bluuebunny/crossref_metadata_2025_split huggingface dataset:
MO‐D‐BRA‐02: Application of Hypofractionation in the Prostate
Authors: Pollack A 
Published: July 2007

Prostate cancer exhibits slow growth with a potential doubling time ranging from weeks to months (median 42 days). From these data emerged a hypothesis that adenocarcinoma of the prostate may behave more like a late reacting tissue. Brenner and colleagues (1) used data from prostate low dose rate permanent seed implants and external beam radiotherapy series and derived an α/β of approximately 1.5. Many other groups have also calculated the α/β ratio to be in the < 3.0 range; yet, hyperfractionation does not seem to compromise outcome after radiotherapy (2). There are many potential pitfalls of these analyses and some investigators have concluded that the α/β for prostate cancer is closer to that for late effects of the surrounding normal tissues (>3).Understanding the α/β ratio for prostate cancer is key to designing clinical trials that maximize the efficacy of radiotherapy. If the α/β for prostate cancer is lower than the surrounding normal tissues, hypofractionation will afford an advantage in terms of greater sensitivity of prostate cancer to this strategy, as compared to the bladder and rectum. Brenner et al (3) have estimated the α/β for the rectum to be over 5.0. Recently, Fiorino and Valdagni (4) have argued that these estimates may be inaccurate because of variation in, and dependence of toxicity on, the proportion of rectum receiving higher radiation doses.Clinical results in the PSA/IMRT era using hypofractionation show that this strategy is well tolerated by the surrounding normal tissues, with outcomes consistent with a low α/β. Kupelian et al. (5) have treated a large series of men to 70 Gy at 2.5 Gy per fraction with excellent results. As an offshoot of this strategy, RTOG 04‐15 contrasts this hypofractionation regimen with 73.8 Gy in 1.8 Gy fractions.The Cleveland Clinic data also prompted us at Fox Chase Cancer Center to devise a randomized hypofractionation trial comparing 76 Gy at 2.0 Gy per fraction to 70.2 Gy at 2.7 Gy/Fx. The latter hypofractionation regimen is equivalent to 84.4 Gy at 2.0 Gy/Fx, assuming an α/β of 1.5. A total of 307 patients were entered from 2002 to 2006. The trial has completed accrual. Acute toxicity in the first 100 men entered shows minor differences between the two treatment groups (6). Analysis of late toxicity during the first year of follow‐up also is revealing little difference. The encouraging results thus far with hypofractionation suggest that more significant hypofractionation (e.g., stereotactic radiotherapy) might be cost‐effective and potentially advantageous.Objectives1. To understand the alpha/beta ratio for prostate cancer.2. To appreciate the efficacy of hypofractionation and resultant toxicity.
MO‐E‐L100F‐03: Noninvasive Temperature Imaging Using Diagnostic Pulse‐Echo Ultrasound
Authors: Ebbini E 
Published: July 2007

Several ultrasonic parameters are known to have temperature dependence including the speed of sound, attenuation, nonlinearity parameter, etc. Local changes in tissue temperature can be estimated noninvasively using diagnostic pulse‐echo ultrasound. A number of temperature estimation methods have been proposed since the early 1990s with varying levels of success. One method that was investigated by numerous groups is based on minute changes in echo locations due to temperature‐dependent changes in the speed of sound and thermal expansion. Both in vitro and in vivo results have been obtained to demonstrate the feasibility of the method. However, several limitations have been shown to limit the use of this method in practice. In this paper, we describe a true two‐dimensional displacement tracking algorithm with robust temperature estimation from real‐time 2D pulse‐echo ultrasound. The method employs a physics‐based Kalman filter derived from the transient bioheat transfer equation (BHTE). The filter is shown to be effective in rejecting displacement artifacts from tissue motion as well as those resulting from the thermal lens effects.This lecture will provide a description of the BHTE and the system approach leading to the design of the Kalman filter for tracking the temperature data based on the observed displacements in echo location in the region of interest. The tracking properties of the filter and its ability to reject artifacts from the observed displacements will be illustrated. One‐dimensional and two‐dimensional versions of the filter will be presented and contrasted in terms of their ability to reject displacement artifacts. Comparisons with previously published algorithms will be given using in vivo and in vitro data.We will also present results on using the Kamlan filter methodology in tracking changes in tissue absorption associated with lesion formation using high intensity focused ultrasound (HIFU). This technique may lead to quantitative parameter imaging for monitoring and control of HIFU treatments under ultrasound image guidance.The Educational Objectives:1. Understand the origin of temperature‐dependence of relevant acoustic parameter and their effects on observed pulse‐echo data.2. Understand the limitations of noninvasive temperature estimation using pulse‐echo data.3. Understand the connection between the physical model for temperature evolution and robust temperature and parameter tracking in tissue media.
MO‐E‐M100J‐01: Anatomical Imaging
Authors: Mageras G 
Published: July 2007

