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This study reports the development and validation of a model-based, 3D patient dose reconstruction method for pre-treatment quality assurance using EPID images. The method is also investigated for sensitivity to potential MLC delivery errors. Each cine-mode EPID image acquired during plan delivery was processed using a previously developed back-projection dose reconstruction model providing a 3D dose estimate on the CT simulation data. Validation was carried out using 24 SBRT-VMAT patient plans by comparing: (1) ion chamber point dose measurements in a solid water phantom, (2) the treatment planning system (TPS) predicted 3D dose to the EPID reconstructed 3D dose in a solid water phantom, and (3) the TPS predicted 3D dose to the EPID and our forward predicted reconstructed 3D dose in the patient (CT data). AAA and AcurosXB were used for TPS predictions. Dose distributions were compared using 3%/3 mm (95% tolerance) and 2%/2 mm (90% tolerance) γ-tests in the planning target volume (PTV) and 20% dose volumes. The average percentage point dose differences between the ion chamber and the EPID, AcurosXB, and AAA were 0.73 ± 1.25%, 0.38 ± 0.96% and 1.06 ± 1.34% respectively. For the patient (CT) dose comparisons, seven (3%/3 mm) and nine (2%/2 mm) plans failed the EPID versus AAA. All plans passed the EPID versus Acuros XB and the EPID versus forward model γ-comparisons. Four types of MLC sensitive errors (opening, shifting, stuck, and retracting), of varying magnitude (0.2, 0.5, 1.0, 2.0 mm), were introduced into six different SBRT-VMAT plans. γ-comparisons of the erroneous EPID dose and original predicted dose were carried out using the same criteria as above. For all plans, the sensitivity testing using a 3%/3 mm γ-test in the PTV successfully determined MLC errors on the order of 1.0 mm, except for the single leaf retraction-type error. A 2%/2 mm criteria produced similar results with two more additional detected errors.

Purpose: PARETO (Pareto‐Aware Radiotherapy Evolutionary Treatment Optimization) is a novel multiobjective treatment planning system that performs beam orientation and fluence optimization simultaneously using an advanced evolutionary algorithm. In order to reduce the number of parameters involved in this enormous search space, we present several methods for modeling the beam fluence. The parameterizations are compared using innovative tools that evaluate fluence complexity, solution quality, and run efficiency. Methods: A PARETO run is performed using the basic weight (BW), linear gradient (LG), cosine transform (CT), beam group (BG), and isodose‐projection (IP) methods for applying fluence modulation over the projection of the Planning Target Volume in the beam's‐eye‐view plane. The solutions of each run are non‐dominated with respect to other trial solutions encountered during the run. However, to compare the solution quality of independent runs, each run competes against every other run in a round robin fashion. Score is assigned based on the fraction of solutions that survive when a tournament selection operator is applied to the solutions of the two competitors. To compare fluence complexity, a modulation index, fractal dimension, and image gradient entropy are calculated for the fluence maps of each optimal plan. Results: We have found that the LG method results in superior solution quality for a spine phantom, lung patient, and cauda equina patient. The BG method produces solutions with the highest degree of fluence complexity. Most methods result in comparable run times. Conclusion: The LG method produces superior solution quality using a moderate degree of fluence modulation.

As radiation treatment delivery becomes more complex, including dynamic IMRT and VMAT, the argument for routine patient dose verification becomes more compelling. This work demonstrates a technique that utilizes our pre-existing portal dose image prediction algorithm to compute 3D patient dose from recorded on-treatment portal images. This approach can be applied on CT simulation data or daily cone-beam CT data sets. Here we demonstrate the robustness of our dose reconstruction technique with phantom and patient examples, with delivery schemes including IMRT and VMAT. For an example prostate treatment site, 3D dose distributions reconstructed in the patient model are computed for each fraction, and DVHs presented. Results indicate that the patient dose reconstruction algorithm compares well with treatment planning system computed doses for controlled test situations. For patient examples the 3D chi comparison values (similar to the gamma comparison) ranged from 94.5% to 100% agreement for voxels > 10% maximum dose for all treatments and phantom cases. We show an example where the DVH for fraction nine of a prostate treatment fails acceptability criteria, due to a previously unnoticed positioning error. Future work involves building our patient dose reconstruction into a QA package, subsequently integrating it into a clinical workflow. We are also investigating the use of this tool as a backbone for an in-house adaptive radiotherapy implementation. This work is supported by Varian Medical Systems.

Amorphous silicon (a‐Si) electronic portal imaging devices(EPIDs) have been heavily investigated as treatment verification tools, with a particular focus on intensity modulated radiation therapy(IMRT). This verification could be accomplished through a comparison of measured portal images to predicted images. A general fluence determination for portal doseimage prediction would be a great asset in order to model the complex modulation of IMRT. A physically‐based parameter fluence model was developed by matching multi‐leaf collimator defined predicted images to measured image profiles. The fluence model was composed of a focal Gaussian and extrafocal Gaussian‐like source (Pearson VII). Specific aspects of the MLCs and secondary collimators were also modeled (eg. jaw and MLC transmission factors, MLC rounded leaf tips, tongue and groove effect, interleaf leakage, MLC offsets). The resulting calculated fluence was then convolved with Monte Carlo generated EPID‐specific dose kernels to convert incident fluence to dosedelivered to the EPID. Measured EPID data was obtained with an a‐Si EPID for various MLC‐defined fields (1×1 to 20×20 cm2) over a range of source‐to‐imager distances. These measured profiles were used to determine the fluence model parameters and the resulting model was tested on prostate and oropharyngeal IMRT fields. The model predicted the open‐field profiles within 2%, 2mm, while the predicted IMRT fields were generally within 3%, 3mm for at least 96% of the pixels. This model demonstrates the necessary accuracy needed for IMRT portal doseimage prediction in complex clinical examples (

