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The aim of this work is to investigate to what extent it is possible to use the secondary collimator jaws to reduce the transmitted radiation through the multileaf collimator (MLC) during an intensity modulated radiation therapy (IMRT). A method is developed and introduced where the jaws follow the open window of the MLC dynamically (dJAW method). With the aid of three academic cases (Closed MLC, Sliding-gap, and Chair) and two clinical cases (prostate and head and neck) the feasibility of the dJAW method and the influence of this method on the applied dose distributions are investigated. For this purpose the treatment planning system Eclipse and the Research-Toolbox were used as well as measurements within a solid water phantom were performed. The transmitted radiation through the closed MLC leads to an inhomogeneous dose distribution. In this case, the measured dose within a plane perpendicular to the central axis differs up to 40% (referring to the maximum dose within this plane) for 6 and 15 MV. The calculated dose with Eclipse is clearly more homogeneous. For the Sliding-gap case this difference is still up to 9%. Among other things, these differences depend on the depth of the measurement within the solid water phantom and on the application method. In the Chair case, the dose in regions where no dose is desired is locally reduced by up to 50% using the dJAW method instead of the conventional method. The dose inside the chair-shaped region decreased up to 4% if the same number of monitor units (MU) as for the conventional method was applied. The undesired dose in the volume body minus the planning target volume in the clinical cases prostate and head and neck decreased up to 1.8% and 1.5%, while the number of the applied MU increased up to 3.1% and 2.8%, respectively. The new dJAW method has the potential to enhance the optimization of the conventional IMRT to a further step.

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The synchronization of dynamic multileaf collimator (DMLC) response with respiratory motion is critical to ensure the accuracy of DMLC-based four dimensional (4D) radiation delivery. In practice, however, a finite time delay (response time) between the acquisition of tumor position and multileaf collimator response necessitates predictive models of respiratory tumor motion to synchronize radiation delivery. Predicting a complex process such as respiratory motion introduces geometric errors, which have been reported in several publications. However, the dosimetric effect of such errors on 4D radiation delivery has not yet been investigated. Thus, our aim in this work was to quantify the dosimetric effects of geometric error due to prediction under several different conditions. Conformal and intensity modulated radiation therapy (IMRT) plans for a lung patient were generated for anterior-posterior/posterior-anterior (AP/PA) beam arrangements at 6 and 18 MV energies to provide planned dose distributions. Respiratory motion data was obtained from 60 diaphragm-motion fluoroscopy recordings from five patients. A linear adaptive filter was employed to predict the tumor position. The geometric error of prediction was defined as the absolute difference between predicted and actual positions at each diaphragm position. Distributions of geometric error of prediction were obtained for all of the respiratory motion data. Planned dose distributions were then convolved with distributions for the geometric error of prediction to obtain convolved dose distributions. The dosimetric effect of such geometric errors was determined as a function of several variables: response time (0-0.6 s), beam energy (6/18 MV), treatment delivery (3D/4D), treatment type (conformal/IMRT), beam direction (AP/PA), and breathing training type (free breathing/audio instruction/visual feedback). Dose difference and distance-to-agreement analysis was employed to quantify results. Based on our data, the dosimetric impact of prediction (a) increased with response time, (b) was larger for 3D radiation therapy as compared with 4D radiation therapy, (c) was relatively insensitive to change in beam energy and beam direction, (d) was greater for IMRT distributions as compared with conformal distributions, (e) was smaller than the dosimetric impact of latency, and (f) was greatest for respiration motion with audio instructions, followed by visual feedback and free breathing. Geometric errors of prediction that occur during 4D radiation delivery introduce dosimetric errors that are dependent on several factors, such as response time, treatment-delivery type, and beam energy. Even for relatively small response times of 0.6 s into the future, dosimetric errors due to prediction could approach delivery errors when respiratory motion is not accounted for at all. To reduce the dosimetric impact, better predictive models and/or shorter response times are required.

