bluuebunny/crossref_metadata_2025_split huggingface dataset:
TU‐A‐12A‐07: CT‐Based Biomarkers to Characterize Lung Lesion: Effects of CT Dose, Slice Thickness and Reconstruction Algorithm Based Upon a Phantom Study
Authors: Zhao B , Tan Y , Tsai W , Lu L , Schwartz L , Lu Z , So J , Goldman J 
Published: July 2014

Purpose:Radiogenomics promises the ability to study cancer tumor genotype from the phenotype obtained through radiographic imaging. However, little attention has been paid to the sensitivity of image features, the image‐based biomarkers, to imaging acquisition techniques. This study explores the impact of CT dose, slice thickness and reconstruction algorithm on measuring image features using a thorax phantom.Methods:Twentyfour phantom lesions of known volume (1 and 2mm), shape (spherical, elliptical, lobular and spicular) and density (‐630, ‐10 and +100 HU) were scanned on a GE VCT at four doses (25, 50, 100, and 200 mAs). For each scan, six image series were reconstructed at three slice thicknesses of 5, 2.5 and 1.25mm with continuous intervals, using the lung and standard reconstruction algorithms. The lesions were segmented with an in‐house 3D algorithm. Fifty (50) image features representing lesion size, shape, edge, and density distribution/texture were computed. Regression method was employed to analyze the effect of CT dose, slice of thickness and reconstruction algorithm on these features adjusting 3 confounding factors (size, density and shape of phantom lesions).Results:The coefficients of CT dose, slice thickness and reconstruction algorithm are presented in Table 1 in the supplementary material. No significant difference was found between the image features calculated on low dose CT scans (25mAs and 50mAs). About 50% texture features were found statistically different between low doses and high doses (100 and 200mAs). Significant differences were found for almost all features when calculated on 1.25mm, 2.5mm, and 5mm slice thickness images. Reconstruction algorithms significantly affected all density‐based image features, but not morphological features.Conclusions:There is a great need to standardize the CT imaging protocols for radiogenomics study because CT dose, slice thickness and reconstruction algorithm impact quantitative image features to various degrees as our study has shown.
TU‐C‐16A‐01: Joint AAPM/SEFM/AMPR Educational Workshop On “Education of Radiotherapy Physicists”
Authors: Mahesh M , Borras C , Frey G , Ribas‐Morales M , Ballester F , Kazantsev P , Kostylev D 
Published: July 2014

This workshop is jointly organized by the AAPM, the Spanish (SEFM) and the Russian (AMPR) Medical Physics Societies, as part of formal educational exchange agreements signed by the AAPM with each one of these two societies.With the rapid technological advances in radiation therapy both for treatment and imaging, it is challenging how physics is taught to medical physicists practicing in radiation therapy. The main Objectives: of this workshop is to bring forth current status, challenges and issues related to education of radiation therapy physicists here in the US, Spain and Russia. Medical physicists from each one of these countries will present educational requirements of international recommendations and directives and analyze their impact on national legislations. Current and future educational models and plans for harmonization will be described. The role of universities, professional societies and examination boards, such as the American Board of Radiology, will be discussed. Minimum standards will be agreed upon.Learning Objectives:

Review medical physics educational models supported by AAPM, SEFM, and AMPR.
Discuss the role of governmental and non‐governmental organizations in elaborating and adopting medical physics syllabi.
Debate minimum educational standards for medical physics education based on country‐specific resources.
TU‐C‐19A‐01: “Leaning In” to Equal Opportunity for Women: The Responsibility of Individuals, Employers and Organizations
Authors: Ranger N , Travers E 
Published: July 2014

The publication of the book “Lean In” by Sheryl Sandberg created a lively discussion around the question of whether women were doing all they could do to ensure their own career success and advancement. In this session we will focus on the different roles and responsibilities that individuals, employers, and organizations need to embrace to ensure equal access to opportunity for individual women at all stages of their career. Initiatives within the AAPM and other professional organizations, institutional leadership and mentoring programs and strategies that individual women can adapt to take charge of their own career success, will be addressed.Learning Objectives:

Learn about the efforts within the AAPM and related organizations geared towards enhancing opportunities for women.
Learn about the types of programs that institutions can create to support career success.
Learn strategies to apply to your own career to enhance your professional success.
TU‐C‐BRE‐02: A Novel, Highly Efficient and Automated Quality Assurance Tool for Modern Linear Accelerators
Authors: Goddu S , Sun B , Yaddanapudi S , Kamal G , Baltes C , Rose S , Stinson K , Mutic S 
Published: July 2014

