Application of Monte Carlo calculations for validation of a treatment planning system in high dose rate brachytherapy

AimThe accuracy of treatment planning systems is of vital importance in treatment outcomes in brachytherapy. In the current study the accuracy of dose calculations of a high dose rate (HDR) brachytherapy treatment planning system (TPS) was validated using the Monte Carlo method.Materials and methodsThree ⁶⁰Co sources of the GZP6 afterloading brachytherapy system were modelled using MCNP4C Monte Carlo (MC) code. The dose distribution around all the sources was calculated by MC and a dedicated treatment planning system. The results of both methods were compared.ResultsThere was good agreement (<2%) between TPS and MC calculated dose distributions except at a point near the sources (<1 cm) and beyond the tip of the sources.ConclusionsOur study confirmed the accuracy of TPS calculated dose distributions for clinical use in HDR brachytherapy.     

A machine learning-based framework for delivery error prediction in proton pencil beam scanning using irradiation log-files

PurposeThis study aims to investigate the use of machine learning models for delivery error prediction in proton pencil beam scanning (PBS) delivery.MethodsA dataset of planned and delivered PBS spot parameters was generated from a set of 20 prostate patient treatments. Planned spot parameters (spot position, MU and energy) were extracted from the treatment planning system (TPS) for each beam. Delivered spot parameters were extracted from irradiation log-files for each beam delivery following treatment. The dataset was used as a training dataset for three machine learning models which were trained to predict delivered spot parameters based on planned parameters. K-fold cross validation was employed for hyper-parameter tuning and model selection where the mean absolute error (MAE) was used as the model evaluation metric. The model with lowest MAE was then selected to generate a predicted dose distribution for a test prostate patient within a commercial TPS.ResultsAnalysis of the spot position delivery error between planned and delivered values resulted in standard deviations of 0.39 mm and 0.44 mm for x and y spot positions respectively. Prediction error standard deviation values of spot positions using the selected model were 0.22 mm and 0.11 mm for x and y spot positions respectively. Finally, a three-way comparison of dose distributions and DVH values for select OARs indicates that the random-forest-predicted dose distribution within the test prostate patient was in closer agreement to the delivered dose distribution than the planned distribution.ConclusionsPBS delivery error can be accurately predicted using machine learning techniques.     

Automatic VMAT technique to treat glioblastoma: A two years’ experience

PurposeThe present work aims to guide the physicist in order to start automated planning for the VMAT treatment of glioblastoma multiforme (GBM) by giving a recipe that was set up and tested during a long-term (two years) evaluation.MethodsAn automatic technique in AutoPlanning module of the Pinnacle3 (Philips Medical Systems, Fitchburg, WI) treatment planning system was created and validated by comparing dose distributions of automatic plans (APs) and manual plans (MPs) and by performing a blind AP-MP comparison on a cohort of 20 patients. Automatic technique was then applied to 145 patients and failures were recorded i.e. the number of times for which dose distributions produced by the automatic module were not suitable for treatment.ResultsEach of the 20 APs considered in the validation step was clinically acceptable and proved to be better (15 cases) or equal (5 cases) respect to MPs. A statistically significant improvement in brain stem, optic pathways, cochleae, pituitary gland and scalp sparing was observed for APs, while no statistically significant differences were recorded in target coverage or plan parameters. For only 5 cases out of the 145 plans the operator intervention was needed in order to obtain a clinical acceptable plan, while for the remaining 140 plans the automatic created solution was suitable.ConclusionsA straightforward automatic procedure has been created and tested in our clinic. The AutoPlanning technique proposed represents a reliable tool to improve treatment planning efficiency and the recipe, here presented, could be simply imported to every radiotherapy center.     

