Collapsed Cone Convolution Algorithm Research Articles

Quantified difference of the collapsed cone convolution (CCC) and Monte Carlo (MC) algorithms based on DVH and gamma analysis for cervical cancer radiation therapy

ObjectiveTo quantify the difference between the (collapsed cone convolution) CCC algorithm and the (Monte Carlo) MC algorithm and remind that the planners should pay attention to some possible uncertainties of the two algorithms when employing the two algorithms. MethodsThirty patients’ cervical cancer VMAT plans were designed with a Pinnacle TPS (Philips) and divided equally into two groups: the simple group (SG, target volume was only the PTV) and the complex group (CG, target volume included the PTV and PGTV). The plans from the Pinnacle TPS were transferred to the Monaco TPS (Elekta).The plans’ parameters all remained unchanged, and the dose was recalculated. Gamma passing rates (GPRs) obtained from dose distribution from Pinnacle TPS compared with that from Monaco TPS with SNC software based on three triaxial planes (transverse, sagittal and coronal). GPRs and DVH were used to quantify the difference between the CCC algorithm in pinnacle TPS and the MC algorithm in Monaco TPS. ResultsAmong the statistical dose indexes in DVHs from the Pinnacle and Monaco TPSs, there were 7(7/15) dose indexes difference with statistically significant differences in the SG, and 10(10/18) dose indexes difference with statistically significant differences in the CG. With 3%/3 mm criterion, the most (5/6) GPRs were greater than 95% from the SG and CG. But with 2%/2 mm criterion, the most (5/6) GPRs were less than 90% from the two groups. In addition, we found that GPRs were also related to the selected triaxial planes and the complexity of the plan (GPRs varied with the SG and CG). ConclusionsObvious difference between the CCC and MC algorithms from Pinnacle and Monaco TPS. DVH maybe better than 2D gamma analysis on quantifying difference of the CCC and MC algorithms. Some attention should be paid to the uncertainty of the TPS algorithm, especially when the indicator on the DVH is at the critical point of the threshold value, because the algorithm used may overestimate or underestimate the DVH indicator.

Deep-neural network approaches for predicting 3D dose distribution in intensity-modulated radiotherapy of the brain tumors.

The aim of this study is to reduce treatment planning time by predicting the intensity-modulated radiotherapy 3D dose distribution using deep learning for brain cancer patients. "For this purpose, two different approaches in dose prediction, i.e., first only planning target volume (PTV) and second PTV with organs at risk (OARs) as input of the U-net model, are employed and their results are compared." The data of 99 patients with glioma tumors referred for IMRT treatment were used so that the images of 90 patients were regarded as training datasets and the others were for the test. All patients were manually planned and treated with sixth-field IMRT; the photon energy was 6MV. The treatment plans were done with the Collapsed Cone Convolution algorithm to deliver 60Gy in 30 fractions. The obtained accuracy and similarity for the proposed methods in dose prediction when compared to the clinical dose distributions on test patients according to MSE, dice metric and SSIM for the Only-PTV and PTV-OARs methods are on average (0.05, 0.851, 0.83) and (0.056, 0.842, 0.82) respectively. Also, dose prediction is done in an extremely short time. The same results of the two proposed methods prove that the presence of OARs in addition to PTV does not provide new knowledge to the network and only by defining the PTV and its location in the imaging slices, does the dose distribution become predictable. Therefore, the Only-PTV method by eliminating the process of introducing OARs can reduce the overall designing time of treatment by IMRT in patients with glioma tumors.

Precise dosimetric comparison between GAMOS and the collapsed cone convolution algorithm of 4D DOSE accumulated in lung SBRT treatments