A beam orientation optimization (BOO) algorithm based on optimizing beam intersection volume (BIV) components within an Organ-at-Risk (OAR) is proposed to improve conventional intensity-modulated radiation therapy (IMRT). A simulated annealing algorithm was employed to search for the optimal set of five beam orientations (5-opt) which simultaneously minimize the BIV components within an OAR. The 5-opt plans were compared to standard 5, 7, and 9 equiangular-spaced beam plans (5-equi, 7-equi, 9-equi) for: (1) gastric (2) Radiation Therapy Oncology Group (RTOG) P-0126 prostate and (3) RTOG H-0022 oropharyngeal (Stage-III, IV) cancer patients. In the gastric case, the coplanar 5-opt plan reduced the right kidney V 20 Gy by 41.1%, 32.1%, and 29.5% compared to the 5-equi, 7-equi, and 9-equi plans. In the prostate case, the coplanar 5-opt plan improved rectal sparing over all standard plans with a reduction of the V 75 Gy, V 70 Gy, V 65 Gy, and V 60 Gy of 3.9%, 6.2%, 8.1%, and 10.6% compared to the 5-equi plan. In both oropharyngeal cases, the non-coplanar 5-opt plan substantially reduced the V 30 Gy and mean dose to the contralateral parotid compared to the 5-equi, 7-equi, and 9-equi plans: (Stage-III) 8.9%, 7.0%, 8.6% and 4.1 Gy, 2.5 Gy, 2.7 Gy (Stage-IV) 11.2%, 11.2%, 10.8% and 7.8 Gy, 7.9 Gy, 8.0 Gy. In conclusion, the method of optimizing BIV to produce substantial improvements in OAR sparing over conventional IMRT has been demonstrated to be robust for application to a variety of IMRT treatment sites.

Amorphous silicon (a-Si) electronic portal imaging devices (EPIDs) continue to be investigated as treatment verification tools, with a particular focus on intensity modulated radiation therapy (IMRT). This verification could be accomplished through a comparison of measured portal images to predicted portal dose images. A general fluence determination tailored to portal dose image prediction would be a great asset in order to model the complex modulation of IMRT. A proposed physics-based parameter fluence model was commissioned by matching predicted EPID images to corresponding measured EPID images of multileaf collimator (MLC) defined fields. The two-source fluence model was composed of a focal Gaussian and an extrafocal Gaussian-like source. Specific aspects of the MLC and secondary collimators were also modeled (e.g., jaw and MLC transmission factors, MLC rounded leaf tips, tongue and groove effect, interleaf leakage, and leaf offsets). Several unique aspects of the model were developed based on the results of detailed Monte Carlo simulations of the linear accelerator including (1) use of a non-Gaussian extrafocal fluence source function, (2) separate energy spectra used for focal and extrafocal fluence, and (3) different off-axis energy spectra softening used for focal and extrafocal fluences. The predicted energy fluence was then convolved with Monte Carlomore » generated, EPID-specific dose kernels to convert incident fluence to dose delivered to the EPID. Measured EPID data were obtained with an a-Si EPID for various MLC-defined fields (from 1x1 to 20x20 cm{sup 2}) over a range of source-to-detector distances. These measured profiles were used to determine the fluence model parameters in a process analogous to the commissioning of a treatment planning system. The resulting model was tested on 20 clinical IMRT plans, including ten prostate and ten oropharyngeal cases. The model predicted the open-field profiles within 2%, 2 mm, while a mean of 96.6% of pixels over all IMRT fields was in agreement with the 2%, 3 mm criteria. This model demonstrates accuracy commensurate to existing methods for IMRT pretreatment verification with portal dose image prediction of complex clinical examples (

The effect of beam divergence on dose calculation via Monte Carlo generated dose kernels was investigated in an amorphous silicon electronic portal imaging device (EPID). The flat-panel detector was simulated in EGSnrc with an additional 3.0 cm water buildup. The model included details of the detector's imaging cassette and the front cover upstream of it. To approximate the effect of the EPID's rear housing, a 2.1 cm air gap and 1.0 cm water slab were introduced into the simulation as equivalent backscatter material. Dose kernels were generated with an incident pencil beam of monoenergetic photons of energy 0.1, 2, 6, and 18 MeV. The orientation of the incident pencil beam was varied from 0 degrees to 14 degrees in 2 degrees increments. Dose was scored in the phosphor layer of the detector in both cylindrical (at 0 degrees) and Cartesian (at 0 degrees - 14 micro) geometries. To reduce statistical fluctuations in the Cartesian geometry simulations at large radial distances from the incident pencil beam, the voxels were first averaged bilaterally about the pencil beam and then combined into concentric square rings of voxels. Profiles of the EPID dose kernels displayed increasing asymmetry with increasing angle and energy. A comparison of the superposition (tilted kernels) and convolution (parallel kernels) dose calculation methods via the chi-comparison test (a derivative of the gamma-evaluation) in worst-case-scenario geometries demonstrated an agreement between the two methods within 0.0784 cm (one pixel width) distance-to-agreement and up to a 1.8% dose difference. More clinically typical field sizes and source-to-detector distances were also tested, yielding at most a 1.0% dose difference and the same distance-to-agreement. Therefore, the assumption of parallel dose kernels has less than a 1.8% dosimetric effect in extreme cases and less than a 1.0% dosimetric effect in most clinically relevant situations and should be suitable for most clinical dosimetric applications. The resulting time difference for the parallel kernel assumption versus the tilted kernels was 10.5 s vs 18 h (a factor of approximately 6000), dependent on existing hardware and software details.

A two step algorithm to predict portal dose images in arbitrary detector systems has been developed recently. The current work provides a validation of this algorithm on a clinically available, amorphous silicon flat panel imager. The high-atomic number, indirect amorphous silicon detector incorporates a gadolinium oxysulfide phosphor scintillating screen to convert deposited radiation energy to optical photons which form the portal image. A water equivalent solid slab phantom and an anthropomorphic phantom were examined at beam energies of 6 and 18 MV and over a range of air gaps (approximately 20-50 cm). In the many examples presented here, portal dose images in the phosphor were predicted to within 5% in low-dose gradient regions, and to within 5 mm (isodose line shift) in high-dose gradient regions. Other basic dosimetric characteristics of the amorphous silicon detector were investigated, such as linearity with dose rate (+/- 0.5%), repeatability (+/- 2%), and response with variations in gantry rotation and source to detector distance. The latter investigation revealed a significant contribution to the image from optical photon spread in the phosphor layer of the detector. This phenomenon is generally known as "glare," and has been characterized and modeled here as a radially symmetric blurring kernel. This kernel is applied to the calculated dose images as a convolution, and is successfully demonstrated to account for the optical photon spread. This work demonstrates the flexibility and accuracy of the two step algorithm for a high-atomic number detector. The algorithm may be applied to improve performance of dosimetric treatment verification applications, such as direct image comparison, backprojected patient dose calculation, and scatter correction in megavoltage computed tomography. The algorithm allows for dosimetric applications of the new, flat panel portal imager technology in the indirect configuration, taking advantage of a greater than tenfold increase in detector sensitivity over a direct configuration.