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One limitation to the widespread implementation of Monte Carlo (MC) patient dose-calculation algorithms for radiotherapy is the lack of a general and accurate source model of the accelerator radiation source. Our aim in this work is to investigate the sensitivity of the photon-beam subsource distributions in a MC source model (with target, primary collimator, and flattening filter photon subsources and an electron subsource) for 6- and 18-MV photon beams when the energy and radial distributions of initial electrons striking a linac target change. For this purpose, phase-space data (PSD) was calculated for various mean electron energies striking the target, various normally distributed electron energy spread, and various normally distributed electron radial intensity distributions. All PSD was analyzed in terms of energy, fluence, and energy fluence distributions, which were compared between the different parameter sets. The energy spread was found to have a negligible influence on the subsource distributions. The mean energy and radial intensity significantly changed the target subsource distribution shapes and intensities. For the primary collimator and flattening filter subsources, the distribution shapes of the fluence and energy fluence changed little for different mean electron energies striking the target, however, their relative intensity compared with the target subsource change, which can be accounted for by a scaling factor. This study indicates that adjustments to MC source models can likely be limited to adjusting the target subsource in conjunction with scaling the relative intensity and energy spectrum of the primary collimator, flattening filter, and electron subsources when the energy and radial distributions of the initial electron-beam change.

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A major barrier to widespread clinical implementation of Monte Carlo dose calculation is the difficulty in characterizing the radiation source within a generalized source model. This work aims to develop a generalized three-component source model (target, primary collimator, flattening filter) for 6- and 18-MV photon beams that match full phase-space data (PSD). Subsource by subsource comparison of dose distributions, using either source PSD or the source model as input, allows accurate source characterization and has the potential to ease the commissioning procedure, since it is possible to obtain information about which subsource needs to be tuned. This source model is unique in that, compared to previous source models, it retains additional correlations among PS variables, which improves accuracy at nonstandard source-to-surface distances (SSDs). In our study, three-dimensional (3D) dose calculations were performed for SSDs ranging from 50 to 200 cm and for field sizes from 1 x 1 to 30 x 30 cm2 as well as a 10 x 10 cm2 field 5 cm off axis in each direction. The 3D dose distributions, using either full PSD or the source model as input, were compared in terms of dose-difference and distance-to-agreement. With this model, over 99% of the voxels agreed within +/-1% or 1 mm for the target, within 2% or 2 mm for the primary collimator, and within +/-2.5% or 2 mm for the flattening filter in all cases studied. For the dose distributions, 99% of the dose voxels agreed within 1% or 1 mm when the combined source model-including a charged particle source and the full PSD as input-was used. The accurate and general characterization of each photon source and knowledge of the subsource dose distributions should facilitate source model commissioning procedures by allowing scaling the histogram distributions representing the subsources to be tuned.

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PURPOSE: Study of behavior and influence of a multileaf collimator (MLC) on dose calculation, verification, and portal energy spectra in the case of intensity-modulated fields obtained with a step-and-shoot or a dynamic technique. METHODS: The 80-leaf MLC for the Varian Clinac 2300 C/D was implemented in a previously developed Monte Carlo (MC) based multiple source model (MSM) for a 6 MV photon beam. Using this model and the MC program GEANT, dose distributions, energy fluence maps and energy spectra at different portal planes were calculated for three different MLC applications. RESULTS: The comparison of MC-calculated dose distributions in the phantom and portal plane, with those measured with films showed an agreement within 3% and 1.5 mm for all cases studied. The deviations mainly occur in the extremes of the intensity modulation. The MC method allows to investigate, among other aspects, dose components, energy fluence maps, tongue-and-groove effects and energy spectra at portal planes. CONCLUSION: The MSM together with the implementation of the MLC is appropriate for a number of investigations in intensity-modulated radiation therapy (IMRT).

