMPT (IMPTfull), which had no restriction on the single field homogeneity. 4D Monte Carlo simulations were performed upon the patient 4DCT geometry, including deformable image registration and incorporating the detailed timing structure of the proton delivery system. Motion effects were quantified via comparison of the results of the 4D simulations (4D-IMPT20%, 4D-IMPTfull) with those of a 3D Monte Carlo simulation (3D-IMPT20%, 3D-IMPTfull) upon the planning CT using the equivalent uniform dose (EUD), V95 and D1-D99. The effects in normal lung were quantified using mean lung dose (MLD) and V90%. RESULTS: For 2.5Gy(RBE), the mean EUD for the large spot size is 99.9% ± 2.8% for 4D-IMPT20% compared to 100.1% ± 2.9% for 4D-IMPTfull. The corresponding values are 88.6% ± 8.7% (4D-IMPT20%) and 91.0% ± 9.3% (4D-IMPTfull) for the smaller spot size. The EUD value is higher in 69.7% of the considered deliveries for 4D-IMPTfull. The V95 is also higher in 74.7% of the plans for 4D-IMPTfull, implying that IMPTfull plans experience less underdose compared to IMPT20%. However, the target dose homogeneity is improved in the majority (67.8%) of plans for 4D-IMPT20%. The higher EUD and V95 suggests that the degraded homogeneity in IMPTfull is actually due to the introduction of hot spots in the target volume, perhaps resulting from the sharper in-target dose gradients. The greatest variations between the IMPT20% and IMPTfull deliveries are observed for patients with the largest motion amplitudes. These patients would likely be treated using gating or another motion mitigation technique, which was not the focus of this study. CONCLUSIONS: For the treatment parameters considered in this study, the differences between IMPTfull and IMPT20% are only likely to be clinically significant for patients with large (>20 mm) motion amplitudes.

Motion interplay as a function of patient parameters and spot size in spot scanning proton therapy for lung cancer.

PURPOSE: To quantify the impact of respiratory motion on the treatment of lung tumors with spot scanning proton therapy. METHODS AND MATERIALS: Four-dimensional Monte Carlo simulations were used to assess the interplay effect, which results from relative motion of the tumor and the proton beam, on the dose distribution in the patient. Ten patients with varying tumor sizes (2.6-82.3 cc) and motion amplitudes (3-30 mm) were included in the study. We investigated the impact of the spot size, which varies between proton facilities, and studied single fractions and conventionally fractionated treatments. The following metrics were used in the analysis: minimum/maximum/mean dose, target dose homogeneity, and 2-year local control rate (2y-LC). RESULTS: Respiratory motion reduces the target dose homogeneity, with the largest effects observed for the highest motion amplitudes. Smaller spot sizes (σ ≈ 3 mm) are inherently more sensitive to motion, decreasing target dose homogeneity on average by a factor 2.8 compared with a larger spot size (σ ≈ 13 mm). Using a smaller spot size to treat a tumor with 30-mm motion amplitude reduces the minimum dose to 44.7% of the prescribed dose, decreasing modeled 2y-LC from 87.0% to 2.7%, assuming a single fraction. Conventional fractionation partly mitigates this reduction, yielding a 2y-LC of 71.6%. For the large spot size, conventional fractionation increases target dose homogeneity and prevents a deterioration of 2y-LC for all patients. No correlation with tumor volume is observed. The effect on the normal lung dose distribution is minimal: observed changes in mean lung dose and lung V20 are <0.6 Gy(RBE) and <1.7%, respectively. CONCLUSIONS: For the patients in this study, 2y-LC could be preserved in the presence of interplay using a large spot size and conventional fractionation. For treatments using smaller spot sizes and/or in the delivery of single fractions, interplay effects can lead to significant deterioration of the dose distribution and lower 2y-LC.

Monte Carlo study of the potential reduction in out-of-field dose using a patient-specific aperture in pencil beam scanning proton therapy.

This study is aimed at identifying the potential benefits of using a patient-specific aperture in proton beam scanning. For this purpose, an accurate Monte Carlo model of the pencil beam scanning (PBS) proton therapy (PT) treatment head at Massachusetts General Hospital (MGH) was developed based on an existing model of the passive double-scattering (DS) system. The Monte Carlo code specifies the treatment head at MGH with sub-millimeter accuracy. The code was configured based on the results of experimental measurements performed at MGH. This model was then used to compare out-of-field doses in simulated DS treatments and PBS treatments. For the conditions explored, the penumbra in PBS is wider than in DS, leading to higher absorbed doses and equivalent doses adjacent to the primary field edge. For lateral distances greater than 10 cm from the field edge, the doses in PBS appear to be lower than those observed for DS. We found that placing a patient-specific aperture at nozzle exit during PBS treatments can potentially reduce doses lateral to the primary radiation field by over an order of magnitude. In conclusion, using a patient-specific aperture has the potential to further improve the normal tissue sparing capabilities of PBS.

Tissue equivalency of phantom materials for neutron dosimetry in proton therapy.

PURPOSE: Previous Monte Carlo and experimental studies involving secondary neutrons in proton therapy have employed a number of phantom materials that are designed to represent human tissue. In this study, the authors determined the suitability of common phantom materials for dosimetry of secondary neutrons, specifically for pediatric and intracranial proton therapy treatments. METHODS: This was achieved through comparison of the absorbed dose and dose equivalent from neutrons generated within the phantom materials and various ICRP tissues. The phantom materials chosen for comparison were Lucite, liquid water, solid water, and A150 tissue equivalent plastic, These phantom materials were compared to brain, muscle, and adipose tissues. RESULTS: The magnitude of the doses observed were smaller than those reported in previous experimental and Monte Carlo studies, which incorporated neutrons generated in the treatment head. The results show that for both neutron absorbed dose and dose equivalent, no single phantom material gives agreement with tissue within 5% at all the points considered. Solid water gave the smallest mean variation with the tissues out of field where neutrons are the primary contributor to the total dose. CONCLUSIONS: Of the phantom materials considered, solid water shows best agreement with tissues out of field.