Comparison of individual and composite field analysis using array detector for Intensity Modulated Radiotherapy dose verification

AimTo compare the measured and calculated individual and composite field planar dose distribution of Intensity Modulated Radiotherapy plans.Materials and methodsThe measurements were performed in Clinac DHX linear accelerator with 6 MV photons using Matrixx device and a solid water phantom. The 20 brain tumor patients were selected for this study. The IMRT plan was carried out for all the patients using Eclipse treatment planning system. The verification plan was produced for every original plan using CT scan of Matrixx embedded in the phantom. Every verification field was measured by the Matrixx. The TPS calculated and measured dose distributions were compared for individual and composite fields.Results and discussionThe percentage of gamma pixel match for the dose distribution patterns were evaluated using gamma histogram. The gamma pixel match was 95–98% for 41 fields (39%) and 98% for 59 fields (61%) with individual fields. The percentage of gamma pixel match was 95–98% for 5 patients and 98% for other 12 patients with composite fields. Three patients showed a gamma pixel match of less than 95%. The comparison of percentage gamma pixel match for individual and composite fields showed more than 2.5% variation for 6 patients, more than 1% variation for 4 patients, while the remaining 10 patients showed less than 1% variation.ConclusionThe individual and composite field measurements showed good agreement with TPS calculated dose distribution for the studied patients. The measurement and data analysis for individual fields is a time consuming process, the composite field analysis may be sufficient enough for smaller field dose distribution analysis with array detectors.     

Dose distribution correction for the influence of magnetic field using a deep convolutional neural network for online MR-guided adaptive radiotherapy

PurposeThis study aimed to develop a deep convolutional neural network (CNN)-based dose distribution conversion approach for the correction of the influence of a magnetic field for online MR-guided adaptive radiotherapy.MethodsOur model is based on DenseNet and consists of two 2D input channels and one 2D output channel. These three types of data comprise dose distributions without a magnetic field (uncorrected), electron density (ED) maps, and dose distributions with a magnetic field. These data were generated as follows: both types of dose distributions were created using 15-field IMRT in the same conditions except for the presence or absence of a magnetic field with the GPU Monte Carlo dose in Monaco version 5.4; ED maps were acquired with planning CT images using a clinical CT-to-ED table at our institution. Data for 50 prostate cancer patients were used; 30 patients were allocated for training, 10 for validation, and 10 for testing using 4-fold cross-validation based on rectum gas volume. The accuracy of the model was evaluated by comparing 2D gamma-indexes against the dose distributions in each irradiation field with a magnetic field (true).ResultsThe gamma indexes in the body for CNN-corrected uncorrected dose against the true dose were 94.95% ± 4.69% and 63.19% ± 3.63%, respectively. The gamma indexes with 2%/2-mm criteria were improved by 10% in most test cases (99.36%).ConclusionsOur results suggest that the CNN-based approach can be used to correct the dose-distribution influences with a magnetic field in prostate cancer treatment.     

Evaluation of optimization workflow using design of experiment (DoE) for various field configurations in volumetric-modulated arc therapy

PurposeIn volumetric-modulated arc therapy (VMAT), field configurations such as couch or arc angles are defined manually or using a template. A field configuration is reselected through trial-and-error in the case of undesirable resultant planning. To efficiently plan for desirable quality, configurations should be assessed before dose calculation. Design of experiments (DoE) is an optimization technique that efficiently reveals the influence of inputs on outputs. We developed an original tool using DoE to determine the field configuration selection and evaluated the efficacy of this workflow for clinical practice.MethodsComputed-tomography scans of 17 patients and target structures were acquired retrospectively from a brain tumor treated using a dual-arc VMAT plan. The configurations of the couch, arc, collimator angles, field sizes, and beam energy were determined using DoE. The resultant dose distributions obtained using the DoE-selected configuration were compared with the clinical plan.ResultsThe averaged differences between the DoE and clinical plan for 17 patients of doses to 50% of the planning target volume (PTV-D50%), Brain-D60%, Brain-D30%, Brain stem-D1%, Left eye-D1%, Right eye-D1%, Optic nerve-D1%, and Chiasm-D1% were 0.2 ± 0.5%, −1.0 ± 4.6%, 1.7 ± 3.5%, −2.5 ± 6.7%, −0.2 ± 4.9%, −1.2 ± 3.6%, −2.8 ± 7.3%, and −2.1 ± 5.7%, respectively.ConclusionsOur optimization workflow obtained using DoE for various field configurations provided the same or slightly superior plan quality compared with that created by experts. This process is feasible for clinical practice and will efficiently improve treatment quality while removing the influence of the planner’s experience.     

