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Purpose: The need for four-dimensional (4D) treatment planning becomes indispensable when it comes to radiation therapy for moving tumors in the thoracic and abdominal regions. The primary purpose of this study is to combine the actual breathing trace during each individual treatment fraction with the Linac's log file information and Monte Carlo 4D dose calculations. We investigated this workflow on multiple computed tomography (CT) datasets in a clinical environment for stereotactic body radiation therapy (SBRT) treatment planning., Methods: We have developed a workflow, which allows us to recalculate absorbed dose to a 4DCT dataset using Monte Carlo calculation methods and accumulate all 4D doses in order to compare them to the planned dose using the Linac's log file, a 4DCT dataset, and the patient's actual breathing curve for each individual fraction. For five lung patients, three-dimensional-conformal radiation therapy (3D-CRT) and volumetric modulated arc treatment (VMAT) treatment plans were generated on four different CT image datasets: a native free-breathing 3DCT, an average intensity projection (AIP) and a maximum intensity projection (MIP) CT both obtained from a 4DCT, and a 3DCT with density overrides based on the 3DCT (DO). The Monte Carlo 4D dose has been calculated on each 4DCT phase using the Linac's log file and the patient's breathing trace as a surrogate for tumor motion and dose was accumulated to the gross tumor volume (GTV) at the 50% breathing phase (end of exhale) using deformable image registration., Results: Δ D 98 % and Δ D 2 % between 4D dose and planned dose differed largely for 3DCT-based planning and also for DO in three patients. Least dose differences between planned and recalculated dose have been found for AIP and MIP treatment planning which both tend to be superior to DO, but the results indicate a dependency on the breathing variability, tumor motion, and size. An interplay effect has not been observed in the small patient cohort., Conclusions: We have developed a workflow which, to our best knowledge, is the first incorporation of the patient breathing trace over the course of all individual treatment fractions with the Linac's log file information and 4D Monte Carlo recalculations of the actual treated dose. Due to the small patient cohort, no clear recommendation on which CT can be used for SBRT treatment planning can be given, but the developed workflow, after adaption for clinical use, could be used to enhance a priori 4D Monte Carlo treatment planning in the future and help with the decision on which CT dataset treatment planning should be carried out., (© 2019 American Association of Physicists in Medicine.)

Background: The purpose of the present study is to compare finite size pencil beam (fsPB) and Monte Carlo (MC) based optimization of lung intensity-modulated stereotactic radiotherapy (lung IMSRT)., Materials and Methods: A fsPB and a MC algorithm as implemented in a biological IMRT planning system were validated by film measurements in a static lung phantom. Then, they were applied for static lung IMSRT planning based on three different geometrical patient models (one phase static CT, density overwrite one phase static CT, average CT) of the same patient. Both 6 and 15 MV beam energies were used. The resulting treatment plans were compared by how well they fulfilled the prescribed optimization constraints both for the dose distributions calculated on the static patient models and for the accumulated dose, recalculated with MC on each of 8 CTs of a 4DCT set., Results: In the phantom measurements, the MC dose engine showed discrepancies < 2%, while the fsPB dose engine showed discrepancies of up to 8% in the presence of lateral electron disequilibrium in the target. In the patient plan optimization, this translates into violations of organ at risk constraints and unpredictable target doses for the fsPB optimized plans. For the 4D MC recalculated dose distribution, MC optimized plans always underestimate the target doses, but the organ at risk doses were comparable. The results depend on the static patient model, and the smallest discrepancy was found for the MC optimized plan on the density overwrite one phase static CT model., Conclusions: It is feasible to employ the MC dose engine for optimization of lung IMSRT and the plans are superior to fsPB. Use of static patient models introduces a bias in the MC dose distribution compared to the 4D MC recalculated dose, but this bias is predictable and therefore MC based optimization on static patient models is considered safe.

