Index of content:
Volume 38, Issue 1, January 2011
Office-based cone-beam and digital tomosynthesis systems using flat-panel technology should not be referred to as CT units38(2011); http://dx.doi.org/10.1118/1.3512800View Description Hide Description
- RADIATION THERAPY PHYSICS
38(2011); http://dx.doi.org/10.1118/1.3519873View Description Hide DescriptionPurpose:
Compton cameraimaging (CCI) systems are currently under investigation for radiotherapy dosereconstruction and verification. The ability of such a system to provide real-time images during dose delivery will be limited by the computational speed of the image reconstruction algorithm. In this work, the authors present a fast and simple method by which to generate an initial back-projected image from acquired CCI data, suitable for use in a filtered back-projection algorithm or as a starting point for iterative reconstruction algorithms, and compare its performance to the current state of the art.Methods:
Each detector event in a CCI system describes a conical surface that includes the true point of origin of the detectedphoton. Numerical image reconstruction algorithms require, as a first step, the back-projection of each of these conical surfaces into an image space. The algorithm presented here first generates a solution matrix for each slice of the image space by solving the intersection of the conical surface with the image plane. Each element of the solution matrix is proportional to the distance of the corresponding voxel from the true intersection curve. A threshold function was developed to extract those pixels sufficiently close to the true intersection to generate a binary intersection curve. This process is repeated for each image plane for each CCI detector event, resulting in a three-dimensional back-projection image. The performance of this algorithm was tested against a marching algorithm known for speed and accuracy.Results:
The threshold-based algorithm was found to be approximately four times faster than the current state of the art with minimal deficit to image quality, arising from the fact that a generically applicable threshold function cannot provide perfect results in all situations. The algorithm fails to extract a complete intersection curve in image slices near the detector surface for detector event cones having axes nearly parallel to the image plane. This effect decreases the sum of the image, thereby also affecting the mean, standard deviation, and SNR of the image. All back-projected events associated with a simulated point source intersected the voxel containing the source and the FWHM of the back-projected image was similar to that obtained from the marching method.Conclusions:
The slight deficit to image quality observed with the threshold-based back-projection algorithm described here is outweighed by the 75% reduction in computation time. The implementation of this method requires the development of an optimum threshold function, which determines the overall accuracy of the method. This makes the algorithm well-suited to applications involving the reconstruction of many large images, where the time invested in threshold development is offset by the decreased image reconstruction time. Implemented in a parallel-computing environment, the threshold-based algorithm has the potential to provide real-time dose verification for radiation therapy.
Beam commissioning and measurements validating the beam model in a new TPS that converts helical tomotherapy plans to step-and-shoot IMRT plans38(2011); http://dx.doi.org/10.1118/1.3519975View Description Hide DescriptionPurpose:
A new type of treatment planning system calledSHAREPLAN has been studied, which enables the transfer of treatment plans generated for helical tomotherapy delivery to plans that can be delivered on C-arm linacs. The purpose is to ensure continuous patient treatment during periods of unscheduled downtime for the TomoTherapy unit, particularly in clinics without a backup unit. The purpose of this work was to verify that the plans generated in this novel planning system are deliverable and accurate. The work consists primarily of beam commissioning, verification of the beam model, and measurements verifying that generated plans are deliverable with sufficient accuracy.Methods:
The beam commissioning process involves input of general geometric properties of the modeled linac, profiles and depth dose curves for a specific photon nominal energy (6 MV), and the automated modeling of other beam properties. Some manual tuning of the beam model is required. To evaluate its accuracy, the confidence limit concept [J. Venselaar et al., “Tolerances for the accuracy of photon beam dose calculations of treatment planning systems,” Radiother. Oncol.60, 191–201 (2001)] was used, which is a method supported by ESTRO. Measurements were conducted with a 2D diode array at the commissioned linac as a final check of the beam model and to evaluate whether the generated plans were deliverable and accurate.Results:
The comparison and evaluation of calculated data points and measured data according to the method applied confirmed the accuracy of the beam model. The profiles had a confidence limit of 1.1% and the depth dose curves had a confidence limit of 1.7%, both of which were well below the tolerance limit of 2%. Plan specific QC measurements and evaluation verified that different plans generated in the TPS were deliverable with sufficient accuracy at the commissioned linac, as none of the 160 beams for the 20 different plans evaluated had a fraction of approved data points below 90%, the local clinical approval criterion for delivery QA measurements.Conclusions:
This study is a validation of the new TPS as it verifies that the generated plans are deliverable at a commissioned linac with adequate accuracy. A thorough investigation of the treatment plan quality will require a separate study. The TPS is proving to be a useful and time-saving complement, especially for clinics having a single unit for helical delivery among its conventional linacs.
