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Objective. Deep-learning (DL)-based dose engines have been developed to alleviate the intrinsic compromise between the calculation accuracy and efficiency of the traditional dose calculation algorithms. However, current DL-based engines typically possess high computational complexity and require powerful computing devices. Therefore, to mitigate their computational burdens and broaden their applicability to a clinical setting where resource-limited devices are available, we proposed a compact dose engine via knowledge distillation (KD) framework that offers an ultra-fast calculation speed with high accuracy for prostate Volumetric Modulated Arc Therapy (VMAT). Approach. The KD framework contains two sub-models: a large pre-trained teacher and a small to-be-trained student. The student receives knowledge transferred from the teacher for better generalization. The trained student serves as the final engine for dose calculation. The model input is patient computed tomography and VMAT dose in water, and the output is DL-calculated patient dose. The ground-truth \dose was computed by the Monte Carlo module of the Monaco treatment planning system. Twenty and ten prostate cases were included for model training and assessment, respectively. The model’s performance (teacher/student/student-only) was evaluated by Gamma analysis and inference efficiency. Main results. The dosimetric comparisons (input/DL-calculated/ground-truth doses) suggest that the proposed engine can effectively convert low-accuracy doses in water to high-accuracy patient doses. The Gamma passing rate (2%/2 mm, 10% threshold) between the DL-calculated and ground-truth doses was 98.64 ± 0.62% (teacher), 98.13 ± 0.76% (student), and 96.95 ± 1.02% (student-only). The inference time was 16 milliseconds (teacher) and 11 milliseconds (student/student-only) using a graphics processing unit device, while it was 936 milliseconds (teacher) and 374 milliseconds (student/student-only) using a central processing unit device. Significance. With the KD framework, a compact dose engine can achieve comparable accuracy to that of a larger one. Its compact size reduces the computational burdens and computing device requirements, and thus such an engine can be more clinically applicable.

Most commercially available treatment planning systems (TPSs) approximate the continuous delivery of volumetric modulated arc therapy (VMAT) plans with a series of discretized static beams for treatment planning, which can make VMAT dose computation extremely inefficient. In this study, we developed a polar-coordinate-based pencil beam (PB) algorithm for efficient VMAT dose computation with high-resolution gantry angle sampling that can improve the computational efficiency and reduce the dose discrepancy due to the angular under-sampling effect.6 MVThe dosimetric comparisons on the homogeneous phantom between the proposed PB algorithm and the CCC algorithm for 10 VMAT arcs demonstrate that the proposed algorithm can achieve a dosimetric accuracy comparable to that of the CCC algorithm with average gamma passing rates of 96% (2%/2mm) and 98% (3%/3mm). In addition, the proposed algorithm can provide better computational efficiency for VMAT dose computation using a PC equipped with a 4-core processor, compared to the CCC algorithm utilizing a dual 10-core server. Moreover, the computation complexity theory reveals that the proposed algorithm has a great advantage with regard to computational efficiency for VMAT dose computation on homogeneous medium, especially when a fine angular sampling rate is applied. This can support a reduction in dose errors from the angular under-sampling effect by using a finer angular sampling rate, while still preserving a practical computing speed. For dose calculation on the heterogeneous phantom, the proposed algorithm with heterogeneity corrections can still offer a reasonable dosimetric accuracy with comparable computational efficiency to that of the CCC algorithm.We proposed a novel polar-coordinate-based pencil beam algorithm for VMAT dose computation that enables a better computational efficiency while maintaining clinically acceptable dosimetric accuracy and reducing dose error caused by the angular under-sampling effect. It also provides a flexible VMAT dose computation structure that allows adjustable sampling rates and direct dose computation in regions of interest, which makes the algorithm potentially useful for clinical applications such as independent dose verification for VMAT patient-specific QA.

Purpose Despite being the standard metric in patient-specific quality assurance (QA) for intensity-modulated radiotherapy (IMRT), gamma analysis has two shortcomings: (a) it lacks sensitivity to small but clinically relevant errors (b) it does not provide efficient means to classify the error sources. The purpose of this work is to propose a dual neural network method to achieve simultaneous error detection and classification in patient-specific IMRT QA. Methods For a pair of dose distributions, we extracted the dose difference histogram (DDH) for the low dose gradient region and two signed distance-to-agreement (sDTA) maps (one in x direction and one in y direction) for the high dose gradient region. An artificial neural network (ANN) and a convolutional neural network (CNN) were designed to analyze the DDH and the two sDTA maps, respectively. The ANN was trained to detect and classify six classes of dosimetric errors: incorrect multileaf collimator (MLC) transmission (±1%) and four types of monitor unit (MU) scaling errors (±1% and ±2%). The CNN was trained to detect and classify seven classes of spatial errors: incorrect effective source size, 1 mm MLC leaf bank overtravel or undertravel, 2 mm single MLC leaf overtravel or undertravel, and device misalignment errors (1 mm in x- or y direction). An in-house planar dose calculation software was used to simulate measurements with errors and noise introduced. Both networks were trained and validated with 13 IMRT plans (totaling 88 fields). A fivefold cross-validation technique was used to evaluate their accuracy. Results Distinct features were found in the DDH and the sDTA maps. The ANN perfectly identified all four types of MU scaling errors and the specific accuracies for the classes of no error, MLC transmission increase, MLC transmission decrease were 98.9%, 96.6%, and 94.3%, respectively. For the CNN, the largest confusion occurred between the 1-mm-MLC bank overtravel class and the 1-mm-device alignment error in x-direction class, which brought the specific accuracies down to 90.9% and 92.0%, respectively. The specific accuracy for the 2-mm-single MLC leaf undertravel class was 93.2% as it misclassified 5.7% of the class as being error free (false negative). Otherwise, the specific accuracy was above 95%. The overall accuracies across the fivefold were 98.3 ± 0.7% and 95.6% ± 1.5% for the ANN and the CNN, respectively. Conclusions Both the DDH and the sDTA maps are suitable features for error classification in IMRT QA. The proposed dual neural network method achieved simultaneous error detection and classification with excellent accuracy. It could be used in complement with the gamma analysis to potentially shift the IMRT QA paradigm from passive pass/fail analysis to active error detection and root cause identification.

Purpose Directly extracting the respiratory phase pattern of the tumor using cone-beam computed tomography (CBCT) projections is challenging due to the poor tumor visibility caused by the obstruction of multiple anatomic structures on the beam's eye view. Predicting tumor phase information using external surrogate also has intrinsic difficulties as the phase patterns between surrogates and tumors are not necessary to be congruent. In this work, we developed an algorithm to accurately recover the primary oscillation components of tumor motion using the combined information from both CBCT projections and external surrogates. Methods The algorithm involved two steps. First, a preliminary tumor phase pattern was acquired by applying local principal component analysis (LPCA) on the cropped Amsterdam Shroud (AS) images. In this step, only the cropped image of the tumor region was used to extract the tumor phase pattern in order to minimize the impact of pattern recognition from other anatomic structures. Second, by performing multivariate singular spectrum analysis (MSSA) on the combined information containing both external surrogate signal and the original waveform acquired in the first step, the primary component of the tumor phase oscillation was recovered. For the phantom study, a QUASAR respiratory motion phantom with a removable tumor-simulator insert was employed to acquire CBCT projection images. A comparison between LPCA only and our method was assessed by power spectrum analysis. Also, the motion pattern was simulated under the phase shift or various amplitude conditions to examine the robustness of our method. Finally, anatomic obstruction scenarios were simulated by attaching a heart model, PVC tubes, and RANDO® phantom slabs to the phantom, respectively. Each scenario was tested with five real-patient breathing patterns to mimic real clinical situations. For the patient study, eight patients with various tumor locations were selected. The performance of our method was then evaluated by comparing the reference waveform with the extracted signal for overall phase discrepancy, expiration phase discrepancy, peak, and valley accuracy. Results In tests of phase shifts and amplitude variations, the overall peak and valley accuracy was -0.009 ± 0.18 sec, and no time delay was found compared to the reference. In anatomical obstruction tests, the extracted signal had 1.6 ± 1.2 % expiration phase discrepancy, -0.12 ± 0.28 sec peak accuracy, and 0.01 ± 0.15 sec valley accuracy. For patient studies, the extracted signal using our method had -1.05 ± 3.0 % overall phase discrepancy, -1.55 ± 1.45% expiration phase discrepancy, 0.04 ± 0.13 sec peak accuracy, and -0.01 ± 0.15 sec valley accuracy, compared to the reference waveforms. Conclusions An innovative method capable of accurately recognizing tumor phase information was developed. With the aid of extra information from the external surrogate, an improvement in prediction accuracy, as compared with traditional statistical methods, was obtained. It enables us to employ it as the ground truth for 4D-CBCT reconstruction, gating treatment, and other clinic implementations that require accurate tumor phase information.

Purpose The authors have previously shown the feasibility of using an artificial neural network (ANN) to eliminate the volume average effect (VAE) of scanning ionization chambers (ICs). The purpose of this work was to evaluate the method when applied to beams of different energies (6 and 10 MV) and modalities [flattened (FF) vs unflattened (FFF)], measured with ICs of various sizes. Methods The three‐layer ANN extracted data from transverse photon beam profiles using a sliding window, and output deconvolved value corresponding to the location at the center of the window. Beam profiles of seven fields ranging from 2 × 2 to 10 × 10 cm2 at four depths (1.5, 5, 10 and 20 cm) were measured with three ICs (CC04, CC13, and FC65‐P) and an EDGE diode detector for 6 MV FF and FFF. Similar data for the 10 MV FF beam was also collected with CC13 and EDGE. The EDGE‐measured profiles were used as reference data to train and test the ANNs. Separate ANNs were trained by using the data of each beam energy and modality. Combined ANNs were also trained by combining data of different beam energies and/or modalities. The ANN's performance was quantified and compared by evaluating the penumbra width difference (PWD) between the deconvolved and reference profiles. Results Excellent agreement between the deconvolved and reference profiles was achieved with both separate and combined ANNs for all studied ICs, beam energies, beam modalities, and geometries. After deconvolution, the average PWD decreased from 1–3 mm to under 0.15 mm with separate ANNs and to under 0.20 mm with combined ANN. Conclusions The ANN‐based deconvolution method can be effectively applied to beams of different energies and modalities measured with ICs of various sizes. Separate ANNs yielded marginally better results than combined ANNs. An IC‐specific, combined ANN can provide clinically acceptable results as long as the training data includes data of each beam energy and modality.

