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Impact of Image Noise on Gamma Index Calculation

Purpose: The Gamma Index defines an asymmetric metric between the evaluated image and the reference image. It provides a quantitative comparison that can be used to indicate sample-wised pass/fail on the agreement of the two images. The Gamma passing/failing rate has become an important clinical evaluation tool. However, the presence of noise in the evaluated and/or reference images may change the Gamma Index, hence the passing/failing rate, and further, clinical decisions. In this work, we systematically studied the impact of the image noise on the Gamma Index calculation. Methods: We used both analytic formulation and numerical calculations in our study. The numerical calculations included simulations and clinical images. Three different noise scenarios were studied in simulations: noise in reference images only, in evaluated images only, and in both. Both white and spatially correlated noises of various magnitudes were simulated. For clinical images of various noise levels, the Gamma Index of measurement against calculation, calculation against measurement, and measurement against measurement, were evaluated. Results: Numerical calculations for both the simulation and clinical data agreed with the analytic formulations, and the clinical data agreed with the simulations. For the Gamma Index of measurement against calculation, its distribution has an increased mean and an increased standard deviation as the noise increases. On the contrary, for the Gamma index of calculation against measurement, its distribution has a decreased mean and stabilized standard deviation as the noise increases. White noise has greater impact on the Gamma Index than spatially correlated noise. Conclusions: The noise has significant impact on the Gamma Index calculation and the impact is asymmetric. The Gamma Index should be reported along with the noise levels in both reference and evaluated images. Reporting of the Gamma Index with switched roles of the images as reference and evaluated images or some composite metrics would be a good practice.

SU‐E‐T‐691: On the Use of Multiple Beam Angles to Minimize the Impact of High Density Fiducial Markers in the Prostate Proton Radiotherapy

Purpose: Fiducial markers are commonly used in prostate radiotherapy to improve accuracy of target localization. However, in proton therapy, since the proton range is sensitive to the material it travels through, under‐dose to the prostate has been reported in conventional passive scattering treatment and 3D‐modulation based intensity modulated proton therapy (IMPT), in the presence of high density fiducial markers inside the prostate. This study investigated the ability of using multiple beam angles to minimize the dosimetric impact of fiducial markers in 3D‐modulation and distal edge tracking (DET) based IMPT. Methods: CTimages of a typical prostate patient with three gold markers (3mm by 1mm, density = 19.3 g/cc) were used in this study. 2‐field lateral and 4‐field box type 3D‐modulation proton treatment plans as well as DET plans with evenly spaced 18, 10, and 6 beam angles were generated to deliver 70Gy to 95% of the PTV. Geant4 Monte Carlo code was used for dose calculation. The plan was performed on images with fiducial markers artificially removed. Then the delivered dose distribution was calculated with fiducial markers present in the patient. The dose distributions between the planed and delivered were then compared to evaluate the efficacy of using multiple beam angles to minimize the dosimetric deviations. The tumor control probability (TCP) was also used to quantify the dose variation. Results: The preliminary result shows all the 3D‐modulation and DET plans yielded equivalent PTV coverage. The planned and delivered D98% of prostate was 68.68Gy vs. 68.32Gy in 18‐field DET, 67.83Gy vs. 65.53Gy in 10‐field DET, and 67.82Gy vs. 58.19Gy in 2‐field 3D‐Modulation. No significant dose change to rectum and bladder was observed. Conclusions: With high density fiducial markers present in the target, multiple beam angles are recommended in proton treatment plans to avoid significant under‐dose to the target.

SU-F-T-667: Development and Validation of Dose Calculation for An Open-Source KV Treatment Planning System for Small Animal Radiotherapy

