bluuebunny/crossref_metadata_2025_split huggingface dataset:
MO‐A‐BRB‐01: Review of TG‐262 Internal Survey of Practices in EMR for External Beam Therapy
Authors: Mechalakos J. 
Published: June 2015

The process of converting to an electronic chart for radiation therapy can be daunting. It requires a dedicated committee to first research and choose appropriate software, to review the entire documentation policy and flow of the clinic, to convert this system to electronic form or if necessary, redesign the system to more easily conform to the electronic process. Those making the conversion and those who already use electronic charting would benefit from the shared experience of those who have been through the process in the past. Therefore TG262 was convened to provide guidance on electronic charting for external beam radiation therapy and brachytherapy.This course will present the results of an internal survey of task group members on EMR practices in External Beam Radiation Therapy as well as discuss important issues in EMR development and structure for both EBRT and brachytherapy.Learning Objectives:

Be familiarized with common practices and pitfalls in development and maintenance of an electronic chart in Radiation Oncology
Be familiarized with important issues related to electronic charting in External Beam Radiation Therapy
Be familiarized with important issues related to electronic charting in Brachytherapy
MO‐A‐BRB‐02: Considerations and Issues in Electronic Charting for Brachytherapy
Authors: Richardson S. 
Published: June 2015

The process of converting to an electronic chart for radiation therapy can be daunting. It requires a dedicated committee to first research and choose appropriate software, to review the entire documentation policy and flow of the clinic, to convert this system to electronic form or if necessary, redesign the system to more easily conform to the electronic process. Those making the conversion and those who already use electronic charting would benefit from the shared experience of those who have been through the process in the past. Therefore TG262 was convened to provide guidance on electronic charting for external beam radiation therapy and brachytherapy.This course will present the results of an internal survey of task group members on EMR practices in External Beam Radiation Therapy as well as discuss important issues in EMR development and structure for both EBRT and brachytherapy.Learning Objectives:

Be familiarized with common practices and pitfalls in development and maintenance of an electronic chart in Radiation Oncology
Be familiarized with important issues related to electronic charting in External Beam Radiation Therapy
Be familiarized with important issues related to electronic charting in Brachytherapy
MO‐AB‐BRA‐01: A Novel Method to Objectively Quantify Normal Tissue Toxicity in the Esophagus
Authors: Niedzielski J , Yang J , Stingo F , Krafft S , Martel M , Briere T , Mohan R , Court L 
Published: June 2015

Purpose:Inconsistency between NTCP models for esophagitis prediction leads to reduced treatment efficacy, and arises from using subjective endpoints. We investigate esophageal swelling as an objective endpoint for NTCP modeling.Methods:A novel voxel‐based method was developed to quantify expansion in the esophagus. Utilizing deformable image registration (DIR) between a plan and serial CT image set, this technique calculates esophageal volume change from the Jacobian Map. This voxel‐volume change quantifies esophageal swelling. Next, a technique was developed to reduce uncertainty in esophageal volume change calculations due to physiological variation (i.e. swallowing, esophageal air pockets, etc.). The technique's effectiveness was evaluated by comparing expansion calculations on week01 CTs with and without corrections for 65 patients. This methodology was tested on sixty‐five patients with NSCLC that had esophagitis scoring (CTCAE3.0, 15 Grade3, 31 Grade2, 19 Grade0) and 6–8 weekly 4DCTs during treatment (IMRT). Esophageal swelling was analyzed for the treatment week of highest response. Dose was accumulated weekly using DIR. Logistic regression models were used to examine the relationship between expansion and grade3 esophagitis, and used to determine optimal binary endpoints of expansion. The relationship between dose and esophageal expansion as the endpoint was compared with dose to grade NTCP models. Performance of models was quantified with area under the curve (AUC) from ROC analysis.Results:Uncertainty in esophageal expansion calculations were reduced from 14.3% to 6.9%. The following expansion metrics were the most significantly correlated to grade3 esophagitis: maximum expansion (AUC=0.87,pval<0.001) and length of esophagus expanding>20% (LExp20%) (AUC=0.88,pval<0.01). The optimal expansion endpoint metrics were: Maximum Expansion>1.4 and LExp20%>50mm. Multivariate NTCP model with expansion endpoints outperformed NTCP model with grade endpoints: dose‐to‐expansion endpoint AUC=0.91, dose‐to‐grade endpoint AUC=0.81.Conclusion:Esophageal swelling is a continuous, objective, and in‐vivo metric of esophageal toxicity. Esophageal swelling endpoints can increase the performance of NTCP models.
MO‐AB‐BRA‐04: Correct Identification of Low‐Attenuation Intracranial Hemorrhage and Calcification Using Dual‐Energy Computed Tomography in a Phantom System
Authors: Nute J , Jacobsen M , Wei W , Baiu C , Popnoe D , Schellingerhout D , Cody D 
Published: June 2015

