Reference Dose Distribution Research Articles

Effect of statistical fluctuation in Monte Carlo based photon beam dose calculation on gamma index evaluation

The γ-index test has been commonly adopted to quantify the degree of agreement between a reference dose distribution and an evaluation dose distribution. Monte Carlo (MC) simulation has been widely used for the radiotherapy dose calculation for both clinical and research purposes. The goal of this work is to investigate both theoretically and experimentally the impact of the MC statistical fluctuation on the γ-index test when the fluctuation exists in the reference, the evaluation, or both dose distributions. To the first order approximation, we theoretically demonstrated in a simplified model that the statistical fluctuation tends to overestimate γ-index values when existing in the reference dose distribution and underestimate γ-index values when existing in the evaluation dose distribution given the original γ-index is relatively large for the statistical fluctuation. Our numerical experiments using realistic clinical photon radiation therapy cases have shown that (1) when performing a γ-index test between an MC reference dose and a non-MC evaluation dose, the average γ-index is overestimated and the gamma passing rate decreases with the increase of the statistical noise level in the reference dose; (2) when performing a γ-index test between a non-MC reference dose and an MC evaluation dose, the average γ-index is underestimated when they are within the clinically relevant range and the gamma passing rate increases with the increase of the statistical noise level in the evaluation dose; (3) when performing a γ-index test between an MC reference dose and an MC evaluation dose, the gamma passing rate is overestimated due to the statistical noise in the evaluation dose and underestimated due to the statistical noise in the reference dose. We conclude that the γ-index test should be used with caution when comparing dose distributions computed with MC simulation.

Projection imaging of photon beams using Čerenkov-excited fluorescence

Full 3D beam profiling and quality assurance (QA) of therapeutic megavoltage linear accelerator (LINAC) x-ray photon beams is not routinely performed due to the slow point-by-point measurement nature of conventional scanning ionization chamber systems. In this study we explore a novel optical-based dose imaging approach using a standard commercial camera, water tank, and fluorescent dye, which when excited by the Čerenkov emission induced by the radiation beam, allows 2D projection imaging in a fast timeframe, potentially leading toward 3D tomographic beam profiling. Detailed analysis was carried out to optimize the imaging parameters in the experimental setup. The results demonstrate that the captured images are linear with delivered dose, independent of dose rate, and comparison of experimentally captured images to a reference dose distribution for a 4 × 4 cm2 6 MV x-ray photon beam yielded results with improved accuracy over a previous study which used direct imaging and Monte Carlo calibration of the Čerenkov emission itself. The agreement with the reference dose distribution was within 1–2% in the lateral direction, and ±3% in the depth direction. The study was restricted to single 2D image projection, with the eventual goal of creating full 3D profiles after tomographic reconstruction from multiple projections. Given the increasingly complex advances in radiation therapy, and the increased emphasis on patient-specific treatment plans, further refinement of the technique could prove to be an important tool for fast and robust QA of x-ray photon LINAC beams.

Projection imaging of photon beams by the Čerenkov effect

A novel technique for beam profiling of megavoltage photon beams was investigated for the first time by capturing images of the induced Čerenkov emission in water, as a potential surrogate for the imparted dose in irradiated media. A high-sensitivity, intensified CCD camera (ICCD) was configured to acquire 2D projection images of Čerenkov emission from a 4 × 4 cm(2) 6 MV linear accelerator (LINAC) x-ray photon beam operating at a dose rate of 400 MU∕min incident on a water tank with transparent walls. The ICCD acquisition was gated to the LINAC sync pulse to reduce background light artifacts, and the measurement quality was investigated by evaluating the signal to noise ratio and measurement repeatability as a function of delivered dose. Monte Carlo simulations were used to derive a calibration factor for differences between the optical images and deposited dose arising from the anisotropic angular dependence of Čerenkov emission. Finally, Čerenkov-based beam profiles were compared to a percent depth dose (PDD) and lateral dose profile at a depth of d(max) from a reference dose distribution generated from the clinical Varian ECLIPSE treatment planning system (TPS). The signal to noise ratio was found to be 20 at a delivered dose of 66.6 cGy, and proportional to the square root of the delivered dose as expected from Poisson photon counting statistics. A 2.1% mean standard deviation and 5.6% maximum variation in successive measurements were observed, and the Monte Carlo derived calibration factor resulted in Čerenkov emission images which were directly correlated to deposited dose, with some spatial issues. The dose difference between the TPS and PDD predicted by Čerenkov measurements was within 20% in the buildup region with a distance to agreement (DTA) of 1.5-2 mm and ±3% at depths beyond d(max). In the lateral profile, the dose difference at the beam penumbra was within ±13% with a DTA of 0-2 mm, ±5% in the central beam region, and 2%-3% in the beam umbra. The results from this initial study demonstrate the first documented use of Čerenkov emission imaging to profile x-ray photon LINAC beams in water. The proposed modality has several potential advantages over alternative methods, and upon future refinement may prove to be a robust and novel dosimetry method.