PURPOSE An open-source, convolution/superposition based kV-treatment planning system(TPS) was developed for small animal radiotherapy from previously existed in-house MV-TPS. It is flexible and applicable to both step and shoot and helical tomotherapy treatment delivery. For initial commissioning process, the dose calculation from kV-TPS was compared with measurements and Monte Carlo(MC) simulations. METHODS High resolution, low energy kernels were simulated using EGSnrc user code EDKnrc, which was used as an input in kV-TPS together with MC-simulated x-ray beam spectrum. The Blue Water™ homogeneous phantom (with film inserts) and heterogeneous phantom (with film and TLD inserts) were fabricated. Phantom was placed at 100cm SSD, and was irradiated with 250 kVp beam for 10mins with 1.1cm × 1.1cm open field (at 100cm) created by newly designed binary micro-MLC assembly positioned at 90cm SSD. Gafchromic™ EBT3 film was calibrated in-phantom following AAPM TG-61 guidelines, and were used for measurement at 5 different depths in phantom. Calibrated TLD-100s were obtained from ADCL. EGS and MNCP5 simulation were used to model experimental irradiation set up calculation of dose in phantom. RESULTS Using the homogeneous phantom, dose difference between film and kV-TPS was calculated: mean(x)=0.9%; maximum difference(MD)=3.1%; standard deviation(σ)=1.1%. Dose difference between MCNP5 and kV-TPS was: x=1.5%; MD=4.6%; σ=1.9%. Dose difference between EGS and kV-TPS was: x=0.8%; MD=1.9%; σ=0.8%. Using the heterogeneous phantom, dose difference between film and kV-TPS was: x=2.6%; MD=3%; σ=1.1%; and dose difference between TLD and kV-TPS was: x=2.9%; MD=6.4%; σ=2.5%. CONCLUSION The inhouse, open-source kV-TPS dose calculation system was comparable within 5% of measurements and MC simulations in both homogeneous and heterogeneous phantoms. The dose calculation system of the kV-TPS is validated as a part of initial commissioning process for small animal radiotherapy. The kV-TPS has the potential for accurate dose calculation for any kV treatment or imaging modalities.

SU-C-16A-07: Sculpting Isodose Lines: Design of An Internally Shielded Tandem for Cervical Cancer Brachytherapy

PURPOSE With the prescription method moving from point A to 3D volume based in cervical cancer HDR brachytherapy, the traditional pear-shaped isodose lines are desired to be sculptured to conform to the irregular shaped target. The standard single channel tandem cannot generate asymmetric isodose lines. Most of the directionally shielded sources proposed in literature are challenging to manufacture and operate. In this study, we proposed a novel internally shielded tandem applicator design which gave users more freedom to manipulate isodose lines while planning. METHODS The proposed tandem design has one centrally located lead cylindrical rod of 8 mm in diameter serving as the internal shield. Multiple source channels with the diameter of 2 mm are evenly spaced and engraved on the central cylindrical rod. The overall diameter of the tandem with polymer encapsulation was kept to be 10 mm. Various number of channels and engraving depths have been tested in the design process. Geant4 Monte Carlo toolkit was used for dose calculation assuming a Varian VS2000 source was placed inside the applicator. A Monte Carlo based planning system has been developed in-house to generate brachytherapy plans. Test plans by using this internally shielded tandem were generated for 3 clinical cases. RESULTS Water phantom results shown the dose distribution from a VS2000 source in the tandem was strongly distorted towards one direction due to the presence of shielding material. Conformal plans with asymmetric isodose distributions around the tandem can be generated by optimizing dwell times in different channels. CONCLUSION An effective and easy-to-use internally shielded tandem was developed. It gave user the freedom to sculpt isodose lines to generate conformal plans for cervical cancer brachytherapy.

SU-E-T-08: A Convolution Model for Head Scatter Fluence in the Intensity Modulated Field

PURPOSE To efficiently calculate the head scatter fluence for an arbitrary intensity-modulated field with any source distribution using the source occlusion model. METHOD The source occlusion model with focal and extra focal radiation (Jaffray et al, 1993) can be used to account for LINAC head scatter. In the model, the fluence map of any field shape at any point can be calculated via integration of the source distribution within the visible range, as confined by each segment, using the detector eyes view. A 2D integration would be required for each segment and each fluence plane point, which is time-consuming, as an intensity-modulated field contains typically tens to hundreds of segments. In this work, we prove that the superposition of the segmental integrations is equivalent to a simple convolution regardless of what the source distribution is. In fact, for each point, the detector eyes view of the field shape can be represented as a function with the origin defined at the points pinhole reflection through the center of the collimator plane. We were thus able to reduce hundreds of source plane integration to one convolution. We calculated the fluence map for various 3D and IMRT beams and various extra-focal source distributions using both the segmental integration approach and the convolution approach and compared the computation time and fluence map results of both approaches. RESULTS The fluence maps calculated using the convolution approach were the same as those calculated using the segmental approach, except for rounding errors (<0.1%). While it took considerably longer time to calculate all segmental integrations, the fluence map calculation using the convolution approach took only ∼1/3 of the time for typical IMRT fields with ∼100 segments. CONCLUSIONS The convolution approach for head scatter fluence calculation is fast and accurate and can be used to enhance the online process.

