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This study reports the microstructure and surface properties of P20 steel processed by laser surface engineering (involving surface hardening and melting), which are carried out using a fiber laser with the maximum power of 2 kW. Ultrafine martensite laths with high boundary density are formed both in the laser surface hardened layer and in the melted layer. This dramatically improves the surface hardness of the P20 steel. However, the laser surface melted layer exhibits a relatively lower hardness than the laser surface hardened layer. It can be attributed to the remarkable autotempering effect and the vaporization of alloy elements in the melted layer. The wear resistance and thermal cracking resistance of the samples treated by laser surface engineering show a significant improvement compared with the as received material. The surface hardened layer exhibits superior wear and thermal cracking resistance due to its relatively high surface hardness and plastic deformation resistance, which can effectively suppress the formation of cracks during wear and thermal cracking tests.

The influence of the initial structure on formation of austenite, evolution of structure, and elevation of operating characteristics of steel SA508 Gr.3 (0.24% C, 1.40% Mn, 0.88% Ni, 0.54% Mo) after an intercritical heat treatment (IHT) is studied. After the IHT, the grain size of the hypoeutectoid ferrite in the steel with an initially ferritic-bainitic structure is much larger than in the initially bainitic or martensitic structures. The density of the low-angle and high-angle boundaries is much higher in the steel with initial bainitic or martensitic microstructure. The initial microstructure affects substantially the strength and the impact toughness of the steel subjected to IHT. The mechanical properties are increased as a result of refinement of the microstructure and growth of the density of grain boundaries.

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.

Based on the population change data of 2005-2009, 2010-2014, 2015-2019 and 2005-2019, the shrinking cities in Northeast China are determined to analyze their spatial distribution pattern. And the influencing factors and effects of Shrinking Cities in Northeast China are explored by using multiple linear regression method and random forest regression method. The results show that: 1) In space, the shrinking cities in Northeast China are mainly distributed in the “land edge” areas represented by Changbai Mountain, Sanjiang Plain, Xiaoxing’an Mountain and Daxing’an Mountain. In terms of time, the contraction center shows an obvious trend of moving northward, while the opposite expansion center shows a trend of moving southward, and the Shrinking Cities gather further; 2) in the study of influencing factors, the results of multiple linear regression and random forest regression show that socio-economic factors play a major role in the formation of shrinking cities; 3) the precision of random forest regression is higher than that of multiple linear regression. The results show that per capita GDP has the greatest impact on the contraction intensity, followed by the unemployment rate, science and education expenses and the average wage of on-the-job workers. Among the four influencing factors, only the unemployment rate promotes the contraction, and the other three influencing factors inhibit the formation of shrinking cities to various degrees.

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.

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.

Changes in agricultural land productivity have become a crucial criterion for assessing the effectiveness of land consolidation (LC). In this study, agricultural land productivity under LC was observed and monitored in terms of two important factors: vegetation productivity and soil productivity, which were represented by net primary productivity (NPP) and soil organic matter (SOM), respectively. Based on spatial and temporal variations before and after the implementation of LC, the response of vegetation and soil productivity to LC was further discussed. The main results are as follows: (1) The effectiveness of LC could be quantitatively confirmed in terms of both vegetation and soil productivity. Compared with vegetation productivity, soil productivity had stronger and more positive response to LC. (2) The effectiveness of LC was characterized by temporal attenuation, which specifically showed that the improvement of vegetation and soil productivity followed a trajectory of "increase–stability" after the implementation of LC. (3) The effectiveness of LC was seasonal, coinciding with the farming period. In other words, the effectiveness of LC became completely prominent with the implementation of agricultural activities. This phenomenon was particularly more pronounced from the aspect of soil productivity.