38(2011); http://dx.doi.org/10.1118/1.3519988View Description Hide DescriptionPurpose:
In permanent seed implants, 60 to more than 100 small metal capsules are inserted in the prostate, creating artifacts in x-ray computed tomography(CT)imaging. The goal of this work is to develop an automatic method for metal artifact reduction (MAR) from small objects such as brachytherapy seeds for clinical applications.Methods:
The approach for MAR is based on the interpolation of missing projections by directly using raw helical CT data (sinogram). First, an initial image is reconstructed from the raw CT data. Then, the metal objects segmented from the reconstructed image are reprojected back into the sinogram space to produce a metal-only sinogram. The Steger method is used to determine precisely the position and edges of the seed traces in the raw CT data. By combining the use of Steger detection and reprojections, the missing projections are detected and replaced by interpolation of non-missing neighboring projections.Results:
In both phantom experiments and patient studies, the missing projections have been detected successfully and the artifacts caused by metallic objects have been substantially reduced. The performance of the algorithm has been quantified by comparing the uniformity between the uncorrected and the corrected phantom images. The results of the artifact reduction algorithm are indistinguishable from the true background value.Conclusions:
An efficient algorithm for MAR in seed brachytherapy was developed. The test results obtained using raw helical CT data for both phantom and clinical cases have demonstrated that the proposed MAR method is capable of accurately detecting and correcting artifacts caused by a large number of very small metal objects (seeds) in sinogram space. This should enable a more accurate use of advanced brachytherapydose calculations, such as Monte Carlo simulations.
38(2011); http://dx.doi.org/10.1118/1.3521465View Description Hide DescriptionPurpose:
Radiation therapy with high dose rate and flattening filter-free (FFF) beams has the potential advantage of greatly reduced treatment time and out-of-field dose. Current inverse planning algorithms are, however, not customized for beams with nonuniform incident profiles and the resultant IMRT plans are often inefficient in delivery. The authors propose a total-variation regularization (TVR)-based formalism by taking the inherent shapes of incident beam profiles into account.Methods:
A novel TVR-based inverse planning formalism is established for IMRT with nonuniform beam profiles. The authors introduce a TVR term into the objective function, which encourages piecewise constant fluence in the nonuniform FFF fluence domain. The proposed algorithm is applied to lung and prostate and head and neck cases and its performance is evaluated by comparing the resulting plans to those obtained using a conventional beamlet-based optimization (BBO).Results:
For the prostate case, the authors’ algorithm produces acceptable dose distributions with only 21 segments, while the conventional BBO requires 114 segments. For the lung case and the head and neck case, the proposed method generates similar coverage of target volume and sparing of the organs-at-risk as compared to BBO, but with a markedly reduced segment number.Conclusions:
TVR-based optimization in nonflat beam domain provides an effective way to maximally leverage the technical capacity of radiation therapy with FFF fields. The technique can generate effective IMRT plans with improved dose delivery efficiency without significant deterioration of the dose distribution.
38(2011); http://dx.doi.org/10.1118/1.3523097View Description Hide DescriptionPurpose:
Recently, several robotic systems have been developed to perform accurate and consistent image-guided brachytherapy. Before introducing a new device into clinical operations, it is important to assess the reliability and mean time before failure (MTBF) of the system. In this article, the authors present the preclinical evaluation and analysis of the reliability and MTBF of an autonomous robotic system, which is developed for prostate seed implantation.Methods:
The authors have considered three steps that are important in reliability growth analysis. These steps are: Identification and isolation of failures, classification of failures, and trend analysis. For any one-of-a-kind product, the reliability enhancement is accomplished through test-fix-test. The authors have used failure mode and effect analysis for collection and analysis of reliability data by identifying and categorizing the failure modes. Failures were classified according to severity. Failures that occurred during the operation of this robotic system were considered as nonhomogenous Poisson process. The failure occurrence trend was analyzed using Laplace test. For analyzing and predicting reliability growth, commonly used and widely accepted models, Duane’s model and the Army Material Systems Analysis Activity, i.e., Crow’s model, were applied. The MTBF was used as an important measure for assessing the system’s reliability.Results:
During preclinical testing, 3196 seeds (in 53 test cases) were deposited autonomously by the robot and 14 critical failures were encountered. The majority of the failures occurred during the first few cases. The distribution of failures followed Duane’s postulation as well as Crow’s postulation of reliability growth. The Laplace test index was −3.82, indicating a significant trend in failure data, and the failure intervals lengthened gradually. The continuous increase in the failure occurrence interval suggested a trend toward improved reliability. The MTBF was 592 seeds, which implied that several prostate seed implantation cases would be possible without encountering any critical failure. The shape parameter for the MTBF was 0.3859 , suggesting a positive reliability growth of this robotic system. At 95% confidence, the reliability for deposition of 65 seeds was more than 90%.Conclusions:
Analyses of failure mode strongly indicated a gradual improvement of reliability of this autonomous robotic system. High MTBF implied that several prostate seed implant cases would be possible without encountering any critical failure.
