bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐FF‐T‐501: The Effect of Monte Carlo‐Based Dose Calculations On Tumor Control Probability Modeling
Authors: Huang E , Lindsay P , Hope A , El Naqa I , Bradley J , Deasy J 
Published: April 2010

Purpose: It has not been established whether accurate lung dosimetry really has an impact on metrics and modeling related to outcome prediction. We studied the impact of Monte Carlo‐based dose calculations on TCP modeling of lung cancer tumors. Methods and Materials: All analyzable patients treated for NSCLC between 1991 and 2001 at Washington University in St. Louis (n=56) had TCP modeled using water equivalent dosimetry and Monte‐Carlo corrected dosimetry in turn. Clinical factors in the modeling included age, gender, chemotherapy, performance status, weight loss, and smoking. Dosimetric variables included Vx, Dx, maximum dose, mean dose and minimum dose covering the primary GTV. The best multivariate logistic models for both treatment planning system dose (homogeneous, uncorrected for tissue heterogeneities) and Monte‐Carlo corrected dose were obtained. Results: The best multivariate model for homogeneous dose calculations is a six‐parameter model (Spearman's rank correlation coefficient, R=0.62) including V75_TCPgtvPlan, V80_TCPgtvPlan, Mindose_TCPgtvPlan, age, PreTxChemo and gtvVol. However, there was not a strong preference for specific dose‐volume terms, and many models had a similar predictive power. The best multivariate model for Monte‐Carlo corrected dose is a two‐parameter model (R=0.527) including V75_TCPgtvMC and gtvVol, and the modeling strongly indicated that only two terms were necessary to explain the data. Interestingly, the Monte Carlo model has the superior ‘face validity” while the water‐based model resulted in a higher overall predictive power. The reasons for this are currently unknown. Conclusions: Monte‐Carlo corrected dose significantly impacts resulting TCP modeling, which demonstrates the need accurate modeling. Differences in the resulting models between water‐based and Monte Carlo based dosimetry remain poorly understood and will require further research.Partially supported by NIH R01 grant CA85181.
MO‐SAM‐BRB‐01: Biological Aspects of Heavy Charged Particle Radiation Therapy
Authors: Paganetti H 
Published: April 2010

The relative biological effectiveness (RBE) is defined as the ratio of the doses required by two radiations to cause the same level of effect. Thus, the RBE depends on the dose and the biological endpoint.Proton therapy has been based on the use of a generic RBE of 1.1, which is applied to all treatments independent of dose/fraction, position in the irradiated volume, initial beam energy or the particular tissue. The variability of RBE in clinical situations is believed to be within 10% but quantitative dependencies of the RBE on various physical and biological properties are disregarded. The magnitude of RBE values and their variations is significantly larger for Carbon ion therapy. Studies have demonstrated significant RBE values of more than 3 in clinically relevant scenarios for Carbon ions. Further, there might be considerable variations in RBE within the irradiated volume that are being considered in treatment planning and delivery.Heavy ions have a potential advantage compared to protons when it comes to their therapeutic ratio due to an elevated RBE in the tumor (based on the oxygen enhancement ratio and higher average LET values) compared to the surrounding tissue. However, on the other hand, at present there are still considerable uncertainties in heavy ion RBE values. Elevated RBE values (even for protons) might be expected particularly near the edges of the high‐dose volume because doses may be deposited by high‐LET particles. The increase in RBE as a function of depth in the patient results in an extension of the bio‐effective range of the beam. Further, because RBE values may increase with deceasing dose causing elevated RBE values for organs at risk compared to the target area. In order to incorporate detailed RBE modeling in treatment planning as a function of LET, dose and endpoint, two aspects have to be considered. Firstly, the available information from experimental studies and secondly, our ability to calculate RBE values for a given treatment plan based on parameters extracted from such experiments. RBE values are often based on cell survival data because this is the main endpoint of interest in radiation therapy. However, one migt expect differences in RBE for cell survival compared to cell mutation, the latter being an important endpoint for late effects.This educational session will focus on summarizing the mechanisms behind RBE variations among treatment modalities. Further, RBE variations as a function of LET, tissue and dose will be presented based on experimental and simulated data for proton and Carbon ion beams. Finally, different approaches for theoretical modeling of RBE values for treatment planning purposes will be discussed briefly.Learning Objectives:1. Understand the mechanisms behind heavy charged particle RBE values2. Understand the variations of RBE as a function of physical and biological parameters3. Understand the clinical implication of RBE values in proton and Carbon ion therapy
MO‐SAM‐304A‐01: Optimizing CT Dose and Image Quality for Different Patient Sizes
Authors: Cody D , McNitt‐Gray M 
Published: April 2010