This presentation surveys imaging systems, their limitations and expectations for target and organ‐at‐risk position determination, delineation and respiratory motion estimation. Discussion will focus on systems that are in current clinical use. Imaging techniques at simulation usually attempt to use the same patient breathing conditions as at treatment, among them, breath hold, free breathing, coached breathing, or abdominal compression. CT remains the dominant standard for anatomical imaging of external beam radiotherapy simulation. CT acquisition techniques for motion estimation include breath hold at different inspiration levels, or more recently, respiration‐correlated CT (RCCT), involving retrospective sorting of axial images by means of a respiration signal. A limitation of RCCT is that images at a given position along the patient are confined to a single respiratory cycle, and assumes that the breathing pattern is repeatable, which is known to be violated to some extent depending on the patient. Further, images are acquired over several cycles and resorted into a single one; thus cycle‐to‐cycle changes in breathing pattern lead to artifacts. Coached breathing attempts to achieve more repeatable breathing and has shown varying degrees of improvement in some patients. Breath‐hold CT fidelity is similarly dependent on breath‐hold repeatability. Ideally imaging over several breath cycles is desirable, but imaging dose imposes limitations with RCCT, while patient fatigue limits breath‐hold CT. A possible future direction of development is to complement CT with modalities that can image over several cycles with little or no additional dose. For example, repeat MRI in the sagittal plane provides not only a self‐consistent image in terms of respiratory motion but also an estimate of cycle‐to‐cycle variation in motion extent, which is valuable for evaluating the sensitivity of a treatment plan to such variation.Education Objectives:1. Understand the current technological advances in radiotherapy imaging at simulation to provide spatial information and respiratory motion estimation;2. Understand the limitations, current expectations, and possible further improvements of these imaging systems.
MO‐E‐M100J‐04: Planning Target Volume Determination
Authors: van Herk M , Wolthaus J , Sonke JJ , Remeijer P , Damen E , Lebesque JV 
Published: July 2007

Treatment planning should be based on a high fidelity representation of the patient's anatomy, as it will be at time of treatment. The imaging setup (couch, immobilization, alignment) should therefore be representative for the treatment situation. When basing a treatment plan on a single scan (which is current clinical practice), the optimal imaging strategy is therefore to create an anatomical model that is as close as possible to the “average” anatomy. For random organ motion, plan optimization can therefore be achieved by averaging the geometry of multiple scans (i.e., adaptive radiotherapy). For periodic motion it has been proposed to use a scan with the organs as close as possible to their time‐weighted average position — by selecting a single scan out of 4DCT. Using these methods, the systematic errors due to treatment preparation are minimized and the dose distributions will be very close to a full 4D planning (using all scans out of a 4DCT scan). Using image guidance some other error sources can be eliminated. However, even with image guidance there are residual errors: such as uncertainty in GTV and CTV delineation, in image registration, and in setup correction and uncertainty due to intra‐fraction motion. Currently, simple margin recipes are used to estimate the correct CTV‐PTV margin such that the net effect of all these uncertainties does not compromise the goal of the treatment: eradicate the tumor while sparing normal tissues. One should be aware, however, that the most simple margin recipes are based on many assumptions: such as Gaussian distributions, penumbra width in water, systematic error SD > random error SD, and plans with a more or less uniform dose distribution. In case of image guidance for lung tumors all of these assumptions break down, and simple recipes typically will overestimate the required margin. Based on a more detailed analysis, it appears that the margin that can be used for hypofractionated lung radiotherapy can be very small (1 cm or less), even for large respiratory amplitudes (2 cm).Educational Objectives:1. Understand the need for a representative planning CT, i.e., minimize systematic errors.2. Understand the difference between systematic and random errors, and the effect that respiratory motion has on the delivery of radiotherapy.3. Understand the need for margins, even in case of image‐guided. radiotherapy.4. Understand the derivation of margins for image‐guided radiotherapy of lung cancer.
MO‐E‐BRA‐02: Principles of Adaptive and Robust Control in Treatment Planning
Authors: Sharpe MB 
Published: July 2007

