Biomedical subjects

Jeffrey V Siebers

Publications and source records attributed to Jeffrey V Siebers.

At least 19 recordsLinked to original sources

PubMed2006

An analysis of 6-MV versus 18-MV photon energy plans for intensity-modulated radiation therapy (IMRT) of lung cancer.

PURPOSE: To analyse the supposed benefits of low over high photon energies for the radiotherapy of lung cancer. MATERIALS AND METHODS: For 13 patients, 6- and 18-MV IMRT planning was performed using identical planning objectives and dose constraints. Plans were compared according to dose-volume histogram (DVH) analysis including conformity and homogeneity indices (CI and HI) and overall plan quality (composite score CS), considering also magnitude and location of planning target volumes (PTVs). RESULTS: With 6-MV plans, CSs were better in 11/13, HIs in 10/13 and CIs in 6/13 patients compared with 18-MV plans. Six-MV plans resulted in a better normal tissue sparing except for specified dose levels to the thorax and spinal cord. On average differences between 6 and 18 MV both for the PTV and normal tissues were not statistically significant (p>0.05). Considering size and location of the PTVs as well as their relative position to normal tissue, overall no significant differences between 6 and 18 MV were observed. CONCLUSIONS: On average no clinically or statistically significant differences between 6- and 18-MV plans were observed. High photon energies should therefore not be excluded a priori when a dose-calculation algorithm is utilized that accurately accounts for heterogeneities.

Dose-Response Relationship, Radiation↗

PubMed2006

Dosimetric verification for intensity-modulated radiotherapy of thoracic cancers using experimental and Monte Carlo approaches.

PURPOSE: To investigate the dosimetric accuracy of commercial treatment planning systems used in intensity-modulated radiotherapy (IMRT) for thoracic cancer. METHODS AND MATERIALS: Clinical IMRT plans for lung and esophageal cancers and mesothelioma were used to investigate the accuracy of dose calculations from two commercial treatment planning systems (Pinnacle and Corvus systems). Dose distributions were measured with ion chambers and thermoluminescent dosimeters for individual IMRT fields and composite treatment plans in water phantoms and anthropomorphic phantoms. A Monte Carlo-based system was established to compute three-dimensional dose distributions to compare with the treatment planning system calculations. RESULTS: Dose calculations from the Pinnacle system were acceptable within 5% of the local dose or a 5-mm distance-to-agreement for 80% of the points measured with ion chambers, 74% of the points measured with thermoluminescent dosimeters, and 96% of the points compared with the Monte Carlo calculations. For the Corvus system, 89% of the points agreed with the measured dose and 98% agreed with the Monte Carlo calculations. Underestimation of the dose from the treatment planning system was found in the low-dose regions (<50% of the prescribed dose), possibly caused by inadequate modeling of the multileaf collimators. CONCLUSION: The Pinnacle and Corvus dose calculations were acceptable for thoracic IMRT in high-dose regions. Beam modeling is likely the most critical factor for the accuracy of IMRT dose calculations.

Algorithms↗

PubMed2006

Monte Carlo-based dosimetry of head-and-neck patients treated with SIB-IMRT.

PURPOSE: To evaluate the accuracy of previously reported superposition/convolution (SC) dosimetric results by comparing with Monte Carlo (MC) dose calculations for head-and-neck intensity-modulated radiation therapy (IMRT) patients treated with the simultaneous integrated boost technique. METHODS AND MATERIALS: Thirty-one plans from 24 patients previously treated on a phase I/II head-and-neck squamous cell carcinoma simultaneous integrated boost IMRT protocol were used. Clinical dose distributions, computed with an SC algorithm, were recomputed using an EGS4-based MC algorithm. Phantom-based dosimetry quantified the fluence prediction accuracy of each algorithm. Dose-volume indices were used to compare patient dose distributions. RESULTS AND DISCUSSION: The MC algorithm predicts flat-phantom measurements better than the SC algorithm. Average patient dose indices agreed within 2.5% of the local dose for targets; 5.0% for parotids; and 1.9% for cord and brainstem. However, only 1 of 31 plans agreed within 3% for all indices; 4 of 31 agreed within 5%. In terms of the prescription dose, 4 of 31 plans agreed within 3% for all indices, whereas 28 of 31 agreed within 5%. CONCLUSIONS: Average SC-computed doses agreed with MC results in the patient geometry; however deviations >5% were common. The fluence modulation prediction is likely the major source of the dose discrepancy. The observed dose deviations can impact dose escalation protocols, because they would result in shifting patients to higher dose levels.

