bluuebunny/crossref_metadata_2025 huggingface dataset:
WE‐G‐211‐08: Performance Study of Regularized Phase Retrieval from X‐Ray Differential Phase Contrast Projection Image
Authors: Li K , Zambelli J , Bevins N , Qi Z , Chen G
Published: November 2011

Purpose: X‐ray differential phase contrast (DPC) projection imaging has shown promise for superior image contrast. In the field of medical imaging, however, its differential nature makes the projection image difficult to use for direct diagnosis. In this study, a phase retrieval method is introduced to generate phase images, which are compared with absorption images to demonstrate the benefits of phase contrast projection imaging. Methods: The method involves the minimization of a cost function that includes two terms: a quadratic norm that enforces consistency between the phase image and the DPC image, and a nonconvex norm of the phase imageˈs gradient in the direction perpendicular to the stripes. A weighting parameter α is applied to the second term to tailor the content of stripes. This cost function is minimized to solve for the phase image. A grating‐based DPC system was used to acquire the DPC and absorption images of a cylindrical phantom. The DPC, absorption, directly‐integrated phase and regularized phase images were compared. To evaluate the image quality, simulated spheres of different contrasts and diameters were added to the experimental data. CNR of the beads in the integrated image was used as the figure of merit to optimize the regularization. Results: The retrieved phase image provides complementary information of the phantom that is otherwise lost in the direct‐integrated images because of the presence of stripe noise. Regularized integration improved image quality in terms of CNR and the content of stripe noise. The optimal regularization parameter can be determined from the peaks of the CNR‐α curves and is dependent on the objectˈs contrast. Conclusions: Regularized integration allows for artifact‐free phase retrieval from DPC images and a fair comparison between phase contrast and absorption images. DPC imagingˈs potential application in medical imaging is highlighted by the complementary information provided by the phase image.
WE‐G‐211‐09: X‐Ray Compton Scatter Imaging on Volumetric CT Systems
Authors: Niu T , Zhu L
Published: November 2011

Purpose: The conventional x‐ray CT imaging does not fully utilize all the radiation events. Based on photon interaction mechanisms, many advanced techniques have been proposed to obtain more physical properties of the object. For example, photoelectric response is used to track nano‐particles and phase contrast images are generated from Rayleigh scatter. In this work, we propose a Compton scatter imaging method to measure object electron densities. As compared to existing methods, our approach has a simple and efficient data acquisition process, and therefore is more practical and widely applicable on clinical CT systems with a conventional large‐area detector. Methods: An algorithm for calculation of the object electron density from Compton scatter photons is derived based on photon attenuation and the Klein‐Nishina formula. A Compton scatter imaging method is then designed on a clinical cone‐beam CT system. We place a pinhole collimator in front of the detector such that the incident direction of each measured scatter signal can be determined if single scattering is assumed. In this preliminary study, we use a pencil beam, and estimate the object electron density along the primary beam using scatter from one projection. The feasibility and performance of the proposed method is evaluated using Monte Carlo (MC) simulations. Results: The phantom contains breast gland as the background material with a 10‐cm diameter, and three lymph rods as the contrast objects. These two materials have a contrast of <0.1% and are indistinguishable in conventional CT imaging. The proposed method obtains an electron density image with a 2.6% contrast on the three rods, indicating a superior imaging capability. Conclusions: An effective Compton scatter imaging method is proposed and evaluated using MC simulations. As our method extends the x‐ray imaging capability for material decomposition and accurate dose calculation, it is attractive in advanced clinical applications.
WE‐G‐220‐01: Thermal Dosimetry Issues in Thermal Therapy
Authors: Stafford R
Published: November 2011

Minimally invasive thermal therapies deliver heat to tissue in a controlled manner in order to modulate a host of microscopic and macroscopic events in tissue. Irreversible tissue damage from heating is a cumulative process that depends on exposure time as well as temperature and is often an endpoint for thermal therapies, particularly thermal ablation. Models for predicting the extent of damage after exposure to heat have been implemented and investigated in cells and tissue. With respect to rapid, high temperature ablations, the most often used approaches include simple temperature threshold models, Arrhenius rate models, and cumulative equivalent minutes at 43°C (CEM 43°C). While displaying significantly different responses at lower temperatures or long exposure times, these approaches are more closely related at higher temperatures.

