bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐E‐T‐478: Geometrical Splitting Technique to Improve the Computational Efficiency in Monte Carlo Calculations for Proton Therapy
Authors: Ramos‐Mendez J , Perl J , Faddegon B , Paganetti H
Published: June 2012

Purpose: To implement a geometry based particle splitting technique in order to reduce the computation time when generating treatment head phase space files for proton therapy dose calculations using Monte Carlo (MC) calculations and to validate the doses generated from these phase spaces with respect to reference simulations. Methods: The treatment nozzles at the Francis H Burr Proton Therapy Center (FHBPTC) were modeled with a new MC tool (‘TOPAS’ based on Geant4). For variance reduction purposes, two particle‐splitting planes were implemented, one downstream of the second ionization chamber the other upstream of the aperture of the nozzle and phase spaces in IAEA format were recovered. The symmetry of the proton beam was considered to split the particles by a factor of 4 per plane. Split particles were randomly positioned at different locations rotated around the beam axis. The computational efficiency was calculated and dose profiles compared for a voxelized water phantom for different treatment fields for both the reference and optimized simulations. Depth‐dose curves and beam profiles were analyzed. Dose calculation in patients was simulated to compare the performance. Results: Normalized computational efficiency between 10 and 14.5 were reached. Percentage difference between dose profiles in water for simulations done with and without particle splitting is within the statistical precision of 2%, 1 standard deviation. Dose distributions for the realistic patient treatment show differences up to 4% in the regions of interest, within 2 standard deviations. Conclusions: By considering the cylindrically symmetric region of the nozzle and the splitting planes separated at strategic distance, considerable time reduction can be achieved without compromising the precision. This approach will reduce the time for phase space simulations for clinical MC dose calculation at FHBPTC by more than a factor of 10.
SU‐E‐T‐493: Accelerated Monte Carlo Methods for Photon Dosimetry Using a Dual‐GPU System and CUDA
Authors: Liu T , Ding A , Xu X
Published: June 2012

Purpose: To develop a Graphics Processing Unit (GPU) based Monte Carlo (MC) code that accelerates dose calculations on a dual‐GPU system. Methods: We simulated a clinical case of prostate cancer treatment. A voxelized abdomen phantom derived from 120 CT slices was used containing 218×126×60 voxels, and a GE LightSpeed 16‐MDCT scanner was modeled. A CPU version of the MC code was first developed in C++ and tested on Intel Xeon X5660 2.8GHz CPU, then it was translated into GPU version using CUDA C 4.1 and run on a dual Tesla m2090 GPU system. The code was featured with automatic assignment of simulation task to multiple GPUs, as well as accurate calculation of energy‐ and material‐ dependent cross‐sections. Results: Double‐precision floating point format was used for accuracy. Doses to the rectum, prostate, bladder and femoral heads were calculated. When running on a single GPU, the MC GPU code was found to be ×19 times faster than the CPU code and ×42 times faster than MCNPX. These speedup factors were doubled on the dual‐GPU system. The dose Result was benchmarked against MCNPX and a maximum difference of 1% was observed when the relative error is kept below 0.1%. Conclusions: A GPU‐based MC code was developed for dose calculations using detailed patient and CT scanner models. Efficiency and accuracy were both guaranteed in this code. Scalability of the code was confirmed on the dual‐GPU system.
SU‐E‐T‐498: A Preliminary Monte Carlo Simulation Study of the Varian TrueBeam Linear Accelerator
Authors: Johnson D , Chen Y , Schnell E , Ahmad S
Published: June 2012

Purpose: To benchmark the quality of Monte Carlo simulation results with the commissioning data for a Varian TrueBeam accelerator. Methods: IAEA phase space files of a 6MV TrueBeam accelerator provided by Varian were implemented using GEANT4 Monte Carlo code. The present application consisted of upper and lower jaws and a cubic water phantom of 0.125 cubic meters in volume. Both radial and transverse dose profiles (in 5 different depths) and a central axis percentage depth dose (PDD) curve were recorded in the phantom. Field sizes of as small as 4×4 cm2 and as large as 30×30 cm2 were simulated with 2.0E9 incident particles each. The results were then compared with our commissioning data performed in a Wellhoffer Blue Phantom with a 0.13cc ion‐chamber and a 0.8×0.8mm diode. Results: The GEANT4 simulated PDD curve compared favorably within ∼2% against the measured ion‐chamber PDD for all field sizes and against the measured diode PDD for all fields less then 20×20cm2. The simulated in‐plane and cross‐plane profiles compared well within 2 mm at the 50% level against the measured profiles for all field sizes. Conclusions: These results demonstrate the feasibility of utilizing Monte‐Carlo simulated beam data in the commissioning of a linear accelerator. The increasing speed and capability of the desktop computer will Result in the adoption of Monte‐ Carlo techniques for dosimetric calculations.
SU‐E‐T‐508: A Novel Method of Heterogeneity Compensation for the Convolution / Superposition Algorithm
Authors: Jacques R , McNutt T
Published: June 2012