Algorithms↗

PubMed2006

Development and commissioning of a multileaf collimator model in monte carlo dose calculations for intensity-modulated radiation therapy.

A multileaf collimator (MLC) model, "MATMLC," was developed to simulate MLCs for Monte Carlo (MC) dose calculations of intensity-modulated radiation therapy (IMRT). This model describes MLCs using matrices of regions, each of which can be independently defined for its material and geometry, allowing flexibility in simulating MLCs from various manufacturers. The free parameters relevant to the dose calculations with this MLC model included MLC leaf density, interleaf air gap, and leaf geometry. To commission the MLC model and its free parameters for the Varian Millennium MLC-120 (Varian Oncology Systems, Palo Alto, CA), we used the following leaf patterns: (1) MLC-blocked fields to test the effects of leaf transmission and leakage; (2) picket-fence fields to test the effects of the interleaf air gap and tongue-groove design; and (3) abutting-gap fields to test the effects of rounded leaf ends. Transmission ratios and intensity maps for these leaf patterns were calculated with various sets of modeling parameters to determine their dosimetric effects, sensitivities, and their optimal combinations to give the closest agreement with measured results. Upon commissioning the MLC model, we computed dose distributions for clinical IMRT plans using the MC system and verified the results with those from ion chamber and thermoluminescent dosimeter measurements in water phantoms and anthropomorphic phantoms. This study showed that the MLC transmission ratios were strongly dependent on both leaf density and the interleaf air gap. The effect of interleaf air gap and tongue-groove geometry can be determined most effectively through fence-type MLC patterns. Using the commissioned MLC model, we found that the calculated dose from the MC system agreed with the measured data within clinically acceptable criteria from low- to high-dose regions, showing that the model is acceptable for clinical applications.

Humans↗

PubMed2005

Effect of patient setup errors on simultaneously integrated boost head and neck IMRT treatment plans.

PURPOSE: The purpose of this study is to determine dose delivery errors that could result from random and systematic setup errors for head-and-neck patients treated using the simultaneous integrated boost (SIB)-intensity-modulated radiation therapy (IMRT) technique. METHODS AND MATERIALS: Twenty-four patients who participated in an intramural Phase I/II parotid-sparing IMRT dose-escalation protocol using the SIB treatment technique had their dose distributions reevaluated to assess the impact of random and systematic setup errors. The dosimetric effect of random setup error was simulated by convolving the two-dimensional fluence distribution of each beam with the random setup error probability density distribution. Random setup errors of sigma = 1, 3, and 5 mm were simulated. Systematic setup errors were simulated by randomly shifting the patient isocenter along each of the three Cartesian axes, with each shift selected from a normal distribution. Systematic setup error distributions with Sigma = 1.5 and 3.0 mm along each axis were simulated. Combined systematic and random setup errors were simulated for sigma = Sigma = 1.5 and 3.0 mm along each axis. For each dose calculation, the gross tumor volume (GTV) received by 98% of the volume (D(98)), clinical target volume (CTV) D(90), nodes D(90), cord D(2), and parotid D(50) and parotid mean dose were evaluated with respect to the plan used for treatment for the structure dose and for an effective planning target volume (PTV) with a 3-mm margin. RESULTS: Simultaneous integrated boost-IMRT head-and-neck treatment plans were found to be less sensitive to random setup errors than to systematic setup errors. For random-only errors, errors exceeded 3% only when the random setup error sigma exceeded 3 mm. Simulated systematic setup errors with Sigma = 1.5 mm resulted in approximately 10% of plan having more than a 3% dose error, whereas a Sigma = 3.0 mm resulted in half of the plans having more than a 3% dose error and 28% with a 5% dose error. Combined random and systematic dose errors with sigma = Sigma = 3.0 mm resulted in more than 50% of plans having at least a 3% dose error and 38% of the plans having at least a 5% dose error. Evaluation with respect to a 3-mm expanded PTV reduced the observed dose deviations greater than 5% for the sigma = Sigma = 3.0 mm simulations to 5.4% of the plans simulated. CONCLUSIONS: Head-and-neck SIB-IMRT dosimetric accuracy would benefit from methods to reduce patient systematic setup errors. When GTV, CTV, or nodal volumes are used for dose evaluation, plans simulated including the effects of random and systematic errors deviate substantially from the nominal plan. The use of PTVs for dose evaluation in the nominal plan improves agreement with evaluated GTV, CTV, and nodal dose values under simulated setup errors. PTV concepts should be used for SIB-IMRT head-and-neck squamous cell carcinoma patients, although the size of the margins may be less than those used with three-dimensional conformal radiation therapy.

