Results for “CHART” — Page 59

DOE OSTI2014

MO-G-BRE-04: Automatic Verification of Daily Treatment Deliveries and Generation of Daily Treatment Reports for a MR Image-Guided Treatment Machine

Purpose: Two aims of this work were to develop a method to automatically verify treatment delivery accuracy immediately after patient treatment and to develop a comprehensive daily treatment report to provide all required information for daily MR-IGRT review. Methods: After systematically analyzing the requirements for treatment delivery verification and understanding the available information from a novel MR-IGRT treatment machine, we designed a method to use 1) treatment plan files, 2) delivery log files, and 3) dosimetric calibration information to verify the accuracy and completeness of daily treatment deliveries. The method verifies the correctness of delivered treatment plans and beams, beam segments, and for each segment, the beam-on time and MLC leaf positions. Composite primary fluence maps are calculated from the MLC leaf positions and the beam-on time. Error statistics are calculated on the fluence difference maps between the plan and the delivery. We also designed the daily treatment delivery report by including all required information for MR-IGRT and physics weekly review - the plan and treatment fraction information, dose verification information, daily patient setup screen captures, and the treatment delivery verification results. Results: The parameters in the log files (e.g. MLC positions) were independently verified and deemed accurate and trustable. A computer program was developed to implement the automatic delivery verification and daily report generation. The program was tested and clinically commissioned with sufficient IMRT and 3D treatment delivery data. The final version has been integrated into a commercial MR-IGRT treatment delivery system. Conclusion: A method was developed to automatically verify MR-IGRT treatment deliveries and generate daily treatment reports. Already in clinical use since December 2013, the system is able to facilitate delivery error detection, and expedite physician daily IGRT review and physicist weekly chart review.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-D-BRD-05: Online Framework for Plan Tracking and Automatic Checks in Radiation Therapy

Purpose: To develop an online framework that tracks a patient’s plan from initial simulation to treatment and that helps automate elements of the physics plan checks usually performed in the record and verify (RV) system and treatment planning system. Methods: We have developed PlanTracker, an online plan tracking system that automatically imports new patients tasks and follows it through treatment planning, physics checks, therapy check, and chart rounds. A survey was designed to collect information about the amount of time spent by medical physicists in non-physics related tasks. We then assessed these non-physics tasks for automation. Using these surveys, we directed our PlanTracker software development towards the automation of intra-plan physics review. We then conducted a systematic evaluation of PlanTracker’s accuracy by generating test plans in the RV system software designed to mimic real plans, in order to test its efficacy in catching errors both real and theoretical. Results: PlanTracker has proven to be an effective improvement to the clinical workflow in a radiotherapy clinic. We present data indicating that roughly 1/3 of the physics plan check can be automated, and the workflow optimized, and show the functionality of PlanTracker. When the full system is in clinical use we will present data on improvement of time use in comparison to survey data prior to PlanTracker implementation. Conclusion: We have developed a framework for plan tracking and automatic checks in radiation therapy. We anticipate using PlanTracker as a basis for further development in clinical/research software. We hope that by eliminating the most simple and time consuming checks, medical physicists may be able to spend their time on plan quality and other physics tasks rather than in arithmetic and logic checks. We see this development as part of a broader initiative to advance the clinical/research informatics infrastructure surrounding the radiotherapy clinic. This research project has been financially supported by Varian Medical Systems, Palo Alto, CA, through a Varian MRA.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-D-BRD-07: Evaluation of the Effectiveness of Statistical Process Control Methods to Detect Systematic Errors For Routine Electron Energy Verification