Purpose: To report on the commissioning and clinical validation of the first commercially available independent Monte Carlo (MC) three‐dimensional (3D) dose calculation for CyberKnife robotic radiosurgery system® (Accuray, Sunnyvale, CA). Methods: The independent dose calculation (IDC) by SciMoCa® (Scientific RT, Munich, Germany) was validated based on water measurements of output factors and dose profiles (unshielded diode, field‐size dependent corrections). A set of 84 patient‐specific quality assurance (QA) measurements for multi‐leaf collimator (MLC) plans, using an Octavius two‐dimensional SRS1000 array (PTW, Freiburg, Germany), was compared to results of respective calculations. Statistical process control (SPC) was used to detect plans outside action levels. Results: Of all output factors for the three collimator systems of the CyberKnife, 99% agreed within 2% and 81% within 1%, with a maximum deviation of 3.2% for a 5‐mm fixed cone. The profiles were compared using a one‐dimensional gamma evaluation with 2% dose difference and 0.5 mm distance‐to‐agreement (Γ(2,0.5)). The off‐centre ratios showed an average pass rate >99% (92–100%). The agreement of the depth dose profiles depended on field size, with lowest pass rates for the smallest MLC field sizes. The average depth dose pass rate was 88% (35–99%). The IDCs showed a Γ(2,1) pass rate of 98%. Statistical process control detected six plans outside tolerance levels in the measurements, all of which could be attributed the measurement setup. Independent dose calculations showed problems in five plans, all due to differences in the algorithm between TPS and IDC. Based on these results changes were made in the class solution for treatment plans. Conclusion: The first commercially available MC 3D dose IDC was successfully commissioned and validated for the CyberKnife and replaced all routine patient‐specific QA measurements in our clinic. [ABSTRACT FROM AUTHOR]

Purpose: The two distinct dose computation paradigms of Boltzmann equation solvers and Monte Carlo simulation both promise in principle maximum accuracy. In practice, clinically acceptable calculation times demand approximations and numerical short‐cuts on one hand, and modeling the beam characteristics of a real linear accelerator to the required accuracy on the other. A thorough benchmark of both algorithm types therefore needs to start with beam modeling, and needs to include a number of clinically challenging treatment plans. Methods: The Acuros XB (v 13.7, Varian Medical Systems) and SciMoCa (v 1.0, Scientific RT) algorithms were commissioned for the same Varian Clinac accelerator for beam qualities 6 and 15 MV. Beam models were established with water phantom measurements and MLC calibration protocols. In total, 25 patients of five case classes (lung/three‐dimensional (3D) conformal, lung/IMRT, head and neck/VMAT, cervix/IMRT, and rectum/VMAT) were randomly selected from the clinical database and computed with both algorithms. Statistics of 3D gamma analysis for various dose/distance‐to‐agreement (DTA) criteria and differences in selected DVH parameters were analyzed. Results: The percentage of points fulfilling a gamma evaluation was scored as the gamma agreement index (GAI), denoted as G(ΔD, DTA). G(3,3), G(2,2), and G(1,1) were evaluated for the full body, PTV, and selected organs at risk (OARs). For all patients, G(3,3) ≥ 99.9% and G(2,2) > 97% for the body. G(1,1) varied among the patients. However, for all patients, G(1,1) > 70% and G(1,1) > 80% for 68% of the patients. For each patient, the mean dose deviation was ΔD < 1% for the body, PTV, and all evaluated OARs, respectively. In dense bone and at off‐axis distance > 10 cm, the Acuros algorithm yielded slightly higher doses. In the first layer of voxels of the patient surface, the calculated doses deviated between the algorithms. However, at the second voxel, good agreement was observed. The differences in D(98%PTV) were <1.9% between the two algorithms and for 76% of the patients, deviations were below 1%. Conclusions: Overall, an outstanding agreement was found between the Boltzmann equation solver and Monte Carlo. High‐accuracy dose computation algorithms have matured to a level that their differences are below common experimental detection thresholds for clinical treatment plans. Aside from residual differences which could be traced back to implementation details and fundamental cross‐section data, both algorithms arrive at identical dose distributions. [ABSTRACT FROM AUTHOR]