SU‐E‐T‐475: An Accurate Linear Model of Tomotherapy MLC‐Detector System for Patient Specific Delivery QA

PURPOSE An accurate leaf fluence model can be used in applications such as patient specific delivery QA and in-vivo dosimetry for TomoTherapy systems. It is known that the total fluence is not a linear combination of individual leaf fluence due to leakage-transmission, tongue-and-groove, and source occlusion effect. Here we propose a method to model the nonlinear effects as linear terms thus making the MLC-detector system a linear system. METHODS A leaf pattern basis (LPB) consisting of no-leaf-open, single-leaf-open, double-leaf-open and triple-leaf-open patterns are chosen to represent linear and major nonlinear effects of leaf fluence as a linear system. An arbitrary leaf pattern can be expressed as (or decomposed to) a linear combination of the LPB either pulse by pulse or weighted by dwelling time. The exit detector responses to the LPB are obtained by processing returned detector signals resulting from the predefined leaf patterns for each jaw setting. Through forward transformation, detector signal can be predicted given a delivery plan. An equivalent leaf open time (LOT) sinogram containing output variation information can also be inversely calculated from the measured detector signals. Twelve patient plans were delivered in air. The equivalent LOT sinograms were compared with their planned sinograms. RESULTS The whole calibration process was done in 20 minutes. For two randomly generated leaf patterns, 98.5% of the active channels showed differences within 0.5% of the local maximum between the predicted and measured signals. Averaged over the twelve plans, 90% of LOT errors were within +/-10 ms. The LOT systematic error increases and shows an oscillating pattern when LOT is shorter than 50 ms. CONCLUSION The LPB method models the MLC-detector response accurately, which improves patient specific delivery QA and in-vivo dosimetry for TomoTherapy systems. It is sensitive enough to detect systematic LOT errors as small as 10 ms.

An automatic dose verification system for adaptive radiotherapy for helical tomotherapy

Purpose: During a typical 5-7 week treatment of external beam radiotherapy, there are potential differences between planned patients anatomy and positioning, such as patient weight loss, or treatment setup. The discrepancies between planned and delivered doses resulting from these differences could be significant, especially in IMRT where dose distributions tightly conforms to target volumes while avoiding organs-at-risk. We developed an automatic system to monitor delivered dose using daily imaging. Methods: For each treatment, a merged image is generated by registering the daily pre-treatment setup image and planning CT using treatment position information extracted from the Tomotherapy archive. The treatment dose is then computed on this merged image using our in-house convolution-superposition based dose calculator implemented on GPU. The deformation field between merged and planning CT is computed using the Morphon algorithm. The planning structures and treatment doses are subsequently warped for analysis and dose accumulation. All results are saved in DICOM format with private tags and organized in a database. Due to the overwhelming amount of information generated, a customizable tolerance system is used to flag potential treatment errors or significant anatomical changes. A web-based system and a DICOM-RT viewer were developed for reporting and reviewing the results. Results: More than 30 patients were analysed retrospectively. Our in-house dose calculator passed 97% gamma test evaluated with 2% dose difference and 2mm distance-to-agreement compared with Tomotherapy calculated dose, which is considered sufficient for adaptive radiotherapy purposes. Evaluation of the deformable registration through visual inspection showed acceptable and consistent results, except for cases with large or unrealistic deformation. Our automatic flagging system was able to catch significant patient setup errors or anatomical changes. Conclusions: We developed an automatic dose verification system that quantifies treatment doses, and provides necessary information for adaptive planning without impeding clinical workflows.