Purpose:Intracranial hemorrhage and calcification with Single‐Energy CT (SECT) attenuation below 100HU cannot be reliably identified using currently clinically available means. Calcification is typically benign but hemorrhage can carry a risk of intracranial bleeding and contraindicate use of anticoagulant therapies. A biologically‐relevant phantom was used to investigate identification of unknown intracranial lesions using dual‐energy CT (DECT) as a verification of prior lesion differentiation results.Methods:Prior phantom work investigating calcification and hemorrhage differentiation resulted in 3D‐DECT raw data (water density, calcium density, 68keV) for a range of DECT protocol variations: image thicknesses (1.25, 2.5, 3.75, 5mm), CTDIvol (36.7 to 132.6mGy) and reconstruction algorithms (Soft, Standard, Detail). Acquisition‐specific raw data were used to create a plane of optimal differentiation based on the geometric bisector of 3D‐linear regression of the two lesion distributions. Verification hemorrhage and calcification lesions, ranging in size from 0.5 to 1.5cm, were created at varying attenuation from 50 to 100HU. Lesions were inserted into a biologically‐relevant brain phantom and scanned using SECT (3.75mm images, Standard, 67mGy) and a range of DECT protocols (3.75mm images, Standard, [67, 105.6, 132.6mGy]). 3D‐DECT data were collected and blinded for analysis. The 3D‐DECT distribution of the lesion was then compared to the acquisition‐matched geometric bisector plane and the mean lesion value's position relative to the plane, indicating lesion identity, and the percentage of voxels on the identified side of the plane, indicating identification confidence, were derived.Results:98% of the 120 lesions investigated were identified correctly as hemorrhage or calcification. 74% were identified with greater than 80% confidence. Increases in CTDIvol and lesion diameter were associated with increased identification confidence.Conclusion:Intracranial lesions of unknown etiology were identified with 80% confidence for 74% of lesions investigated. These phantom data suggest that the identification of intracranial lesions below 100HU is clinically feasible using DECT.This research was conducted at the MD Anderson Center for Advanced Biomedical Imaging in‐part with equipment support from General Electric Healthcare
MO‐AB‐BRA‐05: Monte Carlo Simulation of Glandular Breast Dose in Mammography Using Breast CT‐Derived Glandular Distributions
Authors: Hernandez A , Boone J , Seibert J 
Published: June 2015

Purpose:To determine the effect of breast CT‐derived fibroglandular distributions on glandular dose in mammography.Methods:Previously‐reported 3D glandular distributions, obtained from a large cohort of breast CT (bCT) data sets (N=219), were fit to bi‐Gaussian functions and used as probability density maps to assign glandular distributions within compressed breast models. Using a conventional mammography geometry, MCNPX was used to simulate monoenergetic normalized glandular dose “DgN(E)” values in compressed phantoms composed of either a homogeneous mixture of glandular and adipose tissue or heterogeneously distributed glandular tissue. The DgN(E) values were weighted by mammographic x‐ray spectra to produce polyenergetic DgN (pDgN) values for the homogeneous (pDgNhomo) and heterogeneous (pDgNhetero) tissue compositions. This work quantified the effect of permutations in glandular fraction, phantom size, x‐ray technique, and location of glandular distributions on pDgN values.Results:Averaged across all phantom sizes and glandular fractions, pDgNhetero values were 30.1% and 21.6% lower than the pDgNhomo values for the Mo and W x‐ray spectra, respectively, when the heterogeneous distributions were centered within the breast phantom. Displacement of the glandular distributions in the superior and inferior directions resulted in pDgNhetero values 5.7% and 49.4% lower than pDgNhomo values, respectively, for Mo x‐ray spectra. Lateral displacement of the glandular distributions resulted in no notable difference in pDgN values.Conclusion:This study demonstrates that glandular dose values in mammography are 20 to 30% lower than assumed using the homogeneous approximation resulting from overestimation of glandular tissue at the breast entrance where the dose deposition is higher. The sensitivity analysis also demonstrates that the differences depend on likely perturbations in the glandular distributions. While these results are robust because the glandular distributions are modeled from a large cohort of bCT data sets, future work will focus on improved quantification of the glandular distributions based on breast size and glandular fraction.
MO‐AB‐BRA‐06: Noise Index for Model Based Iterative Reconstruction (MBIR)? A Prospective Trial with 110 Human Subjects
Authors: Gomez‐Cardona D , Li K , Lubner M G , Pickhardt P J , Chen G‐H 
Published: June 2015

