bluuebunny/crossref_metadata_2025_split huggingface dataset:
TU‐B‐211A‐01: Treatment Planning of Complex Cases: Strategies and Tradeoffs
Authors: Nurushev T , Hunt M 
Published: April 2010

The rapid increase in the complexity of treatment planning is a reflection of recent advances in the clinical technology. These include the use of multi‐modality and 4D imaging for planning, advanced treatment delivery and imaging capabilities available now on many linear accelerators. Intensity modulated radiotherapy (IMRT), already the most common form of treatment at some institutions, is increasingly being combined with other complex treatment capabilities such as respiratory monitoring or control, in‐room 2D or 3D imaging, or intra‐fractional patient motion monitoring.Successful integration of any of these methods into the clinic relies on the increasing sophistication and ability of treatment planning staff to design and prepare not just the dose distribution but all data and images required for treatment. Although IMRT optimization and leaf sequencing algorithms are fairly mature, confidently identifying an “optimum” plan and appropriately evaluating the normal tissue and target trade‐offs can still be difficult and time consuming particularly for complex cases. Complex treatment procedures such as image‐guided treatment or respiratory monitoring can present a substantial challenge in terms of the effort required to manage, evaluate and appropriately use the many image sets acquired during planning and treatment. Dose escalation protocols and stereotactic body radiosurgery programs are being initiated at more institutions. Each of these demands a careful evaluation of initial and daily patient preparation and setup and a thorough understanding of the uncertainties associated with planning and treatment.This course will focus on strategies and techniques for coping with some of the more complex planning issues that arise in today's technology‐intensive department on all stages, from planning image acquisition to dose delivery.Learning Objectives:1. Understand the trade‐offs in IMRT planning and the role of target/normal tissue geometry and beam geometry in creating IMRT plans2. Understand the increasing role of treatment planning staff in the analysis, use and preparation of images for planning and treatment3. Identify sources of inter‐ and intra‐fractional uncertainty and their impact on dose escalation and stereotactic body radiosurgery programs
TU‐B‐303A‐01: Digital Mammography: A Radiologist's Perspective
Authors: Gutierrez R 
Published: April 2010

Full Field Digital Mammography (FFDM) systems are rapidly gaining in popularity and are replacing conventional film‐screen mammography (FSM) systems in breast centers throughout the country. Radiolgists are faced with unique challenges brought about by this transition of technology.In this lecture, the utility of full field digital mammography in clinical practice will be presented. Some of the challenges faced by radiologists who have transitioned from film screen mammography to digital mammography will also be discussed, and case examples illustrating the utility of FFDM will be presented. The clinical utility of computer‐aided detection (CAD) software packages will also be addressed.Learning objectives:1. Understand the clinical impact that full‐field digital mammography has had on the daily practice of breast imaging.2. Recognize the advantages and disadvantages of FFDM systems.3. Understand some of the challenges that breast imagers face when transitioning from FSM to FFDM systems.4. Understand how computer‐aided detection (CAD) systems are used in clinical practice.
TU‐C‐BRD‐03: An Integrated Robotic‐Based Irradiation System for Small Animal Research
Authors: Moros E , Sharma S , Corry P , Chao M , Griffin R , Mihaylov I , Penagaricano J 
Published: April 2010