Flattening filter free (FFF) linear accelerators produce a fluence distribution that is forward peaked. Various dosimetric benefits, such as increased dose rate, reduced leakage and out of field dose has led to the growth of FFF technology in the clinic. The literature has suggested the idea of vendors offering dedicated FFF units where the flattening filter (FF) is removed completely and manipulating the beam to deliver conventional flat radiotherapy treatments. This work aims to develop an effective way to deliver modulated flat beam treatments, rather than utilizing a physical FF. This novel optimization model is an extension of the direct leaf trajectory optimization (DLTO) previously developed for volumetric modulated radiation therapy (VMAT) and is capable of accounting for all machine and multileaf collimator (MLC) dynamic delivery constraints, using a combination of linear constraints and a convex objective function. Furthermore, the tongue and groove (T&G) effect was also incorporated directly into our model without introducing nonlinearity to the constraints, nor nonconvexity to the objective function. The overall beam flatness, machine deliverability, and treatment time efficiency were assessed. Regular square fields, including field sizes of 10 × 10 cm2 to 40 × 40 cm2 were analyzed, as well as three clinical fields, and three arbitrary contours with "concave" features. Quantitative flatness was measured for all modulated FFF fields, and the results were comparable or better than their open FF counterparts, with the majority having a quantitative flatness of less than 3.0%. The modulated FFF beams, due to the included efficiency constraint, were able to achieve acceptable delivery time compared to their open FF counterpart. The results indicated that the dose uniformity and flatness for the modulated FFF beams optimized with the DLTO model can successfully match the uniformity and flatness of their conventional FF counterparts, and may even provide further benefit by taking advantage of the unique FFF beam characteristics.

The continuous delivery of volumetric modulated arc therapy (VMAT) plans is usually approximated by discrete apertures at evenly-spaced gantry angles for dose calculation purposes. This approximation can potentially lead to large dose calculation errors if the gantry angle spacings are large and/or there are large changes in the MLC apertures from one control point (CP) to the next. In this work, we developed a sliding-window (SW) method to improve VMAT dose calculation accuracy. For any 2 adjacent VMAT CPs ni and ni + 1, the dose distribution was approximated by a 2-CP SW IMRT beam with the starting MLC positions at CP ni and ending MLC positions at CP ni + 1, with the gantry angle fixed in the middle of the 2 VMAT CPs. Therefore, a VMAT beam with N CPs was approximated by a SW plan with N-1 SW beams. To validate the method, VMAT plans were generated for 10 patients in Pinnacle using 4° gantry spacing. Each plan was converted to a SW plan and dose was recalculated. Another VMAT plan, with 1° gantry spacing, was created by interpolating the original VMAT beam. The original plans were delivered on an Elekta Versa HD and measured with ArcCHECK. For both the isodose distribution and DVH, there were significant differences between the original VMAT plan and either the SW or the interpolated plan. However, they were indistinguishable between the SW and the interpolated plans. When compared with measurement, the average passing rates of the original VMAT plans were 87.3 ± 2.8% and 93.1 ± 1.0% for the 5 HN and 5 spine SBRT cases, respectively. On the other hand, the passing rates for both the VMAT1 and SW plans were above 95% for all the 10 cases studied. The dose calculation times of the original VMAT plans and the SW plans were very similar. We conclude that the proposed SW approach improves VMAT dose calculation accuracy without increase in dose calculation time.

Purpose Traditionally, the treatment couch coordinates (TCCs) for patients undergoing radiotherapy can only be determined at the time of treatment, placing pressure on the treating therapists and leaving several pathways for errors such as wrong‐site treatment or wrong treatment table shift from a reference point. The purpose of this work is to propose an accurate, robust, and streamlined system that calculates TCC in advance. Methods The proposed system combines the advantages of two different calculation methods that use an indexed immobilization device. The first method uses an array of reference ball bearings (BBs) embedded in the CT scanner’s couch‐top. To obtain the patient‐specific TCC, the spatial offset of the treatment planning isocenter from the reference BB is used. The second method performs a calculation using the one‐to‐one mapping relationship between the CT scanner’s DICOM (Digital Imaging and Communications in Medicine) coordinate system and the TCC system. Both methods use a reference point in the CT coordinate system to correlate a point in the TCC system to perform the coordinate transfer between the two systems. Both methods were used to calculate the TCC and the results were checked against each other, creating an integrated workflow via automated self‐checking. The accuracy of the calculation system was retrospectively evaluated with 275 patients, where the actual treatment position determined with cone‐beam CT was used as a reference. Results An efficient workflow transparent to the therapists at both CT simulation and treatment was created. It works with any indexed immobilization device and can be universally applied to all treatment sites. The two methods had comparable accuracy, with 95% of the calculations within 3 mm. The inter‐fraction variation was within ± 1.0 cm for 95% of the coordinates across all the treatment sites. Conclusions A robust, accurate, and streamlined system was implemented to calculate TCCs in advance. It eases the pressure on the treating therapists, reduces patient setup time, and enhances the patient safety by preventing setup errors.

Purpose The use of the ionization chamber array ICProfiler (ICP) is limited by its relatively poor detector spatial resolution and the inherent volume averaging effect (VAE). The purpose of this work is to study the feasibility of reconstructing VAE‐free continuous photon beam profiles from ICP measurements with a machine learning technique. Methods In‐ and cross‐plane photon beam profiles of a 6 MV beam from an Elekta linear accelerator, ranging from 2 × 2 to 10 × 10 cm2 at 1.5 cm, 5 cm, and 10 cm depth, were measured with an ICP. The discrete measurements were interpolated with a Makima method to obtain continuous beam profiles. Artificial neural networks (ANNs) were trained to restore the penumbra of the beam profiles. Plane‐specific (in‐ and cr‐plane) ANNs and a combined ANN were separately trained. The performance of the ANNs was evaluated using the penumbra width difference (PWD, the difference between the penumbra widths of the reconstructed and the reference profile). The plane‐specific and the combined ANNs were compared to study the feasibility of using a single ANN for both in‐ and cross‐plane. Results The profiles reconstructed with all the ANNs had excellent agreement with the reference. For in‐plane, the ANNs reduced the PWD from 1.6 ± 0.7 mm at 1.5 cm depth to 0.1 ± 0.1 mm, from 1.8 ± 0.6 mm at 5.0 cm depth to 0.1 ± 0.1 mm, and from 2.4 ± 0.1 mm at 10.0 cm depth to 0.0 ± 0.0 mm; for cross‐plane, the ANNs reduced the PWD from 1.2 ± 0.4 mm at 1.5 cm depth, 1.2 ± 0.3 mm at 5.0 cm depth, and 1.6 ± 0.1 mm at 10.0 cm depth, to 0.1 ± 0.1 mm. Conclusions This study demonstrated the feasibility of using simple ANNs to reconstruct VAE‐free continuous photon beam profiles from discrete ICP measurements. A combined ANN can restore the penumbra of in‐ and cross‐plane beam profiles of various fields at different depths.

The charges on this task group (TG) were as follows: (a) provide specific procedural guidelines for performing the tests recommended in TG 142; (b) provide estimate of the range of time, appropriate personnel, and qualifications necessary to complete the tests in TG 142; and (c) provide sample daily, weekly, monthly, or annual quality assurance (QA) forms. Many of the guidelines in this report are drawn from the literature and are included in the references. When literature was not available, specific test methods reflect the experiences of the TG members (e.g., a test method for door interlock is self-evident with no literature necessary). In other cases, the technology is so new that no literature for test methods was available. Given broad clinical adaptation of volumetric modulated arc therapy (VMAT), which is not a specific topic of TG 142, several tests and criteria specific to VMAT were added.

Purpose To propose a universal, parameterized gradient-based method (PGM) for radiation field size determination. Methods The PGM locates the beam profile's edge by parameterizing its penumbra region with a modified sigmoid function where the inflection point can be determined in a closed form. The parametrization was validated with filter-flattened (FF), flattening-filter-free (FFF) and wedged profiles measured on two Elekta linac models (Synergy and Versa HD). Gamma analysis with the delta dose function set to zero was used to quantitatively assess the parameterization accuracy. Field sizes of FF beams were calculated with the PGM and the full width at half maximum (FWHM) methods for comparison. To assess the consistency of the PGM and the FWHM method with geometric scaling across different depths, the calculated field size at a reference depth was scaled to other depths and compared with the field sizes calculated from the measured profiles. The method was also validated against a maximum-slope method (MSM) with wedge and FFF profiles. We also evaluated the robustness of the three methods with respect to measurement noise, varying scanning step sizes, detector characteristics, and beam energy/modality. Results Small distance-to-agreement (0.02 ± 0.02 mm) between the measured and parameterized penumbra region was observed for all profiles. The differences between the field sizes calculated with the FWHM method and the PGM were consistent (0.9 ± 0.3 mm), with the FWHM method yielding larger values. With geometrical scaling, the PGM and the FWHM method produced maximum differences of 0.26 and 1.16 mm, respectively. For wedge and FFF beams, the mean differences relative to FF fields were 0.15 ± 0.09 mm and 0.57 ± 0.91 mm for the PGM and the MSM, respectively. The PGM was also found to produce more consistent results than the FWHM method and the MSM when measurement noise, scanning step size, detector characteristics, and beam energy/modality changed. Conclusion The proposed PGM is universally applicable to all beam modalities (FF, wedge and FFF) for accurate field size determination. Compared to the FWHM and the MSM, it is more robust to variations in measurement condition and detection system.

Background and purpose The aim is to determine the radiobiological parameters of four popular normal tissue complication probability (NTCP) models that describe the dose–response relations of salivary glands and pharyngeal constrictors to the severity of patient reported xerostomia and dysphagia, respectively 6 and 12 months post chemo-radiotherapy, furthermore, to evaluate the goodness-of-fit of the NTCP models for different combinations of glands and constrictors. Material and methods Forty-three patients were treated on a prospective multi-institutional phase II study (ClinicalTrials.gov, NCT01530997) assessing the efficacy of de-intensified chemoradiotherapy in patients with favorable risk, HPV-associated oropharyngeal squamous cell carcinoma. All patients received 60 Gy intensity modulated radiotherapy with concurrent weekly intravenous cisplatinum. All patients reported severity of their xerostomia and dysphagia (pre- and post-treatment) using the patient reported outcome version of the CTCAE (PRO-CTCAE). A change in severity (from baseline) of ≥2 was considered clinically meaningful. The Lyman–Kutcher–Burman (LKB), Relative Seriality (RS), Logit, and Relative Seriality Logit (RSL) NTCP models were used to fit the patients’ dose/volume data to changes in PRO-CTCAE severity of xerostomia and dysphagia (from baseline to 6 and 12 months post-treatment). The correlation of the models with the patient outcomes was performed for different combinations of salivary glands and different sections of pharyngeal constrictors. The goodness-of-fit of the different models was assessed through the area under the receiver operating characteristic curve (AUC), maximum of the log-likelihood function, normal error distribution and Akaike information criterion (AIC). Results The dose/volume metrics of the combined contralateral (parotid + submandibular) glands appear to correlate best with xerostomia, at both 6- and 12-months. Among the different sections of pharyngeal constrictors, the dose/volume metrics of the superior pharyngeal constrictors appear to correlate best with dysphagia at 6 months. The AUC values ranged from 0.72 to 0.85 in the case of xerostomia and 0.73 to 0.74 in the case of dysphagia over the different models. The four NTCP models showed similar goodness-of-fit. The differences in AIC between the different models were less than 2 and ranged within 0.7 and 0.8 in the cases of xerostomia and dysphagia, respectively. The calculated parameters of the LKB model were D50 = 26.9 Gy, m = 0.63, n = 1.0 for the combined contralateral glands at 12 months and D50 = 62.0 Gy, m = 0.10, n = 0.49 for the superior pharyngeal constrictors at 6 months. Conclusions The values of the parameters of four NTCP models were determined for salivary glands and pharyngeal constrictors. All four models could fit the clinical data equally well. The NTCP predictions of the combined contralateral glands and superior pharyngeal constrictors showed the best correlation with the patient reported outcomes of xerostomia and dysphagia, respectively.