Purpose:Noise index (NI) enables the mAs to be automatically determined to achieve the desired CT noise level. The scientific foundation behind the use of NI is the linear relationship between noise variance (σ2) and the 1/mAs. This relationship has been severely violated by the use of the highly nonlinear MBIR algorithm, making the traditional NI system no longer valid. This work studied how the quantitative relationship between σ2 and mAs should be modified in MBIR so that a new NI‐mAs correspondence can be established.Methods:A comprehensive investigation using an anthropomorphic abdominal phantom, in‐vivo swine, and an IRB‐approved prospective human subject trial with a cohort of 110 subjects was performed. All scans were performed using a 64‐slice CT scanner (Discovery CT750 HD, GE Healthcare) with typical abdominal protocols. Several mAs levels were used for the phantom and swine (10–350 mAs), while for human subjects two mAs levels were used. Both FBP and MBIR (Veo, GE Healthcare) reconstructions were performed. Values of σ2 were measured in relatively uniform regions such as liver and fat. The measured variances were related to mAs through the power‐law relationship σ2 = α(mAs)^(−β).Results:For liver, β is 1.0±0.10 for FBP and 0.4±0.12 for MBIR. The difference in β between the two methods is statistically significant (p<0.001). For patients with a given size (effective diameter∼28 cm), the α value is 1.2×10⁵ for FBP and 600 for MBIR. The R2 value fitting was 0.96±0.03.Conclusion:As long as the noise magnitude of a standard dose FBP image is known, in addition to predicting the noise magnitude of the corresponding MBIR image at the same dose, one can also predict the noise magnitude of the MBIR image at reduced dose. Therefore, it is both plausible and necessary to establish a new NI‐mAs correspondence system for the MBIR.This work was partially supported by an NIH grant R01CA169331 and GE Healthcare. K. Li, D. Gomez‐Cardona, M. G. Lubner: Nothing to disclose. P. J. Pickhardt: Co‐founder, VirtuoCTC, LLC Stockholder, Cellectar Biosciences, Inc. G.‐ H. Chen: Research funded, GE Healthcare; Research funded, Siemens AX.
MO‐AB‐BRA‐07: Prompt Gamma‐Ray Spectroscopy for Range Verification of Clinical Proton Beams
Authors: Verburg J , Bortfeld T , Seco J 
Published: June 2015

Purpose:We developed a pre‐clinical prototype system for range verification of proton pencil‐beam scanning fields. The system was evaluated using phantom treatment plans delivered with a clinical dose rate.Methods:The absolute range of proton pencil‐beams was verified through an optimization procedure, which matches energy‐ and time‐resolved prompt gamma‐ray measurements with models, based on cross sections for discrete prompt gamma‐ray line excitations. Phantom experiments were performed with a pre‐clinical prototype detector, using treatment plans delivered with a clinical pencil‐beam scanning system. The detector consisted of an actively shielded lanthanum(III) bromide scintillator. Tungsten was used to collimate the gamma‐rays. To support high event rates, the detector readout featured custom amplifiers and an active voltage divider for the photomultiplier. The detector signals were acquired by fast analog‐to‐digital converters and processed using digital algorithms. The data acquisition was also synchronized with the pencil‐beam scanning and dosimetry systems.Results:We successfully acquired prompt gamma‐ray spectra during the delivery of proton pencil‐beams with a clinical beam current of 2 nA at the exit of the treatment head. The number of events in the primary detector ranged from 1 × 10⁶ to 2 × 10⁶ per second. In phantom experiments, non‐uniform range errors were introduced by placing strips of plastic in the beam path. The magnitudes and positions of these range errors were correctly detected in two‐dimensional range maps that were generated from the measurements. With our small scale prototype, a 1.0 mm standard deviation on the absolute range required about 5 × 10⁸ protons per delivered pencil‐beam.Conclusions:Prompt gamma‐ray spectroscopy to verify the absolute range of proton beams was demonstrated under clinical pencil‐beam delivery conditions. A 1 mm to 2 mm range verification accuracy for a field delivering 1 Gy, appears feasible with a full scale system.This work was supported by the Federal Share of program income earned on C06‐CA059267, Proton Therapy Research and Treatment Center.
MO‐AB‐BRA‐08: Rapid Treatment Field Uniformity Optimization for Total Skin Electron Beam Therapy Using Cherenkov Imaging
Authors: Andreozzi J , Jarvis L , Zhang R , Williams B , Glaser A , Pogue B , Gladstone D 
Published: June 2015

