Automatic dose verification system for breast radiotherapy: Method validation, contour propagation and DVH parameters evaluation.

PURPOSE: Image guided radiotherapy (IGRT) strategies allow detecting and monitoring anatomical changes during external beam radiotherapy (EBRT). However, assessing the dosimetric impact of anatomical changes is not straightforward. In current IGRT strategies dose volume histograms (DVH) are not available due to lack of contours and dose recalculations on the cone-beam CT (CBCT) scan. This study investigates the feasibility of using automatically calculated DVH parameters in CBCTs using an independent dose calculation engine and propagated contours. METHOD: A prospective study (NCT03385031) of thirty-one breast cancer patients who received additional CBCT imaging (N = 70) was performed. Manual and automatically propagated contours were generated for all CBCTs and an automatic dose recalculation was performed. Differences between planned and CBCT-derived DVH parameters (mean and maximum dose to targets, 95% volume coverage to targets and mean heart dose (MHD)) were calculated using the dose verification system with manual and propagated contours and, in both cases, benchmarked against DVH differences quantified in the TPS using manually contoured CBCTs. RESULTS: Differences in DVH parameters between the TPS and dose verification system with propagated contours were -1.3% to 0.7% (95% CI) for mean dose to the target volume, -0.3 to 0.2 Gy (95% CI) in MHD and -3.9% to 2.9% (95% CI) in target volume coverage. CONCLUSION: The use of an independent fully automatic dose verification system with contour propagation showed to be feasible and sufficiently reliable to recalculate CBCT based DVHs during breast EBRT. Volume coverage parameters, i.e. V95%, proved to be especially sensitive to contouring differences.

External validation of a hidden Markov model for gamma-based classification of anatomical changes in lung cancer patients using EPID dosimetry.

PURPOSE: To externally validate a hidden Markov model (HMM) for classifying gamma analysis results of in vivo electronic portal imaging device (EPID) measurements into different categories of anatomical change for lung cancer patients. Additionally, the relationship between HMM classification and deviations in dose-volume histogram (DVH) metrics was evaluated. METHODS: The HMM was developed at CHU de Québec (CHUQ), and trained on features extracted from gamma analysis maps of in vivo EPID measurements from 483 fractions (24 patients, treated with three-dimensional 3D-CRT or intensity modulated radiotherapy), using the EPID measurement of the first treatment fraction as reference. The model inputs were the average gamma value, standard deviation, and average value of the highest 1% of gamma values, all averaged over all beams in a fraction. The HMM classified each fraction into one of three categories: no anatomical change (Category 1), some anatomical change (no clinical action needed, Category 2) and severe anatomical change (clinical action needed, Category 3). The external validation dataset consisted of EPID measurements from 263 fractions of 30 patients treated at Maastro with volumetric modulated arc therapy (VMAT) or hybrid plans (containing both static beams and VMAT arcs). Gamma analysis features were extracted in the same way as in the CHUQ dataset, by using the EPID measurement of the first fraction as reference (γQ), and additionally by using an EPID dose prediction as reference (γM). For Maastro patients, cone beam computed tomography (CBCT) scans and image-guided radiotherapy (IGRT) classification of these images were available for each fraction. Contours were propagated from the planning CT to the CBCTs, and the dose was recalculated using a Monte Carlo dose engine. Dose-volume histogram metrics for targets and organs-at-risk (OARs: lungs, heart, mediastinum, spinal cord, brachial plexus) were extracted for each fraction, and compared to the planned dose. HMM classification of the external validation set was compared to threshold classification based on the average gamma value alone (a surrogate for clinical classification at CHUQ), IGRT classification as performed at Maastro, and differences in DVH metrics extracted from 3D dose recalculations on the CBCTs. RESULTS: The HMM achieved 65.4%/65.0% accuracy for γQ and γM, respectively, compared to average gamma threshold classification. When comparing HMM classification with IGRT classification, the overall accuracy was 29.7% for γQ and 23.2% for γM. Hence, HMM classification and IGRT classification of anatomical changes did not correspond. However, there is a trend towards higher deviations in DVH metrics with classification into higher categories by the HMM for large OARs (lungs, heart, mediastinum), but not for the targets and small OARs (spinal cord, brachial plexus). CONCLUSION: The external validation shows that transferring the HMM for anatomical change classification to a different center is challenging, but can still be valuable. The HMM trained at CHUQ cannot be used directly to classify anatomical changes in the Maastro data. However, it may be possible to use the model in a different capacity, as an indicator for changes in the 3D dose based on two-dimensional EPID measurements.