Purpose Most VMAT algorithms compute the dose on discretized apertures with small angular separations for practical reasons. However, machines deliver the VMAT dose with a continuously moving MLC and gantry and a continuously changing dose rate. The computed dose can deviate from the delivered dose, especially if no, or loose, MLC movement constraints are applied for the VMAT optimization. The goal of this paper is to establish a simplified mathematical model to analyze the discrepancy between the VMAT plan calculation dose and the delivered dose and to provide a reasonable solution for clinical implementation. Methods A simplified metric is first introduced to describe the discrepancy between doses computed with discretized apertures and a continuous delivery model. The delivery fluences were formed separately for six different leaf movement scenarios. The formula was then rewritten in a more general form. The correlation between discretized and continuous fluence is summarized using this general form. The Fourier analysis for the impacts from three separate factors – dose kernel width, aperture width, aperture distance – to the dose discrepancy is also presented in order to provide insight into the dose discrepancy caused by under-sampling in the frequency domain. Finally, a weighting-based interpolation (WBI) algorithm, which can improve the aperture interpolation efficiency, is proposed. The associated evaluation methods and criteria for the proposed algorithm are also given. Results The comparisons between the WBI algorithm and the equal angular interpolation (EAI) method suggested that the proposed algorithm has a great advantage with regard to aperture number efficiency. To achieve a 90% gamma passing rate using the dose computed with apertures generated with 0.5° EAI, with the initial optimization apertures as the standard for the comparison, the WBI needs only 66% and 54% of the aperture numbers that the EAI method needs for a 2° and a 4° angular separation of the VMAT optimization, respectively. The results also suggested that the weighted dose error index value, Θ, can be used as a stopping criterion for an interpolation algorithm, e.g., WBI or EAI, or as an indicator for sampling level evaluations. The phantom results indicate that the gamma passing rate decreases with increasing depth, from the phantom surface to the iso center, for the plans computed with under-sampled apertures. No obvious variation trends were observed for the plans computed with well-sampled apertures. Conclusions The mathematical analysis suggests that the dose discrepancies due to under-sampling are strongly correlated with the aperture width, the distance between apertures, and the width of the dose kernel. The WBI algorithm proves to be an efficient aperture interpolation strategy and is useful for dose computation of VMAT plans.

The aim of this study is to perform a direct comparison of the source model for photon beams with and without flattening filter (FF) and to develop an efficient independent algorithm for planar dose calculation for FF‐free (FFF) intensity‐modulated radiotherapy (IMRT) quality assurance (QA). The source model consisted of a point source modeling the primary photons and extrafocal bivariate Gaussian functions modeling the head scatter, monitor chamber backscatter, and collimator exchange effect. The model parameters were obtained by minimizing the difference between the calculated and measured in‐air output factors (S c). The fluence of IMRT beams was calculated from the source model using a backprojection and integration method. The off‐axis ratio in FFF beams were modeled with a fourth degree polynomial. An analytical kernel consisting of the sum of three Gaussian functions was used to describe the dose deposition process. A convolution‐based method was used to account for the ionization chamber volume averaging effect when commissioning the algorithm. The algorithm was validated by comparing the calculated planar dose distributions of FFF head‐and‐neck IMRT plans with measurements performed with a 2D diode array. Good agreement between the measured and calculated S c was achieved for both FF beams (

Purpose: To investigate the geometry dependence of the detector response function (DRF) of three commonly used scanning ionization chambers and its impact on a convolution-based method to address the volume averaging effect (VAE). Methods: A convolution-based approach has been proposed recently to address the ionization chamber VAE. It simulates the VAE in the treatment planning system (TPS) by iteratively convolving the calculated beam profiles with the DRF while optimizing the beam model. Since the convolved and the measured profiles are subject to the same VAE, the calculated profiles match the implicit “real” ones when the optimization converges. Three DRFs (Gaussian, Lorentzian, and parabolic function) were used for three ionization chambers (CC04, CC13, and SNC125c) in this study. Geometry dependent/independent DRFs were obtained by minimizing the difference between the ionization chamber-measured profiles and the diode-measured profiles convolved with the DRFs. These DRFs were used to obtain eighteen beam models for a commercial TPS. Accuracy of the beam models were evaluated by assessing the 20%–80% penumbra width difference (PWD) between the computed and diode-measured beam profiles. Results: The convolution-based approach was found to be effective for all three ionization chambers with significant improvement for all beam models. Up to 17% geometry dependence of the three DRFs was observed for the studied ionization chambers. With geometry dependent DRFs, the PWD was within 0.80 mm for the parabolic function and CC04 combination and within 0.50 mm for other combinations; with geometry independent DRFs, the PWD was within 1.00 mm for all cases. When using the Gaussian function as the DRF, accounting for geometry dependence led to marginal improvement (PWD < 0.20 mm) for CC04; the improvement ranged from 0.38 to 0.65 mm for CC13; for SNC125c, the improvement was slightly above 0.50 mm. Conclusions: Although all three DRFs were found adequate to represent the response of the studied ionization chambers, the Gaussian function was favored due to its superior overall performance. The geometry dependence of the DRFs can be significant for clinical applications involving small fields such as stereotactic radiotherapy.

Purpose: In radiation therapy, accurate data acquisition of photon beam dosimetric quantities is important for (1) beam modeling data input into a treatment planning system (TPS), (2) comparing measured and TPS modeled data, (3) the quality assurance process of a linear accelerator’s (Linac) beam characteristics, (4) the establishment of a standard data set for comparison with other data, etcetera. Parameterization of the photon beam dosimetry creates a data set that is portable and easy to implement for different applications such as those previously mentioned. The aim of this study is to develop methods to parameterize photon beam dosimetric quantities, including percentage depth doses (PDDs), profiles, and total scatter output factors (Scp). Methods: Scp, PDDs, and profiles for different field sizes, depths, and energies were measured for a Linac using a cylindrical 3D water scanning system. All data were smoothed for the analysis and profile data were also centered, symmetrized, and geometrically scaled. The Scp data were analyzed using an exponential function. The inverse square factor was removed from the PDD data before modeling and the data were subsequently analyzed using exponential functions. For profile modeling, one halfside of the profile was divided into three regions described by exponential, sigmoid, and Gaussian equations. All of the analytical functions are field size, energy, depth, and, in the case of profiles, scan direction specific. The model’s parameters were determined using the minimal amount of measured data necessary. The model’s accuracy was evaluated via the calculation of absolute differences between the measured (processed) and calculated data in low gradient regions and distance-to-agreement analysis in high gradient regions. Finally, the results of dosimetric quantities obtained by the fitted models for a different machine were also assessed. Results: All of the differences in the PDDs’ buildup and the profiles’ penumbra regions were less than 2 and 0.5 mm, respectively. The differences in the low gradient regions were 0.20% ± 0.20% (

Compared to 3D cone beam computed tomography (3D CBCT), the image quality of commercially available four-dimensional (4D) CBCT is severely impaired due to the insufficient amount of projection data available for each phase. Since the traditional Feldkamp-Davis-Kress (FDK)-based algorithm is infeasible for reconstructing high quality 4D CBCT images with limited projections, investigators had developed several compress-sensing (CS) based algorithms to improve image quality. The aim of this study is to develop a novel algorithm which can provide better image quality than the FDK and other CS based algorithms with limited projections. We named this algorithm 'the common mask guided image reconstruction' (c-MGIR).In c-MGIR, the unknown CBCT volume is mathematically modeled as a combination of phase-specific motion vectors and phase-independent static vectors. The common-mask matrix, which is the key concept behind the c-MGIR algorithm, separates the common static part across all phase images from the possible moving part in each phase image. The moving part and the static part of the volumes were then alternatively updated by solving two sub-minimization problems iteratively. As the novel mathematical transformation allows the static volume and moving volumes to be updated (during each iteration) with global projections and 'well' solved static volume respectively, the algorithm was able to reduce the noise and under-sampling artifact (an issue faced by other algorithms) to the maximum extent. To evaluate the performance of our proposed c-MGIR, we utilized imaging data from both numerical phantoms and a lung cancer patient. The qualities of the images reconstructed with c-MGIR were compared with (1) standard FDK algorithm, (2) conventional total variation (CTV) based algorithm, (3) prior image constrained compressed sensing (PICCS) algorithm, and (4) motion-map constrained image reconstruction (MCIR) algorithm, respectively. To improve the efficiency of the algorithm, the code was implemented with a graphic processing unit for parallel processing purposes.Root mean square error (RMSE) between the ground truth and reconstructed volumes of the numerical phantom were in the descending order of FDK, CTV, PICCS, MCIR, and c-MGIR for all phases. Specifically, the means and the standard deviations of the RMSE of FDK, CTV, PICCS, MCIR and c-MGIR for all phases were 42.64 ± 6.5%, 3.63 ± 0.83%, 1.31% ± 0.09%, 0.86% ± 0.11% and 0.52 % ± 0.02%, respectively. The image quality of the patient case also indicated the superiority of c-MGIR compared to other algorithms.The results indicated that clinically viable 4D CBCT images can be reconstructed while requiring no more projection data than a typical clinical 3D CBCT scan. This makes c-MGIR a potential online reconstruction algorithm for 4D CBCT, which can provide much better image quality than other available algorithms, while requiring less dose and potentially less scanning time.

In the era of high‐precision radiotherapy, cone‐beam CT (CBCT) is frequently utilized for on‐board treatment guidance. However, CBCT images usually contain severe shading artifacts due to strong photon scatter from illumination of a large volume and non‐optimized patient‐specific data measurements, limiting the full clinical applications of CBCT. Many algorithms have been proposed to alleviate this problem by data correction on projections. Sophisticated methods have also been designed when prior patient information is available. Nevertheless, a standard, efficient, and effective approach with large applicability remains elusive for current clinical practice. In this work, we develop a novel algorithm for shading correction directly on CBCT images. Distinct from other image‐domain correction methods, our approach does not rely on prior patient information or prior assumption of patient data. In CBCT, projection errors (mostly from scatter and non‐ideal usage of bowtie filter) result in dominant low‐frequency shading artifacts in image domain. In circular scan geometry, these artifacts often show global or local radial patterns. Hence, the raw CBCT images are first preprocessed into the polar coordinate system. Median filtering and polynomial fitting are applied on the transformed image to estimate the low‐frequency shading artifacts (referred to as the bias field) angle‐by‐angle and slice‐by‐slice. The low‐pass filtering process is done firstly along the angular direction and then the radial direction to preserve image contrast. The estimated bias field is then converted back to the Cartesian coordinate system, followed by 3D low‐pass filtering to eliminate possible high‐frequency components. The shading‐corrected image is finally obtained as the uncorrected volume divided by the bias field. The proposed algorithm was evaluated on CBCT images of a pelvis patient and a head patient. Mean CT number values and spatial non‐uniformity on the reconstructed images were used as image quality metrics. Within selected regions of interest, the average CT number error was reduced from around 300 HU to 42 and 38 HU, and the spatial nonuniformity error was reduced from above 17.5% to 2.1% and 1.7% for the pelvis and the head patients, respectively. As our method suppresses only low‐frequency shading artifacts, patient anatomy and contrast were retained in the corrected images for both cases. Our shading correction algorithm on CBCT images offers several advantages. It has a high efficiency, since it is deterministic and directly operates on the reconstructed images. It requires no prior information or assumptions, which not only achieves the merits of CBCT‐based treatment monitoring by retaining the patient anatomy, but also facilitates its clinical use as an efficient image‐correction solution. PACS number(s): 87.57.C‐, 87.57.cp, 87.57.Q‐

