bluuebunny/crossref_metadata_2025_split huggingface dataset:
MO‐E‐17A‐05: Individualized Patient Dosimetry in CT Using the Patient Dose (PATDOSE) Algorithm
Authors: Hernandez A , Boone J 
Published: July 2014

Purpose:Radiation dose to the patient undergoing a CT examination has been the focus of many recent studies. While CTDIvol and SSDE‐based methods are important tools for patient dose management, the CT image data provides important information with respect to CT dose and its distribution. Coupled with the known geometry and output factors (kV, mAs, pitch, etc.) of the CT scanner, the CT dataset can be used directly for computing absorbed dose.Methods:The HU numbers in a patient's CT data set can be converted to linear attenuation coefficients (LACs) with some assumptions. With this (PAT‐DOSE) method, which is not Monte Carlo‐based, the primary and scatter dose are computed separately. The primary dose is computed directly from the geometry of the scanner, x‐ray spectrum, and the known patient LACs. Once the primary dose has been computed to all voxels in the patient, the scatter dose algorithm redistributes a fraction of the absorbed primary dose (based on the HU number of each source voxel), and the methods here invoke both tissue attenuation and absorption and solid angle geometry. The scatter dose algorithm can be run N times to include Nth‐scatter redistribution. PAT‐DOSE was deployed using simple PMMA phantoms, to validate its performance against Monte Carlo‐derived dose distributions.Results:Comparison between PAT‐DOSE and MCNPX primary dose distributions showed excellent agreement for several scan lengths. The 1st‐scatter dose distributions showed relatively higher‐amplitude, long‐range scatter tails for the PAT‐DOSE algorithm then for MCNPX simulations.Conclusion:The PAT‐DOSE algorithm provides a fast, deterministic assessment of the 3‐D dose distribution in CT, making use of scanner geometry and the patient image data set. The preliminary implementation of the algorithm produces accurate primary dose distributions however achieving scatter distribution agreement is more challenging. Addressing the polyenergetic x‐ray spectrum and spatially dependent scatter fractions will improve algorithm accuracy.Funding Support: UC Davis Clinical and Translational Science Center (CTSC) Award; NIH IMSD Student Fellowship; Saxon Student FellowshipDisclosure: PATENT Royalties from Samsung for dosimetry algorithm
MO‐E‐17A‐12: Direct Realization of the CT Dose to Phantom: Energy to Heat Conversion in Polyethylene Using Calorimetry
Authors: Chen‐Mayer H , Tosh R 
Published: July 2014

Purpose:To develop a primary reference standard for absorbed dose to phantom for medical CT dosimetry. CT dosimetry relies on the implementation of the CTDI standard based on air kerma. We are taking a step toward an absorbed dose to water standard by first investigating the dose in a solid phantom. By directly measuring the heat converted from the incident radiation, the absorbed dose in the phantom at a point can be assessed with primary methods without relying on indirect conversions.Methods:The calorimeter contains two small thermistors embedded in a removable PE “core” inserted into the cylindrical HDPE phantom. A core made with polystyrene (PS) was also tested because of its purportedly negligible heat defect. Measurements were made using the two cores and with a calibrated ionization chamber in a CT beam. The air chamber values were converted to the dose to medium using appropriate stopping‐power ratios from the literature, and then compared to the thermal data.Results:The PS core data yielded a dose of 1.3 times (4‐run average, 3% std. dev.) higher than the converted chamber value, whereas the PE core data were inexplicably higher. The possible systematic errors include 1) excess heat from the thermistors, 2) in PE the exothermic chemical reactions, 3) uncertainties of the specific heat capacities of the materials, 4) thermal drift, and 5) theoretical conversion of chamber values. Monte Carlo simulations and finite element heat transfer calculations were performed to address some of these issues. The general validity was assessed in a 6 MV photon beam with an entirely different calibration scheme.Conclusion:This study demonstrates the feasibility but also revealed the difficulty in developing a new primary reference standard for absorbed dose to material for CT. Additional experimental and theoretical work is planned to achieve our goal.
MO‐F‐16A‐05: Spot‐Scanning Proton Therapy Patient‐Specific Quality Assurance: Our Methodology and Results From 295 Treatment Plans
Authors: Mackin D , Zhang X , Li Y , Li H , Wu R , Poenisch F , Suzuki K , Kerr M , Holmes C , Zhu X , Sahoo N , Gillin M 
Published: July 2014