SU-E-T-41: 2D Vs 3D Gamma Analysis: Establishment of Comparable Clinical Action Limits

Purpose: As clinics begin to use 3D quality assurance (QA) metrics, an investigation into appropriate action limits is required. This can be accomplished by comparing results of the 3D metric to the existing 2D metric. To investigate this, we compared 2D and 3D gamma analysis results to determine 3D gamma action limits that would Result in comparable 2D QA outcomes. Methods: 2D and 3D gamma QA analysis results for ten clinical IMRT patients using a variety of distance‐to‐agreements (DTA), dose‐thresholds, and interpolated slice thicknesses were chosen for this study. Clinical treatment planning system (TPS)‐calculated dose (evaluated) distribution and Monte Carlo‐calculated (reference) dose distribution were compared using DoseLab (Mobius Medical Systems) gamma analysis software that calculates 2‐ and 3‐dimensional gamma index for a given DTA. Each comparison evaluated the 2‐ and 3‐D average gamma and percent of pixels passing for the following acceptance criteria: ±5%/5mm, 3%/3mm, 2%/2mm, and 1%/1mm using 1 mm slice thicknesses (no dose threshold used). The effect of low‐dose thresholds and slice thickness was also evaluated. Results: The percent of pixels passing for each DTA was better for 3D as compared to the 2D analysis (2D vs 3D): 99.8% vs. 99.9% for 5%/5mm, 99.0% vs. 99.7% for 3%/3mm, 96.4% vs. 98.4% for 2%/2mm, and 79.3% vs. 83.4% for 1%/1mm. Using the low‐dose threshold resulted in worse gamma for both 2D and 3D gamma. However, similar to the no‐threshold results, use of dose threshold resulted in worse agreement for 2D than 3D for all DTA (4.1% decrease compared to 1.7% at 15% low‐dose threshold). No appreciable differences in gamma were observed as a function of slice thickness. Conclusions: Clinical use of 3D gamma analysis requires use of action limits (% of pixel passing and γ values) that are more stringent than 2D for comparable QA results.

The impact of resolution to Gamma pass rate in the verification of dose distribution

Objective To study the impact of the resolution of reference dose distribution and evaluated dose distribution to Gamma rate in the verification of IMRT. Methods Designed four fields, the resolution of dose distribution calculated in water phantom and exported from TPS are 1 ,2,3 ,4,5,6 mm. To calculate Gamma index by IBA's OmniPro-I'mRT software in different sampling resolution. Results When the resolution of evaluated dose distribution was fixed, the change of reference dose distribution's resolution has little effect on Gamma rate (5％ to IMRT field) ;When the resolution of reference dose distribution was fixed , the Gamma rate increased as the evaluated dose distribution's resolution ( ＞ 1 mm) raise ( the Gamma rate increase ( 15. 2 ±6. 2) ％ ( t = 11. 99 ,P < 0. 01 ) and ( 14. 9 ± 5. 5) ％ ( t = 13. 24 , P ＜ 0. 01 ) while the resolution of evaluated dose distribution changed from 6 mm t0 3 mm and from 3 mm to 1 mm respectively) .Conclusions To use Camma method for verification of IMRT, the measured data can be as a reference dose distribution without interpolation;the computed data by TPS can be as a evaluated dose distribution and it is more appropriate for the resolution of 1 mm. Key words: Resolution; Gamma rate; Verification of dose distribution

Image-Based Dynamic Multileaf Collimator Tracking of Moving Targets During Intensity-Modulated Arc Therapy