Prediction of multi-criteria optimization (MCO) parameter efficiency in volumetric modulated arc therapy (VMAT) treatment planning using machine learning (ML)

PurposeTo predict the impact of optimization parameter changes on dosimetric plan quality criteria in multi-criteria optimized volumetric-modulated-arc therapy (VMAT) planning prior to optimization using machine learning (ML).MethodsA data base comprising a total of 21,266 VMAT treatment plans for 44 cranial and 18 spinal patient geometries was generated. The underlying optimization algorithm is governed by three highly composite parameters which model a combination of important aspects of the solution. Patient geometries were parametrized via volume- and shape properties of the voxel objects and overlap-volume histograms (OVH) of the planning-target-volume (PTV) and a relevant organ-at-risk (OAR). The impact of changes in one of the three optimization parameters on the maximally achievable value range of five dosimetric properties of the resulting dose distributions was studied. To predict the extent of this impact based on patient geometry, treatment site, and current parameter settings prior to optimization, three different ML-models were trained and tested. Precision-recall curves, as well as the area-under-curve (AUC) of the resulting receiver-operator-characteristic (ROC) curves were analyzed for model assessment.ResultsSuccessful identification of parameter regions resulting in a high variability of dosimetric plan properties depended on the choice of geometry features, the treatment indication and the plan property under investigation. AUC values between 0.82 and 0.99 could be achieved. The best average-precision (AP) values obtained from the corresponding precision/recall curves ranged from 0.71 to 0.99.ConclusionsMachine learning models trained on a database of pre-optimized treatment plans can help finding relevant optimization parameter ranges prior to optimization.     

Dosimetric and radiobiological comparison of TG-43 and Monte Carlo calculations in 192Ir breast brachytherapy applications

PurposeTo investigate the clinical significance of introducing model based dose calculation algorithms (MBDCAs) as an alternative to TG-43 in ¹⁹²Ir interstitial breast brachytherapy.Materials and methodsA 57 patient cohort was used in a retrospective comparison between TG-43 based dosimetry data exported from a treatment planning system and Monte Carlo (MC) dosimetry performed using MCNP v. 6.1 with plan and anatomy information in DICOM-RT format. Comparison was performed for the target, ipsilateral lung, heart, skin, breast and ribs, using dose distributions, dose-volume histograms (DVH) and plan quality indices clinically used for plan evaluation, as well as radiobiological parameters.ResultsTG-43 overestimation of target DVH parameters is statistically significant but small (less than 2% for the target coverage indices and 4% for homogeneity indices, on average). Significant dose differences (>5%) were observed close to the skin and at relatively large distances from the implant leading to a TG-43 dose overestimation for the organs at risk. These differences correspond to low dose regions (<50% of the prescribed dose), being less than 2% of the prescribed dose. Detected dosimetric differences did not induce clinically significant differences in calculated tumor control probabilities (mean absolute difference <0.2%) and normal tissue complication probabilities.ConclusionWhile TG-43 shows a statistically significant overestimation of most indices used for plan evaluation, differences are small and therefore not clinically significant. Improved MBDCA dosimetry could be important for re-irradiation, technique inter-comparison and/or the assessment of secondary cancer induction risk, where accurate dosimetry in the whole patient anatomy is of the essence.     