Various dosimetric benefits such as increased dose rate, and reduced leakage and out of field dose have led to the growth of flattening-filter-free (FFF) technology in the clinic. In this study, we concentrate on investigating the feasibility of using FFF beams to deliver conventional flat beams, since completely getting rid of the flattening-filter module from the gantry head can not only simplify the gantry design but also decrease the workload on machine maintenance and quality assurance. Two intensity modulated radiotherapy techniques, step-and-shoot (S&S) and sliding window (SW), were used to generate flat beam profiles for 6 regular-shaped beams and 3 clinical beams while operating in FFF mode. The inverse plans were generated based on uniform dose optimization. Degree of flatness, MU efficiency, and beam delivery time for both methods were assessed. S&S technique is able to achieve a degree of flatness less than 2.5% for most field configurations. While SW technique was able to generate relatively flat beams for field sizes less than 18 × 18 cm2. For all field configurations, S&S beams resulted in a longer delivery time compared to reference flat beams and SW beams. For field sizes less than 18 × 18 cm2, SW modulated FFF beams resulted in a faster delivery time compared to reference flat beams. The ability to deliver conventional flat beams is not absent when operating in FFF mode. Utilizing beam modulation, FFF mode can achieve reasonable flat profiles and comparable efficiency to conventional flat beams. The ability to deliver most clinical treatments from the same treatment unit will allow for less quality assurance as well as maintenance, and completely eliminate the need for the flattening filter on modern linacs.

PURPOSE/OBJECTIVE(S) To determine if routinely replanning patients treated for oropharyngeal cancer that is p16-positive and clinical neck stage N2b (AJCC 7th edition) is likely to result in dose changes that will improve patient outcomes to a meaningful degree. METHODS In 10 consecutive patients treated with primary radiotherapy (RT) and concurrent weekly chemotherapy for p16-positive N2b oropharyngeal carcinoma, we prospectively evaluated dose changes from replanning for the final 4 or 2 weeks of RT of a 7-week RT program. RESULTS Replanning for the final 4 or 2 weeks improved planning target volume coverage by an average of 4 and 2 percentage points, respectively. For all normal structures, the dose change was small (

Purpose Ionization chambers are the detectors of choice for photon beam profile scanning. However, they introduce significant volume averaging effect (VAE) that can artificially broaden the penumbra width by 2-3 mm. The purpose of this study was to examine the feasibility of photon beam profile deconvolution (the elimination of VAE from ionization chamber-measured beam profiles) using a three-layer feedforward neural network. Methods Transverse beam profiles of photon fields between 2 × 2 and 10 × 10 cm2 were collected with both a CC13 ionization chamber and an EDGE diode detector on an Elekta Versa HD accelerator. These profiles were divided into three datasets (training, validation and test) to train and test a three-layer feedforward neural network. A sliding window was used to extract input data from the CC13-measured profiles. The neural network produced the deconvolved value at the center of the sliding window. The full deconvolved profile was obtained after the sliding window was moved over the measured profile from end to end. The EDGE-measured beam profiles were used as reference for the training, validation, and test. The number of input neurons, which equals the sliding window width, and the number of hidden neurons were optimized with a parametric sweeping method. A total of 135 neural networks were fully trained with the Levenberg-Marquardt backpropagation algorithm. The one with the best overall performance on the training and validation dataset was selected to test its generalization ability on the test dataset. The agreement between the neural network-deconvolved profiles and the EDGE-measured profiles was evaluated with two metrics: mean squared error (MSE) and penumbra width difference (PWD). Results Based on the two-dimensional MSE plots, the optimal combination of sliding window width of 15 and 5 hidden neurons was selected for the final neural network. Excellent agreement was achieved between the neural network-deconvolved profiles and the reference profiles in all three datasets. After deconvolution, the mean PWD reduced from 2.43 ± 0.26, 2.44 ± 0.36, and 2.46 ± 0.29 mm to 0.15 ± 0.15, 0.04 ± 0.03, and 0.14 ± 0.09 mm for the training, validation, and test dataset, respectively. Conclusions We demonstrated the feasibility of photon beam profile deconvolution with a feedforward neural network in this work. The beam profiles deconvolved with a three-layer neural network had excellent agreement with diode-measured profiles.

The ionization chamber volume averaging effect is a well-known issue without an elegant solution. The purpose of this study is to propose a novel convolution-based approach to address the volume averaging effect in model-based treatment planning systems (TPSs). Ionization chamber-measured beam profiles can be regarded as the convolution between the detector response function and the implicit real profiles. Existing approaches address the issue by trying to remove the volume averaging effect from the measurement. In contrast, our proposed method imports the measured profiles directly into the TPS and addresses the problem by reoptimizing pertinent parameters of the TPS beam model. In the iterative beam modeling process, the TPS-calculated beam profiles are convolved with the same detector response function. Beam model parameters responsible for the penumbra are optimized to drive the convolved profiles to match the measured profiles. Since the convolved and the measured profiles are subject to identical volume averaging effect, the calculated profiles match the real profiles when the optimization converges. The method was applied to reoptimize a CC13 beam model commissioned with profiles measured with a standard ionization chamber (Scanditronix Wellhofer, Bartlett, TN). The reoptimized beam model was validated by comparing the TPS-calculated profiles with diode-measured profiles. Its performance in intensity-modulated radiation therapy (IMRT) quality assurance (QA) for ten head-and-neck patients was compared with the CC13 beam model and a clinical beam model (manually optimized, clinically proven) using standard Gamma comparisons. The beam profiles calculated with the reoptimized beam model showed excellent agreement with diode measurement at all measured geometries. Performance of the reoptimized beam model was comparable with that of the clinical beam model in IMRT QA. The average passing rates using the reoptimized beam model increased substantially from 92.1% to 99.3% with 3%/3 mm and from 79.2% to 95.2% with 2%/2 mm when compared with the CC13 beam model. These results show the effectiveness of the proposed method. Less inter-user variability can be expected of the final beam model. It is also found that the method can be easily integrated into model-based TPS.

Purpose: The use of sophisticated dose calculation procedure in modern radiation therapy treatment planning is inevitable in order to account for complex treatment fields created by multileaf collimators (MLCs). As a consequence, independent volumetric dose verification is time consuming, which affects the efficiency of clinical workflow. In this study, the authors present an efficient adaptive beamlet-based finite-size pencil beam (AB-FSPB) dose calculation algorithm that minimizes the computational procedure while preserving the accuracy. Methods: The computational time of finite-size pencil beam (FSPB) algorithm is proportional to the number of infinitesimal and identical beamlets that constitute an arbitrary field shape. In AB-FSPB, dose distribution from each beamlet is mathematically modeled such that the sizes of beamlets to represent an arbitrary field shape no longer need to be infinitesimal nor identical. As a result, it is possible to represent an arbitrary field shape with combinations of different sized and minimal number of beamlets. In addition, the authors included the model parameters to consider MLC for its rounded edge and transmission. Results: Root mean square error (RMSE) between treatment planning system and conventional FSPB on a 10 × 10 cm2 square field using 10 × 10, 2.5 × 2.5, and 0.5 × 0.5 cm2 beamlet sizes were 4.90%, 3.19%, and 2.87%, respectively, compared with RMSE of 1.10%, 1.11%, and 1.14% for AB-FSPB. This finding holds true for a larger square field size of 25 × 25 cm2, where RMSE for 25 × 25, 2.5 × 2.5, and 0.5 × 0.5 cm2 beamlet sizes were 5.41%, 4.76%, and 3.54% in FSPB, respectively, compared with RMSE of 0.86%, 0.83%, and 0.88% for AB-FSPB. It was found that AB-FSPB could successfully account for the MLC transmissions without major discrepancy. The algorithm was also graphical processing unit (GPU) compatible to maximize its computational speed. For an intensity modulated radiation therapy (∼12 segments) and a volumetric modulated arc therapy fields (∼90 control points) with a 3D grid size of 2.0 × 2.0 × 2.0 mm3, dose was computed within 3–5 and 10–15 s timeframe, respectively. Conclusions: The authors have developed an efficient adaptive beamlet-based pencil beam dose calculation algorithm. The fast computation nature along with GPU compatibility has shown better performance than conventional FSPB. This enables the implementation of AB-FSPB in the clinical environment for independent volumetric dose verification.

Purpose: Accurately localizing lung tumor localization is essential for high-precision radiation therapy techniques such as stereotactic body radiation therapy (SBRT). Since direct monitoring of tumor motion is not always achievable due to the limitation of imaging modalities for treatment guidance, placement of fiducial markers on the patient’s body surface to act as a surrogate for tumor position prediction is a practical alternative for tracking lung tumor motion during SBRT treatments. In this work, the authors propose an innovative and robust model to solve the multimarker position optimization problem. The model is able to overcome the major drawbacks of the sparse optimization approach (SOA) model. Methods: The principle-component-analysis (PCA) method was employed as the framework to build the authors’ statistical prediction model. The method can be divided into two stages. The first stage is to build the surrogate tumor matrix and calculate its eigenvalues and associated eigenvectors. The second stage is to determine the “best represented” columns of the eigenvector matrix obtained from stage one and subsequently acquire the optimal marker positions as well as numbers. Using 4-dimensional CT (4DCT) and breath hold CT imaging data, the PCA method was compared to the SOA method with respect to calculation time, average prediction accuracy, prediction stability, noise resistance, marker position consistency, and marker distribution. Results: The PCA and SOA methods which were both tested were on all 11 patients for a total of 130 cases including 4DCT and breath-hold CT scenarios. The maximum calculation time for the PCA method was less than 1 s with 64 752 surface points, whereas the average calculation time for the SOA method was over 12 min with 400 surface points. Overall, the tumor center position prediction errors were comparable between the two methods, and all were less than 1.5 mm. However, for the extreme scenarios (breath hold), the prediction errors for the PCA method were not only smaller, but were also more stable than for the SOA method. Results obtained by imposing a series of random noises to the surrogates indicated that the PCA method was much more noise resistant than the SOA method. The marker position consistency tests using various combinations of 4DCT phases to construct the surrogates suggested that the marker position predictions of the PCA method were more consistent than those of the SOA method, in spite of surrogate construction. Marker distribution tests indicated that greater than 80% of the calculated marker positions fell into the high cross correlation and high motion magnitude regions for both of the algorithms. Conclusions: The PCA model is an accurate, efficient, robust, and practical model for solving the multimarker position optimization problem to predict lung tumor motion during SBRT treatments. Due to its generality, PCA model can also be applied to other imaging guidance system whichever using surface motion as the surrogates.

