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SU-E-P-03: Implementing a Low Dose Lung Screening CT Program Meeting Regulatory Requirements

Purpose: To provide information pertaining to IROC Houston QA Center's (RPC) credentialing process for institutions participating in NCI-sponsored clinical trials. Purpose: Provide guidance to the Radiology Departments with the intent of implementing a Low Dose CT Screening Program using different CT Scanners with multiple techniques within the framework of the required state regulations. Method: State Requirements for the purpose of implementing a Low Dose CT Lung Protocol required working with the Radiology and Pulmonary Department in setting up a Low Dose Screening Protocol designed to reduce the radiation burden to the patients enrolled. Radiation dose measurements (CTDIvol) for various CT manufacturers (Siemens16, Siemens 64, Philips 64, and Neusoft128) for three different weight based protocols. All scans were reviewed by the Radiologist. Prior to starting a low dose lung screening protocol, information had to be submitted to the state for approval. Performing a Healing Arts protocol requires extensive information. This not only includes name and address of the applicant but a detailed description of the disease, the x-ray examination and the population to be examined. The unit had to be tested by a qualified expert using the technique charts. The credentials of all the operators, the supervisors and the Radiologists had to be submitted to the state. Results: All the appropriate documentation was sent to the state for review. The measured results between the Low Dose Protocol versus the default Adult Chest Protocol showed that there was a dose reduction of 65% for small (100-150 lb.) patient, 75% for the Medium patient (151-250 lbs.), and a 55% reduction for the Large patient ( over 250 lbs.). Conclusion: Measured results indicated that the Low Dose Protocol indeed lowered the screening patient's radiation dose and the institution was able to submit the protocol to the State's regulators.

60 APPLIED LIFE SCIENCES↗

TH-A-19A-11: Validation of GPU-Based Monte Carlo Code (gPMC) Versus Fully Implemented Monte Carlo Code (TOPAS) for Proton Radiation Therapy: Clinical Cases Study

Purpose: For proton radiation therapy, Monte Carlo simulation (MCS) methods are recognized as the gold-standard dose calculation approach. Although previously unrealistic due to limitations in available computing power, GPU-based applications allow MCS of proton treatment fields to be performed in routine clinical use, on time scales comparable to that of conventional pencil-beam algorithms. This study focuses on validating the results of our GPU-based code (gPMC) versus fully implemented proton therapy based MCS code (TOPAS) for clinical patient cases. Methods: Two treatment sites were selected to provide clinical cases for this study: head-and-neck cases due to anatomical geometrical complexity (air cavities and density heterogeneities), making dose calculation very challenging, and prostate cases due to higher proton energies used and close proximity of the treatment target to sensitive organs at risk. Both gPMC and TOPAS methods were used to calculate 3-dimensional dose distributions for all patients in this study. Comparisons were performed based on target coverage indices (mean dose, V90 and D90) and gamma index distributions for 2% of the prescription dose and 2mm. Results: For seven out of eight studied cases, mean target dose, V90 and D90 differed less than 2% between TOPAS and gPMC dose distributions. Gamma index analysis for all prostate patients resulted in passing rate of more than 99% of voxels in the target. Four out of five head-neck-cases showed passing rate of gamma index for the target of more than 99%, the fifth having a gamma index passing rate of 93%. Conclusion: Our current work showed excellent agreement between our GPU-based MCS code and fully implemented proton therapy based MC code for a group of dosimetrically challenging patient cases.

60 APPLIED LIFE SCIENCES↗

TH-E-BRE-07: Development of Dose Calculation Error Predictors for a Widely Implemented Clinical Algorithm