Should dose from small fields be limited for dose verification procedures?: uncertainty versus small field dose in VMAT treatments.

Over the years, radiotherapy treatments have become more complex and conformal, leading to an increased use of small field segments in volumetric modulated arc therapy (VMAT) arcs. The impact of small field dose inaccuracy on dose verification methods has not been studied yet. The aim of this work is therefore to quantify the relationship between the uncertainty of a 2D pre-treatment dose prediction model and the proportion of dose coming from small fields in VMAT arcs for a range of clinical plans. The model evaluated in this work predicts 2D portal dose images (PDIs) without a patient or phantom in the beam. The uncertainty of the model was calculated through simulation of model parameter deviations. The proportion of dose from small fields in a VMAT arc was determined by comparing a PDI with only dose from small fields with the original PDI. The uncertainty and proportion of dose from small fields were calculated for 109 VMAT arcs (41 head and neck, 33 lung, 35 prostate). The correlation was assessed with a linear regression. There is a statistically significant positive correlation between the uncertainty of the model and the proportion of dose from small fields in a VMAT arc, for each treatment site individually, as well as for all tumor sites together. The strongest relationship is found for the prostate cases. As there is a positive relationship between the uncertainty of the 2D pre-treatment dose prediction model, it may be wise to limit the dose from small fields in VMAT arcs, to avoid additional uncertainty in the dose verification process.

Validation and uncertainty analysis of a pre-treatment 2D dose prediction model.

Independent verification of complex treatment delivery with megavolt photon beam radiotherapy (RT) has been effectively used to detect and prevent errors. This work presents the validation and uncertainty analysis of a model that predicts 2D portal dose images (PDIs) without a patient or phantom in the beam. The prediction model is based on an exponential point dose model with separable primary and secondary photon fluence components. The model includes a scatter kernel, off-axis ratio map, transmission values and penumbra kernels for beam-delimiting components. These parameters were derived through a model fitting procedure supplied with point dose and dose profile measurements of radiation fields. The model was validated against a treatment planning system (TPS; Eclipse) and radiochromic film measurements for complex clinical scenarios, including volumetric modulated arc therapy (VMAT). Confidence limits on fitted model parameters were calculated based on simulated measurements. A sensitivity analysis was performed to evaluate the effect of the parameter uncertainties on the model output. For the maximum uncertainty, the maximum deviating measurement sets were propagated through the fitting procedure and the model. The overall uncertainty was assessed using all simulated measurements. The validation of the prediction model against the TPS and the film showed a good agreement, with on average 90.8% and 90.5% of pixels passing a (2%,2 mm) global gamma analysis respectively, with a low dose threshold of 10%. The maximum and overall uncertainty of the model is dependent on the type of clinical plan used as input. The results can be used to study the robustness of the model. A model for predicting accurate 2D pre-treatment PDIs in complex RT scenarios can be used clinically and its uncertainties can be taken into account.

Three-dimensional dose evaluation in breast cancer patients to define decision criteria for adaptive radiotherapy.

