Volume 39, Issue 12, December 2012
Index of content:
Many methods have been proposed for tumor segmentation from positron emission tomographyimages. Because of the increasingly important role that [11C]choline is playing in oncology and because no study has compared segmentation methods on this tracer, the authors assessed several segmentation algorithms on a [11C]choline test-retest dataset.Methods:
Fixed and adaptive threshold-based methods, fuzzy C-means (FCM), Canny's edge detection method, the watershed transform, and the fuzzy locally adaptive Bayesian algorithm (FLAB) were used. Test-retest [11C]choline scans of nine patients with breast cancer were considered and the percent test-retest variability %VARTEST-RETEST of tumor volume (TV) was employed to assess the results. The same methods were then applied to two denoised datasets generated by applying either a Gaussian filter or the wavelet transform.Results:
The (semi)automated methods FCM, FLAB, and Canny emerged as the best ones in terms of TV reproducibility. For these methods, the %root mean square error %RMSE of %VARTEST-RETEST, defined as , was in the range 10%–21.2%, depending on the dataset and algorithm. Threshold-based methods gave TV estimates which were extremely variable, particularly on the unsmoothed data; their performance improved on the denoised datasets, whereas smoothing did not have a remarkable impact on the (semi)automated methods. TV variability was comparable to that of SUVMAX and SUVMEAN (range 14.7%–21.9% for %RMSE of %VARTEST-RETEST, after the exclusion of one outlier, 40%–43% when the outlier was included).Conclusions:
The TV variability obtained with the best methods was similar to the one reported for TV in previous [18F]FDG and [18F]FLT studies and to the one of SUVMAX/SUVMEAN on the authors’ [11C]choline dataset. The good reproducibility of [11C]choline TV warrants further studies to test whether TV could predict early response to treatment and survival, as for [18F]FDG, to complement/substitute the use of SUVMAX and SUVMEAN.
Physicists who are responsible for high-tech radiotherapy procedures should have to be specially credentialed39(2012); http://dx.doi.org/10.1118/1.4748333View Description Hide Description
- RADIATION THERAPY PHYSICS
39(2012); http://dx.doi.org/10.1118/1.4764482View Description Hide DescriptionPurpose:
To develop a real time dose monitoring and dose reconstruction tool to identify and quantify sources of errors during patient specific volumetric modulated arc therapy (VMAT) delivery and quality assurance.Methods:
The authors develop a VMAT delivery monitor tool called linac data monitor that connects to the linac in clinical mode and records, displays, and compares real time machine parameters with the planned parameters. A new measure, called integral error, keeps a running total of leaf overshoot and undershoot errors in each leaf pair, multiplied by leaf width, and the amount of time during which the error exists in monitor unit delivery. Another tool reconstructs Pinnacle3™ format delivered plan based on the saved machine logfile and recalculates actual delivereddose in patient anatomy.Delivery characteristics of various standard fractionation and stereotactic body radiation therapy(SBRT) VMAT plans delivered on Elekta Axesse and Synergy linacs were quantified.Results:
The MLC and gantry errors for all the treatment sites were 0.00 ± 0.59 mm and 0.05 ± 0.31°, indicating a good MLC gain calibration. Standard fractionation plans had a larger gantry error than SBRT plans due to frequent dose rate changes. On average, the MLC errors were negligible but larger errors of up to 6 mm and 2.5° were seen when dose rate varied frequently. Large gantry errors occurred during the acceleration and deceleration process, and correlated well with MLC errors (r = 0.858, p = 0.0004). PTV mean, minimum, and maximum dose discrepancies were 0.87 ± 0.21%, 0.99 ± 0.59%, and 1.18 ± 0.52%, respectively. The organs at risk (OAR) doses were within 2.5%, except some OARs that showed up to 5.6% discrepancy in maximum dose. Real time displayed normalized total positive integral error (normalized to the total monitor units) correlated linearly with MLC (r = 0.9279, p < 0.001) and gantry errors (r = 0.742, p = 0.005). There is a strong correlation between total integral error and PTV mean (r = 0.683, p = 0.015), minimum (r = 0.6147, p = 0.033), and maximum dose (r = 0.6038, p = 0.0376).Conclusions:
Errors may exist during complex VMAT planning and delivery.Linac data monitor is capable of detecting and quantifying mechanical and dosimetric errors at various stages of planning and delivery.
39(2012); http://dx.doi.org/10.1118/1.4764483View Description Hide DescriptionPurpose:
The authors present a stochastic framework for radiotherapy patient positioning directly utilizing radiographic projections. This framework is developed to be robust against anatomical nonrigid deformations and to cope with challenging imaging scenarios, involving only a few cone beam CT projections from short arcs.Methods:
Specifically, a Bayesian estimator (BE) is explicitly derived for the given scanning geometry. This estimator is compared to reference methods such as chamfer matching (CM) and the minimization of the median absolute error adapted as tools of robust image processing and statistics. In order to show the performance of the stochastic short-arc patient positioning method, a CIRS IMRT thorax phantom study is presented with movable markers and the utilization of an Elekta Synergy® XVI system. Furthermore, a clinical prostate CBCT scan of a Varian® On-Board Imager® system is utilized to investigate the robustness of the method for large variations of image quality (anterior-posterior vs lateral views).Results:
The results show that the BE shifts reduce the initial setup error of up to 3 cm down to 3 mm at maximum for an imaging arc as short as 10° while CM achieves residual errors of 7 mm at maximum only for arcs longer than 40°. Furthermore, the BE can compensate robustly for low image qualities using several low quality projections simultaneously.Conclusions:
In conclusion, an estimation method for marker-based patient positioning for short imaging arcs is presented and shown to be robust and accurate for deformable anatomies.
