bluuebunny/crossref_metadata_2025_split huggingface dataset:
WE‐D‐201B‐04: Advances in Instrumentation and Techniques for Quantitative Myocardial Perfusion SPECT
Authors: Tsui B 
Published: August 2010

Myocardial perfusion (MP) SPECT (single‐photon emission computed tomography) is a leading diagnostic tool for cardiovascular disease. Its continued importance and popularity have been fueled by new advances in instrumentation and image reconstruction and processing methods. Quantitative three‐dimensional (3D) image reconstruction methods that model the counting statistics in the acquired data and the physics of the imaging process have been widely adopted in clinical practice. They provide improved reconstructed image noise and accurate compensation of image degrading factors including collimator‐detector blur, and photon attenuation and scatter in the patient resulting in significant improvement in both the quality and quantitative accuracy of MP SPECT images. Extension of the quantitative 3D image reconstruction method to four‐dimensional (4D) has been shown to benefit 4D gated MP SPECT. Special collimators designed to provide both improved spatial resolution and increased detection efficiency have been developed and implemented on conventional SPECT systems for application to MP SPECT. The need to provide accurate attenuation compensation and anatomical correlation with MP information for individual patient has resulted in the development of multimodality SPECT/CT systems which have become standard system configuration. More recently, dedicated cardiac SPECT and SPECT/CT systems have emerged in the market place that hold great promise to advance MP SPECT a big step forward. The presentation will describe the basic principles of quantitative 3D and 4D image reconstruction methods. Advances in special collimation and SPECT/CT system designs for MP SPECT will be presented. The improvement in image quality and quantitative accuracy will be demonstrated by simulated, experimental phantom and clinical images.Learning Objectives:1. Describe the basic principles of quantitative 3D and 4D image reconstruction methods that have led to significant improved quality and quantitative accuracy of 3D and 4D gated myocardial perfusion and SPECT images.2. Describe the recent advances in instrumentation for improve myocardial perfusion SPECT.3. Demonstrate the advances using simulated, experimental phantom and clinical MP SPECT images.
WE‐E‐203‐02: Collaborative Teaching; a Model for Enriching the Medical Physics Learning Environment
Authors: Sprawls P 
Published: August 2010

The classroom remains a valuable element in medical physics education because it brings the learners (students, residents, etc.) into direct contact with knowledgeable and experienced medical physicists who can motivate and guide the learning process. A longstanding limitation of the traditional classroom is its separation and isolation from the actual physical realities (medical imaging procedures, radiation therapy applications, etc.) that are being studied.Most learning facilitators (medical physics teachers) recognize the effectiveness and value of high‐quality visuals for the classroom as a “window” to the world of physical reality. It is generally not practical or efficient for each teacher to produce all of the visuals needed for his or her classroom activities. This is a limitation because of time, resources, and probably the experience and skills to produce effective visuals.The objective of the Collaborative Teaching Model and Project reported here is to enrich medical physics classrooms and collaborative learning discussions by providing high‐quality and effective visuals as an open and free resource that eliminates the limitation of efficiency for individual on‐site teachers and institutions. The collaborative model is composed of the synergistic combination of many on‐site class/conference room teacher/facilitators and a centralized supporting facilitator. Each makes specific and unique contributions to the learning environment.The on‐site classroom teacher/facilitators contribute to the learning environment and process in many ways. They provide knowledge and experience that is specific to the local applied physics and clinical environment, have an interactive relationship with the learners, motivate and guide the learning process, and play a major role in helping the learners understand and apply the science and technology to clinical procedures.The centralized supporting facilitator translates extensive career experience into high‐quality visuals and related materials that are available online as an open resource (http://www.sprawls.org/resources) to all learning facilitators and learners around the world.
WE‐E‐203‐03: Encyclopaedia of Medical Physics EMITEL
Authors: Tabakov S , Sprawls P 
Published: August 2010