The equivalent fields concept has been studied using a variation of the convolution dose calculation method. This allows a better understanding of this classic, widely-used concept and its relation to modern dose calculation techniques. Total scatter energy contribution as a function of field size was computed by radially integrating three-dimensional point interaction scatter kernels representing cobalt-60, 6 MV and 24 MV photon beam spectra and utilizing reciprocity. For arbitrarily shaped treatment fields, equivalent square or circular fields are chosen based on a conservation of energy approach. Associated depth dose curves are generated via convolution of primary fluence with pre-integrated scatter kernels. For the energy spectra used, the resulting equivalent circle to square relationships agree with the empirical equation recommended in the British Journal of Radiology Supplement 25 (BJR 25) (to within 2%). Tables converting rectangular fields to equivalent squares and circles have been generated and most (approximately 63%) of the equivalent square (and circular) field sizes are within 0.5 cm of the BJR 25 tables. This agreement provides an explanation for the successful use of a single relationship for all therapeutic energies. Fields of different shape will be approximately equivalent only when the scatter kernels are similar in shape and total energy content. The equivalent field concept inevitably results in an optimal match of depth dose curves at a single depth only. These ideas are demonstrated for a highly elongated (2 x 30 cm2) field and its equivalent square field. The invalidity of the equivalent fields concept off-axis is demonstrated by examining predicted dose deposition for several points in and around a 15 x 15 cm2 cobalt-60 beam. Modern convolution techniques are shown to offer a unique approach to the classic equivalent fields method. The appropriate use of the BJR 25 equivalent fields tables is recommended for all photon energies.

Purpose: This study determined the interobserver variability of Gross Tumor Volume (GTV) with [18F] Fludeoxyglucose (FDG)-PET/CT compared to CT alone in Stage III Non-Small Cell Lung Cancer (NSCLC) using 3D analysis. Materials and Methods: Twenty-nine patients underwent simultaneous co-registered CT and FDG-PET/CT for radiotherapy planning. GTV for lung tumor and mediastinal lymphadenopathy contoured by three different radiation oncologists was compared for changes in volume and position. Interobserver variability was determined with vector displacement and Dice Similarity Coefficient (DSC). Concordance for the number of lymph nodes was determined. Results: Mean GTV for lung tumor with FDG-PET/CT and CT alone was 62.0 cm3 and 74.64 cm3, (p=0.0005) with 17% reduction in GTV by FDG-PET/CT. Mean GTV for mediastinal lymphadenopathy was 15.72 cm3 and 19.02 cm3 (p=0.084) with 17% reduction in GTV. Mean vector displacement of lung tumor was 2.0 mm with FDG-PET/CT versus 7.1 mm with CT alone (p = 0.0016) with 3.6 fold reduction in interobserver variability. Mean vector displacement of mediastinal lymphadenopathy was 1.53 mm with FDG-PET versus 10.2 mm for CT alone (p= 0.0005) with 6.7 fold reduction in interobserver variability. Median DSC for the primary GTV was 0.87 for FDG-PET/CT and 0.74 for CT alone. Median DSC for nodal GTV was 0.79 and 0.59 respectively. All physicians agreed on the number of lymph nodes on CT alone in 15/29 vs. 27/29 patients on PET/CT. Only two of the three physicians agreed on the number of lymph nodes contoured for CT alone in 12/29 versus only 2/29 patients for FDG-PET/CT (p=0.0018).

Purpose: A cine‐EPID based method to separately measure the mechanical motioncharacteristics of gantry, jaws and multi‐leaf collimator as a function of gantry angle during VMAT has been developed. Methods: Irradiations were performed using 6 MV beams of a Varian Trilogy linear accelerator with an aS1000 EPID.Images were acquired using 360 MU irradiations at 600 MU/min in cine acquisition mode at 2 Hz frame‐rate. To establish the gantry isocentre, a Winston‐Lutz technique was used with a circular collimator rigidly attached to the gantry head. The displacement of the centre of a fixed tungsten ball at isocentre from the field centre was determined on each image with a sub‐pixel thresholding technique. EPID coordinates were transformed to room coordinates. Jaw and MLC sag relative to the gantry head were determined from the displacement of a gantry‐mounted tungsten ball relative to static jaw and MLC positions. MLC speed constancy was determined by segmenting MLC positions on each image for a constant leaf‐speed test pattern. Gantry speed constancy was assessed with an independent liquid‐based inclinometer and the linac gantry angle potentiometer. Results: The gantry isocentre was ∼ 1 mm amplitude with changes in isocentre occuring over time suggesting frequent measurement is required. Jaw sag was found to be very small ∼ 0.2 mm amplitude, with MLC sag ∼ 0.6 mm. Average leaf speed was found to be consistent for the MLC leaves however the variation in speed varied systematically across the leaf bank which requires further investigation. Gantry speed was consistent although the inclinometer was found to lag ∼ 2 degrees in reading from the potentiometer. Conclusions: The cine‐EPID based method quantifies the mechanical motioncharacteristics of the linac as a function of gantry angle during arc‐therapy with improved precision and efficiency of quality assurance over previous methods. This work supported by NHMRC Grant 569211

Purpose: Utilization of an aSi EPID to develop an in vivo patient dose verification system for rotational IMRT (rIMRT) delivery requires accurate knowledge of gantry angle as a function of time. Currently the accuracy of the gantry angle stamp in the header of the EPIDimage is limited to approximately +/−3 degrees. This work investigates several unique methods for a more accurate determination of the gantry angle during rIMRT. Methods: Gantry angles were determined using: (1) an incremental rotary encoder attached to the rotational axis of the gantry, (2) a direct analogue‐to‐digital measurement of the gantry potentiometer, and (3) through EPIDimage analyses of an in‐house phantom (manufactured at sub‐millimeter precision). The phantom consists of a cylindrical acrylic frame with one wire wrapped helically around its surface and one straight wire traversing its central axis. This design creates EPIDimages with unique and identifiable wire intersection points as a function of gantry orientation. Analysis of the treatment console log files was compared to the above methods. Results: The gantry potentiometer is considered the most accurate gantry angle but is unavailable during treatment. The ClinacLog produced discrepancies of up to ±2 degrees, the DynaLog up to ±1 degrees, and the encoder up to ±0.5 degrees with respect to the potentiometer. Preliminary analysis comparing our phantom‐determined gantry angles with the encoder gantry angles showed agreement within ±0.5 degrees of each other for 85% of the data and differed at most by 1.3 degrees from each other. Conclusions: We have developed several techniques to determine gantry angle as a function of time during rIMRT. We have shown a strong agreement in gantry determination by our phantom and encoder. This investigation of gantry angle is critical to develop an accurate in vivo patient dose verification system for rIMRT delivery.

