A Monte Carlo-based procedure for independent monitor unit calculation in IMRT treatment plans

External beam patient dose verification based on the integral quality monitor (IQM®) output signals

BACKGROUND

The Integral Quality Monitor (IQM^®) can essentially measure the integral fluence through a segment and provide real-time information about the accuracy of radiation delivery based on comparisons of measured segment signals and pre-calculated reference values. However, the present IQM chamber cannot calculate the dose in the patient.

AIM

This study aims to make use of IQM field output signals to calculate the number of monitor units (MUs) delivered through an arbitrary treatment field in order to convert Monte Carlo (MC)-generated dose distributions in a patient model into absolute dose.

METHODS

XiO and Monaco treatment planning systems (TPSs) were used to define treatment beam portals for cervix and esophagus conformal radiotherapy as well as prostate intensity-modulated radiotherapy for the translation of patient and beam setup information from DICOM to DOSXYZnrc. The planned beams were simulated in a patient model built from actual patient CT images and each simulated integral field/segment was weighted with its MUs before summation to get the total dose in the plan. The segment beam weights (MUs) were calculated as the ratio of the open-field IQM measured signal and the calculated signal per MU extracted from chamber sensitivity maps. These are the actual MUs delivered not just MUs set. The beam weighting method was evaluated by comparing weighted MC doses with original planned doses using profile and isodose comparisons, dose difference maps, γ analysis and dose-volume histogram (DVH) data.

RESULTS

γ pass rates of up to 98% were found, except for the esophagus plan where the γ pass rate was below 45%. DVH comparisons showed good agreement for most organs, with the largest differences observed in low-density lung. However, these discrepancies can result from differences in dose calculation algorithms or differences in MUs used for dose weighting planned by the TPS and MUs calculated using IQM field output signals. To test this, a 4-field box DOSXYZnrc MC simulation weighted with planned (XiO) MUs was compared with the same simulation weighted with IQM-based MUs. Dose differences of up to 5% were found on the isocentre slice. For XiO versus MC, up to 7% dose differences were found, indicating additional error due to limitations of XiO's superposition algorithm. Dose differences between MC Monaco and MC EGSnrc were less than 3%.

CONCLUSIONS

The most valuable comparison was MC versus MC as it eliminated algorithm discrepancies and evaluated dose differences precisely according to beam weighting. For XiO TPS, care must be taken as dose differences may also arise due to limitations in XiO's planning software, not merely due to differences in MUs. Overall, the IQM was successfully used to compute beam dose weights to accurately reconstruct the patient dose using unweighted MC beams. Our technique can be used for pre-treatment QA provided each segment output is known and an accurate linac source model is available.

Predicting VMAT patient-specific QA results using a support vector classifier trained on treatment plan characteristics and linac QC metrics

The use of treatment plan characteristics to predict patient-specific quality assurance (QA) measurement results has recently been reported as a strategy to help facilitate automated pre-treatment verification workflows or to provide a virtual assessment of delivery quality. The goal of this work is to investigate the potential of using treatment plan characteristics and linac performance metrics (i.e. quality control test results) in combination with machine learning techniques to predict the results of VMAT patient-specific QA measurements. Using features that describe treatment plan complexity and linac performance metrics, we trained a linear support vector classifier (SVC) to classify the results of VMAT patient-specific QA measurements. The 'targets' in this model were simple classes representing median dose difference between measured and expected dose distributions-'hot' if the median dose deviation was  >1%, 'cold' if it was  <-1%, and 'normal' if it was within  ±1%. A total of 1620 unique patient-specific QA measurements were available for model development and testing. 75% of the data were used to develop and cross-validate the model, and the remaining 25% were used for an independent assessment of model performance. For the model development phase, a recursive feature elimination (RFE) cross-validation technique was used to eliminate unimportant features. Model performance was assessed using receiver operator characteristic (ROC) curve metrics. Of the ten features found to be most predictive of patient-specific QA measurement results, half were derived from treatment plan characteristics and half from quality control (QC) metrics characterizing linac performance. The model achieved a micro-averaged area under the ROC curve of 0.93, and a macro-averaged area under the ROC curve of 0.88. This work demonstrates the potential of using both treatment plan characteristics and routine linac QC results in the development of machine learning models for VMAT patient-specific QA measurements.

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.

Multi-institutional comparison of secondary check of treatment planning using computer-based independent dose calculation for non-C-arm linear accelerators

PURPOSE

This report covers the first multi-institutional study of independent monitor unit (MU)/dose calculation verification for the CyberKnife, Vero4DRT, and TomoTherapy radiotherapy delivery systems.