Local control by radiation therapy relates directly to the dose delivered to the diseased tissue, but can be limited by the dose tolerated by adjacent structures. This axiom has guided clinical practice into a number of technological shifts over the past several decades. Intensity‐modulated radiotherapy (IMRT) has emerged as an important means to achieve higher doses and to intensify treatment, while simultaneously decreasing the dose in normal tissues. However, the proximity of critical normal organs to disease and geometric uncertainties arising from organ movement continue to present significant challenges in some anatomical sites.Advances in image‐guided radiation therapy (IGRT) permit more frequent soft‐tissue imaging in the course of treatment delivery, creating opportunities to enhance the accuracy and precision of treatment. A framework for considering image‐guidance strategies and their implications for treatment planning is required. For example, target localization can improve geometric accuracy in the on‐line setting; i.e., during treatment delivery. An off‐line statistical analysis of a patient's images can also enhance precision by supporting the adaptation of margins. Even a complete re‐optimization of the plan is possible, in response to systematic anatomical changes accumulated with the progression of treatment. Frequent re‐optimization is potentially inefficient and expensive, within the constraints of current technologies, clinical practices, and QA standards. Clearly, there are trade‐offs between the level of effort required to an exploit IGRT for adaptive re‐planning, and the potential benefits of re‐planning. The concept of robust optimization points to the possibility designing treatment plans that are tolerant to uncertainties in treatment delivery. Robust plans may reduce the need for routine re‐planning in response to variations in patient setup, organ movement, or progressive changes leading to organ deformation.This presentation reviews clinical experience with IGRT, and explores the implications, opportunities and challenges for treatment planning in the era of IGRT. The central principles of using IGRT in IMRT treatment planning with respect to requirements for adaptive re‐planning and the design of robust IMRT treatments.Educational Objectives:1. To review illustrate clinical applications of IGRT.2. To describe how the adoption of IGRT can influence external beam treatment planning.3. To outline how IGRT information is used for re‐planning of IMRT treatments, and in the design of plans that are tolerant to uncertainties in treatment delivery.
MO‐E‐L100E‐01: Writing and Reviewing Medical Physics Papers
Authors: Hendee W , Karellas A , Rogers D , Slattery P 
Published: July 2007

There is an art to writing a scientific paper so that it communicates accurately, succinctly, and comprehensively. Developing this art comes with experience, and sharing that experience with younger physicists is an obligation of senior scientists, especially those with editorial responsibilities for the journal. In this workshop, the preparation of a scientific manuscript will be dissected so participants can appreciate how each part is developed and then assembled into a complete paper. Then the review process for the paper will be discussed, including how to examine a paper and write an insightful and constructive review. Finally, we will consider the challenge of accommodating the concerns and recommendations of a reviewer in preparing a revision of the paper.A second feature of the workshop will be a discussion of the process of electronic submission of a paper for consideration by Medical Physics. The web‐based PeerX‐Press engine for manuscript submission and management will be examined, with attention to special features such as epaps and line‐referencing. Finally, new features of Medical Physics will be explained, such as Vision 20/20 manuscripts, Physics Letters and the standardized formatting of book reviews.Education Objectives:1. Improve the participants' abilities to write a scientific manuscript.2. Understand the review process for Medical Physics manuscripts and how to participate in and benefit from it.3. Appreciate the many features of the PeerX‐Press electronic management process for Medical Physics manuscripts.4. Develop a knowledge of new features of Medical Physics.
TU‐A‐BRB‐01: Imaging for Planning/Verification: In‐Room Imaging
Authors: Brock K 
Published: July 2007