Radical treatment techniques such as stereotactic body radiation therapy (SBRT) are becoming popular and they involve delivery of large doses in fewer fractions. Due to this feature of SBRT, a high-resolution, pre-treatment dose verification method that makes use of a 3D patient representation would be appropriate. Such a technique will provide additional information about dose delivered to the target volume(s) and organs-at-risk (OARs) in the patient volume compared to 2D verification methods. In this work, we investigate an electronic portal imaging device (EPID) based pre-treatment QA method which provides an accurate reconstruction of the 3D-dose distribution in the patient model. Customized patient plans are delivered ‘in air’ and the portal images are collected using the EPID in cine mode. The images are then analysed to determine an estimate of the incident energy fluence. This is then passed to a collapsed-cone convolution dose algorithm which reconstructs a 3D patient dose estimate on the CT imaging dataset. To date, the method has been applied to 5 SBRT patient plans. Reconstructed doses were compared to those calculated by the TPS. Reconstructed mean doses were mostly within 3% of those in the TPS. DVHs of target volumes and OARs compared well. The Chi pass rates using 3%/3mm in the high dose region are greater than 97% in all cases. These initial results demonstrate clinical feasibility and utility of a robust, efficient, effective and convenient pre-treatment QA method using EPID. Research sponsored in part by Varian Medical Systems.

The objective of this work is to commission the 6MV-SRS beam model in COMPASS (v2.1, IBA-Dosimetry) and validate its use for patient specific QA of hypofractionated prostate treatments. The COMPASS system consists of a 2D ion chamber array (MatriXX{sup Evolution}), an independent gantry angle sensor and associated software. The system can either directly calculate or reconstruct (using measured detector responses) a 3D dose distribution on the patient CT dataset for plan verification. Beam models are developed and commissioned in the same manner as a beam model is commissioned in a standard treatment planning system. Model validation was initially performed by comparing both COMPASS calculations and reconstructions to measured open field beam data. Next, 10 hypofractionated prostate RapidArc plans were delivered to both the COMPASS system and a phantom with ion chamber and film inserted. COMPASS dose distributions calculated and reconstructed on the phantom CT dataset were compared to the chamber and film measurements. The mean (± standard deviation) difference between COMPASS reconstructed dose and ion chamber measurement was 1.4 ± 1.0%. The maximum discrepancy was 2.6%. Corresponding values for COMPASS calculation were 0.9 ± 0.9% and 2.6%, respectively. The average gamma agreement index (3%/3mm) for COMPAS reconstruction and film wasmore » 96.7% and 95.3% when using 70% and 20% dose thresholds, respectively. The corresponding values for COMPASS calculation were 97.1% and 97.1%, respectively. Based on our results, COMPASS can be used for the patient specific QA of hypofractionated prostate treatments delivered with the 6MV-SRS beam.« less

Purpose: Stereotactic body radiation therapy (SBRT) delivered via volumetric modulated arc therapy (VMAT) can strongly benefit from an in vivo patient dose verification due to the large doses per fraction. Electronic portal imaging devices (EPIDs) can be utilized as a patient dose dosimeter. In this work we present a physics-based model which utilizes on-treatment EPID images to reconstruct the dose delivered to an anthropomorphic phantom during SBRT-VMAT delivery. Methods: An SBRT linac beam was modeled using Monte Carlo methods and verified with measured data. Our dose reconstruction model back-projects EPID measured focal fluence upstream of the patient and adds a predicted extra-focal fluence component. This fluence is forward projected onto the patient's density matrix and convolved with dose kernels to calculate dose. The model was validated for two prostate, three lung, and two spine SBRT-VMAT treatments. Results were compared to the treatment planning system's calculation. Results: 2%/2 mm chi comparison calculations gave pass rates for the whole volume, infield, and high dose region respectively, and no lower than: 98%, 95%, 99% for the prostate plans, 99%, 92%, 85% for the lung plans, and 91%, 85%, 81% for the spine plans. A 3%/3mm calculation gave pass rates no lower than 99%,more » 94%, and 90% for all dose regions for the prostate, lung, and spine respectively. Conclusions: We have developed a physics-based model which calculates delivered dose to phantom (or patient) for SBRT-VMAT delivery using on treatment EPID images. The accuracy of the results has allowed us to test this model clinically.« less

The effect of a transmission detector (TRD), a novel IMRTquality assurance tool to be used for in vivo dose measurements, was investigated. As a scattering material, the device will be a source of contaminantelectrons and could potentially affect prescribed dose to patients during treatment. The goals of this investigation are to characterize the effect of the TRD on the clinical photon beam including IMRT fields, using Monte Carlo simulation. The linear accelerator head and the TRD were modeled using BEAMnrc. Particles scored at 70 cm and 100cm SSD for different field sizes (i.e. 5×5 cm2, 10×10 cm2, and 20 × 20 cm2) with and without the TRD were separated according to where they were created in the linac head. In addition, two IMRT fields with and without the TRD were simulated and their respective absolute dose distributions were compared. Without the TRD, air is the major source of contaminantelectrons. When TRD is used, it absorbs nearly all the incident contaminantelectrons, while becoming the major source of contaminantelectrons. For both IMRT fields, the percentage dose differences of the calculated absolute doses with and without TRD at the isocenter were found to be within uncertainty of the measured transmission factor for the TRD. Although a major source of contaminantelectrons, the TRD does not introduce excessive electron contamination into a clinical 6 MV photon beam and is therefore suitable for in vivo dose measurements if fully commissioned as an IMRTquality assurance tool. Research partly sponsored by IBA Dosimetry.

Radiation therapy has become increasingly complex with the introduction of new technologies like intensity modulated radiation therapy(IMRT) and rotational‐IMRT. Thorough dosimetric verification is required to ensure sufficient tumour coverage and normal tissue sparing. Pretreatment verification is conventionally performed prior to a patient's course of treatment, but validation during treatmentdelivery does not usually occur. One method to determine whether the treatment was delivered correctly is through the comparison of a measured portal image (taken with an a‐Si EPID) to a predicted portal doseimage (modeling the same EPID). In this work, a patient scatter model was incorporated into an existing fluence model to account for the effect of a patient during an in vivo portal image measurement. The patient/phantom CT data set is converted to an equivalent homogeneous phantom (EHP). The modeled beam fluence is then ray‐traced through the EHP and onto the EPID, accounting for patient attenuation. Patient scatter fluence is calculated through the superposition of a library of pre‐calculated Monte Carlo scatter fluence kernels. The dosedelivered to the EPID is determined with the convolution of a series of mono‐energetic dose kernels. The patient scatter model was tested with slab phantoms for a range of thicknesses, air gaps and field sizes, and was found to accurately predict images within 2% and 3 mm. A prostate in vivoIMRT field prediction was also carried out, with a comparison of the relative images resulting in a model accuracy of 3% and 3 mm.