Purpose: To evaluate the ability of statistical process control methods to detect systematic errors when using a two dimensional (2D) detector array for routine electron beam energy verification. Methods: Electron beam energy constancy was measured using an aluminum wedge and a 2D diode array on four linear accelerators. Process control limits were established. Measurements were recorded in control charts and compared with both calculated process control limits and TG-142 recommended specification limits. The data was tested for normality, process capability and process acceptability. Additional measurements were recorded while systematic errors were intentionally introduced. Systematic errors included shifts in the alignment of the wedge, incorrect orientation of the wedge, and incorrect array calibration. Results: Control limits calculated for each beam were smaller than the recommended specification limits. Process capability and process acceptability ratios were greater than one in all cases. All data was normally distributed. Shifts in the alignment of the wedge were most apparent for low energies. The smallest shift (0.5 mm) was detectable using process control limits in some cases, while the largest shift (2 mm) was detectable using specification limits in only one case. The wedge orientation tested did not affect the measurements as this did not affect the thickness of aluminum over the detectors of interest. Array calibration dependence varied with energy and selected array calibration. 6 MeV was the least sensitive to array calibration selection while 16 MeV was the most sensitive. Conclusion: Statistical process control methods demonstrated that the data distribution was normally distributed, the process was capable of meeting specifications, and that the process was centered within the specification limits. Though not all systematic errors were distinguishable from random errors, process control limits increased the ability to detect systematic errors using routine measurement of electron beam energy constancy.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2015

SU-E-P-27: Efficient Process for AccuBoost Planning and Treatment Delivery to Minimize Patient Compression Time

Purpose: To implement an efficient and robust process for AccuBoost planning and treatment delivery that can be safely performed by a single Physicist while minimizing patient’s total session time. Methods: Following a thorough commissioning and validation process, templates were created in the brachytherapy planning system for each AccuBoost applicator. Tables of individual and total nominal dwell times for each applicator as a function of separation were generated to streamline planning while an Excel-based nomogram provided by the vendor functions as a secondary verification of the treatment parameters. Tables of surface dose as a function of separation and applicator, along with concise guidance documents for applicator selection, are readily available during the planning process. The entire process is described in a set of detailed Standard Operating Procedures which, in addition to the items described above, include a verbal time-out between the primary planner and the individual performing the secondary verification as well as direct visual confirmation of applicator placement using an articulated mirror. Prior to treatment initiation, a final time-out is conducted with the Radiation Oncologist. Chart documentation is finalized after the patient is released from compression following completion of the treatment. Results: With the aforementioned procedures, it has been possible to consistently limit the time required to prepare each treatment such that the patient is typically under compression for less than 10 minutes per orientation prior to the initiation of the treatment, which is particularly important for APBI cases. This process can be overseen by a single physicist assisted by a dosimetrist and has been optimized during the past 16 months, with 180 treatment sessions safely completed to date. Conclusion: This work demonstrates the implementation of an efficient and robust process for real-time-planned AccuBoost treatments that effectively minimizes the time that the patient is under compression.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-J-15: Automatically Detect Patient Treatment Position and Orientation in KV Portal Images

Purpose: In the course of radiation therapy, the complex information processing workflow will Result in potential errors, such as incorrect or inaccurate patient setups. With automatic image check and patient identification, such errors could be effectively reduced. For this purpose, we developed a simple and rapid image processing method, to automatically detect the patient position and orientation in 2D portal images, so to allow automatic check of positions and orientations for patient daily RT treatments. Methods: Based on the principle of portal image formation, a set of whole body DRR images were reconstructed from multiple whole body CT volume datasets, and fused together to be used as the matching template. To identify the patient setup position and orientation shown in a 2D portal image, the 2D portal image was preprocessed (contrast enhancement, down-sampling and couch table detection), then matched to the template image so to identify the laterality (left or right), position, orientation and treatment site. Results: Five day’s clinical qualified portal images were gathered randomly, then were processed by the automatic detection and matching method without any additional information. The detection results were visually checked by physicists. 182 images were correct detection in a total of 200kV portal images. The correct rate was 91%. Conclusion: The proposed method can detect patient setup and orientation quickly and automatically. It only requires the image intensity information in KV portal images. This method can be useful in the framework of Electronic Chart Check (ECCK) to reduce the potential errors in workflow of radiation therapy and so to improve patient safety. In addition, the auto-detection results, as the patient treatment site position and patient orientation, could be useful to guide the sequential image processing procedures, e.g. verification of patient daily setup accuracy. This work was partially supported by research grant from Varian Medical System.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-T-235: Data Mining for Evaluating Treatment Performances Over a Large Quantity of Data to Monitor and Improve SBRT Workflow

