bluuebunny/crossref_metadata_2025_split huggingface dataset:
TH‐A(SAM)‐211‐02: Yttrium‐90 Microsphere Therapy Planning and Dose Calculations
Authors: Kappadath S C 
Published: November 2011

Yttrium‐90 microsphere therapy, a form of radiation therapy, is an increasingly popular option for care of patients with liver metastases or unresectable hepatocellular carcinoma. The therapy directly delivers Yttrium‐90 microspheres via the hepatic artery to specifically targeted disease sites. Following Yttrium‐90 microsphere therapy, a vast majority of Yttrium‐90 microspheres preferentially lodge in neoplastic tissue due to their embolic size (mean diameter 32 μm) and targeted trans‐arterial delivery. Once embolized the microspheres do not migrate but deposits upto 90% of its energy in the first 5 mm of tissue.Prior to Yttrium‐90 microsphere therapy, a 99mTc‐MAA examination is conducted to evaluate catheter placement and lung‐shunt fraction. The lung shunt fraction and absorbed dose estimates for lung and liver that guide Yttrium‐90 administered activity are based on nuclear medicine imaging. A review of the pre‐ and post‐therapy imaging procedures underlying Yttrium‐ 90 microsphere therapy will be presented. Calculation of the lung shunt fraction and dosimetry models to estimate radiation absorbed doses will be discussed. Radiation safety issues will be also be reviewed.Educational Objectives:1. To understand the imaging sequence for Yttrium‐90 microsphere therapy planning and dose calculations2. To understand calculation of lung shunt fraction and estimation of absorbed dose for lung and liver3. To become familiar with radiation safety and regulations surrounding Yttrium‐90 microsphere therapy
TH‐A‐224‐01: Automated Segmentation through Deformable Registration
Authors: Schreibmann E 
Published: November 2011

Segmentation remains the most time‐consuming task in radiotherapy planning. In a fundamental paradigm shift, atlas segmentation recently emerged as a fully automated technology that relies on matching an image, through deformable registration, to a template with carefully segmented structures. The method works well for structures that do not have a clear border in low‐contrast regions.Due to its practicability, the approach was recently incorporated by various vendors in their software solutions. With significant cost and time saving achievable through implementation of atlas segmentation in your clinic, the aim of this course is to familiarize you with the approach and terminology in a simple and intuitive presentation.Examples of integrating atlas segmentation in the daily clinical workflow will be presented to illustrate advantages and lessons learned when adapting this new technology in the clinic. Latest research findings in auto‐ segmenting difficult structures in thoracic and abdominal anatomy will also be presented.Learning objectives:1. Understand how atlas‐based segmentation simplifies segmentation for treatment planning2. Show how atlas‐based image segmentation can be integrated in the daily clinical workflow3. Present current research findings and problems
TH‐A‐BRA‐02: Review of the Radiobiological Principles of Radiotherapy and Radiation Protection
Authors: Borras C 
Published: November 2011

The radiobiological principles underlying radiation protection guidelines will be reviewed, analyzing the published results of the effects of ionizing radiation at the cellular level, in animal experiments and, especially,in epidemiological studies. Human data on radiation induced cancer and genetic effects published by the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) and the Biological Effects of Ionizing Radiation (BEIR) Committee,with their latest estimates of risk per unit dose, will be presented. The dose response of normal tissues will be discussed, including effects on the developing embryo and fetus. The recent draft of the International Commission on Radiological Protection (ICRP) on Early and late effects of radiation in normal tissues and organs: threshold doses for tissue reactions and other non‐cancer effects of radiation in a radiation protectioncontext,which includes follow up times much longer than those common in radiotherapy (up to 20 to 40 versus 5 to 10 years) for some tissues, will be introduced. In particular, the current information on acute and chronic radiation syndromes, as well as the newly proposed threshold doseof 0.5 Gy for cataract induction and cardiovascular effects, will be examined. The impact of these newly proposed threshold values on the development of radiation protection guidelines and standards, especially in the forthcoming International Basic Safety Standards on Protection against Ionizing Radiation and for the Safety of Radiation Sources(BSS),will be evaluated. The units and their values used in radiation protection, and the operational units used for measurements, will be presented. The concepts of equivalent dose vs dose equivalent as well as the term effective dose, the Sv unit, and the radiation and tissue weighting factors will be explained and illustrated.Learning Objectives:1. To understand the radiobiological basis of radiation protection standards.2. To distinguish between stochastic and deterministic effects.3. To define the radiation protection magnitudes and units, their values and their practical measurement.
TH‐A‐BRB‐01: Low Dose Rate Prostate Brachytherapy Quality Assurance and Treatment Evaluation
Authors: Butler W , Chen Z 
Published: November 2011