Purpose: We developed a better method of accounting for the effects of heterogeneity in convolution algorithms. We integrated this method into our GPU‐accelerated, multi‐energetic convolution/superposition (C/S) implementation. In doing so, we have created a new dose algorithm: heterogeneity compensated superposition (HCS). Methods: Convolution in the spherical density‐scaled distance space, a.k.a. C/S, has proven to be a good estimator of the dose deposited in a homogeneous volume. However, near heterogeneities electron disequilibrium occurs, leading to faster fall‐off and re‐buildup than predicted by C/S. We propose to filter the actual patient density in a position and direction sensitive manner, allowing the dose deposited near interfaces to be increased or decreased relative to traditional C/S. We implemented the effective density function as a multivariate first‐order recursive filter. We compared HCS against traditional C/S using the ICCR 2000 Monte‐Carlo accuracy benchmark, 23 similar accuracy benchmarks and 5 patient cases. For the patient cases, we created custom routines capable of using the discrete material mappings used by Monte‐Carlo. C/S normally considers each voxel to be a mixture of materials based on a piecewise‐linear density look‐up table. Results: Multi‐energetic HCS increased the dosimetric accuracy for the vast majority of voxels; in many cases near Monte‐Carlo results were achieved. HCS improved the mean Van Dyk error by 0.79 (% of Dmax or mm) on average for the patient volumes; reducing the mean error from 1.93%|mm to 1.14%|mm. We found a mean error difference of up to 0.30 %|mm between linear and discrete material mappings. Very low densities (i.e. <0.1 g / cm3) remained problematic, but may be solvable with a better filter function. Conclusions: We have developed a novel dose calculation algorithm based on the principals of C/S that better accounts for the electron disequilibrium caused by patient heterogeneity. This work was funded in part by the National Science Foundation under Grant No. EEC9731748, in part by Johns Hopkins University internal funds and in part by Elekta.
SU‐E‐T‐510: Calculation of High Resolution and Material‐Specific Photon Energy Deposition Kernels
Authors: Huang J , Childress N , Kry S
Published: June 2012

Purpose: To calculate photon energy deposition kernels (EDKs) used for convolution/superposition dose calculation at a higher resolution than the original Mackie et al. 1988 kernels and to calculate material‐specific kernels that describe how energy is transported and deposited by secondary particles when the incident photon interacts in a material other than water. Methods: The high resolution EDKs for various incident photon energies were generated using the EGSnrc user‐code EDKnrc, which forces incident photons to interact at the center of a 60 cm radius sphere of water. The simulation geometry is essentially the same as the original Mackie calculation but with a greater number of scoring voxels (48 radial, 144 angular bins). For the material‐specific EDKs, incident photons were forced to interact at the center of a 1 mm radius sphere of material (lung, cortical bone, silver, or titanium) surrounded by a 60 cm radius water sphere, using the original scoring voxel geometry implemented by Mackie et al. 1988 (24 radial, 48 angular bins). Results: Our Monte Carlo‐calculated high resolution EDKs showed excellent agreement with the Mackie kernels, with our kernels providing more information about energy deposition close to the interaction site. Furthermore, our EDKs resulted in smoother dose deposition functions due to the finer resolution and greater number of simulation histories. The material‐specific EDK results show that the angular distribution of energy deposition is different for incident photons interacting in different materials. Calculated from the angular dose distribution for 300 keV incident photons, the expected polar angle for dose deposition () is 28.6° for water, 33.3° for lung, 36.0° for cortical bone, 44.6° for titanium, and 58.1° for silver, showing a dependence on the material in which the primary photon interacts. Conclusions: These high resolution and material‐specific EDKs have implications for convolution/superposition dose calculations in heterogeneous patient geometries, especially at material interfaces.
SU‐E‐T‐513: Clinical Implementation of a GPU Accelerated Pencil Beam Dose Calculation Algorithm
Authors: Chen H , Xiao Z , Du D , Yang D , Mutic S , Li H
Published: June 2012

Purpose: This work reports a clinical implementation of a GPU accelerated pencil beam dose calculation algorithm (GPU‐PB). Methods: Model parameters were determined using in‐house scripts written in MATLAB. Dose distributions in a water phantom were calculated using a Pinnacle TPS for various open field sizes. Lateral profiles at 2‐mm incremental depths were used to calculate PB kernel parameters. Weighted sum of squares were used for least‐squares parameter fitting utilizing a Levenberg‐marquardt algorithm. Weightings were adjusted based on goodness of fitting and in accordance with field size to suppress deviations due to horn effects. The scale factor was fitted iteratively. The calculated doses for two patient cases were analyzed with a 3D gamma method (3%/3mm). Results: Excellent agreement between Pinnacle calculation and GPU‐PB calculation was achieved regarding PDD, profiles and output factor. For a head‐neck 10‐field step‐and‐shoot IMRT case, gamma passing rate was over 99% and maximum absolute dose value is 75.6 Gy vs. 73.9 Gy, differing by 2.3%. Similar results were obtained for a SBRT lung case. Gamma passing rate is a function of PB kernel cut‐off distance and beamlet resolution. It appears that if the highest accuracy is desired, a resolution of 10 mm or better in the direction parallel to MLC travel and a cutoff distance of 10 cm or better should be used. The calculation time increases with both cut‐off distance and beamlet resolution. For example, GPU calculation time is 1.36 seconds for 5 cm cut‐off distance, and increases to 4.84 s for 15 cm cut‐off distance. Conclusions: A GPU accelerated PB dose calculation algorithm has been implemented using clinical measurement data. Excellent agreement with Pinnacle TPS has been achieved. Beamlet size and PB cut‐off distance should be chosen according to desired dose calculation accuracy and speed.
SU‐E‐T‐518: Dose Perturbation at Air‐Tissue Interface in Proton Beam Therapy
Authors: Das I , Moskvin V , Coutinho L , Cheng C
Published: June 2012