Purpose: Several shortcomings of the current implementation of the analytic anisotropic algorithm (AAA) may lead to dose calculation errors in highly modulated treatments delivered to highly heterogeneous geometries. Here we introduce a set of dosimetric error predictors that can be applied to a clinical treatment plan and patient geometry in order to identify high risk plans. Once a problematic plan is identified, the treatment can be recalculated with more accurate algorithm in order to better assess its viability. Methods: Here we focus on three distinct sources dosimetric error in the AAA algorithm. First, due to a combination of discrepancies in smallfield beam modeling as well as volume averaging effects, dose calculated through small MLC apertures can be underestimated, while that behind small MLC blocks can overestimated. Second, due the rectilinear scaling of the Monte Carlo generated pencil beam kernel, energy is not properly transported through heterogeneities near, but not impeding, the central axis of the beamlet. And third, AAA overestimates dose in regions very low density (< 0.2 g/cm{sup 3}). We have developed an algorithm to detect the location and magnitude of each scenario within the patient geometry, namely the field-size index (FSI), the heterogeneous scatter index (HSI), and the lowdensity index (LDI) respectively. Results: Error indices successfully identify deviations between AAA and Monte Carlo dose distributions in simple phantom geometries. Algorithms are currently implemented in the MATLAB computing environment and are able to run on a typical RapidArc head and neck geometry in less than an hour. Conclusion: Because these error indices successfully identify each type of error in contrived cases, with sufficient benchmarking, this method can be developed into a clinical tool that may be able to help estimate AAA dose calculation errors and when it might be advisable to use Monte Carlo calculations.

60 APPLIED LIFE SCIENCES↗

SU-C-BRD-02: A Team Focused Clinical Implementation and Failure Mode and Effects Analysis of HDR Skin Brachytherapy Using Valencia and Leipzig Surface Applicators

Purpose: and Leipzig applicators (VLAs) are single-channel brachytherapy surface applicators used to treat skin lesions up to 2cm diameter. Source dwell times can be calculated and entered manually after clinical set-up or ultrasound. This procedure differs dramatically from CT-based planning; the novelty and unfamiliarity could lead to severe errors. To build layers of safety and ensure quality, a multidisciplinary team created a protocol and applied Failure Modes and Effects Analysis (FMEA) to the clinical procedure for HDR VLA skin treatments. Methods: team including physicists, physicians, nurses, therapists, residents, and administration developed a clinical procedure for VLA treatment. The procedure was evaluated using FMEA. Failure modes were identified and scored by severity, occurrence, and detection. The clinical procedure was revised to address high-scoring process nodes. Results: Several key components were added to the clinical procedure to minimize risk probability numbers (RPN): -Treatments are reviewed at weekly QA rounds, where physicians discuss diagnosis, prescription, applicator selection, and set-up. Peer review reduces the likelihood of an inappropriate treatment regime. -A template for HDR skin treatments was established in the clinical EMR system to standardize treatment instructions. This reduces the chances of miscommunication between the physician and planning physicist, and increases the detectability of an error during the physics second check. -A screen check was implemented during the second check to increase detectability of an error. -To reduce error probability, the treatment plan worksheet was designed to display plan parameters in a format visually similar to the treatment console display. This facilitates data entry and verification. -VLAs are color-coded and labeled to match the EMR prescriptions, which simplifies in-room selection and verification. Conclusion: Multidisciplinary planning and FMEA increased delectability and reduced error probability during VLA HDR Brachytherapy. This clinical model may be useful to institutions implementing similar procedures.

60 APPLIED LIFE SCIENCES↗

Initial implementation of the conversion from the energy-subtracted CT number to electron density in tissue inhomogeneity corrections: An anthropomorphic phantom study of radiotherapy treatment planning