Pencil beam kernels describing scattered photon fluence behind homogeneous water slabs at various air gap distances were generated using the EGS Monte Carlo code. Photon scatter fluence was scored in separate bins based on the particle's history: singly scattered, multiply scattered, and bremsstrahlung and positron annihilation photons. Simultaneously, the mean energy and mean angle with respect to the incident photon pencil beam were tallied. Kernels were generated for incident photon pencil beams exhibiting monoenergetic spectra of 2.0 and 10.0 MeV, and polyenergetic spectra representative of 6 and 24 MV beams. Reciprocity was used to generate scatter fractions on the central axis for various field sizes, phantom thicknesses, and air gaps. The scatter kernels were further characterized by full width at half-maximum estimates. Modulation transfer functions were calculated, providing theoretical estimates of the limit of performance of portal imaging systems due to the intrinsic scattering of photon radiation through the patient.

Purpose: We seek to improve the quality of in vivo prostate MRSIdata acquisition by utilizing an optimized conformal voxel technique coupled with a spatial‐spectral excitation PRESS pulse sequence for short echo time acquisitions. Method and Materials: All subjects were scanned on a GE 1.5T Signa MR scanner equipped with Echospeed gradients. A standard endorectal coil in combination with a torso phased‐array coil was used. The PRESS pulse sequence was modified to include the optimized conformal voxel MR spectroscopic imaging technique (CV‐MRS). This method uses up to twenty Very Selective Saturation (VSS) pulses, automatically positioned in three dimensions, to “conform” the excitation volume to the shape of the prostate, effectively nulling signal from periprostatic lipids. Subjects were scanned using both the standard PRESS and the optimized CV‐MRS techniques at long and short echo times (TE). In vivo prostate spectra were collected and processed using a modified version of LCModel. Results: We observed an average lipid reduction of 60±18% for 17 subjects over the entire prostate when using the optimized CV‐MRS technique as compared to standard MRSI techniques. In specific regions along the peripheral zone, we observed lipid reduction greater than 95%. The effect of reducing the lipid contamination has resulted in a ∼70% improvement in peak identification of key prostate metabolites, based on goodness‐of‐fit parameters. Furthermore, short TE acquisitions have resulted in a substantial increase in the citrate signal, full visualization of the citrate multiplet and other metabolites not seen at long echo times. Conclusion: In vivo implementation of this optimized MRSI technique has confirmed the reduction in peripheral lipid contamination, and improved the quality of spectra throughout the prostate. Furthermore, this is the first demonstration of short TE in vivo prostate MRSI acquisitions, which provides significant signal increase and reveal short TE metabolites to potentially improve prostate cancer detection.

The effect of beam divergence on dose calculation via Monte Carlo generated dose kernels was investigated in an amorphous‐silicon electronic portal imaging device(EPID). The complete detector was simulated in EGSnrc with a 3.0 cm water buildup. The model included details of the detector'simaging cassette, the front cover upstream of it and equivalent backscatter material to approximate the EPID's complex rear housing. Dose kernels were generated with an incident pencil beam of monoenergetic photons of energies 0.1, 2, 6 and 18 MeV. Dose was scored in the phosphor layer of the detector in both cylindrical (at 0° pencil beam orientation) and cartesian (at 0° – 14° in 2° increments) geometries. The parallel (0°) kernels were then convolved with a simple incident fluence map; a full superposition employing the tilted kernels (simulating a divergent beam) and the same incident fluence map was also calculated. Profiles of the dose kernels were observed to demonstrate increasing asymmetry with increasing angle and energy. Comparison of superposition to convolution dose calculation methods in worst‐case‐scenario geometries demonstrated an agreement between the two methods within 0.784 mm distance‐to‐agreement and up to a 1.5% dose difference. More clinically typical field sizes and source‐to‐detector distances were also tested, yielding at most a 1.0% dose difference and the same distance‐to‐agreement. The assumption of parallel dose kernels has less than a 1.5% dosimetric effect in extreme cases and less than a 1.0% dosimetric effect in most clinically relevant situations and should be suitable for most clinical dosimetric applications.

Dosimetric verification of patient treatment plans has become increasingly important due to the widespread use of complicated delivery techniques. IMRT and VMAT treatments are typically verified prior to start of the patient's course of treatment, using a point dose and/or a film measurement. Pre-treatment verification will not detect patient or machine-related errors; therefore, in vivo dosimetric verification is the only way to determine if the patient's treatment was delivered correctly. Portal images were acquired throughout the course of five prostate and six head-and-neck patient IMRT treatments. The corresponding predicted images were calculated using a previously developed portal dose image prediction algorithm, which combines a versatile fluence model with a patient scatter and EPID dose prediction model. The prostate patient image agreement was found to vary day-to-day due to rectal gas pockets and the effect of adjustable support rails on the patient couch. The head-and-neck patient images were observed to be more consistent daily, but an increased measured dose was evident at the periphery of the patient, likely due to patient weight loss. The majority of the fields agreed within 3% and 3 mm for greater than 90% of the pixels, as established by the χ-comparison. This work demonstrates the changes in patient anatomy that are detectable with the portal dose image prediction model. Prior to clinical implementation, the effect of the couch must be incorporated into the model, the image acquisition must be automatically scheduled and routine EPID QA must be undertaken to ensure the collection of high-quality EPID images.