38(2011); http://dx.doi.org/10.1118/1.3523624View Description Hide DescriptionPurpose:
A biomechanical model was constructed to give insight into pelvic organ motion as a result of bladder filling changes.Methods:
The authors used finite element(FE)modeling to simulate bladder wall deformation caused by urine inflow. For ten volunteers, a series of MRI scans of the pelvic area was recorded at regular intervals of 10 min over 1 h. For the series of scans, the bladder volume gradually increased while the rectal volume was constant. The MR image with the bladder volume closest to 250 ml was selected as the reference in each volunteer. All pelvic structures were defined from the reference image including bladder wall, small bowel, prostate (male), uterus (female), rectum, pelvic bone, and the rest of the body. These structures were translated to FE meshes. Using appropriate material properties for all organs, deformations of these organs as a response to changing bladder pressure were computed.Results:
The computation results showed realistic anisotropic deformation of the bladder wall: The bladder became more elongated in the cranial and anterior directions with increasing bladder volume. After fitting the volume of the computed bladder to the actual bladder volume on the test images, the computed bladder shape agreed well with the real bladder shape (overlap from 0.79 to 0.93). The average mean bladder wall prediction errors of all the volunteers were 0.31 cm average and 0.29 cm SD.Conclusions:
In conclusion, a FE based mechanical bladder model shows promise for the prediction of the short-term bladder shape change using only one pelvic scan and volume change of the bladder as input. The accuracy levels achieved with this method are likely mostly limited by inaccuracies in material properties and sliding tissue between organs, which has not been modeled. This model can potentially be used to improve image-guidedradiotherapy for bladder cancer patients, i.e., by prediction short-term bladder deformation.
38(2011); http://dx.doi.org/10.1118/1.3523619View Description Hide Description
Purpose: Four-dimensional computed tomography (4D CT) can provide patient-specific motion information for radiotherapy planning and delivery. Motion estimation in 4D CT is challenging due to the reduced image quality and the presence of artifacts. We aim to improve the robustness of deformable registration applied to respiratory-correlated imaging of the lungs, by using a global problem formulation and pursuing a restrictive parametrization for the spatiotemporal deformation model.
Methods: A spatial transformation based on free-form deformations was extended to the temporal domain, by explicitly modeling the trajectory using a cyclic temporal model based on B-splines. A global registration criterion allowed to consider the entire imagesequence simultaneously and enforce the temporal coherence of the deformation throughout the respiratory cycle. To ensure a parametrization capable of capturing the dynamics of respiratory motion, a prestudy was performed on the temporal dimension separately. The temporal parameters were tuned by fitting them to diaphragm motion data acquired for a large patient group. Suitable properties were retained and applied to spatiotemporal registration of 4D CT data. Registration results were validated using large sets of landmarks and compared to consecutive spatial registrations. To illustrate the benefit of the spatiotemporal approach, we also assessed the performance in the presence of motion-induced artifacts.
Results: Cubic B-splines gave better or similar fitting results as lower orders and were selected because of their inherently stronger regularization. The fitting and registration errors increased gradually with the temporal control point spacing, representing a trade-off between achievable accuracy and sensitivity to noise and artifacts. A piecewise smooth trajectory model, allowing for a discontinuous change of speed at end-inhale, was found most suitable to account for the sudden changes of motion at this breathing phase. The spatiotemporal modeling allowed a reduction of the number of parameters of 45%, while maintaining registration accuracy within 0.1 mm. The approach reduced the sensitivity to artifacts.