Purpose: To achieve accurate tissue inhomogeneity corrections in radiotherapy treatment planning, the authors had previously proposed a novel conversion of the energy-subtracted computed tomography (CT) number to an electron density (ΔHU–ρ{sub e} conversion), which provides a single linear relationship between ΔHU and ρ{sub e} over a wide range of ρ{sub e}. The purpose of this study is to present an initial implementation of the ΔHU–ρ{sub e} conversion method for a treatment planning system (TPS). In this paper, two example radiotherapy plans are used to evaluate the reliability of dose calculations in the ΔHU–ρ{sub e} conversion method. Methods: CT images were acquired using a clinical dual-source CT (DSCT) scanner operated in the dual-energy mode with two tube potential pairs and an additional tin (Sn) filter for the high-kV tube (80–140 kV/Sn and 100–140 kV/Sn). Single-energy CT using the same DSCT scanner was also performed at 120 kV to compare the ΔHU–ρ{sub e} conversion method with a conventional conversion from a CT number to ρ{sub e} (Hounsfield units, HU–ρ{sub e} conversion). Lookup tables for ρ{sub e} calibration were obtained from the CT image acquisitions for tissue substitutes in an electron density phantom (EDP). To investigate the beam-hardening effect on dosimetric uncertainties, two EDPs with different sizes (a body EDP and a head EDP) were used for the ρ{sub e} calibration. Each acquired lookup table was applied to two radiotherapy plans designed using the XiO TPS with the superposition algorithm for an anthropomorphic phantom. The first radiotherapy plan was for an oral cavity tumor and the second was for a lung tumor. Results: In both treatment plans, the performance of the ΔHU–ρ{sub e} conversion was superior to that of the conventional HU–ρ{sub e} conversion in terms of the reliability of dose calculations. Especially, for the oral tumor plan, which dealt with dentition and bony structures, treatment planning with the HU–ρ{sub e} conversion exhibited apparent discrepancies between the dose distributions and dose–volume histograms (DVHs) of the body-EDP and head-EDP calibrations. In contrast, the dose distributions and DVHs of the body-EDP and head-EDP calibrations coincided with each other almost perfectly in the ΔHU–ρ{sub e} conversion for 100–140 kV/Sn. The difference between the V{sub 100}’s (the mean planning target volume receiving 100% of the prescribed dose; a DVH parameter) of the body-EDP and head-EDP calibrations could be reduced to less than 1% using the ΔHU–ρ{sub e} conversion, but exceeded 11% for the HU–ρ{sub e} conversion. Conclusions: The ΔHU–ρ{sub e} conversion can be implemented for currently available TPS’s without any modifications or extensions. The ΔHU–ρ{sub e} conversion appears to be a promising method for providing an accurate and reliable inhomogeneity correction in treatment planning for any ill-conditioned scans that include (i) the use of a calibration EDP that is nonequivalent to the patient’s body tissues, (ii) a mismatch between the size of the patient and the calibration EDP, or (iii) a large quantity of high-density and high-atomic-number tissue structures.

60 APPLIED LIFE SCIENCES↗

SU-E-T-10: A Clinical Implementation and the Dosimetric Evidence in High Dose Rate Vaginal Multichannel Applicator Brachytherapy

Purpose: The multichannel cylindrical applicator has a distinctive modification of the traditional single channel cylindrical applicator. The novel multichannel applicator has additional peripheral channels that provide more flexibility both in treatment planning process and outcomes. To protect by reducing doses to adjacent organ at risk (OAR) while maintaining target coverage with inverse plan optimization are the goals for such novel Brachytherapy device. Through a series of comparison and analysis of reults in more than forty patients who received HDR Brachytherapy using multichannel vaginal applicator, this procedure has been implemented in our institution. Methods: Multichannel planning was CT image based. The CTV of 5mm vaginal cuff rind with prescribed length was well reconstructed as well as bladder and rectum. At least D95 of CTV coverage is 95% of prescribed dose. Multichannel inverse plan optimization algorithm not only shapes target dose cloud but set dose avoids to OAR’s exclusively. The doses of D2cc, D5cc and D5; volume of V2Gy in OAR’s were selected to compare with single channel results when sole central channel is only possibility. Results: Study demonstrates plan superiorly in OAR’s doe reduction in multi-channel plan. The D2cc of the rectum and bladder were showing a little lower for multichannel vs. single channel. The V2Gy of the rectum was 93.72% vs. 83.79% (p=0.007) for single channel vs. multichannel respectively. Absolute reduced mean dose of D5 by multichannel was 17 cGy (s.d.=6.4) and 44 cGy (s.d.=15.2) in bladder and rectum respectively. Conclusion: The optimization solution in multichannel was to maintain D95 CTV coverage while reducing the dose to OAR’s. Dosimetric advantage in sparing critical organs by using a multichannel applicator in HDR Brachytherapy treatment of the vaginal cuff is so promising and has been implemented clinically.