BACKGROUND: Dose-guided adaptive radiation therapy (DGART) is the systematic evaluation and adaptation of the dose delivery during treatment for an individual patient. The aim of this study is to define quantitative action levels for DGART by evaluating changes in 3D dose metrics in breast cancer and correlate them with clinical expert evaluation. MATERIAL AND METHODS: Twenty-three breast cancer treatment plans were evaluated, that were clinically adapted based on institutional IGRT guidelines. Reasons for adaptation were variation in seroma, hematoma, edema, positioning or problems using voluntary deep inspiration breath hold. Sixteen patients received a uniform dose to the breast (clinical target volume 1; CTV1). Six patients were treated with a simultaneous integrated boost to CTV2. The original plan was copied to the CT during treatment (re-CT) or to the stitched cone-beam CT (CBCT). Clinical expert evaluation of the re-calculated dose distribution and extraction of dose-volume histogram (DVH) parameters were performed. The extreme scenarios were evaluated, assuming all treatment fractions were given to the original planning CT (pCT), re-CT or CBCT. Reported results are mean ± SD. RESULTS: DVH results showed a mean dose (Dmean) difference between pCT and re-CT of -0.4 ± 1.4% (CTV1) and -1.4 ± 2.1% (CTV2). The difference in V95% was -2.6 ± 4.4% (CTV1) and -9.8 ± 8.3% (CTV2). Clinical evaluation and DVH evaluation resulted in a recommended adaptation in 17/23 or 16/23 plans, respectively. Applying thresholds on the DVH parameters: Dmean CTV, V95% CTV, Dmax, mean lung dose, volume exceeding 107% (uniform dose) or 90% (SIB) of the prescribed dose enabled the identification of patients with an assumed clinically relevant dose difference, with a sensitivity of 0.89 and specificity of 1.0. Re-calculation on CBCT imaging identified the same plans for adaptation as re-CT imaging. CONCLUSIONS: Clinical expert evaluation can be related to quantitative DVH parameters on re-CT or CBCT imaging to select patients for DGART.

Detection of anatomical changes in lung cancer patients with 2D time-integrated, 2D time-resolved and 3D time-integrated portal dosimetry: a simulation study.

The aim of this work is to assess the performance of 2D time-integrated (2D-TI), 2D time-resolved (2D-TR) and 3D time-integrated (3D-TI) portal dosimetry in detecting dose discrepancies between the planned and (simulated) delivered dose caused by simulated changes in the anatomy of lung cancer patients. For six lung cancer patients, tumor shift, tumor regression and pleural effusion are simulated by modifying their CT images. Based on the modified CT images, time-integrated (TI) and time-resolved (TR) portal dose images (PDIs) are simulated and 3D-TI doses are calculated. The modified and original PDIs and 3D doses are compared by a gamma analysis with various gamma criteria. Furthermore, the difference in the D 95% (ΔD 95%) of the GTV is calculated and used as a gold standard. The correlation between the gamma fail rate and the ΔD 95% is investigated, as well the sensitivity and specificity of all combinations of portal dosimetry method, gamma criteria and gamma fail rate threshold. On the individual patient level, there is a correlation between the gamma fail rate and the ΔD 95%, which cannot be found at the group level. The sensitivity and specificity analysis showed that there is not one combination of portal dosimetry method, gamma criteria and gamma fail rate threshold that can detect all simulated anatomical changes. This work shows that it will be more beneficial to relate portal dosimetry and DVH analysis on the patient level, rather than trying to quantify a relationship for a group of patients. With regards to optimizing sensitivity and specificity, different combinations of portal dosimetry method, gamma criteria and gamma fail rate should be used to optimally detect certain types of anatomical changes.

Is integrated transit planar portal dosimetry able to detect geometric changes in lung cancer patients treated with volumetric modulated arc therapy?