Impact of interfractional changes in head and neck cancer patients on the delivered dose in intensity modulated radiotherapy with protons and photons

PurposeTo investigate the influence of interfractional changes on the delivered dose of intensity modulated proton (IMPT) and photon plans (IMXT).Methods and materialsFive postoperative head and neck cancer patients, previously treated with tomotherapy at our institute, were analyzed. The planning study is based on megavoltage (MV) control images. For each patient one IMPT plan and one IMXT plan were generated on the first MV-CT and recalculated on weekly control MV-CTs in the actual treatment position. Dose criteria for evaluation were coverage and conformity of the planning target volume (PTV), as well as mean dose to parotids and maximum dose to spinal cord.ResultsConsiderable dosimetric changes were observed for IMPT and IMXT plans. Proton plans showed a more pronounced increase of maximum dose and decrease of minimum dose with local underdosage occurring even in the center of the PTV (worst IMPT vs. IMXT coverage: 66.7% vs. 85.0%). The doses to organs at risk (OARs) increased during the treatment period. However, the OAR doses of IMPT stayed below corresponding IMXT values at any time. For both modalities treatment plans did not necessarily worsen monotonically throughout the treatment.ConclusionsAlthough absolute differences between planned and reconstructed doses were larger in IMPT plans, doses to OARs were higher in IMXT plans. Tumor coverage was more stable in IMXT plans; IMPT dose distributions indicated a high risk for local underdosage during the treatment course.     

3D dosimetric validation of ultrasound-guided radiotherapy with a dynamically deformable abdominal phantom

ObjectivesThe purpose of this study was to dosimetrically benchmark gel dosimetry measurements in a dynamically deformable abdominal phantom for intrafraction image guidance through a multi-dosimeter comparison. Once benchmarked, the study aimed to perform a proof-of-principle study for validation measurements of an ultrasound image-guided radiotherapy delivery system.MethodsThe phantom was dosimetrically benchmarked by delivering a liver VMAT plan and measuring the 3D dose distribution with DEFGEL dosimeters. Measured doses were compared to the treatment planning system and measurements acquired with radiochromic film and an ion chamber. The ultrasound image guidance validation was performed for a hands-free ultrasound transducer for the tracking of liver motion during treatment.ResultsGel dosimeters were compared to the TPS and film measurements, showing good qualitative dose distribution matches, low γ values through most of the high dose region, and average 3%/5 mm γ-analysis pass rates of 99.2%(0.8%) and 90.1%(0.8%), respectively. Gel dosimeter measurements matched ion chamber measurements within 3%. The image guidance validation study showed the measurement of the treatment delivery improvements due to the inclusion of the ultrasound image guidance system. Good qualitative matching of dose distributions and improvements of the γ-analysis results were observed for the ultrasound-gated dosimeter compared to the ungated dosimeter.ConclusionsDEFGEL dosimeters in phantom showed good agreement with the planned dose and other dosimeters for dosimetric benchmarking. Ultrasound image guidance validation measurements showed good proof-of-principle of the utility of the phantom system as a method of validating ultrasound-based image guidance systems and potentially other image guidance methods.     

Assessing the need for adaptive radiotherapy in head and neck cancer patients using an automatic planning tool

BackgroundUnbiased analysis of the impact of adaptive radiotherapy (ART) is necessary to evaluate dosimetric benefit and optimize clinics’ workflows. The aim of the study was to assess the need for adaptive radiotherapy (ART) in head and neck (H&N) cancer patients using an automatic planning tool in a retrospective planning study.Materials and methodsThirty H&N patients treated with adaptive radiotherapy were analysed. Patients had a CT scan for treatment planning and a verification CT during treatment according to the clinic’s protocol. Considering these images, three plans were retrospectively generated using the iCycle tool to simulate the scenarios with and without adaptation: 1) the optimized plan based on the planning CT; 2) the optimized plan based on the verification CT (ART-plan); 3) the plan obtained by considering treatment plan 1 re-calculated in the verification CT (non-ART plan). The dosimetric endpoints for both target volumes and OAR were compared between scenarios 2 and 3 and the SPIDERplan used to evaluate plan quality.ResultsThe most significant impact of ART was found for the PTVs, which demonstrated decreased D98% in the non-ART plan. A general increase in the dose was observed for the OAR but only the spinal cord showed a statistical significance. The SPIDERplan analysis indicated an overall loss of plan quality in the absence of ART.ConclusionThese results confirm the advantages of ART in H&N patients, especially for the coverage of target volumes. The usage of an automatic planning tool reduces planner-induced bias in the results, guaranteeing that the observed changes derive from the application of ART.     