Conclusions: Spatiotemporal registration can provide accurate motion estimation for 4D CT and improves the robustness to artifacts.
4D dose-position verification in radiation therapy using the RADPOS system in a deformable lung phantom38(2011); http://dx.doi.org/10.1118/1.3515461View Description Hide DescriptionPurpose:
A novel 4Din vivodosimetry system (RADPOS), in conjunction with a deformable lung phantom, has been evaluated as a potential quality assurance tool for 4D radiotherapy.Methods:
RADPOS detectors, which consist of a MOSFET dosimeter combined with an electromagnetic positioning probe, were placed inside the deformable lung phantom. One detector was positioned directly inside a tumor embedded in the lung phantom and another was positioned inside the lung portion of the phantom, outside the tumor.CT scans were taken with the phantom at three breathing phases, and for each phase, the detector position inside the phantom was read with the RADPOS software and compared to the position as determined from the CT data. These values were also compared to RADPOS measurements taken with the phantom on the couch of a Varian Clinac 6EX linac. The deformable phantom and the RADPOS system were also used in two radiation delivery scenarios: (1) A simulation of a free-breathing delivery and (2) a simulation of an adaptive treatment.Results:
Compared to CTimaging, the RADPOS positional accuracy was found to be better than 2.5 mm. The radial displacement measurements taken in the CT and linac rooms agreed to within an average of. Hence, the system can provide relative displacement measurements in the treatment room, consistent with measurements made in the CT room. For the free-breathing delivery, the total dose reported by RADPOS agreed to within 4% and 5% of the treatment planning doses in the tumor and the lung portion of the phantom, respectively. The RADPOS-measured dose values for the adaptive delivery were within 1.5% of the treatment plan values, which was well within the estimated experimental uncertainties.Conclusions:
This work has shown that the deformable lung phantom-RADPOS system can be an efficient quality assurance tool for 4D radiation therapy.
On Monte Carlo modeling of megavoltage photon beams: A revisited study on the sensitivity of beam parameters38(2011); http://dx.doi.org/10.1118/1.3523625View Description Hide DescriptionPurpose:
To commission Monte Carlobeammodels for five Varian megavoltage photonbeams (4, 6, 10, 15, and 18 MV). The goal is to closely match measured dose distributions in water for a wide range of field sizes (from to ). The second objective is to reinvestigate the sensitivity of the calculated dose distributions to variations in the primary electron beam parameters.Methods:
TheGEPTSMonte Carlo code is used for photonbeam simulations and dose calculations. The linear accelerator geometric models are based on (i) manufacturer specifications, (ii) corrections made by Chibani and Ma [“On the discrepancies between Monte Carlodose calculations and measurements for the 18 MV Varian photon beam,” Med. Phys.34, 1206–1216 (2007)], and (iii) more recent drawings. Measurements were performed using pinpoint and Farmer ionization chambers, depending on the field size. Phase space calculations for small fields were performed with and without angle-based photon splitting. In addition to the three commonly used primary electron beam parameters ( is the mean energy, FWHM is the energy spectrum broadening, and is the beam radius), the angular divergence of primary electrons is also considered.Results:
The calculated and measured dose distributions agreed to within 1% local difference at any depth beyond 1 cm for different energies and for field sizes varying from to . In the penumbra regions, the distance to agreement is better than 0.5 mm, except for 15 MV (0.4–1 mm). The measured and calculated output factors agreed to within 1.2%. The 6, 10, and 18 MV beammodels use , while the 4 and 15 MV beammodels require and 0.6°, respectively. The parameter sensitivity study shows that varying the beam parameters around the solution can lead to 5% differences with measurements for small (e.g., ) and large (e.g., ) fields, while a perfect agreement is maintained for the field. The influence of on the central-axis depth dose and the strong influence of on the lateral dose profiles are demonstrated.Conclusions:
Dose distributions for very small and very large fields were proved to be more sensitive to variations in, , and in comparison with the field. Monte Carlobeammodels need to be validated for a wide range of field sizes including small field sizes (e.g., ).
38(2011); http://dx.doi.org/10.1118/1.3524227View Description Hide Description
Purpose: To design a fast Winston Lutz (fWL) algorithm for accurate analysis of radiation isocenter from images without edge detection or center of mass calculations.
