Analysis of the long-term stability of the output of electron beams generated by the Novac11™ IORT accelerator.

AIM: The aim of the study was to analyze the long-term stability of electron beams generated by the Novac11™ IORT accelerator. BACKGROUND: Novac11™ (NRT®) is a mobile electron accelerator designed to irradiate small areas of tissue, up to 10 cm in diameter, with electron beams during surgical procedures. It is characterized by a great mobility guaranteed by a number of degrees of freedom enabling irradiation in the conditions of an operating theatre. MATERIALS AND METHODS: Over the period of January 2013 and September 2016, the measurement sessions of the output of clinically used beam qualities (6, 8 and 10 MeV) were carried out 41 times. Because of the unsatisfactory long-term stability, an extra procedure of tuning of the magnetron, suggested by the manufacturer, was introduced in October 2015, 15 measurements were performed since then. The output of the Novac11™ accelerator was measured in the reference conditions recommended by the IAEA Report 398, the measurements of the charge in the ionization chamber at the reference depth were carried out with a Dose1™ electrometer and a plane-parallel chamber PPC05™ from IBA®. RESULTS: The introduction of the tuning of the magnetron procedure resulted in satisfactory long-term stability of the measured outputs below 2%. CONCLUSIONS: After the introduction of the STV parameter tuning procedure, the long-term stability of the Novac11™ output increased considerably and is within the values declared by the manufacturer.

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

AIM: In 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. BACKGROUND: 3D-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 METHODS: Optimization 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. RESULTS: Mean 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. CONCLUSIONS: Applying 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.

Implementation of a dose gradient method into optimization of dose distribution in prostate cancer 3D-CRT plans.

AIM: The aim of this work is to present a method of beam weight and wedge angle optimization for patients with prostate cancer. BACKGROUND: 3D-CRT is usually realized with forward planning based on a trial and error method. Several authors have published a few methods of beam weight optimization applicable to the 3D-CRT. Still, none on these methods is in common use. MATERIALS AND METHODS: Optimization is based on the assumption that the best plan is achieved if dose gradient at ICRU point is equal to zero. Our optimization algorithm requires beam quality index, depth of maximum dose, profiles of wedged fields and maximum dose to femoral heads. The method was tested for 10 patients with prostate cancer, treated with the 3-field technique. Optimized plans were compared with plans prepared by 12 experienced planners. Dose standard deviation in target volume, and minimum and maximum doses were analyzed. RESULTS: The quality of plans obtained with the proposed optimization algorithms was comparable to that prepared by experienced planners. Mean difference in target dose standard deviation was 0.1% in favor of the plans prepared by planners for optimization of beam weights and wedge angles. Introducing a correction factor for patient body outline for dose gradient at ICRU point improved dose distribution homogeneity. On average, a 0.1% lower standard deviation was achieved with the optimization algorithm. No significant difference in mean dose-volume histogram for the rectum was observed. CONCLUSIONS: Optimization shortens very much time planning. The average planning time was 5 min and less than a minute for forward and computer optimization, respectively.

Comparison of calculation algorithms to predict the IQM detector response for various modulation degrees of VMAT treatment plans on linear accelerator equipped with the HD120 MLC.

PURPOSE: The calculation model for the integral quality monitor (IQM) system does not take into account the characteristics of the HD120 multileaf collimator (MLC), which some Varian accelerators are equipped with. Some treatment plans prepared with this collimator are characterized by a high level of modulation. The aim of the work was to prepare a model for that collimator and to determine the influence of modulation on results of the verification carried out with the use of IQM system. METHODS: The short and long stabilities of the IQM detector response were verified by measuring the signal for a 6 MV flattening filter-free (FFF) beam with the static field of 10 × 10 cm2 size. The obtained results were compared with the measurements performed with the PTW Farmer chamber. Next, the signals for 35 static square fields 4 × 4 cm2 , covering the whole field 38 × 20 cm2 , were measured with the IQM. Based on the results of these measurements, the original calculation model has been changed in order to achieve the smallest differences between calculations and measurements. While tuning the model, the characteristics of the HD120 MLC were included. Measurements were performed for 30 clinical plans (86 arcs) prepared with 6 MV FFF beams. Among those 30 plans, there were were multitarget plans with single isocenter. For each plan, the modulation complexity score (MCS) was calculated. The measurement results were compared with the calculation results performed with the original and authors' calculation model. RESULTS: Very good stability of the short and long stabilities of the IQM detector response was obtained. Measurements performed for 35 static fields revealed that for the manufacturer's and for the authors' models, the deviation exceeded 3% for 12 and five of the 35 static fields, respectively. The differences for the manufacturer's and authors' algorithms were in the range of ±2% for the 15 and 26 of the fields, respectively. For original and the authors' models, the differences between measured and calculated signals (starting with the segment number 40) were within the range of ±3.5% for 87.6% and 96.7% of all arcs for the respective models. For both models, the dependence of the compliance of measurements and calculations on the MCS was observed. For most of the very modulated arcs, the measured signal was at least 3% lower than the calculated one. The largest differences between measurements and calculations were obtained for single-isocenter multitarget plans. CONCLUSIONS: The signal predicted by an algorithm taking into account the real geometry of the collimating system of the Edge accelerator (equipped with the HD120 MLC) made it possible to obtain greater consistency between the measurements and calculations. We characterized the dependence between the MCS of each arc and the compliance of the measurements and calculations. Much worse results were obtained for single-isocenter multitarget plans.

Computed tomography as a source of electron density information for radiation treatment planning.