Intensity-modulated arc therapy (IMAT) enables efficient and highly conformal dose delivery. However, intrafraction motion may compromise the delivered target dose distribution. Dynamic multileaf collimator (DMLC) tracking can potentially mitigate the impact of target motion on the dose. The purpose of this study was to use a single kV imager for DMLC tracking during IMAT and to investigate the ability of this tracking to maintain the dose distribution. A motion phantom carrying a two-dimensional (2D) ion chamber array and buildup material with an embedded gold marker reproduced eight representative tumor trajectories (four lung tumors, four prostate). For each trajectory, a low and high IMAT plan were delivered with and without DMLC tracking. The three-dimensional (3D) real-time target position signal for tracking was provided by fluoroscopic kV images acquired immediately before and during treatment. For each image, the 3D position of the embedded marker was estimated from the imaged 2D position by a probability-based method. The MLC leaves were continuously refitted to the estimated 3D position. For lung, prediction was used to compensate for the tracking latency. The delivered 2D dose distributions were measured with the ion chamber array and compared with a reference dose distribution delivered without target motion using a 3%/3 mm γ-test. For lung tumor motion, tracking reduced the mean γ-failure rate from 38% to 0.7% for low-modulation IMAT plans and from 44% to 2.8% for high-modulation plans. For prostate, the γ-failure rate reduction was from 19% to 0% (low modulation) and from 20% to 2.7% (high modulation). The dominant contributor to the residual γ-failures during tracking was target localization errors for most lung cases and leaf fitting errors for most prostate cases. Image-based tracking for IMAT was demonstrated for the first time. The tracking greatly improved the dose distributions to moving targets.

Modification of the gamma function for the recognition of over- and under-dose regions in three dimensions

In order to evaluate two-dimensional radiation dose distributions, an algorithm called the Gamma function has recently been modified. The current study concentrates on modification of the gamma function as a three-dimensional dose distribution evaluation tool, and includes the recognition of over-dose/under-dose areas. Using a sign term, the conventional gamma function separates the disagreed areas into two parts: over-dose and under-dose areas. The new gamma function was modified using an extension of the dose difference criterion, ΔD, from two dimensions into three dimensions. In order to provide two-dimensional dose maps for analysis, several images were acquired for a range of regular and irregular radiation fields using a Scanning Liquid Ionization Chamber Electronic Portal Imaging Device. The raw images were then converted into two-dimensional transmitted dose maps using an empirical method. They were utilized as reference dose maps. Translational and rotational manipulations were performed on the reference dose distribution maps to provide evaluated dose maps. The reference and evaluated dose maps were then compared using conventional and modified gamma tools. The results indicated that the modified algorithm is able to enhance the over- and under-dose regions. In addition, a slight increase of the agreement percentage for reference and evaluated dose maps were observed by the extension of ΔD to three dimensions. It is concluded that the modified method is more realistic and applicable for the evaluation of both two-dimensional and three-dimensional dose distributions.

Keeping an eye on the ring: COMS plaque loading optimization for improved dose conformity and homogeneity.

PurposeTo improve tumor dose conformity and homogeneity for COMS plaque brachytherapy by investigating the dosimetric effects of varying component source ring radionuclides and source strengths.Material and methodsThe MCNP5 Monte Carlo (MC) radiation transport code was used to simulate plaque heterogeneity-corrected dose distributions for individually-activated source rings of 14, 16 and 18 mm diameter COMS plaques, populated with 103Pd, 125I and 131Cs sources. Ellipsoidal tumors were contoured for each plaque size and MATLAB programming was developed to generate tumor dose distributions for all possible ring weighting and radionuclide permutations for a given plaque size and source strength resolution, assuming a 75 Gy apical prescription dose. These dose distributions were analyzed for conformity and homogeneity and compared to reference dose distributions from uniformly-loaded 125I plaques. The most conformal and homogeneous dose distributions were reproduced within a reference eye environment to assess organ-at-risk (OAR) doses in the Pinnacle3 treatment planning system (TPS). The gamma-index analysis method was used to quantitatively compare MC and TPS-generated dose distributions.ResultsConcentrating > 97% of the total source strength in a single or pair of central 103Pd seeds produced the most conformal dose distributions, with tumor basal doses a factor of 2-3 higher and OAR doses a factor of 2-3 lower than those of corresponding uniformly-loaded 125I plaques. Concentrating 82-86% of the total source strength in peripherally-loaded 131Cs seeds produced the most homogeneous dose distributions, with tumor basal doses 17-25% lower and OAR doses typically 20% higher than those of corresponding uniformly-loaded 125I plaques. Gamma-index analysis found > 99% agreement between MC and TPS dose distributions.ConclusionsA method was developed to select intra-plaque ring radionuclide compositions and source strengths to deliver more conformal and homogeneous tumor dose distributions than uniformly-loaded 125I plaques. This method may support coordinated investigations of an appropriate clinical target for eye plaque brachytherapy.