Methods: An algorithm has been developed to implement the Winston Lutz test for mechanical/radiation isocenter agreement using an electronic portal imaging device(EPID). The algorithm detects the position of the radiation shadow of a tungsten ball within a stereotactic cone. The fWL algorithm employs a double convolution to independently find the position of the sphere and cone centers. Subpixel estimation is used to achieve high accuracy. Results of the algorithm were compared to (1) a human observer with template guidance and (2) an edge detection/center of mass (edCOM) algorithm. Testing was performed with high resolution (0.05mm/px, film) and low resolution (0.78mm/px, EPID)image sets.
Results: Sphere and cone center relative positions were calculated with the fWL algorithm for high resolution test images with an accuracy of compared to for the human observer, and for the edCOM algorithm. The fWL algorithm required 0.01 s per image compared to 5 s for the edCOM algorithm and 20 s for the human observer. For lower resolution images the fWL algorithm localized the centers with an accuracy of compared to for the edCOM algorithm.
Conclusions: A fast (subsecond) subpixel algorithm has been developed that can accurately determine the center locations of the ball and cone in Winston Lutz test images without edge detection or COM calculations.
38(2011); http://dx.doi.org/10.1118/1.3483785View Description Hide DescriptionPurpose:
To accelerate dose calculation to interactive rates using highly parallel graphics processing units (GPUs).Methods:
The authors have extended their prior work in GPU-accelerated superposition/convolution with a modern dual-source model and have enhanced performance. The primary source algorithm supports both focused leaf ends and asymmetric rounded leaf ends. The extra-focal algorithm uses a discretized, isotropic area source and models multileaf collimator leaf height effects. The spectral and attenuation effects of static beam modifiers were integrated into each source’s spectral function. The authors introduce the concepts of arc superposition and delta superposition. Arc superposition utilizes separate angular sampling for the total energy released per unit mass (TERMA) and superposition computations to increase accuracy and performance. Delta superposition allows single beamlet changes to be computed efficiently. The authors extended their concept of multi-resolution superposition to include kernel tilting. Multi-resolution superposition approximates solid angle ray-tracing, improving performance and scalability with a minor loss in accuracy. Superposition/convolution was implemented using the inverse cumulative-cumulative kernel and exact radiological path ray-tracing. The accuracy analyses were performed using multiple kernel ray samplings, both with and without kernel tilting and multi-resolution superposition.Results:
Source model performance was (data dependent) for a high resolution field using an NVIDIA (Santa Clara, CA) GeForce GTX 280. Computation of the physically correct multispectral TERMA attenuation was improved by a material centric approach, which increased performance by over 80%. Superposition performance was improved by to 0.058 and 0.94 s for and water phantoms; a speed-up of 101–144× over the highly optimized Pinnacle3 (Philips, Madison, WI) implementation. times were 8.3 and 94 s, respectively, on an AMD (Sunnyvale, CA) Opteron 254 (two cores, 2.8 GHz).Conclusions:
The authors have completed a comprehensive, GPU-accelerated dose engine in order to provide a substantial performance gain over CPU based implementations. Real-time dose computation is feasible with the accuracy levels of the superposition/convolution algorithm.
