bluuebunny/crossref_metadata_2025_split huggingface dataset:
MO‐FF‐A2‐04: An Accurate Mechanical Quality Assurance Procedure for a New High Performance Linac
Authors: Lovelock DM , Wang P , Kirov A , Lim S , LoSasso T 
Published: August 2010

Purpose T o establish QA procedures for the mechanical systems of a new linac that has been developed to deliver radiation, using image‐guidance, to the target with improved spatial accuracy. The procedures are required to be able to detect mechanical errors of much less than 1 mm, be independent of the linac's own readouts and calibration procedures, and be fast enough for the physicist to perform on a monthly or more frequent schedule. Method and Materials In image guided delivery, mechanical properties that will affect the spatial accuracy with which dose is delivered include:• radiation isocenter ‐imaging origin displacement,• position errors of the jaws and MLC leaves,• accuracy with which the patient support couch can respond to a change in position request.To measure these quantities, we use the machine's kV, MV, and infra‐red imaging systems. We report on the techniques used, and the estimates of their accuracy. Results The preliminary estimate of the measurement uncertainty of the radiation isocenter — imaging origin offset is ± 0.3 mm. The observed offset is within the measurement error. The accuracy of the field size seen in the MV images is ± 0.2mm. Couch accuracy for shifts of up to 2 cm, the magnitudes expected using image guidance, was found to be within the measurement error. The ability to control the machine using scripts allows gantry and collimator positioning, couch positioning, beam delivery and imaging in all modes, to be sequenced and performed automatically. Thus the time required for a complete mechanical QA procedure is greatly shortened. Conclusion The imaging components of a new linac can be positioned with sufficient reproducibility and accuracy to allow their use in a mechanical QA program that can achieve the sub‐mm accuracy needed for this machine. Research supported by Varian Medical Systems
TU‐A‐BRA‐01: Non‐Coplanar Treatment of Hypofractionated Intracranial SRT with Tomotherapy
Authors: Murphy S , Yang C , Sheth N , Chen Y 
Published: August 2010

Purpose: To report on a newly developed positional device and dosimetric results in Tomotherapy intracranial hypofractionatedStereotactic Radiosurgery Treatment (SRT) with non‐coplanar beam characteristics. Methods: An in‐house developed positional device has been adapted to generate the non‐coplanar dosimetric effects in selected hypofractionated intracranial SRT patients. Three different head positions and CT data sets of same patients were scanned to provide the basic panning information. Contrast is also provided to delineate CTV. Dose constraints for PTV and OARs were scaled down according to the total composite dose (30Gy is split into 12Gy, 12Gy and 6Gy with 5 treatment fractions). The ability to change the rotational angles of the head for each treatment fraction would reduce the volume of normal brain tissue irradiated to lower clinically significant doses and increase the dose gradient surrounding the treatment area. Due to the TomoTherapy nature of helical co‐planar treatment, this methodology will generate a composite non‐coplanar delivery in order to reduce the low dose spread inside the PTV slices. Planning was performed with the three CT data sets and the composite dosimetry was evaluated to prove the clinical efficacy. Results and Discussion: Clinical dosimetry results indicate improved dosimetry coverage while minimizing the scattered dose to the volume slices of PTV. Composite dosimetry indicated the 50% isodose volume minus target volume was reduced by 9.4% for a small tumor (0.7cm3). For a medium tumor (2.5cm3), the volume was reduced by 8.9% and for a large tumor (4.2cm3), the volume was reduced by 13.0%. All those reduction ha shown by manipulating the various head treatment positions, we can achieve lower dose sparing inside the volume of PTV slices. Conclusions: Our developed device and composite dosimetric results have shown the clinical benefits to improve the dose gradient and minimize the low dose region inside the PTV CT slices.
TU‐A‐204C‐01: New Technologies for Image Quality Improvement and Dose Reduction in CT
Authors: Mahesh M 
Published: August 2010