Purpose:To evaluate treatment field heterogeneity resulting from gantry angle choice in total skin electron beam therapy (TSEBT) following a modified Stanford dual‐field technique, and determine a relationship between source to surface distance (SSD) and optimized gantry angle spread.Methods:Cherenkov imaging was used to image 62 treatment fields on a sheet of 1.2m × 2.2m × 1.2cm polyethylene following standard TSEBT setup at our institution (6 MeV, 888 MU/min, no spoiler, SSD=441cm), where gantry angles spanned from 239.5° to 300.5° at 1° increments. Average Cherenkov intensity and coefficient of variation in the region of interest were compared for the set of composite Cherenkov images created by summing all unique combinations of angle pairs to simulate dual‐field treatment. The angle pair which produced the lowest coefficient of variation was further studied using an ionization chamber. The experiment was repeated at SSD=300cm, and SSD=370.5cm. Cherenkov imaging was also implemented during TSEBT of three patients.Results:The most uniform treatment region from a symmetric angle spread was achieved using gantry angles +/−17.5° about the horizontal axis at SSD=441cm, +/−18.5° at SSD=370.5cm, and +/−19.5° at SSD=300cm. Ionization chamber measurements comparing the original treatment spread (+/−14.5°) and the optimized angle pair (+/−17.5°) at SSD=441cm showed no significant deviation (r=0.999) in percent depth dose curves, and chamber measurements from nine locations within the field showed an improvement in dose uniformity from 24.41% to 9.75%. Ionization chamber measurements correlated strongly (r=0.981) with Cherenkov intensity measured concurrently on the flat Plastic Water phantom. Patient images and TLD results also showed modest uniformity improvements.Conclusion:A decreasing linear relationship between optimal angle spread and SSD was observed. Cherenkov imaging offers a new method of rapidly analyzing and optimizing TSEBT setup geometry by providing a 2D image of the treatment plane as a sum of the two fields.This study has been funded by NIH grants R21EB17559 and R01CA109558 as well as Norris Cotton Cancer Center Pilot funding.
MO‐AB‐BRA‐10: Cancer Therapy Outcome Prediction Based On Dempster‐Shafer Theory and PET Imaging
Authors: Lian C , Li H , Denoeux T , Chen H , Robinson C. , Vera P , Ruan S 
Published: June 2015