BACKGROUND: Geometric changes are frequent during the course of treatment of lung cancer patients. This may potentially result in deviations between the planned and actual delivered dose. Electronic portal imaging device (EPID)-based integrated transit planar portal dosimetry (ITPD) is a fast method for absolute in-treatment dose verification. The aim of this study was to investigate if ITPD could detect geometric changes in lung cancer patients. MATERIALS AND METHODS: A total of 460 patients treated with volumetric modulated arc therapy (VMAT) following daily cone beam computed tomography (CT)-based setup were visually inspected for geometrical changes on a daily basis. Forty-six patients were subject to changes and had a re-CT and an adaptive treatment plan. The reasons for adaptation were: change in atelectasis (n = 18), tumor regression (n = 9), change in pleural effusion (n = 8) or other causes (n = 11). The ITPDs were calculated on both the initial planning CT and the re-CT and compared with a global gamma (γ) evaluation (criteria: 3%\3mm). A treatment fraction failed when the percentage of pixels failing in the radiation fields exceeded 10%. Dose-volume histograms (DVHs) were compared between the initial plan versus the plan re-calculated on the re-CT. RESULTS: The ITPD threshold method detected 76% of the changes in atelectasis, while only 50% of the tumor regression cases and 42% of the pleural effusion cases were detected. Only 10% of the cases adapted for other reasons were detected with ITPD. The method has a 17% false-positive rate. No significant correlations were found between changes in DVH metrics and γ fail-rates. CONCLUSIONS: This study showed that most cases with geometric changes caused by atelectasis could be captured by ITPD, however for other causes ITPD is not sensitive enough to detect the clinically relevant changes and no predictive power of ITPD was found.

Time dependent pre-treatment EPID dosimetry for standard and FFF VMAT.

Methods to calibrate Megavoltage electronic portal imaging devices (EPIDs) for dosimetry have been previously documented for dynamic treatments such as intensity modulated radiotherapy (IMRT) using flattened beams and typically using integrated fields. While these methods verify the accumulated field shape and dose, the dose rate and differential fields remain unverified. The aim of this work is to provide an accurate calibration model for time dependent pre-treatment dose verification using amorphous silicon (a-Si) EPIDs in volumetric modulated arc therapy (VMAT) for both flattened and flattening filter free (FFF) beams. A general calibration model was created using a Varian TrueBeam accelerator, equipped with an aS1000 EPID, for each photon spectrum 6 MV, 10 MV, 6 MV-FFF, 10 MV-FFF. As planned VMAT treatments use control points (CPs) for optimization, measured images are separated into corresponding time intervals for direct comparison with predictions. The accuracy of the calibration model was determined for a range of treatment conditions. Measured and predicted CP dose images were compared using a time dependent gamma evaluation using criteria (3%, 3 mm, 0.5 sec). Time dependent pre-treatment dose verification is possible without an additional measurement device or phantom, using the on-board EPID. Sufficient data is present in trajectory log files and EPID frame headers to reliably synchronize and resample portal images. For the VMAT plans tested, significantly more deviation is observed when analysed in a time dependent manner for FFF and non-FFF plans than when analysed using only the integrated field. We show EPID-based pre-treatment dose verification can be performed on a CP basis for VMAT plans. This model can measure pre-treatment doses for both flattened and unflattened beams in a time dependent manner which highlights deviations that are missed in integrated field verifications.

First clinical results of adaptive radiotherapy based on 3D portal dosimetry for lung cancer patients with atelectasis treated with volumetric-modulated arc therapy (VMAT).

UNLABELLED: Atelectasis in lung cancer patients can change rapidly during a treatment course, which may displace the tumor/healthy tissues, or change tissue densities locally. This may result in differences between the planned and the actually delivered dose. With complex delivery techniques treatment verification is essential and inter-fractional adaptation may be necessary. We present the first clinical results of treatment adaptation based on an in-house developed three-dimensional (3D) portal dose measurement (PDM) system. MATERIAL AND METHODS: A method was developed for 3D PDM combined with cone beam computed tomography (kV-CBCT) imaging. Lung cancer patients are monitored routinely with this imaging technique. During treatment, the first three fractions are analyzed with 3D PDM and weekly thereafter. The reconstructed measured dose is compared to the planned dose using dose-volume histograms and a γ evaluation. Patients having |γ|> 1 in more than 5% of the (primary tumor or organ at risk) volume were subjected to further analysis. In this study we show the PDM dose changes for five patients. RESULTS: We detected relevant dose changes induced by changes in atelectasis in the presented cases. Two patients received two treatment adaptations after being detected with PDM confirmed by visual inspection of the kV-CBCTs, and in two other patients the radiation treatment plan was adapted once. In one case no dose delivery change was detected with PDM. CONCLUSION: The first clinical patients show that 3D PDM combined with kV-CBCT is a valuable quality assurance tool for detecting anatomical alterations and their dosimetric consequences during the course of radiotherapy. In our clinic, 3D PDM is fully automated for ease and speed of the procedure, and for minimization of human error. The technique is able to flag patients with suspected dose discrepancies for potential adaptation of the treatment plan.