The Encyclopaedia of Medical Physics EMITEL was developed under the EU pilot project European Medical Imaging Technology e‐Encyclopaedia for Lifelong Learning. This reference material includes 3400 encylopaedic entries (approximately 2100 pages), supported by thousands of illustrations. All materials are available free at the web site www.emite12.eu.The work on the project was initiated in 2001 and its main development was from 2006 to 2009. The core project Consortium includes specialists from King's College London (Contractor) and Ring's College Hospital, University of Lund and Lund University Hospital, University of Florence, AM Studio Plovdiv and the International Organization for Medical Physics (IOMP). Later the contributors grew to more than hundred (listed at the web above).The articles (entries) in the Encyclopaedia are grouped in 7 categories ‐ Physics of: X‐ray Diagnostic Radiology, Nuclear Medicine; Radiotherapy; Magnetic Resonance Imaging; Ultrasound Imaging; Radiation Protection and General terms. Each entry is refereed.EMITEL used as background a specially developed database of specific terms covering the main areas of Medical Physics (listed above). These terms (article titles) were translated into 25 languages by specially formed Working groups. Thus the Dictionary associated with the Encyclopaedia includes: English, Swedish, Italian, French, German, Portuguese, Spanish, Bulgarian, Czech, Estonian, Greek, Hungarian, Latvian, Lithuanian, Polish, Romanian, Russian, Slovenian, Bengal, Chinese, Iranian, Arabic, Malaysian, Thai, Turkish.The web site is build with two Search Engines ‐ one searching into the Lists of terms (in all languages) and another one searching inside the text of the articles. The latest allowed significant increase of the potential of the e‐Encyclopaedia, including search for related terms, acronyms and synonyms. To use this facility the user has to select Search in Full Text and specify the category/area of the search (as described above).EMITEL includes also a Content Management System, allowing future editing and update.
TH‐A‐201C‐01: Quantitative Molecular Imaging Using PET/CT to Assess Response to Therapy
Authors: Kinahan P 
Published: August 2010

Recent publications have established quantitative measures of tracer uptake used in positron emission tomography (PET) imaging as a predictor of patient outcome including pathologic response disease‐free survival and overall survival in single institution imaging and therapy trials. There is increasing interest in using PET as a biomarker to evaluate response to therapy and possibly as an endpoint for cancer therapeutic response in multi‐center trials. However several sources of variance and inherent in quantifying PET tracer uptake should understood and determined in order to ascertain the significance of differences in serial measurements and aid estimation of expected variances during clinical trial design.In this presentation we will review the major sources of bias and variability from the patient imaging protocol data processing and image analysis. We will also briefly discuss artifacts from PET and PET/CT imaging.The presentation will conclude with a review of efforts to address complexities that arise from combining quantitative PET/CT data from multiple patients at multiple sites. Research partially supported by NIH grant U01‐CA148131 and NCI Contract 24XS036‐004 (RIDER).
TH‐B‐204C‐01: Parallel Imaging: Technology Clinical Applications and Image Quality Issues
Authors: Yanasak N 
Published: August 2010

Parallel imaging in magnetic resonance imaging (or “pMRI”) is a family of techniques that uses the position of multiple RF coil elements to assist in spatial localization of signal as opposed to phase‐encoding techniques. This approach provides a wealth of new imaging options and advantages to the MR user. Basically the reduction in the number of required phase encodings to produce an image can be used to acquire image data within a shorter window of time. This characteristic can be used in a variety of ways to reduce image acquisition time; to increase image matrices for a given acquisition time; to mitigate geometric distortion; or to reduce SAR over the duration of a scan. Finally pMRI can be implemented in virtually all existing sequences. The current use of pMRI is widespread as a result of these advantages with a tendency toward increased utilization as the technology matures.The advantages that pMRI provides are not without cost. pMRI is implemented in multiple “flavors” all of which require some degree of mathematical prowess to understand fully. Although pMRI is frequently useful it can cause problems within some imaging contexts (e.g. low SNR imaging patients prone to movement). Artifacts associated with pMRI are odd and varied in appearance. Finally an MR system that passes quality assurance tests for non parallel imaging on a given day may not have the necessary performance for pMRI. In 2005 the AAPM MRI subcommittee created Task Group #118 in order to provide guidelines to the Medical Physics community that address these concerns.This presentation will provide an overview of pMRI from concept to application. Conclusions and recommendations determined within Task Group #118 will also be summarized.Learning Objectives:1. To understand the basis of the pMRI technique including required hardware and reconstruction methods.2. To conceptualize what components of a quality assurance program may be important for MR systems using pMRI.3. To gain insight into the suggested (and inappropriate) uses of the technique for clinical benefit.4. To observe new directions of pMRI development and how this may change clinical practice in the next few years.
TH‐C‐BRA‐01: An introduction to GPU Computing
Authors: Sharp G 
Published: August 2010

The graphical processing unit (GPU) is a special‐purpose co‐processor used to perform fast calculation of 2D and 3D graphics commands for computer displays. Recently GPUs have begun to be used as general‐purpose vector processors for a wide range of scientific programs. GPU programming is used in domains such as medical imaging financial analysis and oil exploration.This talk will introduce the history and capabilities of modern GPU‐based computing systems. I will describe the hardware organization of GPUs and describe how multithreaded GPU programs map onto the hardware. Next I will introduce the CUDA language and software tools used to create GPU‐accelerated programs. Finally I will present an overview of existing libraries and applications.Learning Objectives:1. Learn the history and capabilities of GPU‐based computing systems2. Learn the hardware organization of GPUs3. Learn tools and procedures for programming GPUs
TH‐C‐BRA‐03: GPU‐Based Cone Beam CT Reconstruction
Authors: Jia X , Lou Y , Li R , Lewis J , Gu X , Men C , Song W , Jiang S 
Published: August 2010