Most medical events in prostate seed brachytherapy may be attributed to physician or physicist error, but human failures resulting in patient harm often can be attributed to inadequate mechanisms to prevent failures from propagating to the patient. Quality assurance (QA) of permanent seed brachytherapy is particularly important because this modality, unique to radiotherapy, leaves a permanent record of the implant quality within the patient.This symposium aims to review the properties of permanent LDR brachytherapy that have made it so successful and the challenges that have prevented the full realization of its theoretical advantages. The temporal interplay between radioactive decay, resolution rate of procedure‐induced edema, and cellular processes will be discussed along with their effect on the design and evaluation of LDR prostate brachytherapy. Recent recommendations of AAPM TG‐137 on prostate brachytherapy treatment planning and dose reporting will be reviewed.An analysis of actual medical events and typical errors, for example seed strength in the plan versus the strength ordered versus the strength implanted, will help focus on critical components of the process map. A methodology to score failure modes and effects via the product of Likelihood × Severity × Undetectability will allow users to score procedural steps dynamically. Quality control steps such as second checks or calibrations will be seen as vital in keeping the scores below a level of concern.Finally, the physicist has a responsibility to offer suggestions to improve dosimetry when systematic trends are evident and to identify and report errors.Learning objectives:1. Discuss recent developments and insights in LDR prostate brachytherapy2. Identify critical physics components and their impact on QA and treatment evaluation3. Highlight factors that require special attention in the planning and execution of implants4. Demonstrate implementation of QA practices in an LDR prostate brachytherapy program
TH‐A‐110‐01: Digital Projection X‐Ray Detectors: A Review of Current Technology and Commercial Landscape
Authors: Yorkston J , Gingold E 
Published: November 2011

In the last decade there has been an explosion in the number of digital projection x‐ray acquisition systems available in the marketplace. There has been an accompanying explosion in the terminology describing the different x‐ray detector technologies used in the different commercial systems. Various companies use similar nomenclature to describe systems that incorporate markedly different detector technologies, while others use different terminology to describe essentially the same technology. This has resulted in considerable confusion in the clinical community as to the differentiating features of different commercially available systems.This lecture will review the most common digital projection x‐ray detector technologies with a particular focus on identifying the differentiating aspects of their design and capabilities. Particular attention will be paid to the similarities and differences in the detectorˈs fundamental imaging components with a view to explaining the range of imaging capabilities of the different approaches.The second half of the presentation will focus on the clinical implementation of the different detector technologies. A broad review of the currently available clinical systems will be given and the connection between system capabilities and detector design will be discussed. The issue of detector “speed” in a digital environment will be addressed in the context of the new IEC exposure index currently being implemented by system manufacturers. The talk will conclude with a discussion of the new wireless digital detectors currently being introduced into the clinical workplace.Learning Objectives:1. Identify and understand the differentiating features of different digital projection x‐ray detector technologies2. Understand the impact of detector design on system imaging performance3. Understand the clinical limitations and advantages inherent to the different detector designs4. Review the current commercial system landscape in terms of the different detector technologies
TH‐A‐301‐01: Managing Pediatric CT Patient Doses
Authors: Strauss K 
Published: November 2011