Purpose: The loss of transverse equilibrium along the central axis of the proton beam in the presence of the air/tissue interface creates dose perturbation that has not been fully quantified. This gets magnified in small fields that are used for lung and patch up fields. Air‐tissue dose perturbation is studied in a phantom and verified with Monte Carlo simulation. Methods: Air channel of variable thickness that could be found in trachea, larynx and small lesions in lung were studied. To mimic air/tissue interface a simple phantom geometry was used with EBT films. The results confirmed the presence of dose perturbations which were investigating using water phantom in reference condition (10×10 cm2 field, 16 cm range and 10 cm SOBP). A variable air column was created in the front of the phantom. A small volume ion chamber was used to collect high resolution profile data in water. The simulation was performed with 3×10̂7 particles with the Monte Carlo particle transport code FLUKA version 2011.2.10 with cut off energy of 100keV. Results: The dose perturbations were visible on film and quantified by ion chamber measurements in water. Dose perturbations at air‐tissue interfaces are shown to be significant (−20 to +30%). The measured profiles show significant discontinuities in dose up to +30% in low density medium. The magnitude is dependence on the location and width of the air gap. Under and over dose perturbation pattern is not predicted by treatment planning system (TPS) due to proton transport algorithm and calculation bin. The Monte Carlo simulation confirmed our measured data. Conclusions: Significant dose perturbation exists with high‐dose region in low density medium that is not predicated by TPS. The magnitude and shape is position and gap size dependent. This study provides the presence of dosimetric discontinuities that should be evaluated clinically at interfaces.
SU‐E‐T‐519: Experimental Evaluation of Deterministic Acuros XB Radiation Transport Algorithm for Heterogeneity Dose Calculation Using the Radiological Physics Center's Lung Phantom
Authors: Han T , Mourtada F , Repchak R , Tonigan J , Mikell J , Howell R , Salehpour M , Molineu A , Followill D
Published: June 2012

Purpose: To evaluate the heterogeneity corrected dose calculations from the Acuros XB (AXB), a novel deterministic dose calculation algorithm based on grid‐based Boltzmann transport equation solver (GBBS), for IMRT and VMAT plans. Methods: The Radiological Physics Center's lung phantom was used to create clinically equivalent IMRT and VMAT plans (RapidArc) with the Eclipse planning system 10.0 that were delivered using a Varian 23 iX. Absolute doses and relative dose distributions were measured with thermoluminescent dosimeters (TLDs) and radiochromic film. The measured dose distributions were compared with calculated doses from both AXB (11.0.3) and AAA (10.0.24) dose calculation algorithms. The AXB calculated dose‐to‐water and dose‐to‐medium were both compared to measurements. Gamma analysis (±7%/4mm, ±5%/3mm, and ±3%/3mm) was used to quantify correspondence between AXB dose distributions and the film measurements. The computation time between AAA and AXB were also evaluated. Results: For TLD point doses, both AAA and AXB heterogeneity corrected dose calculations are within 5% inside the PTV for both IMRT and VMAT plans. The agreements observed between the measured and calculated doses for both AXB dose reporting methods are better than those observed with the AAA algorithm. The gamma analysis showed that the differences between AAA, AXB and film measurement met the RPC ±7%/4 mm criteria. The percent of pixels passing rate for both the AXB dose to medium and AXB dose to water are higher than AAA. The computation time between AAA and AXB are comparable for IMRT plans but AXB is significantly faster (4 times) than AAA for VMAT plans. Conclusions: The AXB implemented in the Eclipse planning system calculates a more accurate heterogeneity corrected dose than the AAA algorithm as compared to measurement in lung and improve the calculation speed for VMAT radiotherapy. Work supported by grants CA10953, CA81647, 2R44CA105806‐02, CA016672 (NCI, DHHS).
SU‐E‐T‐524: The Effect of CT Contrast on CyberKnife Treatment Planning
Authors: Kim H , Chang A , Park Y , Ye S
Published: June 2012

Purpose: To investigate the effect of CT contrast enhancement (CE) on the 3D dose distributions of non‐coplanar small field beams in the CyberKnife (CK) treatment planning system. Methods: Twenty patients treated by pre‐CE CT plans were recruited to this retrospective plan study. Their post‐CE CT plans were based on the pre‐CE CT plan data and calculated using the same MU and beam paths in either Ray‐Tracing or Monte Carlo (MC) algorithms. The differences in doses of the beam path and the reference point and in DVHs of target and OARs between the pre‐CE CT and the post‐CE CT plans were compared. The minimum dose, the maximum dose, the mean dose, and the dose received to 50% of the target and OARs volumes, and the target volume coverage were also compared. Results: The dose differences between the pre‐CE and post‐CE plans in a single beam path were less than 50 cGy in both calculation algorithms. At the center of target volume, it was 1.9% (maximum 6.2%) in Ray‐Tracing and 1.5% (maximum 4.0%) in MC, with respect to the prescription dose. The post‐CE plans showed on average 2% decrease in the OAR maximum dose (maximum 6.4% in Ray‐Tracing and 5.8% in MC). Regardless of the algorithms, the dose to the target and the target volume coverage of post‐CE plans were on average reduced by 2% and 1 %, respectively, with a maximum reduction of 6.1% (in Ray‐Tracing) in the minimum target dose. Conclusions: The CK treatment plan using the post‐CE CT could generally result in a few % dose differences from the pre‐CE CT plan. However, it could be more than 6%, depending on the target positions in the body and the calculation algorithms. Thus the post‐CE CT in CK treatment plans should be used with a caution.
SU‐E‐T‐537: Photon Beam Modeling and Verification of Collapsed Cone Convolution Algorithm for Dose Calculation in a Radiation Treatment Planning System
Authors: Jung J , Cho W , Lee J , Kim D , Kim M , Suh T
Published: June 2012