BackgroundIt is widely accepted that Monte Carlo dose calculations offers a higher precision that the commercially available dose calculation algorithms. This advantage may be especially relevant for lung Stereotactic Body Radiation Therapy (SBRT), as this is a precise technique applied to an area of big inhomogeneity. PurposeWe conducted a comparative study to reveal the differences between the doses calculated using the Collapsed Cone Convolution algorithm and the GAMOS/Geant4 Monte Carlo calculation for lung cancer patients treated with Stereotactic Body Radiation Therapy on an Elekta Versa HD linac. MethodsFor this study a set of ten patient treatments carried out at the Clínica Universidad de Navarra was selected. Theanalysis is based on the comparison of several dosimetric quantities for the Gross Tumor Volume (GTV) and several OrgansAt Risk (OARs), and also a gamma index calculation with distance-to-agreement set to 2 mm and dose difference to 3%, as recommended by ICRU to assess clinical impact. In order to guarantee a small uncertainty in the Monte Carlo calculation of the dosimetric quantities, we studied in detail the validity of different methods that may be used to determine this uncertainty.To compensate for lung movements, a 4D-Cone-beam Computed Tomography (CBCT) was acquired before treatment, whichallowed us to identify eight respiratory phases using a temporal binning. Using commercial MIM software®, we performed a deformable image registration between the eight CT respiration phases to construct the 4D doses. The same procedure was applied for the Treatment Planning System (TPS) dose files and for the Monte Carlo dose files. ResultsThe differences between the two algorithms reveal the known weaknesses of the Collapsed Cone Convolution (CCC) algorithm for the calculation of lateral doses and in regions of large density change. The comparison between the two algorithms for individual phase doses shows differences up to 5% of the GTV D95 or 3–4 Gy in some OARs, which may have a clinical impact. Nevertheless these differences are reduced for the 4D dose in most quantities under study. ConclusionsComparing the dose calculated with a Collapsed Cone Convolution algorithm with GAMOS/Geant4 for ten patients and eight respiratory phases, we found some differences that could have a clinical impact. When combining the eight temporal phases into a 4D dose using the MIM Deformable Image Registration software, the differences diminished substantially.Our statistical analysis concludes that dose uncertainty in the voxels with a maximum dose below a given percentage guarantees uncertainty in the dosimetric quantities below that figure.

A polar-coordinate-based pencil beam algorithm for VMAT dose computation with high-resolution gantry angle sampling.

Most commercially available treatment planning systems (TPSs) approximate the continuous delivery of volumetric modulated arc therapy (VMAT) plans with a series of discretized static beams for treatment planning, which can make VMAT dose computation extremely inefficient. In this study, we developed a polar-coordinate-based pencil beam (PB) algorithm for efficient VMAT dose computation with high-resolution gantry angle sampling that can improve the computational efficiency and reduce the dose discrepancy due to the angular under-sampling effect. 6 MV pencil beams were simulated on a uniform cylindrical phantom under an EGSnrc Monte Carlo (MC) environment. The MC-generated PB kernels were collected in the polar coordinate system for each bixel on a fluence map and subsequently fitted via a series of Gaussians. The fluence was calculated using a detectors' eye view with off-axis and MLC transmission factors corrected. Doses of VMAT arc on the phantom were computed by summing the convolution results between the corresponding PB kernels and fluence for each bixel in the polar coordinate system. The convolution was performed using fast Fourier transform to expedite the computing speed. The calculated doses were converted to the Cartesian coordinate system and compared with the reference dose computed by a collapsed cone convolution (CCC) algorithm of the TPS. A heterogeneous phantom was created to study the heterogeneity corrections using the proposed algorithm. Ten VMAT arcs were included to evaluate the algorithm performance. Gamma analysis and computation complexity theory were used to measure the dosimetric accuracy and computational efficiency, respectively. The dosimetric comparisons on the homogeneous phantom between the proposed PB algorithm and the CCC algorithm for 10 VMAT arcs demonstrate that the proposed algorithm can achieve a dosimetric accuracy comparable to that of the CCC algorithm with average gamma passing rates of 96% (2%/2mm) and 98% (3%/3mm). In addition, the proposed algorithm can provide better computational efficiency for VMAT dose computation using a PC equipped with a 4-core processor, compared to the CCC algorithm utilizing a dual 10-core server. Moreover, the computation complexity theory reveals that the proposed algorithm has a great advantage with regard to computational efficiency for VMAT dose computation on homogeneous medium, especially when a fine angular sampling rate is applied. This can support a reduction in dose errors from the angular under-sampling effect by using a finer angular sampling rate, while still preserving a practical computing speed. For dose calculation on the heterogeneous phantom, the proposed algorithm with heterogeneity corrections can still offer a reasonable dosimetric accuracy with comparable computational efficiency to that of the CCC algorithm. We proposed a novel polar-coordinate-based pencil beam algorithm for VMAT dose computation that enables a better computational efficiency while maintaining clinically acceptable dosimetric accuracy and reducing dose error caused by the angular under-sampling effect. It also provides a flexible VMAT dose computation structure that allows adjustable sampling rates and direct dose computation in regions of interest, which makes the algorithm potentially useful for clinical applications such as independent dose verification for VMAT patient-specific QA.