Proper management of the radiation dose received by pediatric CT patients requires CT scan parameters tailored for the pediatric patient based on the patientˈs size and the specific nature of the CT exam. One approach is to develop specific technique charts for each different CT scanner in the department as a function of patient size for each specific type of CT exam. This results in the need for numerous technique charts.An alternative approach to managing patient doses in pediatric CT is the estimation of the patient dose prior to the scan to be compared with department developed reference doses. The methods developed by AAPM Task Group 204 will be reviewed as an approach to calculating a “Size Specific Dose Estimate” (SSDE) for each patient prior administering their scan. Methods to review this data and utilize it to manage the radiation dose received by the patient will be discussed.Learning Objectives1. Participant will understand the limitations of the two standard CT dose indices, CTDIvol and DLP, with respect to CT dose estimates.2. Participant will learn how to calculate the SSDE.3. Participant will learn how to use SSDE values to manage the CT radiation doses received by pediatric patients.
TH‐A‐220‐08: A Feasibility Study of a Rigidity Penalty Term for Deformable Alignment in the Head and Neck Region
Authors: Kim J , Matuszak M , Saitou K , Balter J 
Published: November 2011

Purpose: To investigate the feasibility and impact of a rigidity penalty (RP) on displacement vector field (DVF) for improvement of deformable alignment in the neck region. Methods: An existing B‐spline image registration method was modified to contain a weighted sum of image similarity measure and penalty terms. The penalty term was derived from the orthogonality condition of the deformation gradient tensor. This term was applied to a cervical vertebral body (C3) which was segmented from a reference image. Sum of squared difference (SSD) was used for the image similarity measure. The method was tested on cone‐beam CT scans taken for head and neck intensity‐modulated radiation therapy. To evaluate the accuracies of the existing and modified methods, the strain components of DVFs were calculated, and the measured versus transformed coordinates of 10 landmarks located on the vertebra were compared. Results: The RP value was minimized by the penalized image registration method although the SSD was slightly compromised. The strain components of the DVFs were significantly reduced. Moreover, the registration errors of the landmark pairs were decreased (−0.254 ± 2.176, −2.045 ± 3.894, 0.562 ± 3.179) [mm] to (− 0.381 ± 0.580, 0.236 ± 1.996, 0.437 ± 1.250) [mm]. Conclusions: Reduction in strain indicates that the RP term successfully discouraged local deformation. In addition, improvement in the registration accuracy of the landmark pairs shows the modified method outperforms unregularized alignment. The results also indicate that image alignment using only intensity metrics may result in nonphysical DVFs. Ongoing work will further explore optimizing the weighting of the penalty for clinical images in the neck region, as well as testing on a finite element modeled representation of the neck anatomy undergoing controlled physical deformations.This work was supported by NIHP01CA59827.
TH‐B‐224‐01: PET Imaging of Tumor Microenvironment for Radiation Treatment Planning
Authors: Pugachev A 
Published: November 2011

Positron Emission Tomography (PET) imaging of the fluorodeoxyglucose (18F‐FDG) has been the workhorse of oncologic nuclear medicine as it allows for the detection of most cancer lesions with high sensitivity and specificity. However, for the purpose of radiation therapy treatment planning, it is important not only to detect the disease but also to define its extent and, potentially, the subvolumes characterized by different levels of radioresistance. Correspondingly, for PET‐based treatment planning it is not the uptake of the tracer in the lesion as a whole but rather the spatial pattern of the tracer uptake that is used to derive the spatial characteristics of the prescribed dose. Therefore, demonstration of positive correlation between PET SUV value and a certain histopathological measure across a cohort of patients is not sufficient to validate the use of PET tracer for treatment planning. Instead, validation of PET tracers has to include a step demonstrating spatial concordance of the tracer uptake pattern with the distribution of the feature of interest, i.e. hypoxia, proliferation, etc. The presentation will demonstrate that direct imaging of any tumor microenvirionmental parameter in detail is not achievable with any clinically‐relevant non‐invasive imaging modality, as the required resolution would have to be under 100micron. Instead, PET image obtained with any tracer represents a convolution of the point spread function of the imaging device with the tissue viability, PET tracer delivery (availability), and, finally, the specificity of the tracer. Correspondingly, utilization of “functional PET volume” delineation techniques for defining therapeutic targets should be approached carefully. A non‐binary dose‐painting approach using a well characterized tracer might constitute a more robust method of utilization of biological information that can be obtained with PET.Learning objectives:1. Become aware of the role played by the highly heterogeneous nature of tumor microenvironment in the formation of PET image.2. Understand the importance of the spatial distribution of the tracer as opposed to a single‐value characteristic such as maximum or average SUV when PET image is to be used for radiation treatment planning.3. Learn about alternative non‐binary ways of utilization of PET imaging in radiation treatment planning.
TH‐C‐BRA‐01: Online Adaptive Radiotherapy: Technical Barriers and Potential Solutions
Authors: Jiang S , Gu X , Jia X , Men C , Gautier Q , Uribe‐Sanchez A , Mell L , Mundt A 
Published: November 2011