Purpose: Recent knowledge on the effects of cardiac toxicity warrants greater precision for left-sided breast radiotherapy. Different breath-hold (BH) maneuvers (abdominal vs thoracic breathing) can lead to chest wall positional variations, even though the patient’s tidal volume remains consistent. This study aims to investigate the feasibility of using optical tracking for real-time quality control of active breathing coordinator (ABC)-assisted deep inspiration BH (DIBH). Methods: An in-house optical tracking system (OTS) was used to monitor ABC-assisted DIBH. The stability and localization accuracy of the OTS were assessed with a ball-bearing phantom. Seven patients with left-sided breast cancer were included. A free-breathing (FB) computed tomography (CT) scan and an ABC-assisted BH CT scan were acquired for each patient. The OTS tracked an infrared (IR) marker affixed over the patient’s xiphoid process to measure the positional variation of each individual BH. Using the BH within which the CT scan was performed as the reference, the authors quantified intra- and interfraction BH variations for each patient. To estimate the dosimetric impact of BH variations, the authors studied the positional correlation between the marker and the left breast using the FB CT and BH CT scans. The positional variations of 860 BHs as measured by the OTS were retrospectively incorporated into the original treatment plans to evaluate their dosimetric impact on breast and cardiac organs [heart and left anterior descending (LAD) artery]. Results: The stability and localization accuracy of the OTS was within 0.2 mm along each direction. The mean intrafraction variation among treatment BHs was less than 2.8 mm in all directions. Up to 12.6 mm anteroposterior undershoot, where the patient’s chest wall displacement of a BH is less than that of a reference BH, was observed with averages of 4.4, 3.6, and 0.1 mm in the anteroposterior, craniocaudal, and mediolateral directions, respectively. A high positional correlation between the marker and the breast was found in the anteroposterior and craniocaudal directions with respective Pearson correlation values of 0.95 and 0.93, but no mediolateral correlation was found. Dosimetric impact of BH variations on breast coverage was negligible. However, the mean heart dose, mean LAD dose, and max LAD dose were estimated to increase from 1.4/7.4/18.6 Gy (planned) to 2.1/15.7/31.0 Gy (delivered), respectively. Conclusions: In ABC-assisted DIBH, large positional variation can occur in some patients, due to their different BH maneuvers. The authors’ study has shown that OTS can be a valuable tool for real-time quality control of ABC-assisted DIBH.

Historical radiotherapy treatment plans lack 3D images sets required for estimating mean organ doses to patients. Alternatively, Monte Carlo-based models of radiotherapy devices coupled with whole-body computational phantoms can permit estimates of historical in-field and out-of-field organ doses as needed for studies associating radiation exposure and late tissue toxicities. In recreating historical patient treatments with 60Co based systems, the major components to be modeled include the source capsule, surrounding shielding layers, collimators (both fixed and adjustable), and trimmers as needed to vary field size. In this study, a computational model and experimental validation of the Theratron T-1000 are presented. Model validation is based upon in-field commissioning data collected at the University of Florida, published out-of-field data from the British Journal of Radiology (BJR) Supplement 25, and out-of-field measurements performed at the University of Wisconsin's Accredited Dosimetry Calibration Laboratory (UWADCL). The computational model of the Theratron T-1000 agrees with central axis percentage depth dose data to within 2% for 6 × 6 to 30 × 30 cm2 fields. Out-of-field doses were found to vary between 0.6% to 2.4% of central axis dose at 10 cm from field edge and 0.42% to 0.97% of central axis dose at 20 cm from the field edge, all at 5 cm depth. Absolute and relative differences between computed and measured out-of-field doses varied between ±2.5% and ±100%, respectively, at distances up to 60 cm from the central axis. The source-term model was subsequently combined with patient-morphometry matched computational hybrid phantoms as a method for estimating in-field and out-of-field organ doses for patients treated for Hodgkin's Lymphoma. By changing field size and position, and adding patient-specific field shaping blocks, more complex historical treatment set-ups can be to recreated, particularly those for which 2D or 3D image sets are unavailable.

Purpose: Commercial optical tracking system such as BrainLab ExacTrac© suffers from ambiguous markers which can cause significant delay in patient treatment. We developed an ambiguity‐free optical tracking system for high precision SBRT.Methods: The optical tracking system consists of a pair of camerasensors, 4∼8 infra‐red (IR) reflective markers affixed on patient skin and in‐house developed software. We developed an effective algorithm to automatically eliminate ambiguous markers. A recursive backtracking algorithm was developed to build one‐to‐one correspondence between reference markers and optical markers. The algorithm was able to deal with missing, misplaced, or occluded markers by introducing ‘dummy’ markers. Isocenter displacements were calculated in six‐degree of freedom through rigid‐body registration between reference markers and optical markers. The system accuracy was evaluated with a pelvis phantom against cone beam CT(CBCT) and ExacTrac. The impact of number of markers on tracking accuracy was also evaluated. The performance of automatic ambiguity elimination was assessed with synthetic and clinic marker patterns. Results: Difference of isocenter displacement reported by our system and commercial systems (CBCT, ExacTrac) were within 0.5 mm/0.1o. Impact of number of markers on tracking accuracy in our phantom test was negligible with isocenter displacement varying within 0.2 mm/0.2o when number of markers varied from 4 to 8. The system successfully identified and eliminated ambiguous markers in both synthetic and clinic marker patterns. Conclusions: An accurate optical tracking system free of ambiguous markers was developed for patient positioning and monitoring in high precision SBRT. The developed algorithms to eliminate ambiguous markers and to handle missing, misplaced or occluded markers were effective and efficient.

Purpose: To optimize planning and delivery efficiency, and quality of head and neck IMRT through the evaluation of planning parameters. This study also serves to identify the impact on dose accuracy due to calculation grid size. Methods: Eleven head and neck patients, 45 trials per patient (495 trials in total), were evaluated varying IMRT parameters of dose grid, minimum MU per segment, minimum segment area, and control point number. Plans were recomputed on Pinnacle Treatment Planning System (TPS), and scaled to the planning target volume (PTV) constraint of 95% volume. Differential dose volume histograms (DVHs) were exported, and a program was written to compile DVH results. Plans were delivered on an Elekta Synergy linear accelerator to assess delivery time. Plan quality, calculation time, and delivery time served as this study's endpoints. Results: The 4 mm dose grid with 2 mm fluence grid in each direction, saving 1/3 the computation time, were most comparable by DVH results to the 2 mm dose and fluence grid. Dose uncertainty due to dose calculation grid effect was as high as 8.2%, 5.5 Gy for PTVs and 13.3%, 2.1 Gy for organs at risk. Smaller volumes and high gradient regions were more susceptible to uncertainties. Threshold values that maintained adequate plan quality were 5 cm2 for minimum segment area and 5 MU for minimum MU. Minimum MU was more costly in terms of plan quality compared to the minimum segment area. Conclusions: DVH differences can be effectively used to quantify the dose grid calculation uncertainty. For minimum MU and segment area, the DVH differences are an effect of the intensity map, defined by MLC shape and the number of control points. Exceeding the adequate number of control points diminishes returns of plan quality and increases patient treatment time.

The purpose of this study is to investigate changes in lung tumor internal target volume during stereotactic body radiotherapy treatment (SBRT) using magnetic resonance imaging (MRI). Ten lung cancer patients (13 tumors) undergoing SBRT (48 Gy over four consecutive days) were evaluated. Each patient underwent three lung MRI evaluations: before SBRT (MRI‐1), after fraction 3 of SBRT (MRI‐3), and three months after completion of SBRT (MRI‐3m). Each MRI consisted of T1‐weighted images in axial plane through the entire lung. A cone‐beam CT (CBCT) was taken before each fraction. On MRI and CBCT taken before fractions 1 and 3, gross tumor volume (GTV) was contoured and differences between the two volumes were compared. Median tumor size on CBCT before fractions 1 (CBCT‐1) and 3 (CBCT‐3) was 8.68 and 11.10 cm3, respectively. In 12 tumors, the GTV was larger on CBCT‐3 compared to CBCT‐1 (median enlargement, 1.56 cm3). Median tumor size on MRI‐1, MRI‐3, and MRI‐3m was 7.91, 11.60, and 3.33 cm3, respectively. In all patients, the GTV was larger on MRI‐3 compared to MRI‐1 (median enlargement, 1.54 cm3). In all patients, GTV was smaller on MRI‐3m compared to MRI‐1 (median shrinkage, 5.44 cm3). On CBCT and MRI, all patients showed enlargement of the GTV during the treatment week of SBRT, except for one patient who showed minimal shrinkage (0.86 cm3). Changes in tumor volume are unpredictable; therefore, motion and breathing must be taken into account during treatment planning, and image‐guided methods should be used, when treating with large fraction sizes. PACS number: 87.53.Ly

Treatment of the wrong body part due to incorrect setup is among the leading types of errors in radiotherapy. The purpose of this paper is to report an efficient automatic patient safety system (PSS) to prevent gross setup errors. The system consists of a pair of charge‐coupled device (CCD) cameras mounted in treatment room, a single infrared reflective marker (IRRM) affixed on patient or immobilization device, and a set of in‐house developed software. Patients are CT scanned with a CT BB placed over their surface close to intended treatment site. Coordinates of the CT BB relative to treatment isocenter are used as reference for tracking. The CT BB is replaced with an IRRM before treatment starts. PSS evaluates setup accuracy by comparing real‐time IRRM position with reference position. To automate system workflow, PSS synchronizes with the record‐and‐verify (R&V) system in real time and automatically loads in reference data for patient under treatment. Special IRRMs, which can permanently stick to patient face mask or body mold throughout the course of treatment, were designed to minimize therapist's workload. Accuracy of the system was examined on an anthropomorphic phantom with a designed end‐to‐end test. Its performance was also evaluated on head and neck as well as abdominalpelvic patients using cone‐beam CT (CBCT) as standard. The PSS system achieved a seamless clinic workflow by synchronizing with the R&V system. By permanently mounting specially designed IRRMs on patient immobilization devices, therapist intervention is eliminated or minimized. Overall results showed that the PSS system has sufficient accuracy to catch gross setup errors greater than 1 cm in real time. An efficient automatic PSS with sufficient accuracy has been developed to prevent gross setup errors in radiotherapy. The system can be applied to all treatment sites for independent positioning verification. It can be an ideal complement to complex image‐guidance systems due to its advantages of continuous tracking ability, no radiation dose, and fully automated clinic workflow. PACS number: 87.55.Qr

Purpose: In this work, the authors propose a novel registration strategy for translation-only correction scenarios of lung stereotactic body radiation therapy setups, which can achieve optimal dose coverage for tumors as well as preserve the consistency of registrations with minimal human interference. Methods: The proposed solution (centroid-to-centroidor CTC solution) uses the average four-dimensional CT (A4DCT) as the reference CT. The cone-beam CT(CBCT) is deformed to acquire a new centroid for the internal target volume (ITV) on the CBCT. The registration is then accomplished by simply aligning the centroids of the ITVs between the A4DCT and the CBCT. Sixty-seven cases using 64 patients (each case is associated with separate isocenters) have been investigated with the CTC method and compared with the conventional gray-value (G) mode and bone (B) mode registration methods. Dosimetric effects among the tree methods were demonstrated by 18 selected cases. The uncertainty of the CTC method has also been studied. Results: The registration results demonstrate the superiority of the CTC method over the other two methods. The differences in the D99 and D95 ITV dose coverage between the CTC method and the original plan is small (within 5%) for all of the selected cases except for one for which the tumor presented significant growth during the period between the CT scan and the treatment. Meanwhile, the dose coverage differences between the original plan and the registration results using either the B or G method are significant, as tumor positions varied dramatically, relative to the rib cage, from their positions on the original CT. The largest differences between the D99 and D95 dose coverage of the ITV using the B or G method versus the original plan are as high as 50%. The D20 differences between any of the methods versus the original plan are all less than 2%. Conclusions: The CTC method can generate optimal dose coverage to tumors with much better consistency compared with either the G or B method, and it is especially useful when the tumor position varies greatly from its position on the original CT, relative to the rib cage.