In-situ Ti(C, N) reinforced AlCoCrFeNiSi-based high entropy alloy coating with functional gradient double-layer structure is successfully fabricated on the H13 substrate using laser cladding. The microstructures and wear resistance of the gradient coating are characterized using SEM, EBSD, TEM, EDS and wear test, respectively. The results show that FCC solid-solution matrix is formed in first layer, while a mixture of disordered BCC phase (Fe-Cr) and ordered B2 phase (Al-Ni-Ti) with coherent interface is found as the matrix in second layer. Ti(C, N) ceramic particles are in-situ synthesized in the coating due to the large negative mixing enthalpy of Ti-C and Ti-N atom pairs. The solid-solution strengthening and dislocation strengthening caused by the dissolution of Ti into B2 phase, accompanying with the fine grain strengthening caused by the microstructure refinement and dispersion strengthening of Ti(C, N) particles, contribute to the high surface hardness and wear resistance. The dominant wear mechanism of this coating is oxidation wear with a small amount of abrasive wear. It can be concluded that AlCoCrFeNiSi-based high entropy alloy coating with in-situ Ti(C, N) reinforcement dramatically improves the wear resistance of the H13 substrate.

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.

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.

Macrosegregation refers to the chemical segregation, which occurs quite commonly in the large forgings such as nuclear reactor pressure vessel. This work assesses the effect of macrosegregation and homogenization treatment on the mechanical properties of a pressure-vessel steel (SA508 Gr.3). It was found that the primary reason for the inhomogeneity of the microstructure was the segregation of Mn, Mo, and Ni. Martensite, and coarse upper bainite with M-A (martensite-austenite) islands have been obtained, respectively, in the positive and negative segregation zone during a simulated quenching process. During tempering, the carbon-rich M-A islands decomposed into a mixture of ferrite and numerous carbides which deteriorated the toughness of the material. The segregation has been substantially minimized by a homogenizing treatment. The results indicate that the material homogenized has a higher impact toughness than the material with segregation, due to the reduction in M-A island in the negative segregation zone. It can be concluded that the microstructure and mechanical properties have been improved remarkably by means of homogenization treatment.

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 (

Retained austenite( RA ) usually presents in the quenched Nuclear Pressure-Vessel SA508 Gr.3 steel. In the present work, the characteristic of RA decomposition and its effect on the impact toughness were investigated by microstructure observation, dilatometric experiments and Charpy impact tests. The results show that the RA transformed into martensite and bainite during tempering at 230 °C and 400 °C respectively, while mixture of long rod carbides and ferrite formed at 650 °C. The long rod carbides formed from RA decomposition decrease the critical cleavage stress for initiation of micro-cracks, and deteriorate the impact toughness of the steel. Pre-tempering at a low temperature such as 230 °C or 400 °C leading to the decomposition of RA into martensite or baintie can eliminate the deterioration of the toughness caused by direct decomposition into long rod carbides. The absorbed energy indicate that pre-tempering at 400 °C can drive dramatically improvement in the toughness of the steel.

In recent years, sensors in the Internet of things have been commonly used in Human&rsquo, s life. APT (Advanced Persistent Threats) has caused serious damage to network security and the sensors play an important role in the attack process. For a long time, attackers infiltrate, attack, conceal, spread, and steal information of target groups through the compound use of various attacking means, while existing security measures based on single-time nodes cannot defend against such attacks. Attackers often exploit the sensors&rsquo, vulnerabilities to attack targets because the security level of the sensors is relatively low when compared with that of the host. We can find APT attacks by checking the suspicious domains generated at different APT attack stages, since every APT attack has to use DNS to communicate. Although this method works, two challenges still exist: (1) the detection method needs to check a large scale of log data, (2) the small number of attacking samples limits conventional supervised learning. This paper proposes an APT detection framework AULD (Advanced Persistent Threats Unsupervised Learning Detection) to detect suspicious domains in APT attacks by using unsupervised learning. We extract ten important features from the host, domain name, and time from a large number of DNS log data. Later, we get the suspicious cluster by performing unsupervised learning. We put all of the domains in the cluster into the list of malicious domains. We collected 1,584,225,274 DNS records from our university network. The experiments show that AULD detected all of the attacking samples and that AULD can effectively detect the suspicious domain names in APT attacks.