An integrated, image‐guided irradiation system for small animal research has been developed. The system is capable of precise, accurate, reproducible and quantifiable 3D conformal delivery of radiation dose distributions to organs/tumors. The main hardware components are: (1) A Seifert Isovolt Titan 225 kV X‐ray tube with beam collimation provided by a custom‐made variable diameter “cone” or a set of motor‐driven symmetric “jaws”, thereby allowing field sizes from 0.5 mm in diameter to 7 cm square field at ∼33.5 cm SSD. (2) A six‐degrees‐of‐freedom (6DOF) robotic arm (Adept Viper s650) was integrated for precise animal positioning/motion (repeatability of ±0.020 mm in XYZ direction and angular precision of ±0.2°). The system is housed in a custom 6 × 6 × 6 ft3 shielded enclosure inside a laboratory. When the beam is aimed horizontally to (3) a flat panel amorphous silicon detector (XRD 0820 CN3, Perkin Elmer, Fremont, CA) a series of 2D‐radiographs can be recorded while the robot rotates the animal. Each image is composed of 1024 by 1024 pixels with a 200 μm pixel size at a frame rate of 7.5 Hz. An open source cone beam computed tomography (CBCT) reconstruction tool (OSCAR‐2, University of Toronto) using the Feldkamp‐Davis‐Kress (FDK) filtered back projection algorithm was implemented for CBCT image reconstruction. Thus, targeting can be accomplished by the use of orthogonal radiographs and/or CBCT. A dose engine and CBCT‐based treatment planning are ongoing projects.Dosimetric measurements and preliminary animal experiments have demonstrated the basic capabilities of the system in terms of radiation dose, dose rate and precision targeting. The system has also been used successfully in experiments to detect the molecular signaling occurring after spatially fractionated radiation therapy (GRID) in vivo.A description of the system and a summary of experiments performed to date will be presented.Learning Objectives:1. Appreciate the challenges of developing a high precision 3D conformal irradiator for small animals.2. Learn about the main hardware components of the system and their integration.3. Understand the advantages of using a 6DOF robot for imaging (motion) and beam delivery (positioning).4. Learn about some of the potential research projects that such a system can make possible.This research was sponsored by the Arkansas Biosciences Institute and the Central Arkansas Radiation Therapy Institute.
TU‐C‐BRC‐01: Imaging as a Biomarker
Authors: Mankoff DA 
Published: April 2010

There is an increasing trend towards more individualized, targeted cancer therapy. This places new demands for tools to help guide treatment selection and evaluate early response to the selected therapy. While cancer treatment selection has traditionally depended on tissue‐based biomarkers, functional and molecular imaging can play an important and complementary role in directing targeted cancer therapy and monitoring early response. Imaging has several capabilities distinct from tissue sampling and assay, including the ability to measure the heterogeneity of target expression and to characterize in vivo pharmacodynamics. The use of molecular imaging to direct cancer therapy departs from the traditional role of cancer imaging to detect and localize cancer sites. This implies an expansion of the scope of cancer imaging from detection methods that rely on features such as aberrant glycolysis that are present in tumors but not in normal tissues, to a broader approach using imaging to quantify in vivo phenotype. In the latter case, the absence of a particular tumor feature, such as a target receptor, may be as important as its presence. The need to simultaneously localize and characterize tumor sites places an emphasis on multi‐modality imaging such as PET/CT or multiple PET images using combinations of different imaging probes. This talk will review applications of molecular imaging to targeted cancer therapy for clinical trials and clinical practice, focusing mostly on PET. Examples using molecular imaging to (1) predict tumor clinical behavior, (2) identify therapeutic targets, (3) predict therapeutic resistance, and (4) evaluate early response to therapy will be shown. The theme of the presentation will be that quantitative in vivo measures of tumor phenotype using imaging are complementary to in vitro assay in directing targeted, individualized cancer therapy.Learning Objectives:1. Describe ways in which molecular imaging can help direct cancer therapy.2. Discuss the complementary role of in vitro assay and in vivo imaging in measuring cancer phenotype.3. List examples of how imaging can be used to help direct cancer therapy.
TU‐C‐303A‐03: Real‐Time Profiling of Respiratory Motion and Its Application to Continuous Horizon Prediction
Authors: Ruan D , Fessler J , Balter J , Keall P 
Published: April 2010