Purpose: To quality assure a large quantity of retrospective treatment cases for treatment performances by randomly sampling is inefficient. Here we provide a method to efficiently monitor and investigate the QA of SBRT workflow over Mosaiq. Methods: The code developed with Microsoft SQL Server Management Studio 2008R2 and VBA was used for retrieving and sorting data from Mosaiq (version 2.3–2.6 during 2012–2015). SBRT patients were filtered by fractional dose over 350cGy and total fraction number less than 6, which SBRT prescriptions were defined. The quality assurance on the SBRT workflow was focused on the treatment deliveries such as patient positioning setup, CBCT indicated offsets and couch shifted corrections. The treatment delivery were done by Varian Truebeam systems and the record/verify by Mosaiq. Results: Total 82 SBRT patients corresponding to 103 courses and 854 CBCT images were found by the retrieval query. Most centers record daily pre-treatment (Pre-Tx: before treatment shift) image-guided shifts along treatment course for inter-fraction motion record, and it is useful to also verify it with post-treatment imaging (Post-Tx: after treatment CBCT verification) to verify intra-fraction motion. Analyzing the details of daily recorded shifts can reveals the information of patient-setup and staff’s record/verify behaviors. 3 examples were provided as solid evidences and on-going rectification for preventing future mistakes. Conclusions: The report gave feasible examples for inspector to verify a large amount of data during site investigation. This program can also be extended to a scheduled data mining with software to periodical analyze the timely records in Mosaiq, for example, a various control charts for different QA purposes. As the current trend of automation in radiation therapy field, the data mining would be a necessary tool in the future, just as the automatic plan quality evaluation has been under development in Eclipse.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

MO-B-BRB-00: Optimizing the Treatment Planning Process

The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi-automatic plan evaluation, (e) quality checklist for error prevention, (f) iterative process, (g) balance of speed and quality Learning Objectives: Gain familiarity with the workflow of modern treatment planning process. Understand the scope and challenges of managing modern treatment planning processes. Gain familiarity with Lean Six Sigma approaches and their implementation in the treatment planning workflow.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

MO-B-BRB-01: Optimize Treatment Planning Process in Clinical Environment

The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi-automatic plan evaluation, (e) quality checklist for error prevention, (f) iterative process, (g) balance of speed and quality Learning Objectives: Gain familiarity with the workflow of modern treatment planning process. Understand the scope and challenges of managing modern treatment planning processes. Gain familiarity with Lean Six Sigma approaches and their implementation in the treatment planning workflow.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

MO-B-BRB-02: Maintain the Quality of Treatment Planning for Time-Constraint Cases

The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi-automatic plan evaluation, (e) quality checklist for error prevention, (f) iterative process, (g) balance of speed and quality Learning Objectives: Gain familiarity with the workflow of modern treatment planning process. Understand the scope and challenges of managing modern treatment planning processes. Gain familiarity with Lean Six Sigma approaches and their implementation in the treatment planning workflow.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

MO-B-BRB-03: Systems Engineering Tools for Treatment Planning Process Optimization in Radiation Medicine

The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi-automatic plan evaluation, (e) quality checklist for error prevention, (f) iterative process, (g) balance of speed and quality Learning Objectives: Gain familiarity with the workflow of modern treatment planning process. Understand the scope and challenges of managing modern treatment planning processes. Gain familiarity with Lean Six Sigma approaches and their implementation in the treatment planning workflow.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-G-BRD-06: The Imaging and Radiation Oncology Core Houston (IROC Houston) QA Center International Activities Outside North America

