Prediction of GTV median dose differences eases Monte Carlo re-prescription in lung SBRT (original) (raw)
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A clinical study of MLC-based IMRT lung dose calculation accuracy on plan evaluation parameters
Journal of Cancer Science and Therapy, 2010
Intensity Modulated Radiation Therapy (IMRT) is widely accepted as an appropriate method to treat tumors at many different anatomic locations including lung. Dose calculation algorithms that have different degrees of accuracy are used to produce clinical IMRT treatment plans. In this study, Monte Carlo (MC) dose calculation was used to evaluate the reliability of plan evaluation parameters compared to a pencil beam (PB) dose calculation for IMRT of the lung.Twenty fi ve lung IMRT cases were randomly selected for analysis. Plan evaluation parameters were calculated using PB and MC methods for the targets and organs at risk (OARs). Comparisons were made using dose-volume histograms, mean dose, and equivalent uniform dose. The following doses-volume histogram points were compared: D 98 , D 95 of the GTV and PTV, V 20 and V 30 for the lungs, D 33 for the heart and esophagus and D max for the spinal cord. Mean dose differences were 3.6 ± 2.3% and 4.3 ± 2.8% for the GTV and PTV, respectively. The average EUD differences were 4.1 ± 2.4% for the GTV and 5.7 ± 4.9% for the PTV. Less than 2% differences were observed between the MC and PB algorithms for all OAR plan evaluation parameters. However, minimum and maximum differences for some plan evaluation parameters ranged from about ±20%.There are appreciable differences in plan evaluation parameters between the PB and MC calculations for the targets. The mean dose and EUD have a weak but statistically signifi cant inverse dependence on the number of fi elds, total MU, GTV volume and PTV volume for the targets. There can be large case-to-case differences between PB and MC for both the targets and OARs. Accurate MC calculations can remove those remaining systematic errors from treatment plans compared to PB calculations.
Investigation of Dose Calculation Accuracy in VMAT Planning for SBRT Lung Treatment
International Journal of Radiation Oncology*Biology*Physics, 2010
Purpose: Choosing an appropriate parameter on the computerized treatment planning systems (TPSs) influences on the accuracy of dose calculation. Several dosimetric parameters have been studied to achieve a more accurate dose and qualitative plan. The purpose of this study was to determine the impact of maximum control point on the dose calculation on Eclipse TPSs for lung Stereotactic Body Radiation Therapy (SBRT) considering the plan quality, the computation time and the treatment file size. Methods: Dose distributions for the 8 lung SBRT plans with varying maximum control point of 64, 166, and 320 were calculated by Eclipse TPSs with flattening filter free (FFF) beam. The treatment dose was prescribed at 85% isodose level of 54 Gy to the planning target volume (PTV). The dosimetric impact can be evaluated from target coverage, conformity index (CI), homogeneity index (HI), and organ at risk (OAR) doses, while the computation time and the file storage space were compared with the recommended number of control point. Results: The use of 64 control points per subfields tended to increase the dose at PTV and OARs comparing with the 166 and 320 control point plans, while the HI and CI values were similar. The average increases of OARs doses including the spinal cord, heart, esophagus and total lung depended on the photon beam energy. The higher average control point (AVG) number leaded to increase the computation time and the file size for both 6X-FFF and 10X-FFF photon beams. The correlations between AVG and plan storage space were observed in the same ratio as the computation time. Conclusion: Using the minimal number of control point, the quantitative analysis in the PTV and OARs showed no clinically significant variation in dose, therefore choosing an optimal number of fixed control points leaded to balance the plan quality, the computation time and the file size.