39(2012); http://dx.doi.org/10.1118/1.4764486View Description Hide DescriptionPurpose:
Both temporal and thermal dependencies of the dose response have been observed in radiochromic dosimeters. As these dependencies may be influenced by the dose level, the present study investigates the temperature dependence during irradiation and the temporal change of the optical response following irradiation of radiochromic dosimeters at a range of doses.Methods:
Cuvette samples of the PRESAGE™ radiochromic dosimeter were irradiated within a dose range of 0–10 Gy at irradiation temperatures within 5–35 °C and postirradiation storage within 6–30 °C. The optical response due to irradiation was measured using a standard spectrophotometer and the data were analyzed in terms of thermal and temporal change.Results:
The initial dose response was linear over the applied dose range independent of irradiation temperature. However, the optical response to a specific dose increased exponentially with irradiation temperature corresponding to an activation energy of 0.114 ± 0.007 eV. The temporal change in dose response after irradiation consisted of an offset, an auto-oxidation rate with activation energy 0.84 ± 0.03 eV, and an initial exponential increase in optical response (1.6 ± 0.2 eV) followed by an exponential decrease in optical response (0.98 ± 0.08 eV). These contributions depended on both storage temperature and the dose given, leading to a nonlinear dose response with time at low storage temperatures and a high auto-oxidation rate at high storage temperatures.Conclusions:
Thermal equilibration is important to the radiochromic dosimeter investigated due to an exponential change in dose response with irradiation temperature and a considerable postirradiation temporal change in response. For the dosimeter version investigated in this study, a compromise in storage temperature has to be made between increasing the nonlinearity of the dose response with time and inducing a high auto-oxidation rate.
39(2012); http://dx.doi.org/10.1118/1.4765049View Description Hide DescriptionPurpose:
Secondary particles produced in the collision of protons with beam modifiers are of concern in proton therapy. Nevertheless, secondary radiation can provide information on the dosimetric parameters through its dependency on the modulating accessories (range shifter and range modulating wheel). Relatively little data have been reported in the literature for low-energy proton beams. The present study aims at characterizing the neutron and photon secondary radiation at the low-energy proton therapy facility of the Centre Antoine Lacassagne (CAL), and studying their correlation to the dosimetric parameters to explore possible practical uses of secondary radiation in the treatment quality for proton therapy.Methods:
The Monte Carlo code MCNPX was used to simulate the proton therapy facility at CAL. Neutron and photon fluence, Φ, and ambient dose equivalent per protondose, H*(10)/D, were determined across the horizontal main plane spanning the whole treatment room. H*(10)/D was also calculated at two positions of the treatment room where dosimetric measurements were performed for validation of the Monte Carlo calculations. Calculations and measurements were extended to 100 clinical spread-out Bragg Peaks (SOBPs) covering the whole range of therapeutic dose rates (D/MU) employed at CAL. In addition, the values of D and MU were also calculated for each SOBP and the results analyzed to study the relationship between secondary radiation and dosimetric parameters.Results:
The largest production of the secondary particles takes place at the modulating devices and the brasscollimators located along the optical bench. Along the beam line and off the beam axis to 2.5 m away, H*(10)/D values ranged from 5.4μSv/Gy to 5.3 mSv/Gy for neutrons, and were 1 order of magnitude lower for photons. H*(10)/D varied greatly with the distance and angle to the beam axis. A variation of a factor of 5 was found for the different range of modulations (SOBPs). The ratios between calculations and measurements were 2.3 and 0.5 for neutrons and photons, respectively, and remained constant for all the range of SOBPs studied, which provided validation for the Monte Carlo calculations. H*(10)/D values were found to correlate to the protondose rate D/MU with a power fit, both for neutrons and photons. This result was exploited to implement a system to obtain D/MU values from the measurement of the integrated photon ambient dose equivalent H*(10) during treatment, which provides a method to control the dosimetric parameters D/MU and D.Conclusions:
The treatment room at CAL is moderately polluted by secondary particles. The constant ratio between measurements and calculations for all SOBPs showed that simulations correctly predict the dosimetric parameters and the dependence of the production of secondary particles on the modulation. The correlation between H*(10)/D and D/MU is a useful tool for quality control and is currently used at CAL. This system works as an indirectin vivodosimetry method, which is so far not feasible in proton therapy. This tool requires very simple instrumentation and can be implemented from the measurement of either photons or neutrons.
Organ sample generator for expected treatment dose construction and adaptive inverse planning optimization39(2012); http://dx.doi.org/10.1118/1.4765457View Description Hide DescriptionPurpose:
To create an organ sample generator (OSG) for expected treatment dose construction and adaptive inverse planning optimization. The OSG generates random samples of organs of interest from a distribution obeying the patient specific organ variation probability density function (PDF) during the course of adaptive radiotherapy.Methods:
Principle component analysis (PCA) and a time-varying least-squares regression (LSR) method were used on patient specific geometric variations of organs of interest manifested on multiple daily volumetric images obtained during the treatment course. The construction of the OSG includes the determination of eigenvectors of the organ variation using PCA, and the determination of the corresponding coefficients using time-varying LSR. The coefficients can be either random variables or random functions of the elapsed treatment days depending on the characteristics of organ variation as a stationary or a nonstationary random process. The LSR method with time-varying weighting parameters was applied to the precollected daily volumetric images to determine the function form of the coefficients. Eleven h&n cancer patients with 30 daily cone beam CTimages each were included in the evaluation of the OSG. The evaluation was performed using a total of 18 organs of interest, including 15 organs at risk and 3 targets.Results:
Geometric variations of organs of interest during h&n cancerradiotherapy can be represented using the first 3 ∼ 4 eigenvectors. These eigenvectors were variable during treatment, and need to be updated using new daily images obtained during the treatment course. The OSG generates random samples of organs of interest from the estimated organ variation PDF of the individual. The accuracy of the estimated PDF can be improved recursively using extra daily image feedback during the treatment course. The average deviations in the estimation of the mean and standard deviation of the organ variation PDF for h&n cancerradiotherapy were less than 2 and 1 mm, respectively, for most organs after the second week of treatment. After the first three weeks of treatment, the mean discrepancy of the dose estimation accuracy was within 1% for most of organs, the corresponding standard deviation was within 2.5% for parotids, the brain stem and the cochleae, and within 1% for other organs.Conclusions:
A patient specific OSG is feasible and can be used to generate random samples of organs of interest for the expected treatment dose construction and adaptive inverse planning. The accuracy of the OSG can be improved continuously and recursively during the adaptive treatment course using daily volumetric image feedback.