From 1998 onwards there has been evolutionary advances in multiple‐row detector computed tomography (MDCT) technologies with demand for improved spatial and temporal resolution and three‐dimensional imaging. This has led to rapid race to develop MDCT scanners that yield the highest number of slices per CT gantry rotation (4‐16‐64‐128‐320). At the same time, the number of CT examinations performed in the United States has been growing at an annual rate of approximately 10% with nearly 68 million procedures performed in 2007 alone. The apparent increase in the number of CT procedures, protocols and the associated radiation dose and risks has drawn considerable attention. It appears that the so‐called ‘slice wars’ with regard to the number of slices provided per CT gantry rotation may be reaching a plateau and increasing concerns about radiation dose due to CT examinations are fueling the efforts to reduce radiation dose and leading to the beginning of the so‐called ‘dose wars’.A number of radiation dose reduction strategies are been developed. At the same time, an effort to provide further improvement in image quality and image quantification at lower radiation dose is gaining ground. Dual energy CT (DECT) methods are slowly emerging from research and becoming a clinical reality. The dual x‐ray source (Dual‐source CT), fast tube voltage (kVp) switching, single x‐ray source dual detection (sandwich detector), photon counting detection and dual‐scanning approaches are few of the different approaches currently developed for performing DECT. In addition, new technologies are been developed to further improve image quality, enhance diagnostic information and at the same time yield low radiation dose.There is an increasing demand for the medical physicists to assist clinicians in developing, reviewing and recommending changes to the clinical protocols. Therefore, it is critical for the medical physicists to become familiar with the new technologies such as dual‐energy CT and to understand strategies to reduce radiation doses in CT, image quantification methods and many other aspects.In this lecture, new technologies that are currently developed, such as dual energy CT, image quantification method, radiation dose reducing strategies and others will be discussed.Learning Objectives:1. To become familiar with radiation dose reduction strategies in CT.2. To understand various image quality improvements in CT.3. To describe various technological approaches to perform dual‐energy CT (DECT).
TU‐A‐202‐01: Peak Skin Dose Reconstruction and TJC Sentinel Event
Authors: Anderson J , Arbique G , Guild J 
Published: August 2010

In 2005, the Joint Commission established a new reviewable Sentinel Event tied to radiation exposure. Proper identification and investigation of Sentinel Events are critical issues for maintaining Joint Commission accreditation of a hospital, mandating that the physicist correctly approach this problem. The newly defined sentinel event treats both radiotherapy and fluoroscopy, but we consider only the issues arising from the specific inclusion of prolonged fluoroscopy procedures that result in high (> 1500 rads) cumulative skin doses. The specific details of what constitutes the fluoroscopic Sentinel Event, mechanisms for detecting potential events, how to investigate an event, and what happens in the course of reviewing a Sentinel Event are addressed.The air kerma monitors required by the FDA on fluoroscopic equipment manufactured since 2006 are very useful tools for dose determination in these cases, but they do not provide a direct or complete answer. Case studies are reviewed that illustrate how to estimate doses both with and without cumulative air kerma readings.Learning Objectives:1. Review the definitions of the new Joint Commission Sentinel Event for fluoroscopic radiation exposure.2. Identify monitoring policies and procedures to detect potential fluoroscopic Sentinel Events.3. Discuss practical aspects and pitfalls of using air kerma monitors and technique values to calculate maximum skin doses.
TU‐B‐202‐01: Revision of NRC's Safety Culture Policy Statement and Proposed 10 CFR Part 37, “Physical Security of Byproduct Material.”
Authors: Carpenter C 
Published: August 2010