Physics in Medicine and Biology, 2005
In this study, we show that beam model differences play an important role in the comparison of dose calculated with various algorithms for lung cancer treatment planning. These differences may impact the accurate correlation of dose with clinical outcome. To accomplish this, we modified the beam model penumbral parameters in an equivalent path length (EPL) algorithm and subsequently compared the EPL doses with those generated with Monte Carlo (MC). A single AP beam was used for beam fitting. Two different beam models were generated for EPL calculations: (1) initial beam model (init fit) and (2) optimized beam model (best fit), with parameters optimized to produce the best agreement with MC calculated profiles at several depths in a water phantom. For the 6 MV, AP beam, EPL(init fit) calculations were on average within 2%/2 mm (1.4 mm max.) agreement with MC; the agreement for EPL(best fit) was 2%/0.5 mm (1.0 mm max.). For the 15 MV, AP beam, average agreements with MC were 5%/2 mm (7.4%/2.6 mm max.) for EPL(init fit) and 2%/1.0 mm (1.3 mm max.) for EPL(best fit). Treatment planning was performed using a realistic lung phantom using 6 and 15 MV photons. In all homogeneous phantom plans, EPL(best fit) calculations were in better agreement with MC. In the heterogeneous 6 MV plan, differences between EPL(best fit and init fit) and MC were significant for the tumour. The EPL(init fit), unlike the EPL(best fit) calculation, showed large differences in the lung relative to MC. For the 15 MV heterogeneous plan, clinically important differences were found between EPL(best fit or init fit) and MC for tumour and lung, suggesting that the algorithmic difference in inhomogeneous tissues was most influential in this case. Finally, an example is presented for a 6 MV conformal clinical treatment plan. In both homogeneous and heterogeneous cases, differences between EPL(best fit) and MC for lung tissues were smaller compared to those between EPL(init fit) and MC. Although the extent to 0031-9155/05/050801+15$30.00
Radiotherapy and Oncology, 2010
Purpose: To provide a prescription dose for Monte Carlo (MC) treatment planning in patients with nonsmall-cell lung cancer according to tumor size and location. Methods: Fifty-three stereotactic radiotherapy plans designed using the equivalent path-length (EPL) algorithm were re-calculated using MC. Plans were compared by the minimum dose to 95% of the PTV (D95), the heterogeneity index (HI) and the mean dose to organs at risk (OARs). Based on changes in D95, the prescription dose was converted from EPL to MC. Based on changes in HI, we examined the feasibility of MC prescription to plans re-calculated but not re-optimized with MC. Results: The MC fraction dose for peripheral tumors is 16-18 Gy depending on tumor size. For central tumors the MC dose was reduced less than for peripheral tumors. The HI decreased on average by 4-9% in peripheral tumors and 3-5% in central tumors. The mean dose to OARs was lower for MC than EPL, and correlated strongly (R 2 = 0.98-0.99). Conclusion: For the conversion from EPL to MC we recommend a separate prescription dose according to tumor size. MC optimization is not required if a HI P 70% is accepted. Dose constraints to OARs can be easily converted due to the high EPL-MC correlation.
Physics in Medicine and Biology, 2006
Dosimetric studies are necessary for all patients treated with targeted radiotherapy. In order to attain the precision required, we have developed Oedipe, a dosimetric tool based on the MCNPX Monte Carlo code. The anatomy of each patient is considered in the form of a voxel-based geometry created using computed tomography (CT) images or magnetic resonance imaging (MRI). Oedipe enables dosimetry studies to be carried out at the voxel scale. Validation of the results obtained by comparison with existing methods is complex because there are multiple sources of variation: calculation methods (different Monte Carlo codes, point kernel), patient representations (model or specific) and geometry definitions (mathematical or voxel-based). In this paper, we validate Oedipe by taking each of these parameters into account independently. Monte Carlo methodology requires long calculation times, particularly in the case of voxel-based geometries, and this is one of the limits of personalized dosimetric methods. However, our results show that the use of voxel-based geometry as opposed to a mathematically defined geometry decreases the calculation time two-fold, due to an optimization of the MCNPX2.5e code. It is therefore possible to envisage the use of Oedipe for personalized dosimetry in the clinical context of targeted radiotherapy.