39(2012); http://dx.doi.org/10.1118/1.4766434View Description Hide DescriptionPurpose:
The purpose of this work was to investigate the relationship between dynamically accumulated dose (dynamic dose) and 4D accumulated dose (4D dose) for irradiation of moving tumors, and to quantify the dose uncertainty induced by tumor motion.Methods:
The authors established that regardless of treatment modality and delivery properties, the dynamic dose will converge to the 4D dose, instead of the 3D static dose, after multiple deliveries. The bounds of dynamic dose, or the maximum estimation error using 4D or static dose, were established for the 4D and static doses, respectively. Numerical simulations were performed (1) to prove the principle that for each phase, after multiple deliveries, the average number of deliveries for any given time converges to the total number of fractions (K) over the number of phases (N); (2) to investigate the dose difference between the 4D and dynamic doses as a function of the number of deliveries for deliveries of a “pulsed beam”; and (3) to investigate the dose difference between 4D dose and dynamic doses as a function of delivery time for deliveries of a “continuous beam.” A Poissonmodel was developed to estimate the mean dose error as a function of number of deliveries or delivered time for both pulsed beam and continuous beam.Results:
The numerical simulations confirmed that the number of deliveries for each phase converges toK/N, assuming a random starting phase. Simulations for the pulsed beam and continuous beam also suggested that the dose error is a strong function of the number of deliveries and/or total deliver time and could be a function of the breathing cycle, depending on the mode of delivery. The Poissonmodel agrees well with the simulation.Conclusions:
Dynamically accumulated dose will converge to the 4D accumulated dose after multiple deliveries, regardless of treatment modality. Bounds of the dynamic dose could be determined using quantities derived from 4D doses, and the mean dose difference between the dynamic dose and 4D dose as a function of number of deliveries and/or total deliver time was also established.
39(2012); http://dx.doi.org/10.1118/1.4766875View Description Hide DescriptionPurpose:
In this work, the authors propose a novel registration strategy for translation-only correction scenarios of lung stereotactic body radiation therapy setups, which can achieve optimal dose coverage for tumors as well as preserve the consistency of registrations with minimal human interference.Methods:
The proposed solution (centroid-to-centroidor CTC solution) uses the average four-dimensional CT (A4DCT) as the reference CT. The cone-beam CT(CBCT) is deformed to acquire a new centroid for the internal target volume (ITV) on the CBCT. The registration is then accomplished by simply aligning the centroids of the ITVs between the A4DCT and the CBCT. Sixty-seven cases using 64 patients (each case is associated with separate isocenters) have been investigated with the CTC method and compared with the conventional gray-value (G) mode and bone (B) mode registration methods. Dosimetric effects among the tree methods were demonstrated by 18 selected cases. The uncertainty of the CTC method has also been studied.Results:
The registration results demonstrate the superiority of the CTC method over the other two methods. The differences in the D99 and D95 ITV dose coverage between the CTC method and the original plan is small (within 5%) for all of the selected cases except for one for which the tumor presented significant growth during the period between the CT scan and the treatment. Meanwhile, the dose coverage differences between the original plan and the registration results using either the B or G method are significant, as tumor positions varied dramatically, relative to the rib cage, from their positions on the original CT. The largest differences between the D99 and D95 dose coverage of the ITV using the B or G method versus the original plan are as high as 50%. The D20 differences between any of the methods versus the original plan are all less than 2%.Conclusions:
The CTC method can generate optimal dose coverage to tumors with much better consistency compared with either the G or B method, and it is especially useful when the tumor position varies greatly from its position on the original CT, relative to the rib cage.