Purpose:Quality assurance (QA) of complex linear accelerators is critical and highly time consuming. Varian’s Machine Performance Check (MPC) uses IsoCal phantom to test geometric and dosimetric aspects of the TrueBeam systems in <5min. In this study we independently tested the accuracy and robustness of the MPC tools.Methods:MPC is automated for simultaneous image‐acquisition, using kV‐and‐MV onboard‐imagers (EPIDs), while delivering kV‐and‐MV beams in a set routine of varying gantry, collimator and couch angles. MPC software‐tools analyze the images to test: i) beam‐output and uniformity, ii) positional accuracy of isocenter, EPIDs, collimating jaws (CJs), MLC leaves and couch and iii) rotational accuracy of gantry, collimator and couch. 6MV‐beam dose‐output and uniformity were tested using ionization‐chamber (IC) and ICarray. Winston‐Lutz‐Tests (WLT) were performed to measure isocenter‐offsets caused by gantry, collimator and couch rotations. Positional accuracy of EPIDs was evaluated using radio‐opaque markers of the IsoCal phantom. Furthermore, to test the robustness of the MPC tools we purposefully miscalibrated a non‐clinical TrueBeam by introducing errors in beam‐output, energy, symmetry, gantry angle, couch translations, CJs and MLC leaves positions.Results:6MV‐output and uniformity were within ±0.6% for most measurements with a maximum deviation of ±1.0%. Average isocenter‐offset caused by gantry and collimator rotations was 0.316±0.011mm agreeing with IsoLock (0.274mm) and WLT (0.41mm). Average rotation‐induced couch‐shift from MPC was 0.378±0.032mm agreeing with WLT (0.35mm). MV‐and‐kV imager‐offsets measured by MPC were within ±0.15mm. MPC predicted all machine miscalibrations within acceptable clinical tolerance. MPC detected the output miscalibrations within ±0.61% while the MLC and couch positions were within ±0.06mm and ±0.14mm, respectively. Gantry angle miscalibrations were detected within ±0.1°.Conclusions:MPC is a useful tool for QA of TrueBeam systems and its automation makes it highly efficient for testing both geometric and dosimetric aspects of the machine. This is very important for hypo‐fractionated SBRT treatments.Received support from Varian Medical Systems, Palo Alto, CA 94304‐1038.
TU‐C‐BRE‐03: Aggregation of Linac Measurement Data
Authors: Kerns J , Alvarez P , Followill D , Lowenstein J , Molineu A , Summers P , Kry S 
Published: July 2014

Purpose:Accurate data of linear accelerator radiation characteristics is important for treatment planning system commissioning as well as regular quality assurance of the machine. The RPC has performed site visits of numerous machines . Data gathered from Varian machines from the past 15 years are presented. The data collected can be used as a secondary check or when commissioning a new machine to verify that values are reasonable.Methods:Data from the past 15 years of RPC site visits was compiled and analyzed. Data was composed from measurements from approximately 400 Varian machines. Each dataset consists of several point measurements at various locations in a water phantom to measure percentage depth dose, output factors, including small MLC fields, off‐axis factors, and wedge factors if applicable. Common statistical values are presented for each machine type. Where applicable, data was compared to other reference data given by the vendor or a select number of previous researchers.Results:Data is separated by energy and parameter and then analyzed by machine class. Data distributions of the parameter data were normal except occasionally at the tails. Distributions of the data for each class and parameter are tabulated to give not simply a singular reference value, but metrics about the distribution: 5th and 95th percentile values and the standard deviation as well as the median.Conclusion:The RPC has collected numerous data on Varian linacs and presented the finding of the past 15 years. The data can be used as a reference data set for physicists to compare against. A linac that deviates from the values does not necessarily indicate there is a problem as long as the treatment planning system correlates to the machine. Comparison of linac and treatment planning system data to external reference data can prevent serious treatment errors.
TU‐C‐BRE‐04: 3D Gel Dosimetry Using ViewRay On‐Board MR Scanner: A Feasibility Study
Authors: Zhang L , Du D , Green O , Rodriguez V , Wooten H , Xiao Z , Yang D , Hu Y , Li H 
Published: July 2014

