bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐F‐P‐10: A Web‐Based Radiation Safety Relational Database Module for Regulatory Compliance
Authors: Rosen C , Ramsay B , Konerth S , Roller D , Ramsay A 
Published: July 2016

Purpose:Maintaining compliance with Radioactive Materials Licenses is inherently a time‐consuming task requiring focus and attention to detail. Staff tasked with these responsibilities, such as the Radiation Safety Officer and associated personnel must retain disparate records for eventual placement into one or more annual reports. Entering results and records in a relational database using a web browser as the interface, and storing that data in a cloud‐based storage site, removes procedural barriers. The data becomes more adaptable for mining and sharing.Methods:Web‐based code was written utilizing the web framework Django, written in Python. Additionally, the application utilizes JavaScript for front‐end interaction, SQL, HTML and CSS. Quality assurance code testing is performed in a sequential style, and new code is only added after the successful testing of the previous goals. Separate sections of the module include data entry and analysis for audits, surveys, quality management, and continuous quality improvement. Data elements can be adapted for quarterly and annual reporting, and for immediate notification of user determined alarm settings.Results:Current advances are focusing on user interface issues, and determining the simplest manner by which to teach the user to build query forms. One solution has been to prepare library documents that a user can select or edit in place of creation a new document. Forms are being developed based upon Nuclear Regulatory Commission federal code, and will be expanded to include State Regulations.Conclusion:Establishing a secure website to act as the portal for data entry, storage and manipulation can lead to added efficiencies for a Radiation Safety Program. Access to multiple databases can lead to mining for big data programs, and for determining safety issues before they occur. Overcoming web programming challenges, a category that includes mathematical handling, is providing challenges that are being overcome.
SU‐F‐P‐12: Leveraging a Communication Tool to Assess IMRT Planning Process Efficiency and Identify Improvement Opportunities
Authors: Evans J 
Published: July 2016

Purpose:To utilize an existing patient‐specific IMRT QA communication tool to quantify our department's compliance with existing IMRT planning policies and to identify opportunities for improvement.Methods:A centralized network‐based spreadsheet is utilized by our dosimetrists to communicate to the physics team when an IMRT plan is ready for patient‐specific QA measurement. Since Feb. 2014, the dosimetrists and physicists track additional date information for each case including treatment start, contour approval, plan approval, and QA measurement. Since Jan. 2015, our team also tracks if, and why, a patient plan requires more than one QA measurement. Two time periods were analyzed: Feb. 2014 to Dec. 2014 and Jan. 2015 to Dec. 2015. The Excel “networkdays” function was used to calculate the number of days between process steps for each case. Histogram analysis was used to quantify environmental hazards created by compressed timelines for QA. The rate of and the reasons for QA re‐measurement was also quantified.Results:In 2014, 27.3% of QA measurements were performed the day before treatment start. From this, we modified our QA policies and staffing. In 2015, this day before start QA rate was reduced to 20%, but is ultimately limited by physician plan approval. In 2014, 29% of cases were approved by the physician within 2 or fewer days of treatment start. In 2015, this rate increased to 38% of cases. In 2015, 16.4% of QA measurements were a re‐measurement. The 2 most common themes for a re‐measurement were clinical reasons (re‐sim, re‐plan, contours modified) or a measurement setup error, e.g. the MatrixX ion chamber plane being left in a high dose gradient region.Conclusion:Leveraging an existing communication tool has allowed us to quantify our IMRT process performance, identify bottlenecks for improvement, and quantify improvement following policy changes.
SU‐F‐P‐13: NRG Oncology Medical Physics Manpower Survey Quantifying Support Demands for Multi Institutional Clinical Trials
Authors: Monroe J , Boparai K , Xiao Y , Followill D , Galvin J , Sohn J 
Published: July 2016