Purpose: To determine if our in‐house patient specific QA process, which utilizes the COMPASS (v2.1, IBA‐Dosimetry) system, can detect delivery errors introduced in clinical IMRT plans. Methods: The COMPASS system consists of a 2D chamber array mounted in the gantry, an independent gantry angle sensor and associated software. Patient specific QA at our clinic involves the creation of two QA structures, one consisting of all clinical PTVs, the other generated from the 20% isodose line. The gamma agreement index (GAI) within the two QA structures is used to compare 3D COMPASS reconstructed dose with planned dose distributions. Ten clinical DMLC‐IMRT plans (5 prostate, 5 head & neck) were included in this study. Plans were modified by systematically shifting leaf pair positions so that that all nonzero leaf gaps were increased by 2.0 mm and 1.0 mm for the two sites, respectively. Verification plans were created for both the original and modified plans in order to quantify the dosimetric effect of the introduced errors via in‐phantom ion chamber measurements. Finally, plans were delivered to COMPASS and 3D dose distributions were reconstructed on both the phantom and patient CT datasets. Reconstructed doses on the patient CT were analyzed as per our QA procedure. Results: On average, measured ion chamber values for the modified plans deviated from the original planning doses by 3.1 ± 1.2% (Range: 1.0%–5.3%). For each of the six modified plans in which this metric exceeded 3%, GAI values for at least one of the QA structures were below 95%, which would be flagged by our QA process. Only one of the other modified and none of the original plans had GAI values

Purpose: To measure the detector response function of an online dose verification device and to validate our measurement by applying the detector response to Monte Carlo (MC) derived incident fluence. Methods: A transmission detector array (IBA Dosimetry, Schwarzenbruck, Germany) was recently developed as an IMRTquality assurance tool. To understand the detector system performance for verification of IMRT fluence, the detector response function at 6MV of a single ion chamber in the detector was measured with a narrow slit collimator. The narrow slit was formed by two 24 × 72 × 152 mm3 lead blocks, which provided a slit of 0.25 × 10 mm2. The LSF of the detector was obtained by laterally translating it in 0.25 mm steps underneath the slit. Two head‐and‐neck IMRT fields were also measured using the device. The same fields were simulated in our BEAMnrc MC model, and the MC incident fluence was convolved with the 2D detector response to obtain calculated dose. The measured and calculated dose distributions were then quantitatively compared using chi comparison (3%/3mm) for in‐field points (defined as those above 10% maximum dose). Results: The FWHM of the measured detector response for a single chamber is 4.3 mm which is comparable to the chamber diameter of 3.8 mm. For both examined IMRT fields, the Chi comparison between measured and calculated data show good agreement with 100% of in‐field points below a chi of 1.0 (chi

Purpose: To determine the best parameterization of fluence modulation for PARETO (Pareto‐Aware Radiotherapy Evolutionary Treatment Optimization) multi‐objective treatment planningsoftware, as judged by the complexity of each parameterization, the efficiency, and the quality of the plans produced. Methods: PARETO simultaneously optimizes the number of beams, beam orientations, and fluence modulation. For this investigation, we have tested four fluence parameterizations on a paraspinal tumour phantom and a spine patient data set using a pre‐determined number of beams. The first method applies linear gradients over the projection of Planning Target Volume (PTV) in the beam's‐eye‐view plane. The second method applies the two‐dimensional inverse cosine transform of a few low‐frequency parameters. Another method interpolates between the intensities of a coarse grid of square beamlets. Also, an isodose‐based contour method defines regions on the fluence maps that are assigned different intensities. Methods which produce plans of the best quality (as judged by dose‐volume histograms) will have a similar distribution of non‐dominated solutions. The complexity of each parameterization is determined by the number of parameters, and the efficiency is determined by the run time. Results: For both geometries, we found that the set of non‐dominated solutions of each parameterization overlapped in the projection of the PTV conformity fitness function and the quadrature‐averaged Organs‐At‐Risk (OAR) fitness function. The beam group and cosine transform methods produced some plans which did slightly better in simultaneously achieving good PTV conformity and OAR dose sparing. The cosine transform and linear gradient methods proved to be the most efficient. The cosine transform method also has the least number of parameters per beam. Conclusions: We have found that several different parameterizations of fluence modulation produce non‐dominated solutions of similar quality. The cosine transform method is the best choice for efficiently producing solutions that do well in PTV conformity and OAR sparing.

Purpose: To create a physical fluence model for portal doseimage prediction that will be used to verify patient radiation treatment delivery. Methods and Materials: A physical fluence model was created to predict portal doseimages. This model utilized Monte Carlo simulation and linac‐specific engineering schematics of the MLCs to create as accurate a model as possible. The fluence model consists of a focal and extra‐focal source, determined to be a Gaussian and Gaussian‐like function, respectively. The MLC transmission is calculated by attenuating a pre‐MLC BEAMnrc spectrum through the leaves; the MLC leaf‐tip and tongue‐and‐groove are modeled using the schematics. Incident energy fluence profiles from BEAMnrc are used to account for the field shape and beam horns. The asymmetric backscatter from the EPID arm is also modeled. The energy fluence is converted to dose using a superposition of EPID‐specific dose kernels. Scatter from the patient or phantom is approximated using Monte Carlo calculated scatter fluence kernels. The model is tested on simple slab phantoms for a variety of field sizes, thicknesses and air gaps. It was also tested on one field acquired during a patient's prostate IMRTtreatment. Results: Predicted images with phantoms in the beam agreed within 2%, 2 mm in relative comparison with the measured images. After calibration of measured and predicted images to absolute units, the images agreed within 3% and 3 mm. The patient IMRT field predicted image was not ideal when compared to the measured image, mainly because the patient is heterogeneous. Conclusions: The physical fluence model, in conjunction with the patient scatter model, is accurate and could be used to verify patient treatment. The algorithm is versatile and can be applied to a variety of treatment scenarios.

Purpose: We introduce a novel multi‐objective treatment planning system called PARETO (Pareto‐Aware Radiotherapy Evolutionary Treatment Optimization), which simultaneously optimizes beam angles and fluence patterns by treating the PTV conformity and dose to OARs as separate objectives that are optimized by a powerful multi‐objective parallel genetic algorithm (GA).Methods: PARETO treats radiotherapytreatment planning as a single monolithic optimization problem, in which beam angle configurations and fluence patterns are explored to simultaneously optimize the PTV dose conformity and a dose objective for each OAR. We use a Pareto‐ranking scheme to discover necessary compromises between objectives. A final non‐dominated database of solutions is compiled from all plans evaluated during the run such that no solution in the database is superior to any other solution in all objectives. A graphical tool allows rapid navigation of the pre‐optimized database to select a final treatment option for the patient.Results: PARETO is at the stage of a working prototype. Solutions are of high quality, as judged by DVH curves and dose distribution, and consistent results are obtained between runs. Only minor differences in trade‐off surfaces result from four different fluence parameterizations of varying complexity, but they differ by a factor of ∼4 in speed. A novel feature allows optimization of the number of beams and a realistic test case shows that no further improvements in conformity are found for more than ∼9 beams. A newly implemented GPU‐based ray tracer, including convolution with a patient dose kernel, results in a speedup factor of ∼3 compared to CPU‐based computation. Conclusions: This work demonstrates PARETO's feasibility as a treatment‐planning tool, which replaces manual iterative optimization of treatment plans with a rapid graphical exploration of pre‐optimized solutions. Clinically acceptable run times of less than an hour appear within reach by combining several of our GPU‐based systems in parallel. J. Fiege discloses authorship of the Ferret GA (used by PARETO) and ownership of nQube Technical Computing Corporation, which distributes this optimization software.