To investigate the geometry dependence of the detector response function (DRF) of three commonly used scanning ionization chambers and its impact on a convolution-based method to address the volume averaging effect (VAE).A convolution-based approach has been proposed recently to address the ionization chamber VAE. It simulates the VAE in the treatment planning system (TPS) by iteratively convolving the calculated beam profiles with the DRF while optimizing the beam model. Since the convolved and the measured profiles are subject to the same VAE, the calculated profiles match the implicit "real" ones when the optimization converges. Three DRFs (Gaussian, Lorentzian, and parabolic function) were used for three ionization chambers (CC04, CC13, and SNC125c) in this study. Geometry dependent/independent DRFs were obtained by minimizing the difference between the ionization chamber-measured profiles and the diode-measured profiles convolved with the DRFs. These DRFs were used to obtain eighteen beam models for a commercial TPS. Accuracy of the beam models were evaluated by assessing the 20%-80% penumbra width difference (PWD) between the computed and diode-measured beam profiles.The convolution-based approach was found to be effective for all three ionization chambers with significant improvement for all beam models. Up to 17% geometry dependence of the three DRFs was observed for the studied ionization chambers. With geometry dependent DRFs, the PWD was within 0.80 mm for the parabolic function and CC04 combination and within 0.50 mm for other combinations; with geometry independent DRFs, the PWD was within 1.00 mm for all cases. When using the Gaussian function as the DRF, accounting for geometry dependence led to marginal improvement (PWD0.20 mm) for CC04; the improvement ranged from 0.38 to 0.65 mm for CC13; for SNC125c, the improvement was slightly above 0.50 mm.Although all three DRFs were found adequate to represent the response of the studied ionization chambers, the Gaussian function was favored due to its superior overall performance. The geometry dependence of the DRFs can be significant for clinical applications involving small fields such as stereotactic radiotherapy.

Purpose: The efficacy of image-guided high-dose rate brachytherapy for cervical cancer is limited by the ineffective rectal sparing devices available commercially and the potential applicator movement. We developed a novel device using a balloon catheter and a belt immobilization system, serving for rectal dose reduction and applicator immobilization purposes, respectively. Methods: The balloon catheter is constructed by gluing a short inflatable tube to a long regular open-end catheter. Contrast agent (10) cm3 is injected into the inflatable end, which is affixed to the tandem and ring applicator, to displace the posterior vaginal wall. The belt immobilization system consists of a specially designed bracket that can hold and fix itself to the applicator, a diaper-like Velcro fastener package used for connecting the patient’s pelvis to the bracket, and a buckle that holds the fasteners to stabilize the whole system. The treatment data for 21 patients with cervical cancer using both balloon catheter and belt immobilization system were retrospectively analyzed. Computed tomography and magnetic resonance images, acquired about 30 minutes apart, were registered to evaluate the effectiveness of the immobilization system. Results: In comparison with a virtual rectal blade, the balloon decreased the rectal point dose by 34% ± 4.2% (from 276 ± 57 to 182 ± 38 cGy), corresponding to an extra sparing distance of 7.9 ± 1.1 mm. The maximum sparing distance variation per patient is 1.4 ± 0.6 mm, indicating the high interfractional reproducibility for rectum sparing. With the immobilization system, the mean translational and rotational displacements of the applicator set are Conclusions: The rectal balloon provides significant dose reduction to the rectum and it may potentially minimize patient discomfort. The immobilization system permits almost no movement of the applicator during treatment. This work has the potential to be promoted as a standardized solution for high-dose rate treatment of cervical cancer.

In radiation therapy, accurate data acquisition of photon beam dosimetric quantities is important for (1) beam modeling data input into a treatment planning system (TPS), (2) comparing measured and TPS modeled data, (3) the quality assurance process of a linear accelerator's (Linac) beam characteristics, (4) the establishment of a standard data set for comparison with other data, etcetera. Parameterization of the photon beam dosimetry creates a data set that is portable and easy to implement for different applications such as those previously mentioned. The aim of this study is to develop methods to parameterize photon beam dosimetric quantities, including percentage depth doses (PDDs), profiles, and total scatter output factors (S(cp)).S(cp), PDDs, and profiles for different field sizes, depths, and energies were measured for a Linac using a cylindrical 3D water scanning system. All data were smoothed for the analysis and profile data were also centered, symmetrized, and geometrically scaled. The S(cp) data were analyzed using an exponential function. The inverse square factor was removed from the PDD data before modeling and the data were subsequently analyzed using exponential functions. For profile modeling, one halfside of the profile was divided into three regions described by exponential, sigmoid, and Gaussian equations. All of the analytical functions are field size, energy, depth, and, in the case of profiles, scan direction specific. The model's parameters were determined using the minimal amount of measured data necessary. The model's accuracy was evaluated via the calculation of absolute differences between the measured (processed) and calculated data in low gradient regions and distance-to-agreement analysis in high gradient regions. Finally, the results of dosimetric quantities obtained by the fitted models for a different machine were also assessed.All of the differences in the PDDs' buildup and the profiles' penumbra regions were less than 2 and 0.5 mm, respectively. The differences in the low gradient regions were 0.20% ± 0.20% (1% for all) and 0.50% ± 0.35% (1% for all) for PDDs and profiles, respectively. For S(cp) data, all of the absolute differences were less than 0.5%.This novel analytical model with minimum measurement requirements was proved to accurately calculate PDDs, profiles, and S(cp) for different field sizes, depths, and energies.

Purpose: The purpose of this work is to investigate the impact of small rotational errors on the magnitudes and distributions of spatial dose variations for intracranial stereotactic radiotherapy (SRT) treatment setups, and to assess the feasibility of using the original dose map overlaid with rotated contours (ODMORC) method as a fast, online evaluation tool to estimate dose changes (using DVHs) to clinical target volumes (CTVs) and organs-at-risks (OARs) caused by small rotational setup errors. Methods: Fifteen intracranial SRT cases treated with either three-dimensional conformal radiation therapy (3DCRT) or intensity-modulated radiation therapy(IMRT) techniques were chosen for the study. Selected cases have a variety of anatomical dimensions and pathologies. Angles of ±3° and ±5° in all directions were selected to simulate the rotational errors. Dose variations in different regions of the brain, CTVs, and OARs were evaluated to illustrate the various spatial effects of dose differences before and after rotations. DVHs accounting for rotations that were recomputed by the treatment planning system (TPS) and those generated by the ODMORC method were compared. A framework of a fast algorithm for multicontour rotation implemented by ODMORC is introduced as well. Results: The average values of relative dose variations between original dose and recomputed dose accounting for rotations were greater than 4.0% and 10.0% in absolute mean and in standard deviation, respectively, at the skull and adjacent regions for all cases. They were less than 1.0% and 2.5% in absolute mean and in standard deviation, respectively, for dose points 3 mm away from the skull. The results indicated that spatial dose to any part of the brainorgans or tumors separated from the skull or head surface would be relatively stable before and after rotations. Statistical data of CTVs and OARs indicate the lens and cochleas have the large dose variations before and after rotations, whereas the remaining ROIs have insignificant dose differences. DVH comparisons suggest that the ODMORC method is able to estimate the DVH of CTVs fairly accurately (within 1.5% of relative dose differences for evaluation volumes). The results also show that most of the OARs including the brain stem, spinal cord, chiasm, hippocampuses, optic nerves, and retinas, which were relatively distal from the skull and surface, had good agreement (within 2.0% of relative dose differences for 0.1 cc of the volumes ) between the ODMORC method and the recomputation, whereas OARs more proximate to the bone-tissue interface or surface, such as the lenses and cochlea, had larger dose variations (greater than 5.0%) for some cases due to the incapability of the ODMORC to account for scatter contribution variations proximate to interfaces and intrinsic dose calculation uncertainties for ROIs with small volumes. Conclusions: The ODMORC method can be implemented as an online evaluation system for rotation-induced dose changes of CTVs and most OARs and for other related dose consequence analyses.

The purpose of this study was to investigate the feasibility of using a single QA device for comprehensive, efficient daily QA of a linear accelerator (Linac) and three image‐guided stereotactic positioning systems (IGSPSs). The Sun Nuclear Daily QA 3 (DQA3) device was used to perform daily dosimetry and mechanical accuracy tests for an Elekta Linac, as well as daily image geometric and isocenter coincidence accuracy tests for three IGSPSs: the AlignRT surface imaging system; the frameless SonArray optical tracking System (FSA) and the Elekta kV CBCT. The DQA3 can also be used for couch positioning, repositioning, and rotational tests during the monthly QA. Based on phantom imaging, the Linac coordinate system determined using AlignRT was within 0.7 mm/0.6° of that of the CBCT system. The difference is attributable to the different calibration methods that are utilized for these two systems. The laser alignment was within 0.5 mm of the isocenter location determined with the three IGSPSs. The ODI constancy was ± 0.5 mm. For gantry and table angles of 0°, the mean isocenter displacement vectors determined using the three systems were within 0.7 mm and 0.6° of one another. Isocenter rotational offsets measured with the systems were all ≤ 0.5°. For photon and electron beams tested over a period of eight months, the output was verified to remain within 2%, energy variations were within 2%, and the symmetry and flatness were within 1%. The field size and light‐radiation coincidence were within 1mm ± 1 mm. For dosimetry reproducibility, the standard deviation was within 0.2% for all tests and all energies, except for photon energy variation which was 0.6%. The total measurement time for all tasks took less than 15 minutes per QA session compared to 40 minutes with our previous procedure, which utilized an individual QA device for each IGSPS. The DQA3 can be used for accurate and efficient Linac and IGSPS daily QA. It shortens QA device setup time, eliminates errors introduced by changing phantoms to perform different tests, and streamlines the task of performing dosimetric checks. PACS number: 87.56.Fc