38(2011); http://dx.doi.org/10.1118/1.3523614View Description Hide DescriptionPurpose:
To investigate dosimetric differences among several clinical treatment planning systems (TPS) and Monte Carlo(MC) codes for brachytherapy of intraocular tumors using or plaques, and to evaluate the impact on the prescription dose of the adoption of MC codes and certain versions of a TPS (Plaque Simulator with optional modules).Methods:
Three clinical brachytherapy TPS capable of intraocular brachytherapytreatment planning and two MC codes were compared. The TPS investigated were Pinnacle v8.0dp1, BrachyVision v8.1, and Plaque Simulator v5.3.9, all of which use the AAPM TG-43 formalism in water. The Plaque Simulator software can also handle some correction factors from MC simulations. The MC codes used areMCNP5 v1.40 and BrachyDose/EGSnrc. Using these TPS and MC codes, three types of calculations were performed: homogeneous medium with point sources (for the TPS only, using the 1D TG-43 dose calculation formalism); homogeneous medium with line sources (TPS with 2D TG-43 dose calculation formalism and MC codes); and plaque heterogeneity-corrected line sources (Plaque Simulator with modified 2D TG-43 dose calculation formalism and MC codes). Comparisons were made of doses calculated at points-of-interest on the plaque central-axis and at off-axis points of clinical interest within a standardized model of the right eye.Results:
For the homogeneous water medium case, agreement was within for the point- and line-source models when comparing between TPS and between TPS and MC codes, respectively. For the heterogeneous medium case, dose differences (as calculated using the MC codes and Plaque Simulator) differ by up to 37% on the central-axis in comparison to the homogeneous water calculations. A prescription dose of 85 Gy at 5 mm depth based on calculations in a homogeneous medium delivers 76 Gy and 67 Gy for specific and sources, respectively, when accounting for COMS-plaque heterogeneities. For off-axis points-of-interest, dose differences approached factors of 7 and 12 at some positions for and , respectively. There was good agreement () among MC codes and Plaque Simulator results when appropriate parameters calculated using MC codes were input into Plaque Simulator. Plaque Simulator and MC users are perhaps at risk of overdosing patients up to 20% if heterogeneity corrections are used and the prescribed dose is not modified appropriately.Conclusions:
Agreement within 2% was observed among conventional brachytherapy TPS and MC codes for intraocular brachytherapydose calculations in a homogeneous water environment. In general, the magnitude of dose errors incurred by ignoring the effect of the plaque backing and Silastic insert (i.e., by using the TG-43 approach) increased with distance from the plaque’s central-axis. Considering the presence of material heterogeneities in a typical eye plaque, the best method in this study for dose calculations is a verified MC simulation.
38(2011); http://dx.doi.org/10.1118/1.3525839View Description Hide DescriptionPurpose:
Plan reconstruction for permanent implant prostate brachytherapy is the process of determining the correspondence between planned and implanted seeds in postimplant analysis. Plan reconstruction informs many areas of brachytherapy quality assurance, including the verification of seed segmentation, misplacement and migration assessment, implant simulations, and the dosimetry of mixed-activity or mixed-species implants.Methods:
An algorithm has been developed for stranded implants which uses the interseed spacing constraints imposed by the suture to improve the accuracy of reconstruction. Seventy randomly selected clinical cases with a mean of 23.6 (range 18–30) needles and mean density of 2.0 (range 1.6–2.6) were automatically reconstructed and the accuracy compared to manual reconstructions performed using a custom 3D graphical interface.Results:
Using the automatic algorithm, the mean accuracy of the assignment relative to manual reconstruction was found to be. Fifty-two of the 70 cases (74%) were error-free; of seeds in the remaining cases, were found to be attributed to the correct strand and were correctly connected to their neighbors. Any necessary manual correction using the interface is usually straightforward. For the clinical data set tested, neither the number of seeds or needles, average density, nor the presence of clusters was found to have an effect on reconstruction accuracy using this method.Conclusions:
Routine plan reconstruction of stranded implants can be performed with a high degree of accuracy to support postimplant dosimetry and quality analyses.
Estimation of three-dimensional intrinsic dosimetric uncertainties resulting from using deformable image registration for dose mapping38(2011); http://dx.doi.org/10.1118/1.3528201View Description Hide DescriptionPurpose:
This article presents a general procedural framework to assess the point-by-point precision in mapped dose associated with the intrinsic uncertainty of a deformable image registration (DIR) for any arbitrary patient.Methods:
Dose uncertainty is obtained via a three-step process. In the first step, for each voxel in an imaging pair, a cluster of points is obtained by an iterative DIR procedure. In the second step, the dispersion of the points due to the imprecision of the DIR method is used to compute the spatial uncertainty. Two different ways to quantify the spatial uncertainty are presented in this work. Method A consists of a one-dimensional analysis of the modules of the position vectors, whereas method B performs a more detailed 3D analysis of the coordinates of the points. In the third step, the resulting spatial uncertainty estimates are used in combination with the mapped dose distribution to compute the point-by-point dose standard deviation. The process is demonstrated to estimate the dose uncertainty induced by mapping a 62.6 Gy dose delivered on maximum exhale to maximum inhale of a ten-phase four-dimensional lungCT.Results:
For the demonstration lungimage pair, the standard deviation of inconsistency vectors is found to be up to 9.2 mm with a mean of 1.3 mm. This uncertainty results in a maximum estimated dose uncertainty of 29.65 Gy if method A is used and 21.81 Gy for method B. The calculated volume with dose uncertainty above 10.00 Gy is for method A and for method B.Conclusions:
This procedure represents a useful tool to evaluate the precision of a mapped dose distribution due to the intrinsic DIR uncertainty in a patient. The procedure is flexible, allowing incorporation of alternative intrinsic error models.