60 APPLIED LIFE SCIENCES↗

SU-E-T-121: Analyzing the Broadening Effect On the Bragg Peak Due to Heterogeneous Geometries and Implementing User-Routines in the Monte-Carlo Code FLUKA in Order to Reduce Computation Time

Purpose: Aim of this study was to analyze the modulating, broadening effect on the Bragg Peak due to heterogeneous geometries like multi-wire chambers in the beam path of a particle therapy beam line. The effect was described by a mathematical model which was implemented in the Monte-Carlo code FLUKA via user-routines, in order to reduce the computation time for the simulations. Methods: The depth dose curve of 80 MeV/u C12-ions in a water phantom was calculated using the Monte-Carlo code FLUKA (reference curve). The modulating effect on this dose distribution behind eleven mesh-like foils (periodicity ∼80 microns) occurring in a typical set of multi-wire and dose chambers was mathematically described by optimizing a normal distribution so that the reverence curve convoluted with this distribution equals the modulated dose curve. This distribution describes a displacement in water and was transferred in a probability distribution of the thickness of the eleven foils using the water equivalent thickness of the foil’s material. From this distribution the distribution of the thickness of one foil was determined inversely. In FLUKA the heterogeneous foils were replaced by homogeneous foils and a user-routine was programmed that varies the thickness of the homogeneous foils for each simulated particle using this distribution. Results: Using the mathematical model and user-routine in FLUKA the broadening effect could be reproduced exactly when replacing the heterogeneous foils by homogeneous ones. The computation time was reduced by 90 percent. Conclusion: In this study the broadening effect on the Bragg Peak due to heterogeneous structures was analyzed, described by a mathematical model and implemented in FLUKA via user-routines. Applying these routines the computing time was reduced by 90 percent. The developed tool can be used for any heterogeneous structure in the dimensions of microns to millimeters, in principle even for organic materials like lung tissue.

60 APPLIED LIFE SCIENCES↗

SU-E-T-329: Dosimetric Impact of Implementing Metal Artifact Reduction Methods and Metal Energy Deposition Kernels for Photon Dose Calculations

Purpose: To investigate two strategies for reducing dose calculation errors near metal implants: use of CT metal artifact reduction methods and implementation of metal-based energy deposition kernels in the convolution/superposition (C/S) method. Methods: Radiochromic film was used to measure the dose upstream and downstream of titanium and Cerrobend implants. To assess the dosimetric impact of metal artifact reduction methods, dose calculations were performed using baseline, uncorrected images and metal artifact reduction Methods: Philips O-MAR, GE’s monochromatic gemstone spectral imaging (GSI) using dual-energy CT, and GSI imaging with metal artifact reduction software applied (MARs).To assess the impact of metal kernels, titanium and silver kernels were implemented into a commercial collapsed cone C/S algorithm. Results: The CT artifact reduction methods were more successful for titanium than Cerrobend. Interestingly, for beams traversing the metal implant, we found that errors in the dimensions of the metal in the CT images were more important for dose calculation accuracy than reduction of imaging artifacts. The MARs algorithm caused a distortion in the shape of the titanium implant that substantially worsened the calculation accuracy. In comparison to water kernel dose calculations, metal kernels resulted in better modeling of the increased backscatter dose at the upstream interface but decreased accuracy directly downstream of the metal. We also found that the success of metal kernels was dependent on dose grid size, with smaller calculation voxels giving better accuracy. Conclusion: Our study yielded mixed results, with neither the metal artifact reduction methods nor the metal kernels being globally effective at improving dose calculation accuracy. However, some successes were observed. The MARs algorithm decreased errors downstream of Cerrobend by a factor of two, and metal kernels resulted in more accurate backscatter dose upstream of metals. Thus, these two strategies do have the potential to improve accuracy for patients with metal implants in certain scenarios. This work was supported by Public Health Service grants CA 180803 and CA 10953 awarded by the National Cancer Institute, United States of Health and Human Services, and in part by Mobius Medical Systems.