METHODS

A total of 973 clinical treatment plans were collected from 12 institutions. Commercial software employing the Clarkson algorithm was used for verification after a measurement validation study, and the doses from the treatment planning systems (TPSs) and verification programs were compared on the basis of the mean value ± two standard deviations. The impact of heterogeneous conditions was assessed in two types of sites: non-lung and lung.

RESULTS

The dose difference for all locations was 0.5 ± 7.2%. There was a statistically significant difference (P < 0.01) in dose difference between non-lung (-0.3 ± 4.4%) and lung sites (3.5 ± 6.7%). Inter-institutional comparisons showed that various systematic differences were associated with the proportion of different treatment sites and heterogeneity correction.

CONCLUSIONS

This multi-institutional comparison should help to determine the departmental action levels for CyberKnife, Vero4DRT, and TomoTherapy, as patient populations and treatment sites may vary between the modalities. An action level of ±5% could be considered for intensity-modulated radiation therapy (IMRT), non-IMRT, and volumetric modulated arc radiotherapy using these modalities in homogenous and heterogeneous conditions with a large treatment field applied to a large region of homogeneous media. There were larger systematic differences in heterogeneous conditions with a small treatment field because of differences in heterogeneity correction with the different dose calculation algorithms of the primary TPS and verification program.

Independent calculation of monitor units for VMAT and SPORT

PURPOSE

Dose and monitor units (MUs) represent two important facets of a radiation therapy treatment. In current practice, verification of a treatment plan is commonly done in dose domain, in which a phantom measurement or forward dose calculation is performed to examine the dosimetric accuracy and the MU settings of a given treatment plan. While it is desirable to verify directly the MU settings, a computational framework for obtaining the MU values from a known dose distribution has yet to be developed. This work presents a strategy to calculate independently the MUs from a given dose distribution of volumetric modulated arc therapy (VMAT) and station parameter optimized radiation therapy (SPORT).

METHODS

The dose at a point can be expressed as a sum of contributions from all the station points (or control points). This relationship forms the basis of the proposed MU verification technique. To proceed, the authors first obtain the matrix elements which characterize the dosimetric contribution of the involved station points by computing the doses at a series of voxels, typically on the prescription surface of the VMAT/SPORT treatment plan, with unit MU setting for all the station points. An in-house Monte Carlo (MC) software is used for the dose matrix calculation. The MUs of the station points are then derived by minimizing the least-squares difference between doses computed by the treatment planning system (TPS) and that of the MC for the selected set of voxels on the prescription surface. The technique is applied to 16 clinical cases with a variety of energies, disease sites, and TPS dose calculation algorithms.

RESULTS

For all plans except the lung cases with large tissue density inhomogeneity, the independently computed MUs agree with that of TPS to within 2.7% for all the station points. In the dose domain, no significant difference between the MC and Eclipse Anisotropic Analytical Algorithm (AAA) dose distribution is found in terms of isodose contours, dose profiles, gamma index, and dose volume histogram (DVH) for these cases. For the lung cases, the MC-calculated MUs differ significantly from that of the treatment plan computed using AAA. However, the discrepancies are reduced to within 3% when the TPS dose calculation algorithm is switched to a transport equation-based technique (Acuros™). Comparison in the dose domain between the MC and Eclipse AAA/Acuros calculation yields conclusion consistent with the MU calculation.

CONCLUSIONS

A computational framework relating the MU and dose domains has been established. The framework does not only enable them to verify the MU values of the involved station points of a VMAT plan directly in the MU domain but also provide a much needed mechanism to adaptively modify the MU values of the station points in accordance to a specific change in the dose domain.

Towards effective and efficient patient-specific quality assurance for spot scanning proton therapy

An intensity-modulated proton therapy (IMPT) patient-specific quality assurance (PSQA) program based on measurement alone can be very time consuming due to the highly modulated dose distributions of IMPT fields. Incorporating independent dose calculation and treatment log file analysis could reduce the time required for measurements. In this article, we summarize our effort to develop an efficient and effective PSQA program that consists of three components: measurements, independent dose calculation, and analysis of patient-specific treatment delivery log files. Measurements included two-dimensional (2D) measurements using an ionization chamber array detector for each field delivered at the planned gantry angles with the electronic medical record (EMR) system in the QA mode and the accelerator control system (ACS) in the treatment mode, and additional measurements at depths for each field with the ACS in physics mode and without the EMR system. Dose distributions for each field in a water phantom were calculated independently using a recently developed in-house pencil beam algorithm and compared with those obtained using the treatment planning system (TPS). The treatment log file for each field was analyzed in terms of deviations in delivered spot positions from their planned positions using various statistical methods. Using this improved PSQA program, we were able to verify the integrity of the data transfer from the TPS to the EMR to the ACS, the dose calculation of the TPS, and the treatment delivery, including the dose delivered and spot positions. On the basis of this experience, we estimate that the in-room measurement time required for each complex IMPT case (e.g., a patient receiving bilateral IMPT for head and neck cancer) is less than 1 h using the improved PSQA program. Our experience demonstrates that it is possible to develop an efficient and effective PSQA program for IMPT with the equipment and resources available in the clinic.