Multi‐modality imaging is improving the accuracy and precision in treatment planning by including more information in the initial model of the patient. The goals of imaging for treatment planning are to determine the boundaries and functional information of the tumor and critical normal structures. Quantification of physiological motion has also become increasingly important in highly conformal treatment planning. Obstacles for imaging include improving contrast, limiting artifacts, improving temporal and spatial resolution, and reducing or eliminating the interference of motion.Combining the soft tissue imaging of MR, functional imaging of MR, CT, PET and SPECT with geometrically robust CT imaging improves the definition of the tumor and critical normal structures. In addition, dynamic information can be accurately quantified and incorporated into the treatment planning process through 4D imaging capabilities in CT and repeat MR imaging. Reducing motion artifacts allows improvement in tumor definition. Methods of reducing the interference of motion on image acquisition include suspending the motion, through voluntary or assisted methods, and reducing the imaging session length, through multi‐slice acquisition and parallel imaging. Optimizing imaging sequences and contrast enhancement and timing improves the ability to define the tumor. The integration of these multi‐modality images into one more complete model of the patient is evolving through the use of automatic registration methods.The presentation will highlight the benefits of multi‐modality imaging in the treatment planning of tumors in the thorax, abdomen, and pelvis. Image optimization strategies will be discussed for each modality and developments to improve image acquisition and integration into treatment planning will be described.Educational Objectives:1. Appreciate the benefits of including multi‐modality imaging in treatment planning.2. Understand methods to optimize the acquisition of multi‐modality images for accurate treatment planning, including sequences, postprocessing, and timing.3. Identify technical developments to improve image acquisition and integration into treatment planning.
TU‐A‐BRB‐02: Imaging for Planning/Verification: In‐Room Imaging
Authors: Papanikolaou N 
Published: July 2007

It was not too long ago when CT based treatment planning was reserved for the few patients that was critical to have volumetric imaging, and treatment verification was limited to planar films of mediocre quality from a megavoltage imaging source. Today, we use multi‐modality based planning (CT, MRI, PET etc) and we employ sophisticated imaging tools and techniques to verify the correct delivery of the treatment. Such imaging capabilities include electronic portal imaging devices coupled with megavoltage (MV) or kilovoltage (kV) x‐ray sources, MV and kV cone beam CT, ultrasound guidance, optical systems, MV computed tomography, CT on rails and others. The goal of any in‐room imaging device is to verify that the patient setup is accurate and in accordance to the treatment plan. While some modalities allow for pre‐treatment verification, others can also provide on‐treatment verification feedback. The choice of the modality to use depends largely on user preference but also on the investment the clinic is willing to make to purchase the necessary equipment. Nonetheless, image based treatment verification has become a necessary and valuable aspect of our clinical practice and is enabling us to become a lot more aggressive with the planning and delivery of radiation treatments. Image Guided Radiation Therapy (IGRT) is undoubtedly the future of radiation therapy.In this presentation we will discuss some of the most popular methods of imaging for treatment verification techniques. Clinical examples will also be presented to demonstrate the implementation, use, and clinical experience with these modalities.Educational Objectives:1. Review of existing image based treatment verification modalities.2. Discuss pros and cons of each modality and appropriateness of use.
TU‐SAMS‐L100J‐03: Optimizing CT Image Protocols With Respect To Quality and Radiation Dose
Authors: Cody D , Kofler J 
Published: July 2007