Purpose: Respiration‐induced tumor motions are semi‐periodic and exhibit different variations that have distinct clinical implications. We develop and investigate a system that is capable of estimating baseline drift, frequency variation and fundamental change (oscillatory amplitude and shape) in real time and utilize such information to predict abdominal or thoracic tumor positions. Method and Materials: The observation is modeled as a periodic fundamental pattern modulated in both frequency and baseline, which is subsequently corrupted by independent additive noise. To jointly estimate these coupled components online, we utilize three key techniques : (1) augment state to capture system dynamics and hysteresis; (2) create a low order elliptical shape model to characterize semi‐periodicity; (3) perform Poincare sectioning to automatically identify iso‐phase instances. Linear interpolation/extrapolation from iso‐phase points provides a continuous phase warping function. The baseline drift is obtained by projecting the elliptical center onto the original time‐displacement axis. A least squared error (LSE) estimate for the fundamental pattern is obtained by inversely phase‐ warping the observed trajectory and compensating for the mean drift. The proposed method is applied to simulated data with known “ground‐truth”. In a preliminary prediction test with RPM data, each component (baseline, phase and fundamental pattern) is extrapolated respectively, and then reassembled to provide a “predicted trajectory”. Results: The proposed method provides the first unsupervised system that achieves robust real‐time estimation of mean displacement, phase and fundamental pattern. Application of the online profiling system to prediction yields continuous horizon prediction of 3∼5 seconds, with similar behavior to what is expected from human observers.Conclusion: We have proposed an online profiling paradigm for describing and characterizing respiratory motions. Tests on simulation data and RPM signals have demonstrated the efficacy of the proposed method.This work was partially sponsored by NIH P01‐CA59827.
TU‐C‐303A‐04: Slow Gantry Rotation Acquisition Protocol for Four‐Dimensional Digital Tomosynthesis
Authors: Maurer J , Pan T , Yin F 
Published: April 2010

Purpose: Four‐dimensional digital tomosynthesis (4D‐DTS) was recently introduced as a novel on‐board 4D imaging technique. The purpose of this study is to develop and implement a slow gantry rotation acquisition protocol for 4D‐DTS. A formalism for determining appropriate acquisition parameters based on patients' respiratory characteristics was derived and tested. Methods & Materials: Equations were derived to explain the relationships between slow gantry acquisition parameters (scan speed, frame rate and scan angle) and respiratory characteristics (average period and regularity). Additional equations relate acquisition parameters with resultant scan times, projection numbers and the distribution of projections within phase bins once sorting and binning are complete. Phantom studies were conducted to test the new protocol. A body phantom was mounted on a moving platform to simulate short and long respiratory cycles (3 and 6‐s) and scanned using the slow gantry protocol with a 1.1‐deg/sec scan speed and a 7.8‐fps frame rate. Projections were binned and sorted into 10 phases with 10% phase windows. Resultant distributions of projections within phase bins were compared with expected distributions based on the derived formalism. Reconstructions were completed to investigate dependence on respiratory period. Results: The maximum angular intervals between projections within phase bins were estimated by the formalism to be 3.5 and 6.8° for the 3 and 6‐s profiles, respectively. Actual values ranged 3.4 to 3.6° for the 3‐s profile and from 6.8 to 7.16° for the 6‐s profile. Reconstructions demonstrated the importance of adjusting scan speed according to respiratory cycle length. Conclusion: A 4D‐DTS slow gantry rotation acquisition protocol was developed, implemented, and tested. The derived formalism has proven useful for determining appropriate acquisition parameters based on respiratory characteristics and will be used as a framework for further optimization and testing of the protocol.Conflict of Interest: Partially supported by a Varian research grant.
TU‐C‐303A‐08: A Hybrid Strategy Using Discriminant Analysis for Prostate Intrafraction Motion Management
Authors: Adamson J , Wu Q , Yan D 
Published: April 2010