NRC is in the process of updating and expanding its 1989 policy statement on safety culture to include the full range of NRC regulated activities and to better address security issues. NRC published its draft safety culture policy statement in the Federal Register (74 FR 57525) November 6, 2009, and held a public work shop February 2010. One NRC objective is to develop a common definition of safety culture, and safety‐culture‐related language that can be used by the NRC, the Agreement States, licensees, and others involved with nuclear materials in the United States. NRC believes safety culture is important in ensuring safety, security, and the protection of the environment in the use of regulated materials and is a leading indicator of a licensee's performance. NRC has a responsibility to consider safety culture as part of its oversight responsibilities. Under the Medical Policy Statement, it is clear that for medical use licensees NRC has regulatory responsibility over not only the radiation safety of the public and radiation workers but also patients, when appropriate. NRC expects its licensees to have and maintain a safety‐conscious work environment in which employees and contractors are encouraged to raise safety concerns (including patient radiation safety concerns) and feel free to raise these concerns both to their own management and to the NRC without fear of retaliation. These concerns should be promptly reviewed, properly prioritized, appropriately resolved, and timely feedback provided to those raising the concerns. In NRC's inspection report for the Department of Veteran's Affairs multiple medical events involving prostate brachytherapy, one of the underling root causes and concerns was the lack of a positive safety culture environment to encourage medical physicists and others to raise concerns to the licensee.NRC is developing a proposed rule, to among other things, add a new Title 10 Code of Federal Regulations Part 37, “Physical Security of Byproduct Material.” The proposed rule would include in the regulations the security requirements NRC implemented by Orders to certain licensees for the use of category 1 and category 2 quantities of radioactive material. These include provisions for the background investigation and access authorization program, provisions for physical protection during use of category 1 and category 2 quantities of radioactive material, and security provisions for the transport of category 1 and category 2 quantities of radioactive material. Medical physicists are affected by the Orders and proposed rule only if they use category 1 and category 2 quantities of radioactive material.Learning Objectives:1. Understand NRC's proposed expansion of its Safety Culture Policy.2. Understand basic physical security provisions of NRC's proposed 10 CFR Part 37.
TU‐C‐201C‐01: NCI Initiatives on Translational Research: An Overview of Opportunities
Authors: Clarke L 
Published: August 2010

NCI has initiated a number of new initiatives that are focused on the development of methods to develop and robustly validate current and next generation of imaging platforms. Over the last decade while there has been significant development of a range of imaging platforms and methods that are designed to address the cancer problem, such as screening of early cancer; cancer diagnosis, characterization, prediction and measurement of response to therapy, and image guided therapy including drug delivery systems. However as imaging methodologies move towards multi‐modality and molecular imaging platforms, coupled with recent advances in nano‐carriers and molecular probes, the ability to robustly validate these technologies, and perform multi‐parametric and quantitative measurements, is becoming increasingly complex. In addition the next generation of imaging technologies often involves imaging at resolution scales from the cellular to the organ level, where traditional pathological validation strategies are often limited. Thus the development and in particular the robust validation of these technologies, including clinical decision making, as required in the new era of personalized medicine, poses significant barriers for FDA approval, CMS reimbursement and ultimately their commercial dissemination as enabling tools for pre clinical and clinical research in cancer.NCI therefore has initiated several new initiatives that specifically address support for translational research that includes a means to broadly engage the research and industry community to develop both public resources and consensus methods to validate these emerging imaging platforms. The new initiatives will be of interest to medical physicists and computer scientists involved in imaging research and clinical practice.Learning Objective:1. Understand the opportunity for research support for translational research at NCI2. Understand the importance of development a consensus on how to validate emerging imaging technologies.
TU‐D‐204C‐01: Some Uses of Neural Networks in Radiation Therapy
Authors: Murphy M , Wu J 
Published: August 2010