A method for registration of single photon emission computed tomography (SPECT) and computed tomography (CT) images for liver stereotactic radiotherapy (SRT)39(2012); http://dx.doi.org/10.1118/1.4766877View Description Hide DescriptionPurpose:
To describe a simple method of coregistration of nonanatomic liverSPECT and CTimages acquired in separate sessions for three-dimensional (3D)-CRT planning utilizing dual radiolabeled and radiopaque body surface markers, and evaluate the accuracy of the registration on the patient surface.Methods:
Ten patients treated for liver metastases or hepatocellular carcinoma with stereotactic body radiation therapy or 3D-CRT were selected for this study to evaluate the SPECT/CT registration process. All patients were positioned in a custom-molded vacuum bag on the flat table top. Nine radiopaque markers were taped to the abdominal surface in three axial planes at the level of the liver. Following CTimaging, the nine radiopaque markers were then labeled with radioactive tags, each containing 10μCi of 99mTc, and SPECTimages were acquired. The metric used to evaluate the registration was the fiducial registration error (FRE), defined as the root mean square of the distance between pairs of homologous markers on the CT and SPECTimages. The evaluation of the registration accuracy was performed in two steps: first the minimum number of markers necessary to obtain a robust registration was optimized; second the FRE was calculated on the remaining set of unused markers. Additionally, the deformation of the patient's abdominal surface between CT and SPECT acquisition sessions was evaluated using the distances between all possible unused marker pairs on the CT and SPECTimages separately. The root mean square of the CT-to-SPECT difference between those distances was used to define the deformation index (DI). The registration method was evaluated on all ten patients in addition to an anthropomorphic phantom study.Results:
The minimum number of markers above which the registration was not improved by more than 1 mm was 4. The FRE, calculated over the 5 remaining markers, was 6.1 mm for the patient population and 1.8 mm for the phantom study. The DI was 5.0 mm on average over all 10 patients and correlated well with the FRE. The DI was 1.6 mm for the phantom study, which represented the imaging systems’ resolution and the ability to place the CT and SPECT markers at the exact same location.Conclusions:
It is feasible to use radiolabeled and radiopaque dual body surface markers for registration of SPECT and CTimages acquired in separate sessions allowing conformal avoidance of SPECT-defined functional normal liver. Point-based rigid registration accuracy on the patient surface of 6.1 mm can be achieved using 4 dual body surface markers. The main contribution to the registration error is the deformation of the abdominal surface, arising from the inability to setup the patient in the exact same position at different times on two different imaging systems, and to properly account for breathing artifacts on the CT and SPECTimages.
39(2012); http://dx.doi.org/10.1118/1.4768159View Description Hide DescriptionPurpose:
To perform a methodological comparison of volumetric modulated arc therapy (VMAT)-like and tomotherapy-like techniques for a prostate geometry, exploring the dependence on machine, delivery, and optimization parameters of cost function values optimized for each technique.Methods:
A gradient-descent algorithm is used to optimize tomotherapy-like treatments, while VMAT-like optimization is carried out using a direct-aperture simulated annealing algorithm with 180 control points equispaced at 2° angles. Dose distributions are linked to fluences via a three-dimensional double-gaussian pencil beam model. Plans are optimized for a prostate geometry, outlined according to the CHHiP protocol. The cost function used for optimization contains ten simple functions, each of which describes a single planning objective. These functions are split into three structure groups according to whether they are used to control PTV, rectal or bladder dose levels. Different optimizations have been performed by varying the relative weights of each of these structure groups, exploring in this way a three-dimensional Pareto front. Plan quality is studied according to the value of the optimized cost function and the relative Euclidean distance between the components of the cost function and those of the nearest plan lying on a reference Pareto front obtained for tomotherapy-like plans generated using a 1 cm fan-beam width and 1/3 pitch.Results:
The quality of tomotherapy-like optimization depends on the fan-beam width,s, and rotation pitch, p, used to deliver the treatment. These values together define the effective longitudinal resolution with which fluence can be modulated, and lower cost function values are obtained for treatments optimized with tighter pitches and narrower fan-beam widths (higher modulation resolution). On the other hand, the cost function values of VMAT-like optimizations depends on the optimization running time, leaf displacement constraints, and number of arcs employed, as well as on the size of the beamlets used in the optimization (a change in leaf width from 5 to 10 mm clearly worsens the value of the objective function, but only a marginal improvement is observed when the leaf movement discretization step is reduced from 5 to 5/3 mm). However, for no combination of these parameter values did VMAT-like optimizations match the cost function values of optimized tomo-like plans obtained for s = 1 cm and p = 1/3 (or 1/2). This is the case all across the Pareto front. On the other hand, cost function values of VMAT-like plans are generally lower than those of optimized tomotherapy-like plans obtained for s = 2.5 cm.Conclusions:
Tomotherapy-like plans created for the prostate geometry using a 1 cm fan-beam width and pitches of 1/3 or 1/2 have lower cost function values than VMAT-like plans, although the associated dosimetric improvements are quite small, both techniques generating very good dose distributions. When a 2.5 cm wide fan-beam is used for tomotherapy-like treatments the pattern is reversed, the tomotherapy-like plans having higher cost functions than the VMAT-like ones.
39(2012); http://dx.doi.org/10.1118/1.4761864View Description Hide DescriptionPurpose:
The objective of this work was to develop a quality control (QC) tool to reduce intensity modulated radiotherapy(IMRT) planning variability and improve treatment plan quality using mathematical models that predict achievable organ-at-risk (OAR) dose-volume histograms (DVHs) based on individual patient anatomy.Methods:
A mathematical framework to predict achievable OAR DVHs was derived based on the correlation of expected dose to the minimum distance from a voxel to the PTV surface. OAR voxels sharing a range of minimum distances were computed as subvolumes. A three-parameter, skew-normal probability distribution was used to fit subvolume dose distributions, and DVH prediction models were developed by fitting the evolution of the skew-normal parameters as a function of distance with polynomials. Cohorts of 20 prostate and 24 head-and-neck IMRT plans with identical clinical objectives were used to train organ-specificaveragemodels for rectum, bladder, and parotids. A sum of residuals analysis quantifying the integrated difference between the clinically approved DVH and predicted DVH evaluated similarity between DVHs. The ability of the averagemodels to prospectively predict DVHs was evaluated on an independent validation cohort of 20 prostate plans. Statistical comparison of the sums of residuals between training and validation cohorts quantified the accuracy of the averagemodel. Restricted sums of residuals (RSR) were used to identify potential outliers, where large values of RSR indicate a clinical DVH that exceeds the predicted DVH by a considerable amount. A refinedmodel was obtained for each organ by excluding outliers with large RSR values from the training cohort. The refinedmodel was applied to the original training cohort and restricted sums of residuals were utilized to estimate potential DVH improvements. All cases were replanned and evaluated by the physician that approved the original plan. The ability of the refinedmodels to correctly identify outliers was assessed using the residual sum between the original and replanned DVHs to quantify dosimetric gains realized under replanning.Results:
Statistical analysis of average sum of residuals for rectum (), bladder (), and parotid () training cohorts yielded mean values near zero and small with respect to the standard deviations, indicating that the averagemodels are capturing the essential behavior of the training cohorts. The predictive abilities of the average rectum and bladder models were statistically indistinguishable between the training and validation sets, with and for the validation set. The refined models’ ability to detect outliers and predict achievable OAR DVHs was demonstrated by a strong correlation between predicted gains (RSR) and realized gains after replanning with sample correlation coefficients of r = 0.92 for the rectum, r = 0.88 for the bladder, and r = 0.84 for the parotid glands.Conclusions:
The results demonstrate that our mathematical framework and modest training cohorts successfully predict achievable OAR DVHs based on individual patient anatomy. The models correctly identified suboptimal plans that demonstrated further OAR sparing after replanning. This modeling technique requires no manual intervention except for appropriate selection of a training set with identical evaluation criteria. Clinical implementation is in progress to evaluate impact on real-time IMRT QC.