60 APPLIED LIFE SCIENCES↗

SU-E-T-465: Implementation of An Automated Collision Detection Program Using Open Source Software for the Pinnacle Treatment Planning System

Purpose: Potential collisions between the gantry head and the patient or table assembly are difficult to detect in most treatment planning systems. We have developed and implemented a novel software package for the representation of potential gantry collisions with the couch assembly at the time of treatment planning. Methods: Physical dimensions of the Varian Edge linear accelerator treatment head were measured and reproduced using the Visual Python display package. A script was developed for the Pinnacle treatment planning system to generate a file with the relevant couch, gantry, and isocenter positions for each beam in a planning trial. A python program was developed to parse the information from the TPS and produce a representative model of the couch/gantry system. Using the model and the Visual Python libraries, a rendering window is generated for each beam that allows the planner to evaluate the possibility of a collision. Results: Comparison against heuristic methods and direct verification on the machine validated the collision model generated by the software. Encounters of <1 cm between the gantry treatment head and table were visualized as collisions in our virtual model. Visual windows were created depicting the angle of collision for each beam, including the anticipated table coordinates. Visual rendering of a 6 arc trial with multiple couch positions was completed in under 1 minute, with network bandwidth being the primary bottleneck. Conclusion: The developed software allows for quick examination of possible collisions during the treatment planning process and helps to prevent major collisions prior to plan approval. The software can easily be implemented on future planning systems due to the versatility and platform independence of the Python programming language. Further integration of the software with the treatment planning system will allow the possibility of patient-gantry collision detection for a range of treatment machines.

60 APPLIED LIFE SCIENCES↗

SU-E-T-467: Implementation of Monte Carlo Dose Calculation for a Multileaf Collimator Equipped Robotic Radiotherapy System

Purpose: To improve the treatment efficiency and capabilities for full-body treatment, a robotic radiosurgery system has equipped with a multileaf collimator (MLC) to extend its accuracy and precision to radiation therapy. To model the MLC and include it in the Monte Carlo patient dose calculation is the goal of this work. Methods: The radiation source and the MLC were carefully modeled to consider the effects of the source size, collimator scattering, leaf transmission and leaf end shape. A source model was built based on the output factors, percentage depth dose curves and lateral dose profiles measured in a water phantom. MLC leaf shape, leaf end design and leaf tilt for minimizing the interleaf leakage and their effects on beam fluence and energy spectrum were all considered in the calculation. Transmission/leakage was added to the fluence based on the transmission factors of the leaf and the leaf end. The transmitted photon energy was tuned to consider the beam hardening effects. The calculated results with the Monte Carlo implementation was compared with measurements in homogeneous water phantom and inhomogeneous phantoms with slab lung or bone material for 4 square fields and 9 irregularly shaped fields. Results: The calculated output factors are compared with the measured ones and the difference is within 1% for different field sizes. The calculated dose distributions in the phantoms show good agreement with measurements using diode detector and films. The dose difference is within 2% inside the field and the distance to agreement is within 2mm in the penumbra region. The gamma passing rate is more than 95% with 2%/2mm criteria for all the test cases. Conclusion: Implementation of Monte Carlo dose calculation for a MLC equipped robotic radiosurgery system is completed successfully. The accuracy of Monte Carlo dose calculation with MLC is clinically acceptable. This work was supported by Accuray Inc.

60 APPLIED LIFE SCIENCES↗

SU-E-T-500: Initial Implementation of GPU-Based Particle Swarm Optimization for 4D IMRT Planning in Lung SBRT

Purpose 4D-IMRT planning, combined with dynamic MLC tracking delivery, utilizes the temporal dimension as an additional degree of freedom to achieve improved OAR-sparing. The computational complexity for such optimization increases exponentially with increase in dimensionality. In order to accomplish this task in a clinically-feasible time frame, we present an initial implementation of GPU-based 4D-IMRT planning based on particle swarm optimization (PSO). Methods The target and normal structures were manually contoured on ten phases of a 4DCT scan of a NSCLC patient with a 54cm3 right-lower-lobe tumor (1.5cm motion). Corresponding ten 3D-IMRT plans were created in the Eclipse treatment planning system (Ver-13.6). A vendor-provided scripting interface was used to export 3D-dose matrices corresponding to each control point (10 phases × 9 beams × 166 control points = 14,940), which served as input to PSO. The optimization task was to iteratively adjust the weights of each control point and scale the corresponding dose matrices. In order to handle the large amount of data in GPU memory, dose matrices were sparsified and placed in contiguous memory blocks with the 14,940 weight-variables. PSO was implemented on CPU (dual-Xeon, 3.1GHz) and GPU (dual-K20 Tesla, 2496 cores, 3.52Tflops, each) platforms. NiftyReg, an open-source deformable image registration package, was used to calculate the summed dose. Results The 4D-PSO plan yielded PTV coverage comparable to the clinical ITV-based plan and significantly higher OAR-sparing, as follows: lung Dmean=33%; lung V20=27%; spinal cord Dmax=26%; esophagus Dmax=42%; heart Dmax=0%; heart Dmean=47%. The GPU-PSO processing time for 14940 variables and 7 PSO-particles was 41% that of CPU-PSO (199 vs. 488 minutes). Conclusion Truly 4D-IMRT planning can yield significant OAR dose-sparing while preserving PTV coverage. The corresponding optimization problem is large-scale, non-convex and computationally rigorous. Our initial results indicate that GPU-based PSO with further software optimization can make such planning clinically feasible. This work was supported through funding from the National Institutes of Health and Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