Fast in vivo volume dose reconstruction via Reference Dose Perturbation

Purpose: Accurate on-line reconstruction of in-vivo volume dose that accounts for both machine and patient discrepancy is not clinically available. We present a simple reference-dose-perturbation algorithm that reconstructs in-vivo volume dose fast and accurately. Methods: We modelled the volume dose as a function of the fluence map and density image. Machine (output variation, jaw/leaf position errors, etc.) and patient (setup error, weight loss, etc.) discrepancies between the plan and delivery were modelled as perturbation of the fluence map and density image, respectively. Delivered dose is modelled as perturbation of the reference dose due to change of the fluence map and density image. We used both simulated and clinical data to validate the algorithm. The planned dose was used as the reference. The reconstruction was perturbed from the reference and accounted for output-variations and the registered daily image. The reconstruction was compared with the ground truth via isodose lines and the Gamma Index. Results: For various plans and geometries, the volume doses were reconstructed in few seconds. The reconstruction generally matched well with the ground truth. For the 3%/3mm criteria, the Gamma pass rates were 98% for simulations and 95% for clinical data. The differences mainly appeared on the surface of the phantom/patient. Conclusions: A novel reference-dose-perturbation dose reconstruction model is presented. The model accounts for machine and patient discrepancy from planning. The algorithm is simple, fast, yet accurate, which makes online in-vivo 3D dose reconstruction clinically feasible.

MO‐D‐108‐04: Validation of a Simple Portal Dose Calculation Model for Plan QA and In‐Vivo Dosimetry

PURPOSE To validate a simple portal dose calculator for plan QA and in-vivo dosimetry. METHODS We model portal dose as a function of the fluence map, patient attenuation, patient scatter and portal response. Fluence maps are reconstructed using control-point sequence in RTPlan. Patient attenuation is calculated via ray-tracing through the patient CT. The effect of patient scatter and portal response is modeled by convolution, where the convolution kernel is derived from the commissioning measurements of different beam energies, different field sizes, different phantom thickness, and different source to image distances (SIDs). For various IMRT/3D plan, phantom and patient geometry, both in-air and in-transit portals were calculated. The calculations were compared with portal measurements. The Gamma Index of measurements against predicted portals with various dose difference (DD) criteria (1%, 2%, 3%, 4%, 5%, etc) and distance to agreement (DTA) criteria (1 mm, 2 mm, 3 mm, 4 mm, 5 mm, etc) were calculated. The Gamma pass rates of various DD and DTA criteria were evaluated and formed a Gamma table. RESULTS For various IMRT beams, the head, body and lung phantoms, the in-air and in-transit portal calculations matched well with portal measurements. The Gamma pass rates for in-air portal are above 97% for 2 mm, 2% criteria and above 99% for 3 mm, 3% criteria. The Gamma pass rates for in-transit portal were above 90% for 2 mm, 2% criteria and above 95% for 3 mm, 3% criteria. CONCLUSION The simple portal dose calculation model is validated via phantom measurements. The model could be used in clinic for in-air and intransit portal prediction.

SU‐E‐T‐109: Calypso RF Interference On Portal Images and a Physical Filter Solution

PURPOSE Portal measurement is becoming an important tool for in vivo dosimetric verification, and Calypso provides real-time tracking capability; however, when both work simultaneously, large interference arises for portal measurement. The purpose of this study is to investigate the interference of Calypso on portal measurement and mitigation of the interference by applying aluminum shielding over portal panels. METHODS For the same IMRT field and phantom setup, we acquired portal measurements at every 15 degree gantry angle, without and with Calypso, and for those measurements with Calypso, we also acquired portal measurements without and with aluminum shielding over the portal panels. The aluminum shielding consists of a layer of aluminum foil of 0.1 mm thickness covering the portal panel. The measurements without Calypso and without aluminum shielding were regarded as the reference images. All other measurements were regarded as the test images. We measured the deviation of the test images from the reference images by the amplitude difference and using the Gamma Index (3%, 3 mm). RESULTS With Calypso interference and without aluminum shielding, the signals are larger than the reference, and in some unfavorable gantry angles, the signals can be as much as 15% larger. With aluminum shielding, the interference was much reduced to ∼3% for those unfavorable angles, and the Gamma passing rate achieves 95% for most of the angles. CONCLUSION The Calypso interference on portal measurements is gantry angle dependent due to panel orientation and proximity with respect to the Calypso transducer. Shielding on the portal panel can largely reduce electronic interference, and it is anticipated that with an improved complete shielding over the entire portal panel, the interference could be further reduced.