bluuebunny/crossref_metadata_2025_split huggingface dataset:
MO‐C‐12A‐01: Quantitative Imaging Initiatives: Why, Who, What, and How?
Authors: Sullivan D , Jackson E , Clarke L , Petrick N , Russek S 
Published: July 2014

Over the past decade, there has been an increasing focus on quantitative imaging (QI), which, according to one definition, is “the extraction of quantifiable features from medical images for the assessment of normal or the severity, degree of change, or status of a disease, injury, or chronic condition relative to normal” (www.rsna.org/QIBA). To achieve the goals of QI requires the development and standardization of data acquisition, data analysis, and data display techniques, as well as appropriate reporting structures. As such, successful implementation of QI relies heavily on expertise from the fields of medical physics, radiology, statistics, and informatics as well as collaboration from vendors of imaging acquisition, analysis, and reporting systems. When successfully implemented, QI techniques will provide image‐derived metrics with known bias and variance that can be validated with anatomically and physiologically relevant measures, including treatment response, and the heterogeneity of that response, and outcome. Such non‐invasive measures can then be used effectively in clinical and translational research as well as patient care. In addition to modality‐specific QI efforts implemented by individual scientific organizations, national and international organizations, including the NCI, RSNA, FDA, and NIST, appreciating the tremendous potential of QI but also understanding the associated challenges, have become increasingly involved. This symposium session will focus on 1) introducing QI and illustrating why it is important, even though challenging, in both research and clinical applications, and 2) providing overviews of QI efforts from national and international organizations, including the RSNA, NCI, FDA, and NIST.Learning Objectives:

Understand the importance and potential of QI in research and clinical applications.
Understand key challenges of QI and current barriers to implementation.
Understand the current QI efforts of several national and international agencies and organizations, including the FDA, NCI, NIST, and RSNA.
MO‐E‐18A‐01: Imaging: Best Practices In Pediatric Imaging
Authors: Willis C , Strauss K , MacDougall R , Sammet C 
Published: July 2014

This imaging educational program will focus on solutions to common pediatric imaging challenges. The speakers will present collective knowledge on best practices in pediatric imaging from their experience at dedicated children's hospitals. Areas of focus will include general radiography, the use of manual and automatic dose management in computed tomography, and enterprise‐wide radiation dose management in the pediatric practice.The educational program will begin with a discussion of the complexities of exposure factor control in pediatric projection radiography. Following this introduction will be two lectures addressing the challenges of computed tomography (CT) protocol optimization in the pediatric population. The first will address manual CT protocol design in order to establish a managed radiation dose for any pediatric exam on any CT scanner. The second CT lecture will focus on the intricacies of automatic dose modulation in pediatric imaging with an emphasis on getting reliable results in algorithmbased technique selection. The fourth and final lecture will address the key elements needed to developing a comprehensive radiation dose management program for the pediatric environment with particular attention paid to new regulations and obligations of practicing medical physicists.Learning Objectives:

To understand how general radiographic techniques can be optimized using exposure indices in order to improve pediatric radiography.
To learn how to establish diagnostic dose reference levels for pediatric patients as a function of the type of examination, patient size, and individual design characteristics of the CT scanner.
To learn how to predict the patient's radiation dose prior to the exam and manually adjust technique factors if necessary to match the patient's dose to the department's established dose reference levels.
To learn how to utilize manufacturer‐provided automatic dose modulation technology to consistently achieve patient doses within the department's established size‐based diagnostic reference range.
To understand the key components of an enterprise‐wide pediatric dose management program that integrates the expanding responsibilities of medial physicists in the new era of dose monitoring.
MO‐E‐BRE‐01: Determination, Minimization and Communication of Uncertainties in Radiation Therapy
Authors: Van Dyk J , Palta J , Bortfeld T , Mijnheer B 
Published: July 2014