Purpose: The aim of this study is to evaluate the accuracy the collapsed cone convolution (CCC) algorithm for dose calculation in a radiation treatment planning system (TPS). Methods: We modeled various photon beams for various setup conditions in a radiation treatment planning system (CorePLANTM, Seoul C&J, Korea). The beam models were generated at various set‐up conditions such as open beam or wedged beam, 6 MV or 15 MV beam and field sizes from 4×4 cm2 to 40 × 40 cm2. Each beam model was optimized by spectrum modeling from measured percent depth dose (PDD) data, dose profile modeling from a measured profile at a specific depth (10 cm) data. Dose calculation was performed using conventional CCC algorithm. All measured data were acquired from a Clinac 21EX (Varian Medical System, Palo Alto, CA, USA) linear accelerator with the setting of SSD = 100 cm. All calculated PDD and dose profiles at various depths from generated beam models were compared to the measured data. Results: Calculated dose data from each beam model showed good agreements within 2% of difference to the measured PDD and within 3% dose profiles at various depths. Some regions such as penumbra region at 20 × 20 cm2 field size and horn region at wedge field showed dose discrepancies over 3%. The results of PDD at all situations showed well agreement with measured data under the 10×10 cm2 field size. For wedged cases, however, under the 5 cm depths, some inconsistency at penumbra region were appeared. Conclusions: In this study, we verified the accuracy of CCC algorithm in the TPS. Calculated results by our implemented algorithm was well satisfied with measured dose at small field size (〈20 7 times; 20 cm2). Our next study will perform to compensate theses inconsistencies.
SU‐E‐T‐540: Evaluation of Forced‐Density Corrected Dose Calculation for Lung Cancer Treatment
Authors: Li J , Xiao Y , Harrison A , Yu Y
Published: June 2012

Purpose: The study was aimed to evaluate the accuracy of lung cancer treatment dose calculations using a bulk electron density for forced‐density correction, in situations where CT images are acquired in other institutions and the information of CT number to electron density (CT‐to‐ED) conversion is unavailable for conducting pixel density correction. Methods: Eleven 3D SBRT lung cases were studied. Treatment plans were generated initially with pixel‐density correction using a known CT‐to‐ED conversion, in a CMS XIO treatment planning system using superposition algorithm. The plans were re‐calculated with contour‐based density correction, i.e., forced‐density correction: a density of 0.26 g/cm3 was assigned to lung structures, which was a population average taken from a literature, and unit density was assigned to other structures. Monitor units were kept the same in both plans. Results: The doses calculated using forced‐density correction were compared against those calculated using pixel‐density correction. The absolute percentage differences of PTV D95, PTV mean dose, and V20, among the 11 cases, were 2.49±1.69%, 1.69±1.5%, and 1.88±2.36%, respectively. Conclusions: The results showed that the dose calculation using the bulk density and forced density correction generated dose distributions close to those calculated using pixel‐density correction and actual CT‐to‐ED conversion. None
SU‐E‐T‐543: Beam Attenuation Characteristics of Treatment Couches
Authors: Cochran B , Kim G , Rice R
Published: June 2012

Purpose: Measure photon beam attenuation characteristics of the Varian EXACT, Varian IGRT treatment couches and two CIVCO Universal extensions; and assess accuracy of Varian's Eclipse treatment planning system in modeling the beam attenuation of each couch. Methods: Dose Measurements were taken using a Farmer ion chamber inside a cylindrical acrylic phantom. They were taken for two photon energies (6MV and 15MV), at three different field sizes, for various gantry angles through the couch. EXACT couch was tested both with the adjustable rails pushed to the outside of the couch, and pushed to the center of the couch. IGRT couch was divided by thickness into three sections. Effects on surface dose were measured using a Tissue Maximum Ratio or Percent Depth Dose curve. CIVCO extensions were CT scanned for inclusion in the planning system. All measurements were modeled in the Eclipse treatment planning system for comparison. Results: Maximum attenuation was measured at 6MV with the smallest field for all couch setups. The EXACT couch produced a maximum attenuation of 19.2% and a surface dose increase of 47% of Dmax through the couch. Maximum attenuation for the IGRT couch and both CIVCO extensions were between 6–8%. Through the couch, the IGRT couch showed a surface dose increase of 29% of Dmax,; the CIVCO extensions produced a surface dose increase of 33% and 7% of Dmax. Maximum difference between measured and planned dose was 7%, for the EXACT couch, 1.9% for the IGRT couch and 2.4% for both CIVCO extensions. Conclusions: These treatment couches were shown to affect delivered and surface dose. Including the couch structure during treatment planning can account for the couch attenuation in most cases, but some attenuation values are underestimated in the planning software. Largest effects are for oblique treatment angles using low energy and small field sizes.
SU‐E‐T‐544: Commissioning and Clinical Evaluation of a Secondary Check Software for 3D Conformal and IMRT Treatment Plans
Authors: Foong P , Looe H , Poppe B
Published: June 2012