Cone‐beam CT (CBCT) has been widely used in image guided radiation therapy (IGRT) to acquire updated volumetric anatomical information before treatment fractions for accurate patient alignment purpose. However the excessive x‐ray imaging doses (a few cGy per scan) delivered to patients from serial CBCT scans raise a clinical concern in most IGRT procedures. This fact has greatly limited exploitation of IGRT's maximal potential. The imaging dose can be effectively reduced by reducing the number of x‐ray projections and/or lowering mAs levels in a CBCT scan. The image quality reconstructed from conventional FDK‐type algorithms however will be highly degraded. Recently total variation (TV) method has demonstrated its ability to reconstruct CBCT images from a few number of noisy x‐ray projections. Nonetheless such a method can hardly be applied in real clinical environments due to its long computational time (a few hours). It is highly desirable to develop a fast reconstruction scheme to obtain high quality CBCT images from undersampled and noisy projection data so as to lower the imaging dose.Utilizing GPU to speed up the computationally intensive tasks in CBCT reconstruction problems has drawn a lot of attention recently. In this talk GPU‐based CBCT reconstruction algorithms will be reviewed with an emphasis on an iterative CBCT reconstruction algorithm via TV regularization. We have recently developed a GPU‐friendly version of the forward‐backward splitting algorithm to solve the TV‐based reconstruction problem. Multi‐grid technique is also employed. It is found that 40 x‐ray projections are sufficient to reconstruct CBCT images with satisfactory quality for IGRT patient alignment purpose. Phantom studies indicate that CBCT images can be successfully reconstructed with our algorithm under as low as 0.1 mAs/projection level. Comparing with currently widely used full‐fan head‐and‐neck scanning protocol of about 360 projections with 0.4 mAs/projection it is estimated that an overall 36 times dose reduction has been achieved. Moreover the reconstruction time is about 130 sec on an NVIDIA Tesla C1060 GPU card which is estimated ∼100 times faster than similar iterative reconstruction approaches. The high computational efficiency and satisfactory image quality make the iterative low dose CBCT reconstruction approach feasible in real clinical environments.Learning Objectives:1. Understand basic concepts of GPU‐based CBCT reconstruction.2. Understand main challenges in GPU‐based iterative CBCT reconstruction approach and how an iterative CBCT reconstruction problem is solved on GPU.Conflict of Interest: The research presented here is partially supported by NVIDIA.
TH‐C‐BRA‐04: Radiation Therapy Dose Calculation Using Graphics Processing Units
Authors: McNutt T , Jacques R 
Published: August 2010

Dose computation methods in radiotherapy have traditionally been developed for central processing units (CPUs). Methods used in radiation therapy treatment planning must balance clinical accuracy requirements with practical planning time limits. The first commercial 3D treatment planning systems in the early 1990s took between 5–30 minutes to compute a beam depending on the dose grid size and computation method. In the years that followed CPU performance increased with Moore's law and more reasonable dose computation speeds of several seconds to minutes were achieved. However in recent years CPUs have increased computing power with additional cores not clock speed. At the same time graphic processing units (GPUs) have evolved from fixed function devices into flexible general purpose hardware. Today general purpose GPU computing (GPGPU) has turned desktops into supercomputers and languages such as OpenCL CUDA (Compute Unified Device Architecture) Fortran CUDA C and DirectCompute have allowed for fast GPU program development.Currently convolution/superposition algorithms are the primary computation methods used in treatment planning systems due to their combination of reasonable performance and accuracy. Monte Carlo methods are becoming more prevalent but they still have performance problems. Porting these algorithms to the GPU promises to provide a several orders of magnitude performance increase; resulting in near real‐time convolution/superposition dose computation.The implementation of these algorithms on the many‐core architecture of the GPU poses several challenges and opportunities. The first concern is dividing the algorithm up into many separate parallel processes that can be run independently of one another. The second concern is memory access patterns; for example the manually caching via shared memory the avoidance of write on write conflicts and the maximization of memory bandwidth efficiency. The third concern is how to best leverage the specific processing capabilities of the GPU such as hardware exponentials.Several approaches to implementing dose computation algorithms on the GPU will be discussed. The performance increase in these newer algorithms provides new opportunities in the way we approach treatment planning — whether it be real time treatment planning or enabling dosimetric guidance to treatment delivery.Learning Objectives;1. To understand the architecture differences between CPU and GPU2. To understand approaches complications and advantages to implementing pencil beam convolution/superposition algorithm and Monte Carlo algorithms on the GPU3. To understand the implications of the performance gain on treatment planning processes
TH‐C‐BRA‐05: Real‐Time Re‐planning for Online Adaptive Radiotherapy
Authors: Jiang S , Gu X , Men C , Jia X , Fluck O , Choi D , Majumdar A 
Published: August 2010