Medical Physicists have a general understanding of uncertainties in the radiation treatment process, both with respect to dosimetry and geometry. However, there is a desire to be more quantitative about uncertainty estimation. A recent International Atomic Energy Agency (IAEA) report (about to be published) recommends that we should be as “accurate as reasonably achievable, technical and biological factors being taken into account”. Thus, a single recommendation as a goal for accuracy in radiation therapy is an oversimplification. That report also suggests that individual clinics should determine their own level of uncertainties for their specific treatment protocols. The question is “how do we implement this in clinical practice”? AAPM Monograph 35 (2011 AAPM Summer School) addressed many specific aspects of uncertainties in each of the steps of a course of radiation treatment. The intent of this symposium is: (1) to review uncertainty considerations in the entire radiation treatment process including uncertainty determination for each step and uncertainty propagation for the total process, (2) to consider aspects of robust optimization which optimizes treatment plans while protecting them against uncertainties, and (3) to describe various methods of displaying uncertainties and communicating uncertainties to the relevant professionals. While the theoretical and research aspects will also be described, the emphasis will be on the practical considerations for the medical physicist in clinical practice.Learning Objectives:

To review uncertainty determination in the overall radiation treatment process.
To consider uncertainty modeling and uncertainty propagation.
To highlight the basic ideas and clinical potential of robust optimization procedures to generate optimal treatment plans that are not severely affected by uncertainties.
To describe methods of uncertainty communication and display.
MO‐E‐BRD‐01: Adapt‐A‐Thon – Texas Hold’em Invitational
Authors: Kessler M , Brock K , Pouliot J , Dong L 
Published: July 2014

Software tools for image‐based adaptive radiotherapy such as deformable image registration, contour propagation and dose mapping have progressed beyond the research setting and are now commercial products available as part of both treatment planning systems and stand‐alone applications. These software tools are used together to create clinical workflows to detect, track and evaluate changes in the patient and to accumulate dose. Deviations uncovered in this process are used to guide decisions about replanning/adaptation with the goal of keeping the delivery of prescribed dose “on target” throughout the entire course of radiotherapy. Since the output from one step of the adaptive process is used as an input for another, it is essential to understand and document the uncertainty associated with each of the step and how these uncertainties are propagated. This in turn requires an understanding how the underlying tools work. Unfortunately, important details about the algorithms used to implement these tools are scarce or incomplete, too often for competitive reasons. This is in contrast to the situation involving other basic treatment planning algorithms such as dose calculations, where the medical physics community essentially requires vendors to provide physically important details about their underlying theory and clinical implementation. Vendors should adopt this same level of information sharing when it comes to the tools and techniques for image guided adaptive radiotherapy. The goal of this session is to start this process by inviting vendors and medical physicists to discuss and demonstrate the available tools and describe how they are intended to be used in clinical practice. The format of the session will involve a combination of formal presentations, interactive demonstrations, audience participation and some friendly “Texas style” competition.Learning Objectives:

Understand the components of the image‐based adaptive radiotherapy process.
Understand the how these components are implemented in various commercial systems.
Understand the different use cases and workflows currently supported these tools.
MO‐E‐17A‐02: Incorporation of Contrast Medium Dynamics in Anthropomorphic Phantoms: The Advent of 5D XCAT Models
Authors: Sahbaee P , Samei E , Segars W 
Published: July 2014

