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.

Influence of the jaw tracking technique on the dose calculation accuracy of small field VMAT plans.

PURPOSE: The aim of this study was to evaluate experimentally the accuracy of the dose calculation algorithm AcurosXB in small field highly modulated Volumetric Modulated Arc Therapy (VMAT). METHOD: The 1000SRS detector array inserted in the rotational Octavius 4D phantom (PTW) was used for 3D dose verification of VMAT treatments characterized by small to very small targets. Clinical treatment plans (n = 28) were recalculated on the phantom CT data set in the Eclipse TPS. All measurements were done on a Varian TrueBeamSTx, which can provide the jaw tracking technique (JTT). The effect of disabling the JTT, thereby fixing the jaws at static field size of 3 × 3 cm2 and applying the MLC to shape the smallest apertures, was investigated for static fields between 0.5 × 0.5-3 × 3 cm2 and for seven VMAT patients with small brain metastases. The dose calculation accuracy has been evaluated by comparing the measured and calculated dose outputs and dose distributions. The dosimetric agreement has been presented by a local gamma evaluation criterion of 2%/2 mm. RESULTS: Regarding the clinical plans, the mean ± SD of the volumetric gamma evaluation scores considering the dose levels for evaluation of 10%, 50%, 80% and 95% are (96.0 ± 6.9)%, (95.2 ± 6.8)%, (86.7 ± 14.8)% and (56.3 ± 42.3)% respectively. For the smallest field VMAT treatments, discrepancies between calculated and measured doses up to 16% are obtained. The difference between the 1000SRS central chamber measurements compared to the calculated dose outputs for static fields 3 × 3, 2 × 2, 1 × 1 and 0.5 × 0.5 cm2 collimated with MLC whereby jaws are fixed at 3 × 3 cm2 and for static fields shaped with the collimator jaws only (MLC retracted), is on average respectively, 0.2%, 0.8%, 6.8%, 5.7% (6 MV) and 0.1%, 1.3%, 11.7%, 21.6% (10 MV). For the seven brain mets patients was found that the smaller the target volumes, the higher the improvement in agreement between measured and calculated doses after disabling the JTT. CONCLUSION: Fixing the jaws at 3 × 3 cm2 and using the MLC with high positional accuracy to shape the smallest apertures in contrast to the JTT is currently found to be the most accurate treatment technique.

Accuracy of dose calculations on kV cone beam CT images of lung cancer patients.

PURPOSE: To develop a clinically feasible method for dose calculations on cone beam CT (CBCT) images of two different vendors, and to determine the accuracy of these dose calculations for lung cancer patients. METHODS: Lung cancer patients with CBCT imaging (n = 10 for Elekta, n = 6 for Varian) and a repeated planning CT scan on the same day were selected. For CBCT dose calculations, an adapted Hounsfield units-to-mass density table (HU table) was used which was obtained by comparing CT values of corresponding points on the CBCT and the repeated planning CT scan. Dose calculations with three different HU tables were compared: a patient-specific, a general thorax-CBCT, and the standard CT HU table. Planning CT data were used to compensate for the limited field of view (FOV) (Elekta) or scan length (Varian) of the CBCT. For evaluation, clinically relevant dose metrics were compared between the repeated CT and CBCT to assess the accuracy of dose calculations on CBCT for both vendors. RESULTS: For both vendors, isodose lines and dose volume histograms were very similar between dose calculation on CBCT and CT. For Varian, average differences between CT and CBCT dose calculations were 2%-3% for most dose metrics when the standard CT HU table was used. A better agreement was observed when a thorax-CBCT HU table was used, with differences of 1%-2%. No added value was found by using a patient-specific HU table, showing similar results as the general thorax-CBCT HU table. For Elekta, the dose metrics showed large deviations when the CT HU table was used, but using a patient-specific HU table resulted in similar accuracy as for Varian CBCT dose calculations, with average differences between repeated CT and CBCT dose metrics below 3%, and for most dose metrics even below 2%. CONCLUSIONS: Differences between Elekta and Varian CBCT, including hardware, reconstruction software, HU calibration, FOV, and scan length, resulted in different challenges for CBCT dose calculations for the different vendors. For Elekta CBCT scans, the procedure with a patient-specific HU table resulted in similar accuracy as for Varian CBCT dose calculations with a general HU correction for all thorax patients. The vendor-specific corrective methods used in this study resulted in dose calculations feasible for treatment re-evaluation for both Elekta and Varian CBCT scans.