By seamlessly integrating treatment simulation and planning into the treatment delivery process online adaptive radiation therapy (ART) allows real‐time treatment adaptations based on the current patient anatomy and therefore holds significant promise in maximally compensating for interfraction anatomical uncertainties. The clinical realization of online ART is extremely challenging mainly due to the inability for real‐time treatment re‐planning. For real‐time treatment re‐planning three key components need to be done in real time: anatomy segmentation dose calculation and treatment plan (re‐)optimization. We have implemented all three components on GPU and gained real‐time efficiency. Our preliminary results on an NVIDIA Tesla C1060 GPU card for various clinical scenarios are very promising. For a typical 9‐field prostate IMRT case the deformable registration can be done in 7 seconds the dose calculation takes less than 2 seconds and the plan re‐optimization takes less than 3 seconds. Therefore a new plan can be developed in about 12 seconds. These results laid a solid foundation for the development of a clinically functioning online ART re‐planning system.Learning Objectives:1. Understand the basic concept and main challenge of online ART2. Gain knowledge in the use of GPU for real‐time re‐planningConflict of Interest: The research presented here is partially supported by NVIDIA.
TH‐D‐BRA‐01: Epidemiologic Evidence of Late Effects from Diagnostic Imaging and Radiation Therapy
Authors: Howell R 
Published: August 2010

Owing to advances in diagnostic imaging chemotherapy and radiation therapy (RT) the survival rate for many types of cancer has greatly improved in recent years. Considering this increased survival rate many of these patients will face late complications in the years following treatment. In particular long‐term survivors are at a substantially increased risk for radiation related late effects such as second cancers and cardiovascular disease. Research in late effects includes population based epidemiological studies that quantify the relationship between excess risk and radiation dose. An additional aspect of late effects research aims to reduce dose to radiosensitive organs and tissues associated with excess risk for late effects while maintaining equivalent or improved local control. The quantification of radiation‐induced late effects and the use of modern delivery techniques to reduce such effects is an important and growing area of research in medical physics as evidenced by a recent surge in publications.The objective of this symposium is to provide an overview of related late effects following diagnostic imaging and radiation therapy. Within the context of the symposium objectives the first presentation in the session will provide context for the symposium by providing an overview of National Cancer Institute and European Cancer Registries epidemiological studies for radiation related second cancers cardiovascular disease and other late effects. Specifically the presentation will focus on epidemiological data and dose response relationships for second cancers and will discuss the need for additional studies to better establish dose response relationships for cardiovascular disease for various cardiac toxicity endpoints.Learning Objectives:1. Understand sources of epidemiological data for radiation related late effects.2. Understand limitations of epidemiological data for radiation related late effects.3. Understand dose response relationships for specific late effects.
TH‐D‐BRA‐02: Late Effects from Modern Radiation Therapy
Authors: Newhauser W 
Published: August 2010

Long‐term survival rates for patients with cancer are large and increasing. In survivors who received radiotherapy the prevalence of radiogenic late effects is also large and increasing with the potential to become a public health issue of considerable proportion. A multitude of late effects are associated with radiation exposure include the development of second cancers cardiac toxicity cognitive deficits and musculoskeletal growth abnormalities in children. In modern radiotherapy much effort is devoted to developing personalized treatments that control the tumor while minimizing acute toxicities to surrounding healthy tissues; comparatively less attention is paid to minimizing late effects. However in recent years much progress has been made toward quantifying the radiation exposures and the associated risks of late effects from modern external beam radiation radiotherapies. The objectives of this lecture are to provide an introduction to radiotherapy‐induced late effects including the governing biologic and technical factors to discuss techniques to minimize radiation exposures and risks and to speculate on future developments that will enable personalized risk‐optimized radiation treatments.Learning Objectives:1. Understand sources of radiation exposure and risk of relevance to radiogenic related late effects following modern external beam radiotherapy.2. Understand techniques to quantify radiation exposures and to predict the associated risks of late effects.3. Understand techniques to minimize radiation exposures and risks using existing technologies.