Comparing Collapsed Cone Convolution Algorithm With Acuros and Its Implication on NRG Clinical Trials

The Varian Eclipse implementation of the Linear Boltzmann Transport Equation, Acuros XB dose calculation algorithm has the same accuracy as Monte Carlo but is much faster and has already been implemented in many clinics. Like Monte Carlo, Acuros allows the user to report dose to water or dose to medium. The main aim of this study is to compare both Acuros XB dose-to-medium Dm,m and dose-to-water Dw,m algorithms with the widely used Collapsed Cone Convolution (CCC) algorithm and provide some implications on NRG clinical trials.Six lung patients who previously received VMAT-based treatments at our institution were analyzed by recalculating their plans for each one with CCC algorithm (reviewed and approved by our Radiation Oncologists) and with both reporting modes of Acuros XB algorithm. All plans used the same monitor units (MU). For each patient, V100 of planning target volume (PTV) and D98 of gross tumor volume (GTV) in each plan were compared and dose distributions calculated by CCC, Acuros Dw,m and Acuros Dm,m were visually compared as well.Differences between PTV V100 calculated by CCC and Acuros XB Dm,m varies from 13.2% to 0.4% with a mean value of 4.3%, while the differences between PTV V100 calculated by CCC and Acuros XB Dw,m varies from 4.2% to 0.6% with a mean value of 2.2%. The differences between PTV V100 calculated by Acuros XB Dm,m and Acuros XB Dw,m varies from 14.6% to 0.1% with a mean value of 3.9%. When GTV D98 is evaluated, the largest difference between CCC and Acuros XB Dm,m is 4.53% with mean value of 2.43%, while the largest difference between CCC and Acuros XB Dw,m is 4.11% with mean value of 1.77%. For all the cases, GTV D98 calculated by CCC is closer to the ones calculated by Acuros XB Dw,m.The present study shows that the differences in dose calculated by CCC and Acuros Dm,m are larger than the dose differences between CCC and Acuros Dw,m. This difference will cause significant discrepancies if both CCC and Acuros Dm,m are used in clinical trials. This study indicates that Acuros Dw,m should be used to be consistent with CCC, however, this contradicts current recommendations in literature. Hence, further investigation and clarification are needed about which dose reporting mode should be used.

محاسبه دز جذبی در ماده معادل بافت ریه و مقایسه آن با پیشبینی برنامه طراحی درمان مبتنی بر الگوریتم پیچش مخروطهای فروریخته

محاسبه دز جذبی در ماده معادل بافت ریه و مقایسه آن با پیشبینی برنامه طراحی درمان مبتنی بر الگوریتم پیچش مخروطهای فروریخته

Dosimetric evaluation of lung treatment plans produced by the Prowess Panther system using Monte Carlo simulation

Purpose: This study evaluated the accuracy of lung dose calculation done by the fast photon effective (FPE) and the collapsed cone convolution (CCC) algorithms of the Prowess Panther treatment planning system (TPS) using Monte Carlo (MC) simulation. Materials and methods: A set of treatment plans of test cases including an acrylic phantom, the QUASAR multi-purpose body phantom, and one lung cancer patient, were created the system to assess the accuracy of the FPE and CCC algorithms. The DICOM-RT files of the plans were imported to the EGSnrc-based Monte Carlo simulation for dose calculations. The plans generated by the TPS and Monte Carlo simulation were compared using relative dose error comparison and 3D gamma index. The gamma index, using global methods, was implemented in PTW-VeriSoft with 3%/3 mm, 2%/2 mm criteria. Results: There was a good agreement between Monte Carlo-simulated and TPS-calculated doses for both the QUASAR multi-purpose body phantom and one lung cancer patient. However, discrepancies for the FPE algorithm were found to be 10% in the inhomogeneous medium such as the lung. Conclusions: The FPE algorithm may not accurately predict the dose distributions in and near the inhomogeneous structures. Monte Carlo simulation and CCC algorithm are more accurate than the FPE algorithm in calculating the dose in an inhomogeneous medium. The FPE and CCC algorithms must be validated before clinical implementation of the system.

Commissioning of the Mobius3D independent dose verification system for TomoTherapy.