Small field segments surrounded by large areas only shielded by a multileaf collimator: Comparison of experiments and dose calculation39(2012); http://dx.doi.org/10.1118/1.4762564View Description Hide DescriptionPurpose:
Complex radiotherapy fields delivered using a tertiary multileaf collimator(MLC) often feature small open segments surrounded by large areas of the beam only shielded by the MLC. The aim of this study was to test the ability of two modern dose calculation algorithms to accurately calculate the dose in these fields which would be common, for example, in volumetric modulated arc treatment (VMAT) and study the impact of variations in dosimetric leaf gap (DLG), focal spot size, and MLC transmission in the beam models.Methods:
Nine test fields with small fields (0.6–3 cm side length) surrounded by large MLC shielded areas (secondary collimator 12 × 12 cm2) were created using a 6 MV beam from a Varian Clinac iX linear accelerator with 120 leaf MLC. Measurements of output factors and profiles were performed using a diamond detector (PTW) and compared to two dose calculations algorithms anisotropic analytical algorithm [(AAA) and Acuros XB] implemented on a commercial radiotherapytreatment planning system (Varian Eclipse 10).Results:
Both calculation algorithms predicted output factors within 1% for field sizes larger than 1 × 1 cm2. For smaller fields AAA tended to underestimate the dose. Profiles were predicted well for all fields except for problems of Acuros XB to model the secondary penumbra between MLC shielded fields and the secondary collimator. A focal spot size of 1 mm or less, DLG 1.4 mm and MLC transmission of 1.4% provided a generally good model for our experimental setup.Conclusions:
AAA and Acuros XB were found to predict the dose under small MLC defined field segments well. While DLG and focal spot affect mostly the penumbra, the choice of correct MLC transmission will be essential to model treatments such as VMAT accurately.
Clinical evaluation of a commercial orthopedic metal artifact reduction tool for CT simulations in radiation therapy39(2012); http://dx.doi.org/10.1118/1.4762814View Description Hide DescriptionPurpose:
Severe artifacts in kilovoltage-CT simulation images caused by large metallic implants can significantly degrade the conspicuity and apparent CT Hounsfield number of targets and anatomic structures, jeopardize the confidence of anatomical segmentation, and introduce inaccuracies into the radiation therapy treatment planning process. This study evaluated the performance of the first commercial orthopedic metal artifact reduction function (O-MAR) for radiation therapy, and investigated its clinical applications in treatment planning.Methods:
Both phantom and clinical data were used for the evaluation. The CIRS electron density phantom with known physical (and electron) density plugs and removable titanium implants was scanned on a Philips Brilliance Big Bore 16-slice CT simulator. The CT Hounsfield numbers of density plugs on both uncorrected and O-MAR corrected images were compared. Treatment planning accuracy was evaluated by comparing simulated dose distributions computed using the true density images, uncorrected images, and O-MAR corrected images. Ten CTimage sets of patients with large hip implants were processed with the O-MAR function and evaluated by two radiation oncologists using a five-point score for overall image quality, anatomical conspicuity, and CT Hounsfield number accuracy. By utilizing the same structure contours delineated from the O-MAR corrected images, clinical IMRT treatment plans for five patients were computed on the uncorrected and O-MAR corrected images, respectively, and compared.Results:
Results of the phantom study indicated that CT Hounsfield number accuracy and noise were improved on the O-MAR corrected images, especially for images with bilateral metal implants. Theγ pass rates of the simulated dose distributions computed on the uncorrected and O-MAR corrected images referenced to those of the true densities were higher than 99.9% (even when using 1% and 3 mm distance-to-agreement criterion), suggesting that dose distributions were clinically identical. In all patient cases, radiation oncologists rated O-MAR corrected images as higher quality. Formerly obscured critical structures were able to be visualized. The overall image quality and the conspicuity in critical organs were significantly improved compared with the uncorrected images: overall quality score (1.35 vs 3.25, P = 0.0022); bladder (2.15 vs 3.7, P = 0.0023); prostate and seminal vesicles/vagina (1.3 vs 3.275, P = 0.0020); rectum (2.8 vs 3.9, P = 0.0021). The noise levels of the selected ROIs were reduced from 93.7 to 38.2 HU. On most cases (8/10), the average CT Hounsfield numbers of the prostate/vagina on the O-MAR corrected images were closer to the referenced value (41.2 HU, an average measured from patients without metal implants) than those on the uncorrected images. High γ pass rates of the five IMRT dose distribution pairs indicated that the dose distributions were not significantly affected by the CTimage improvements.Conclusions:
Overall, this study indicated that the O-MAR function can remarkably reduce metal artifacts and improve both CT Hounsfield number accuracy and target and critical structure visualization. Although there was no significant impact of the O-MAR algorithm on the calculated dose distributions, we suggest that O-MAR corrected images are more suitable for the entire treatment planning process by offering better anatomical structure visualization, improving radiation oncologists’ confidence in target delineation, and by avoiding subjective density overrides of artifact regions on uncorrected images.