Algorithms↗

PubMed2005

Verification of the optimal backscatter for an aSi electronic portal imaging device.

Electronic portal imaging devices (EPIDs), currently used for determining proper patient placement during irradiation in a radiotherapy treatment, can also be used as dosimeters. However, the Varian aS500 portal imager exhibits dosimetric artefacts caused by non-uniform backscatter from mechanical support structures located behind the imager. Monte Carlo simulations predict that adding 5 mm of Pb behind the imaging cassette will reduce the non-uniform backscatter to <1% for 6 MV and to <1.5% for 18 MV photon beams. This study experimentally tested this hypothesis by comparing images using an unmodified test imager and an imager modified by adding 3 and 5 mm of Pb behind the imaging cassette. Using the modified imager containing 5 mm of Pb, the non-uniform backscatter was reduced to <0.5% for 6 MV and <0.6% for 18 MV beams. Addition of the 5 mm of Pb increased the detector contrast by 3.5% +/- 0.5% at 6 MV and 5.0% +/- 0.7% at 18 MV, and increased the resolution by 0.9% +/- 0.2% at 6 MV and 0.5% +/- 0.12% at 18 MV.

Body Burden↗

PubMed2005

Four-dimensional radiotherapy planning for DMLC-based respiratory motion tracking.

Four-dimensional (4D) radiotherapy is the explicit inclusion of the temporal changes in anatomy during the imaging, planning, and delivery of radiotherapy. Temporal anatomic changes can occur for many reasons, though the focus of the current investigation is respiration motion for lung tumors. The aim of this study was to develop 4D radiotherapy treatment-planning methodology for DMLC-based respiratory motion tracking. A 4D computed tomography (CT) scan consisting of a series of eight 3D CT image sets acquired at different respiratory phases was used for treatment planning. Deformable image registration was performed to map each CT set from the peak-inhale respiration phase to the CT image sets corresponding to subsequent respiration phases. Deformable registration allows the contours defined on the peak-inhale CT to be automatically transferred to the other respiratory phase CT image sets. Treatment planning was simultaneously performed on each of the eight 3D image sets via automated scripts in which the MLC-defined beam aperture conforms to the PTV (which in this case equaled the GTV due to CT scan length limitations) plus a penumbral margin at each respiratory phase. The dose distribution from each respiratory phase CT image set was mapped back to the peak-inhale CT image set for analysis. The treatment intent of 4D planning is that the radiation beam defined by the DMLC tracks the respiration-induced target motion based on a feedback loop including the respiration signal to a real-time MLC controller. Deformation with respiration was observed for the lung tumor and normal tissues. This deformation was verified by examining the mapping of high contrast objects, such as the lungs and cord, between image sets. For the test case, dosimetric reductions for the cord, heart, and lungs were found for 4D planning compared with 3D planning. 4D radiotherapy planning for DMLC-based respiratory motion tracking is feasible and may offer tumor dose escalation and/or a reduction in treatment-related complications. However, 4D planning requires new planning tools, such as deformable registration and automated treatment planning on multiple CT image sets.