Feasibility of intensity-modulated radiotherapy to treat gastric cancer

AimTo present a proposed gastric cancer intensity-modulated radiotherapy (IMRT) treatment planning protocol for an institution that have not introduced volumetric modulated arc therapy in clinical practice. A secondary aim was to determine the impact of 2DkV set-up corrections on target coverage and organ at risk (OAR).Methods and MaterialsTwenty consecutive patients were treated with a specially-designed non-coplanar 7-field IMRT technique. The isocenter-shift method was used to estimate the impact of 2DkV-based set-up corrections on the original base plan (BP) coverage. An alternative plan was simulated (SP) by taking into account isocenter shifts. The SP and BP were compared using dose-volume histogram (DVH) plots calculated for the internal target volume (ITV) and OARs.ResultsBoth plans delivered a similar mean dose to the ITV (100.32 vs. 100.40%), with no significant differences between the plans in internal target coverage (5.37 vs. 4.96%). Similarly, no significant differences were observed between the maximal dose to the spinal cord (67.70 and 67.09%, respectively) and volume received 50% of the prescribed dose of: the liver (62.11 vs. 59.84%), the right (17.62 vs. 18.58%) and left kidney (29.40 vs. 30.48%). Set-up margins (SM) were computed as 7.80 mm, 10.17 mm and 6.71 mm in the left-right, cranio-caudal and anterior-posterior directions, respectively.ConclusionPresented IMRT protocol (OAR dose constraints with selected SM verified by 2DkV verification) for stomach treatment provided optimal dose distribution for the target and the critical organs. Comparison of DVH for the base and the modified plan (which considered set-up uncertainties) showed no significant differences.     

Precision IORT – Image guided intraoperative radiation therapy (igIORT) using online treatment planning including tissue heterogeneity correction

BackgroundTo the present date, IORT has been eye and hand guided without treatment planning and tissue heterogeneity correction. This limits the precision of the application and the precise documentation of the location and the deposited dose in the tissue. Here we present a set-up where we use image guidance by intraoperative cone beam computed tomography (CBCT) for precise online Monte Carlo treatment planning including tissue heterogeneity correction.Materials and methodsAn IORT was performed during balloon kyphoplasty using a dedicated Needle Applicator. An intraoperative CBCT was registered with a pre-op CT. Treatment planning was performed in Radiance using a hybrid Monte Carlo algorithm simulating dose in homogeneous (MCwater) and heterogeneous medium (MChet). Dose distributions on CBCT and pre-op CT were compared with each other. Spinal cord and the metastasis doses were evaluated.ResultsThe MCwater calculations showed a spherical dose distribution as expected. The minimum target dose for the MChet simulations on pre-op CT was increased by 40% while the maximum spinal cord dose was decreased by 35%. Due to the artefacts on the CBCT the comparison between MChet simulations on CBCT and pre-op CT showed differences up to 50% in dose.ConclusionsigIORT and online treatment planning improves the accuracy of IORT. However, the current set-up is limited by CT artefacts. Fusing an intraoperative CBCT with a pre-op CT allows the combination of an accurate dose calculation with the knowledge of the correct source/applicator position. This method can be also used for pre-operative treatment planning followed by image guided surgery.     

Dose gradient based algorithm for beam weights selection in 3D-CRT plans

AimIn this work we test the usage of dose gradient based algorithm for the selection of beam weights in 3D-CRT plans for different cancer locations. Our algorithm is easy to implement for three fields technique with wedges defined by planner.Background3D-CRT is usually realized with forward planning which is quite time consuming. Several authors published a few methods of beams weights optimization applicable to the 3D-CRT.Materials and methodsOptimization is based on an assumption that the best plan is achieved if dose gradient at ICRU point is equal to zero. Method was tested for 120 patients, treated in our clinic in 2011-2012, with different cancer locations. For each patient, three fields conformal plan (6 MV and 15 MV X-ray) with the same geometry as proposed by experienced planners was prepared. We compared dose distributions achieved with the proposed method and those prepared by experienced planners. The homogeneity of dose distributions was compared in terms of STD and near minimum and near maximum doses in the PTV.ResultsMean difference of STD obtained by the proposed algorithm and by planners was 0.1%: 0.1% for prostate cancer, 0.3% for lung cancer, −0.1% for esophagus cancer, 0.1% for rectum cancer, −0.1% for gynecology cancer, −0.1% for stomach cancer.ConclusionsApplying the proposed algorithm leads to obtain the similar dose distribution homogeneity in the PTV as these achieved by planners and therefore can serve as a support in creating 3D-CRT plans. It is also simple to use and can significantly speed up the treatment planning process.     