Purpose:To report on the patient‐specific quality assurance (PSQA) results for 295 spot‐scanning proton therapy treatment plans from the MD Anderson PTC‐Houston. We show how the results differed by treatment site and how they were affected by the treatment plan optimization method and by a range shifter in the treatment field. We also discuss some causes of PSQA problems.Methods:The PSQA procedure, which is designed to verify both the accuracy of the treatment planning system's (Eclipse™ v8.9) dose calculations and the dose delivery of the Hitachi PROBEAT synchrotron, consists of (1) an end‐to‐end test in which the beam is delivered and measured at the prescribed gantry angle, and (2) additional dose plane measurements made from gantry angle 270°. HPlusQA™ software automatically performs the gamma analysis with criteria 3% (dose tolerance), 3 mm (distance‐to‐agreement, DTA) and 2%, 2 mm. Passing is defined as at least 90% of the pixels having a gamma score less than 1.Results:The PSQA gamma passing rate was 96.2% for 3%, 3 mm, and 85.3% for 2%, 2 mm. The rate depended on the treatment site. For example, the 3%, 3 mm passing rate was 95% for head and neck plans, vs 100% for prostate plans. The passing rates of multi‐ vs. single‐field optimization plans did not significantly differ. However, the rate for fields with range shifters was 94.8±0.6%, vs 99.0±0.6% for those without (p = 0.002). Longitudinal dose gradients caused most of the low scores. Overestimation of the calculated dose proximal to the spread‐out Bragg peak (SOBP) caused many of the others.Conclusion:The planned and delivered doses consistently agreed within tolerance levels. Minor dose modeling deficiencies remain proximal to the SOBP. The 3% dose tolerance, 3 mm DTA, with 90% pixel passing rate is a reasonable action level for 2D gamma comparisons.
MO‐G‐19A‐01: ABR Exams; A Glimpse Behind the Curtains
Authors: Ibbott G , Dieterich S , Yester M , Allison J , Seibert J 
Published: July 2014

While the vast majority of clinical medical physicists either have taken, or will take the ABR certification exams, there appears to be limited understanding about the process of creating, administering, scoring and evaluating the exams. In this course, ABR trustees and volunteers will educate current and future ABR diplomates about the process of question writing, written exam assembly, evaluation of the performance of the exams, and preparation and delivery of the oral board exam. By understanding the process behind creating the written and oral exams, ABR candidates and diplomates will gain a better understanding of the framework of the exams, including the financial resources needed. At the same time, understanding the many hours of volunteer work needed to create a fair and meaningful exam may create a positive incentive to respect the exam confidentiality.Learning Objectives:

Understand the characteristics of a well‐written exam question.
Learn about the process of developing and administering an exam.
Review the application of psychometric analysis to the ABR exams.
Appreciate the effort and expense involved in preparing the certification exams.
MO‐G‐BRE‐01: A Real‐Time Virtual Delivery System for Photon Radiotherapy Delivery Monitoring
Authors: Shi F , Gu X , Graves Y , Jiang S , Jia X 
Published: July 2014

Purpose:Treatment delivery monitoring is important for radiotherapy, which enables catching dosimetric error at the earliest possible opportunity. This project develops a virtual delivery system to monitor the dose delivery process of photon radiotherapy in real‐time using GPU‐based Monte Carlo (MC) method.Methods:The simulation process consists of 3 parallel CPU threads. A thread T1 is responsible for communication with a linac, which acquires a set of linac status parameters, e.g. gantry angles, MLC configurations, and beam MUs every 20 ms. Since linac vendors currently do not offer interface to acquire data in real time, we mimic this process by fetching information from a linac dynalog file at the set frequency. Instantaneous beam fluence map (FM) is calculated. A FM buffer is also created in T1 and the instantaneous FM is accumulated to it. This process continues, until a ready signal is received from thread T2 on which an inhouse developed MC dose engine executes on GPU. At that moment, the accumulated FM is transferred to T2 for dose calculations, and the FM buffer in T1 is cleared. Once the calculation finishes, the resulting 3D dose distribution is directed to thread T3, which displays it in three orthogonal planes overlaid on the CT image for treatment monitoring. This process continues to monitor the 3D dose distribution in real‐time.Results:An IMRT and a VMAT cases used in our patient‐specific QA are studied. Maximum dose differences between our system and treatment planning system are 0.98% and 1.58% for the two cases, respectively. The average time per MC calculation is 0.1sec with <2% relative uncertainty. The update frequency of ∼10Hz is considered as real time.Conclusion:By embedding a GPU‐based MC code in a novel data/work flow, it is possible to achieve real‐time MC dose calculations to monitor delivery process.
MO‐G‐BRE‐02: A Survey of IMRT QA Practices for More Than 800 Institutions
Authors: Pulliam K , Kerns J , Howell R , Followill D , O' Daniel J , Kry S 
Published: July 2014