Purpose: To describe the extent of IROC Houston’s (formerly the RPC) QA activities and audit results for radiotherapy institutions outside of North America (NA). Methods: The IROC Houston’s QA program components were designed to audit the radiation dose calculation chain from the NIST traceable reference beam calibration, to inclusion of dosimetry parameters used to calculate tumor doses, to the delivery of the radiation dose. The QA program provided to international institutions includes: 1) remote TLD/OSLD audit of machine output, 2) credentialing for advanced technologies, and 3) review of patient treatment records. IROC Houston uses the same standards and acceptance criteria for all of its audits whether for North American or international sites. Results: IROC Houston’s QA program has reached out to radiotherapy sites in 43 different countries since 2013 through their participation in clinical trials. In the past two years, 2,778 international megavoltage beam outputs were audited with OSLD/TLD. While the average IROC/Inst ratio is near unity for all sites monitored, there are international regions whose results are significantly different from the NA region. In the past 2 years, 477 and 87 IMRT H&N phantoms were irradiated at NA and international sites, respectively. Regardless of the OSLD beam audit results, the overall pass rate (87 percent) for all international sites (no region separation) is equal to the NA sites. Of the 182 international patient charts reviewed, 10.7 percent of the dose calculation points did not meet our acceptance criterion as compared to 13.6 percent for NA sites. The lower pass rate for NA sites results from a much larger brachytherapy component which has been shown to be more error prone. Conclusion: IROC Houston has expanded its QA services worldwide and continues a long history of improving radiotherapy dose delivery in many countries. Funding received for QA audit services from the Korean GOG, DAHANCA, EORTC, ICON and CMIC Group.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Postoperative 3D spine reconstruction by navigating partitioning manifolds

Purpose: The postoperative evaluation of scoliosis patients undergoing corrective treatment is an important task to assess the strategy of the spinal surgery. Using accurate 3D geometric models of the patient’s spine is essential to measure longitudinal changes in the patient’s anatomy. On the other hand, reconstructing the spine in 3D from postoperative radiographs is a challenging problem due to the presence of instrumentation (metallic rods and screws) occluding vertebrae on the spine. Methods: This paper describes the reconstruction problem by searching for the optimal model within a manifold space of articulated spines learned from a training dataset of pathological cases who underwent surgery. The manifold structure is implemented based on a multilevel manifold ensemble to structure the data, incorporating connections between nodes within a single manifold, in addition to connections between different multilevel manifolds, representing subregions with similar characteristics. Results: The reconstruction pipeline was evaluated on x-ray datasets from both preoperative patients and patients with spinal surgery. By comparing the method to ground-truth models, a 3D reconstruction accuracy of 2.24 ± 0.90 mm was obtained from 30 postoperative scoliotic patients, while handling patients with highly deformed spines. Conclusions: This paper illustrates how this manifold model can accurately identify similar spine models by navigating in the low-dimensional space, as well as computing nonlinear charts within local neighborhoods of the embedded space during the testing phase. This technique allows postoperative follow-ups of spinal surgery using personalized 3D spine models and assess surgical strategies for spinal deformities.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2016

SU-C-209-06: Improving X-Ray Imaging with Computer Vision and Augmented Reality

Purpose: To determine the feasibility of using a computer vision algorithm and augmented reality interface to reduce repeat rates and improve consistency of image quality and patient exposure in general radiography. Methods: A prototype device, designed for use with commercially available hardware (Microsoft Kinect 2.0) capable of depth sensing and high resolution/frame rate video, was mounted to the x-ray tube housing as part of a Philips DigitalDiagnost digital radiography room. Depth data and video was streamed to a Windows 10 PC. Proprietary software created an augmented reality interface where overlays displayed selectable information projected over real-time video of the patient. The information displayed prior to and during x-ray acquisition included: recognition and position of ordered body part, position of image receptor, thickness of anatomy, location of AEC cells, collimated x-ray field, degree of patient motion and suggested x-ray technique. Pre-clinical data was collected in a volunteer study to validate patient thickness measurements and x-ray images were not acquired. Results: Proprietary software correctly identified ordered body part, measured patient motion, and calculated thickness of anatomy. Pre-clinical data demonstrated accuracy and precision of body part thickness measurement when compared with other methods (e.g. laser measurement tool). Thickness measurements provided the basis for developing a database of thickness-based technique charts that can be automatically displayed to the technologist. Conclusion: The utilization of computer vision and commercial hardware to create an augmented reality view of the patient and imaging equipment has the potential to drastically improve the quality and safety of x-ray imaging by reducing repeats and optimizing technique based on patient thickness. Society of Pediatric Radiology Pilot Grant; Washington University Bear Cub Fund.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-D-201-04: Evaluation of Elekta Agility MLC Performance Using Statistical Process Control