Measured vs simulated portal images for low MU fields on three accelerator types: possible consequences for 2D portal dosimetry.

PURPOSE: As external beam treatment plans become more dynamic and the dose to normal tissue is further constrained, treatments may consist of a larger number of beams, each delivering smaller doses (or monitor units, MU), in, e.g., volumetric modulated arc therapy (VMAT). Electronic portal imaging devices (EPID) may be used to verify external beam treatments on integrated fractions as well as in a more time dependent manner such as field by field. For treatment verification performed during a fraction (e.g., individual fields or VMAT control points), the lower limit of EPID measurement capability becomes important. The authors quantified the signal and timing accuracy of EPID images for low MU intensity modulated radiotherapy (IMRT) and conformal fields. METHODS: EPID images were collected from three different vendor's accelerators for low MU fields and compared to expected images. Simulations were performed to replicate the EPID acquisition pattern and to enhance the understanding of EPID readout schemes. RESULTS: Large discrepancies between observed and predicted images were noted due to an under-response to single low MU fields. It is shown that a variability of up to 37% can be observed for low MU fields in clinically used EPID acquisition modes and that the majority of this variability can be accounted for by the readout scheme, integration, and timing of EPID acquisitions. Simulations have confirmed the causes of the discrepancies. The occurrence and extent of the variation has been estimated for clinical settings. CONCLUSIONS: Incorrect absolute EPID signals collected for low MU fields in external beam treatments will negatively affect quantitative applications such as individual field based EPID dosimetry, typically appearing as an underdose, unless corrections to currently employed EPID readout schemes are made.

A fast three-dimensional gamma evaluation using a GPU utilizing texture memory for on-the-fly interpolations.

PURPOSE: A widely accepted method to quantify differences in dose distributions is the gamma (gamma) evaluation. Currently, almost all gamma implementations utilize the central processing unit (CPU). Recently, the graphics processing unit (GPU) has become a powerful platform for specific computing tasks. In this study, we describe the implementation of a 3D gamma evaluation using a GPU to improve calculation time. METHODS: The gamma evaluation algorithm was implemented on an NVIDIA Tesla C2050 GPU using the compute unified device architecture (CUDA). First, several cubic virtual phantoms were simulated. These phantoms were tested with varying dose cube sizes and set-ups, introducing artificial dose differences. Second, to show applicability in clinical practice, five patient cases have been evaluated using the 3D dose distribution from a treatment planning system as the reference and the delivered dose determined during treatment as the comparison. A calculation time comparison between the CPU and GPU was made with varying thread-block sizes including the option of using texture or global memory. RESULTS: A GPU over CPU speed-up of 66 +/- 12 was achieved for the virtual phantoms. For the patient cases, a speed-up of 57 +/- 15 using the GPU was obtained. A thread-block size of 16 x 16 performed best in all cases. The use of texture memory improved the total calculation time, especially when interpolation was applied. Differences between the CPU and GPU gammas were negligible. CONCLUSIONS: The GPU and its features, such as texture memory, decreased the calculation time for gamma evaluations considerably without loss of accuracy.

Calibration of megavoltage cone-beam CT for radiotherapy dose calculations: correction of cupping artifacts and conversion of CT numbers to electron density.