Virtual Tangential-fields Arc Therapy (ViTAT) for whole breast irradiation: Technique optimization and validation

PurposeTo test the performances of a volumetric arc technique named ViTAT (Virtual Tangential-fields Arc Therapy) mimicking tangential field irradiation for whole breast radiotherapy.MethodsViTAT plans consisted in 4 arcs whose starting/ending position were established based on gantry angle distribution of clinical plans for right and left-breast. The arcs were completely blocked excluding the first and last 20°. Different virtual bolus densities and thicknesses were preliminarily evaluated to obtain the best plan performances. For 40 patients with tumor laterality equally divided between right and left sides, ViTAT plans were optimized considering the clinical DVHs for OARs (resulting from tangential field manual planning) to constrain them: ViTAT plans were compared with the clinical tangential-fields in terms of DVH parameters for both PTV and OARs.ResultsDistal angle values were suggested in the ranges [220°,240°] for the right-breast and [115°,135°] for the left-breast cases; medial angles were [60°,40°] for the right side and [295°,315°] for the left side, limiting the risk of collision. The optimal virtual bolus had −500 HU density and 1.5 cm thickness. ViTAT plans generated dose distributions very similar to the tangential-field plans, with significantly improved PTV homogeneity. The mean doses of ipsilateral OARs were comparable between the two techniques with minor increase of the low-dose spread in the range 2–15 Gy (few % volume); contralateral OARs were slightly better spared with ViTAT.ConclusionViTAT dose distributions were similar to tangential-fields. ViTAT should allow automatic plan optimization by developing knowledge-based DVH prediction models of patients treated with tangential-fields.     

Evaluation of a commercial automatic treatment planning system for liver stereotactic body radiation therapy treatments

PurposeAutomated treatment planning is a new frontier in radiotherapy. The Auto-Planning module of the Pinnacle³ treatment planning system (TPS) was evaluated for liver stereotactic body radiation therapy treatments.MethodsTen cases were included in the study. Six plans were generated for each case by four medical physics experts. The first two planned with Pinnacle TPS, both with manual module (MP) and Auto-Planning one (AP). The other two physicists generated two plans with Monaco TPS (VM). Treatment plan comparisons were then carried on the various dosimetric parameters of target and organs at risk, monitor units, number of segments, plan complexity metrics and human resource planning time. The user dependency of Auto-Planning was also tested and the plans were evaluated by a trained physician.ResultsStatistically significant differences (Anova test) were observed for spinal cord doses, plan average beam irregularity, number of segments, monitor units and human planning time. The Fisher-Hayter test applied to these parameters showed significant statistical differences between AP e MP for spinal cord doses and human planning time; between MP and VM for monitor units, number of segments and plan irregularity; for all those between AP and VM. The two plans created by different planners with AP were similar to each other.ConclusionsThe plans created with Auto-Planning were comparable to the manually generated plans. The time saved in planning enables the planner to commit more resources to more complex cases. The independence of the planner enables to standardize plan quality.     