The microstructural evolution of reactor pressure vessel (RPV) steel and its effect on the mechanical properties during tempering at 650 °C were studied to reveal the time-dependent toughness and temper embrittlement. The results show that the toughening of the material should be attributed to the decomposition of the martensite/austenite constituents and uniform distribution of carbides. When the tempering duration was 5 h, the strength of the investigated steel decreased to strike a balance with the material impact toughness that reached a plateau. As the tempering duration was further increased, the material strength was slightly reduced but the material impact toughness deteriorated drastically. This time-dependent temper embrittlement is different from traditional temper embrittlement, and it can be partly attributed to the softening of the matrix and the broadening of the ferrite laths. Moreover, the dimensions and distribution of the grain carbides are the most important factors of the impact toughness.

Purpose: To investigate the use of local noise power spectrum (NPS) to characterize image noise and wavelet analysis to isolate defective pixels and inter-subpanel flat-fielding artifacts for quantitative quality assurance (QA) of electronic portal imaging devices (EPIDs). Methods: A total of 93 image sets including custom-made bar-pattern images and open exposure images were collected from four iViewGT a-Si EPID systems over three years. Global quantitative metrics such as modulation transform function (MTF), NPS, and detective quantum efficiency (DQE) were computed for each image set. Local NPS was also calculated for individual subpanels by sampling region of interests within each subpanel of the EPID. The 1D NPS, obtained by radially averaging the 2D NPS, was fitted to a power-law function. The r-square value of the linear regression analysis was used as a singular metric to characterize the noise properties of individual subpanels of the EPID. The sensitivity of the local NPS was first compared with the global quantitative metrics using historical image sets. It was then compared with two commonly used commercial QA systems with images collected after applying two different EPID calibration methods (single-level gain and multilevel gain). To detect isolated defective pixels and inter-subpanel flat-fielding artifacts, Haar wavelet transform was applied on the images. Results: Global quantitative metrics including MTF, NPS, and DQE showed little change over the period of data collection. On the contrary, a strong correlation between the local NPS (r-square values) and the variation of the EPID noise condition was observed. The local NPS analysis indicated image quality improvement with the r-square values increased from 0.80 ± 0.03 (before calibration) to 0.85 ± 0.03 (after single-level gain calibration) and to 0.96 ± 0.03 (after multilevel gain calibration), while the commercial QA systems failed to distinguish the image quality improvement between the two calibration methods. With wavelet analysis, defective pixels and inter-subpanel flat-fielding artifacts were clearly identified as spikes after thresholding the inversely transformed images. Conclusions: The proposed local NPS (r-square values) showed superior sensitivity to the noise level variations of individual subpanels compared with global quantitative metrics such as MTF, NPS, and DQE. Wavelet analysis was effective in detecting isolated defective pixels and inter-subpanel flat-fielding artifacts. The proposed methods are promising for the early detection of imaging artifacts of EPIDs.

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% (

Gas nitriding and laser surface engineering are popular technologies to improve the surface performance of steels. This study evaluates the effect of duplex treatment of gas nitriding and laser surface engineering on surface hardness, wear and corrosion resistance of P20 plastic mold steel. It is found that gas nitriding at 550 °C for 20 h with nitrogen potential of 0.18 generates a nitrided layer without nitrides, which drastically improves the wear resistance. Simultaneously, the corrosion resistance is also marginal improved by the gas nitriding. Laser surface hardening further elevates the surface hardness and wear resistance of the nitrided layer due to the formation of martensite. Besides, a small amount of austenite retains in surface layer after laser surface hardening, which may lead to the galvanic attack at the phase interface between martensite and retained austenite and deteriorate the surface corrosion resistance. Laser surface melting results in the denitrification of nitrided layer and the formation of holes at the bottom of melted layer, thus reducing the surface hardness and wear resistance. Meanwhile, the denitrified surface layer also exhibits a degraded corrosion resistance owe to the decreasing nitrogen content and the formation of mixed structure of martensite and retained austenite.

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.