Megavoltage cone-beam CT (MV CBCT) is used for three-dimensional imaging of the patient anatomy on the treatment table prior to or just after radiotherapy treatment. To use MV CBCT images for radiotherapy dose calculation purposes, reliable electron density (ED) distributions are needed. Patient scatter, beam hardening and softening effects result in cupping artifacts in MV CBCT images and distort the CT number to ED conversion. A method based on transmission images is presented to correct for these effects without using prior knowledge of the object's geometry. The scatter distribution originating from the patient is calculated with pencil beam scatter kernels that are fitted based on transmission measurements. The radiological thickness is extracted from the scatter subtracted transmission images and is then converted to the primary transmission used in the cone-beam reconstruction. These corrections are performed in an iterative manner, without using prior knowledge regarding the geometry and composition of the object. The method was tested using various homogeneous and inhomogeneous phantoms with varying shapes and compositions, including a phantom with different electron density inserts, phantoms with large density variations, and an anthropomorphic head phantom. For all phantoms, the cupping artifact was substantially removed from the images and a linear relation between the CT number and electron density was found. After correction the deviations in reconstructed ED from the true values were reduced from up to 0.30 ED units to 0.03 for the majority of the phantoms; the residual difference is equal to the amount of noise in the images. The ED distributions were evaluated in terms of absolute dose calculation accuracy for homogeneous cylinders of different size; errors decreased from 7% to below 1% in the center of the objects for the uncorrected and corrected images, respectively, and maximum differences were reduced from 17% to 2%, respectively. The presented method corrects the MV CBCT images for cupping artifacts and extracts reliable ED information of objects with varying geometries and composition, making these corrected MV CBCT images suitable for accurate dose calculation purposes.

Treatment verification in the presence of inhomogeneities using EPID-based three-dimensional dose reconstruction.

Treatment verification is a prerequisite for the verification of complex treatments, checking both the treatment planning process and the actual beam delivery. Pretreatment verification can detect errors introduced by the treatment planning system (TPS) or differences between planned and delivered dose distributions. In a previous paper we described the reconstruction of three-dimensional (3-D) dose distributions in homogeneous phantoms using an in-house developed model based on the beams delivered by the linear accelerator measured with an amorphous silicon electronic portal imaging device (EPID), and a dose calculation engine using the Monte Carlo code XVMC. The aim of the present study is to extend the method to situations in which tissue inhomogeneities are present and to make a comparison with the dose distributions calculated by the TPS. Dose distributions in inhomogeneous phantoms, calculated using the fast-Fourier transform convolution (FFTC) and multigrid superposition (MGS) algorithms present in the TPS, were verified using the EPID-based dose reconstruction method and compared to film and ionization chamber measurements. Differences between dose distributions were evaluated using the gamma-evaluation method (3%/3 mm) and expressed as a mean gamma and the percentage of points with gamma> 1 (P(gamma>1)). For rectangular inhomogeneous phantoms containing a low-density region, the differences between film and reconstructed dose distributions were smaller than 3%. In low-density regions there was an overestimation of the planned dose using the FFTC and MGS algorithms of the TPS up to 20% and 8%, respectively, for a 10 MV photon beam and a 3 x 3 cm2 field. For lower energies and larger fields (6 MV, 5 x 5 cm2), these differences reduced to 6% and 3%, respectively. Dose reconstruction performed in an anthropomorphic thoracic phantom for a 3-D conformal and an IMRT plan, showed good agreement between film data and reconstructed dose values (P(gamma>1) <6%). The algorithms of the TPS underestimated the dose in the low-dose regions outside the treatment field, due to an implementation error of the jaws and multileaf collimator of the linac in the TPS. The FFTC algorithm of the TPS showed differences up to 6% or 6 mm at the interface between lung and breast. Two intensity-modulated radiation therapy head and neck plans, reconstructed in a commercial phantom having a bone-equivalent insert and an air cavity, showed good agreement between film measurement, reconstructed and planned dose distributions using the FFTC and MGS algorithm, except in the bone-equivalent regions where both TPS algorithms underestimated the dose with 4%. Absolute dose verification was performed at the isocenter where both planned and reconstructed dose were within 2% of the measured dose. Reproducibility for the EPID measurements was assessed and found to be of negligible influence on the reconstructed dose distribution. Our 3-D dose verification approach is based on the actual dose measured with an EPID in combination with a Monte Carlo dose engine, and therefore independent of a TPS. Because dose values are reconstructed in 3-D, isodose surfaces and dose-volume histograms can be used to detect dose differences in target volume and normal tissues. Using our method, the combined planning and treatment delivery process is verified, offering an easy to use tool for the verification of complex treatments.