Intensity-modulated radiation therapy (IMRT) treatment planning requires tradeoffs to be made between delivering a prescribed dose to the planning target volume (PTV) and sparing the organ's-at-risk (OARs). Traditionally in clinical practice, treatment planners manually optimize beam orientations, objectives, and/or weights in a time-consuming, trial-and-error process to find some acceptable compromise, with no guarantee that this solution is actually optimal. We propose a novel and powerful fluence and beam orientation optimization package for radiotherapy optimization, called PARETO (Pareto-Aware Radiotherapy Evolutionary Treatment Optimization), which consists of a multi-objective genetic algorithm capable of optimizing several objective functions simultaneously and mapping the structure of their trade-off surface efficiently and in detail. Fitness functions, based on mean dose for the OARs and PTV, as well as fluence gradients are optimized. PARETO intelligently varies all beam orientations and beam fluence to simultaneously optimize all objectives. Over many generations, the entire family of Pareto-optimal treatment plans, spanning a multi-dimensional trade-off surface, is mapped out. Pareto-optimal solutions are stored in a database and trade-offs between the competing objectives can be visualized graphically and explored. The efficacy of the solutions provided by PARETO was evaluated using a commercial treatment planning system with five coplanar IMRT treatment plans for a homogenous phantom consisting of three OARs surrounding a central PTV. This work demonstrated that the fitness functions within PARETO have a strong correlation to the dose distribution. Thus, from many Pareto-optimal plans, the clinician may select the plan which they decide is the most appropriate multi-objective compromise for a patient.

INTRODUCTION: Amorphous‐silicon electronic portal imaging devices(EPIDs) have been established as useful tools for dosimetry. To accurately reconstruct the patient dose delivered during rotational IMRT, one must acquire time‐resolved EPIDimages as a function of gantry‐angle. Dose reconstruction accuracy is directly impacted by the accuracy of the geometry of the imaging system, including the gantry‐angle readout (i.e. source geometry) and the EPID support‐arm sag (i.e. imager geometry). This work investigates these two factors. METHODS: The EPID support‐arm sag was investigated through measurements performed on Varian E‐arm and R‐arm models at two institutes and employing two different analysis methods. One method imaged an isocentric ball‐bearing whose position was tracked over all gantry‐angles. The second method involved analysing field edges to obtain the field centre location of all images. Gantry‐angle accuracy was examined by comparing the gantry‐angle indicated at the treatment console readout to the gantry‐angle written to the EPID DICOM header. We developed a method of measuring gantry‐angle directly from the gantry‐angle potentiometer. RESULTS: The E‐arm showed maximum displacement of roughly 0.6mm (cross‐plane) and 0.8mm (in‐plane). R‐arm results were significantly worse, estimated at 8.5mm (cross‐plane) and 5.0mm (in‐plane). Gantry‐angle analysis demonstrated approximately 2 degrees of uncertainty in the gantry‐angle contained in the EPIDimage. A direct measurement of the gantry angle potentiometer was demonstrated. CONCLUSIONS: Two main factors affecting patient dose reconstruction using EPIDdosimetry have been investigated. EPID support‐arm sag can be measured (and corrected). Near real‐time gantry‐angle measurement can be performed through directly monitoring the potentiometer signal.

Multi‐objective radiotherapy beam angle optimization is currently unavailable in commercial treatment planningsoftware. The PARETO (Pareto‐Aware Radiotherapy Evolutionary Treatment Optimization)software package presented here uses a sophisticated evolutionary algorithm that is capable of handling this difficult computational problem, while simultaneously incorporating IMRT fluence optimization. In this work, we focus on establishing the validity of the PARETO software in obtaining reasonable beam fluence maps for fixed gantry IMRT. PARETO IMRT solutions for a simple cylindrical phantom containing various structures (one planning target volume and one‐to‐three organs‐at‐risk) are compared to resulting fluence patterns at fixed beam angles generated by a commercial treatment planning system. We find that PARETO solutions agree well with those of the commercial system, with differences mainly attributable to the differences in the underlying dose calculation algorithm. Our approach to fluence modulation will allow PARETO to generate a database of optimal solutions for beam angles and IMRT plans that represent the best possible trade‐offs between competing treatment objectives.

The goal of this project is to develop a real‐time automatic comparison tool to detect portal doseimage errors and has two logical parts: 1. A mechanism to detect the presence of a significant discrepancy. 2. A set of components to identify the probable cause(s) of the discrepancy including geometrical positioning errors as well as machine specific delivery errors. Initially, we have only considered in‐plane rotations and translations. A total of ∼700 portal images of an anthropomorphic pelvic phantom were obtained using a Varian aS1000 EPID. The images contained combinations of three types of geometrical patient set‐up errors. The angle of rotation (about the axis perpendicular to the EPID) was varied from [−5, +5] degrees and the translational distance was varied from [−10, +10] mm. The majority of the images were acquired from the AP direction however ∼130 images were of a lateral view. The system was found to be sensitive to in‐plane rotations down to ∼ 2°, out of plane rotations greater than ∼4° and displacements 3mm. For the lateral views, the calculated rotation was correct to within 1/2° and translations to within 5mm 53% of the time. Considering only translations, the accuracy increases to ∼82%. The results are much better for the AP views. The in‐plane rotation was within ±1/2deg; for all cases and the displacement error was greater than 1.5 mm in only 1 case. The system was able to analyze an image pair in ∼10s, however, no effort was put toward optimization of the system.

Intensity modulated radiation therapy(IMRT) aims to deliver a uniform prescribed dose of radiation to a planning target volume (PTV), while also minimizing the dose to each nearby organ at risk (OAR). IMRTtreatment planning is therefore a multi‐objective optimization problem, which can be addressed by powerful multi‐objective optimization techniques from the field of evolutionary computing. We introduce a software package called PARETO (Pareto‐Aware Radiotherapy Evolutionary Optimization), under development at the University of Manitoba and CancerCare Manitoba, which uses a sophisticated multi‐objective genetic algorithm called Ferret to find Pareto‐optimal beam orientations and fluence maps for IMRTtreatment planning. We discuss our fitness functions and a novel geometric method for parameterizing fluence maps for use with the Ferret Genetic Algorithm. We show that our method replaces manual iterative optimization methods currently used with a faster navigation of a pre‐optimized database of solutions. We present an illustrative example that applies the code to a geometric phantom with three OARs, and show that the PARETO finds two distinct classes of solutions.