39(2012); http://dx.doi.org/10.1118/1.4768161View Description Hide Description
Purpose: The intensity modulated radiation therapy(IMRT) patient-specific quality assurance (QA) (referred to as QA in this paper for simplicity) process is a time and resource intensive effort in every clinic. The use of a global QA tolerance criterion for all treatment sites may be too tight for some complex sites increasing false negatives and rejections of QA measurements which typically results in wasted efforts, treatment delays, and decreased efficiency. At the same time, other sites requiring a less complex plan might have a high false positive leading to approvals of QA measurements that actually need to be rejected. This work is an effort to adopt statistical tools to
1. develop a tool to identify statistical variations in the process, monitor trends, detect outliers, and proactively identify drifts in the overall QA results;
2. analyze the results of the QA process, identify similarities and differences between treatment plans of different treatment sites, and evaluate the possibility of site-specific tolerance levels for QA approval tolerances.
Methods: The analysis was performed for QA measurements made using two ion chamber points. A custom software tool was developed for data processing and analysis. This tool facilitated QA data collection, retrieval, visualization, real-time feedback, and advanced statistical analysis of the data. Statistical techniques based on analysis of variance were used to evaluate the need for site-specific tolerances and statistical process control was used to study statistical variations in the process.
Results: A retrospective analysis of the QA process variability was performed in order to identify site-specific tolerances for the QA measurements and to reduce false positive and false negative QA results. From the data, it can be seen that the treatment sites are significantly different and need site-specific tolerance levels for QA approval. The in-house developed tool was used to further monitor the QA process using individual (I), standard deviations (S), and exponentially weighted moving averages charts for process variability studies.
Conclusions: The authors have studied the analysis of variance on ion chamber measurements made for IMRT treatment plans on different sites, identified similarities and differences between different sites, and thereby evaluated the need for site-specific tolerances for QA acceptance policy. The authors have proposed a way to calculate the appropriate tolerances for different treatment sites and illustrated the clinical usage. Variability at each step of the process increases the uncertainty in the process. The authors have explained the different approaches taken to reduce the variability at each step of the entire process. This process can be used for the benefit during/as part of an IMRT commissioning process in any clinic. The authors have also developed a tool to automate the process of data collection, analysis, and monitoring the process quality via standard deviations and EWMA charts.
Fast transit portal dosimetry using density-scaled layer modeling of aSi-based electronic portal imaging device and Monte Carlo method39(2012); http://dx.doi.org/10.1118/1.4764563View Description Hide DescriptionPurpose:
Fast and accurate transit portal dosimetry was investigated by developing a density-scaled layer model of electronic portal imaging device(EPID) and applying it to a clinical environment.Methods:
The model was developed for fast Monte Carlo dose calculation. The model was validated through comparison with measurements of dose on EPID using first open beams of varying field sizes under a 20-cm-thick flat phantom. After this basic validation, the model was further tested by applying it to transit dosimetry and dosereconstruction that employed our predetermined dose-response-based algorithm developed earlier. The application employed clinical intensity-modulated beams irradiated on a Rando phantom. The clinical beams were obtained through planning on pelvic regions of the Rando phantom simulating prostate and large pelvis intensity modulated radiation therapy. To enhance agreement between calculations and measurements of dose near penumbral regions, convolution conversion of acquired EPIDimages was alternatively used. In addition, thickness-dependent image-to-dosecalibration factors were generated through measurements of image and calculations of dose in EPID through flat phantoms of various thicknesses. The factors were used to convert acquired images in EPID into dose.Results:
For open beam measurements, the model showed agreement with measurements in dose difference better than 2% across open fields. For tests with a Rando phantom, the transit dosimetry measurements were compared with forwardly calculated doses in EPID showing gamma pass rates between 90.8% and 98.8% given 4.5 mm distance-to-agreement (DTA) and 3% dose difference (DD) for all individual beams tried in this study. The reconstructeddose in the phantom was compared with forwardly calculated doses showing pass rates between 93.3% and 100% in isocentric perpendicular planes to the beam direction given 3 mm DTA and 3% DD for all beams. On isocentric axial planes, the pass rates varied between 95.8% and 99.9% for all individual beams and they were 98.2% and 99.9% for the composite beams of the small and large pelvis cases, respectively. Three-dimensional gamma pass rates were 99.0% and 96.4% for the small and large pelvis cases, respectively.Conclusions:
The layer model of EPID built for Monte Carlo calculations offered fast (less than 1 min) and accurate calculation for transit dosimety and dosereconstruction.