Purpose: The increasing complexities of the geometry of 3D radiation treatment plans possess challengesto the monitor unit (MU) and dose verification in clinical routine. In this work, the commissioningof the DIAMOND software (PTW‐Freiburg Germany) for two Siemens linear accelerators(Primus & Artiste) along with the evaluation of its performance is described. Methods: DIAMOND employs the modified Clarkson integration method for dose computation and a pointeye‐view (PEV) method for scatter calculation on collimators by a geometrical back‐projectinginto the collimation system from the view of the source. During the commissioning process, themachine data (geometrical set up) and dosimetry base data such as the percentage depth dose(PDD), head scatter factor Sc as well as total scatter factor Sc,p, off‐axis profiles are entered into the software. A comprehensive validation process is performed following the provided protocol.For evaluation purposes, twelve 3D conformal treatment plans and two prostate IMRT plans arecalculated with DIAMOND and the results are compared to the values from the treatmentplanning system (TPS). Results: The deviations of the MU for 3D conformal treatment plans computed with the DIAMONDsoftware are within ±3%. For IMRT plan verification, the dose at a point in the target volume iscomputed for every treatment beam, with deviations within 0.40% to 3.28%. The typical time forsingle dose point verification is less than a minute, thus minimizing the clinical workload of theverification process. For dose matrices calculation at certain plane, a relative longercomputation time is needed depending on a field dimension. Conclusions: In this work, we have demonstrated the ability of the DIAMOND software to compute MU anddose at a point for 3D conformal and IMRT plans. Its speed and accuracy implies that DIAMOND can be implemented as independent secondary check software in the clinical routine.
SU‐E‐T‐547: Rotating Shield Brachytherapy (RSBT) for Cervical Cancer
Authors: Yang W , Kim Y , Liu Y , Wu X , Flynn R
Published: June 2012

Purpose: To assess rotating shield brachytherapy (RSBT) delivered with the electronic brachytherapy (eBT) source comparing to intracavitary (IC) and intracavitary plus supplemental interstitial brachytherapy (IC+IS BT) delivered with conventional isotope radiation source. Method and Materials: IC, IC+IS and RSBT plan was simulated for 5 patients with advanced cervical cancer (>40cc). One BT plan for each patient (fraction 1) guided by magnetic resonance imaging (MRI) was used in our treatment planning system (TPS). A bio‐ and MRI‐compatible polycarbonate (Makrolon Rx3158) intrauterine applicator was simulated for IC and RSBT, and the vienna applicator was simulated for IC+IS BT. 192Ir was used as the radiation source of IC and IC+IS BT; Xoft AxxentTM eBT source was used for RSBT. A 0.5 mm thick tungsten shield was used for RS‐BT with different azimuthal and zenith angles. The total dose for each plan was escalated as the external beam radiation therapy (EBRT) plus BT times fraction number (5 in our case). Results: RSBT and IC+IS BT had higher dose conformity in terms of D90 than IC BT for all the patients. The advantage of RSBT over IC+IS BT was dependent on the shield emission angle, tumor shape and tandem applicator location. The delivery time of RSBT was increased as finer emission angle was selected. Conclusions:RSBT is a less‐invasive potential alternative to conventional IC and IC+IS BT for treating bulky (>40cc) cervical cancer. RSBT can provide better treatment outcome with clinically acceptable increased delivery time if proper emission angle is selected based on the tumor shape and tandem applicator location. supported in part by NSF grants CCF‐0830402 and CCF‐0844765; and the NIH grant K25‐CA123112, and American Cancer Society seed grant (IRG‐77‐004‐31).
SU‐E‐T‐549: On Importance of Accurate Treatment Couch Modeling in SmartArc VMAT Plans
Authors: Ter‐Antonyan R , Frieda D
Published: June 2012

Purpose: We investigate the impact of a treatment couch and its modeling in a treatment planning system on accurate dose delivery in Volumetric Modulated Arc Therapy (VMAT). Methods: A cone‐beam CT of a Varian couch on a Varian Clinac 21EX unit, consisting of a carbon‐fiber imaging couch top and supporting rails, was acquired, and a couch model was created in Philips Pinnacle 9.0 TPS based on the geometry of the couch top and the rails. The densities of the modeled couch top and the rails were based on the Hounsfield Unit and CT number‐to‐density information obtained from the CBCT scan. The densities were then adjusted based on the ion chamber measurements of a beam transmitting through the couch posteriorly at different gantry angles varying 1–5 degrees. SmartArc VMAT plans for patient treatment with and without the modeled couch were then generated and dose distributions were verified using the IBA MatriXX 2D ion chamber array. Results: We found that depending on the gantry angle the beam can be attenuated by up to 17% when going through the supporting rails, and up to 5% when passing through the couch top. Because of this, dose distributions of SmartArc plans were not accurate and did not pass the dose verification criteria without accurate modeling of the treatment couch. Adding the couch model remedies this problem and avoids underdosing the target. Conclusions: We showed that the impact of a treatment couch in radiation therapy can be significant, and it is essential to include an accurate model of the couch in the treatment planning system, particularly for SmartArc VMAT plans in Philips Pinnacle TPS.
SU‐E‐T‐554: PTV to Skin Proximity for Head and Neck IMRT Treatment Planning
Authors: Price R , Koren S , Hossain M , Veltchev I , Galloway T , Flanagan P , Ma C
Published: June 2012