In radiation therapy, a secondary independent dose verification is an important component of a quality control system. Mobius3D calculates three‐dimensional (3D) patient dose using reference beam data and a collapsed cone convolution algorithm and analyzes dose‐volume histogram automatically. There are currently no published data on commissioning and determining tolerance levels of Mobius3D for TomoTherapy. To verify the calculation accuracy and adjust the parameters of this system, we compared the measured dose using an ion chamber and film in a phantom with the dose calculated using Mobius3D for nine helical intensity‐modulated radiation therapy plans, each with three nominal field widths. We also compared 126 treatment plans used in our institution to treat prostate, head‐and‐neck, and esophagus tumors based on dose calculations by treatment planning system for given dose indices and 3D gamma passing rates with those produced by Mobius3D. On the basis of these results, we showed that the action and tolerance levels at the average dose for the planning target volume (PTV) at each treatment site are at μ ± 2σ and μ ± 3σ, respectively. After adjusting parameters, the dose difference ratio on average was −0.2 ± 0.6% using ion chamber and gamma passing rate with the criteria of 3% and 3 mm on average was 98.8 ± 1.4% using film. We also established action and tolerance levels for the PTV at the prostate, head‐and‐neck, esophagus, and for the organ at risk at all treatment sites. Mobius3D calculations thus provide an accurate secondary dose verification system that can be commissioned easily and immediately after installation. Before clinical use, the Mobius3D system needs to be commissioned using the treatment plans for patients treated in each institution to determine the calculational accuracy and establish tolerances for each treatment site and dose index.

A Monte Carlo evaluation of dose distribution of commercial treatment planning systems in heterogeneous media.

Calculations from a treatment planning system (TPS) in heterogeneous regions may present significant inaccuracies due to loss of electronic equilibrium. The purpose of this study is to evaluate and quantify the differences of dose distributions computed by some of the newest dose calculation algorithms, including collapsed cone convolution (CCC), fast Fourier transform (FFT) convolution, and superposition convolution, in heterogeneity of the lung. A 6-MV Siemens Primus linear accelerator was simulated by MCNPX Monte Carlo (MC) code, and the results of percentage depth dose (PDD) and dose profile values were compared with measured data. The ISOgray TPS was used and PDDs of CCC, FFT, and superposition convolution algorithms were compared with the results obtained by MCNPX code. CT2MCNP software was used to convert the computed tomography images of the lung tissue to MC input files, and dose distributions from the three algorithms were compared to MC method. For PDD curves in buildup region, the maximum underdosage of ISOgray TPS was at the surface (19%) and comes in closer agreement when depth increases (average 7.08%). Dose differences (DD) between different algorithms and MC were typically 4.81% (range: 1.95% to 7.30%), -1.55% (range: -5.14% to 5.26%) and 4.96% (range: 2.00% to 7.4%) in the lung for the CCC, FFT, and superposition algorithms, respectively. The difference between monitor units and maximum dose calculated using the three algorithms were 0.5% and 1.61%, respectively. The maximum DD of 7% was observed between MC and TPS results. Significant differences were found when the calculation algorithms were compared with MC method in lung tissue, and this difference is not negligible. It is recommended to use of MC-based TPS for the treatment fields including lung tissue.

Evaluation of dose calculation algorithms using different density materials for in-field and out-of-field conditions

The accuracy of the dose calculation is vital in the stereotactic ablative body radiotherapy (SABR) technique to achieve clinically effective dose distribution for better tumor control. Multiple commercial radiotherapy treatment planning systems (TPS) were implemented with different algorithms, such as Acuros XB in Eclipse and Superposition in XiO. The aim of this study is to investigate five different dose calculation algorithms, namely, pencil beam convolution (PBC), Acuros XB, AAA implemented in an Eclipse system, collapsed cone convolution (CCC) algorithm implemented in Mobius3D and superposition algorithms implemented in the XiO system, and then validate the results against measurements using an Institute of Physical Sciences in Medicine (IPSM) phantom with different density materials for in-field and out-of- field conditions. The IPSM phantom was used to investigate the dose calculation algorithm performances in four different densities (water, lung, ribs, and dense bone) using different beam configurations, including small beam fields utilised in lung SABR. Five commercial algorithms implemented in two TPS (Eclipse and XiO) and one plan check(M3D) system were used for in-field and out-of-field measurement. In the in-field condition, the Acuros XB algorithm had lower mean differences than the measured dose by the IC ranging from -0.46 to 0.24for all the densities. In the out-of-field condition, the results of eclipse system: AAA, PBC and Acuros XB algorithms demonstrated underdose point's measurements by -40% for all densities except for AAA calculations in lung density (overdosed by 40%). The measured points of the superposition algorithms were overestimated to the actual dose less than 30% in water, lung and dense bone. At the same densities, the CCC algorithms showed relatively the lowest differences in percentage compared to the superposition algorithms. Our results showed that the Acuros XB and superposition algorithms are closer to the actual measured dose than AAA, PBC and CCC for majority of the field conditions for water-equivalent, lung, rib and dense bone densities. The CCC algorithm resulted in a better agreement with the measurement of the out-of-field points compared with the other algorithms.

Dosimetric and Monte Carlo verification of jaws-only IMRT plans calculated by the Collapsed Cone Convolution algorithm for head and neck cancers.