PURPOSE: To evaluate the performance of computed tomography (CT) systems of various designs as a source of electron density (rho(el)) data for treatment planning of radiation therapy. MATERIAL AND METHODS: Dependence of CT numbers on relative electron density of tissue-equivalent materials (HU-rho(el) relationship) was measured for several general-purpose CT systems (single-slice, multislice, wide-bore multislice), for radiotherapy simulators with a single-slice CT and kV CBCT (cone-beam CT) options, as well as for linear accelerators with kV and MV CBCT systems. Electron density phantoms of four sizes were used. Measurement data were compared with the standard HU-rhoel relationships predefined in two commercial treatment-planning systems (TPS). RESULTS: The HU-rho(el) relationships obtained with all of the general-purpose CT scanners operating at voltages close to 120 kV were very similar to each other and close to those predefined in TPS. Some dependency of HU values on tube voltage was observed for bone- equivalent materials. For a given tube voltage, differences in results obtained for different phantoms were larger than those obtained for different CT scanners. For radiotherapy simulators and for kV CBCT systems, the information on rhoel was much less precise because of poor uniformity of images. For MV CBCT, the results were significantly different than for kV systems due to the differing energy spectrum of the beam. CONCLUSION: The HU-rho(el) relationships predefined in TPS can be used for general-purpose CT systems operating at voltages close to 120 kV. For nontypical imaging systems (e.g., CBCT), the relationship can be significantly different and, therefore, it should always be measured and carefully analyzed before using CT data for treatment planning.

Coping with interfraction time trends in tumor setup.

PURPOSE: Interfraction tumor setup variations in radiotherapy are often reduced with image guidance procedures. Clinical target volume (CTV)-planning target volume (PTV) margins are then used to deal with residual errors. We have investigated characterization of setup errors in patient populations with explicit modelling of occurring interfraction time trends. METHODS: The core of a "trendline characterization" of observed setup errors in a population is a distribution of trendlines, each obtained by fitting a straight line through a patient's daily setup errors. Random errors are defined as daily deviations from the trendline. Monte Carlo simulations were performed to predict the impact of offline setup correction protocols on residual setup errors in patient populations with time trends. A novel CTV-PTV margin recipe was derived that assumes that systematic underdosing of tumor edges in multiple consecutive fractions, as caused by trend motion, should preferentially be avoided. Similar to the well-known approach by van Herk et al. for conventional error characterization (no explicit modelling of trends), only a predefined percentage of patients (generally 10%) was allowed to have nonrandom (systematic + trend) setup errors outside the margin. Additionally, a method was proposed to avoid erroneous results in Monte Carlo simulations with setup errors, related to decoupling of error sources in characterizations. The investigations were based on a database of daily measured setup errors in 835 prostate cancer patients that were treated with 39 fractions, and on Monte Carlo-generated patient populations with time trends. RESULTS: With conventional characterization of setup errors in patient populations with time trends, predicted standard deviations of residual systematic errors ( Σ res ) after application of an offline correction protocol could be underestimated by more than 50%, potentially resulting in application of too small margins. With the new trendline characterization this was avoided. With the novel CTV-PTV margin recipe with an allowed 10% of patients having nonrandom errors outside the margin, the observed percentage was 10.0% ± 0.2%. When using conventional characterization of errors and the van Herk margin recipe, on average 58.0% ± 24.3% of patients had errors outside the margin, while 10% was prescribed. For populations with no time trends, the novel recipe simplifies to the generally applied M = 2.5 Σ + 0.7 σ formula proposed by van Herk et al. CONCLUSIONS: In populations with time trends in setup errors, the use of trendline characterizations in Monte Carlo simulations for establishment of residual errors after a setup correction protocol can avoid application of erroneous margins. The novel margin recipe can be used to accurately control the percentage of patients with nonrandom errors outside the margin. In case of daily image guidance of patients with multiple targets with differential motion, the recipe can be used to establish margins for the targets that are not the primary target for the image guidance (e.g., nodal regions). Probabilistic planning might be improved by using trendline characterization for modelling of setup errors. Population analyses of interfraction setup errors need to take into account potential time trends.

Method of predicting the mean lung dose based on a patient׳s anatomy and dose-volume histograms.

The aim of this study was to propose a method to predict the minimum achievable mean lung dose (MLD) and corresponding dosimetric parameters for organs-at-risk (OAR) based on individual patient anatomy. For each patient, the dose for 36 equidistant individual multileaf collimator shaped fields in the treatment planning system (TPS) was calculated. Based on these dose matrices, the MLD for each patient was predicted by the homemade DosePredictor software in which the solution of linear equations was implemented. The software prediction results were validated based on 3D conformal radiotherapy (3D-CRT) and volumetric modulated arc therapy (VMAT) plans previously prepared for 16 patients with stage III non-small-cell lung cancer (NSCLC). For each patient, dosimetric parameters derived from plans and the results calculated by DosePredictor were compared. The MLD, the maximum dose to the spinal cord (Dmax cord) and the mean esophageal dose (MED) were analyzed. There was a strong correlation between the MLD calculated by the DosePredictor and those obtained in treatment plans regardless of the technique used. The correlation coefficient was 0.96 for both 3D-CRT and VMAT techniques. In a similar manner, MED correlations of 0.98 and 0.96 were obtained for 3D-CRT and VMAT plans, respectively. The maximum dose to the spinal cord was not predicted very well. The correlation coefficient was 0.30 and 0.61 for 3D-CRT and VMAT, respectively. The presented method allows us to predict the minimum MLD and corresponding dosimetric parameters to OARs without the necessity of plan preparation. The method can serve as a guide during the treatment planning process, for example, as initial constraints in VMAT optimization. It allows the probability of lung pneumonitis to be predicted.