Purpose:MR based 3D gel has been proposed for radiation therapy dosimetry. However, access to MR scanner has been one of the limiting factors for its wide acceptance. Recent commercialization of an on‐board MR‐IGRT device (ViewRay) may render the availability issue less of a concern. This work reports our attempts to simulate MR based dose measurement accuracy on ViewRay using three different gels.Methods:A spherical BANG gel dosimeter was purchased from MGS Research. Cylindrical MAGIC gel and Fricke gel were fabricated in‐house according to published recipes. After irradiation, BANG and MAGIC were imaged using a dual‐echo spin echo sequence for T2 measurement on a Philips 1.5T MR scanner, while Fricke gel was imaged using multiple spin echo sequences. Difference between MR measured and TPS calculated dose was defined as noise. The noise power spectrum was calculated and then simulated for the 0.35 T magnetic field associated with ViewRay. The estimated noise was then added to TG‐119 test cases to simulate measured dose distributions. Simulated measurements were evaluated against TPS calculated doses using gamma analysis.Results:Given same gel, sequence and coil setup, with a FOV of 180×90×90 mm3, resolution of 3×3×3 mm3, and scanning time of 30 minutes, the simulated measured dose distribution using BANG would have a gamma passing rate greater than 90% (3%/3mm and absolute). With a FOV 180×90×90 mm3, resolution of 4×4×5 mm3, and scanning time of 45 minutes, the simulated measuremened dose distribution would have a gamma passing rate greater than 97%. MAGIC exhibited similar performance while Fricke gel was inferior due to much higher noise.Conclusions:The simulation results demonstrated that it may be feasible to use MAGIC and BANG gels for 3D dose verification using ViewRay low‐field on‐board MRI scanner.
TU‐C‐BRE‐05: Clinical Implications of AAA Commissioning Errors and Ability of Common Commissioning ' Credentialing Procedures to Detect Them
Authors: McVicker A , Oldham M , Yin F , Adamson J 
Published: July 2014

Purpose:To test the ability of the TG‐119 commissioning process and RPC credentialing to detect errors in the commissioning process for a commercial Treatment Planning System (TPS).Methods:We introduced commissioning errors into the commissioning process for the Anisotropic Analytical Algorithm (AAA) within the Eclipse TPS. We included errors in Dosimetric Leaf Gap (DLG), electron contamination, flattening filter material, and beam profile measurement with an inappropriately large farmer chamber (simulated using sliding window smoothing of profiles). We then evaluated the clinical impact of these errors on clinical intensity modulated radiation therapy (IMRT) plans (head and neck, low and intermediate risk prostate, mesothelioma, and scalp) by looking at PTV D99, and mean and max OAR dose. Finally, for errors with substantial clinical impact we determined sensitivity of the RPC IMRT film analysis at the midpoint between PTV and OAR using a 4mm distance to agreement metric, and of a 7% TLD dose comparison. We also determined sensitivity of the 3 dose planes of the TG‐119 C‐shape IMRT phantom using gamma criteria of 3% 3mm.Results:The largest clinical impact came from large changes in the DLG with a change of 1mm resulting in up to a 5% change in the primary PTV D99. This resulted in a discrepancy in the RPC TLDs in the PTVs and OARs of 7.1% and 13.6% respectively, which would have resulted in detection. While use of incorrect flattening filter caused only subtle errors (<1%) in clinical plans, the effect was most pronounced for the RPC TLDs in the OARs (>6%).Conclusion:The AAA commissioning process within the Eclipse TPS is surprisingly robust to user error. When errors do occur, the RPC and TG‐119 commissioning credentialing criteria are effective at detecting them; however OAR TLDs are the most sensitive despite the RPC currently excluding them from analysis.
TU‐C‐BRE‐07: Quantifying the Clinical Impact of VMAT Delivery Errors Relative to Prior Patients’ Plans and Adjusted for Anatomical Differences
Authors: Stanhope C , Wu Q , Yuan L , Liu J , Hood R , Yin F , Adamson J 
Published: July 2014