Purpose:A survey was taken by NRG Oncology to assess Full Time Equivalent (FTE) contributions to multi institutional clinical trials by medical physicists.No current quantification of physicists’ efforts in FTE units associated with clinical trials is available. The complexity of multi‐institutional trials increases with new technologies and techniques. Proper staffing may directly impact the quality of trial data and outcomes. The demands on physics time supporting clinical trials needs to be assessed.Methods:The NRG Oncology Medical Physicist Subcommittee created a sixteen question survey to obtain this FTE data. IROC Houston distributed the survey to their list of 1802 contact physicists.Results:After three weeks, 363 responded (20.1% response). 187 (51.5%) institutions reporting external beam participation were processed. There was a wide range in number of protocols active and supported at each institution. Of the 187 clinics, 134 (71.7%) participate in 0 to 10 trials, 28 (15%) in 11 to 20 trials, 10 (5.3%) in 21 to 30 trials, 9 (4.8%) had 40 to 75 trials. On average, physicist spent 2.7 hours (SD: 6.0) per week supervising or interacting with clinical trial staff. 1.25 hours (SD: 3.37), 1.83 hours (SD: 4.13), and 0.64 hours(SD: 1.13) per week were spent on patient simulation, reviewing treatment plans, and maintaining a DICOM server, respectively. For all protocol credentialing activities, physicist spent an average of 37.05 hours (SD: 96.94) yearly. To support dosimetrists, clinicians, and therapists, physicist spend on average 2.07 hours (SD: 3.52) per week just reading protocols. Physicist attended clinical trial meetings for on average 1.13 hours (SD: 1.85) per month.Conclusion:Responding physicists spend a nontrivial amount of time: 8.8 hours per week (0.22 FTE) supporting, on average, 9 active multi‐institutional clinical trials.
SU‐F‐P‐14: Oxygen Inhalation Should Be the Conventional Approach in the Treatment of Thoracic and Abdominal Cancer by Radiotherapy with Active Breathing Control (ABC)
Authors: Gong G , Guo Y , Yin Y 
Published: July 2016

Purpose:To investigate the feasibility and potential benefit of oxygen inhalation (OI) during radiotherapy applying an active breathing control (ABC) device, by analyzing the blood oxygen saturation (SpO2) and the instantaneous heart rate (IHR) variation in breath holding with OI and oxygen non‐inhalation (ONI).Methods:The 27 healthy volunteers (16 males, 11 females) who were involved in this trial were all required to hold their breath for 10 times, non‐inhaling and inhaling oxygen successively. The breath‐holding time (BHT), rest time (RT), SpO2 and IHR under different oxygen status were recorded and compared.Results:The volunteers were divided into two groups according to SpO2 variations in breath‐holding: group A (12 cases), with less than2% decline of SpO2; group B (15 cases), with a decline that surpassed 2%, and which could reach 3–6%. The BHT of group A, without inhaling oxygen, was significantly longer than that of group B (mean 33.77s Vs 30.51s, p<0.05); and was extended by 26.6% and 27.85%, after inhaling oxygen, in groups A and B, respectively. The SpO2 decreased in all volunteers during RT with ONI, to an extent that could reach up to 6%. The IHR of all volunteers showed the fast‐slow‐fast variation rule, and the oxygen had little effect. More than 70% of the volunteers stated that oxygen made them feel more comfortable and were more cooperative when ABC was used.Conclusion:The SpO2 declines during breath holding and RT could not be ignored while applying ABC, oxygen inhalation should become a conventional method with lengthening BHT and shortening RT, which yielded the benefit of improving the stability and reproducibility.
SU‐F‐P‐21: Study of Dosimetry Accuracy of Small Passively Scattered Proton Beam Fields
Authors: Li Y , Gautam A , Kerr M , Martin C , Poenisch F , Zhang X , Li H , Wu R , Zhu X , Gillin M , Sahoo N 
Published: July 2016

Purpose:To study the accuracy of the dose distribution of very small irregular fields of passively scattered proton beams calculated by the analytical pencil beam model of the Eclipse treatment planning system (TPS).Methods:An irregular field with a narrow region (width < 1 cm) that was used for the treatment of a small volume adjacent to a previously treated area were chosen for this investigation. Point doses at different locations inside the field were measured with a small volume ion chamber (A26, Standard Imaging). 2‐D dose distributions were measured using a 2‐D ion chamber array (MatriXX, IBA). All the measurements were done in plastic water phantom. The measured dose distributions were compared with the verification plan dose calculated in a water like phantom for the patient treatment field without the use of the compensator.Results:Point doses measured with the ion chamber in the narrowest section of the field were found to differ as much as 10% from the Eclipse calculated dose at some of the points. The 2‐D dose distribution measured with the MatriXX which was validated by comparison with limited film measurement, at the proximal 95%, center of the spread out Bragg Peak and distal 90% depths agreed reasonably well with the TPS calculated dose distribution with more than 92% of the pixels passing the 2% / 2 mm dose distance agreement.Conclusion:The dose calculated by the pencil beam model of the Eclipse TPS for narrow irregular fields may not be accurate within 5% at some locations of the field, especially at the points close to the field edge due to the limitation of the dose calculation model. Overall accuracy of the calculated 2‐D dose distribution was found to be acceptable for the 2%/2 mm dose/distance agreement with the measurement.
SU‐F‐P‐32: A Phantom Study of Accuracy of Four‐Dimensional Cone‐Beam CT (4D‐CBCT) Vs. Three‐Dimensional Cone Beam CT (3D‐CBCT) in Image Guided Radiotherapy
Authors: He R , Morris B , Duggar N , Markovich A , Standford J , Lu J , Yang C 
Published: July 2016