Routine individualised patient dosimetry using electronic portal imaging devices.

BACKGROUND AND PURPOSE: To analyse the results of routine EPID measurements for individualised patient dosimetry. MATERIALS AND METHODS: Calibrated camera-based EPIDs were used to measure the central field dose, which was compared with a dose prediction at the EPID level. For transit dosimetry, dose data were calculated using patient transmission and scatter, and compared with measured values. Furthermore, measured transit dose data were back-projected to an in vivo dose value at 5 cm depth in water (D(5)) and directly compared with D(5) from the treatment planning system. Dose differences per treatment session were calculated by weighting dose values with the number of monitor units per beam. Reported errors were categorised and analysed for approximately 37,500 images from 2511 patients during a period of 24 months. RESULTS: Pre-treatment measurements showed a mean dose difference per treatment session of 0.0+/-1.7% (1 SD). Transfer errors were detected and corrected prior to the first treatment session. An accelerator output variation of about 4% was found between two weekly QC measurements. Patient dosimetry showed mean transit and D(5) dose differences of -0.7+/-5.2% (1 SD) and -0.3+/-5.6% (1 SD) per treatment session, respectively. Dose differences could be related to set-up errors, organ motion, erroneous density corrections and changes in patient anatomy. CONCLUSIONS: EPIDs can be used routinely to accurately verify treatment parameter transfer and machine output. By applying transit and in vivo dosimetry, more insight can be obtained with respect to the different error sources influencing dose delivery to a patient.

A Monte Carlo based three-dimensional dose reconstruction method derived from portal dose images.

The verification of intensity-modulated radiation therapy (IMRT) is necessary for adequate quality control of the treatment. Pretreatment verification may trace the possible differences between the planned dose and the actual dose delivered to the patient. To estimate the impact of differences between planned and delivered photon beams, a three-dimensional (3-D) dose verification method has been developed that reconstructs the dose inside a phantom. The pretreatment procedure is based on portal dose images measured with an electronic portal imaging device (EPID) of the separate beams, without the phantom in the beam and a 3-D dose calculation engine based on the Monte Carlo calculation. Measured gray scale portal images are converted into portal dose images. From these images the lateral scattered dose in the EPID is subtracted and the image is converted into energy fluence. Subsequently, a phase-space distribution is sampled from the energy fluence and a 3-D dose calculation in a phantom is started based on a Monte Carlo dose engine. The reconstruction model is compared to film and ionization chamber measurements for various field sizes. The reconstruction algorithm is also tested for an IMRT plan using 10 MV photons delivered to a phantom and measured using films at several depths in the phantom. Depth dose curves for both 6 and 10 MV photons are reconstructed with a maximum error generally smaller than 1% at depths larger than the buildup region, and smaller than 2% for the off-axis profiles, excluding the penumbra region. The absolute dose values are reconstructed to within 1.5% for square field sizes ranging from 5 to 20 cm width. For the IMRT plan, the dose was reconstructed and compared to the dose distribution with film using the gamma evaluation, with a 3% and 3 mm criterion. 99% of the pixels inside the irradiated field had a gamma value smaller than one. The absolute dose at the isocenter agreed to within 1% with the dose measured with an ionization chamber. It can be concluded that our new dose reconstruction algorithm is able to reconstruct the 3-D dose distribution in phantoms with a high accuracy. This result is obtained by combining portal dose images measured prior to treatment with an accurate dose calculation engine.