Artificial Neural Networks (ANN) have become a staple of machine learning applications. They can be used for pattern recognition, data classification, and process control problems, several of which come up in modern radiation therapy. In this presentation we will look at two representative applications of ANNs: (1) the prediction of breathing, to compensate instrumental lag time in systems that automatically compensate for respiratory motion of a tumor; (2) the analysis of patient setup corrections generated automatically via rigid image registration, to recognize poor or failed results as a quality assurance (QA) measure.All systems that attempt to actively compensate respiratory motion will have intrinsic delays that necessitate predicting the future tumor position by up to several hundred milliseconds. However, every patient breathes differently, which makes the use of analytical breathing models problematic. An ANN is capable of learning the breathing pattern of any given patient directly from incoming data and making an accurate prediction of its future amplitude. We will show examples of this application.Image‐guided radiation therapy (IGRT) relies on image acquisition and registration to optimally position the patient for treatment. However, rigid image registration algorithms can sometimes fall into local minima that can be far removed from the optimal setup position. If one identifies a set of significant “features” of the registration result, such as the shape of the cost function surface in the neighborhood of the solution at convergence, an ANN can use them to classify a particular registration as good or bad, according to some predetermined criteria. This provides an important QA tool to assess patient setups.Learning objectives:1. learn the basic concepts of ANNs as they are used for pattern recognition and classification.2. learn how to use an ANN in a real‐time tumor tracking process.3. understand how an ANN can be trained and used to recognize imperfect patient setup shifts for QA purposes.
TU‐D‐204C‐02: Machine Learning in Real‐time Tumor Localization
Authors: Li R , Jiang S 
Published: August 2010

Real‐time tumor localization is an essential step to achieve conformai lung cancer radiotherapy. In practice, tumors may be localized either directly (e.g., in fluoroscopy) or indirectly by some type of surrogate. Direct localization with implanted markers poses the risk of pneumothorax to lung cancer patients, while indirect localization is limited by its accuracy. Direct localization in fluoroscopy without implanted markers achieves a reasonable tradeoff between accuracy and risk to the patients. However, due to the poor soft tissue contrast and superposition of different anatomical structures, it is generally very difficult to localize the tumor in fluoroscopy with conventional methods in computer vision and image processing.Recently, machine learning has gained great popularity in many aspects of radiation therapy. In this lecture, we will demonstrate the applications of various machine learning techniques in the context of real‐time tumor localization in lung cancer radiotherapy. These cover a wide range of well established machine learning techniques, including principal component analysis (PCA), artificial neural networks, and support vector regression, etc.. We will distinguish between two different paradigms when applying these techniques: one in a two‐dimensional (2D) framework and the other in a three‐dimensional (3D) framework. In the 2D framework, a (supervised) regression model is built between a parametric representation of the fluoroscopic images. and the tumor locations of the fluoroscopicimag fluoroscopic images. Because the representation of the fluoroscopic images is implicit in the 2D framework, it is difficult to account for deformational and large translational changes in the tumor. In the 3D framework, by incorporating the prior information in 4DCT or 4DCBCT, a PCA model is constructed to explicitly represent the entire lung motion in a realistic and efficient way. This model allows one to use a single x‐ray projection image to not only derive the 3D tumor location, but also reconstruct the corresponding volumetric image of the patient. With the aid of graphics processing units, this computationally intensive task can be achieved within half a second given one projection.This lecture provides an overview of the different machine learning techniques used in real‐time tumor localization. A detailed description of these machine learning techniques is also presented. Finally, extensions to the current framework as well as some future directions are discussed.Learning Objectives:1. Understand the benefits and challenges of real‐time tumor localization without implanted markers.2. Understand the principles of different types of machine learning techniques for real‐time tumor localization.3. Understand how machine learning techniques are used to achieve accurate real‐time tumor localization.Conflict of Interest: This work is partially supported by Varian Master Research Agreement.
TU‐D‐201B‐01: Challenges and Experience in CT Dose Assessment & Dose Reduction ‐ an International Perspective
Authors: Rehani M 
Published: August 2010