Purpose:To develop a unique method to incorporate the dynamics of contrast‐medium propagation into the anthropomorphic phantom, to generate a five‐dimensional (5D) patient model for multimodality imaging studies.Methods:A compartmental model of blood circulation network within the body was embodied into an extended cardiac‐torso (4D‐XCAT) patient model. To do so, a computational physiologic model of the human cardiovascular system was developed which includes a series of compartments representing heart, vessels, and organs. Patient‐specific cardiac output and blood volume were used as inputs influenced by the weight, height, age, and gender of the patient's model. For a given injection protocol and given XCAT model, the contrast‐medium transmission within the body was described by a series of mass balance differential equations, the solutions to which provided the contrast enhancement‐time curves for each organ; thereby defining the tissue materials including the contrastmedium within the XCAT model. A library of time‐dependent organ materials was then defined. Each organ in each voxelized 4D‐XCAT phantom was assigned to a corresponding time‐varying material to create the 5D‐XCAT phantom in which the fifth dimension is blood/contrast‐medium within the temporal domain.Results:The model effectively predicts the time‐varying concentration behavior of various contrast‐medium administration in each organ for different patient models as function of patient size (weight/height) and different injection protocol factors (injection rate and pattern, iodine concentration or volume). The contrast enhanced XCAT patient models was developed based on the concentration of iodine as a function of time after injection.Conclusion:Majority of medical imaging systems take advantage of contrast‐medium administration in terms of better image quality, the effect of which was ignored in previous optimization studies. The study enables a comprehensive optimization of contrast administration both in terms of image quality and radiation dose, and can be used in different modalities such as CT, MRI, and ultrasound.
MO‐E‐17A‐06: Organ Dose in Abdomen‐Pelvis CT: Does TG 111 Equilibrium Dose Concept Better Accounts for KVp Dependence Than Conventional CTDI?
Authors: Li X , Morgan A , Dong F , Primak A , Davros W , Segars W 
Published: July 2014

Purpose:In CT imaging, a desirable quality assurance (QA) dose quantity should account for the dose variability across scan parameters and scanner models. Recently, AAPM TG 111 proposed to use equilibrium dose‐pitch product, in place of CT dose index (CTDI100), for scan modes involving table translation. The purpose of this work is to investigate whether this new concept better accounts for the kVp dependence of organ dose than the conventional CTDI concept.Methods:The adult reference female extended cardiac‐torso (XCAT) phantom was used for this study. A Monte Carlo program developed and validated for a 128‐slice CT system (Definition Flash, Siemens Healthcare) was used to simulate organ dose for abdomenpelvis scans at five tube voltages (70, 80, 100, 120, 140 kVp) with a pitch of 0.8 and a detector configuration of 2×64×0.6 mm. The same Monte Carlo program was used to simulate CTDI100 and equilibrium dose‐pitch product. For both metrics, the central and peripheral values were used together with helical pitch to calculate a volume‐weighted average, i.e., CTDIvol and (Deq)vol, respectively.Results:While other scan parameters were kept constant, organ dose depended strongly on kVp; the coefficient of variation (COV) across the five kVp values ranged between 70–75% for liver, spleen, stomach, pancreas, kidneys, colon, small intestine, bladder, and ovaries, all of which were inside the primary radiation beam. One‐way analysis of variance (ANOVA) for the effect of kVp was highly significant (p=3e−30). When organ dose was normalized by CTDIvol, the COV across the five kVp values reduced to 7–16%. The effect of kVp was still highly significant (p=4e−4). When organ dose was normalized by (Deq)vol, the COV further reduced to 4−12%. The effect of kVp was borderline significant (p=0.04).Conclusion:In abdomen‐pelvis CT, TG 111 equilibrium dose concept better accounts for kVp dependence than the conventional CTDI.This work is supported by a faculty startup fund from the Cleveland State University.
MO‐E‐17A‐11: In‐Phantom Detector Response in a Kilovoltage X‐Ray Beam
Authors: Lawless M , DeWerd L 
Published: July 2014