In cases where the ability to visualize the spatiotemporal distribution of heat and resulting damage is realizable, comparisons between these models are possible and useful for comparing with results from imaging and/or pathology correlates. Here we provide a review of the different models for high‐temperature ablations and use magnetic resonance temperature imaging results of thermal ablations, compared to with post‐treatment imaging or histology to illustrate some of the differences between these models when used for predicting outcomes in thermal therapy. Implications for therapy monitoring and guidance are discussed as are future prospects for predicting iso‐effects other than tissue destruction in tissue.

Educational Objectives:

1. Learn basic concepts of thermal dosimetry

2. Understand current usage and potential limitations of applying current models
TH‐A(SAM)‐211‐01: Absorbed Dose Estimation with Internal Emitters
Authors: Williams L
Published: November 2011

The fundamental equality used in internal emitter absorbed dose (D) estimation is D = S*Ã. Here, D and Ã are vectors and S is a rectangular matrix. Generally D and Ã have components assigned to the various body organs. Voxel‐based calculations are also possible if data are obtained in a 3‐D format. The first step in making the estimate is to perform activity (A) measurements in each of the organs that can be visualized in the scanning and/or imaging process. Essentially 6 methods are available for this quantification ranging from inverse‐square counting to quantitative SPECT (QSPECT) or PET. The most common technique is the geometric‐mean method (GM) which requires that two images be acquired simultaneously on each side of the patient. Given a set of counts for each source organ over time A(t), one must integrate numerically to find Ã. It is standard procedure to represent data at times beyond the last imaging point as a physical decay using the half life of the radiolabel. We should note that some agents used for Targeted Radionuclide Therapy (TRT) may not give off photons so that a surrogate agent is used; e.g., 111‐In‐antibody in lieu of 90Y‐antibody.

Given the Ã vector, the estimator then may use S in two types of computations. A type I computation involves using the S matrix obtained from a relevant humanoid phantom. In this case, all organ sizes are specified for a standard man, woman or child and the biological data (Ã) from each animal or patient must be normalized accordingly. Type I calculations are used in regulatory applications and in comparing one agent with another scientifically. Type II computations are patient‐specific in that Ã is unchanged, but S must be modified to represent the geometry of the individual. In TRT, Type II estimates are made with relatively small amounts of activity prior to the start of therapy. Generally, human S values are standard tabulations available in OLINDA and other software. If murine dose estimates are needed, however, some S values are available. The result of the matrix multiplication of S and Ã is a set of doses for each of up to 30 or more target tissues. Because of external beam precedents, it is now becoming common to use both D and D2 in the analysis of tumor regression and normal organ toxicity. In this analysis, one plots the clinical outcome, such as tumor size, vs. a quadratic polynomial in dose. One anticipates a sigmodal response. Using such analyses, it is possible that TRT can evolve into a clinical strategy beyond its present limitation to B‐cell lymphomas.

Learning Objectives:

1. Knowing methods to determine organ activity.

2. Realizing the errors in activity measurement.

3. Understanding the types of dose estimate (phantom vs patient).

4. Using dose as a first step in estimation effectiveness of therapy.
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 calculations

2. To understand calculation of lung shunt fraction and estimation of absorbed dose for lung and liver

3. 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 planning

2. Show how atlas‐based image segmentation can be integrated in the daily clinical workflow

3. 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 brachytherapy

2. Identify critical physics components and their impact on QA and treatment evaluation

3. Highlight factors that require special attention in the planning and execution of implants

4. Demonstrate implementation of QA practices in an LDR prostate brachytherapy program
TH‐A‐214‐03: Automated Patient‐Specific CT Dose Monitoring System: Assessing Variability in CT Dose
Authors: Christianson O , Li X , Frush D , Samei E
Published: November 2011