CT technology has improved dramatically over the past decade and its clinical utilization has increased significantly as well. While CT can yield exquisite descriptions of anatomy that were not previously possible (at least not with noninvasive techniques), its increased utilization has led concerns over radiation dose; CT has now been identified as the single largest contributor to medical radiation dose to the population and accounts for approximately 50% of medical exposure. Methods to reduce radiation dose have been the focus of all stakeholders (medical physicists, technologists, radiologists, manufacturers and regulators). Reducing dose while maintaining acceptable image quality can be complex and this is made even more complex when considering patients of different sizes. This talk will first describe methods currently used, and some being developed, to estimate radiation dose in patients. This will include a discussion of measurement techniques as well as Monte Carlo simulation‐based techniques. Specific attention will be paid to the differences in dose to patients of different sizes ranging from pediatric patients to obese adult patients. Tradeoffs in image quality and radiation dose will also be described in this context as well. Radiation dose reduction techniques, including a review of various tube current modulation schemes currently being employed will also be described. The effect of these dose reduction methods on both radiation dose and image quality will be discussed, again with attention to how they can be deployed with patients of different size.Learning Objectives:1. Understand how radiation dose for CT studies is currently estimated2. Understand the trade‐offs of dose and image quality, especially for large (obese) patients and in pediatric patients3. Review of the manufacturers' dose modulation methods and how these affect dose in different patients
MO‐A‐213A‐01: Harmonic Imaging
Authors: Zagzebski J 
Published: April 2010

The purpose of this course is to acquaint participants with recent signal processing techniques and modes on ultrasound instruments. Emphasis is on second harmonic imaging, a processing and display mode implemented on most scanners. Harmonic imaging was originally applied to enhance echo signals due to nonlinear scattering by ultrasound contrast agents. However, the modality is much more commonly used in “native tissue harmonic” mode, where echoes originating from nonlinear components of propagating acoustic beams are detected and displayed. The source of these echo signals and the advantages and disadvantages of harmonic imaging will be described. When applied effectively, harmonic imaging provides significant improvements in image quality compared to that obtained using conventional signal processing. A primary reason for harmonic imaging's improved image quality is reduction of acoustic noise caused by reverberations within overlying tissues. Other contributors to high quality ultrasound images include spatial and frequency compounding and speckle reduction. These techniques also will be described and placed in context with harmonic imaging.Learning ObjectivesAfter completing this course, participants will:1. Describe the origin of harmonic echo signals for both conventional and contrast agent imaging modes;2. Contrast resolution and penetration capabilities for harmonic imaging and linear imaging;3. Identify clinical situations where harmonic imaging is used advantageously;4. Describe how harmonic imaging is used to enhance detection of contrast agents;5. State the benefits of spatial and frequency compounding, and speckle reduction.
MO‐B‐211A‐01: Biological/Clinical Outcomes Models in Radiation Therapy Planning
Authors: Yorke E 
Published: April 2010