Purpose:To investigate changes in detector response in a kilovoltage x‐ray beam as a function of depth in phantom.Methods:Detector response in a 120kVp x‐ray beam as a function of depth in a PMMA phantom was determined for a reference class Exradin A12 ionization chamber, an Exradin A1SL ionization chamber, TLD‐100 and EBT3 radiochromic film and normalized to a depth of 1cm. The output of each detector was referenced to the A12 ionization chamber reading to assess changes in detector response as a function of depth. The BEAMnrc, DOSxyz, and egs_chamber user codes of the EGSnrc Monte Carlo code were used to calculate the dose delivered to the detectors from an x‐ray source with similar beam quality to the one used in the measurements.Results:Changes in detector response relative to the A12 ionization chamber of 2%, 7%, and 14% for the A1SL, TLDs, and film, respectively, were observed with the larger changes in response occurring at larger depths. The Monte Carlo calculated changes in dose response showed less deviation, with the largest difference being within 2%.Conclusion:The Monte Carlo simulations show that doses delivered to the different detectors are quite similar, while measurements show that the detector output varies drastically. This indicates that the detector output per unit dose is changing with depth, most likely due to changes in the photon spectrum that occur because of scatter and attenuation of the primary beam. Because detector calibration is often performed at a single point in the kilovoltage energy range, the change in detector response needs to be considered when the measurement conditions differ from those of the calibration. This is of particular concern in computed tomography dose measurement, where calibrations are performed at shallow depths or in air, and measurements are made at deeper locations.
MO‐E‐18C‐01: Open Access Web‐Based Peer‐To‐Peer Training and Education in Radiotherapy
Authors: Pawlicki T , Brown D , Dunscombe P , Mutic S 
Published: July 2014

Purpose:Current training and education delivery models have limitations which result in gaps in clinical proficiency with equipment, procedures, and techniques. Educational and training opportunities offered by vendors and professional societies are by their nature not available at point of need or for the life of clinical systems. The objective of this work is to leverage modern communications technology to provide peer‐to‐peer training and education for radiotherapy professionals, in the clinic and on demand, as they undertake their clinical duties.Methods:We have developed a free of charge web site (https://i.treatsafely.org) using the Google App Engine and datastore (NDB, GQL), Python with AJAX‐RPC, and Javascript. The site is a radiotherapy‐specific hosting service to which user‐created videos illustrating clinical or physics processes and other relevant educational material can be uploaded. Efficient navigation to the material of interest is provided through several RT specific search tools and videos can be scored by users, thus providing comprehensive peer review of the site content. The site also supports multilingual narration\translation of videos, a quiz function for competence assessment and a library function allowing groups or institutions to define their standard operating procedures based on the video content.Results:The website went live in August 2013 and currently has over 680 registered users from 55 countries; 27.2% from the United States, 9.8% from India, 8.3% from the United Kingdom, 7.3% from Brazil, and 47.5% from other countries. The users include physicists (57.4%), Oncologists (12.5%), therapists (8.2%) and dosimetrists (4.8%). There are 75 videos to date including English, Portuguese, Mandarin, and Thai.Conclusion:Based on the initial acceptance of the site, we conclude that this open access web‐based peer‐to‐peer tool is fulfilling an important need in radiotherapy training and education. Site functionality should expand in the future to include document sharing and continuing education credits.
MO‐E‐18C‐04: Advanced Computer Simulation and Visualization Tools for Enhanced Understanding of Core Medical Physics Concepts
Authors: Naqvi S 
Published: July 2014

Purpose:Most medical physics programs emphasize proficiency in routine clinical calculations and QA. The formulaic aspect of these calculations and prescriptive nature of measurement protocols obviate the need to frequently apply basic physical principles, which, therefore, gradually decay away from memory. E.g. few students appreciate the role of electron transport in photon dose, making it difficult to understand key concepts such as dose buildup, electronic disequilibrium effects and Bragg‐Gray theory. These conceptual deficiencies manifest when the physicist encounters a new system, requiring knowledge beyond routine activities.Methods:Two interactive computer simulation tools are developed to facilitate deeper learning of physical principles. One is a Monte Carlo code written with a strong educational aspect. The code can “label” regions and interactions to highlight specific aspects of the physics, e.g., certain regions can be designated as “starters” or “crossers,” and any interaction type can be turned on and off. Full 3D tracks with specific portions highlighted further enhance the visualization of radiation transport problems. The second code calculates and displays trajectories of a collection electrons under arbitrary space/time dependent Lorentz force using relativistic kinematics.Results:Using the Monte Carlo code, the student can interactively study photon and electron transport through visualization of dose components, particle tracks, and interaction types. The code can, for instance, be used to study kerma‐dose relationship, explore electronic disequilibrium near interfaces, or visualize kernels by using interaction forcing. The electromagnetic simulator enables the student to explore accelerating mechanisms and particle optics in devices such as cyclotrons and linacs.Conclusion:The proposed tools are designed to enhance understanding of abstract concepts by highlighting various aspects of the physics. The simulations serve as virtual experiments that give deeper and long lasting understanding of core principles. The student can then make sound judgements in novel situations encountered beyond routine clinical activities.
MO‐F‐16A‐04: Case Study: Estimation of Peak Skin Dose Following a Physician Reported “High Dose” Case and Sentinel Event Considerations
Authors: Supanich M , Chu J , Wehmeyer A 
Published: July 2014