Purpose: To develop an automated patient‐specific radiation dose monitoring system for CT capable of assessing variability in CT dose delivered to individual patients. Methods: CT image data were sent from PACS to a secure dosimetry server. The dose reports were isolated by DICOM routing software and processed by an optical character recognition algorithm to extract the dose length product (DLP). The DICOM headers provided additional study information, including the study description, protocol, patient age, and patient gender. The effective dose was calculated from the DLP using age‐ and protocol‐specific conversion coefficients. We collected data from Duke University Medical Center (DUMC) and Duke Raleigh Hospital (DRH) over a 5 week period, during which we received over 6,500 CT studies. To assist in data analysis, a graphical user interface was developed capable of generating custom filters to isolate specific CT studies. The filters were used to assess variability in three typical protocols (standard chest, abdomen pelvis, and routine head) across both institutions. Results: Our automated CT dose monitoring program permitted quality assurance on a scale that was previously impractical. We were able to identify individual studies that significantly deviated from the median and flagged them for further review to assess the cause of the elevated dose. Additionally, we employed the custom filters to directly compare dose across three CT scanner models at both DUMC and DRH. We found notable variability between scanners and institutions, indicating the potential for dose reduction and standardization without compromising image quality. Conclusions: We developed an automated patient‐specific CT dose monitoring system to assess variability in CT dose to individual patients. This tool facilitates quality assurance and standardization of CT protocols.
TH‐A‐214‐06: Organ Dose Weighting Methods for Tube Current Modulated CT Exams: Demonstration Using Adult Patient Phantoms
Authors: Caracappa P , Ding A , Gu J , Liu B , Xu X
Published: November 2011

Purpose: To demonstrate a method to estimate organ doses from tube current modulated (TCM) CT examinations using angular organ dose weighting. Method and Materials: An extensive set of Monte Carlo dose calcualtions has become available in recent years using realistic models of human anatomy. Dose to individual organs are documented for particular CT slice positions. For longitudinal TCM CT scans, the available slice‐wise dose is weighted by the tube current for that position. This method has been applied to the RPI series of pregnant phantoms at different genstational ages. Organ doses for x‐ray exposures in flat projections in the four primary directions are also available from tabulated data. To account for rotational TCM in organ dose calculations, a geometric combination of these flat projection organ doses is used to generate weighting factors for tube currents that vary with angle. Sample TCM CT scans have been constructed for standard CT scan ranges using the RPI‐Adult Male and RPI‐Adult Female phantoms. Results: Applicaiton of longitudanal TCM to scans of pregnant patients are shown to reduce fetal dose by 25–35% relative to uniform current at maximum patient thickness. The effective dose applying rotational TCM is reduced by 29% for chest scans and 37% for abdominal scans relative to constant‐current scans at those positions. These dose reductions are verified with direct Monte Carlo simulation of the applied TCM scheme. Conclusion: TCM use is known to result in significant dose savings to the patient. Due to the uniqueness of each individual tube current modulated CT scan, direct Monte Carlo simulations of every possible scheme are impractical. This study demonstrates a method to estimate organ doses from an arbitrary TCM scheme using existing CT dose data. This algorithm is being adopted for use in a CT dose software tool, VirtualDose.
TH‐A‐214‐07: Evaluation of Potential Effective Dose Estimates Using Values Included in CT Dose Reports
Authors: Turner A , McNitt‐Gray M
Published: November 2011

Purpose: CT Dose reports include several values (CTDIvol, DLP) for each series in an exam and often the Total DLP. The purpose of this work was to examine potential methods to calculate effective dose (ED) estimates from these reported values and to assess the accuracy of these ED estimates. Method: ED estimates for three types of CT exams were obtained for an adult female patient (who was slightly larger than reference woman size) using region‐specific DLP‐to‐ED coefficients (k‐factors) by: (A) summing the ED calculated for each scan component in each study, and, (B) calculating ED using the total DLP and the average k‐factor across all anatomical regions included in the exam. ED estimates were obtained for a routine abdomen, a three‐phase liver, and a trauma exam. For each exam, ED estimates were compared to reference values obtained using Monte Carlo simulations to estimate organ doses and then applying ICRP Publication 103 definitions. Results: The routine abdomen exam consists of only one scan, thus methods A and B both resulted in an ED estimate of 5.0mSv which underestimated the reference ED by 37%. For a three‐phase liver exam, both methods A and B estimated an ED of 27.9mSv, which also had an error of −37%. For the trauma exam, method A resulted in an ED estimate of 32.2mSv, which had error of −20% and method B produced an ED estimate of 36mSv, which had a smaller error of 10%. Conclusions: In theory, ED estimates should be obtained by multiplying the DLP for each series by the region‐specific k‐factor and summing (Method A); however, for the trauma exam Method B resulted in an ED with lower error. Regardless of what method is used, the ED estimates from k‐factors differed from the reference method for several reasons including not adjusting for patient size.
TH‐A‐214‐08: Change in X‐Ray CT Spectra inside of Dosimetry Phantoms: Beam Hardening or Beam Softening?
Authors: Zhang D , DeMarco J , Cagnon C , Turner A , Khatonabadi M , McNitt‐Gray M
Published: November 2011