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A previously presented algorithm for the reconstruction of bremsstrahlung spectra from transmission data has been implemented into MATHEMATICA. Spectra vectorial algebra has been used to solve the matrix system A * F = T. The new implementation has been tested by reconstructing photon spectra from transmission data acquired in narrow beam conditions, for nominal energies of 6, 15, and 25 MV. The results were in excellent agreement with the original calculations. Our implementation has the advantage to be based on a well-tested mathematical kernel. Furthermore it offers a comfortable user interface.

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Monte Carlo (code GEANT) produced 6 and 15 MV phase space (PS) data were used to define several simple photon beam models. For creating the PS data the energy of starting electrons hitting the target was tuned to get correct depth dose data compared to measurements. The modeling process used the full PS information within the geometrical boundaries of the beam including all scattered radiation of the accelerator head. Scattered radiation outside the boundaries was neglected. Photons and electrons were assumed to be radiated from point sources. Four different models were investigated which involved different ways to determine the energies and locations of beam particles in the output plane. Depth dose curves, profiles, and relative output factors were calculated with these models for six field sizes from 5x5 to 40x40cm2 and compared to measurements. Model 1 uses a photon energy spectrum independent of location in the PS plane and a constant photon fluence in this plane. Model 2 takes into account the spatial particle fluence distribution in the PS plane. A constant fluence is used again in model 3, but the photon energy spectrum depends upon the off axis position. Model 4, finally uses the spatial particle fluence distribution and off axis dependent photon energy spectra in the PS plane. Depth dose curves and profiles for field sizes up to 10x10cm2 were not model sensitive. Good agreement between measured and calculated depth dose curves and profiles for all field sizes was reached for model 4. However, increasing deviations were found for increasing field sizes for models 1-3. Large deviations resulted for the profiles of models 2 and 3. This is due to the fact that these models overestimate and underestimate the energy fluence at large off axis distances. Relative output factors consistent with measurements resulted only for model 4.

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Today electronic portal imaging devices (EPID's) are used primarily to verify patient positioning. They have, however, also the potential as 2D-dosimeters and could be used as such for transit dosimetry or dose reconstruction. It has been proven that such devices, especially liquid filled ionization chambers, have a stable dose response relationship which can be described in terms of the physical properties of the EPID and the pulsed linac radiation. For absolute dosimetry however, an accurate method of calibration to an absolute dose is needed. In this work, we concentrate on calibration against dose in a homogeneous water phantom. Using a Monte Carlo model of the detector we calculated dose spread kernels in units of absolute dose per incident energy fluence and compared them to calculated dose spread kernels in water at different depths. The energy of the incident pencil beams varied between 0.5 and 18 MeV. At the depth of dose maximum in water for a 6 MV beam (1.5 cm) and for a 18 MV beam (3.0 cm) we observed large absolute differences between water and detector dose above an incident energy of 4 MeV but only small relative differences in the most frequent energy range of the beam energy spectra. It is shown that for a 6 MV beam the absolute reference dose measured at 1.5 cm water depth differs from the absolute detector dose by 3.8%. At depth 1.2 cm in water, however, the relative dose differences are almost constant between 2 and 6 MeV. The effects of changes in the energy spectrum of the beam on the dose responses in water and in the detector are also investigated. We show that differences larger than 2% can occur for different beam qualities of the incident photon beam behind water slabs of different thicknesses. It is therefore concluded that for high-precision dosimetry such effects have to be taken into account. Nevertheless, the precise information about the dose response of the detector provided in this Monte Carlo study forms the basis of extracting directly the basic radiometric quantities photon fluence and photon energy fluence from the detector's signal using a deconvolution algorithm. The results are therefore promising for future application in absolute transit dosimetry and absolute dose reconstruction.