Radiation doses in computed tomography (CT) is a matter of global interest. In developing countries, there is a lack of upgrading of technology in many facilities, such as tube current modulation, and a lack of skilled manpower (medical physicists) for dosimetry. There are apprehensions that patients may be getting much higher radiation doses than necessary. The International Atomic Energy Agency (IAEA) launched studies few years ago covering a large number of developing countries to access the situation, create awareness and implement dose management. The studies have covered adults and children in more than 200 facilities in over 30 countries in Africa, Asia, Eastern Europe and Latin America. In view of the lack of medical physicists in diagnostic radiology, staff working in universities, regulatory bodies and even radiographers were utilized to collect information and then imparted dosimetry skills. Standardized data collection forms were developed. As anticipated, significant variations in radiation levels and in the frequency of CT scans were observed. Corrective actions were suggested to those where the values were exceeding diagnostic reference levels and in situations where adult exposure factors were used by pediatric patients. Improvements were assessed. The major challenge comes not from lack of technology, but from lack of skilled manpower. However, it was heartening to achieve the cooperation of participants from so many countries and to document improvement.Learning Objectives:1. To become familiar with the situation of radiation doses in CT in developing countries.2. To understand how dose management projects launched by the IAEA have been pursued despite lack of skilled manpower.3. To become familiar with actions taken and results obtained to improve the situation in a number of developing countries.
TU‐D‐201C‐02: Subharmonic Imaging and Pressure Estimation
Authors: Forsberg F 
Published: August 2010

The use of gas filled microbubbles as contrast agents for ultrasound imaging (US) is well established by now. Such contrast agents are used world‐wide to improve the diagnostic capabilities of US especially when employed in combination with novel nonlinear contrast imaging modes such pulse inversion second harmonic and subharmonic imaging (SHI).Our group has investigated the use of SHI in breast imaging and has produced the first ever human SHI images as well as developed a new contrast imaging mode: dynamic cumulative maximum intensity (CMI) SHI. Fourteen patients with 16 breast lesions, who underwent breast biopsies with histopathological assessment, participated in a pilot study of mammography and contrast US. A Logiq 9 scanner (GE Healthcare, Milwaukee, WI) was modified to perform grayscale SHI (transmitting/receiving at 4.4/2.2 MHz). Of the 16 lesions, 4 were malignant. Mammography had a sensitivity of 100 % and a specificity of 20 %. Baseline grayscale US and PDI both achieved a sensitivity of 50 % and a specificity of 92 %, while contrast‐enhanced PDI produced 75 % and 75 %, respectively. SHI had a sensitivity of 75 % and specificity of 83 %. All the ultrasound modes produced higher specificities than mammography (p<0.04). The area under the ROC curve (Az) for the diagnosis of breast cancer was 0.64 for grayscale and PDI, 0.67 with contrast enhanced PDI, 0.76 for mammography and 0.78 for SHI. For dynamic CMI‐SHI mode the Az increased to 0.90 and this was significantly better (p=0.03) than mammography. More recently, the utility of contrast microbubbles for quantitative measurements of hydrostatic pressure (in mmHg) have been explored. Changes in ambient pressure affect the reflectivity of ultrasound contrast microbubbles leading to an excellent correlation between subharmonic signals and hydrostatic pressure (r2>0.90). We have proposed subharmonic aided pressure estimation (SHAPE; U.S. patent 6,302,845) and provided proof of concept of the feasibility of in vivo SHAPE. The heart and aorta of four dogs were scanned with a Sonix RP scanner (Ultrasonic Medical Corporation, Richmond, BC, Canada) modified to perform SHAPE. Simultaneously, the instantaneous pressures within the aorta were measured using a manometer‐tipped catheter. The instantaneous in vivo pressure measurements and those based on SHAPE were in good accordance over a pressure range of 0 to 70 mmHg (r2 from 0.65–0.85).In conclusion, a new contrast specific imaging technique, SHI, has been investigated for in vivo breast imaging and for quantitative measurements. SHI appear to improve the diagnosis of breast cancer relative to conventional ultrasound and mammography; albeit based on a very limited patient population. Some encouraging results in pressure estimation have been achieved.Learning Objectives:1. Understand the origin of subharmonic bubble signals2. Understand the pro's and con's of SHI3. Understand the principle of SHAPE