The influence of gastric filling instructions on dose delivery in patients with oesophageal cancer: A prospective study.

PURPOSE: To evaluate whether adaptive radiotherapy for unaccounted stomach changes in patients with adenocarcinoma of the gastroesophageal junction (GEJ) is necessary and whether dose differences could be prevented by giving patients food and fluid instructions before treatment simulation and radiotherapy. MATERIAL AND METHODS: Twenty patients were randomly assigned into two groups: patients with and without instructions about restricting food and fluid intake prior to radiotherapy simulation and treatment. Redelineation and offline recalculation of dose distributions based on cone-beam computed tomography (n=100) were performed. Dose-volume parameters were analysed for the clinical target volume extending into the stomach. RESULTS: Four patients who did not receive instructions had a geometric miss (0.7-12 cm(3)) in only one fraction. With instructions, 3 out of 10 patients had a geometric miss (0.1-1.9 cm(3)) in one (n=2) or two (n=1) fractions. The V95% was reduced by more than 5% for one patient, but this underdosage was in an in-air region without further clinical importance. CONCLUSIONS: Giving patients food and fluid instructions for the treatment of GEJ cancer offers no clinical benefit. Using a planning target volume margin of 1cm implies that there is no need for adaptive radiotherapy for GEJ tumours.

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.

Benefits of a clinical data warehouse with data mining tools to collect data for a radiotherapy trial.

INTRODUCTION: Collecting trial data in a medical environment is at present mostly performed manually and therefore time-consuming, prone to errors and often incomplete with the complex data considered. Faster and more accurate methods are needed to improve the data quality and to shorten data collection times where information is often scattered over multiple data sources. The purpose of this study is to investigate the possible benefit of modern data warehouse technology in the radiation oncology field. MATERIAL AND METHODS: In this study, a Computer Aided Theragnostics (CAT) data warehouse combined with automated tools for feature extraction was benchmarked against the regular manual data-collection processes. Two sets of clinical parameters were compiled for non-small cell lung cancer (NSCLC) and rectal cancer, using 27 patients per disease. Data collection times and inconsistencies were compared between the manual and the automated extraction method. RESULTS: The average time per case to collect the NSCLC data manually was 10.4 ± 2.1 min and 4.3 ± 1.1 min when using the automated method (p<0.001). For rectal cancer, these times were 13.5 ± 4.1 and 6.8 ± 2.4 min, respectively (p<0.001). In 3.2% of the data collected for NSCLC and 5.3% for rectal cancer, there was a discrepancy between the manual and automated method. CONCLUSIONS: Aggregating multiple data sources in a data warehouse combined with tools for extraction of relevant parameters is beneficial for data collection times and offers the ability to improve data quality. The initial investments in digitizing the data are expected to be compensated due to the flexibility of the data analysis. Furthermore, successive investigations can easily select trial candidates and extract new parameters from the existing databases.

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 combined dose calculation and verification method for a small animal precision irradiator based on onboard imaging.

PURPOSE: Novel small animal precision microirradiators (micro-IR) are becoming available for preclinical use and are often equipped with onboard imaging (OBI) devices. We investigated the use of OBI as a means to infer the accuracy of the delivered treatment plan. METHODS: Monte Carlo modeling of the micro-IR including an elliptical Gaussian electron beam incident on the x-ray tube was used to score dose and to continue photon transport to the plane of the OBI device. A model of the OBI detector response was used to generate simulated onboard images. Experimental OBI was performed at 225 kVp, gain∕offset and scatter-glare were corrected. Simulated and experimentally obtained onboard images of phantoms and a mouse specimen were compared for a range of photon beam sizes from 2.5 cm down to 0.1 cm. RESULTS: Simulated OBI can be used in small animal radiotherapy to determine if a treatment plan was delivered according to the prescription within an uncertainty of 5% for beams as small as 4 mm in diameter. For collimated beams smaller than 4 mm, beam profile differences remain primarily in the penumbra region of the smallest beams, which may be tolerable for specific preclinical micro-IR investigations. CONCLUSIONS: Comparing simulated to acquired OBI during small animal treatment radiotherapy represents a useful treatment delivery tool.

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.

3D in vivo dosimetry using megavoltage cone-beam CT and EPID dosimetry.