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In external beam radiotherapy, electronic portal imaging becomes more and more an indispensable tool for the verification of the patient setup. For the safe clinical introduction of high dose conformal radiotherapy like intensity modulated radiation therapy, on-line patient setup verification is a prerequisite to ensure that the planned dosimetric coverage of the tumor volume is actually realized in the patient. Since the direction of setup fields often deviates from the direction of the treatment beams, extra dose is delivered to the patient during the acquisition of these portal images which may reach clinical relevance. The aim of this work was to develop a new acquisition mode for the PortalVision aS500 electronic portal imaging device from Varian Medical Systems that allows one to take portal images with reduced dose while keeping good image quality. The new acquisition mode, called RadMode, selectively enables and disables beam pulses during image acquisition allowing one to stop wasting valuable dose during the initial acquisition of "reset frames." Images of excellent quality can be taken with 1 MU only. This low dose per image facilitates daily setup verification with considerably reduced extra dose.

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The migration of monocytes to sites of inflammation is largely determined by their response to chemokines. Although the chemokine specificities and expression patterns of chemokine receptors are well defined, it is still a matter of debate how cells integrate the messages provided by different chemokines that are concomitantly produced in physiological or pathological situations in vivo. We present evidence for one regulatory mechanism of human monocyte trafficking. Monocytes can integrate stimuli provided by inflammatory chemokines in the presence of homeostatic chemokines. In particular, migration and cell responses could occur at much lower concentrations of the CCR2 agonists, in the presence of chemokines (CCL19 and CCL21) that per se do not act on monocytes. Binding studies on CCR2(+) cells showed that CCL19 and CCL21 do not compete with the CCR2 agonist CCL2. Furthermore, the presence of CCL19 or CCL21 could influence the degradation of CCL2 and CCL7 on cells expressing the decoy receptor D6. These findings disclose a new scenario to further comprehend the complexity of chemokine-based monocyte trafficking in a vast variety of human inflammatory disorders.

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BEAMnrc, a code for simulating medical linear accelerators based on EGSnrc, has been bench-marked and used extensively in the scientific literature and is therefore often considered to be the gold standard for Monte Carlo simulations for radiotherapy applications. However, its long computation times make it too slow for the clinical routine and often even for research purposes without a large investment in computing resources. VMC++ is a much faster code thanks to the intensive use of variance reduction techniques and a much faster implementation of the condensed history technique for charged particle transport. A research version of this code is also capable of simulating the full head of linear accelerators operated in photon mode (excluding multileaf collimators, hard and dynamic wedges). In this work, a validation of the full head simulation at 6 and 18 MV is performed, simulating with VMC++ and BEAMnrc the addition of one head component at a time and comparing the resulting phase space files. For the comparison, photon and electron fluence, photon energy fluence, mean energy, and photon spectra are considered. The largest absolute differences are found in the energy fluences. For all the simulations of the different head components, a very good agreement (differences in energy fluences between VMC++ and BEAMnrc <1%) is obtained. Only a particular case at 6 MV shows a somewhat larger energy fluence difference of 1.4%. Dosimetrically, these phase space differences imply an agreement between both codes at the <1% level, making VMC++ head module suitable for full head simulations with considerable gain in efficiency and without loss of accuracy.