Background: The use of high accuracy dose calculation algorithms, such as Monte Carlo (MC) and Collapsed Cone (CC) determine dose in inhomogeneous tissue more accurately than pencil beam (PB) algorithms. However, prescription protocols based on clinical experience with PB are often used for treatment plans calculated with CC. This may lead to treatment plans with changes in field size (FS) and changes in dose to organs at risk (OAR), especially for small tumor volumes in lung tissue treated with SABR. Methods: We re-evaluated 17 3D-conformal treatment plans for small intrapulmonary lesions with a prescription of 60 Gy in fractions of 7.5 Gy to the 80% isodose. All treatment plans were initially calculated in Oncentra MasterPlan® using a PB algorithm and recalculated with CC (CCre-calc). Furthermore, a CC-based plan with coverage similar to the PB plan (CCcov) and a CC plan with relaxed coverage criteria (CCclin), were created. The plans were analyzed in terms of Dmean, Dmin, Dmax and coverage for GTV, PTV and ITV. Changes in mean lung dose (MLD), V10Gy and V20Gy were evaluated for the lungs. The re-planned CC plans were compared to the original PB plans regarding changes in total monitor units (MU) and average FS. Results: When PB plans were recalculated with CC, the average V60Gy of GTV, ITV and PTV decreased by 13.2%, 19.9% and 41.4%, respectively. Average Dmean decreased by 9% (GTV), 11.6% (ITV) and 14.2% (PTV). Dmin decreased by 18.5% (GTV), 21.3% (ITV) and 17.5% (PTV). Dmax declined by 7.5%. PTV coverage correlated with PTV volume (p < 0.001). MLD, V10Gy, and V20Gy were significantly reduced in the CC plans. Both, CCcov and CCclin had significantly increased MUs and FS compared to PB. Conclusions: Recalculation of PB plans for small lung lesions with CC showed a strong decline in dose and coverage in GTV, ITV and PTV, and declined dose in the lung. Thus, switching from a PB algorithm to CC, while aiming to obtain similar target coverage, can be associated with application of more MU and extension of radiotherapy fields, causing greater OAR exposition. [ABSTRACT FROM AUTHOR]

Purpose: Intensity-modulated radiotherapy with photons (IMRT) and protons (IMPT) produces dose distributions that have high conformality to the planning target volume and sufficient sparing of the organs at risk if calculated on a single static computed tomography (CT) scan. For prostate cancer patients, organ movement with related changes to the density distribution in the irradiated volume occurs during the treatment course. We evaluated the sensitivity of IMPT and IMRT plans to organ movement. Methods and Materials: IMPT and IMRT treatment plans were evaluated for 4 patients with an average of 16 CT data sets per patient. The treatment plans were recalculated on all treatment CT scans, and the dose was accumulated in the reference geometry using a deformable registration algorithm. Accurate dose calculation methods were applied for both IMPT and IMRT. Results: With IMPT, unacceptably low total doses in the gross tumor volume were observed for patients with gas in the rectum on the planning CT scan. To achieve a total equivalent uniform dose (EUD) and EUD spread similar to that with IMRT, two methods were crucial for IMPT—a rectal gas water-equivalent density overwrite in the original planning CT scan and initial beam weight setting to achieve a homogeneous dose distribution for the whole planning target volume for each field separately. An improvement in the total EUD for the prostate and rectal wall was also observed for IMRT with the water-equivalent density overwrite of the rectal cavities. Conclusion: The sensitivities of IMPT and IMRT to organ movement are of the same order if appropriate planning strategies are applied. The latter is especially crucial for IMPT. [Copyright &y& Elsevier]

Purpose: To present the implementation of a probability-based, four-dimensional (4D) intensity-modulated radiotherapy (IMRT) planning approach that explicitly optimizes the accumulated dose to moving tissue, estimated using the patient''s probability density function (pdf) of respiratory motion. This is termed “optimization in tissue''s-eye-view”. Methods and Materials: The method incorporates 4D Monte Carlo dose calculation in multiple geometries of a respiratory-correlated CT dataset. The instance doses are weighted according to the breathing pdf and accumulated in a common reference geometry, which involves dose warping based on deformable registration. The algorithm produces deliverable multileaf collimator segments and was tested on a sample lung cancer patient dataset with large target excursion. Accumulated doses of the moving target and organs at risk of this plan were compared with those of corresponding margin-based static IMRT plans for free-breathing and gated treatment, as well as target tracking. Results: Target tracking provided best target coverage. Both the presented 4D IMRT approach for free-breathing treatment and gated treatment gave similar results for target coverage and lung dose, with significantly better target coverage than the margin-based static IMRT plan for free-breathing treatment. Conclusions: The presented 4D planning concept offers an alternative to gating by providing the optimal dose for free-breathing IMRT treatment. Although the focus of this study was 4D lung planning, the approach can be generally applied for IMRT optimization in randomly deforming patient models. [Copyright &y& Elsevier]