The purpose was to determine dose‐delivery errors resulting from systematic rotational setup errors for fractionated stereotactic radiotherapy using direct simulation in a treatment planning system. Ten patients with brain tumors who received intensity‐modulated radiotherapy had dose distributions re‐evaluated to assess the impact of systematic rotational setup errors. The dosimetric effect of rotational setup errors was simulated by rotating images and contours using a 3 by 3 rotational matrix. Combined rotational errors of ± 1°,± 3°,± 5° and ± 7° and residual translation errors of 1 mm along each axis were simulated. Dosimetric effects of the rotated images were evaluated by recomputing dose distributions and compared with the original plan. The mean volume of CTV that received the prescription dose decreased from 99.3%± 0.5% (original) to 98.6%± 1.6% (± 1°), 97.0%± 2.0% (± 3°), 93.1%± 4.6% (± 5°), and 87.8%± 14.2% (± 7°). Minimal changes in the cold and hot spots were seen in the CTV. In general, the increase in the volumes of the organs at risk (OARs) receiving the tolerance doses was small and did not exceed the tolerance, except for cases where the OARs were in close proximity to the PTV. For intracranial tumors treated with IMRT with a CTV‐to‐PTV margin of 3 mm, rotational setup errors of 3° or less didn't decrease the CTV coverage to less than 95% in most cases. However, for large targets with irregular or elliptical shapes, the target coverage decreased significantly as rotational errors of 5° or more were present. Our results indicate that setup margins are warranted even in the absence of translational setup errors to account for rotational setup errors. Rotational setup errors should be evaluated carefully for clinical cases involving large tumor sizes and for targets with elliptical or irregular shape, as well as when isocenter is away from the center of the PTV or OARs are in close proximity to the target volumes. PACS number: 87.53.Bn

Purpose Cone-beam computed tomography (CBCT) is a new image-guided radiation therapy (IGRT) technique for patient alignment in radiotherapy. The CBCT x-ray volume imaging system from Elekta allows for a variety of alignment methods. The aim of this study is to assess the accuracy of soft-tissue-based automatic alignment as compared with manual alignment using intraprostatic fiducials. Methods and materials All patients were treated on an Elekta Synergy S linear accelerator with kilovoltage CBCT. All alignments were performed using the x-ray volume imaging system and associated software. Automatic alignment with gray-value-based registration and manual alignment to fiducial markers were performed. Transitional corrections along each axis as well as 3-dimensional vectors were compared with evaluate the accuracy of gray-value-based registration compared with fiducials. Results The distribution of the 3-dimensional vectors between gray-value and fiducial registrations demonstrated notable differences. The mean summed vector was 0.75 cm, with a standard deviation (SD) of 0.52 cm and range from 0.04 to 2.06 cm. There was minimal difference along the lateral direction, with a mean ± SD of -0.02 cm ± 0.13 cm. However, there were large discrepancies along the superior-inferior and anterior-posterior direction alignments, with mean ± SD values of -0.55 ± 0.48 cm and -0.31 ± 0.43 cm, respectively. Conclusions CBCT with soft-tissue-based automatic corrections is not an accurate alignment compared with manual alignment to fiducial markers for prostate IGRT. We have concluded that a daily manual alignment to fiducials is one of the most reliable methods to maintain accuracy in prostate IGRT.

Purpose To determine if whole-neck intensity-modulated radiotherapy (IMRT) spares the larynx as well as techniques that match a conventional anterior-neck field to an IMRT plan superior to the larynx. Methods and Materials This is a dosimetric study using the treatment planning image sets from 5 consecutively treated patients with node-positive squamous cell carcinoma of the oropharynx, all with gross disease above the larynx. We compared 3 techniques for irradiating the mid- and low-neck lymphatics: whole-neck IMRT, conventional anterior-neck field with split-beam matching, and conventional anterior-neck field with gradient matching. Prescription doses for the high-, intermediate-, and standard-risk planning target volumes were 70 Gy, 60 Gy, and 50 Gy, respectively. Results The mean larynx dose was similar with all techniques with median values: whole-neck IMRT, 28 Gy (range, 17-30 Gy); conventional field with split-beam matching, 26 Gy (range, 21-33 Gy); conventional field with gradient matching, 30 Gy (range, 25-31 Gy). Conclusions With meticulous attention to the details of contouring and treatment planning, it is possible to use whole-neck IMRT without increasing the risk of larynx dysfunction compared to techniques that block the larynx in a conventional anterior-neck field. We discuss the potential advantages of each technique in this article.

Purpose: The aim of this work was to characterize a multi-axis ion chamber array (IC PROFILER; Sun Nuclear Corporation, Melbourne, FL USA) that has the potential to simplify the acquisition of LINAC beam data. Methods: The IC PROFILER (or panel) measurement response was characterized with respect to radiation beam properties, including dose, dose per pulse, pulse rate frequency (PRF), and energy. Panel properties were also studied, including detector-calibration stability, power-on time, backscatter dependence, and the panel's agreement with water tank measurements [profiles, fractional depth dose (FDD), and output factors]. Results: The panel's relative deviation was typically within ({+-}) 1% of an independent (or nominal) response for all properties that were tested. Notable results were (a) a detectable relative field shape change of {approx}1% with linear accelerator PRF changes; (b) a large range in backscatter thickness had a minimal effect on the measured dose distribution (typically less than 1%); (c) the error spread in profile comparison between the panel and scanning water tank (Blue Phantom, CC13; IBA Schwarzenbruck, DE) was approximately ({+-}) 0.75%. Conclusions: The ability of the panel to accurately reproduce water tank profiles, FDDs, and output factors is an indication of its abilities as a dosimetry system. The benefitsmore » of using the panel versus a scanning water tank are less setup time and less error susceptibility. The same measurements (including device setup and breakdown) for both systems took 180 min with the water tank versus 30 min with the panel. The time-savings increase as the measurement load is increased.« less

Purpose: The AlignRT 3 C system is an image-guided stereotactic positioning system (IGSPS) that provides real-time target localization. This study involves the first use of this system with three camera pods. The authors have evaluated its localization accuracy and tracking ability using a cone-beam computed tomography(CBCT) system and an optical tracking system in a clinical setting. Methods: A modified Rando head-and-neck phantom and five patients receiving intracranial stereotactic radiotherapy (SRT) were used to evaluate the calibration, registration, and position-tracking accuracies of the AlignRT 3 C system and to study surface reconstruction uncertainties, including the effects due to interfractional and intrafractional motion, skin tone, room light level, camera temperature, and image registration region of interest selection. System accuracy was validated through comparison with the Elekta kV CBCT system (XVI) and the Varian frameless SonArray (FSA) optical tracking system. Surface-image data sets were acquired with the AlignRT 3 C daily for the evaluation of pretreatment and interfractional and intrafractional motion for each patient. Results for two different reference image sets, planning CT surface contours (CT_S) and previously recorded AlignRT 3 C optical surface images (ART_S), are reported. Results: The system origin displacements for the AlignRT 3 C and XVI systems agreed to within 1.3 mm and 0.7°. Similar results were seen for AlignRT 3 C vs FSA. For the phantom displacements having couch angles of 0°, those that utilized ART_S references resulted in a mean difference of 0.9 mm/0.4° with respect to XVI and 0.3 mm/0.2° with respect to FSA. For phantom displacements of more than ±10 mm and ±3°, the maximum discrepancies between AlignRT and the XVI and FSA systems were 3.0 and 0.4 mm, respectively. For couch angles up to ±90°, the mean (max.) difference between the AlignRT 3 C and FSA was 1.2 (2.3) mm/0.7° (1.2°). For all tests, the mean registration errors obtained using the CT_S references were approximately 1.3 mm/1.0° larger than those obtained using the ART_S references. For the patient study, the mean differences in the pretreatment displacements were 0.3 mm/0.2° between the AlignRT 3 C and XVI systems and 1.3 mm/1° between the FSA and XVI systems. For noncoplanar treatments, interfractional motion displacements obtained using the ART_S and CT_S references resulted in 90th percentile differences within 2.1 mm/0.8° and 3.3 mm/0.3°, respectively, compared to the FSA system. Intrafractional displacements that were tracked for a maximum of 14 min were within 1 mm/1° of those obtained with the FSA system. Uncertainties introduced by the bite-tray were as high as 3 mm/2° for one patient. The combination of gantry, aSi detector panel, and x-ray tube blockage effects during the CBCT acquisition resulted in a registration error of approximately 3 mm. No skin-tone or surface deformation effects were seen with the limited patient sample. Conclusions: AlignRT 3 C can be used as a nonionizing IGSPS with accuracy comparable to current image/marker-based systems. IGSPS and CBCT can be combined for high-precision positioning without the need for patient-attached localization devices.

Purpose: The aim of this work was to simulate the effect of dose distribution changes on detector array calibrations and to explore compensatory methods that are used during calibration measurements. Methods: The array calibration technique that was investigated is known as wide field (WF) calibration. Using this method, a linear array [y-axis (65 detectors) of the IC PROFILER (Sun Nuclear Corporation, Melbourne, FL)] is calibrated with three measurements ({alpha}, {theta}, and {lambda}); each measurement uses the same radiation field, which is larger than the array. For measurement configuration {theta}, the array is rotated by 180 deg. from its position in {alpha}; for {lambda}, the array is shifted by one detector from its position in {theta}. The relative detector sensitivities are then determined through ratios of detector readings at the same field locations (using {theta} and {lambda}). This method results in error propagation that is proportional to the number of detectors in the array. During the procedure, the calibration protocol operates under three postulates, which state that (a) the beam shape does not change between measurements; (b) the relative sensitivities of the detectors do not change; and (c) the scatter to the array does not change as the array is moved.more » The WF calibration's sensitivity to a postulate (a) violation was quantified by applying a sine shaped perturbation (of up to 0.1%) to {alpha}, {theta}, or {lambda}, and then determining the change relative to a baseline calibration. Postulate (a) violations were minimized by using a continuous beam and mechanized array movement during {theta} and {lambda}. A continuously on beam demonstrated more stable beam symmetry as compared to cycling the beam on and off between measurements. Additional side-scatter was also used to satisfy postulate (c). Results: Simulated symmetry perturbations of 0.1% to {theta} or {lambda} resulted in calibration errors of up to 2%; {alpha} was relatively immune to perturbation (

Purpose: Accurate modeling of beam profiles is important for precise treatment planning dosimetry. Calculated beam profiles need to precisely replicate profiles measured during machine commissioning. Finite detector size introduces perturbations into the measured profiles, which, in turn, impact the resulting modeled profiles. The authors investigate a method for extracting the unperturbed beam profiles from those measured during linear accelerator commissioning. Methods: In-plane and cross-plane data were collected for an Elekta Synergy linac at 6 MV using ionization chambers of volume 0.01, 0.04, 0.13, and 0.65 cm{sup 3} and a diode of surface area 0.64 mm{sup 2}. The detectors were orientated with the stem perpendicular to the beam and pointing away from the gantry. Profiles were measured for a 10x10 cm{sup 2} field at depths ranging from 0.8 to 25.0 cm and SSDs from 90 to 110 cm. Shaping parameters of a Gaussian response function were obtained relative to the Edge detector. The Gaussian function was deconvolved from the measured ionization chamber data. The Edge detector profile was taken as an approximation to the true profile, to which deconvolved data were compared. Data were also collected with CC13 and Edge detectors for additional fields and energies on an Elekta Synergy, Varianmore » Trilogy, and Siemens Oncor linear accelerator and response functions obtained. Response functions were compared as a function of depth, SSD, and detector scan direction. Variations in the shaping parameter were introduced and the effect on the resulting deconvolution profiles assessed. Results: Up to 10% setup dependence in the Gaussian shaping parameter occurred, for each detector for a particular plane. This translated to less than a {+-}0.7 mm variation in the 80%-20% penumbral width. For large volume ionization chambers such as the FC65 Farmer type, where the cavity length to diameter ratio is far from 1, the scan direction produced up to a 40% difference in the shaping parameter between in-plane and cross-plane measurements. This is primarily due to the directional difference in penumbral width measured by the FC65 chamber, which can more than double in profiles obtained with the detector stem parallel compared to perpendicular to the scan direction. For the more symmetric CC13 chamber the variation was only 3% between in-plane and cross-plane measurements. Conclusions: The authors have shown that the detector response varies with detector type, depth, SSD, and detector scan direction. In-plane vs cross-plane scanning can require calculation of a direction dependent response function. The effect of a 10% overall variation in the response function, for an ionization chamber, translates to a small deviation in the penumbra from that of the Edge detector measured profile when deconvolved. Due to the uncertainties introduced by deconvolution the Edge detector would be preferable in obtaining an approximation of the true profile, particularly for field sizes where the energy dependence of the diode can be neglected. However, an averaged response function could be utilized to provide a good approximation of the true profile for large ionization chambers and for larger fields for which diode detectors are not recommended.« less