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The GLAaS algorithm for pretreatment intensity modulation radiation therapy absolute dose verification based on the use of amorphous silicon detectors, as described in Nicolini et al. [G. Nicolini, A. Fogliata, E. Vanetti, A. Clivio, and L. Cozzi, Med. Phys. 33, 2839-2851 (2006)], was tested under a variety of experimental conditions to investigate its robustness, the possibility of using it in different clinics and its performance. GLAaS was therefore tested on a low-energy Varian Clinac (6 MV) equipped with an amorphous silicon Portal Vision PV-aS500 with electronic readout IAS2 and on a high-energy Clinac (6 and 15 MV) equipped with a PV-aS1000 and IAS3 electronics. Tests were performed for three calibration conditions: A: adding buildup on the top of the cassette such that SDD-SSD = d(max) and comparing measurements with corresponding doses computed at d(max), B: without adding any buildup on the top of the cassette and considering only the intrinsic water-equivalent thickness of the electronic portal imaging devices device (0.8 cm), and C: without adding any buildup on the top of the cassette but comparing measurements against doses computed at d(max). This procedure is similar to that usually applied when in vivo dosimetry is performed with solid state diodes without sufficient buildup material. Quantitatively, the gamma index (gamma), as described by Low et al. [D. A. Low, W. B. Harms, S. Mutic, and J. A. Purdy, Med. Phys. 25, 656-660 (1998)], was assessed. The gamma index was computed for a distance to agreement (DTA) of 3 mm. The dose difference deltaD was considered as 2%, 3%, and 4%. As a measure of the quality of results, the fraction of field area with gamma larger than 1 (%FA) was scored. Results over a set of 50 test samples (including fields from head and neck, breast, prostate, anal canal, and brain cases) and from the long-term routine usage, demonstrated the robustness and stability of GLAaS. In general, the mean values of %FA remain below 3% for deltaD equal or larger than 3%, while they are slightly larger for deltaD = 2% with %FA in the range from 3% to 8%. Since its introduction in routine practice, 1453 fields have been verified with GLAaS at the authors' institute (6 MV beam). Using a DTA of 3 mm and a deltaD of 4% the authors obtained %FA = 0.9 +/- 1.1 for the entire data set while, stratifying according to the dose calculation algorithm, they observed: %FA = 0.7 +/- 0.9 for fields computed with the analytical anisotropic algorithm and %FA = 2.4 +/- 1.3 for pencil-beam based fields with a statistically significant difference between the two groups. If data are stratified according to field splitting, they observed %FA = 0.8 +/- 1.0 for split fields and 1.0 +/- 1.2 for nonsplit fields without any significant difference.

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Carbon nanotube (CNT) is a one dimensional (1-D) nanostructured material, which has been the focal point of research over the past decade for intriguing applications ranging from nanoelectronics to chemical and biological sensors. Using a first-principles gradient corrected density functional approach, we present a comprehensive study of the geometry and energy band gap in zig-zag semi-conducting (n,0) carbon nanotubes (CNT) to resolve some of the conflicting findings. Our calculations confirm that the single wall (n,0) CNTs fall into two distinct classes depending upon n mod 3 equal to 1 (smaller band gaps) or 2 (larger gaps). The effect of longitudinal strain on the band gap further confirms the existence of two distinct classes: for n mod 3 = 1 or 2, changing Eg by ~ ±110 meV for 1% strain in each case. We also present our findings for the origin of metallicity in multiwall CNTs.

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Purpose: Development of an interpolation algorithm for re‐sampling spatially distributed CT‐data with the following features: global and local integral conservation, avoidance of negative interpolation values for positively defined datasets and the ability to control re‐sampling artifacts. Method and Materials: The interpolation can be separated into two steps: first, the discrete CT‐data has to be continuously distributed by an analytic function considering the boundary conditions. Generally, this function is determined by piecewise interpolation. Instead of using linear or high order polynomialinterpolations, which do not fulfill all the above mentioned features, a special form of Hermitian curve interpolation is used to solve the interpolation problem with respect to the required boundary conditions. A single parameter is determined, by which the behavior of the interpolation function is controlled. Second, the interpolated data have to be re‐distributed with respect to the requested grid. Results: The new algorithm was compared with commonly used interpolation functions based on linear and second order polynomial. It is demonstrated that these interpolation functions may over‐ or underestimate the source data by about 10%–20% while the parameter of the new algorithm can be adjusted in order to significantly reduce these interpolation errors. Finally, the performance and accuracy of the algorithm was tested by re‐gridding a series of X‐ray CT‐images. Conclusion: Inaccurate sampling values may occur due to the lack of integral conservation. Re‐sampling algorithms using high order polynomialinterpolation functions may result in significant artifacts of the re‐sampled data. Such artifacts can be avoided by using the new algorithm based on Hermitian curve interpolation