Electromagnetic Detection and Real-Time DMLC Adaptation to Target Rotation During Radiotherapy

Intrafraction rotation of more than 45° and 25° has been observed for lung and prostate tumors, respectively. Such rotation is not routinely adapted to during current radiotherapy, which may compromise tumor dose coverage. The aim of the study was to investigate the geometric and dosimetric performance of an electromagnetically guided real-time dynamic multileaf collimator (DMLC) tracking system to adapt to intrafractional tumor rotation. Target rotation was provided by changing the treatment couch angle. The target rotation was measured by a research Calypso system integrated with a real-time DMLC tracking system employed on a Varian linac. The geometric beam-target rotational alignment difference was measured using electronic portal images. The dosimetric accuracy was quantified using a two-dimensional ion chamber array. For each beam, the following five delivery modes were tested: 1) nonrotated target (reference); 2) fixed rotated target with tracking; 3) fixed rotated target without tracking; 4) actively rotating target with tracking; and 5) actively rotating target without tracking. Dosimetric performance of the latter four modes was measured and compared to the reference dose distribution using a 3 mm/3% γ-test. Geometrically, the beam-target rotational alignment difference was 0.3° ± 0.6° for fixed rotation and 0.3° ± 1.3° for active rotation. Dosimetrically, the average failure rate for the γ-test for a fixed rotated target was 11% with tracking and 36% without tracking. The average failure rate for an actively rotating target was 9% with tracking and 35% without tracking. For the first time, real-time target rotation has been accurately detected and adapted to during radiation delivery via DMLC tracking. The beam-target rotational alignment difference was mostly within 1°. Dose distributions to fixed and actively rotating targets with DMLC tracking were significantly superior to those without tracking.

TH-C-BRB-02: Gating and Rescanning to Compensate for Organ Motion for Scanned Proton Beam Delivery

Purpose: To evaluate the effect of gating and rescanning on dose distributions for scanned proton beam delivery and achievable irradiation time on a patient specific basis. Methods: We have developed a software tool that simulates scanned proton beam dose delivery to a moving lungtumour by using patient motion and treatment plan data. Based on a 4DCT voxel motion trajectories were calculated along which the dose was accumulated. Using this tool, we investigated rescanning of the ITV for respiration induced organ motion. Furthermore, the effect of gating widow sizes around the exhalation phase (reference phase) as well as gated rescanning was examined. Irradiation time reduction was considered by modeling a high and constant extraction rate of the synchrotron. Results: Rescanning increased the dose homogeneity, however, ten rescans were not sufficient to mitigate interplay effects completely. Gating was found to alleviate local over‐ and under‐dosages. For a gating window of 20%, the minimal dose to 99% of the CTV differed by 6 Gy from the reference dose distribution whereas doses to 1% and 50% differed by less than 1 Gy. For gated rescanning the dose distribution almost reached the reference dose distribution. Interestingly, the difference in the dose distributions for a gating window size of 20% and of 30% was negligible when additional rescanning was applied. However, for a gating window of 20% the treatment time increased by a factor of 3.5 compared to an irradiation without gating. The additional increase of irradiation time due to rescanning (factor 10) could be significantly reduced by the application of an increased extraction rate. Conclusions: Gated rescanning was found to mitigate interplay effects significantly at the cost of increased irradiation time. Based on our study time influencing beam parameters should be subject to an investigation to overcome the problem of elongated irradiation times.