Measurement‐baseddose verification of planned intensity modulated radiotherapy(IMRT) fields requires a detector with good spatial resolution. A novel, transmission detector array has been recently developed by IBA Dosimetry (Germany) as an IMRTquality assurance tool. To characterize the detector system performance for verification of IMRT fluence, the line spread function (LSF) of a single ion chamber in the detector in a clinical 6 MV photon beam was measured with a narrow slit of width 0.25 mm. The LSF of the detector was obtained by laterally translating it in 0.5 mm steps underneath the slit, from the center to 16 mm distance from the center in the cross‐plane direction. The measured signal was corrected for background and leakage. The FWHM of the LSF for the single chamber was found to be 4.2 mm, which is comparable to the chamber size of 3.8 mm. The MTF of the detector system is a sinc function and with a first zero crossing of the MTF at spatial frequency of 0.25 lp/mm. This compares well to the value of 0.15 lp/mm found for the PTW (Germany) 2D‐ARRAY type 10024, also used for dose verification of IMRT fluence. We have successfully measured the LSF for a new novel transmission detector using a narrow slit method and a clinical 6MV photon beam. The transmission detector was found to have a better first zero crossing of the MTF compared to the 2D‐ARRAY type 10024. Research partly sponsored by IBA Dosimetry.

A new ionization chamber array developed by IBA Dosimetry (Germany) is evaluated at our centre. The dosimetric characteristics of this device such as dose and dose rate dependence, stability, energy dependence, profiles and error detection ability were studied. COMPASS is an array with 1600 parallel plate ion chambers. Each chamber is 3.8 mm in diameter and 2mm in height spaced 6.5 mm apart. The array is mounted onto the wedge slot of the Varian Clinac 2100iX (Varian Medical Systems, Palo Alto, CA) linear accelerator. Linearity of the detector with dose and response to dose rate were done using Clinac 2100iX 6 MV beam. The detector showed excellent linearity response with dose and a variation of

Complex radiotherapy techniques, such as intensity modulated radiation therapy(IMRT) or volumetric modulated radiation therapy (VMAT), have greatly increased the motivation for dosimetric verification of radiation therapytreatments. Pretreatment dosimetry is typically carried out prior to a patient's treatment but verification of the actual delivered treatment is not usually performed. Amorphous siliconelectronic portal imaging devices (a‐Si EPIDs) have been established for IMRT verification, with one method involving the comparison of a predicted image to a measured image to determine whether the treatment field was delivered correctly. In this work, a comprehensive physics‐based parameter fluence model is interfaced with a patient scatter model to predict portal doseimages. The patient scatter algorithm consists of a library of Monte Carlo calculated, scattered photon fluence kernels which predict scattered energy fluence exiting the patient or phantom. Images were acquired with an a‐Si EPID using a 6 MV beam and slab material in the beam path to test the model. Field size ranged from 1×1 to 20×20 cm 2 , with solid water thicknesses extending from 1 cm to 25 cm and an air gap of 40 cm. A prostate IMRT field was acquired during a patient treatment for prediction as well. Smaller fields were found to be accurately predicted within 2% and 2 mm, while larger fields were over‐predicted. The prostate field agreed within 2%, 3 mm. The model is able to accurately predict most MLC‐defined fields to within 2% and 2 mm; a prostate IMRT field has also been accurately predicted.

The Monte Carlo technique is used to investigate the influence of a novel transmission detector (IBA Dosimetry, Germany) on a 6MV photon beam. The transmission detector may be used as an in vivoIMRTquality assurance tool , and therefore will be a source of contaminantelectrons. This could potentially affect prescribed dose to patients. The linear accelerator together with the transmission detector and a plastic block tray for comparison, were modeled using BEAMnrc/EGSnrc. Electron fluence at different SSDs (70, 80, 90, 100 cm), electron energy spectra, electronangular distributions, and surface doses were calculated. Calculated data were validated against measurements using a fixed parallel plate chamber. Calculated surface dose for both open field and non‐open fields (i.e. TRD and block tray) agree within 3% of measurement. The fluence of contaminantelectrons produced in the TRD and block tray fields increases at shorter SSD, but most electrons at shorter SSD are low energy electrons with large angular spread. These electrons contribute less to surface dose at larger SSD because they are either out‐scattered or absorbed in air. Surface doses at different SSDs for the block tray are higher than those of the TRD. Contribution of contaminantelectrons to dose in the buildup region increases with increasing field size. For a 20 × 20 cm 2 field, the contribution of electrons is 9.8 % and 8.6% for block tray and TRD respectively, while for a smaller 3 × 3 cm 2 field is 0.35% and 0.75% for TRD and block tray respectively.

PURPOSE: Dosimetric properties of an amorphous‐silicon electronic portal imaging device(EPID) operated in a real‐time acquisition mode were investigated. This mode will be essential for time‐resolved dose verification of dynamic‐IMRT and arc‐IMRT. METHODS: The EPID was used in continuous acquisition mode, where individual sequential image frames are acquired in real‐time. Properties studied include dose linearity and reproducibility. Summed continuous acquisition mode results were also compared to dose results using the well‐studied integrated acquisition mode, for example treatment deliveries including dynamic‐IMRT and single‐arc‐IMRT. Comparison was made using percentage dose difference of in‐field pixels (pixels >10% of maximum signal). Temporally‐resolved EPID response was also compared to that of ion‐chamber data for selected points in the deliveries. RESULTS: Using continuous acquisition mode, EPID response was not linear with dose, with response approximately corresponding to 1–1.5 missed images per irradiation. Reproducibility of EPID response improved with increasing MU. Analysis of the example irradiations revealed summed continuous acquisition mode compared well to integrated acquisition mode, within 2% of maximum dose for more than 95% of in‐field pixels. Time resolved EPID data compared well to ion chamber data, with dose increases/decreases overlying each other. CONCLUSION: Continuous acquisition mode is suited for time‐resolved dosimetry applications including single‐arc‐IMRT and dynamic IMRT, giving comparable dose results to the integrated acquisition mode. Linearity and reproducibility should be adequate for clinical applications although caution should be used in low MU work. Time‐resolved EPID dose information also compared well to time‐resolved ion‐chamber measurements.