38(2011); http://dx.doi.org/10.1118/1.3523615View Description Hide DescriptionPurpose:
When comparing predicted portal doseimages (PDIs) to PDIs acquired by an EPID during treatment delivery, differences are often observed. These differences may be partially attributed to beam attenuation by parts of the treatment couch not taken into account in the PDI prediction. In order to improve the agreement, a model for the treatment couch was derived and included in the PDI prediction.Methods:
A CT scan was used to model the couch top. The model for the couch top base was derived by iteratively matching the predicted and measured PDIs for gantry angles of 0°, 45°, and 90°. For PDI prediction, the modeled treatment couch was added to the CT scan of a patient or phantom by using the recorded couch positions from the record and verify system. To validate the couch model, PDI measurements were performed for a range of couch positions and gantry angles, both with and without an anatomical phantom in the beam.Results:
After including the couch model in the PDI prediction for beams passing through the couch without phantom, the mean local dose differences between measured and predicted PDIs were reduced from up to 5.5% to less than 1.0% at each gantry angle. Similar results were obtained for measurements with a lung phantom on the couch. Although the couch model was originally derived by using a 6 MV photon beam, the results showed that it is also applicable for a 10 MV beam.Conclusions:
A model of the treatment couch was derived and included in the PDI prediction, yielding a substantially improved agreement between measured and predicted PDIs, which makes interpretation of the observed deviations more straightforward.
Feasibility of using cone-beam CT to verify and reposition the optically guided target localization of linear accelerator based stereotactic radiosurgery38(2011); http://dx.doi.org/10.1118/1.3531547View Description Hide DescriptionPurpose:
The optically guided target localization had been developed for linear accelerator based stereotactic radiosurgery(SRS). Unlike the traditional laser localization, the optical guided target localization utilizes a digital system to position patient. Although the system has been proven accurate and robust, it takes away the capability of physicist to directly double check the target position prior to irradiation. Any error from system calibration, data transformation, or head ring position maintenance will not be caught. The purpose of this work is to investigate the possibility of using cone-beam CT(CBCT) to double check the optically guided SRS target localization and reposition the patient.Methods:
A SRS quality assurance (QA) phantom was used in the study. The phantom mounted with SRS head frame was scanned by computer tomography(CT) and planned according to the SRSradiation treatment planning process. A target isocenter is defined and transferred to the optically guided target localization system. The phantom was then transported to the linear accelerator room and localized at the initial position agreed by the optically guided target localization system and the CBCT system. Tests were conducted by moving/rotating the phantom to a set of preset offsets and taking CBCTimages. Shifts detected by CBCT were compared with the preset offsets. Agreements between them were studied to see how well the CBCT was in discovering the optically guided target localization error.Results:
Experiment results demonstrated good agreement between the CBCT detected phantom shift and the preset offset, when the offset is above 1 mm shift or 0.2 degree rotation. Offset less than 1 mm shift or 0.2 degree rotation was not detectable by CBCT.Conclusions:
The study concludes that the CBCT is able to discover the optically guided target localization error due to the system calibration or had ring migration. It is a valuable second check tool for SRS target localization quality assurance. The accuracy of CBCT in estimating patient positioning deviation satisfies the SRS procedures with generous tumor size and margin that can tolerate 1 mm or 0.2 degree accuracy. This avoids sending patient home without treatment.CBCT can be neither used as a primary SRS target localization nor can it be used to reposition the patient that cannot tolerate 1 mm shift or 0.2 degree rotation.