A dose distribution evaluation technique using the k‐d tree for nearest neighbor searching

Purpose:The authors propose an algorithm based on the k‐d tree for nearest neighbor searching to improve the calculation time for 2D and 3D dose distributions.Methods:The calculation method has been widely used for comparisons of dose distributions in clinical treatment plans and quality assurances. By specifying the acceptable dose and distance‐to‐agreement criteria, the method provides quantitative measurement of the agreement between the reference and evaluation dose distributions. The value indicates the acceptability. In regions where , the predefined criterion is satisfied and thus the agreement is acceptable; otherwise, the agreement fails. Although the concept of the method is not complicated and a quick naïve implementation is straightforward, an efficient and robust implementation is not trivial. Recent algorithms based on exhaustive searching within a maximum radius, the geometric Euclidean distance, and the table lookup method have been proposed to improve the computational time for multidimensional dose distributions. Motivated by the fact that the least searching time for finding a nearest neighbor can be an operation with a k‐d tree, where is the total number of the dose points, the authors propose an algorithm based on the k‐d tree for the evaluation in this work.Results:In the experiment, the authors found that the average k‐d tree construction time per reference point is, while the nearest neighbor searching time per evaluation point is proportional to , where is between 2 and 3 for two‐dimensional and three‐dimensional dose distributions, respectively.Conclusions:Comparing with other algorithms such as exhaustive search and sorted list, the k‐d tree algorithm for evaluation is much more efficient.

TU‐E‐204B‐01: First Demonstration of Image‐Based Dynamic MLC Tracking of a Moving Target during Intensity Modulated Arc Therapy

Purpose:Intensity modulated arc therapy (IMAT) enables efficient and highly conformai dose delivery. However, the dose distribution can be compromised by intrafraction target motion. Dynamic MLC (DMLC) tracking can potentially maintain the planned target dose distribution. The purpose of this study was to use a single kV imager for DMLC tracking during IMAT and to investigate the ability of this tracking to maintain the planned dose distribution. Method and Materials:A motion phantom carrying a 2D ion chamber array and build‐up material with an embedded gold marker was programmed to reproduce eight representative tumor trajectories (four prostate, four lung tumors). For each trajectory, a low and high intensity modulated IMAT plan were delivered with and without DMLC tracking, and the resulting 2D dose distributions were measured. The 3D real‐time target position signal for tracking was provided by fluoroscopic kV images acquired immediately before and during treatment. Each kV image was used together with all previous images to estimate the 3D target position and then the MLC leaves were refitted to this estimated target position. For lung, a prediction algorithm was used to compensate for the tracking latency. A 3%/3mm γ‐test was used to quantify the discrepancy between the measured dose distributions and a reference dose distribution delivered without target motion. Results:For the low modulated plans, tracking reduced the mean 3%/3mm γ‐failure rate from 32% to 0.2% for prostate and from 14% to 1% for lung. For the high modulated plans, the γ‐failure rate reduction was from 17% to 6% (prostate) and from 36% to 11% (lung). The finite MLC adaptation speed was a major cause for the residual γ‐failures during tracking. Conclusion:Image‐based tracking with IMAT was demonstrated for the first time. The tracking greatly improved the dose distributions to moving targets. Conflict of Interest: Supported by NTH/NCI R01‐93626 and Varian Medical Systems.