Four‐dimensional, cone‐beam CT (4D CBCT) substantially reduces respiration‐induced motion blurring artifacts in three‐dimension (3D) CBCT. However, the image quality of 4D CBCT is significantly degraded which may affect its accuracy in localizing a mobile tumor for high‐precision, image‐guided radiation therapy (IGRT). The purpose of this study was to investigate the impact of scanning parameters (hereinafter collectively referred to as scanning sequence) and breathing patterns on the image quality and the accuracy of computed tumor trajectory for a commercial 4D CBCT system, in preparation for its clinical implementation. We simulated a series of periodic and aperiodic sinusoidal breathing patterns with a respiratory motion phantom. The aperiodic pattern was created by varying the period or amplitude of individual sinusoidal breathing cycles. 4D CBCT scans of the phantom were acquired with a manufacturer‐supplied scanning sequence (4D‐S‐slow) and two in‐house modified scanning sequences (4D‐M‐slow and 4D‐M‐fast). While 4D‐S‐slow used small field of view (FOV), partial rotation (200°), and no imaging filter, 4D‐M‐slow and 4D‐M‐fast used medium FOV, full rotation, and the F1 filter. The scanning speed was doubled in 4D‐M‐fast (100°/min gantry rotation). The image quality of the 4D CBCT scans was evaluated using contrast‐to‐noise ratio (CNR), signal‐to‐noise ratio (SNR), and motion blurring ratio (MBR). The trajectory of the moving target was reconstructed by registering each phase of the 4D CBCT with a reference CT. The root‐mean‐squared‐error (RMSE) analysis was used to quantify its accuracy. Significant decrease in CNR and SNR from 3D CBCT to 4D CBCT was observed. The 4D‐S‐slow and 4D‐M‐fast scans had comparable image quality, while the 4D‐M‐slow scans had better performance due to doubled projections. Both CNR and SNR decreased slightly as the breathing period increased, while no dependence on the amplitude was observed. The difference of both CNR and SNR between periodic and aperiodic breathing patterns was insignificant (p>0.48). At end‐exhale phases, the motion blurring was negligible for both periodic and aperiodic breathing patterns; at mid‐inhale phase, the motion blurring increased as the period, the amplitude or the amount of cycle‐to‐cycle variation on amplitude increased. Overall, the accuracy of localizing the moving target in 4D CBCT was within 2 mm under all studied cases. No difference in the RMSEs was noticed among the three scanning sequences. The 4D‐M‐fast scans, free of volume truncation artifacts, exhibited comparable image quality and accuracy in tumor motion reconstruction as the 4D‐S‐slow scans with reduced imaging dose (0.60 cGy vs. 0.99 cGy) due to the use of faster gantry rotation and the F1 filter, suggesting its suitability for clinical use. PACS number: 87.55.Qr

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: 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.

Purpose: To determine the accuracy and reproducibility of the automatic‐ setup procedure of a 3D water scanner (3D SCANNER, Sun Nuclear Corp). The procedure automatically aligns the scanner's coordinate system to the Linac coordinate system. A unique off‐center detector holder extends the scan range to 630 mm, eliminating the need for scanner shifts for large‐field scans. Methods: The automatic‐setup procedure provides means to automatically (1) level the tank; (2) zero the detector position to water surface; (3) align the scanner's coordinate system to the Linac system; and (4) correct motor hysteresis. After automatic‐setup, (1) and (2) were evaluated visually by three physicists. Step (3) was tested by moving one of the jaws to the isocenter and scans were made along the jaw edge. Angular misalignment between the scanner and the Linac would Result in a noticeably tilted profile. Step (4) was tested by scanning with the chamber moving forward and then backward five times. The accuracy of the off‐center detector holder was tested by comparing scans made using the regularand the off‐center detector holders. All tests were repeated three times. Results: All tests of the water surface and horizontal chamber movementwere acceptable from the nine independent evaluations. Scans along the jawedge resulted in < 1% in profile tilt, corresponding to < 0.05 degree in angular misalignment. Same direction scans resulted in field edge differences < 0.05 mm, and < 0.2 mm when compared to scans in thereverse direction. There was no difference in accuracy when different scan speeds were used. Profiles obtained using the regular and the off‐centerdetector holders were identical. Conclusions: The automatic‐setupprocedure resulted in accurate alignment of the 3D SCANNER to the Linac. These results were user‐independent. It also provides the ability to scan large fields without the need to change tank setup. This work was partially supported by a research grant from Sun Nuclear Corp., Melbourne, FL.