Purpose: To account for the energy dependence of film‐ or solid state‐based dosimeters used in CT, they are often calibrated in air. However, they are used in a CTDI phantom, which may produce a significantly different spectrum due to scatter. The purpose of this study is to use Monte Carlo simulations to investigate the change in CT x‐ray energy spectra between exposures in air and in CTDI phantoms. Methods: The x‐ray fluence in air, and inside both 16 and 32 cm phantoms were estimated using Monte Carlo simulations. A Siemens Sensation 64 CT scanner using 24×1.2mm beam collimation, and a Toshiba Aquilion 64 CT scanner using 8×4mm beam collimation were simulated. In addition, simulations were performed using 2mm collimation for the Toshiba Aquilion 64. For all conditions, the spectra were estimated by tallying at within the phantom to estimate x‐ray fluence. Based on these spectra, the average energy and estimated Half Value Layer were obtained and compared. Results: For Sensation 64 scanner, the HVL decreased from 9.8 mm Al in air to 7.9 and 7.2 mm Al in center of head and body phantoms, respectively. For Aquilion 64 scanner the HVL decreased from 6.2 mm Al in air to 5.9 and 5.8 mm Al in center of head and body phantoms, respectively; however results also showed that the HVLs increased at 12:00 position (to 6.4 and 6.8 mm Al). For Aquilion scanner at narrow collimation setting, the HVLs increased at all positions. Conclusions: The spectra inside phantoms are nearly always different from that of air — under some conditions it is harder and under others it is softer. These differences in spectra should be taken into account when calibrating dosimeters that have energy dependence.
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 technologies

2. Understand the impact of detector design on system imaging performance

3. Understand the clinical limitations and advantages inherent to the different detector designs

4. 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 Objectives

1. 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‐220‐05: Evaluating the Impact of Dual Energy CT on LDR Brachytherapy Dose Calculations
Authors: Landry G , Granton P , Reniers B , van Rooien B , Beaulieu L , Wildberger J , Verhaegen F
Published: November 2011

Purpose: AAPM TG43, the low dose rate (LDR) brachytherapy dosimetry protocol, ignores the effects of tissue composition and densities. Given the photoelectric effectˈs dominance at the low photon energies in use, the dosimetry is dependent on the elemental composition of tissues. AAPM TG186 was mandated to investigate model based dose calculations (MBDC) such as Monte Carlo (MC) simulations as an alternative to TG43. In MBDC, tissue densities and composition are extracted from single energy CT (SECT) data, which can lead to tissue missassignment. The novel dual energy CT (DECT) technology which is now becoming available may improve tissue segmentation. The study aim is to assess the dose calculation accuracy improvement provided by DECT based tissue segmentation compared to SECT. Methods: A Siemens DECT scanner was modelled with ImaSim, a novel CT image simulation tool. Density and atomic number maps of a virtual phantom containing 23 human tissues were extracted from DECT images taken at 80 kVp and 140 kVp. SECT images taken at 120 kVp were also used for segmentation using 3 and 7 tissues. MC dose calculations were performed with 103‐Pd and 125‐I seeds inserted in the phantom for the three segmentation schemes and compared to a reference calculation. Results: SECT segmentation with 3 tissues performs better than the TG43 approach but does not provide adequate dose calculation accuracy. Increasing the number of tissues to 7 significantly improves accuracy, although errors of more than 10% are observed for certain missassigned tissues. Using DECT segmentation brings accuracy within ±5%. Conclusions: DECT provides superior tissue segmentation resulting in high dose calculation accuracy. While SECT segmentation is outperformed by DECT, dose calculation accuracy is found to be tolerable when using seven tissues, supporting the implementation of MBDC based on widely available SECT.
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 radiotherapy

2. Understand various forms of adaptive radiotherapy

3. Understand various factors when choosing adaptive radiotherapy

4. Discuss practical issues related to clinical implementation
TH‐C‐BRB‐02: Gating and Rescanning to Compensate for Organ Motion for Scanned Proton Beam Delivery
Authors: Kraus K , Heath E , Oelfke U
Published: November 2011