Efficient implementation of the 3D-DDA ray traversal algorithm on GPU and its application in radiation dose calculation39(2012); http://dx.doi.org/10.1118/1.4767755View Description Hide DescriptionPurpose:
The three-dimensional digital differential analyzer (3D-DDA) algorithm is a widely used ray traversal method, which is also at the core of many convolution/superposition (C/S) dose calculation approaches. However, porting existing C/S dose calculation methods onto graphics processing unit (GPU) has brought challenges to retaining the efficiency of this algorithm. In particular, straightforward implementation of the original 3D-DDA algorithm inflicts a lot of branch divergence which conflicts with the GPU programming model and leads to suboptimal performance. In this paper, an efficient GPU implementation of the 3D-DDA algorithm is proposed, which effectively reduces such branch divergence and improves performance of the C/S dose calculation programs running on GPU.Methods:
The main idea of the proposed method is to convert a number of conditional statements in the original 3D-DDA algorithm into a set of simple operations (e.g., arithmetic, comparison, and logic) which are better supported by the GPU architecture. To verify and demonstrate the performance improvement, this ray traversal method was integrated into a GPU-based collapsed cone convolution/superposition (CCCS) dose calculation program.Results:
The proposed method has been tested using a water phantom and various clinical cases on an NVIDIA GTX570 GPU. The CCCS dose calculation program based on the efficient 3D-DDA ray traversal implementation runs 1.42 ∼ 2.67× faster than the one based on the original 3D-DDA implementation, without losing any accuracy.Conclusions:
The results show that the proposed method can effectively reduce branch divergence in the original 3D-DDA ray traversal algorithm and improve the performance of the CCCS program running on GPU. Considering the wide utilization of the 3D-DDA algorithm, various applications can benefit from this implementation method.
Pretreatment patient-specific IMRT quality assurance: A correlation study between gamma index and patient clinical dose volume histogram39(2012); http://dx.doi.org/10.1118/1.4767763View Description Hide DescriptionPurpose:
The aim of this work is to investigate the predictive power of a common conventional intensity modulated radiation therapy(IMRT)quality assurance (QA) performance metric, the gamma passing rate (%GP), through the analysis of the sensitivity and of the correlation between %GP and different dose discrepancies between planned dose-volume histogram (DVH) and perturbed DVH. The perturbed DVH is calculated by using a dedicated software, 3DVH (Sun Nuclear Corporation, Melbourne, FL), which is able to modify the dose distribution calculated by the treatment planning system (TPS) according to the dose discrepancies detected with planar measurements in order to predict the delivered 3D dose distribution in the patient.Methods:
Twenty-seven high-risk prostate cancer (PP) patients and 15 head and neck (HN) cancer patients, treated with IMRT technique, were analyzed. Pretreatment verifications were performed for all patients’ plans by acquiring planar dose distributions of each treatment field with 2D-diode array. Measured dose distributions were compared to the calculated ones using the gamma index (GI) method applying both global (Van Dyk) and local normalization, and %GP were generated for each pair of planar doses using the following acceptance criteria: 1%/1, 2%/2, and 3%/3 mm. Planar dose distributions acquired during pretreatment verifications, together with patient's DICOM RT plan, RT structure set, and RT dose files from TPS were loaded into the 3DVH software. Percentage dose differences (%DE) between DVHs, obtained by TPS and by 3DVH, were calculated; statistical correlation between %DE and %GP was studied by using Pearson's correlation coefficient (r). This analysis was performed, for each patient, on planning target volumes and on some typical organs at risk of the prostatic and head and neck anatomical district. The sensitivity was calculated to correctly identify the pretreatment plans with high dose errors and to quantify the incidence of false negatives, on varying the gamma index method.Results:
Analysis of %DE vs %GP showed that there were only weak correlations (Pearson'sr-values < 0.8). The results also showed numerous instances of false negatives (cases where high IMRT QA passing rates did not imply good agreement in anatomydose metrics) and the reverse, mainly for the 3%/3 mm global gamma passing rate.Conclusions:
The lack of correlation between conventional IMRT QA performance metrics gamma passing rates and dose errors in DVHs values and the low sensitivity of 3%/3 mm global gamma method show that the most common published acceptance criteria have disputable predictive power for per-patient IMRT QA.
39(2012); http://dx.doi.org/10.1118/1.4766270View Description Hide DescriptionPurpose:
Two quantitative methods of measuringelectron beam spot position with respect to the collimator axis of rotation (CAOR) are described.Methods:
Method 1 uses a cylindrical ion chamber (IC) mounted on a jig corotational with the collimator making the relationship among the chamber, jaws, and CAOR fixed and independent of collimator angle. A jaw parallel to the IC axis is set to zero and the IC position adjusted so that the IC signal is approximately 50% of the open field value, providing a large dose gradient in the region of the IC. The cGy/MU value is measured as a function of collimator rotation, e.g., every 30°. If the beam spot does not lie on the CAOR, the signal from the ion chamber will vary with collimator rotation. Based on a measured spatial sensitivity, the distance of the beam spot from the CAOR can be calculated from the IC signal variation with rotation. The 2nd method is image based. Two stainless steel rods, 3 mm in diameter, are mounted to a jig attached to the Linaccollimator. The rods, offset from the CAOR, lay in different planes normal to the CAOR, one at 158 cm SSD and the other at 70 cm SSD. As the collimator rotates the rods move tangent along an envelope circle, the centers of which are on the CAOR in their respective planes. Three images, each at a different collimator rotation, containing the shadows of both rods, are acquired on the Linac EPID. At each angle the shadow of the rods on the EPID defines lines tangent to the projection of the envelope circles. From these the authors determine the projected centers of the two circles at different heights. From the distance of these two points using the two heights and the source to EPID distance, the authors calculate the distance of the beam spot from the CAOR. Measurements with all two techniques were performed on an Elekta Linac.Measurements were performed with the beam spot in nominal clinical position and in a deliberately offset position. Measurements were also performed using the Flexmap image registration/ball-bearing test.Results:
Within their uncertainties, both methods report the same beam spot displacement. In clinical use, a total of 203 monthly beam spot measurements on 14 different beams showed an average displacement of 0.11 mm (σ = 0.07 mm) in-plane and 0.10 mm (σ = 0.07 mm) cross-plane with maximum displacement of 0.37 mm in-plane and 0.34 mm cross-plane.Conclusions:
The methods described provide a quantitative measure of beam spot position, are easy to use, and provide another tool for Linac setup and quality assurance. Fundamental to the techniques is that they are self-referencing–i.e., they do not require the user to independently define the CAOR.