Radiation therapy must strike a balance between clinically acceptable tumor control probability (TCP) and normal tissue complication probability (NTCP). Typical treatments expose several normal organs to incidental dose with an associated risk of a variety of radiation‐induced complications, each of which may depend differently on the spatial and temporal dose distribution. Dose/volume effects, wherein the ‘iso‐complication dose’ increases if the irradiated volume fraction decreases, are particularly important in designing and evaluating treatment plans. These effects are pronounced for some complications and weak for others. The classic “Emami” paper of 1991 summarized guidelines based on decades of clinical experience derived from the simple beam arrangements of the 2‐dimensional planning era when discrete parts of normal tissues typically received uniform doses at conventional fractionation schedules (partial organ irradiation). More recently, 3‐dimensional planning (including IMRT) has led to more conformal distributions with superior patient‐specific dosimetric information. Three‐dimensionl techniques have also encouraged treatment to higher doses and exposed normal tissues to a more variable and inhomogeneous range of dose distributions and fraction sizes. These complex relationships are often summarized in dose‐volume histograms (DVH).Depending on the suspected volume effect, treatment planners use various DVH‐based metrics to estimate complication risks. These include single DVH points (e.g. maximum dose or percent or absolute volume above a dose cut‐point), combinations of such points, generalized equivalent uniform dose (including mean dose) and models (e.g. Lyman model). Co‐morbidities, chemotherapies and other medical factors may also need to be considered. We will describe commonly used evaluation metrics, some of which date back to the early 1990's and others from more recent publications or in‐house experience.The current metrics used to evaluate normal tissue DVHs are sub‐optimal. Under the QUANTEC (Quantitative Analysis of Normal Tissue Effects in the Clinic) initiative, a project that is jointly funded by AAPM and ASTRO, approximately 60 physicists and physicians have critically surveyed the NTCP literature. Their updated consensus guidelines will be published in the near future. Some of their preliminary findings will be discussed here (check the proffered sessions for other presentations).Learning Objectives:1. Understand the general features of the volume effect as applied to NTCP.2. Be familiar with the dose/volume metrics commonly used for complications risk estimation in treatment planning.3. Understand some of the difficulties in determining reliable dosimetric predictors of normal tissue complications.
MO‐C‐BRB‐01: Present and Future Role of Computers in Medicine
Authors: Foster I 
Published: April 2010

Computational methods will transform both biological science and clinical practice over the next decades. Dramatic increases in the quantities of experimental, clinical, and other data, and in our ability to federate data from many sources, are enabling powerful computational approaches such as the mining and integration of data from huge databases in search of novel patterns and correlations. Rapid advances in both computer power and numerical methods enable the use of computational modeling and simulation to study previously inaccessible phenomena at the molecular, cellular, anatomical, and population levels. This marriage of modern biological and medical research with the computational sciences is destined to capture new levels of biological complexity that will motivate new theory, unearth novel biological concepts, and ultimately, drive new diagnostic strategies and treatment approaches.This keynote is given by Ian Foster, who is known as the “father of grid computing”. He is currently The Arthur Holly Compton Distinguished Service Professor of Computer Science, Director of the Computation Institute, and Argonne Distinguished Fellow at The University of Chicago and Argonne National Laboratory. Foster has received the Lovelace Medal of the British Computer Society, the Gordon Bell Prize for high‐performance supercomputing, and is a fellow of the American Association for the Advancement of Science.
MO‐D‐BRD‐02: Dielectric Wall Accelerators for Proton Therapy
Authors: Caporaso G , Chen Y , Sampayan S , Akana G , Anaya R , Anderson D , Blackfield D , Carroll J , Cook E , Falabella S , Guethlein G , Harris J , Hawkins S , Hickman B , Holmes C , Horner A , Nelson S , Paul A , Pearson D , Poole B , Richardson R , Sanders D , Selenes K , Sullivan J , Stanley J , Wang L , Watson J , Weir J 
Published: April 2010