Purpose:SymmetryTM 4D IGRT system of Elekta has been installed at our institution, which offers the 4D CBCT registration option. This study is to evaluate the accuracy of 4D CBCT system by using the CIRS 4D motion phantom and to perform a feasibility study on the implementation of 4D‐CBCT as image guidance for SBRT treatment.Methods:The 3D and 4D CT image data sets are acquired using the CIRS motion phantom on a Philips large bore CT simulator. The motion was set as 0.5 cm superior and inferior directions with 6 seconds recycle time. The 4D CT data were sorted as 10 phases. One identifiable part of the 4D CT QA insert from CIRS phantom was used as the target. The ITV MIP was drawn based on maximum intensity projection (MIP) and transferred as a planning structure into 4D CBCT system. Then the 3D CBCT and 4D CBCT images were taken and registered with the free breath (3D), MIP (4D) and average intensity projection (AIP)(4D) reference data sets. The couch shifts (X, Y, Z) are recorded and compared.Results:Table 1 listed the twelve couch shifts based on the registration of MIP, AIP and free breath CT data sets with 3D CBCT and 4D CBCT for both whole body and local registration. X, Y and Z represent couch shifts in the direction of the right‐left, superior‐inferior and anterior‐posterior. The biggest differences of 0.73 cm and 0.57 cm are noted in the free breath CT data with 4D CBCT and 3D CBCT data registration. Fig. 1 and Fig. 2 are the shift analysis in diagram. Fig. 3 shows the registration.Conclusion:Significant differences exist in the shifts corresponding with the direction of target motion. Further investigations are ongoing.
SU‐F‐P‐35: A Multi‐Institutional Plan Quality Checking Tool Built On Oncospace: A Shared Radiation Oncology Database System
Authors: Bowers M , Robertson S , Moore J , Wong J , Phillips M , Hendrickson K , Evans K , McNutt T 
Published: July 2016

Purpose:Late toxicity from radiation to critical structures limits the possible dose in Radiation Therapy. Perfectly conformal treatment of a target is not realizable, so the clinician must accept a certain level of collateral radiation to nearby OARs. But how much? General guidelines exist for healthy tissue sparing which guide RT treatment planning, but are these guidelines good enough to create the optimal plan given the individualized patient anatomy? We propose a means to evaluate the planned dose level to an OAR using a multi‐institutional data‐store of previously treated patients, so a clinician might reconsider planning objectives.Methods:The tool is built on Oncospace, a federated data‐store system, which consists of planning data import, web based analysis tools, and a database containing:1) DVHs: dose by percent volume delivered to each ROI for each patient previously treated and included in the database.2) Overlap Volume Histograms (OVHs): Anatomical measure defined as the percent volume of an ROI within a given distance to target structures.Clinicians know what OARs are important to spare. For any ROI, Oncospace knows for which patients’ anatomy that ROI was harder to plan in the past (the OVH is less). The planned dose should be close to the least dose of previous patients. The tool displays the dose those OARs were subjected to, and the clinician can make a determination about the planning objectives used.Multiple institutions contribute to the Oncospace Consortium, and their DVH and OVH data are combined and color coded in the output.Results:The Oncospace website provides a plan quality display tool which identifies harder to treat patients, and graphically displays the dose delivered to them for comparison with the proposed plan.Conclusion:The Oncospace Consortium manages a data‐store of previously treated patients which can be used for quality checking new plans.Grant funding by Elekta.
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
Authors: Salinas Aranda F , Suarez V , Arbiser S , Sansogne R 
Published: July 2016

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.
SU‐F‐R‐36: Validating Quantitative Radiomic Texture Features for Oncologic PET: A Digital Phantom Study
Authors: Yang F , Yang Y , Young L 
Published: July 2016