Calculation of the absorbed dose delivered to a patient during radiotherapy treatment is extremely important and has a direct impact on the treatment outcome. The calculation of the dose to tumour and normal tissues is particularly challenging for lung cancer treatments where large density variations can exist. Previous studies have compared different algorithms used for dose calculation in the treatment planning system (TPS). However, the impact of dose calculation accuracy on treatment outcomes prediction has not been widely studied, especially in regards to lung stereotactic body radiotherapy treatment (SBRT). This research aims to investigate the accuracy of the collapsed cone convolution algorithm employed in the Pinnacle 3 TPS for dose calculation of lung SBRT plans and the potential impact of any dose uncertainties on treatment outcomes prediction. For this purpose, a EGSnrc/BEAMnrc Monte Carlo model of an Elekta Axesse linear accelerator equipped with the Beam Modulator collimation system was developed and commissioned. The commissioned model was used to perform Monte Carlo simulations of the dose distribution of twenty early stage non-small cell lung cancer patient plans. The dosimetric parameters of the planning treatment volume (PTV) and organs at risk (OARs) were evaluated and compared with the TPS calculation. The effects of dose calculation uncertainties to the tumour control probability (TCP) and normal tissue complication probability (NTCP) were modelled using the Linear Quadratic Poisson TCP model and the Lyman-Kutcher-Burman NTCP model. The study found that no significant difference was observed in the PTV dose parameters between the TPS and Monte Carlo calculations. An agreement of ±6% was observed for the PTV coverage of the prescribed isodose, and even greater agreement of ±2% for the coverage of the 90% prescribed isodose. The TPS algorithm tended to overestimate the dose to OARs, with the exception of normal lung tissue, brachial plexus, and pericardium. A significant difference was mostly observed for the maximum point dose parameter. However, most dose parameters to OARs were still below the dose constraints outlined in the RTOG 1021 protocol for both the TPS and Monte Carlo plans. The only significant dose constraint violation was observed for the maximum point dose to the ribs, occurring in plans with a tumour located closest to the chest wall. The radiobiological analysis showed that the TCP parameters were more sensitive to dose calculation uncertainties than NTCP
International Journal of Radiation Oncology*Biology*Physics, 2007
Purpose: To formulate uncertainty-based stopping criteria for Monte Carlo (MC) calculations of intensity-modulated radiotherapy and intensity-modulated arc therapy patient dose distributions and evaluate their influence on MC simulation times and dose characteristics. Methods and Materials: For each structure of interest, stopping criteria were formulated as follows: s rel # s rel,tol or Ds rel # D lim s rel,tol within $95% of the voxels, where s rel represents the relative statistical uncertainty on the estimated dose, D. The tolerated uncertainty (s rel,tol ) was 2%. The dose limit (D lim ) equaled the planning target volume (PTV) prescription dose or a dose value related to the organ at risk (OAR) planning constraints. An intensity-modulated radiotherapy-lung, intensity-modulated radiotherapy-ethmoid sinus, and intensity-modulated arc therapy-rectum patient case were studied. The PTV-stopping criteria-based calculations were compared with the PTV+OAR-stopping criteria-based calculations. Results: The MC dose distributions complied with the PTV-stopping criteria after 14% (lung), 21% (ethmoid), and 12% (rectum) of the simulation times of a 100 million histories reference calculation, and increased to 29%, 44%, and 51%, respectively, by the addition of the OAR-stopping criteria. Dose-volume histograms corresponding to the PTV-stopping criteria, PTV+OAR-stopping criteria, and reference dose calculations were indiscernible. The median local dose differences between the PTV-stopping criteria and the reference calculations amounted to 1.4% (lung), 2.1% (ethmoid), and 2.5% (rectum). Conclusions: For the patient cases studied, the MC calculations using PTV-stopping criteria only allowed accurate treatment plan evaluation. The proposed stopping criteria provided a flexible tool to assist MC patient dose calculations. The structures of interest and appropriate values of s rel,tol and D lim should be selected for each patient individually according to the clinical treatment planning goals. Ó 2007 Elsevier Inc.
Commissioning a fast Monte Carlo dose calculation algorithm for lung cancer treatment planning
Journal of Applied Clinical Medical Physics, 2008
A commercial Monte Carlo simulation package, NXEGS 1.12 (NumeriX LLC, New York, NY), was commissioned for photon-beam dose calculations. The same sets of measured data from 6-MV and 18-MV beams were used to commission NXEGS and Pinnacle 6.2b (Philips Medical Systems, Andover, MA). Accuracy and efficiency were compared against the collapsed cone convolution algorithm implemented in Pinnacle 6.2b, together with BEAM simulation (BEAMnrc 2001: National Research Council of Canada, Ottawa, ON). We investigated a number of options in NXEGS: the accuracy of fast Monte Carlo, the re-implementation of EGS4, post-processing technique (dose de-noising algorithm), and dose calculation time. Dose distributions were calculated with NXEGS, Pinnacle, and BEAM in water, lung-slab, and air-cylinder phantoms and in a lung patient plan. We compared the dose distributions calculated by NXEGS, Pinnacle, and BEAM. In a selected region of interest (7725 voxels) in the lung phantom, all but 1 voxel had a gam...