Purpose:There is increased interest in the Radiation Oncology Physics community regarding sensitivity of pre‐treatment IMRT/VMAT QA to delivery errors. Consequently, tools mapping pre‐treatment QA to the patient DVH have been developed. However, the quantity of plan degradation that is acceptable remains uncertain. Using DVHs adapted from prior patients’ plans, we developed a technique to determine the magnitude of various delivery errors required to degrade a treatment plan to outside the clinically accepted range.Methods:DVHs for relevant organs at risk were adapted from a population of prior patients’ plans using a machine learning algorithm to establish the clinically acceptable DVH range specific to the patient’s anatomy. We applied this technique to six low‐risk prostate cancer patients treated with single‐arc VMAT and compared error‐induced DVH changes to the adapted DVHs to determine the magnitude of error required to push the plan outside of the acceptable range. The procedure follows: (1) Errors (systematic ' random shift of MLCs, gantry‐MLC desynchronization, dose rate fluctuations, etc.) were simulated and degraded DVHs calculated using the Varian Eclipse TPS. (2) Adapted DVHs and acceptable ranges for DVHs were established. (3) Relevant dosimetric indices and corresponding acceptable ranges were calculated from the DVHs. Key indices included NTCP (Lyman‐Kutcher‐Burman Model) and QUANTEC’s dose‐volume Objectives: s of V75Gy≤0.15 for the rectum and V75Gy≤0.25 for the bladder.Results:Degradations to the clinical plan became “unacceptable” for 19±29mm and 1.9±2.0mm systematic outward shifts of a single leaf and leaf bank, respectively. All other simulated errors fell within the acceptable range.Conclusion:Utilizing machine learning and prior patients’ plans one can predict a clinically acceptable range of DVH degradation for a specific patient. Comparing error‐induced DVH degradations to this range, it is shown that single‐arc VMAT plans for low‐risk prostate are relatively insensitive to many potential delivery errors.
TU‐C‐BRE‐09: Performance Comparisons of Patient Specific IMRT QA Methodologies Using ROC Analysis
Authors: McKenzie E , Balter P , Stingo F , Followill D , Jones J , Kry S 
Published: July 2014

Purpose:To evaluate the ability of a selection of patient‐specific QA methods to accurately classify IMRT plans as acceptable or unacceptable based on a multiple ion chamber (MIC) phantom.Methods:Twenty‐four IMRT plans were selected (20 previously failed the institutional QA), and were measured on a MIC phantom to assess their dosimetric acceptability. These same plans were then measured using film (Kodak EDR2) and ion chamber (Wellhofer cc04), ArcCheck (Sun Nuclear), and MapCheck (Sun Nuclear) (delivered AP field‐by‐field, AP composite, and with original gantry angles). All gamma analyses were performed at 2%/2mm, 3%/3mm, and 5%/3mm. By using the MIC results as a gold standard, the sensitivity and specificity were calculated across a range of cut‐off thresholds (% pixels passing for gamma analysis, and % dose difference for ion chamber), and were used to form ROC curves. Area under the curve (AUC) was used as a metric to quantify the performance of the various QA methods.Results:Grouping device’s AUC’s revealed two statistically significant different groups: ion chamber (AUC of 0.94), AP composite MapCheck (AUC of 0.85), ArcCheck (AUC of 0.84), and film (AUC of 0.82) were in the better performing group, while original gantry angles and AP field‐by‐field MapCheck (AUC of 0.65 and 0.66, respectively) matched less well with the gold standard results. Optimal cut‐offs were also assessed using the ROC curves. We found that while often 90% of pixels passing is used as a criteria, the differing sensitivities of QA methods can lead to device and methodology‐based optimal cutoff thresholds.Conclusion:While many methods exist to perform the same task of patient‐specific IMRT QA, they utilize different strategies. This work has shown that there are inconsistencies in these methodologies in terms of their sensitivity and specificity to dosimetric acceptability.This work was supported by Public Health Service grants CA010953, CA081647, and CA21661 awarded by the National Cancer Institute, United States Department of Health and Human Services.
TU‐C‐BRE‐10: A Streamlined Approach to EPID Transit Dosimetry
Authors: Morris B , Fontenot J 
Published: July 2014

Purpose:To investigate the feasibility of a simple and efficient transit dosimetry method using the electronic portal imaging device (EPID) for dose delivery error detection and prevention.Methods:In the proposed method, 2D reference transit images are generated for comparison with online images acquired during treatment. Reference transit images are generated by convolving through‐air EPID measurements of each field with pixel‐specific kernels selected from a library of pre‐calculated Monte Carlo pencil kernels of varying radiological thickness. The kernel used for each pixel is selected based on the calculated radiological thickness of the patient along a line joining the pixel and the virtual source. The accuracy of the technique was evaluated in flat homogeneous and heterogeneous plastic water phantoms, a heterogeneous cylindrical phantom, and an anthropomorphic head phantom. Gamma criteria of 3%/3 mm was used to quantify the accuracy of the technique for the various cases.Results:An average of 99.9% and 99.7% of the points in the comparison between the measured and predicted images passed a 3%/3mm gamma for the homogeneous and heterogeneous plastic water phantoms, respectively. 97.1% of the points passed for the analysis of the heterogeneous cylindrical phantom. For the anthropomorphic head phantom, an average of 97.8% of points passed the 3%/3mm gamma criteria for all field sizes. Failures were observed primarily in areas of drastic thickness or material changes and at the edges of the fields.Conclusion:The data suggest that the proposed transit dosimetry method is a feasible approach to in vivo dose monitoring. Future research efforts could include implementation for more complex fields and sensitivity testing of the method to setup errors and changes in anatomy.Oncology Data Systems provided partial funding support but did not participate in the collection or analysis of data
TU‐C‐9A‐01: IROC Organization and Clinical Trial Credentialing
Authors: Followill D , Molineu A , Xiao Y 
Published: July 2014