Purpose:Radiomic texture features derived from the oncologic PET have recently been brought under intense investigation within the context of patient stratification and treatment outcome prediction in a variety of cancer types; however, their validity has not yet been examined. This work is aimed to validate radiomic PET texture metrics through the use of realistic simulations in the ground truth setting.Methods:Simulation of FDG‐PET was conducted by applying the Zubal phantom as an attenuation map to the SimSET software package that employs Monte Carlo techniques to model the physical process of emission imaging. A total of 15 irregularly‐shaped lesions featuring heterogeneous activity distribution were simulated. For each simulated lesion, 28 texture features in relation to the intensity histograms (GLIH), grey‐level co‐occurrence matrices (GLCOM), neighborhood difference matrices (GLNDM), and zone size matrices (GLZSM) were evaluated and compared with their respective values extracted from the ground truth activity map.Results:In reference to the values from the ground truth images, texture parameters appearing on the simulated data varied with a range of 0.73–3026.2% for GLIH‐based, 0.02–100.1% for GLCOM‐based, 1.11–173.8% for GLNDM‐based, and 0.35–66.3% for GLZSM‐based. For majority of the examined texture metrics (16/28), their values on the simulated data differed significantly from those from the ground truth images (P‐value ranges from <0.0001 to 0.04). Features not exhibiting significant difference comprised of GLIH‐based standard deviation, GLCO‐based energy and entropy, GLND‐based coarseness and contrast, and GLZS‐based low gray‐level zone emphasis, high gray‐level zone emphasis, short zone low gray‐level emphasis, long zone low gray‐level emphasis, long zone high gray‐level emphasis, and zone size nonuniformity.Conclusion:The extent to which PET imaging disturbs texture appearance is feature‐dependent and could be substantial. It is thus advised that use of PET texture parameters for predictive and prognostic measurements in oncologic setting awaits further systematic and critical evaluation.
SU‐F‐R‐41: Regularized PCA Can Model Treatment‐Related Changes in Head and Neck Patients Using Daily CBCTs
Authors: Chetvertkov M , Siddiqui F , Chetty I , Kumarasiri A , Liu C , Gordon J 
Published: July 2016

Purpose:To use daily cone beam CTs (CBCTs) to develop regularized principal component analysis (PCA) models of anatomical changes in head and neck (H&N) patients, to guide replanning decisions in adaptive radiation therapy (ART).Methods:Known deformations were applied to planning CT (pCT) images of 10 H&N patients to model several different systematic anatomical changes. A Pinnacle plugin was used to interpolate systematic changes over 35 fractions, generating a set of 35 synthetic CTs for each patient. Deformation vector fields (DVFs) were acquired between the pCT and synthetic CTs and random fraction‐to‐fraction changes were superimposed on the DVFs. Standard non‐regularized and regularized patient‐specific PCA models were built using the DVFs. The ability of PCA to extract the known deformations was quantified. PCA models were also generated from clinical CBCTs, for which the deformations and DVFs were not known. It was hypothesized that resulting eigenvectors/eigenfunctions with largest eigenvalues represent the major anatomical deformations during the course of treatment.Results:As demonstrated with quantitative results in the supporting document regularized PCA is more successful than standard PCA at capturing systematic changes early in the treatment. Regularized PCA is able to detect smaller systematic changes against the background of random fraction‐to‐fraction changes. To be successful at guiding ART, regularized PCA should be coupled with models of when anatomical changes occur: early, late or throughout the treatment course.Conclusion:The leading eigenvector/eigenfunction from the both PCA approaches can tentatively be identified as a major systematic change during radiotherapy course when systematic changes are large enough with respect to random fraction‐to‐fraction changes. In all cases the regularized PCA approach appears to be more reliable at capturing systematic changes, enabling dosimetric consequences to be projected once trends are established early in the treatment course.This work is supported in part by a grant from Varian Medical Systems, Palo Alto, CA
SU‐F‐R‐43: Recursive K‐Means Filter for Preserving Signals of Interest
Authors: Chu A , Yan P , Shih R , Wuu C 
Published: July 2016

Purpose:To use recursive cluster analysis to filter noises and artifacts out of useful signals. The method was applied to CT or CBCT for preserving interested low Hounsfield Unit (HU) signals such as lung tissues while the HU of lung tissues is often overlapped with CT (or CBCT) artifacts.Methods:Cluster analysis is to search for the similarity among data points, which could employ multi‐dimensional techniques. For our purpose, we searched for a robust, fast, and automatic process for sorting interested low HU object in CT, Therefore, 1‐D cluster analysis is suitable for the purpose. However, the 1‐D cluster analysis might not be able to sensitively separate the groups with overlap in values, for example, lung tissue and low‐HU CT artifacts. We found the recursive k‐mean (initialized by k‐mean++ over Euclidean distance) with division of small size groups can efficiently strip the low noises out and reveal the interested group by a repetitive fashion.Results:The algorithm of repetitively regrouping and filtering with a size of small division can effectively remove the low‐HU values of artifacts. Because artifacts are usually scattered separate groups, the lung tissues buried in the low‐HU groups can be revealed with an appropriate recursive steps.Conclusion:The filtering technique is efficient, robust and can be applied to many different applications as long as the distribution of interested signals can be considered as a cluster in value.