A new type of compact induction accelerator is under development at the Lawrence Livermore National Laboratory that promises to increase the average accelerating gradient by at least an order of magnitude over that of existing induction machines. The machine is based on the use of high gradient vacuum insulators, advanced dielectric materials and switches and is being developed for a variety of applications. Research describing an extreme variant of this technology aimed at producing a compact, variable output linear accelerator for proton therapy for cancer will be described along with the technical challenges and issues. The goal of the development is to produce a proton accelerator that will fit in a standard linac vault and deliver intensity modulated proton therapy. Tomotherapy, Inc. has licensed the new accelerator technology from the Lawrence Livermore National Laboratory and the Compact Particle Acceleration Corporation (CPAC) is supporting development of the system. Research sponsored by Tomotherapy, Inc. and CPAC.Conflict of Interest: Some of the co‐authors have a financial interest in Tomotherapy, Inc. and/or CPAC.
MO‐D‐BRC‐01: Introduction: Challenges of Post‐Treatment and Real‐Time Imaging of Dose Deposition in Proton Therapy
Authors: Bortfeld T 
Published: April 2010

The finite range of protons is the primary physical advantage leading to the potentially greatly improved dose distributions in proton radiation therapy. The other side of the coin is that it takes extra care to make sure that the protons actually stop at the right location. Fortunately, proton therapy provides unique opportunities to visualize interactions of the therapeutic beam with the patient. These interactions are more or less closely related to the delivered dose distribution, and can therefore be used as a dose surrogate for treatment verification. In this symposium we will highlight three examples of such interaction mechanisms, as well as their potential to provide clinically useful information about the in‐vivo dose distribution either post‐treatment or even in real‐time. Some of the methods are applicable to photon therapy as well.In this short introduction we will discuss various reasons that lead to uncertainties in the proton range and will show estimates of the magnitude of the range uncertainties. We will then go over techniques to deal with range uncertainties in treatment planning, and will finally discuss what could be gained if we could reduce or eliminate range uncertainties.Learning Objectives:1. Name three reasons for range uncertainties in proton therapy.2. Quantify the magnitude of range uncertainties.3. Name at least one method that reduces the impact of range uncertainties.
MO‐D‐BRC‐04: Prompt Gamma Measurements for the Verification of Dose Deposition in Proton Therapy
Authors: Kim J , Kubo H , Tanimori T 
Published: April 2010

The proton beam radiotherapy has a merit in that the dose deposit falls off at the end of the beam range. However, mismatch of the falloff location with the prescribed dose boundary can cause adverse effects. Measurement of gamma‐rays emitted by nuclear reactions of the incident proton beam with target materials is the only method to verify the dose distribution in situ. We have investigated two different methods of measuring the prompt gamma distribution: 1) multi‐layer collimation method, which measures the 1D distribution of gamma production at the target, to assure the endpoint of the dose deposition, 2) electron‐tracking Compton camera, which can reconstruct gamma trajectories, to verify the dose distribution. The collimation method can be effectively used when the background neutron flux is low. Hence, it can be more readily applicable to the scanning method in terms of the therapy beam delivery compared to the scattering method. Secondly, the Compton camera is a powerful tool to image the prompt gamma distribution. A preliminary experiment has been carried out with a water phantom at the beam energy of 150 MeV, and images of prompt gamma generation are attained. The clinical application could be considered with further improvement of detection efficiency.This lecture will review the uses of multi‐layer shielding and the Compton camera in the measurement of prompt gamma‐rays emitted from the target to verify the dose deposition during proton therapy.Learning Objectives:1. Understand the physics of dose deposition by the proton therapy2. Understand multi‐layer shielding techniques to measure the prompt gamma distribution for the verification of the proton dose.3. Understand the use of an electron‐tracking Compton camera for imaging the prompt gamma generation by a proton beam.
MO‐D‐304A‐07: Investigation of a Diamond X‐Ray Target for Use with Megavoltage Cone‐Beam CT
Authors: Sawkey D , Lu M , Wu V , Faddegon B , Morin O , Cheung J , Aubin M , Gangadharan B , Bani‐Hashemi A 
Published: April 2010