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 study the dosimetric characteristics of a commercial three‐dimensional water scanner (3D SCANNER, Sun Nuclear Corp). The novel cylindrical scanner uses a compact electrometer mounted on the side of the tank, eliminating the need for chamber extension cables. The electrometer has a wide dynamic range, requiring no gain adjustment as scanning conditions change, e.g., field size, dose rate, wedge field, etc. Methods: Measurements from the 3D SCANNER were compared against those from another commercial scanner (Blue Phantom, IBA Dosimetry). Comparable collection intervals and scanning speeds were used on both systems. Profile and depth measurements were performed for open field beams (6 and 18 MV; 10‐cm and 30‐cm squared fields; depths of dmax, 10, and 30 cm) and wedged fields (6 and 18 MV; 30‐cm squared field; depth of 10 cm). Electron beam profile and depth measurements were performed for a 20‐cm squared applicator (6, 12, and 20 MeV; depth of dmax). The root mean square (RMS) values were determined for each scanner'smeasurements.Results: The measuredfield sizes were within 0.06 cm and 0.05 cm for photon and electron beams, respectively. The photon D10/D20 ratios differed by < 0.4% and the electron I50 values were within 0.02 cm. The RMS of the profiles was approximately 0.1% for both the 3D SCANNER and Blue Phantom measurements. Between the two scanners, all measurements agreed within RMS, excluding the penumbra region. Two exceptions occurred: a 0.5% difference was observed in the shoulder of the 12 MeV profiles, and a 0.8% difference was observed in the 6 MeV depth measurements near the surface.Conclusions: The quality of the scanned profile and depth measurements from the 3D SCANNER is comparable to that of another commercial scanner. Both scanning systems have similar levels of scanning noise. This work was partially supported by a research grant from Sun Nuclear Corp., Melbourne, FL

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.

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

To investigate the use of local noise power spectrum (NPS) to characterize image noise and wavelet analysis to isolate defective pixels and inter-subpanel flat-fielding artifacts for quantitative quality assurance (QA) of electronic portal imaging devices (EPIDs).A total of 93 image sets including custom-made bar-pattern images and open exposure images were collected from four iViewGT a-Si EPID systems over three years. Global quantitative metrics such as modulation transform function (MTF), NPS, and detective quantum efficiency (DQE) were computed for each image set. Local NPS was also calculated for individual subpanels by sampling region of interests within each subpanel of the EPID. The 1D NPS, obtained by radially averaging the 2D NPS, was fitted to a power-law function. The r-square value of the linear regression analysis was used as a singular metric to characterize the noise properties of individual subpanels of the EPID. The sensitivity of the local NPS was first compared with the global quantitative metrics using historical image sets. It was then compared with two commonly used commercial QA systems with images collected after applying two different EPID calibration methods (single-level gain and multilevel gain). To detect isolated defective pixels and inter-subpanel flat-fielding artifacts, Haar wavelet transform was applied on the images.Global quantitative metrics including MTF, NPS, and DQE showed little change over the period of data collection. On the contrary, a strong correlation between the local NPS (r-square values) and the variation of the EPID noise condition was observed. The local NPS analysis indicated image quality improvement with the r-square values increased from 0.80 ± 0.03 (before calibration) to 0.85 ± 0.03 (after single-level gain calibration) and to 0.96 ± 0.03 (after multilevel gain calibration), while the commercial QA systems failed to distinguish the image quality improvement between the two calibration methods. With wavelet analysis, defective pixels and inter-subpanel flat-fielding artifacts were clearly identified as spikes after thresholding the inversely transformed images.The proposed local NPS (r-square values) showed superior sensitivity to the noise level variations of individual subpanels compared with global quantitative metrics such as MTF, NPS, and DQE. Wavelet analysis was effective in detecting isolated defective pixels and inter-subpanel flat-fielding artifacts. The proposed methods are promising for the early detection of imaging artifacts of EPIDs.

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.

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.