Modulation factors calculated with an EPID-derived MLC fluence model to streamline IMRT/VMAT second checks

This work outlines the development of a robust method of calculating modulation factors used for the independent verification of MUs for IMRT and VMAT treatments, to replace onerous ion chamber measurements. Two‐dimensional fluence maps were calculated for dynamic MLC fields that include MLC interleaf leakage, transmission, and tongue‐and‐groove effects, as characterized from EPID‐acquired images. Monte Carlo‐generated dose kernels were then used to calculate doses for a modulated field and that field with the modulation removed at a depth specific to the calculation point in the patient using in‐house written software, Mod_Calc. The ratio of these two doses was taken to calculate modulation factors. Comparison between Mod_Calc calculation and ion chamber measurement of modulation factors for 121 IMRT fields yielded excellent agreement, where the mean difference between the two was −0.3%±1.2%. This validated use of Mod_Calc clinically. Analysis of 5,271 dynamic fields from clinical use of Mod_Calc gave a mean difference of 0.3%±1.0% between Mod_Calc and Eclipse‐generated factors. In addition, 99.3% and 96.5% fields pass 5% and 2% criteria, respectively, for agreement between these two predictions. The development and use of Mod_Calc at our clinic has considerably streamlined our QA process for IMRT and RapidArc fields, compared to our previous method based on ion chamber measurements. As a result, it has made it feasible to maintain our established and trusted current in‐house method of MU verification, without resorting to commercial software alternatives.

PACS numbers: 87.55.km, 87.55.Qr, 87.55.kd, 87.57.uq

Application of an independent dose calculation software for estimating the impact of inter-fractional setup shifts in Helical Tomotherapy treatments

The purpose of this study is to validate the capability of in-house independent point dose calculation software to be used as a second check for Helical Tomotherapy treatment plans. The software performed its calculations in homogenous conditions (using the Cheese phantom, which is a cylindrical phantom with radius 15 cm and length 18 cm) using a factor-based algorithm. Fifty patients, who were treated for pelvic (10), prostate (14), lung (10), head & neck (12) and brain (4) cancers, were used. Based on the individual patient kVCT images and the pretreatment MVCT images for each treatment fraction, the corresponding daily patient setup shifts in the IEC-X, IEC-Y, and IEC-Z directions were registered. For each patient, the registered fractional setup shifts were grouped into systematic and random shifts. The average systematic dosimetric variations showed small dose deviation for the different cancer types (1.0%-3.0%) compared to the planned dose. Of the fifty patients, only three had percent differences larger than 5%. The average random dosimetric variations showed relatively small dose deviations (0.2%-1.1%) compared to the planned dose. None of the patients had percent differences larger than 5%. By examining the individual fractions of each patient, it is observed that only in 31 out of 1358 fractions the percent differences exceeded the border of 5%. These results indicate that the overall dosimetric impact from systematic and random variations is small and that the software is a capable platform for independent point dose validation for the Helical Tomotherapy modality.

Performance of independent dose calculation in helical tomotherapy: implementation of the MCSIM code

Currently, a software-based second check dose calculation for helical tomotherapy (HT) is not available. The goal of this study is to evaluate the dose calculation accuracy of the in-house software using EGS4/MCSIM Monte Carlo environment against the treatment planning system calculations. In-house software was used to convert HT treatment plan information into a non-helical format. The MCSIM dose calculation code was evaluated by comparing point dose calculations and dose profiles against those from the HT treatment plan. Fifteen patients, representing five treatment sites, were used in this comparison. Point dose calculations between the HT treatment planning system and the EGS4/MCSIM Monte Carlo environment had percent difference values below 5 % for the majority of this study. Vertical and horizontal planar profiles also had percent difference values below 5 % for the majority of this study. Down sampling was seen to improve speed without much loss of accuracy. EGS4/MCSIM Monte Carlo environment showed good agreement with point dose measurements, compared to the HT treatment plans. Vertical and horizontal profiles also showed good agreement. Significant time saving may be obtained by down-sampling beam projections. The dose calculation accuracy of the in-house software using the MCSIM code against the treatment planning system calculations was evaluated. By comparing point doses and dose profiles, the EGS4/MCSIM Monte Carlo environment was seen to provide an accurate independent dose calculation.