Purpose: The aim of this work is to develop effective calibration methods for a novel four-dimensional (4D) diode array for pretreatment verification of intensity-modulated radiation therapy (IMRT) and rotational therapy. Methods: A novel 4D diode array (ArcCHECK, Sun Nuclear, Melbourne, FL) was developed to meet the needs of appropriate and efficient quality assurance for IMRT and especially rotational radiotherapy. The diode array presents a consistent detector image in beam's eye view at arbitrary gantry angles due to isotropic arrangement of diodes in a three-dimensional (3D) cylindrical phantom. The 50 ms simultaneous update of all diodes on the detector array (fourth dimension) makes it capable of time-resolved beam delivery analysis with any rotational delivery techniques. The calibration procedure consisted of delivering and measuring a series of calibration beams with 5.8 deg. angular spacing surrounding the cylindrical diode array. Correction factors for diode intrinsic sensitivity and directional response dependence were derived from these measurements. A real-time algorithm to derive gantry angles based on the detector signal was developed to interpolate and apply the corresponding angular correction factors. Results: The calibration was validated with ion chamber scanned beam profiles in a 3D water tank. Excellent agreement was observed between diode array measurement andmore » treatment planning system calculation. The accuracy of the gantry angle derivation algorithm was within 1 deg. which caused a less than 0.2% dosimetric uncertainty. Conclusions: With the proposed calibration method and the automatic gantry angle derivation algorithm, the 4D diode array achieved isotropic detector response and is suitable for both IMRT and rotational therapy pretreatment verification.« less

Purpose: The authors have developed a quantitative calibration method for a multileaf collimator (MLC) which measures individual leaf positions relative to the MLC backup jaw on an Elekta Synergy linear accelerator. Methods: The method utilizes a commercially available two-axis detector array (Profiler 2; Sun Nuclear Corporation, Melbourne, FL). To calibrate the MLC bank, its backup jaw is positioned at the central axis and the opposing jaw is retracted to create a half-beam configuration. The position of the backup jaws field edge is then measured with the array to obtain what is termed the radiation defined reference line. The positions of the individual leaf ends relative to this reference line are then inferred by the detector response in the leaf end penumbra. Iteratively adjusting and remeasuring the leaf end positions to within specifications completes the calibration. Using the backup jaw as a reference for the leaf end positions is based on three assumptions: (1) The leading edge of an MLC leaf bank is parallel to its backup jaw's leading edge, (2) the backup jaw position is reproducible, and (3) the measured radiation field edge created by each leaf end is representative of that leaf's position. Data from an electronic portal imagingmore » device (EPID) were used in a similar analysis to check the results obtained with the array. Results: The relative leaf end positions measured with the array differed from those measured with the EPID by an average of 0.11 {+-}0.09 mm per leaf. The maximum leaf positional change measured with the Profiler 2 over a 3 month period was 0.51 mm. A leaf positional accuracy of {+-}0.4 mm is easily attainable through the iterative calibration process. The method requires an average of 40 min to measure both leaf banks. Conclusions: This work demonstrates that the Profiler 2 is an effective tool for efficient and quantitative MLC quality assurance and calibration.« less

The task group (TG) for quality assurance of medical accelerators was constituted by the American Association of Physicists in Medicine's Science Council under the direction of the Radiation Therapy Committee and the Quality Assurance and Outcome Improvement Subcommittee. The task group (TG-142) had two main charges. First to update, as needed, recommendations of Table II of the AAPM TG-40 report on quality assurance and second, to add recommendations for asymmetric jaws, multileaf collimation (MLC), and dynamic/virtual wedges. The TG accomplished the update to TG-40, specifying new test and tolerances, and has added recommendations for not only the new ancillary delivery technologies but also for imaging devices that are part of the linear accelerator. The imaging devices include x-ray imaging, photon portal imaging, and cone-beam CT. The TG report was designed to account for the types of treatments delivered with the particular machine. For example, machines that are used for radiosurgery treatments or intensity-modulated radiotherapy (IMRT) require different tests and/or tolerances. There are specific recommendations for MLC quality assurance for machines performing IMRT. The report also gives recommendations as to action levels for the physicists to implement particular actions, whether they are inspection, scheduled action, or immediate and corrective action. The report is geared to be flexible for the physicist to customize the QA program depending on clinical utility. There are specific tables according to daily, monthly, and annual reviews, along with unique tables for wedge systems, MLC, and imaging checks. The report also gives specific recommendations regarding setup of a QA program by the physicist in regards to building a QA team, establishing procedures, training of personnel, documentation, and end-to-end system checks. The tabulated items of this report have been considerably expanded as compared with the original TG-40 report and the recommended tolerances accommodate differences in the intended use of the machine functionality (non-IMRT, IMRT, and stereotactic delivery).

Purpose: The a im of this study was to investigate the relative accuracy of megavoltage photon-beam dose calculations employing either 5 bulk densities or independent voxel densities determined by calibration of the CT Houndsfield number. Materials/Methods: Full -resolution CT and bulk density treatment plans were generated for 70 lung or esophageal cancer tumors (66 cases) using a commercial treatment planning system with an adaptive convolution dose calculation algorithm (Pinnacle3, Philips Medicals Systems). Bulk densities were applied to segmented regions. Individual and population average densities were compared to the full-resolution plan for each case. Monitor units were kept constant and no normalizations were employed. Dose volume histograms (DVH) and dose difference distributions were examined for all cases. Results: The average densities of the segmented air, lung, fat, soft tissue, and bone for the entire set were found to be 0.1 4 , 0. 26 , 0. 89, 1.02, and 1.1 2 g/cc, respectively. In all cases, the normal tissue DVH agreed to better than 2 % in dose. In 62 of 70 target DVHs, agreement to better than 3 % in dose was observed . Six cases demonstrated emphysema, one with bullous formations and one with a hiatus hernia having a large volume of gas. They required the additional assignment of density to the emphysemic lung and inflammatory changes to the lung, the regions of collapsed lung, the bullous formations, and the hernia gas. Conclusions : Bulk tissue density dose calculation provides an accurate method of heterogeneous dose calculation. However, patients with advanced emphysema may require high-resolution CT studies for accurate treatment planning.

Two commercially available detector arrays were compared for their use in the quality assurance of patient‐specific IMRT treatment plans: one a diode‐based array (MapCHECK) and the other an ion chamber‐based array (MatriXX). The dependence of the response of detectors on field size, dose rate, and radiation energy was measured and compared with reference measurements using a Farmer‐type ionization chamber. The linearity of the detector response, short‐term and long‐term reproducibility, statistical uncertainty as a function of delivered dose, and the validity of the array calibration were also examined to understand the stability and uncertainty of the systems. No field size or SSD dependence was observed within the range of the field sizes and SSDs used in the study at both 6 MV and 18 MV photon energies. Both detector arrays showed negligible errors (

Accurate multileaf collimator (MLC) leaf positioning plays an essential role in the effective implementation of intensity modulated radiation therapy (IMRT). This work evaluates the sensitivity of current patient‐specific IMRT quality assurance (QA) procedures to minor MLC leaf positioning errors. Random errors of up to 2 mm and systematic errors of ±1mm and ±2mm in MLC leaf positions were introduced into 8 clinical IMRT patient plans (totaling 53 fields). Planar dose distributions calculated with modified plans were compared to dose distributions measured with both radiochromic films and a diode matrix. The agreement between calculation and measurement was evaluated using both absolute distance‐to‐agreement (DTA) analysis and γ index with 2%/2mm and 3%/3mm criteria. It was found that both the radiochromic film and the diode matrix could only detect systematic errors on the order of 2 mm or above. The diode array had larger sensitivity than film due to its excellent detector response (such as small variation, linear response, etc.). No difference was found between DTA analysis and γ index in terms of the sensitivity to MLC positioning errors. Higher sensitivity was observed with 2%/2mm than with 3%/3mm in general. When using the diode array and 2%/2mm criterion, the IMRT QA procedure showed strongest sensitivity to MLC position errors and, at the same time, achieved clinically acceptable passing rates. More accurate dose calculation and measurement would further enhance the sensitivity of patient‐specific IMRT QA to MLC positioning errors. However, considering the significant dosimetric effect such MLC errors could cause, patient‐specific IMRT QA should be combined with a periodic MLC QA program in order to guarantee the accuracy of IMRT delivery. PACS numbers: 87.50.Gi, 87.52.Df, 87.52.Px, 87.53.Dq, 87.53.Tf, 87.53.Kn, 87.56.Fc

The aim of this work is to investigate the clinical impact of detector size effect on patient specific intensity-modulated radiation therapy (IMRT) quality assurance (QA). Two photon beam models, BM6 and BM4, were commissioned using photon beam profiles measured with a 6 mm diameter and a 4 mm diameter ion chambers, respectively. A method was developed to extract the "true" cross beam profiles, free of volume averaging effect, using analytic fitting/deconvolution. The method was validated using beam profiles measured with a small (0.8 mm) diode detector for small (< or = 10 x 10 cm2) field sizes. These profiles were used to commission a third beam model (BM08). Planar dose distributions for eight IMRT plans (total of 53 fields) were calculated using the three beam models and measured with a two-dimensional detector array. Analysis using percent dose difference and distance-to-agreement criteria between the calculation and measurement was done to benchmark the performance of each beam model. The average passing rates between calculation and measurement were 93.8%, 98.9%, and 99.4% for BM6, BM4, and BM08, respectively, when 3%/3 mm criteria were used. A gradual increase in passing rates was noticed with the decrease in the size of the detector used to collect commissioning data. When 2%/2 mm criteria were used, the average passing rates increased significantly from 81.6% (BM6) to 92.6% (BM4) and 96.8% (BM08). These results quantify the enhancement of IMRT dose calculation accuracy with the reduction in detector size used for photon beam profiles measurement. Our study indicates that volume averaging effect can significantly affect the results of IMRT patient specific QA. By removing the detector size effect in beam commissioning, excellent passing rates can be achieved with more stringent criteria such as 2%/2 mm. The use of more stringent criteria for IMRT patient specific QA would likely result in higher chances of detecting any dosimetric errors arising from the treatment planning or delivery system.