Dose-Response Relationship, Radiation↗

PubMed2005

Photon-beam subsource sensitivity to the initial electron-beam parameters.

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.

Algorithms↗

PubMed2004

Monte Carlo-based treatment planning for a spoiler system with experimental validation using plane-parallel ionization chambers.

A beam spoiler is often used to increase the build-up dose near the surface for treatment of superficial treatment areas. Photon-beam spoilers produce a large amount of contaminant electrons, conditions for which standard, commercial treatment-planning system dose-calculation algorithms are inadequate for producing accurate dose calculations. In this study, we implemented a Monte Carlo (MC) dose-calculation algorithm for this spoiler system. With and without a spoiler of 1 cm Lucite, depth doses and transverse profiles in the build-up region were measured for field sizes of 5 x 5 cm2 and 10 x 10 cm2 at the spoiler-to-surface distances (STSDs) of 6, 10 and 15 cm. An Attix chamber and a Markus chamber were used for depth doses, whereas a diode detector was used for transverse profiles. An MC simulation using BEAM/DOSXYZ was used to compare the calculated and the measured data. The MC calculations agreed with the Attix chamber measurements within 2% for all STSDs and field sizes, whereas the Markus data--even with corrections made-showed a discrepancy of about 3.5% with a maximum difference of 7.3% for a field size of 10 x 10 cm2 at an STSD of 6 cm. The MC treatment-planning system was successfully applied to a head-and-neck case using 6 MV photon beams with a beam spoiler.

Algorithms↗

PubMed2004

Investigation of the optimal backscatter for an aSi electronic portal imaging device.

The effects of backscattered radiation on the dosimetric response of the Varian aS500 amorphous silicon electronic portal imaging device (EPID) are studied. Measurements demonstrate that radiation backscattered from the EPID mechanical support structure causes 5% asymmetries in the detected signal. To minimize the effect of backscattered radiation from the support structure, this work proposes adding material downstream of the EPID phosphor which provides uniform backscattering material to the phosphor and attenuates backscatter from the support structure before it reaches the phosphor. Two material locations were studied: downstream of the existing image cassette and within the cassette, immediately downstream of the flat-panel imager glass panel. Monte Carlo simulations were used to determine the thicknesses of water, Pb and Cu backscattering materials required to saturate the backscattered signal response for 6 MV and 18 MV beams for material thicknesses up to 50 mm. Water was unable to saturate the backscattered signal for thicknesses up to 50 mm for both energies. For Pb, to obtain a signal within 1% of saturation, 3 mm was required at 6 MV, and 6.8 mm was required at 18 MV. For Cu, thicknesses of 20.6 mm and 22.6 mm were required for the 6 MV and 18 MV beams, respectively. For saturation thicknesses, at 6 MV, the Cu backscatter enhanced the signal more than for Pb (Cu 1.25, Pb 1.11), but at 18 MV the reverse was found (Cu 1.19, Pb 1.23). This is due to the fact that at 6 MV, the backscattered radiation signal is dominated by low-energy scattered photons, which are readily attenuated by the Pb, while at 18 MV, electron backscatter contributes substantially to the signal. Image blurring caused by backscatter spread was less for Pb than Cu. Placing Pb immediately downstream of the glass panel further reduced the signal spread and increased the backscatter enhancement to 1.20 and 1.39 for the 6 MV and 18 MV beams, respectively. Overall, it is determined that adding approximately 5 mm of Pb between the detector and the mechanical support structure will substantially reduce the nonuniformity in the backscattered signals for 6 MV and 18 MV photon beams.