Purpose: Prostate intrafraction motion has been shown to be patient specific; however most current compensation strategies are population wide. We evaluate the feasibility of applying margins based on a subpopulation of patients with similar intrafraction motion characteristics and of predicting group membership within the initial treatment fractions. Method and Materials: 22 prostate patients from a hypofractionated radiotherapy protocol with online CBCT image guidance and kV fluoroscopy measurements of intrafraction motion were divided into small and large motion groups using k‐means clustering of the 90th percentile of vector displacement during treatment delivery. Group margins were computed containing 90% of measured prostate displacements at treatment delivery. Descriptive statistics from the intrafraction motion in the AP and SI‐axes and rectal filling status were used to predict group membership after 2–10 fractions using a perceptron linear discriminant function. Results: ∼75% of patients (17/22) were categorized as having relatively small intrafraction motion, with ∼25% (5/22) having large motion. Population margins were 1.7, 4.0, and 3.9 mm in the RL, AP, and SI axis. When classified into groups, margins for the small motion group reduced to 1.6, 2.9, and 3.0 mm and for the large motion group increased to 2.0, 6.4, and 6.0 mm in the RL, AP, and SI‐axes respectively. The percentage of patients correctly classified after 2, 3, 4, 5, 6, and 10 fractions was 65%, 85%, 90%, 90%, 95%, and 95% when both motion characteristics and rectal filling status were used. Omitting rectal filling status decreased the ability to correctly classify patients with large motion. Conclusion: Discriminant analysis may be used to incorporate intrafraction motion measurements from initial fractions into prostate margin calculation with reasonable accuracy, leading to margin reductions in the AP and SI‐axes for ∼75% of patients and increased coverage for ∼25%.Conflict of Interest: Partially supported by NIH Grant CA118037.
WE‐SAM‐304A‐02: SPECT/CT: Technology Updates, Quality Assurance and Applications
Authors: Kappadath SC 
Published: April 2010

Hybrid SPECT/CT is rapidly becoming a mainstream imaging modality and creating a new paradigm for SPECT imaging. The ability to contemporaneously acquire electromechanically registered dual‐modality SPECT and CT scans improves the SPECT image quality due to CT‐based attenuation correction, and enhances the diagnostic confidence of SPECT by providing an anatomical overlay. The first generation SPECT/CT systems used single‐slice CT scanners and produced CT images of limited quality for anatomical overlay. The CT systems integrated into the latest generation of SPECT/CT systems are fully‐functional diagnostic scanner (scan parameters includes tube current, tube voltage, rotation speed, collimation, pitch, slice thickness, FOV, etc.). In addition to generating high‐quality attenuation maps these CT systems can produce CT scans with diagnostic image quality, capable of greatly improving both the localization and specificity of abnormalities detected on the corresponding SPECT scan. In some cases, these systems are also capable of performing diagnostic CT scans with contrast enhancement. The widest use of SPECT/CT is currently in oncology, with applications including: tumor localization, staging and response to treatment; pre‐surgical mapping (e.g., parathyroid adenomas, sentinel lymph nodes); differentiation of skeletal metastases from other disease processes; functional image‐based radiation therapy treatment planning (e.g., lung perfusion); and quantitative SPECT/CT‐based internal radionuclide therapy dosimetry/treatment planning. Cardiac SPECT/CT is currently focused primarily on improved attenuation correction of SPECT myocardial perfusion images. SPECT/CT is also being utilized for imaging bone and other non‐malignant diseases.This lecture will review the physics principles underlying SPECT/CT imaging, present several examples of the clinical application of SPECT/CT, and provide an overview of the currently available SPECT/CT scanner types and models.Learning Objectives:1. To understand the physical principles underlying SPECT/CT image acquisition, processing, and reconstruction.2. To understand current and future clinical applications of SPECT/CT imaging.3. To become familiar with the various commercially‐available SPECT/CT product offerings.
WE‐A‐211A‐01: New Dosimetry Measurements — New Developments
Authors: Seuntjens J , Gibbons J , Das I 
Published: April 2010