Efficient double-scattering proton therapy with a patient-specific bolus

PurposePassive scattering proton radiotherapy utilizes beam-specific compensators to shape the dose to the distal end of the tumor target. These compensators typically require therapists to enter the treatment room to mount between beams. This study investigates a novel approach that utilizes a single patient-specific bolus to accomplish the role of multi-field compensators to improve the efficiency of the treatment delivery.MethodsRay-tracing from the proton virtual source was used to convert the beam-specific compensators (mounted on the gantry nozzle) into an equivalent bolus thickness on the patient surface. The field bolus contours were combined to create a single bolus. A 3D acrylic bolus was milled for a head phantom. The dose distribution of the compensator plan was compared to the bolus plan using 3D Gamma analysis and film measurements. Boluses for two clinical patients were also designed.ResultsThe calculated phantom dose distribution of the original proton compensator plan was shown to be equivalent to the plan with the surface bolus. Film irradiations with the proton bolus also confirmed the dosimetric equivalence of the two techniques. The dose distribution equivalency of the bolus plans for the clinical patients were demonstrated.ConclusionsWe presented a novel approach that uses a single patient-specific bolus to replace patient compensators during passive scattering proton delivery. This approach has the potential to reduce the treatment time, the compensator manufacturing costs, the risk of potential collision between the compensator and the patient/couch, and the waste of compensator material.     

Concentration modulated skin marker for radiotherapy treatment planning process

Background and purposeFor conformal radiotherapy, it is feasible to achieve high accuracy in contouring the outline of the target volume in treatment planning process. In contouring process, target volume is occasionally defined by means of either surgical clips or skin marker during patient anatomical data acquisition. Treatment planning systems are predicting invalid radiation dose distributions by using surgical clips and skin marker within the patient. Purpose of this study is the production of new skin marker which affects less dose distributions of electron beam.Materials and methodsThe influences of lead and commercial markers on dose calculations in a 3D treatment planning systems were investigated in terms of electron beam energy and dose profile depth. Dose deviation with commercial marker was observed to smaller than lead marker. However this dose deviation was still at big value. In order to reduce of this value, barium sulfate suspension and ultrasound gel were mixed with different volumetric ratio. With the purpose of acception the most suitable marker for radiation therapy, obtained new suspensions were investigated in terms of visibility and dose deviation.ResultsB:G/1:10 marker was determined to cause optimum visibility and the lowest dose deviation on dose calculations in terms of electron beam energy and dose profile depth.ConclusionsAppropriate marker, mixture of substances such as barium sulfate suspension and ultrasound gel can be produced. This marker is both ease of usage and practical and economical. Each clinic can prepare marker which is peculiar to suspension with different concentration of substance for specific visibility. But, it should be taken into account resultant dose deviation to beam calculation depending on barium sulfate concentration.     

Dosimetric impact of statistical uncertainty on Monte Carlo dose calculation algorithm in volumetric modulated arc therapy using Monaco TPS for three different clinical cases

AimTo study the dosimetric impact of statistical uncertainty (SU) per plan on Monte Carlo (MC) calculation in Monaco? treatment planning system (TPS) during volumetric modulated arc therapy (VMAT) for three different clinical cases.BackgroundDuring MC calculation SU is an important factor to decide dose calculation accuracy and calculation time. It is necessary to evaluate optimal acceptance of SU for quality plan with reduced calculation time.Materials and methodsThree different clinical cases as the lung, larynx, and prostate treated using VMAT technique were chosen. Plans were generated with Monaco? V5.11 TPS with 2% statistical uncertainty. By keeping all other parameters constant, plans were recalculated by varying SU, 0.5%, 1%, 2%, 3%, 4%, and 5%. For plan evaluation, conformity index (CI), homogeneity index (HI), dose coverage to PTV, organ at risk (OAR) dose, normal tissue receiving dose ≥5 Gy and ≥10 Gy, integral dose (NTID), calculation time, gamma pass rate, calculation reproducibility and energy dependency were analyzed.ResultsCI and HI improve as SU increases from 0.5% to 5%. No significant dose difference was observed in dose coverage to PTV, OAR doses, normal tissue receiving dose ≥5 Gy and ≥10 Gy and NTID. Increase of SU showed decrease in calculation time, gamma pass rate and increase in PTV max dose. No dose difference was seen in calculation reproducibility and dependent on energy.ConclusionFor VMAT plans, SU can be accepted from 1% to 3% per plan with reduced calculation time without compromising plan quality and deliverability by accepting variations in point dose within the target.