Purpose: The goal of this work was to evaluate measured vs. calculated surface dose as a function of PTV‐to‐skin proximity and calculation matrix oxel size, determine effects on plan quality, and provide parameters and levels of uncertainty for clinical use. Methods: A right‐sided CTV with the lateral border 5mm from the surface was delineated on the CT data of a head and neck phantom. A 5mm PTV was generated except laterally where distances of 0–5mm were used. A 7‐field IMRT plan was generated using the Eclipse TPS. Optimization was performed where 95% of the PTV receives the prescription dose using a matrix size of 2mm3. Dose calculations were repeated for grid sizes of 1, 3 and 5mm3. For each plan nine point dose values were obtained just inside the phantom surface, corresponding to a 2cm2 grid near the central target region. Nine ultra‐thin TLDs were placed on the phantom surface corresponding to the grid. Measured and calculated dose values were compared. Conformality, homogeneity and target coverage were compared. Results: Surface dose is over‐estimated by the TPS by 21 and 8% for 5 and 3mm3 voxels, respectively and accurately predicted for 2mm3 voxels. A voxel size of 1mm3 results in underestimation of 13%. Conformality improves with increasing PTV to skin distance and a CI of unity results for grid sizes of 1–3mm3 between 4 and 4.5mm. Hot spot decreases as the PTV moves away from the surface and falls below 110% at 4mm. Underdosage worsens as the PTV approaches the skin. Conclusions: For decreasing PTV‐to‐skin distance with this TPS, isodose conformality decreases, ‘hot spot’ increases, and target coverage degrades. Surface dose is accurately predicted for a 2mm3 voxel size, while choosing a finer or coarser grid results in underestimation or overestimation, respectively. All of the above appear to hold for VMAT.
MO‐F‐BRA‐06: Systematic Evaluation of a Deformable Image Registration Algorithm from a Commercial Software Package
Authors: Stanley N , Zhong H , Glide‐Hurst C , Chetty I , Movsas B
Published: June 2012

Purpose: As adaptive radiotherapy (ART) becomes more efficient for clinical use, verifying the accuracy of deformable image registration (DIR) is necessary. This study presents a method to evaluate a commercial DIR software package systematically for ART implementation. Methods: We developed multiple computational phantoms to evaluate Velocity Advanced Imaging (VelocityAI, B‐spline‐based algorithm) software. Phantoms were developed with a finite element method (FEM), from CT images of four lung cancer patients by simulating different diaphragm deformations, and also from the CT image of a prostate patient by modeling expansion of the bladder volume. CBCT noise in the simulated prostate phantom was included using a 3D‐noise‐power spectrum. FEM‐based displacement vectors used in the phantom construction served as a gold standard to evaluate the performance of VelocityAI's algorithms at each voxel in the image volume. In addition to computational phantoms, a deformable, physical phantom was developed to validate VelocityAI using automatically tracked landmarks. Results: VelocityAI performed well in high and low‐contrast regions. Average displacement errors range from 0.8–2.6mm, depending on the patient anatomy, magnitude of displacement and target site. With the computational lung phantoms, average errors were between 0.9–2.6mm, and in the physical phantom they were between 0.8–1.9mm. In the prostate phantom, average errors were between 1.0–1.9mm in the prostate, 1.9–2.4mm in the rectum and 1.8–2.1mm across the entire patient volume. Regions where the displacement was large tended to have more registration errors, especially when they bordered rigid structures like bone. Conclusions: VelocityAI (B‐spline‐based) outperforms the Demons algorithm in regions of largely deformed, homogenous tissue. The default parameter setting of VelocityAI is nearly optimal and the CBCT noise has no significant impact on its performance. VelocityAI can be used for DIR of lung and prostate CT images when errors on the order of 2.6 mm are acceptable. The research was supported by NIH/NCI R01CA140341.
MO‐F‐213CD‐01: GPU‐Based Monte Carlo Methods for Accelerating Radiographic and CT Imaging Dose Calculations: Feasibility and Scalability
Authors: Liu T , Ding A , Xu X
Published: June 2012

Purpose: To develop a Graphics Processing Unit (GPU) based Monte Carlo (MC) code that uses a dual‐GPU system to accelerate radiographic simulation and CT imaging dose calculations. Methods: We considered two clinical cases, a chest x‐ray radiography and an abdominal CT scan. In the first case, a voxelized VIP‐Man phantom with detailed 3D anatomical information was used and an x‐ray beam of 120kVp was simulated. In the second case, a voxelized abdomen phantom derived from 120 CT slices was used, and a GE LightSpeed 16‐MDCT scanner was modeled. The CPU version of the MC code was written in C++ and run on Intel Xeon X5660 2.8GHz CPU, then translated into GPU code written in CUDA C and tested on a dual Tesla m2090 GPU system. The code was featured with automatic assignment of simulation task to multiple GPUs, as well as accurate calculation of energy‐ and material‐dependent cross‐sections. Results: Double‐precision floating point format was used for accuracy. In the first case, radiograph formation was simulated and doses to the organs listed in ICRP‐60 were calculated. When running on a single GPU, the MC GPU code was found to be x13 times faster than the CPU code and x29 times faster than MCNPX. In the second case, doses to the rectum, prostate, bladder and femoral heads were calculated. A speedup of x19 was observed compared to CPU code. These speedup factors were doubled on the dual‐GPU system. The imaging dose was benchmarked against MCNPX and a maximum difference of 1% was observed when the relative error is kept below 0.1%. Conclusions: A GPU‐based MC code was developed to simulate radiography and calculate imaging dose using detailed patient and CT scanner models. Efficiency and accuracy were both guaranteed in this code. Scalability of the code was confirmed on the dual‐GPU system.
MO‐F‐213CD‐02: A Series of NURBS and MicroCT‐Based Reference Skeletal Dosimetry Models of Pediatric and Adolescent Skeleton
Authors: Bolch W , Pafundi D , Wayson M , Lee C , Watchman C
Published: June 2012