A CT‐based analytical dose calculation method for HDR brachytherapy

This article presents an analytical dose calculation method for high-dose-rate 192Ir brachytherapy, taking into account the effects of inhomogeneities and reduced photon backscatter near the skin. The adequacy of the Task Group 43 (TG-43) two-dimensional formalism for treatment planning is also assessed. The proposed method uses material composition and density data derived from computed tomography images. The primary and scatter dose distributions for each dwell position are calculated first as if the patient is an infinite water phantom. This is done using either TG-43 or a database of Monte Carlo (MC) dose distributions. The latter can be used to account for the effects of shielding in water. Subsequently, corrections for photon attenuation, scatter, and spectral variations along medium- or low-Z inhomogeneities are made according to the radiological paths determined by ray tracing. The scatter dose is then scaled by a correction factor that depends on the distances between the point of interest, the body contour, and the source position. Dose calculations are done for phantoms with tissue and lead inserts, as well as patient plans for head-and-neck, esophagus, and MammoSite balloon breast brachytherapy treatments. Gamma indices are evaluated using a dose-difference criterion of 3% and a distance-to-agreement criterion of 2 mm. PTRAN_CT MC calculations are used as the reference dose distributions. For the phantom with tissue and lead inserts, the percentages of the voxels of interest passing the gamma criteria (Pgamma > or = 1) are 100% for the analytical calculation and 91% for TG-43. For the breast patient plan, TG-43 overestimates the target volume receiving the prescribed dose by 4% and the dose to the hottest 0.1 cm3 of the skin by 9%, whereas the analytical and MC results agree within 0.4%. Pgamma > or = 1 are 100% and 48% for the analytical and TG-43 calculations, respectively. For the head-and-neck and esophagus patient plans, Pgamma > or = 1 are > or = 99% for both calculation methods. A correction-based dose calculation method has been validated for HDR 192Ir brachytherapy. Its high calculation efficiency makes it feasible for use in treatment planning. Because tissue inhomogeneity effects are small and primary dose predominates in the near-source region, TG-43 is adequate for target dose estimation provided shielding and contrast solution are not used.

Imaging of dose distributions using polymer gels based on radiation induced changes in stiffness

Previously, dose determination based on radiation induced stiffness difference measurements has received no or very little attention. Here, a preliminary evaluation of a combined system for dosimetry based on radiation sensitive gels, ultrasonic elastography and a plane strain inverse algorithm is presented. A block of gel was irradiated along one of its axes producing stiff rod-like regions. The dose distribution found with quantitative ultrasound elastography was compared with a reference dose distribution measured with magnetic resonance imaging. In these early results, the high dose areas were clearly detected, while noise in the ultrasound measurement and strong regularisation in the inverse computing introduced shape distortions, noise in the dose estimates and problems estimating the correct dose contrast. Improvements in the experimental setup and inverse computing are possible, for example by acquisition of transversal ultrasound data, which could essentially reduce the noise and restrict direct influence of the experimental boundary condition on the dose estimation by providing additional information for inverse computing. Based on the preliminary results and the potential for improvement it is concluded that further investigations should follow to establish the potential of the rapidly developing field of elastography for measuring radiation dose based on radiation induced changes in stiffness.

Efficient gamma index calculation using fast Euclidean distance transform

The gamma index is a tool for dose distribution comparison. It combines both dose difference (DD) and distance to agreement (DTA) into a single quantity. Though it is an effective measure, making up for the inadequacy of DD or DTA alone, its calculation can be very time-consuming. For a k-D space with N quantization levels in each dimension, the complexity of the exhaustive search is O(N2k). In this work, we proposed an efficient method that reduces the complexity from O(N2k) to O(NkM), where M is the number of discretized dose values and is comparable to N. More precisely, by embedding the reference dose distribution in a (k+1)-D spatial-dose space, we can use fast Euclidean distance transform with linear complexity to obtain a table of gamma indices evaluated over a range of the (k+1)-D spatial-dose space. Then, to obtain gamma indices for the test dose distribution, it requires only table lookup with complexity O(Nk). Such a table can also be used for other test dose distributions as long as the reference dose distribution is the same. Simulations demonstrated the efficiency of our proposed method. The speedup for 3D gamma index calculation is expected to be on the order of tens of thousands (from O(N6) to O(N3M)) if N is a few hundreds, which makes clinical usage of the 3D gamma index feasible. A byproduct of the gamma index table is that the gradient of the gamma index with respect to either the spatial or dose dimension can be easily derived. The gradient can be used to identify the main causes of the discrepancy from the reference distribution at any dose point in the test distribution or incorporated in treatment planning and machine parameter optimization.