Purpose:A wide range of techniques and measurement devices are employed for IMRT QA, causing a large variation of accepted action limits and potential follow up for failing plans. Such procedures are not well established or accepted in the medical physics community. To achieve the goal of proving insight into current IMRT QA practices, we created an electronic IMRT QA survey. The survey was open to a variety of the most common QA devices and assessed the type of comparison to measurement, action limits, delivery methods, and clinical action for failing QA plans.Methods:We conducted an online survey through the Radiological Physics Center's (RPC) annual survey with the goal of ascertaining elements of routine patient‐specific IMRT QA. A total of 874 institutions responded to the survey. The questions ranged from asking for action limits, dosimeter type(s) used, delivery techniques, and actions taken when a plan fails IMRT QA.Results:The most common (52%) planar gamma criteria was 3%/3 mm with a 95% of pixels passing criteria. The most common QA device were diode arrays (48%). The most common first response to a plan failing QA was to re‐measure at the same point the point dose (89%), second was to re‐measure at a new point (13%), and third was to analyze the plan in relative instead of absolute mode (10%) (Does not add to 100% as not all institutions placed a response for each QA follow‐up option). Some institutions, however, claimed that they had never observed a plan failure.Conclusion:The survey provided insights into the way the community currently performs IMRT QA. This information will help in the push to standardize action limits among dosimeters.
MO‐G‐BRE‐04: Automatic Verification of Daily Treatment Deliveries and Generation of Daily Treatment Reports for a MR Image‐Guided Treatment Machine
Authors: Yang D , li x , Li H , Wooten H , Green O , Rodriguez V , Mutic S 
Published: July 2014

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.
MO‐G‐BRE‐06: Metrics of Success: Measuring Participation and Attitudes Related to Near‐Miss Incident Learning Systems
Authors: Nyflot MJ , Kusano AS , Zeng J , Carlson JC , Novak A , Sponseller P , Jordan L , Kane G , Ford EC 
Published: July 2014

Purpose:Interest in incident learning systems (ILS) for improving safety and quality in radiation oncology is growing, as evidenced by the upcoming release of the national ILS. However, an institution implementing such a system would benefit from quantitative metrics to evaluate performance and impact. We developed metrics to measure volume of reporting, severity of reported incidents, and changes in staff attitudes over time from implementation of our institutional ILS.Methods:We analyzed 2023 incidents from our departmental ILS from 2/2012–2/2014. Incidents were prospectively assigned a near‐miss severity index (NMSI) at multidisciplinary review to evaluate the potential for error ranging from 0 to 4 (no harm to critical). Total incidents reported, unique users reporting, and average NMSI were evaluated over time. Additionally, departmental safety attitudes were assessed through a 26 point survey adapted from the AHRQ Hospital Survey on Patient Safety Culture before, 12 months, and 24 months after implementation of the incident learning system.Results:Participation in the ILS increased as demonstrated by total reports (approximately 2.12 additional reports/month) and unique users reporting (0.51 additional users reporting/month). Also, the average NMSI of reports trended lower over time, significantly decreasing after 12 months of reporting (p<0.001) but with no significant change at months 18 or 24. In survey data significant improvements were noted in many dimensions, including perceived barriers to reporting incidents such as concern of embarrassment (37% to 18%; p=0.02) as well as knowledge of what incidents to report, how to report them, and confidence that these reports were used to improve safety processes.Conclusion:Over a two‐year period, our departmental ILS was used more frequently, incidents became less severe, and staff confidence in the system improved. The metrics used here may be useful for other institutions seeking to create or evaluate their own incident learning systems.
MO‐G‐BRF‐03: BEST IN PHYSICS (JOINT IMAGING‐THERAPY) – Using Quantitative MRI to Test the Validity of the Reaction‐Diffusion Equation in Describing in Vivo Glioma Growth
Authors: Hormuth D , Weis J , Rericha E , Yankeelov T 
Published: July 2014

Purpose:The reaction‐diffusion equation has been used extensively to model brain tumor growth. However, no one has used quantitative, in vivo imaging data to invert the reaction‐diffusion equation to estimate model parameters and then use those values to predict future growth. In this contribution first we determine, in silico, the measurement strategies required to accurately estimate model parameters and test how accurately these parameters can be used to predict future growth. We then perform the analogous studies in vivo where quantitative diffusion weighted magnetic resonance imaging (DW‐MRI) data is used to estimate cell number to constrain and initialize the reaction‐diffusion equation.Methods:Measurement strategies were tested using an in silico tumor, seeded within a rat brain domain and “grown” for 9 days as dictated by the reactiondiffusion equation. Parameters were estimated from data subsets (using days 1–2,1–3,…1‐8) and used to predict subsequent growth. Prediction accuracy was assessed at the region of interest (total volume and cell number, and Dice value) and voxel (concordance correlation coefficient, CCC) levels. Guided by the simulation results, DW‐MRI data was acquired in rats (n=12) with C6 gliomas and used to evaluate the model's accuracy for predicting in vivo tumor growth.Results:Both the in silico and in vivo experiments returned error below 15% when predicting total cell number and volume 1–4 days into the future. The in silico study had CCC and Dice values greater than 0.93 for these predictions. However, the in vivo study had lower Dice (0.64–0.81) and quite poor CCC (0.11–0.25) values.Conclusion:The simulations show that the reaction‐diffusion equation can be used to make accurate bulk scale (i.e., total tumor volume and tumor cell number) predictions of in vivo tumor growth. However, the poor voxel level agreement, suggests the reaction‐diffusion equation is an incomplete description of in vivo C6 glioma growth.NCI‐1U01CA174706, NCI‐ P30CA068485, NCI‐ R01CA138599, NCIR25CA136440
MO‐G‐BRF‐07: Optical Characterization of Novel Terbium‐Doped Nanophosphors Excited by Clinical Electron and Photon Beams for Potential Use in Molecular Imaging Or Photodynamic Therapy
Authors: Darafsheh A , Paik T , Tenuto M , Najmr S , Friedberg J , Murray C , Finlay J 
Published: July 2014