PURPOSE: To develop a method that reconstructs, independently of previous (planning) information, the dose delivered to patients by combining in-room imaging with transit dose measurements during treatment. METHODS AND MATERIALS: A megavoltage cone-beam CT scan of the patient anatomy was acquired with the patient in treatment position. During treatment, delivered fields were measured behind the patient with an electronic portal imaging device. The dose information in these images was back-projected through the cone-beam CT scan and used for Monte Carlo simulation of the dose distribution inside the cone-beam CT scan. Validation was performed using various phantoms for conformal and IMRT plans. Clinical applicability is shown for a head-and-neck cancer patient treated with IMRT. RESULTS: For single IMRT beams and a seven-field IMRT step-and-shoot plan, the dose distribution was reconstructed within 3%/3mm compared with the measured or planned dose. A three-dimensional conformal plan, verified using eight point-dose measurements, resulted in a difference of 1.3 +/- 3.3% (1 SD) compared with the reconstructed dose. For the patient case, planned and reconstructed dose distribution was within 3%/3mm for about 95% of the points within the 20% isodose line. Reconstructed mean dose values, obtained from dose-volume histograms, were within 3% of prescribed values for target volumes and normal tissues. CONCLUSIONS: We present a new method that verifies the dose delivered to a patient by combining in-room imaging with the transit dose measured during treatment. This verification procedure opens possibilities for offline adaptive radiotherapy and dose-guided radiotherapy strategies taking into account the dose distribution delivered during treatment sessions.

A literature review of electronic portal imaging for radiotherapy dosimetry.

Electronic portal imaging devices (EPIDs) have been the preferred tools for verification of patient positioning for radiotherapy in recent decades. Since EPID images contain dose information, many groups have investigated their use for radiotherapy dose measurement. With the introduction of the amorphous-silicon EPIDs, the interest in EPID dosimetry has been accelerated because of the favourable characteristics such as fast image acquisition, high resolution, digital format, and potential for in vivo measurements and 3D dose verification. As a result, the number of publications dealing with EPID dosimetry has increased considerably over the past approximately 15 years. The purpose of this paper was to review the information provided in these publications. Information available in the literature included dosimetric characteristics and calibration procedures of various types of EPIDs, strategies to use EPIDs for dose verification, clinical approaches to EPID dosimetry, ranging from point dose to full 3D dose distribution verification, and current clinical experience. Quality control of a linear accelerator, pre-treatment dose verification and in vivo dosimetry using EPIDs are now routinely used in a growing number of clinics. The use of EPIDs for dosimetry purposes has matured and is now a reliable and accurate dose verification method that can be used in a large number of situations. Methods to integrate 3D in vivo dosimetry and image-guided radiotherapy (IGRT) procedures, such as the use of kV or MV cone-beam CT, are under development. It has been shown that EPID dosimetry can play an integral role in the total chain of verification procedures that are implemented in a radiotherapy department. It provides a safety net for simple to advanced treatments, as well as a full account of the dose delivered. Despite these favourable characteristics and the vast range of publications on the subject, there is still a lack of commercially available solutions for EPID dosimetry. As strategies evolve and commercial products become available, EPID dosimetry has the potential to become an accurate and efficient means of large-scale patient-specific IMRT dose verification for any radiotherapy department.

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.

The next step in patient-specific QA: 3D dose verification of conformal and intensity-modulated RT based on EPID dosimetry and Monte Carlo dose calculations.

BACKGROUND AND PURPOSE: A method was evaluated to reconstruct the 3D dose distribution in patients using their planning CT-scan in combination with a Monte Carlo calculation, and the energy fluence of the actual treatment beams measured pre-treatment with an EPID without the patient or a phantom in the beam. MATERIALS AND METHODS: Nine plans of lung cancer patients treated with a 3D conformal technique, calculated using a simple convolution algorithm (CA), as well as five IMRT treatments of head-and-neck cancer patients, calculated with a more advanced superposition algorithm (SA), were verified. Differences between planned and reconstructed dose distributions were quantified in terms of DVH parameters. RESULTS: For the lung cancer group, differences between the reconstructed mean PTV dose and the values calculated with the TPS were 5.0+/-4.2% (1SD) and -1.4+/-1.5% for the CA and SA algorithm, respectively. No large differences in the lung and spinal cord DVH parameters were found. For the IMRT treatments, the average dose differences in the PTV were generally below 3%. The reconstructed mean parotid gland dose was 3.2+/-1.2% lower, while the maximum spinal cord dose was on average 3.1+/-1.9% higher. CONCLUSIONS: EPID dosimetry combined with 3D dose reconstruction is a useful procedure for patient-specific QA of complex treatments. DVH parameters can be used to interpret the dose distribution delivered to the patient in the same way as during standard treatment plan evaluation.