Image‐guided intensity modulated radiation therapy deliveries are becoming increasingly complex and their verification involves dosimetry measurements in situations that are no longer covered by reference dosimetry protocols or relative dosimetry procedures with simple corrections. These beams are generated as part of intensity modulation (IMRT), stereotactic radiosurgery (SRS), cyber‐knife and gamma‐knife deliveries and involve the use of extremely small fields in order of few millimeters. In this era of joint imaging‐therapy developments, accurate dosimetry techniques are sometimes trivialized and important effects not understood or ignored.This presentation consists of three parts: the first part revisits the guiding principles of measurement dosimetry in standard and nonstandard conditions, definitions of detectors and phantoms, reference dosimetry of conventional beams and also discusses the new developments in reference dosimetry of nonstandard beams. The second part of the presentation concentrates on practical aspects of relative dose measurements with the goal to generate 3D distributions as well as integrated measurements and derived quantities. The third part concentrates on a discussion of relative dosimetry in narrow fields and deals with the choices of possible radiation detectors, the difficulties and possible solutions to measurements in disequilibrium situations created by this era's narrow photon fields.Learning Objectives1. To understand the principles of clinical measurement dosimetry and applicability to standard and nonstandard beams;2. To understand standard clinical reference dosimetry techniques and be exposed to some of the new developments in reference dosimetry in nonstandard beam configurations;3. To get an overview of practical aspects of relative dosimetry techniques for the purpose of 3D dose distributions in standard fields, small photon fields and buil‐up regions;4. To be aware of the complications of measurements and detector choices in electronic disequilibrium situations created by small photon fields.
WE‐A‐BRD‐02: 4D Treatment Planning: Rationale, Methods and Significance
Authors: Rosu M 
Published: April 2010

The breathing‐induced motion adversely affects the radiotherapy process for pulmonary tumors at all stages. During the conventional 3D imaging, motion causes artifacts that lead to erroneous anatomical information that propagates as a systematic error during planning and delivery. For planning, the standard approach to insure tumor coverage in the presence of geometrical uncertainties is to surround the target with a safety region. The pitfall of the margin expansion approach is that additional high doses are delivered to the normal tissue adjacent to the target, thus increasing the chances of radiation‐induced disease, while also limiting tumor dose escalation and, subsequently, the potential for better tumor control. The advent of 4D computed tomography (4D CT) represented a significant step forward toward improved imaging accuracy for regions affected by the respiratory motion due to the ability of reconstructing multiple image sets corresponding to various points during the breathing cycle. The information from the 4D CT is first used to better identify the target region at various stages over the breathing cycle and the extent of motion. Next, the more complete imaging data has to be factored into the planning process. To this end, depending on the treatment delivery strategy, one or more treatment plans are designed for each breathing instance for which data is available. Dose computations are performed on multiple datasets (usually termed as 4D dose calculations), and the cumulative dose is then used to assess the plan quality similar to the conventional 3D planning. The accumulation of doses on a reference image dataset is accomplished by using deformable image registration, which maps corresponding image voxels from one dataset to the reference dataset. To date, several approaches have been developed to fulfill this task. The amount of data available from 4D scans increases significantly the amount of time and effort needed for treatment planning. However, studies have suggested that the dose accumulation process could be reduced to planning on certain datasets only, while preserving at an acceptable level the accuracy that would otherwise be achieved through a full 4D dose computation. Multiple centers have employed the 4D planning approach to study the changes in doses as a result of 4D treatment planning and addressed the clinical significance of the changes observed.In this presentation, we will discuss the rationale for 4D treatment planning, review the methods available for cumulative dose computation, identify potential sources of error specific to the 4D planning approach, and discuss the clinical importance of the dosimetric changes resulting from 4D‐based treatment planning.Learning Objectives:1. Understand the rationale for accounting for respiratory motion during treatment planning.2. Understand the principles of cumulative dose computation.3. Learn about the clinical importance of the changes induced by the respiratory motion.