Purpose:Optical properties of terbium (Tb3+)‐doped gadolinium trifluoride (GdF3) nanoplates irradiated by electron and photon beams were investigated for their potential as optical probes. The contribution of induced Cerenkov radiation in exciting the nanophosphors was investigated as well.Methods:The emission spectra of Terbium‐doped GdF3 dispersed in hexane, embedded in tissue mimicking phantoms were collected by an optical fiber connected to a CCD‐coupled spectrograph, while the samples were irradiated by a medical linear accelerator with electron beams of energies 6, 9, 12, 16, and 20 MeV or X‐ray beams of energies of 6, and 15 MV. The contribution of induced Cerenkov radiation in exciting the nanophosphores was investigated in a dedicated experimental apparatus through optical isolation of the samples and also by using 125 kVp X‐ray beams whose energy is below the threshold for generating Cerenkov radiation in that medium.Results:Terbium‐doped GdF3 nanoplates show characteristic cathodoluminescence emission peaks at 488, 543, 586, and 619 nm, which are responsible for the characteristic f‐f transition of terbium ion. In a series of experiments, the contribution of Cerenkov radiation in the luminescence of such nanophosphors was ruled out.Conclusion:We have characterized the optical properties of Terbium‐doped GdF3 nanoplates. Such nanocrystals with emission tunability and high surface area that facilitates attachment with targeting reagents are promising in situ light source candidates for molecular imaging or exciting a photosensitizer for ultralow fluence photodynamic therapy.This work is supported by the Department of Radiation Oncology at the University of Pennsylvania, the American Cancer Society through IRG‐78‐002‐28, and the University of Pennsylvania's Nano/Bio Interface Center through NSEC DMR08‐32802.
MO‐G‐BRF‐09: Local and Global Function Probability of the Liver
Authors: Wang H , Feng M , Jackson A , R Ten Haken , Lawrence T , Cao Y 
Published: July 2014

Purpose:To develop a local‐and‐global liver function probability model to aid in physiologically adaptive RT in patients with intrahepatic cancer.Methods:Twenty‐two patients enrolled in an IRB‐approved study had liver DCE‐MRI and Indocyanine green (ICG) clearance tests prior to, during and 1 month post RT. The percentage of ICG retention in the blood plasma 15 minutes after administration (ICG‐R15) was used as an overall liver function measure. Portal venous perfusion images were derived from DCE‐MRI. Assuming parallel architecture in the liver and considering both volume and function effects of tissue subunits, a global liver function probability Pl was assumed to be a volume‐weighted summation of local function probabilities p of subunits, excluding the subunits with p<γ, a threshold indicting poor function. The local function probability p was mapped from portal venous perfusion F by a logistic function p(F)=1/(1+(F50/F)^n), where we considered function probabilities saturated at high perfusion and suppressed at low perfusion. Finally, Pl was linearly fitted to a logarithm of ICG‐R15 to determine parameters (F50, n, γ). The leave‐m‐out technique was used to cross‐validate the model. This model was applied to evaluate the doseresponse of the local function probability one month after RT.Results:The best fitted values of (F50, n, γ) were 65.3ml/(100g.min), 2.86 and 0.14, respectively. The leave‐one‐out and 10‐fold tests resulted in 66.34±3.21 and 69.26±}10.35ml/(100g.min) of F50, 2.90±0.76 and 3.25±1.59 of n, and 0.14±0.03 and 0.13±}0.05 of γ, respectively. The derived Pl significantly correlated with ICG‐R15 logarithm (r=0.66, P<;1e‐6). Average percentage reduction in the local function probability post‐RT was related to the local dose by a logistic function (P=1e−6).Conclusion:The local‐and‐global liver function probability model has the potential to guide dose redistribution during a course of treatment to spare liver functional subunits, thereby allowing target d5 ose intensification without increasing the risk for complication.The work was supported by NIH/NCI grant RO1CA132834.