Calculation of correction factors for ionization chamber measurements with small fields in low-density media

The quantity of interest for high-energy photon beam therapy recommended by most dosimetric protocols is the absorbed dose to water. Thus, ionization chambers are calibrated in absorbed dose to water, which is the same quantity as what is calculated by most treatment planning systems (TPS). However, when measurements are performed in a low-density medium, the presence of the ionization chamber generates a perturbation at the level of the secondary particle range. Therefore, the measured quantity is close to the absorbed dose to a volume of water equivalent to the chamber volume. This quantity is not equivalent to the dose calculated by a TPS, which is the absorbed dose to an infinitesimally small volume of water. This phenomenon can lead to an overestimation of the absorbed dose measured with an ionization chamber of up to 40% in extreme cases. In this paper, we propose a method to calculate correction factors based on the Monte Carlo simulations. These correction factors are obtained by the ratio of the absorbed dose to water in a low-density medium □D(w,Q,V1)(low) averaged over a scoring volume V₁ for a geometry where V₁ is filled with the low-density medium and the absorbed dose to water □D(w,QV2)(low) averaged over a volume V₂ for a geometry where V₂ is filled with water. In the Monte Carlo simulations, □D(w,QV2)(low) is obtained by replacing the volume of the ionization chamber by an equivalent volume of water, according to the definition of the absorbed dose to water. The method is validated in two different configurations which allowed us to study the behavior of this correction factor as a function of depth in phantom, photon beam energy, phantom density and field size.

Control chart analysis of data from a multicenter monitor unit verification study

BACKGROUND AND PURPOSE

This study aims to investigate the process of monitor unit verification using control charts. Control charts is a key tool within statistical process control (SPC), through which process characteristics can be visualized, usually chronologically with statistically determined limits.

MATERIAL AND METHODS

Our group has developed a monitor unit verification software that has been adopted at several Swedish institutions for pre-treatment verification of radiotherapy treatments. Deviations between point dose calculations using the treatment planning systems and using the independent monitor unit verification software from 9219 treatment plans and five different institutions were included in this multicenter study. The process of monitor unit verification was divided into subprocesses. Each subprocess was analyzed using probability plots and control charts.

RESULTS

Differences in control chart parameters for the investigated subprocesses were found between different treatment sites and different institutions, as well as between different treatment techniques. 19 of 37 subprocesses met the clinical specification (± 5%), i.e. process capability index was equal to or above one.

CONCLUSIONS

Control charts were found to be a useful tool for continuous analysis of data from the monitor unit verification software for patient specific quality control, as well as for comparisons between different institutions and treatment sites. The derived control chart limits were in agreement with AAPM TG114 guidelines on action levels.

3D dose reconstruction for narrow beams using ion chamber array measurements

3D dose reconstruction is a verification of the delivered absorbed dose. Our aim was to describe and evaluate a 3D dose reconstruction method applied to phantoms in the context of narrow beams. A solid water phantom and a phantom containing a bone-equivalent material were irradiated on a 6 MV linac. The transmitted dose was measured by using one array of a 2D ion chamber detector. The dose reconstruction was obtained by an iterative algorithm. A phantom set-up error and organ interfraction motion were simulated to test the algorithm sensitivity. In all configurations convergence was obtained within three iterations. A local reconstructed dose agreement of at least 3% / 3mm with respect to the planned dose was obtained, except in a few points of the penumbra. The reconstructed primary fluences were consistent with the planned ones, which validates the whole reconstruction process. The results validate our method in a simple geometry and for narrow beams. The method is sensitive to a set-up error of a heterogeneous phantom and interfraction heterogeneous organ motion.

Sensitivity study to evaluate the dosimetric impact of off-axis ratio profiles misalignment on TomoTherapy second dose validation

Accurate dose planning and delivery are very important in the intensity modulated radiation therapy. For helical TomoTherapy dose validation, a TomoTherapy second check software, called MU-Tomo, has been developed using archived patient documents, initial coordinates and planned dose of the point of calculation, and common dosimetric functions. Based on this software, sensitivity studies on 50 patient cases have been evaluated to show the impact of off-axis ratio profile misalignment on point dose calculation. Off-axis ratio is defined as the dose profile normalized to its maximum dose value. Sensitivity studies were done for three scenarios: oscillating the fluctuation regions of two off-axis profiles, shifting the profiles, and rotating the profiles. The result of the oscillation trial is linear along the change of longitudinal off-axis ratio (OARy), while oscillating the lateral off-axis ratio (OARx) has little influence on the dose calculation. For shifting, the variation in the percentage difference from the non-shifting value is about 15 times larger in OARy modification than in OARx modification. Rotating OARx by +/- 6' gave less than 1.5% +/- 0.20% difference compared to the non-rotating value. Rotating OARy by +/- 1' changes the result more than 5% +/- 2.69%. Therefore, for helical TomoTherapy dose validation, commissioned OARy profiles are more sensitive than OARx to oscillation, shifting and rotating. As a result, different tolerances for OARx and OARy may be required for annual quality assurance.