SU‐EE‐A3‐04: On‐Line CT‐Guided Adaptive Re‐Planning Based On Deformed Original Dose Distributions

Purpose: Daily image‐guided setup based on soft tissue target may improve target coverage. However, when significant anatomical changes occur, a simple isocenter shift may not be adequate. In this study, we propose an online IMRT replanning strategy for prostate cancer which uses the deformed dose distributions from the original treatment plan as its objective. Method and Materials: The replanning procedure used was as follows: (1) the dose distribution on the planning CT was deformed to the daily CT and used as the reference objective dose distribution for IMRT replanning; (2) the prescription isodose line on the reference dose distribution was auto‐segmented and used as the fictitious “target volume” to set the initial MLC leaf positions; (3) we developed and implemented a voxel‐by‐voxel dose‐based cost function. The IMRT treatment plan was optimized using the direct machine parameter optimization algorithm to achieve the following goals: (a) inside the region enclosed by the original prescription dose line, the replanned dose distribution was optimized to match with the reference objective; (b) outside this region, the objective function was chosen to lower the dose value and to penalize the dose value exceeding the reference dose for each voxel. The replanning process does not need re‐auto‐segmentation of patient's anatomy, although re‐segmented anatomic contours were used to evaluate the effectiveness of this approach. Results: We compared the dose distributions and the DVHs of the original plan and the daily plans using (1) image‐guided setup based on prostate alignment, (2) deformed dose distribution from the original plan, and (3) our re‐planning method. We found that our re‐planning strategy matched well with the original plan. Conclusion: The replanning strategy using the original dose distribution as the goal for optimization produces dose distributions similar to the original approved plan and is an effective approach for on‐line CT‐guided adaptive radiotherapy.

The impact of different dose–response parameters on biologically optimized IMRT in breast cancer

The full potential of biologically optimized radiation therapy can only be maximized with the prediction of individual patient radiosensitivity prior to treatment. Unfortunately, the available biological parameters, derived from clinical trials, reflect an average radiosensitivity of the examined populations. In the present study, a breast cancer patient of stage I–II with positive lymph nodes was chosen in order to analyse the effect of the variation of individual radiosensitivity on the optimal dose distribution. Thus, deviations from the average biological parameters, describing tumour, heart and lung response, were introduced covering the range of patient radiosensitivity reported in the literature. Two treatment configurations of three and seven biologically optimized intensity-modulated beams were employed. The different dose distributions were analysed using biological and physical parameters such as the complication-free tumour control probability (P+), the biologically effective uniform dose (), dose volume histograms, mean doses, standard deviations, maximum and minimum doses. In the three-beam plan, the difference in P+ between the optimal dose distribution (when the individual patient radiosensitivity is known) and the reference dose distribution, which is optimal for the average patient biology, ranges up to 13.9% when varying the radiosensitivity of the target volume, up to 0.9% when varying the radiosensitivity of the heart and up to 1.3% when varying the radiosensitivity of the lung. Similarly, in the seven-beam plan, the differences in P+ are up to 13.1% for the target, up to 1.6% for the heart and up to 0.9% for the left lung. When the radiosensitivity of the most important tissues in breast cancer radiation therapy was simultaneously changed, the maximum gain in outcome was as high as 7.7%. The impact of the dose–response uncertainties on the treatment outcome was clinically insignificant for the majority of the simulated patients. However, the jump from generalized to individualized radiation therapy may significantly increase the therapeutic window for patients with extreme radio sensitivity or radioresistance, provided that these are identified. Even for radiosensitive patients a simple treatment technique is sufficient to maximize the outcome, since no significant benefits were obtained with a more complex technique using seven intensity-modulated beams portals.

MO‐E‐AUD‐06: Ultra‐Fast Gamma Index Calculation for Quality Assurance and Optimization in Radiotherapy

Purpose It is clinically essential in IMRT to compare two dose distributions for dose quality assurance (DQA). The gamma index (Low et al, 1998), which combines both dose difference and distance to agreement, provides a quantitative measure of acceptability in DQA. However, its calculations can be time‐consuming and limit its applications to 2‐dimensional dose distributions. In this work, we propose an efficient calculation method. Method By embedding the k‐dimensional reference dose distribution in the (k+1)‐dimensional spatial‐dose space, we then use the Euclidean distance transform to find the distance to the reference dose distribution, regarded as a feature set, for every point in a range of the spatial‐dose space. This leads to a table of gamma indices. And the evaluation of the gamma indices for any dose distribution with respect to the reference dose distribution is simply table‐lookup. Our implementation uses a fast Euclidean distance transform, which was developed in Maurer et al, 2003 and proved to have only linear complexity. Results Using simulated 2‐D dose distributions of size 400×400, the pre‐calculation of the Gamma index table takes 26 sec and the table lookup to evaluate the Gamma index for each test dose distribution takes less than 0.1 sec in a 3GHz PC. On the other hand, it takes about 2400 sec using the exhaustive search on the same PC to evaluate the Gamma index for each test distribution. The speedup for 3D Gamma index calculation is expected to be 104∼105. Conclusion Numerical simulations demonstrate the efficiency of our proposed method. Thus, the clinical usage of 3D Gamma index becomes feasible. In addition, the Gamma index table can be used to determine the derivative of Gamma index over the dose distribution, which facilitates the inclusion of Gamma index in treatment planning and/or machine parameters optimization.