Purpose: The hematopoietically active tissues of the skeleton are an important target tissue for dosimetric analysis, both in terms of diagnostic risk optimization and evaluating treatment efficacy. In the work presented here, a recently published dosimetry model of the adult is extended to all pediatric ages of the ICRP reference series. Methods: NURBS/PM‐based computational phantoms of the ICRP 89 reference newborn, 1‐year, 5‐year, 10‐year, and 15‐year male and female were constructed from image segmentation of age and gender‐matched CT images. Bone samples were subsequently acquired from autopsy harvest of two female newborns and one 18‐year male subject. Individual bones were collected and segmented following high‐resolution ex‐vivo CT to yield fractional volumes of cortical bone and spongiosa. Cored samples of spongiosa were later imaged under microCT to yield fractional volumes of bone trabeculae and marrow tissues and to provide a 3D geometry for radiation transport. Previously acquired pathlength distributions of trabecular spongiosa for a 1.7‐year and 9‐year child were used to supplement the dataset. Results: A comprehensive set of absorbed fractions of energy for internally emitted electrons are presented for active and shallow marrow targets in all bones, all ages, and over the energies 1 keV to 10 MeV. These electron absorbed fractions were then used to assemble photon fluence‐to‐dose response functions permitting detailed marrow dosimetry for both externally incident (e.g., CT) and internally emitted (e.g., nuclear medicine) photons by bone site and subject age. Techniques and issues for patient‐specific adjustments are discussed. Conclusions: Marrow dosimetry is a critical component to nuclear medicine risk assessment and therapy treatment planning. This work provides state‐of‐the‐art methods for pediatric marrow dosimetry that supplants those developed previously for simpler stylized models of the pediatric skeleton. R01 CA116743, R01 CA96441, DE‐FG07‐06ID14773
MO‐F‐213CD‐05: Establishing a Follow‐Up Process for Angiographic Patients Receiving an Estimated Entrance Skin Dose in Excess of 5 Gy
Authors: Kanal K , Dickinson R , Zamora D , Cohen W , Valji K , Stewart B
Published: June 2012

Purpose: To establish a follow‐up process for angiography patients estimated to receive an entrance skin dose (ESD) in excess of 5 Gy. Methods: A look‐up table showing the estimated ESD corresponding to incremental displayed air kerma (AK) values was posted within each angio suite. Patients receiving a cumulative AK value corresponding to an ESD exceeding 5 Gy are identified by the technologist. The technologist notifies the diagnostic physics section (DPS) which calculates a more accurate estimation of the ESD by taking into account system and exam‐specific estimated table height and attenuation, backscatter, and mean energy absorption coefficient. The DPS then generates and sends a standard notification alert to the attending physician including case information, estimated ESD, and potential tissue effects. Hospital staff follows‐up with the patient via phone to discuss possible skin effects and the location of where those effects may be observed. The patient is asked to call the clinic if any skin redness or epilation in the area of exposure is observed. Results: In the past 4 months, 15 cases greater than 5 Gy ESD were identified across the different services using the angio suite. Of the 15 cases, the neuro radiology interventional group had the maximum number of cases at 10 (median: 5.2 Gy, max: 7.3 Gy) while the vascular surgery group had 2 cases (median: 7.1 Gy, max: 7.6 Gy) and the vascular interventional group had 3 cases (median: 5.7 Gy, max: 6.8 Gy). All cases received follow‐up. No deterministic effects were observed in these cases as of yet. Conclusions: Establishing a follow‐up procedure for angiography patients receiving an ESD > 5 Gy is essential to anticipate possible skin injury. This is good patient safety practice which falls in line with our institution's patient first initiative.
MO‐G‐BRA‐03: Semi‐Automatic Segmentation of the Prostate Midgland in Magnetic Resonance Images Using Shape and Local Appearance Similarity Analysis
Authors: Shahedi M , Fenster A , Romagnoli C , Ward A D
Published: June 2012

Purpose: To design, develop and test a semi‐automatic segmentation method for the prostate midgland on T2W magnetic resonance (MR) images acquired using an endorectal (ER) coil, based on inter‐subject prostate shape and local boundary appearance similarity.Method and Materials: We used T2W prostate MR images of 33 subjects acquired using an ER coil. From each image, we extracted the closest mid‐gland axial slice to the verumontanum. We partitioned the images into training and test sets using leave‐one‐out cross‐validation. We used the training images to define a point distribution model (PDM) describing shape variability as well as 36 circular ‘mean intensity patches' characterizing the inter‐subject local appearance at anatomically‐defined boundary locations. We chose a patch radius of 17mm based on our assessment of segmentation error, using the mean absolute boundary distance (MAD), on a subset of 13 images during a systematic radius search from 5mm to 25mm. For each test image, we defined 36 homologous rays emanating from the centre of the prostate. We used a radial‐based‐search strategy to translate each mean intensity patch along its corresponding ray and computed the normalized cross‐correlation (NCC) between the mean patch and the underlying patch in the test image at each point. We chose the point with the highest NCC along each ray. We then used the PDM to regularize the selected points. To compare the algorithm's segmentation to manual delineations performed by one operator, we calculated the MAD and Dice similarity coefficient (DSC). Results: We measured a MAD of 1.6 +/− 1.0mm, and a DSC of 89 +/− 6% between the semi‐automatically segmented contours and the manually‐delineated reference standard. Conclusions: NCC of local prostate boundary regions with a learned mean boundary appearance may be suitable for boundary localization and subsequent refinement using a PDM on T2W MR images acquired using an ER coil.
MO‐G‐BRA‐06: Three‐Stage Compton Camera Image Resolution Losses Due Detector Effects
Authors: Mackin D , Polf J , Peterson S , Beddar S
Published: June 2012