The aim of this study is to verify the Prowess Panther jaws-only intensity modulated radiation therapy (JO-IMRT) treatment planning (TP) by comparing the TP dose distributions for head-and-neck (H&N) cancer with the ones simulated by Monte Carlo (MC). To date, dose distributions planned using JO-IMRT for H&N patients were found superior to the corresponding three-dimensional conformal radiotherapy (3D-CRT) plans. Dosimetry of the JO-IMRT plans were also experimentally verified using an ionization chamber, MapCHECK 2, and Octavius 4D and good agreements were shown. Dose distributions of 15 JO-IMRT plans of nasopharyngeal patients were recalculated using the EGSnrc Monte Carlo code. The clinical photon beams were simulated using the BEAMnrc. The absorbed dose to patients treated by fixed-field IMRT was computed using the DOSXYZnrc. The simulated dose distributions were then compared with the ones calculated by the Collapsed Cone Convolution (CCC) algorithm on the TPS, using the relative dose error comparison and the gamma index using global methods implemented in PTW-VeriSoft with 3%/3mm, 2%/2mm, 1%/1mm criteria. There is a good agreement between the MC and TPS dose. The average gamma passing rates were 93.3±3.1%, 92.8±3.2%, 92.4±3.4% based on the 3%/3mm, 2%/2mm, 1%/1mm criteria, respectively. According to the results, it is concluded that the CCC algorithm was adequate for most of the IMRT H&N cases where the target was not immediately adjacent to the critical structures.

Evaluation of dose calculation accuracy of treatment planning systems at hip prosthesis interfaces.

There are an increasing number of radiation therapy patients with hip prosthesis. The common method of minimizing treatment planning inaccuracies is to avoid radiation beams to transit through the prosthesis. However, the beams often exit through them, especially when the patient has a double‐prosthesis. Modern treatment planning systems employ algorithms with improved dose calculation accuracies but even these algorithms may not predict the dose accurately at high atomic number interfaces.The current study evaluates the dose calculation accuracy of three common dose calculation algorithms employed in two commercial treatment planning systems. A hip prosthesis was molded inside a cylindrical phantom and the dose at several points within the phantom at the interface with prosthesis was measured using thermoluminescent dosimeters. The measured doses were then compared to the predicted ones by the planning systems.The results of the study indicate all three algorithms underestimate the dose at the prosthesis interface, albeit to varying degrees, and for both low‐ and high‐energy x rays. The measured doses are higher than calculated ones by 5–22% for Pinnacle Collapsed Cone Convolution algorithm, 2–23% for Eclipse Acuros XB, and 6–25% for Eclipse Analytical Anisotropic Algorithm. There are generally better agreements for AXB algorithm and the worst results are for the AAA.

P2.05-051 Safety of Lung Stereotactic Body Radiotherapy (SBRT): A Single Institution Prospective Study Based on RTOG 0915 Protocol Constraints: Topic: Toxicities

To evaluate toxicity of RTOG 0915 protocol’s constraints in lung SBRT for patients treated with 60Gy in 5 fractions. Between 2010 and 2015, 77 pts were treated with SBRT for single or multiple lung lesions, 43 pts (55.8%) for primary tumor and 34 pts (44.2%) for metastatic lesion. A total of 80 lesions were treated. Four dimensional CT images were acquired; maximum intensity CT reconstruction was used for ITV delineation and average CT reconstruction for OAR contouring and dosimetric calculation.We prescribed 57Gy to 95% of PTV volume and OAR constraints are reported in table 1. Dose calculation was performed in 70% of the cases with collapsed cone convolution algorithm and 7 fields 3D technique and the remaining 30% with Monte Carlo dose calculation and intensity modulated fields (dynamic MLC and VMAT tecniques). Treatments were delivered in 28% of the cases on Elekta-Precise accelerator with electronic portal films on-line setup verifications and the remaining 72% on Elekta-Agility accelerator with cone beam CT. We evaluated pre-treatment respiratory function and we treated only pts with %FEV1 > 40%. We reported toxicity following CTCAE v3.0 score. All the dose/constraints were respected except for the chest wall dose that was higher than 30 Gy in 8 pts (10.3%). Toxicity was evaluated in all the patients except one that was lost in follow-up. We found only lung or chest wall toxicity: 11 pts (14.2%) with a G2 dyspnea, one patient with a G3 dyspnea; 8 pts with a G2 chest wall pain and 1 with a symptomatic rib fracture. We find more lung toxicity in patients with primary tumor because of more chronic lung disease prior to the treatment. The use of these SBRT constraints is safe in both metastatic and primary lung lesions, with a particular attention on pre-treatment respiratory function.