By seamlessly integrating treatment simulation and planning into the treatment delivery process, online adaptive radiotherapy (ART) allows realtime treatment adaptations based on the current patient anatomy and therefore holds significant promise in maximally compensating for anatomical uncertainties. This new paradigm of cancer radiotherapy provides an opportunity to significantly reduce normal tissue toxicity and/or to improve tumor control. Additionally, online ART can also handle the interfraction variation of the organ motion pattern, the inaccuracy of patient positioning (fast but less accurate patient positioning is then allowed), direct treatment without a traditional CT simulation, and the change of treatment strategy in the middle of the treatment course. However, the clinical realization of online ART is extremely challenging, mainly due to three major barriers: the inability for real‐time treatment re‐planning, the concern of excessive imaging dose from daily CT/CBCT, and the lack of an efficient clinical workflow. To overcome these barriers, we have been developing a series of GPU‐based computational tools for real‐time re‐planning, GPU‐based low‐dose CT/CBCT reconstruction, and an innovative computational infrastructure for a streamlined clinical workflow. In this talk, we will discuss the current status of this effort and some initial clinical applications.This lecture will provide an overview of the technical barriers for the clinical realization of online adaptive radiotherapy as well as the current efforts to overcome these barriers.Learning Objectives:1. Understand the great potential of online adaptive radiotherapy;2. Understand the major technical barriers for the clinical realization of online adaptive radiotherapy;3. Understand the great potential of using graphics processing unit (GPU) to achieve high computational efficiency;4. Understand an IMRT plan can be developed in seconds using GPU‐ based computational tools;5. Understand CT/CBCT imaging dose can be reduced by 1–2 orders of magnitude using new reconstruction algorithms;6. Understand a streamlined clinical workflow can be developed for online adaptive radiotherapy.
TH‐C‐BRA‐03: Online Adaptive Radiotherapy: Are We Ready?
Authors: Dong L 
Published: November 2011

With rapid deployment of image‐guided radiation therapy (IGRT), evidence is mounting that daily variations in patientˈs anatomy can be quite complicated. A simple couch shift will not be able to correct all non‐rigid changes in patientˈs anatomy. Adaptive radiotherapy is a replanning process to manage temporal changes in patientˈs anatomy or tumor biology. Adaptive radiotherapy can be based on either morphological changes or physiological changes during a treatment course. In addition, adaptive radiotherapy can be applied either online or offline. The potential clinical benefit for online adaptive radiotherapy depends on (1) the size (dose level) of treatment fraction; (2) the length of adaptive treatment process; (3) the probability and magnitude for intra‐fraction variations; and (4) the predictability for such variations in future treatment fractions. Online vs. offline corrections will be discussed along with anatomical and functional image‐guided adaptive radiotherapy approaches. While technology appears to be the primary obstacle in the present time, the image‐guided adaptive radiotherapy process is a natural extension of image‐guided conformal radiotherapy. Practical issues in deploying adaptive radiotherapy in routine clinical practice will be discussed using institutionˈs experience in several prospectively designed treatment protocols.The learning objectives are:1. Demonstrate limitations of IGRT and benefits of adaptive radiotherapy2. Understand various forms of adaptive radiotherapy3. Understand various factors when choosing adaptive radiotherapy4. Discuss practical issues related to clinical implementation
TH‐C‐BRB‐05: Comparison of Dosimetric Benefit of Online Dose‐Guided Alignment versus Anatomy‐Guided Alignment for Proton Therapy
Authors: Cheung J , Park P , Zhu XR , Court LE , Frank SJ , Kudchadker R , Dong L 
Published: November 2011