Purpose. Compare images and spectra using a dual energy diamond x‐ray target for megavoltage cone‐beam CT (MVCBCT) with those of carbon and tungsten targets. Materials and Methods. A Siemens Oncor linac with megavoltage cone‐beam CT was modified to use either a tungsten, carbon, or diamond target for imaging. The carbon target was used with an accelerating potential of 4.2 MV. The diamond target had a higher density than the carbon, thus reducing electron leakage and allowing the linac waveguide to operate at the same accelerating potential as the treatment beam, namely 6 MV. For this study, the diamond target was operated at both 4.2 and 6 MV. With both diamond and carbon targets, the flattening filter was out of the beam path. Images were acquired both of phantoms, to determine contrast‐to‐noise ratio (CNR), and patients. Results. CNR measured with the phantom were nearly the same with the diamond target and the carbon target when both were operated at 4.2 MV. At 6 MV, CNR with the diamond target was degraded, especially for tissue. The highest quality images of head and neck patients were with the diamond target at 4.2 MV. As compared to the carbon target, there were fewer scattering artifacts, and tissue resolution was better. At 6 MV, there were even fewer artifacts but the contrast was reduced. Conclusions. The diamond target is a viable alternative to the carbon target for the IBL. It can be used at either the same energy as the treatment beam, which simplifies commissioning and QA, or at reduced energy for enhanced contrast.Support from Siemens OCS.
MO‐D‐213A‐03: Practical Aspects of PET Accreditation
Authors: Esser Peter D 
Published: April 2010

PET scanner accreditation is based on reviews of images acquired from the ACR PET phantom. The phantom is relatively easy to fill and set up for a PET study and can be used to measure tomographic uniformity, spatial resolution, and the detectability of “hot” lesions. The variety of resolution and “hot” components enables the reviewers to see relatively subtle differences in system performance.The accreditation phantom images are submitted to a review panel of qualified medical physicists for scoring. The Nuclear Medicine Accreditation Committee has defined acceptable standards for uniformity, spatial resolution and lesion detection.Uniformity and noise are evaluated qualitatively by inspection of reconstructed tomographic sections. Optimal density ranges should be comparable to those used for clinical images. Spatial resolution is judged by identifying the smallest “cold” rods in the phantom and lesion detectability is determined from the “hot” cylinders. The same protocol is also used for the “cold” cylinders that demonstrate the effectiveness of the attenuation and scatter corrections.Learning Objectives:1. Be aware of the ACR PET accreditation process and PET Physicist Qualifications.2. Understand the ACR PET Phantom and testing required for ACR accreditation.3. Understand how phantom images are reviewed by the ACR.4. Be able to activate the ACR Phantom.5. Understand phantom image acquisition and processing.6. Understand PET phantom image contrast, resolution, and uniformity.
MO‐E‐213A‐02: Implementating In Vivo Perfusion Measurements Using DCE MRI
Authors: Cao Y 
Published: April 2010

Although it may appear relatively straightforward to extract quantitative metrics from static or dynamic imaging data, a variety of details are critical to the establishment of a data acquisition, analysis, and interpretation methodology that can significantly influence the fidelity of a clinical or fundamental investigation of imaging as a biomarker. While typical users will find available commercial tools and apply them, understanding these fundamental steps will help both the local investigator as well as national efforts to standardize the methodologies and understand the limits of information that can usefully be extracted by a given technique. As an example, the use of MRI‐based Dynamic Contrast Enhanced (DCE‐MRI) imaging and analysis of perfusion‐related metrics is described. The optimization of an image acquisition protocol, which varies by the tissue being studied, is presented. The steps to process this temporal data are described, including image registration for analysis of intrahepatic perfusion. The variables typically associated with DCE analysis, including Ktrans, blood flow, blood volume, and mean transit time, are defined. The dependence of these variables on image quality and temporal sampling are briefly mentioned. The step‐by‐step analysis of the data to extract regional information is presented. An example paradigm relating the analyzed metrics to external variables (e.g. local radiation dose) is shown.Learning Objectives:1. To understand practical issues to extract quantitative imaging metrics2. To understand how to increase robustness and objectiveness in the analysis3. To understand limitations of derived quantitative imaging metrics