Copper↗

PubMed2004

Monte Carlo computation of dosimetric amorphous silicon electronic portal images.

This study develops and tests a method to compute dosimetric images for an amorphous silicon (a-Si) flat-panel detector so that an accurate quantitative comparison between measured and computed portal images may be made. An EGS4-based Monte Carlo (MC) algorithm is developed to efficiently tally the energy deposition through the use of a virtual detector dose-scoring methodology. The complete geometry of the a-Si imager is utilized in the MC calculation up to the imager rear housing, which is replaced with a uniform thickness material slab. The detector-mounting hardware is modeled as a uniform backscattering material. The amount of backscatter material required to reproduce the measured backscatter is 0.98 g/cm2 of water. A flood-field irradiation, performed in the measurement imaging session, is used to cross-calibrate the computed images with the measured images. Calibrated MC-computed images reproduce measured field-size dependencies of the electronic portal imaging device (EPID) response to within <1%, without the need for optical glare or other empirical corrections. A 10% dose difference between measured and computed images was observed outside the field edge for a 10 x 10 cm2 field that was entirely blocked by the multileaf collimator (MLC). However, this error corresponded with less than 0.15% of the open-field dose. For 10 x 10 cm2 fields produced by 5 and 20 mm dynamically sweeping MLC gaps, more than 98% of the points were found to have a gamma less than one with a 2%, 2 mm criteria. For an intensity modulated radiation therapy (IMRT) patient test field, over 99% of the points were found to have a gamma less than one with a 2%, 2 mm criteria. This study demonstrates that MC can be an effective tool for predicting measured a-Si portal images and may be useful for IMRT EPID-based dosimetry.

Algorithms↗

PubMed2004

Monte Carlo source model for photon beam radiotherapy: photon source characteristics.

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.

Algorithms↗

PubMed2003

Radiotherapy dose calculations in the presence of hip prostheses.

The high density and atomic number of hip prostheses for patients undergoing pelvic radiotherapy challenge our ability to accurately calculate dose. A new clinical dose calculation algorithm, Monte Carlo, will allow accurate calculation of the radiation transport both within and beyond hip prostheses. The aim of this research was to investigate, for both phantom and patient geometries, the capability of various dose calculation algorithms to yield accurate treatment plans. Dose distributions in phantom and patient geometries with high atomic number prostheses were calculated using Monte Carlo, superposition, pencil beam, and no-heterogeneity correction algorithms. The phantom dose distributions were analyzed by depth dose and dose profile curves. The patient dose distributions were analyzed by isodose curves, dose-volume histograms (DVHs) and tumor control probability/normal tissue complication probability (TCP/NTCP) calculations. Monte Carlo calculations predicted the dose enhancement and reduction at the proximal and distal prosthesis interfaces respectively, whereas superposition and pencil beam calculations did not. However, further from the prosthesis, the differences between the dose calculation algorithms diminished. Treatment plans calculated with superposition showed similar isodose curves, DVHs, and TCP/NTCP as the Monte Carlo plans, except in the bladder, where Monte Carlo predicted a slightly lower dose. Treatment plans calculated with either the pencil beam method or with no heterogeneity correction differed significantly from the Monte Carlo plans.

Algorithms↗

PubMed2003

Image reconstruction and the effect on dose calculation for hip prostheses.