Assessing the impact of radiation-induced changes in soft tissue density/thickness on the study of radiation-induced perfusion changes in the lung and heart39(2012); http://dx.doi.org/10.1118/1.4766433View Description Hide DescriptionPurpose:
Abnormalities in single photon emission computed tomography(SPECT) perfusion within the lung and heart are often detected following radiation for tumors in/around the thorax (e.g., lungcancer or left-sided breast cancer). The presence of SPECT perfusion defects is determined by comparing pre- and post-RT SPECTimages. However, RT may increase the density of the soft tissue surrounding the lung/heart (e.g., chest wall/breast) that could possibly lead to an “apparent” SPECT perfusion defect due to increased attenuation of emitted photons. Further, increases in tissue effective depth will also increase SPECTphoton attenuation and may lead to “apparent” SPECT perfusion defects. The authors herein quantitatively assess the degree of density changes and effective depth in soft tissues following radiation in a series of patients on a prospective clinical study.Methods:
Patients receiving thoracic RT were enrolled on a prospective clinical study including pre- and post-RT thoracic computed tomography(CT) scans. Using image registration, changes in tissue density and effective depth within the soft tissues were quantified (as absolute change in average CT Hounsfield units, HU, or tissue thickness, cm). Changes in HU and tissue effective depth were considered as a continuous variable. The potential impact of these tissue changes on SPECTimages was estimated using simulation data from a female SPECT thorax phantom with varying tissue densities.Results:
Pre- and serial post-RT CTimages were quantitatively studied in 23 patients (4 breast cancer, 19 lungcancer). Data were generated from soft tissue regions receiving doses of 20–50 Gy. The average increase in density of the chest was 5 HU (range 46 to −69). The average change in breast density was a decrease of −1 HU (range 13 to −13). There was no apparent dose response in neither the dichotomous nor the continuous analysis. Seventy seven soft tissue contours were created for 19 lungcancer patients. The average change in tissue effective depth was +0.2 cm (range −1.9 to 2.2 cm). The changes in HU represent a <2% average change in tissue density. Based on simulation, the small degree of density and tissue effective depth change is unlikely to yield meaningful changes in either SPECTlung or heart perfusion.Conclusions:
RT doses of 20–50 Gy can cause up to a 46 HU increase in soft tissue density 6 months post-RT. Post-RT soft tissue effective depth may increase by 2.0 cm. These modest increases in soft tissue density and effective depth are unlikely to be responsible for the perfusion changes seen on post-RT SPECTlung or heart scans. Further, there was no clear dose response of thesoft tissue density changes. Ultimately, the authors findings suggest that prior perfusion reports do reflect changes in the physiology of the lungs and heart.
39(2012); http://dx.doi.org/10.1118/1.4758065View Description Hide DescriptionPurpose:
The full benefit of the increased precision of contemporary treatment techniques can only be exploited if the accuracy of the patient positioning is guaranteed. Therefore, more and more imaging modalities are used in the process of the patient setup in clinical routine of radiation therapy. The improved accuracy in patient positioning, however, results in additional dose contributions to the integral patient dose. To quantify this, absorbed dose measurements from typical imaging procedures involved in an image-guided radiation therapytreatment were measured in an anthropomorphic phantom for a complete course of treatment. The experimental setup, including the measurement positions in the phantom, was exactly the same as in a preceding study of radiotherapy stray dose measurements. This allows a direct combination of imagingdose distributions with the therapy dose distribution.Methods:
Individually calibrated thermoluminescent dosimeters were used to measure absorbed dose in an anthropomorphic phantom at 184 locations. The dose distributions from imaging devices used with treatment machines from the manufacturers Accuray, Elekta, Siemens, and Varian and from computed tomography scanners from GE Healthcare were determined and the resulting effective dose was calculated. The list of investigated imaging techniques consisted of cone beam computed tomography (kilo- and megavoltage), megavoltage fan beam computed tomography, kilo- and megavoltage planar imaging, planning computed tomography with and without gating methods and planar scout views.Results:
A conventional 3D planning CT resulted in an effective dose additional to the treatment stray dose of less than 1 mSv outside of the treated volume, whereas a 4D planning CT resulted in a 10 times larger dose. For a daily setup of the patient with two planar kilovoltage images or with a fan beam CT at the TomoTherapy unit, an additional effective dose outside of the treated volume of less than 0.4 mSv and 1.4 mSv was measured, respectively. Using kilovoltage or megavoltage radiation to obtain cone beam computed tomography scans led to an additional dose of 8–46 mSv. For treatment verification images performed once per week using double exposure technique, an additional effective dose of up to 18 mSv was measured.Conclusions:
Daily setup imaging using kilovoltage planar images or TomoTherapy megavoltage fan beam CTimaging can be used as a standard procedure in clinical routine. Daily kilovoltage and megavoltage cone beam computed tomography setup imaging should be applied on an individual or indication based protocol. Depending on the imaging scheme applied, image-guided radiation therapy can be administered without increasing the dose outside of the treated volume compared to therapies without image guidance.