Purpose:In cancer therapy, utilizing FDG‐18 PET image‐based features for accurate outcome prediction is challenging because of 1) limited discriminative information within a small number of PET image sets, and 2) fluctuant feature characteristics caused by the inferior spatial resolution and system noise of PET imaging. In this study, we proposed a new Dempster‐Shafer theory (DST) based approach, evidential low‐dimensional transformation with feature selection (ELT‐FS), to accurately predict cancer therapy outcome with both PET imaging features and clinical characteristics.Methods:First, a specific loss function with sparse penalty was developed to learn an adaptive low‐rank distance metric for representing the dissimilarity between different patients’ feature vectors. By minimizing this loss function, a linear low‐dimensional transformation of input features was achieved. Also, imprecise features were excluded simultaneously by applying a l2,1‐norm regularization of the learnt dissimilarity metric in the loss function. Finally, the learnt dissimilarity metric was applied in an evidential K‐nearest‐neighbor (EK‐ NN) classifier to predict treatment outcome.Results:Twenty‐five patients with stage II–III non‐small‐cell lung cancer and thirty‐six patients with esophageal squamous cell carcinomas treated with chemo‐radiotherapy were collected. For the two groups of patients, 52 and 29 features, respectively, were utilized. The leave‐one‐out cross‐validation (LOOCV) protocol was used for evaluation. Compared to three existing linear transformation methods (PCA, LDA, NCA), the proposed ELT‐FS leads to higher prediction accuracy for the training and testing sets both for lung‐cancer patients (100+/−0.0, 88.0+/−33.17) and for esophageal‐cancer patients (97.46+/−1.64, 83.33+/−37.8). The ELT‐FS also provides superior class separation in both test data sets.Conclusion:A novel DST‐ based approach has been proposed to predict cancer treatment outcome using PET image features and clinical characteristics. A specific loss function has been designed for robust accommodation of feature set incertitude and imprecision, facilitating adaptive learning of the dissimilarity metric for the EK‐NN classifier.
MO‐AB‐207‐01: ACR Update in CT
Authors: McNitt‐Gray M. 
Published: June 2015

A goal of an imaging accreditation program is to ensure adequate image quality, verify appropriate staff qualifications, and to assure patient and personnel safety. Currently, more than 35,000 facilities in 10 modalities have been accredited by the American College of Radiology (ACR), making the ACR program one of the most prolific accreditation options in the U.S. In addition, ACR is one of the accepted accreditations required by some state laws, CMS/MIPPA insurance and others. Familiarity with the ACR accreditation process is therefore essential to clinical diagnostic medical physicists. Maintaining sufficient knowledge of the ACR program must include keeping up‐to‐date as the various modality requirements are refined to better serve the goals of the program and to accommodate newer technologies and practices. This session consists of presentations from authorities in four ACR accreditation modality programs, including magnetic resonance imaging, computed tomography, nuclear medicine, and mammography. Each speaker will discuss the general components of the modality program and address any recent changes to the requirements.Learning Objectives:

To understand the requirements of the ACR MR Accreditation program. The discussion will include accreditation of whole‐body general purpose magnets, dedicated extremity systems well as breast MRI accreditation. Anticipated updates to the ACR MRI Quality Control Manual will also be reviewed.
To understand the requirements of the ACR CT accreditation program, including updates to the QC manual as well as updates through the FAQ process.
To understand the requirements of the ACR nuclear medicine accreditation program, and the role of the physicist in annual equipment surveys and the set up and supervision of the routine QC program.
To understand the current ACR MAP Accreditation requirement and present the concepts and structure of the forthcoming ACR Digital Mammography QC Manual and Program.
MO‐AB‐207‐04: ACR Update in Mammography
Authors: Berns E. 
Published: June 2015

A goal of an imaging accreditation program is to ensure adequate image quality, verify appropriate staff qualifications, and to assure patient and personnel safety. Currently, more than 35,000 facilities in 10 modalities have been accredited by the American College of Radiology (ACR), making the ACR program one of the most prolific accreditation options in the U.S. In addition, ACR is one of the accepted accreditations required by some state laws, CMS/MIPPA insurance and others. Familiarity with the ACR accreditation process is therefore essential to clinical diagnostic medical physicists. Maintaining sufficient knowledge of the ACR program must include keeping up‐to‐date as the various modality requirements are refined to better serve the goals of the program and to accommodate newer technologies and practices. This session consists of presentations from authorities in four ACR accreditation modality programs, including magnetic resonance imaging, computed tomography, nuclear medicine, and mammography. Each speaker will discuss the general components of the modality program and address any recent changes to the requirements.Learning Objectives:

To understand the requirements of the ACR MR Accreditation program. The discussion will include accreditation of whole‐body general purpose magnets, dedicated extremity systems well as breast MRI accreditation. Anticipated updates to the ACR MRI Quality Control Manual will also be reviewed.
To understand the requirements of the ACR CT accreditation program, including updates to the QC manual as well as updates through the FAQ process.
To understand the requirements of the ACR nuclear medicine accreditation program, and the role of the physicist in annual equipment surveys and the set up and supervision of the routine QC program.
To understand the current ACR MAP Accreditation requirement and present the concepts and structure of the forthcoming ACR Digital Mammography QC Manual and Program.