Dosimetric comparison of treatment planning systems using collapsed cone convolution and pencil beam algorithms

AbstractPurposeThe aim of this study is the dosimetric verification and comparative analysis of two different treatment planning systems (TPS) using collapsed cone convolution (CCC) and pencil beam (PB) algorithms for treatment sites of head and neck, chest wall–supraclavicular region, lung and prostate.Methods and materialsTarget volumes and critical organs for treatment sites mentioned above were delineated according to relevant The Radiation Therapy Oncology Group protocols. Treatment plans were generated using 6 MV photon energy with medical linear accelerator and Thermoluminescent Dosimeter-100 dosimeters were used to perform dosimetric verification, which were placed at appropriate locations in the Alderson Rando phantom.Results and conclusionsComparative analysis of CCC and PB algorithms for treatment sites revealed that point dose measurement values were higher with the PB algorithm compared with CCC algorithm, in both head and neck and chest wall–supraclavicular region plans. The most significant difference between two algorithms were found at the supraclavicular region which includes the lung point dose within the treatment field and 7–12 mm depth from the skin, respectively. Unlike the head and neck and chest wall–supraclavicular region plans, CCC and PB algorithms show overall comparable results in lung and prostate plans in terms of point dose measurement values; however, the most prominent difference was found in 7 mm and 6 cm depth from skin, respectively. The CCC algorithm values were higher. Our study confirms that the main reason of PB algorithm calculates less absorbed dose than CCC algorithm in medium transitions, skin entrance and irregular treatment regions is the underestimation of lateral equilibrium’s contribution to the total absorbed dose.

Comparison of Dose Distributions With TG-43 and Collapsed Cone Convolution Algorithms Applied to Accelerated Partial Breast Irradiation Patient Plans

Tocompare the treatment plans for accelerated partial breast irradiation calculated by the new commercially available collapsed cone convolution (CCC) and current standard TG-43-based algorithms for 50 patients treated at our institution with either a Strut-Adjusted Volume Implant (SAVI) or Contura device. We recalculated target coverage, volume of highly dosed normal tissue, and dose to organs at risk (ribs, skin, and lung) with each algorithm. For 1 case an artificial air pocket was added to simulate 10% nonconformance. We performed a Wilcoxon signed rank test to determine the median differences in the clinical indices V90, V95, V100, V150, V200, and highest-dosed 0.1cm(3) and 1.0cm(3) of rib, skin, and lung between the two algorithms. The CCC algorithm calculated lower values on average for all dose-volume histogram parameters. Across the entire patient cohort, the median difference in the clinical indices calculated by the 2 algorithms was <10% for dose to organs at risk, <5% for target volume coverage (V90, V95, and V100), and <4cm(3) for dose to normal breast tissue (V150 and V200). No discernable difference was seen in the nonconformance case. We found that on average over our patient population CCC calculated (<10%) lower doses than TG-43. These results should inform clinicians as they prepare for the transition to heterogeneous dose calculation algorithms and determine whether clinical tolerance limits warrant modification.

Comparison of build-up region doses in oblique tangential 6 MV photon beams calculated by AAA and CCC algorithms in breast Rando phantom

The purpose of this study is to compare the build-up region doses on breast Rando phantom surface with the bolus covered, the doses in breast Rando phantom and also the doses in a lung that is the heterogeneous region by two algorithms. The AAA in Eclipse TPS and the collapsed cone convolution algorithm in Pinnacle treatment planning system were used to plan in tangential field technique with 6 MV photon beam at 200 cGy total doses in Breast Rando phantom with bolus covered (5 mm and 10 mm). TLDs were calibrated with Cobalt-60 and used to measure the doses in irradiation process. The results in treatment planning show that the doses in build-up region and the doses in breast phantom were closely matched in both algorithms which are less than 2% differences. However, overestimate of doses in a lung (L2) were found in AAA with 13.78% and 6.06% differences at 5 mm and 10 mm bolus thickness, respectively when compared with CCC algorithm. The TLD measurements show the underestimate in buildup region and in breast phantom but the doses in a lung (L2) were overestimated when compared with the doses in the two plannings at both thicknesses of the bolus.

An in vivo dose verification method for SBRT-VMAT delivery using the EPID.