SU-E-T-626: Practical Method to Implement Arc Therapy Using Scanned Particle Beams

Purpose: The purpose of this study was to propose a method to implement arc therapy that is compatible with existing particle therapy systems having gantries and pencil-beam scanning capacities. Furthermore, we sought to demonstrate expected benefits of this method for selected clival chordoma patients. Methods: We propose that a desired particle arc treatment plan can be discretized into a finite number of fixed beams and that only one (or a subset) of these beams be delivered in any single treatment fraction; the target should receive uniform dose during each fraction. For 3 clival-chordoma patients, robust-optimized, scanned proton beams were simulated to deliver 78 Gy (RBE) to clinical target volumes (CTVs), using either a single-field plan with a posterior-anterior (PA) beam or a discrete-arc plan with 16 beams that were equally spaced throughout a 360-degree axial arc. Dose-volume metrics were compared with emphasis on the brainstem, since risk of radiation necrosis there can often restrict application of tumoricidal doses for chordomas. Results: The mean volume of brainstem receiving a dose of 60 Gy (RBE) or higher (V60Gy) was 10.3±0.9 cm{sup 3} for the single-field plan and 4.7±1.8 cm{sup 3} for the discrete-arc plan, a reduction of 55% in favor of arcs. The mean dose to the brainstem was also reduced using arcs, by 18%, while the maximum dose was nearly identical for both methods. For the whole brain, V60Gy was reduced by 23%, in favor of arcs. Mean dose to the CTVs were nearly identical for both strategies, within 0.3%. Conclusion: Discrete arc treatments can be implemented using existing scanned particle-beam facilities. Aside from the physical advantages, the biological uncertainties of particle therapy, particularly high in the distal edge, can be reduced by arc therapy via rotational smearing, which may be of benefit for tumors near the brainstem.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

TU-CD-BRD-03: UCSD Experience, with Focus On Implementing Change

It has long been standard practice in radiation oncology to report internally when a patient’s treatment has not gone as planned and to report events to regulatory agencies when legally required. Most potential errors are caught early and never affect the patient. Quality assurance steps routinely prevent errors from reaching the patient, and these “near misses” are much more frequent than treatment errors. A growing number of radiation oncology facilities have implemented incident learning systems to report and analyze both errors and near misses. Using the term “incident learning” instead of “event reporting” emphasizes the need to use these experiences to change the practice and make future errors less likely and promote an educational, non-punitive environment. There are challenges in making such a system practical and effective. Speakers from institutions of different sizes and practice environments will share their experiences on how to make such a system work and what benefits their clinics have accrued. Questions that will be addressed include: How to create a system that is easy for front line staff to access How to motivate staff to report How to promote the system as positive and educational and not punitive or demeaning How to organize the team for reviewing and responding to reports How to prioritize which reports to discuss in depth How not to dismiss the rest How to identify underlying causes How to design corrective actions and implement change How to develop useful statistics and analysis tools How to coordinate a departmental system with a larger risk management system How to do this without a dedicated quality manager Some speakers’ experience is with in-house systems and some will share experience with the AAPM/ASTRO national Radiation Oncology Incident Learning System (RO-ILS). Reports intended to be of value nationally need to be comprehensible to outsiders; examples of useful reports will be shown. There will be ample time set aside for audience members to contribute to the discussion. Learning Objectives: Learn how to promote the use of an incident learning system in a clinic. Learn how to convert “event reporting” into “incident learning”. See examples of practice changes that have come out of learning systems. Learn how the RO-ILS system can be used as a primary internal learning system. Learn how to create succinct, meaningful reports useful to outside readers. Gary Ezzell chairs the AAPM committee overseeing RO-ILS and has received an honorarium from ASTRO for working on the committee reviewing RO-ILS reports. Derek Brown is a director of http://TreatSafely.org . Brett Miller has previously received travel expenses and an honorarium from Varian. Phillip Beron has nothing to report.