CT technology continues to develop at a rapid pace, offering imaging options and features that can dramatically improve image quality. Multichannel systems are now commonplace and the number of channels continues to increase, allowing greater coverage per rotation, shorter scan times, and thinner images. Isotropic volumetric data acquisition permits retrospective reconstructions of many different image thicknesses and reformats can be created through multiple planes. These and many other advances have escalated and expanded the utility of CT imaging as a core diagnostic tool.However, coupled with the improved CT technology is the increased complexity of operating the scanners and the elevated potential of increasing the radiation dose. CT operators must choose from multiple options, many of which are interdependent, for the control of the multitude of available features. The impact of each of these options on image quality and radiation dose can range from subtle to substantial, and may not necessarily be obvious to the operator.This lecture will focus on the clinical implications of CT scan parameters and provide guidance on achieving an optimal compromise between image quality and radiation dose when constructing CT scan protocols.Educational Objectives:1. Understand the influence of primary CT scan parameters on image quality and radiation dose.2. Learn how to use imaging task‐specific priorities with consideration for radiation dose when determining scanner settings.
TU‐B‐BRB‐01: Monte Carlo — II: Clinical Impact
Authors: Ma C 
Published: July 2007

This presentation is aimed at facilitating participants with the clinical application of Monte Carlo dose calculation algorithms in radiotherapy treatment planning and dosimetry verification. Following a brief introduction to the clinical implementation and commissioning of the Monte Carlo dose calculation software detailed discussions will be given on the actual and potential clinical impact of Monte Carlo dose calculation algorithms on conventional electron beam therapy and advanced mixed beam treatments.Patient treatment plans generated using conventional dose calculation algorithms and Monte Carlo methods will be compared with the causes of the dose discrepancies discussed. Further discussions will be conducted on the use of Monte Carlo dose calculation as a radiotherapy treatment QA tool to validate individual patient plans and as an investigation tool to improve target dose conformity and normal tissue sparing using novel treatment techniques.Educational Objectives:1. To introduce important aspects of clinical implementation and commissioning of Monte Carlo dose calculation algorithms for radiotherapy treatment planning.2. To describe the role of Monte Carlo dose calculation in electron therapy and advanced mixed beam treatment planning.3. To describe the applications of Monte Carlo dose calculations in treatment planning and beam delivery QA for advanced radiotherapy treatments.
TU‐C‐L100J‐09: CT Doses: Changes in the Last Twenty‐Five Years
Authors: Frey G , Huda W , Groat G 
Published: July 2007

Purpose. To quantify how CT patient doses, and the corresponding scan times, have changed over the last 25 years. Method. We analyzed data for five generations of CT scanners from one vendor (GE), ranging from the 9800 single slice scanner without slip ring technology used in the early 1980s to a 64 slice VCT, the current state of the art. We determined values of CTDIair and CTDIw at a constant kV/mAs. Effective doses were performed for a standard 32 cm chest CT examination performed at 120 kV using contiguous axial scanning on the 9800, and a pitch of 1 on the VCT. Scan times were computed assuming (contiguous) axial images with a 5 mm thickness.Results. CTDIair of a VCT scanner (30 mGy/100 mAs) is 12% higher than that of a 9800 scanner, whereas the corresponding body VCT CTDIw (9.5 mGy/100 mAs) is 53% higher. The increased doses on modern scanners are a result of reduced focus‐isocenter distances to accommodate faster rotation speeds, changes in beam shaping filters, and overbeaming used on MSCT scanners. Patient effective doses for a routine chest CT examination are 5 mSv/100 mAs on a VCT and 3.2 mSv/100 mAs on a 9800. Acquisition of 64 axial images for a routine chest CT in the early 1980's took ∼5 minutes, whereas modern scanners cover the same volume in only 8 x‐ray tube rotations taking ∼3 seconds.Conclusion. Over the last 25 years, normalized CT patient doses (i.e., per unit mAs) have increased by ∼50%, whereas image acquisition times have been reduced by two orders of magnitude.