A TCP model incorporating setup uncertainty and tumor cell density variation in microscopic extension to guide treatment planning38(2011); http://dx.doi.org/10.1118/1.3531543View Description Hide DescriptionPurpose:
Tumorcontrol probability (TCP) models have been proposed to evaluate and guide treatment planning. However, they are usually based on the dose volume histograms (DVHs) of the planning target volume (PTV) and may not properly reflect the substantial variation in tumor burden from the gross tumor volume (GTV) to the microscopic extension (ME) and to the margin of PTV. In this study, the authors propose a TCP model that can account for the effects of setup uncertainties and tumor cell density decay in the ME region.Methods:
The proposed TCP model is based on the total surviving clonogenic tumor cells (CTCs) after irradiation of a known dose distribution to a region with a CTC distribution. The CTC density was considered to be homogeneous within the GTV, while decreasing exponentially in the ME region. The effect of random setup uncertainty was modeled by convolving the dose distribution with a Gaussian probability density function, represented by a standard deviation,. The effect of systematic setup uncertainty was modeled by summing each calculated TCP for all potential offsets in a Gaussian probability, represented by . The model was then applied to simplified cases to demonstrate the concept. TCP dose responses were calculated for various GTV volumes, DVH shapes, CTC density decay coefficients, probabilities of lymph node metastasis, and random and systematic errors. The slopes of the dose falloff to cover the CTC density decay in the ME region and the margins to compensate setup errors were also analyzed in generalized cases.Results:
The sigmoid TCP dose response curve shifted to the right substantially for a larger GTV, while modestly for cold spots in DVH. A dose distribution with a uniform dose within the GTV, and a linear dose falloff in the ME region, tended to cause a minimal TCP deterioration if a proper dose falloff slope was used. When the dose falloff slope was less steep than a critical slope represented by, the , which is the prescription dose at , and , which is the TCP slope at , varied little with different dose falloff slopes. However, both and deteriorated fast when the slopes were steeper than . The random setup error tended to shift the TCP curve to the right, while the systematic error tended to compress the curve downward. For combined random and systematic errors, we demonstrated that based on the model, a margin of added to the GTV was found to cause a TCP change corresponding to 2% drop at , or 0.5 Gy shift in .Conclusions:
This study conceptually demonstrated that a TCP model incorporating the effects of tumor cell density variation and setup uncertainty may be used to guide radiation treatment planning.
38(2011); http://dx.doi.org/10.1118/1.3531564View Description Hide DescriptionPurpose:
The equivalent field size (EFS) method is widely used to estimate dose of nonstandard fields, such as elongated or arbitrary shaped fields, for both central axis and off axis points. However, its application is limited to fluence maps with uniform intensity. In this work, we propose a generalized EFS (GEFS) for nonuniform fluence maps and present a formula for GEFS-based dose calculation.Methods:
A parallel-beam dose table (PDT) consisting of central axis dose of circular fields of various diameters at various depths is used to define scatter contributions, based on which we calculate GEFS of any given fluence map. Such obtained GEFS, together with the radiological depth and PDT, is used to determine the dose at the point of interest. We tested GEFS-based dose calculation on a water phantom for both uniform and nonuniform fluence maps and compared the results with those by the collapsed cone convolution/superposition (CCCS) method.Results:
For all test cases, the gamma index is less than 1 based on the 3%/1 mm criteria for more than 96% of the calculated points. Larger discrepancies mainly occur along the field edges in the buildup region.Conclusions:
A generalized equivalent field size for nonuniform fluence maps was proposed and its application in calculating dose at any point was presented and verified through comparison with the CCCS method.
Comparing performance of many-core CPUs and GPUs for static and motion compensated reconstruction of C-arm CT data38(2011); http://dx.doi.org/10.1118/1.3525838View Description Hide DescriptionPurpose:
Interventional reconstruction of 3-D volumetric data from C-arm CT projections is a computationally demanding task. Hardwareoptimization is not an option but mandatory for interventional image processing and, in particular, for image reconstruction due to the high demands on performance. Several groups have published fast analytical 3-D reconstruction on highly parallel hardware such as GPUs to mitigate this issue. The authors show that the performance of modern CPU-based systems is in the same order as current GPUs for static 3-D reconstruction and outperforms them for a recent motion compensatedimage reconstruction algorithm.Methods:
This work investigates two algorithms: Static 3-D reconstruction as well as a recent motion compensated algorithm. The evaluation was performed using a standardized reconstruction benchmark, RABBITCT, to get comparable results and two additional clinical data sets.Results:
The authors demonstrate for a parametric B-spline motion estimation scheme that the derivative computation, which requires many write operations to memory, performs poorly on the GPU and can highly benefit from modern CPU architectures with large caches. Moreover, on a 32-core Intel® Xeon® server system, the authors achieve linear scaling with the number of cores used and reconstruction times almost in the same range as current GPUs.Conclusions:
Algorithmic innovations in the field of motion compensated image reconstruction may lead to a shift back to CPUs in the future. For analytical 3-D reconstruction, the authors show that the gap between GPUs and CPUs became smaller. It can be performed in less than 20 s (on-the-fly) using a 32-core server.