Purpose: to evaluate the performance and stability of the Elekta Agility MLC model using an automated quality control (QC) test in combination with statistical process control tools. Methods: Leaf positions were collected daily for 11 Elekta units over 5–19 months using the automated QC test, which analyzes 23 MV images to determine the location of MLC leaves relative to the radiation isocenter. The leaf positions are measured at 5 nominal positions, and images are acquired at collimator 0° and 180° to capture all MLC leaves in the field-of-view. Leaf positioning accuracy was assessed using individual and moving range control charts. Control limits were recomputed following MLC recalibration (occurred 1–2 times for 4 units). Specification levels of ±0.5, ±1 and ±1.5mm were tested. The mean and range of duration between out-of-control and out-of-specification events were determined. Results: Leaf position varied little over time, as confirmed by very tight individual control limits (mean ±0.19mm, range 0.09–0.44). Mean leaf position error was −0.03mm (range −0.89–0.83). Due to sporadic out-of-control events, the mean in-control duration was 3.3 days (range 1–23). Data stayed within ±1mm specification for 205 days on average (range 3–372) and within ±1.5mm for the entire date range. Measurements stayed within ±0.5mm for 1 day on average (range 0–17); however, our MLC leaves were not calibrated to this level of accuracy. Conclusion: The Elekta Agility MLC model was found to perform with high stability, as evidenced by the tight control limits. The in-specification durations support the current recommendation of monthly MLC QC tests with a ±1mm tolerance. Future work is on-going to determine if Agility performance can be optimized further using high-frequency QC test results to drive recalibration frequency. Factors that can affect leaf positioning accuracy, including beam spot motion, leaf gain calibration, drifting leaves, and image artifacts, are under investigation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-110: MRI-Guided Single-Session Simulation, Online Adaptation, and Treatment

Purpose: To develop a combined simulation and treatment workflow for MRI-guided radiation therapy using the ViewRay treatment planning and delivery system. Methods: Several features of the ViewRay MRIdian planning and treatment workflows are used to simulate and treat patients that require emergent radiotherapy. A simple “pre-plan” is created on diagnostic imaging retrieved from radiology PACS, where conformal fields are created to target a volume defined by a physician based on review of the diagnostic images and chart notes. After initial consult in radiation oncology, the patient is brought to the treatment room, immobilized, and imaged in treatment position with a volumetric MR. While the patient rests on the table, the pre-plan is applied to the treatment planning MR and dose is calculated in the treatment geometry. After physician review, modification of the plan may include updating the target definition, redefining fields, or re-balancing beam weights. Once an acceptable treatment plan is finalized and approved, the patient is treated. Results: Careful preparation and judicious choices in the online planning process allow conformal treatment plans to be created and delivered in a single, thirty-minute session. Several advantages have been identified using this process as compared to conventional urgent CT simulation and delivery. Efficiency gains are notable, as physicians appreciate the predictable time commitment and patient waiting time for treatment is decreased. MR guidance in a treatment position offers both enhanced contrast for target delineation and reduction of setup uncertainties. The MRIdian system tools designed for adaptive radiotherapy are particularly useful, enabling plan changes to be made in minutes. Finally, the resulting plans, typically 6 conformal beams, are delivered as quickly as more conventional AP/PA beam arrangements with comparatively superior dose distributions. Conclusion: The ViewRay treatment planning software and delivery system can accommodate a fast simulation and treatment workflow.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-251: The Quality Assurance for the Heavy Patient Load Department in the Developing Country: The Primary Experience of An Entire Workflow QA Process Management in Radiotherapy