60 APPLIED LIFE SCIENCES↗

WE-D-207-01: Background and Clinical Implementation of a Screening Program

In the United States, Lung Cancer is responsible for more cancer deaths than the next four cancers combined. In addition, the 5 year survival rate for lung cancer patients has not improved over the past 40 to 50 years. To combat this deadly disease, in 2002 the National Cancer Institute launched a very large Randomized Control Trial called the National Lung Screening Trial (NLST). This trial would randomize subjects who had substantial risk of lung cancer (due to age and smoking history) into either a Chest X-ray arm or a low dose CT arm. In November 2010, the National Cancer Institute announced that the NLST had demonstrated 20% fewer lung cancer deaths among those who were screened with low-dose CT than with chest X-ray. In December 2013, the US Preventive Services Task Force recommended the use of Lung Cancer Screening using low dose CT and a little over a year later (Feb. 2015), CMS announced that Medicare would also cover Lung Cancer Screening using low dose CT. Thus private and public insurers are required to provide Lung Cancer Screening programs using CT to the appropriate population(s). The purpose of this Symposium is to inform medical physicists and prepare them to support the implementation of Lung Screening programs. This Symposium will focus on the clinical aspects of lung cancer screening, requirements of a screening registry for systematically capturing and tracking screening patients and results (such as required Medicare data elements) as well as the role of the medical physicist in screening programs, including the development of low dose CT screening protocols. Learning Objectives: To understand the clinical basis and clinical components of a lung cancer screening program, including eligibility criteria and other requirements. To understand the data collection requirements, workflow, and informatics infrastructure needed to support the tracking and reporting components of a screening program. To understand the role of the medical physicist in implementing Lung Cancer Screening protocols for CT, including utilizing resources such as the AAPM Protocols and the ACR Designated Lung Screening Center program. UCLA Department of Radiology has an Institutional research agreement with Siemens Healthcare; Dr. McNitt-Gray has been a recipient of Research Support from Siemens Healthcare in the past. Dr. Aberle has been a Member of Advisory Boards for the LUNGevity Foundation (2011-present) and Siemens Medical Solutions. (2013)

60 APPLIED LIFE SCIENCES↗

SU-F-E-15: Initial Experience Implementing a Case Method Teaching Approach to Radiation Oncology Physics Residents, Graduate Students and Doctorate of Medical Physics Students

Purpose: Case Method Teaching approach is a teaching tool used commonly in business school to challenge students with real-world situations—i.e. cases. The students are placed in the role of the decision maker and have to provide a solution based on the multitude of information provided. Specifically, students must develop an ability to quickly make sense of a complex problem, provide a solution incorporating all of the objectives (at time conflicting) and constraints, and communicate that solution in a succinct, professional and effective manner. The validity of the solution is highly dependent on the auxiliary information provided in the case and the basic didactic knowledge of the student. A Case Method Teaching approach was developed and implemented into an on-going course focused on AAPM Task Group reports at UTHSCSA. Methods: A current course at UTHSCSA reviews and discusses 15 AAPM Task Group reports per semester. The course is structured into three topic modules: Imaging QA, Stereotactic Radiotherapy, and Special Patient Measurements—i.e. pacemakers, fetal dose. After a topic module is complete, the students are divided into groups (2–3 people) and are asked to review a case study related to the module topic. Students then provide a solution presented in an executive summary and class presentation. Results: Case studies were created to address each module topic. Through team work and whole-class discussion, a collaborative learning environment was established. Students additionally learned concepts such vendor relations, financial negotiations, capital project management, and competitive strategy. Conclusion: Case Method Teaching approach is an effective teaching tool to further enhance the learning experience of radiation oncology physics students by presenting them with though-provoking dilemmas that require students to distinguish pertinent from peripheral information, formulate strategies and recommendations for action, and confront obstacles to implementation.