Purpose: To explore the feasibility of using daily volumetric imaging for optimizing beam‐by‐beam alignment for proton therapy based on dosimetric factors instead of simple anatomical alignment. Methods: Eight weekly 4DCT images for a lung patient who was previously treated with two‐beam passively scattered proton therapy were analyzed for dosimetric alignment. Only the time‐averaged CT was used for this inter‐fractional alignment study. An anatomy‐based registration was first obtained using rigid registration software. Each weekly CT was retrospectively evaluated by calculating the dose distribution for various potential shifts for each beam using a fast dose approximation method based on range mapping of water‐ equivalent thickness. Deformable image registration was used to deform contours from the original planning CT to each successive CT image for dose evaluation of the target and organs‐at‐risk for each shift. Various dosimetric metrics, which include target coverage (V95), maximum dose to the spinal cord, and mean doses to the esophagus, heart, and total lung, were evaluated for the best alignment. Results: We found that, on average, the relative difference for all beams from the best anatomical alignment to the best dosimetric alignment was 5.8 mm anteriorly, 1.7 mm laterally, and 4.7 mm superiorly. The maximum relative beam displacement between two beams was 12.3 mm. Conclusions: Proton dose distribution changes with the change in patientˈs anatomy. The best alignment based on anatomical alignment may not represent the best dosimetric alignment. Instead of replanning from scratch prior to each treatment, we demonstrated that a slight adjustment to the daily isocenter from the best anatomical alignment could improve target dose coverage and/or spare normal structures. Additionally, beam‐by‐beam alignment may be necessary because the best alignment for each beam may be different.This research was performed in partial fulfillment of the requirements for the Ph.D. degree from The University of Texas Graduate School of Biomedical Sciences at Houston;The University of Texas MD Anderson Cancer Center, Houston, Texas 77030.Supported in part by NCI P01 CA021239
TH‐C‐BRC‐05: 4DCBCT Reconstruction Using a PCA Based DVF Motion Model
Authors: Staub D , Docef A , Murphy M 
Published: November 2011

Purpose: To develop a 4D cone beam CT (4DCBCT) reconstruction algorithm that produces a time series of images with high spatial and temporal resolution, minimal artifact, and no time averaging of data as compared to standard 4DCBCT reconstruction techniques. Methods: Our algorithm works to constrain a motion model by using it to deform a static prior CT image at multiple time steps. It then adjusts the motion model parameters until digitally reconstructed radiographs (DRRs) taken through the deformed prior optimally match the projections of the raw 4DCBCT data‐set. Once the motion model parameters have been optimized the motion model can be used to animate the static CT, in essence producing a 3D video that serves as the reconstructed 4DCBCT. Our motion model uses principal components analysis (PCA) of a DVF training set to generate eigenvectors characterizing de‐correlated modes of anatomic motion. It produces new DVFs by computing weighted sums of the eigenvectors. Each eigenvector weight, or principal coefficient, varies in time uniquely according to a parameterized version of the patient breathing trace. Results: Our current focus is on proof of concept testing using numerically generated data. We plan to test the algorithm on simulated data with different degrees of motion complexity. In addition, we will test the effect on eigenvector quality of different DVF training set acquisition methods. Early results indicate that when supplied with an ideal DVF training set the model can reproduce simple motion to a high degree of accuracy. Conclusions: Our current task is to test our algorithmˈs reconstruction quality with numerically simulated data of varying complexity. Beyond that we plan to test on phantom and patient data. If our reconstruction algorithm is successful it will produce 4DCBCTs with high spatial and temporal resolution, low artifact, and no time averaging.This work supported by NIH P01 CA116602.