Purpose: To implement an entire workflow quality assurance (QA) process in the radiotherapy department and to reduce the error rates of radiotherapy based on the entire workflow management in the developing country. Methods: The entire workflow QA process management starts from patient registration to the end of last treatment including all steps through the entire radiotherapy process. Error rate of chartcheck is used to evaluate the the entire workflow QA process. Two to three qualified senior medical physicists checked the documents before the first treatment fraction of every patient. Random check of the treatment history during treatment was also performed. A total of around 6000 patients treatment data before and after implementing the entire workflow QA process were compared from May, 2014 to December, 2015. Results: A systemic checklist was established. It mainly includes patient’s registration, treatment plan QA, information exporting to OIS(Oncology Information System), documents of treatment QAand QA of the treatment history. The error rate derived from the chart check decreases from 1.7% to 0.9% after our the entire workflow QA process. All checked errors before the first treatment fraction were corrected as soon as oncologist re-confirmed them and reinforce staff training was accordingly followed to prevent those errors. Conclusion: The entire workflow QA process improved the safety, quality of radiotherapy in our department and we consider that our QA experience can be applicable for the heavily-loaded radiotherapy departments in developing country.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-G-TeP4-06: An Integrated Application for Radiation Therapy Treatment Plan Directives, Management, and Reporting

Purpose: With electronic medical records, patient information for the treatment planning process has become disseminated across multiple applications with limited quality control and many associated failure modes. We present the development of a single application with a centralized database to manage the planning process. Methods: The system was designed to replace current functionalities of (i) static directives representing the physician intent for the prescription and planning goals, localization information for delivery, and other information, (ii) planning objective reports, (iii) localization and image guidance documents and (iv) the official radiation therapy prescription in the medical record. Using the Eclipse Scripting Application Programming Interface, a plug-in script with an associated domain-specific SQL Server database was created to manage the information in (i)–(iv). The system’s user interface and database were designed by a team of physicians, clinical physicists, database experts, and software engineers to ensure usability and robustness for clinical use. Results: The resulting system has been fully integrated within the TPS via a custom script and database. Planning scenario templates, version control, approvals, and logic-based quality control allow this system to fully track and document the planning process as well as physician approval of tradeoffs while improving the consistency of the data. Multiple plans and prescriptions are supported along with non-traditional dose objectives and evaluation such as biologically corrected models, composite dose limits, and management of localization goals. User-specific custom views were developed for the attending physician review, physicist plan checks, treating therapists, and peer review in chart rounds. Conclusion: A method was developed to maintain cohesive information throughout the planning process within one integrated system by using a custom treatment planning management application that interfaces directly with the TPS. Future work includes quantifying the improvements in quality, safety and efficiency that are possible with the routine clinical use of this system. Supported in part by NIH-P01-CA-059827.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-H-BRC-04: Implement Lean Methodology to Make Our Current Process of CT Simulation to Treatment More Efficient

Purpose: Our goal is to implement lean methodology to make our current process of CT simulation to treatment more efficient. Methods: In this study, we implemented lean methodology and tools and employed flowchart in excel for process-mapping. We formed a group of physicians, physicists, dosimetrists, therapists and a clinical physics assistant and huddled bi-weekly to map current value streams. We performed GEMBA walks and observed current processes from scheduling patient CT Simulations to treatment plan approval. From this, the entire workflow was categorized into processes, sub-processes, and tasks. For each process we gathered data on touch time, first time quality, undesirable effects (UDEs), and wait-times from relevant members of each task. UDEs were binned per frequency of their occurrence. We huddled to map future state and to find solutions to high frequency UDEs. We implemented visual controls, hard stops, and documented issues found during chart checks prior to treatment plan approval. Results: We have identified approximately 64 UDEs in our current workflow that could cause delays, re-work, compromise the quality and safety of patient treatments, or cause wait times between 1 – 6 days. While some UDEs are unavoidable, such as re-planning due to patient weight loss, eliminating avoidable UDEs is our goal. In 2015, we found 399 issues with patient treatment plans, of which 261, 95 and 43 were low, medium and high severity, respectively. We also mapped patient-specific QA processes for IMRT/Rapid Arc and SRS/SBRT, involving 10 and 18 steps, respectively. From these, 13 UDEs were found and 5 were addressed that solved 20% of issues. Conclusion: We have successfully implemented lean methodology and tools. We are further mapping treatment site specific workflows to identify bottlenecks, potential breakdowns and personnel allocation and employ tools like failure mode effects analysis to mitigate risk factors to make this process efficient.

60 APPLIED LIFE SCIENCES↗