60 APPLIED LIFE SCIENCES↗

SU-F-P-37: Implementation of An End-To-End QA Test of the Radiation Therapy Imaging, Planning and Delivery Process to Identify and Correct Possible Sources of Deviation

Purpose: To implement an end-to-end QA test of the radiation therapy imaging, planning and delivery process, aimed to assess the dosimetric agreement accuracy between planned and delivered treatment, in order to identify and correct possible sources of deviation. To establish an internal standard for machine commissioning acceptance. Methods: A test involving all steps of the radiation therapy: imaging, planning and delivery process was designed. The test includes analysis of point dose and planar dose distributions agreement between TPS calculated and measured dose. An ad hoc 16 cm diameter PMMA phantom was constructed with one central and four peripheral bores that can accommodate calibrated electron density inserts. Using Varian Eclipse 10.0 and Elekta XiO 4.50 planning systems, IMRT, RapidArc and 3DCRT with hard and dynamic wedges plans were planned on the phantom and tested. An Exradin A1SL chamber is used with a Keithley 35617EBS electrometer for point dose measurements in the phantom. 2D dose distributions were acquired using MapCheck and Varian aS1000 EPID.Gamma analysis was performed for evaluation of 2D dose distribution agreement using MapCheck software and Varian Portal Dosimetry Application.Varian high energy Clinacs Trilogy, 2100C/CD, 2000CR and low energy 6X/EX where tested.TPS-CT# vs. electron density table were checked for CT-scanners used. Results: Calculated point doses were accurate to 0.127% SD: 0.93%, 0.507% SD: 0.82%, 0.246% SD: 1.39% and 0.012% SD: 0.01% for LoX-3DCRT, HiX-3DCRT, IMRT and RapidArc plans respectively. Planar doses pass gamma 3% 3mm in all cases and 2% 2mm for VMAT plans. Conclusion: Implementation of a simple and reliable quality assurance tool was accomplished. The end-to-end proved efficient, showing excellent agreement between planned and delivered dose evidencing strong consistency of the whole process from imaging through planning to delivery. This test can be used as a first step in beam model acceptance for clinical use.

60 APPLIED LIFE SCIENCES↗

An Efficient Multicore Implementation of a Novel HSS-Structured Multifrontal Solver Using Randomized Sampling

Here, we present a sparse linear system solver that is based on a multifrontal variant of Gaussian elimination and exploits low-rank approximation of the resulting dense frontal matrices. We use hierarchically semiseparable (HSS) matrices, which have low-rank off-diagonal blocks, to approximate the frontal matrices. For HSS matrix construction, a randomized sampling algorithm is used together with interpolative decompositions. The combination of the randomized compression with a fast ULV HSS factoriz ation leads to a solver with lower computational complexity than the standard multifrontal method for many applications, resulting in speedups up to 7 fold for problems in our test suite. The implementation targets many-core systems by using task parallelism with dynamic runtime scheduling. Numerical experiments show performance improvements over state-of-the-art sparse direct solvers. The implementation achieves high performance and good scalability on a range of modern shared memory parallel systems, including the Intel Xeon Phi (MIC). The code is part of a software package called STRUMPACK - STRUctured Matrices PACKage, which also has a distributed memory component for dense rank-structured matrices.

97 MATHEMATICS AND COMPUTING↗

A Robust and Efficient Implementation of LOBPCG

Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG) is widely used to compute eigenvalues of large sparse symmetric matrices. The algorithm can suffer from numerical instability if it is not implemented with care. This is especially problematic when the number of eigenpairs to be computed is relatively large. In this paper we propose an improved basis selection strategy based on earlier work by Hetmaniuk and Lehoucq as well as a robust convergence criterion which is backward stable to enhance the robustness. Here, we also suggest several algorithmic optimizations that improve performance of practical LOBPCG implementations. Numerical examples confirm that our approach consistently and significantly outperforms previous competing approaches in both stability and speed.

97 MATHEMATICS AND COMPUTING↗