Purpose: To evaluate the effect of gating and rescanning on dose distributions for scanned proton beam delivery and achievable irradiation time on a patient specific basis. Methods: We have developed a software tool that simulates scanned proton beam dose delivery to a moving lung tumour by using patient motion and treatment plan data. Based on a 4DCT voxel motion trajectories were calculated along which the dose was accumulated. Using this tool, we investigated rescanning of the ITV for respiration induced organ motion. Furthermore, the effect of gating widow sizes around the exhalation phase (reference phase) as well as gated rescanning was examined. Irradiation time reduction was considered by modeling a high and constant extraction rate of the synchrotron. Results: Rescanning increased the dose homogeneity, however, ten rescans were not sufficient to mitigate interplay effects completely. Gating was found to alleviate local over‐ and under‐dosages. For a gating window of 20%, the minimal dose to 99% of the CTV differed by 6 Gy from the reference dose distribution whereas doses to 1% and 50% differed by less than 1 Gy. For gated rescanning the dose distribution almost reached the reference dose distribution. Interestingly, the difference in the dose distributions for a gating window size of 20% and of 30% was negligible when additional rescanning was applied. However, for a gating window of 20% the treatment time increased by a factor of 3.5 compared to an irradiation without gating. The additional increase of irradiation time due to rescanning (factor 10) could be significantly reduced by the application of an increased extraction rate. Conclusions: Gated rescanning was found to mitigate interplay effects significantly at the cost of increased irradiation time. Based on our study time influencing beam parameters should be subject to an investigation to overcome the problem of elongated irradiation times.
TH‐C‐BRB‐04: Reliability of Proton‐Nuclear Interaction Cross Section Data to Predict Proton‐Induced PET Images in Proton Therapy
Authors: España S , Zhu X , Daartz J , El Fakhri G , Bortfeld T , Paganetti H
Published: November 2011

Purpose: In‐vivo PET range verification relies on the comparison of measured and simulated activity distributions. The accuracy of the simulated distribution depends on the accuracy of the Monte Carlo code, which is in turn dependent on the accuracy of the available cross sections data for β+ isotope production. We have explored different cross section data available in the literature for the main reaction channels (16O(p,pn)15O, 12C(p,pn)11C and 16O(p,3p3n)11C) contributing to the production of β+ isotopes by proton beams in patients. Methods: Available experimental and theoretical values were implemented in the simulation and compared with measured PET images obtained with a high‐resolution PET scanner. Each reaction channel was studied independently. A phantom with three different materials was built, two of them with high carbon or oxygen concentration and a third one with average soft tissue composition. Monoenergetic and SOBP field irradiations of the phantom were accomplished and measured PET images were compared with simulation results. Results: Different cross section values for the tissue‐equivalent material lead to range differences below 1 mm when a 5 min scan time was employed and close to 5 mm differences for a 30 min scan time with 15 min delay between irradiation and scan (a typical off‐line protocol). Conclusion: The results presented here emphasize the need of more accurate measurement of the cross section values of the reaction channels contributing to the production of PET isotopes by proton beams before this in‐vivo range verification method can achieve mm accuracy.
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‐BRB‐09: The Feasibility of Treating Prostate Patients without Using Range Compensator in Passively Scattered Proton Therapy: A Dosimetry Study
Authors: Zhao Z , Toramatsu C , Slopsema R , Su Z , Li Z
Published: November 2011

Purpose: To investigate the feasibility of treating prostate patients without using a range compensator in proton therapy. Methods and Materials: 10 low risk patients and 10 Intermediate risk patients were randomly selected. The low risk patients are getting 78 CGE to the prostate and the Intermediate patients are getting 78 CGE to the prostate with a boost off proximal seminal vesicle at 46 CGE. The low risk patients were re‐planned without compensator for the entire course and the Intermediate patients were re‐planned for the boost treatment. The comparison between the standard plans and the modified plans was made in terms of PTV coverage and normal tissues doses. The t‐test was performed to compare the differences. Results: For low risk and intermediate risk patients, the quality of coverage, homogeneity index, conformity index CI98% and CI50% and the rectal wall V50, V70, bladder wall V30, V80, V82 and dose to 0.1 cc of total femurs were calculated for standard plans and modified plans. The t‐test showed that the bladder V80 is better than that of standard plans for intermediate risk patients. The rest of the indices for both low risk and intermediate risk patients are not significantly different. A 5% significance level was used in the t‐test. Conclusions: This study showed that the modified plans and the standard plans are comparable. For intermediate risk patients, the bladder wall V80 from the modified plan is better than that of that standard plan. Based on this dosimetry study, it is therefore to conclude that it is feasible to treat prostate patients without using range compensator in proton therapy in passively scattered mode.