As a response to recommendations from a report from the Institute of Medicine, NCI is reorganizing it clinical trial groups into a National Clinical Trial Network (NCTN) that consists of four adult groups (Alliance, ECOGACRIN, NRG, and SWOG) and one children’s group (COG). NRG will house CIRO, a center to promote innovative radiation therapy research and intergroup collaboration in radiation. The quality assurance groups that support clinical trials have also been restructured. ITC, OSU Imaging corelab, Philadelphia Imaging core‐lab, QARC, RPC, and RTOGQA have joined together to create the Imaging and Radiation Oncology Core (IROC) Group. IROC’s mission is to provide integrated radiation oncology and diagnostic imaging quality control programs in support of the NCI’s NCTN thereby assuring high quality data for clinical trials designed to improve the clinical outcomes for cancer patients worldwide. This will be accomplished through five core services: site qualification, trial design support, credentialing, data management, case review. These changes are important for physicist participating in NCI clinical trials to understand. We will describe in detail the IROC’s activities and five core services so that as a user, the medical physicist can learn how to efficiently utilize this group. We will describe common pitfalls encountered in credentialing for current protocols and present methods to avoid them. These may include the which benchmarks are required for NSABP B‐51/RTOG 1304 and how to plan them as well as tips for phantom planning. We will explain how to submit patient and phantom cases in the TRIAD system used by IROC.Learning Objectives:

To understand the basic organization of IROC, its mission and five core services
To learn how to use TRIAD for patient and phantom data submission
To learn how to avoid common pitfalls in credentialing for current trials
TU‐C‐12A‐05: Repeatability Study of Reduced Field‐Of‐View Diffusion‐Weighted MRI On Human Thyroid Gland
Authors: Shukla‐Dave A , Lu Y , Hatzoglou V , Banerjee S , Stambuk H , Shankaranarayanan A , Mazaheri Y , Deasy J 
Published: July 2014

Purpose:To investigate the repeatability of reduced field‐of‐view diffusion‐weighted imaging (rFOV DWI) in quantifying apparent diffusion coefficients (ADCs) for human thyroid glands in a clinical setting.Methods:Nine healthy human volunteers were enrolled and underwent 3T MRI exams. For each volunteer, 3 longitudinal exams (2 weeks apart) with 2 repetitive sessions within each exam, including rFOV and conventional full field‐of‐view (fFOV) DWI scans, were performed. In the acquired DWI images, a fixed‐size region of interest (ROI; diameter=8mm) was placed on thyroid glands to calculate ADC. ADC was calculated using a monoexponential function with a noise correction scheme. The repeatability of ADC was assessed by using coefficient variation (CV) across sessions or exams, which was defined to be: r = 1‐CV, 0 < r < 1, where CV=STD/m, STD is the standard deviation of ADC, and m is the average of ADC across sessions or exams. An experienced radiologist assessed and scored rFOV and fFOV DW images based on image characteristics (1, nondiagnostic; 2, poor; 3, satisfactory; 4, good; and 5, excellent).Analysis of variance (ANOVA) was performed to compare ADC values, CV of ADC, repeatability of ADC across sessions and exams, and radiologic scores between rFOV and fFOV DWI techniques.Results:There was no significant difference in ADC values across sessions and exams either in rFOV or fFOV DWI. The average CVs of both rFOV and fFOV DWI were less than 13%. The repeatability of ADC measurement between rFOV and fFOV DWI was not significantly different. The overall image quality was significantly higher with rFOV DWI than with fFOV DWI.Conclusion:This study suggested that ADCs from both rFOV and fFOV DWI were repeatable, but rFOV DWI had superior imaging quality for human thyroid glands in a clinical setting.