High atomic number inserts, such as hip prostheses and dental fillings, cause streak artifacts on computed tomography (CT) images when filtered back-projection (FBP) methods are used. These streak artifacts severely degrade our ability to differentiate the tumor volume. Also, incorrect Hounsfield numbers yield incorrect electron density information that may lead to erroneous dose calculations, and, as a result, compromise clinical outcomes. The aim of this research was to evaluate the dosimetric consequences of artifacts during radiotherapy planning of a prostate patient containing a hip prosthesis. The CT numbers corresponding to an iron prosthesis were inserted into the right femoral head of an existing CT image set. This artifact-free image was used as the standard image set. CT projections through the image set formed the sinogram, from which filtered back projection and iterative deblurring methods were used to create reconstructed image sets. These reconstructed image sets contained artifacts. Prostate treatment plans were then calculated using a Monte Carlo system for the standard and reconstructed CT image sets. Close to the prosthesis, the CT numbers between the reconstructed and standard image sets differed substantially. However, because the CT number differences covered only a small area, the dose distributions on the reconstructed and standard image sets were not significantly different. The dose-volume histograms for the prostate, rectum, and bladder were virtually identical. Our results indicate that even though CT image artifacts restrict our ability to differentiate tumors and critical structures, the dose distributions for a prostate plan containing a hip prosthesis, calculated on both artifact-free image sets and image sets containing artifacts, are not significantly different.

Algorithms↗

PubMed2003

Determining the incident electron fluence for Monte Carlo-based photon treatment planning using a standard measured data set.

An accurate dose calculation in phantom and patient geometries requires an accurate description of the radiation source. Errors in the radiation source description are propagated through the dose calculation. With the emergence of linear accelerators whose dosimetric characteristics are similar to within measurement uncertainty, the same radiation source description can be used as the input to dose calculation for treatment planning at many institutions with the same linear accelerator model. Our goal in the current research was to determine the initial electron fluence above the linear accelerator target for such an accelerator to allow a dose calculation in water to within 1% or 1 mm of the measured data supplied by the manufacturer. The method used for both the radiation source description and the patient transport was Monte Carlo. The linac geometry was input into the Monte Carlo code using the accelerator's manufacturer's specifications. Assumptions about the initial electron source above the target were made based on previous studies. The free parameters derived for the calculations were the mean energy and radial Gaussian width of the initial electron fluence and the target density. A combination of the free parameters yielded an initial electron fluence that, when transported through the linear accelerator and into the phantom, allowed a dose-calculation agreement to the experimental ion chamber data to within the specified criteria at both 6 and 18 MV nominal beam energies, except near the surface, particularly for the 18 MV beam. To save time during Monte Carlo treatment planning, the initial electron fluence was transported through part of the treatment head to a plane between the monitor chambers and the jaws and saved as phase-space files. These files are used for clinical Monte Carlo-based treatment planning and are freely available from the authors.

Algorithms↗

PubMed2002

A method for photon beam Monte Carlo multileaf collimator particle transport.

Monte Carlo (MC) algorithms are recognized as the most accurate methodology for patient dose assessment. For intensity-modulated radiation therapy (IMRT) delivered with dynamic multileaf collimators (DMLCs), accurate dose calculation, even with MC, is challenging. Accurate IMRT MC dose calculations require inclusion of the moving MLC in the MC simulation. Due to its complex geometry, full transport through the MLC can be time consuming. The aim of this work was to develop an MLC model for photon beam MC IMRT dose computations. The basis of the MC MLC model is that the complex MLC geometry can be separated into simple geometric regions, each of which readily lends itself to simplified radiation transport. For photons, only attenuation and first Compton scatter interactions are considered. The amount of attenuation material an individual particle encounters while traversing the entire MLC is determined by adding the individual amounts from each of the simplified geometric regions. Compton scatter is sampled based upon the total thickness traversed. Pair production and electron interactions (scattering and bremsstrahlung) within the MLC are ignored. The MLC model was tested for 6 MV and 18 MV photon beams by comparing it with measurements and MC simulations that incorporate the full physics and geometry for fields blocked by the MLC and with measurements for fields with the maximum possible tongue-and-groove and tongue-or-groove effects, for static test cases and for sliding windows of various widths. The MLC model predicts the field size dependence of the MLC leakage radiation within 0.1% of the open-field dose. The entrance dose and beam hardening behind a closed MLC are predicted within +/- 1% or 1 mm. Dose undulations due to differences in inter- and intra-leaf leakage are also correctly predicted. The MC MLC model predicts leaf-edge tongue-and-groove dose effect within +/- 1% or 1 mm for 95% of the points compared at 6 MV and 88% of the points compared at 18 MV. The dose through a static leaf tip is also predicted generally within +/- 1% or 1 mm. Tests with sliding windows of various widths confirm the accuracy of the MLC model for dynamic delivery and indicate that accounting for a slight leaf position error (0.008 cm for our MLC) will improve the accuracy of the model. The MLC model developed is applicable to both dynamic MLC and segmental MLC IMRT beam delivery and will be useful for patient IMRT dose calculations, pre-treatment verification of IMRT delivery and IMRT portal dose transmission dosimetry.