Purpose:This work offers as a teaching example a reported high dose fluoroscopy case and the workflow the institution followed to self‐report a radiation overdose sentinel event to the Joint Commission.Methods:Following the completion of a clinical case in a hybrid OR room with a reported air kerma of >18 Gy at the Interventional Reference Point (IRP) the physicians involved in the case referred study to the institution's Radiation Safety Committee (RSC) for review. The RSC assigned a Diagnostic Medical Physicist (DMP) to estimate the patient's Peak Skin Dose (PSD) and analyze the case. Following the DMP's analysis and estimate of a PSD of >15 Gy the institution's adverse event committee was convened to discuss the case and to self‐report the case as a radiation overdose sentinel event to the Joint Commission. The committee assigned a subgroup to perform the root cause analysis and develop institutional responses to the event.Results:The self‐reporting of the sentinel event and the associated root cause analysis resulted in several institutional action items that are designed to improve process and safety. A formal reporting and analysis mechanism was adopted to review fluoroscopy cases with air kerma greater than 6 Gy at the IRP. An improved and formalized radiation safety training program for physicians using fluoroscopy equipment was implemented. Additionally efforts already under way to monitor radiation exposure in the Radiology department were expanded to include all fluoroscopy equipment capable of automated dose reporting.Conclusion:The adverse event review process and the root cause analysis following the self‐reporting of the sentinel event resulted in policies and procedures that are expected to improve the quality and safe usage of fluoroscopy throughout the institution.
MO‐F‐16A‐07: Establishing Reference Values for All CT Exams and Monitoring Them: The Texas Experience
Authors: Clements J , Moirano J , Lindsey R 
Published: July 2014

Purpose:To establish reference levels (RLs) in terms of standard dose metrics (CTDIvol and DLP) for all CT exams performed in a community hospital and monitor clinical exams performed against RLs.Methods:Clinical CT exams already performed were categorized by body region and CTDIvol and DLP values were analyzed. RLs for the dose metrics were established at either the ACR RL or at approximately the 75th percentile for the patient population performed at the facility. Once RLs were set, all patient exams performed were compared to the RLs. Monthly summaries were completed which include the exam type, applicable RL, actual dose metric, and initials of the technologist performing the exam. Performance summaries are posted in the department and discussed quarterly at CT dose committee meetings.Results:Initially, significant overages were observed for abdomen/pelvis exams that used the CTDIvol RL established by the ACR (25 mGy). This RL is for 70 kg patients while a disproportionate number of the patients in our patient population exceed this weight. As a Result, a separate RL was established for abdomen pelvis exams for patients greater than 90kg. After adjusting the abdomen/pelvis RL for patient weight, the total number of exams exceeding RLs has dropped by 50% over a period of 6 months.Conclusion:This work indicates the potential for optimizing CT exams with respect to patient exposure by establishing region‐specific RLs, monitoring values, publishing results, and providing education to staff performing exams. Reasonable RLs have been set for body region and modified based on patient size. This illustrates the need for considering more than an absolute maximum value as a RL and the process of continuous quality improvement. Commercial software has been purchased and will allow for the establishment of more refined RLs and more comprehensive analysis.