Purpose: Three‐stage Compton camera (CC) imaging systems may provide an effective means of detecting and imaging the prompt gamma (PG) radiation emitted from tissue during proton therapy. For these systems to be clinically viable, the resolution of the CC images should be better than the treatment planning margins, ∼3 mm. Detector inaccuracies in the measured gamma interaction positions and energy depositions and Doppler broadening limit the image resolution. The purpose of our study was to determine the inherent limitations of the image resolution due to these detector effects Methods: Using the Geant4 Monte Carlo software program, a three‐stage CC detecting radiation from both gamma point sources and prompt gamma radiation emitted during proton therapy was simulated. To simulate the effects of the detector energy and spatial resolutions an independent, identically distributed random uncertainty term was applied to the MC calculated energy depositions and interaction positions. Doppler broadening was modeled using Geant4. The effects were then measured using the distance of closest approach and the point of closest approach. Results: The major effect of Doppler broadening was to increase the size of the tails of the spatial distributions. Its effect on the full width at half maximum of the point spread function was less than 2 mm. The lateral and energy resolutions of the detector stages moderately enhanced the effects of Doppler broadening, but for the tested values of detector depth resolution, no additional effect was evident. The detector effects changed the depth of the distal falloff for PG emitted during proton therapy by < 1 mm. Conclusions: The spatial and energy resolutions of three‐stage CCs are sufficient for PG imaging during proton therapy. However, because the detector effects render many of the detected gammas unusable for reconstruction, the overall efficiency of the CC is reduced. This work was supported by the National Institutes of Health through award number R21CA137362 from the National Cancer Institute.
TU‐A‐211‐01: ACR MRI Accreditation: Process and Pitfalls
Authors: Price R
Published: June 2012

ACR MRI accreditation was initiated in 1996. Over the years, the accreditation process and requirements have evolved in order to keep pace with the rapidly changing MRI technology. This presentation will briefly review changes that have been initiated in response to the changing technology along with the evolving changes in the responsibilities of the Medical Physicist for providing advice and support for system performance, quality assurance and safety. Specific differences in the accreditation process between conventional general‐purpose MRI systems and specialty (extremity) systems used for anatomical imaging and systems used for breast imaging will be discussed. Additional requirements that have resulted from the Medicare Improvements for Patients and Providers Act (MIPPA), common reasons for accreditation failure and the anticipated changes and updates to the 2004 ACR MRI Quality Control Manual will also be discussed.

Learning Objectives:

1. Review the responsibilities of the Medical Physicist in the accreditation process

2. Discuss the CMS/MIPPA accreditation requirements as of January 1, 2012.

3. Review differences in breast and specialty (extremity) system accreditation

4. Discuss common reasons for accreditation failure

5. Discuss anticipated changes and updates in the ACR MRI Quality Control Manual
TU‐A‐BRCD‐01: Image Acquisition and Processing for Adaptive Radiotherapy
Authors: Kessler M , Siewerdsen J , Sonke J
Published: June 2012

Adaptive radiotherapy involves acquisition and processing of image data from numerous devices at various time scales. In contrast to conventional radiotherapy which mainly involves unidirectional flow of image data in fairly large steps ‐ from the scanners to the planners to the treatment machines ‐ adaptive radiotherapy involves a bidirectional and iterative flow of image data.

Acquisition and processing of multimodality imaging data for the initial planning step is now common place: x‐ray CT provides accurate geometric and density information; MR provides exquisite soft tissue contrast; and nuclear medicine imaging provides unique metabolic information. Data from these modalities are registered and integrated to help define the tumor volume(s) and surrounding healthy tissues. These modalities along with ultrasound and optical imaging can also provide 4D and time series image data to help model moment‐to‐moment physiologic motion and day‐to‐day functional and anatomic changes. Tracking these changes between and during treatment fractions is a key aspect of the adaptive radiotherapy process. Image processing steps required to support this tracking and adaptation of treatments include deformable image registration, contour propagation, and dose accumulation. The outputs of these steps are used to support decisions about maintaining or adapting the current treatment plan.

This course will provide an overview of the different imaging devices used to support adaptive radiotherapy and highlight the benefits and challenges of each. The details of the various image processing tools used to extract, combine, and analyze the information from the various imaging data will also be presented. Finally, the effective use of these devices and tools for the adaptive radiotherapy process will be described and elucidated using several clinical examples.

Learning Objectives:

1. Understand the basic principles of image acquisition used in adaptive radiotherapy

2. Understand the basic principles of image processing used in adaptive radiotherapy

3. Understand how imaging and image processing are used in the adaptive radiotherapy process