Algorithms↗

PubMed2002

The effect of dose calculation accuracy on inverse treatment planning.

The effect of dose calculation accuracy during inverse treatment planning for intensity modulated radiotherapy (IMRT) was studied in this work. Three dose calculation methods were compared: Monte Carlo, superposition and pencil beam. These algorithms were used to calculate beamlets. which were subsequently used by a simulated annealing algorithm to determine beamlet weights which comprised the optimal solution to the objective function. Three different cases (lung, prostate and head and neck) were investigated and several different objective functions were tested for their effect on inverse treatment planning. It is shown that the use of inaccurate dose calculation introduces two errors in a treatment plan, a systematic error and a convergence error. The systematic error is present because of the inaccuracy of the dose calculation algorithm. The convergence error appears because the optimal intensity distribution for inaccurate beamlets differs from the optimal solution for the accurate beamlets. While the systematic error for superposition was found to be approximately 1% of Dmax in the tumour and slightly larger outside, the error for the pencil beam method is typically approximately 5% of Dmax and is rather insensitive to the given objectives. On the other hand, the convergence error was found to be very sensitive to the objective function, is only slightly correlated to the systematic error and should be determined for each case individually. Our results suggest that because of the large systematic and convergence errors, inverse treatment planning systems based on pencil beam algorithms alone should be upgraded either to superposition or Monte Carlo based dose calculations.

Algorithms↗

PubMed2002

Reducing dose calculation time for accurate iterative IMRT planning.

A time-consuming component of IMRT optimization is the dose computation required in each iteration for the evaluation of the objective function. Accurate superposition/convolution (SC) and Monte Carlo (MC) dose calculations are currently considered too time-consuming for iterative IMRT dose calculation. Thus, fast, but less accurate algorithms such as pencil beam (PB) algorithms are typically used in most current IMRT systems. This paper describes two hybrid methods that utilize the speed of fast PB algorithms yet achieve the accuracy of optimizing based upon SC algorithms via the application of dose correction matrices. In one method, the ratio method, an infrequently computed voxel-by-voxel dose ratio matrix (R = D(SC)/D(PB)) is applied for each beam to the dose distributions calculated with the PB method during the optimization. That is, D(PB) x R is used for the dose calculation during the optimization. The optimization proceeds until both the IMRT beam intensities and the dose correction ratio matrix converge. In the second method, the correction method, a periodically computed voxel-by-voxel correction matrix for each beam, defined to be the difference between the SC and PB dose computations, is used to correct PB dose distributions. To validate the methods, IMRT treatment plans developed with the hybrid methods are compared with those obtained when the SC algorithm is used for all optimization iterations and with those obtained when PB-based optimization is followed by SC-based optimization. In the 12 patient cases studied, no clinically significant differences exist in the final treatment plans developed with each of the dose computation methodologies. However, the number of time-consuming SC iterations is reduced from 6-32 for pure SC optimization to four or less for the ratio matrix method and five or less for the correction method. Because the PB algorithm is faster at computing dose, this reduces the inverse planning optimization time for our implementation by a factor of 2 to 8 compared with pure SC optimization, without compromising the quality or accuracy of the final treatment plan.

Algorithms↗