SU‐FF‐T‐239: Gamma‐Test Equivalent Error Margins for Dosimetry Analysis

Purpose: The γ‐test evaluates the difference between two dose distributions in dose‐spatial domain. Previous methods employing the γ‐test at a point to translate spatial variation to acceptable dose difference involve a test distribution and a reference dose. This work developed a method for dose comparison using pre‐calculated acceptable error margins based on one dose distribution. Method and Materials: The expected uncertainty for a reference dose distribution is predetermined without making relevance to another distribution. The error margin at a point is calculated using the γ‐index formula over a sphere of a radius being the maximum distance‐to‐agreement (MDAT). All dose values within the sphere, evaluated using a set of evenly distributed points, are acceptable, whereas appropriate dose margins, up to a maximum dose difference (MDD), are included. Comparison with another distribution is to check against the upper and lower bound of the error margins separately, so γ‐test equivalent failure can be discerned to hot and cold regions. The degree of failures can be analyzed quantitatively for determining how an agreement between the two distributions can be improved globally. For an application, we calculated the error margin of dose measurement for IMRT QA using the distribution of volume‐averaged chamber response. Results: The error margin for IMRT phantom measurement using an IC‐10 chamber was about ±4% for MDD=3% and MDAT=3 mm in a flat region. Asymmetric error margins were found in gradient regions. Expected range for the output measurement with a 1cm×1cm field was (−18.6%, 2.5%) for MDD=2%, MDAT=2 mm, and a measurement was −13.3% off. Conclusion: Using predetermined error margins for a reference distribution is equivalent to the γ‐test in dose comparison. The error margins are not skewed by another distribution and interpretable as expected uncertainty for statistical analysis. The expected values for a reproduced distribution can be different from the reference.

SU-FF-T-217: Evaluation of the Dosimetric Accuracy of a Commercial Adaptive Radiotherapy Process

Purpose: To evaluate the dosimetric accuracy and reproducibility of the TomoTherapy Planned Adaptive system using MVCT datasets. Method and Materials: Comparisons were made between reference dose distributions computed with the TomoTherapy treatment planningsystem (TPS) and verification dose distributions computed on the TomoTherapy Planned Adaptive (PA) system. Both calculations were performed on TomoTherapy megavoltage CT (MVCT) datasets to eliminate differences associated with variations in CT‐density tables. Simulated PTVs drawn on an MVCT of an anthropomorphic radiosurgery head phantom (CIRS, Inc.) were used as input to calculate doses on the TomoTherapy TPS. After plan optimization, a post‐plan MVCT image was taken and used to calculate dose on the TomoTherapy PA system. Initially, calculations were made using the same MVCT dataset as input to both programs to investigate the agreement between the algorithms. Next, calculations were made using registered pre‐ and post‐plan MVCT images to investigate the variation with MVCT datasets. Comparisons were made using the tools available on the PA system and in‐house software to compare doses outside of contoured structures. Results: For calculations on identical datasets, isodose and DVH comparisons between the TomoTherapy TPS and PA systems showed insignificant dose differences (< 0.2%) to all contoured structures. Dose discrepancies within the phantom but outside of contoured structures showed slightly larger variations, although well within 0.5%. Similar results were found for dose calculations using different MVCT datasets. In both cases, the doses computed in air outside the phantom showed the largest differences (up to 21%). Conclusion: Comparisons between TomoTherapy's TPS and PA system MVCT dose calculations showed clinically acceptable agreement everywhere within the phantom. Differences between doses calculated in air are due to differences in the way the algorithms mask low density voxels. Research sponsored by TomoTherapy, Inc.