Radiation treatments have become increasingly more complex with the development of volumetric modulated arc therapy (VMAT) and the use of stereotactic body radiation therapy (SBRT). SBRT involves the delivery of substantially larger doses over fewer fractions than conventional therapy. SBRT-VMAT treatments will strongly benefit from in vivo patient dose verification, as any errors in delivery can be more detrimental to the radiobiology of the patient as compared to conventional therapy. Electronic portal imaging devices (EPIDs) are available on most commercial linear accelerators (Linacs) and their documented use for dosimetry makes them valuable tools for patient dose verification. In this work, the authors customize and validate a physics-based model which utilizes on-treatment EPID images to reconstruct the 3D dose delivered to the patient during SBRT-VMAT delivery. The SBRT Linac head, including jaws, multileaf collimators, and flattening filter, were modeled using Monte Carlo methods and verified with measured data. The simulation provides energy spectrum data that are used by their "forward" model to then accurately predict fluence generated by a SBRT beam at a plane above the patient. This fluence is then transported through the patient and then the dose to the phosphor layer in the EPID is calculated. Their "inverse" model back-projects the EPID measured focal fluence to a plane upstream of the patient and recombines it with the extra-focal fluence predicted by the forward model. This estimate of total delivered fluence is then forward projected onto the patient's density matrix and a collapsed cone convolution algorithm calculates the dose delivered to the patient. The model was tested by reconstructing the dose for two prostate, three lung, and two spine SBRT-VMAT treatment fractions delivered to an anthropomorphic phantom. It was further validated against actual patient data for a lung and spine SBRT-VMAT plan. The results were verified with the treatment planning system (TPS) (ECLIPSE AAA) dose calculation. The SBRT-VMAT reconstruction model performed very well when compared to the TPS. A stringent 2%/2 mm χ-comparison calculation gave pass rates better than 91% for the prostate plans, 88% for the lung plans, and 86% for the spine plans for voxels containing 80% or more of the prescribed dose. Patient data were 86% for the lung and 95% for the spine. A 3%/3 mm χ-comparison was also performed and gave pass rates better than 93% for all plan types. The authors have customized and validated a robust, physics-based model that calculates the delivered dose to a patient for SBRT-VMAT delivery using on-treatment EPID images. The accuracy of the results indicates that this approach is suitable for clinical implementation. Future work will incorporate this model into both offline and real-time clinical adaptive radiotherapy.

Dosimetric Impact of Internal and External Anatomical Changes in Stereotactic Radiosurgery (SRS) of L-Spine Tumors: Beam Configuration Matters

To investigate three treatment planning strategies to minimize the dosimetric variations due to internal and external anatomical changes in stereotactic radiosurgery (SRS) of L-spine tumors. 11 L-spine SRS patients with extensive gas filling in the bowel in the planning CT or pre-treatment cone beam CT were selected for this study. Three coplanar treatment plans were made to deliver 16Gy to 90% of GTV in one fraction using a treatment planning system: 1) Step and shoot IMRT with 9 beams equally distributed around the patient, 2) step and shoot IMRT with 9 posterior beams every 20 degree, and 3) VMAT with 360 degrees full arcs. Dose was calculated with heterogeneity correction and collapsed cone convolution algorithm. Pre-treatment CBCT was registered to the planning CT with the vertebral body as the alignment focus region. For each patient, the external body and bowel gas were contoured on the planning CT and CBCT. To estimate actual delivered dose while considering patient’s anatomy of the treatment day, the following density overrides were performed on the planning CT. To consider external anatomy change, the CBCT external that was outside of the planning CT external were assigned to density one and the CT external outside the CBCT external were assigned to density zero. To consider the internal anatomy change, bowel gas contour in the planning CT was assigned one and the bowel gas contour transferred from the CBCT was assigned to zero. The mean absolute differences (MAD) between planning and estimated delivery in target coverage (V16Gy), maximum dose (0.03cc of volume, D0.03cc) and 12 Gy received by cauda-equina (V12Gy) were evaluated. The MAD of V16Gy for the GTV was 1.8 ± 1.4% (range: 0.2% – 4.9%), 2.4 ± 1.3% (0.1% – 4.9%) and 2.6 ± 1.3% (0.3% – 5.0%) for posterior, uniform and VMAT plans, respectively. The difference was statistically significant for the posterior vs. VMAT plans (p = 0.049) but not significant for the posterior vs. uniform plans (p=0.174). Cauda-equina MAD of V12Gy was 0.9 ± 1.1% (range: 0.1% - 3.9%), 1.2 ± 1.0% (0.1% – 2.7%) and 0.8 ± 0.8% (0% – 1.8%, p=0.024 comparison to uniform) for posterior, uniform and VMAT plans, respectively. The lower cauda-equina MAD of V12Gy for VMAT was because VMAT plans achieved significantly lower V12Gy in the treatment plans (mean: 4.3 ± 1.4%) than posterior (6.7 ± 1.6%) and uniform (6.8 ± 1.6%) plans (p = 0.003). MAD of D0.03cc was 13.1 ± 8.6 cGy (range: 2 – 31 cGy), 19.2 ± 16 cGy (4 – 53 cGy) and 19.3 ± 16 cGy (0 – 59 cGy) for the posterior, uniform and VMAT plans, respectively. The difference was not statistically significant. The posterior plans were less influenced dosimetrically in tumor coverage by variations in abdominal anatomy but were not superior in terms of cauda-equina sparing.

SU‐E‐T‐793: Validation of COMPASS 3D Dosimetry as Pre Treatment Verification with Commercial TPS Algorithms

Purpose:The purpose of this study was to validate the advent of COMPASS 3D dosimetry as a routine pre treatment verification tool with commercially available CMS Monaco and Oncentra Masterplan planning system.Methods:Twenty esophagus patients were selected for this study. All these patients underwent radical VMAT treatment in Elekta Linac and plans were generated in Monaco v5.0 with MonteCarlo(MC) dose calculation algorithm. COMPASS 3D dosimetry comprises an advanced dose calculation algorithm of collapsed cone convolution(CCC). To validate CCC algorithm in COMPASS, The DICOM RT Plans generated using Monaco MC algorithm were transferred to Oncentra Masterplan v4.3 TPS. Only final dose calculations were performed using CCC algorithm with out optimization in Masterplan planning system. It is proven that MC algorithm is an accurate algorithm and obvious that there will be a difference with MC and CCC algorithms. Hence CCC in COMPASS should be validated with other commercially available CCC algorithm. To use the CCC as pretreatment verification tool with reference to MC generated treatment plans, CCC in OMP and CCC in COMPASS were validated using dose volume based indices such as D98, D95 for target volumes and OAR doses.Results:The point doses for open beams were observed &lt;1% with reference to Monaco MC algorithms. Comparisons of CCC(OMP) Vs CCC(COMPASS) showed a mean difference of 1.82%±1.12SD and 1.65%±0.67SD for D98 and D95 respectively for Target coverage. Maximum point dose of −2.15%±0.60SD difference was observed in target volume. The mean lung dose of −2.68%±1.67SD was noticed between OMP and COMPASS. The maximum point doses for spinal cord were −1.82%±0.287SD.Conclusion:In this study, the accuracy of CCC algorithm in COMPASS 3D dosimetry was validated by compared with CCC algorithm in OMP TPS. Dose calculation in COMPASS is feasible within &lt; 2% in comparison with commercially available TPS algorithms.

SU‐E‐T‐220: Computational Accuracy of Adaptive Convolution (AC) and Collapsed Cone Convolution (CCC) Algorithms in the Presence of Air Gaps

Purpose:To compare the percentage depth dose (PDD) computational accuracy of Adaptive Convolution (AC) and Collapsed Cone Convolution (CCC) algorithms in the presence of air gaps.Methods:A 30×30×30 cm3 solid water phantom with two 5cm air gaps was scanned with a CT simulator unit and exported into the Phillips Pinnacle™ treatment planning system. PDDs were computed using the AC and CCC algorithms. Photon energy of 6 MV was used with field sizes of 3×3 cm2, 5×5 cm2, 10×10 cm2, 15×15 cm2, and 20×20 cm2. Ionization chamber readings were taken at different depths in water for all the field sizes. The percentage differences in the PDDs were computed with normalization to the depth of maximum dose (dmax). The calculated PDDs were then compared with measured PDDs.Results:In the first buildup region, both algorithms overpredicted the dose for all field sizes and under‐predicted for all other subsequent buildup regions. After dmax in the three water media, AC under‐predicted the dose for field sizes 3×3 and 5×5 cm2 and overpredicted for larger field sizes, whereas CCC under‐predicted for all field sizes. Upon traversing the first air gap, AC showed maximum differences of –3.9%, −1.4%, 2.0%, 2.5%, 2.9% and CCC had maximum differences of −3.9%, −3.0%,–3.1%, −2.7%, −1.8% for field sizes 3×3, 5×5, 10×10, 15×15, and 20×20 cm2 respectively.Conclusion:The effect of air gaps causes a significant difference in the PDDs computed by both the AC and CCC algorithms in secondary build‐up regions. AC computed larger values for the PDDs except at smaller field sizes. For CCC, the size of the errors in prediction of the PDDs has an inverse relationship with respect to field size. These effects should be considered in treatment planning where significant air gaps are encountered.