bluuebunny/crossref_metadata_2025_split huggingface dataset:
TU‐A‐224‐01: Practical Research Advice: NIH Navigation and Grantsmanship
Authors: Paganetti H , Jeraj R , Beddar S 
Published: November 2011

This 1‐hour symposium will be aimed at introducing new (or junior) AAPM members engaged in research to NIH funding. Recently there have been new changes to the grant submission process. and new initiatives to enhance research using “Multiple‐PI” models. We plan to have two segments. The first segment would be to present some of the tools available within the NIH website and how to navigate through it; present briefly the new changes to the submission process and focus on the new scoring system and the new review criteria that would be essential to submitting a successful grant. The second segment will cover aspects on how to set‐up a clinical research program. This would include practical advice for those researchers who are not at the “NIH submission” level yet as well as the many medical physicists that do not have protected research time but are still eager to do clinically relevant research that sometimes could lead to NIH funding. The symposium will be followed with a 10–15 min interactive Q&A session with the audience.Learning objectives:1. Navigate the NIH website and learn about the new tools2. New changes to the NIH scoring system3. New NIH review criteria4. Practical advice for those researchers who are not at the “NIH submission” level yet.
TU‐A‐BRA‐01: Planning, QA, and the Role of Imaging of Localization for Head and Neck Treatments
Authors: Mayo C , Garces Y , Dong L , Howell R 
Published: November 2011

This educational session is designed to provide practical perspective on head and neck treatment planning and delivery. The panel will draw from their own and the shared experiences of the other panelists to provide a comprehensive discussions of the issues and decisions encountered daily as part of treating patients with head and neck cancer.Contouring, PTV and Organ at Risk Doses: a Physicianˈs perspective ‐ How a physician approaches the question of a practical balance between doses to target and proximal normal tissues will be explored and implications of contouring approaches will be considered.• Use and implications of hand drawn PTV vs CTV + margin = PTV• Organs at risk• Dose trade‐offs• Planning process: When is it good enough? Is the difference between plans clinically observable or art? What dose levels, that can be affected in planning, produce results that are observed in practice?Treatment Planning ‐Strategies in beam selection, contouring of dose sculpting structures and in setting of constraints to enable for driving IMRT opimizers to achieve the balance sought by the physician for targets treated at multiple concurrent dose levels will be discussed. Process flow and time to create plans will be discussed.• Dose Sculpting Structures• Beam selection (IMRT vs VMAT)• Optimization strategiesPatient Positioning Options and Imaging Strategies — The ability of the treatment plan to accurately reflect delivered doses, is linked to the ability to reliably set up and verify the same patient position as in the original CT. A range of typical questions and practical approaches will be discussed. • Patient Positioning Options: Head cup + aquaplast,vac‐loc bag, alpha cradle based,bite block, etc.• Imaging∘ kV vs Conebeam∘ Image treatment fields or just setup fields?∘ How frequently should fields be imaged?∘ Decision tree for use of MV, kV, ConeBeam∘ Use of blended imaging tools for checking measured vs predicted DRR or ConeBeam?∘ When it doesnˈt align, then what?IMRT QA — There area wide array of devices and measurements for QA of IMRT fields. This presentation will address issues encountered in designing practical approaches to demonstrate that the dose planned for a patient can be delivered with acceptable accuracy. The strengths and weaknesses of QA approaches will be discussed.• Measurement devices, strategies and basis for choice• Is gamma analysis alone sufficient? What else is used instead?
TU‐A‐BRB‐01: Convex Optimization Techniques for Handling Delivery Time and Plan Complexity in Multi‐Criteria VMAT Optimization
Authors: Craft D , Bortfeld T 
Published: November 2011

Purpose: To explore the joint trade‐offs of target coverage, organ sparing, and delivery time for volumetric modulated arc therapy (VMAT).Methods: One measure of beam‐on time in IMRT is the “sum of positive gradients” (SPG) of the intensity maps. We adapt this measure to VMAT planning. The adaptation is based on the fact that while the beam rotates through a specified arc length, a certain amount of modulation can be achieved “for free”, that is, without slowing down the gantry. The resulting convex optimization formulation is applied to minimizing or constraining delivery time in VMAT. We also consider the selection of collimator angle, and we explore the following: finding the single collimator angle which offers the quickest delivery while maintaining a specified dosimetric plan quality. Results: We demonstrate the optimization routines on three cases: a pancreas, a prostate, and a lung. We find that SPG smoothing decreases delivery time by a factor of 2 for the pancreas and lung cases and 2.7 for the prostate. For the pancreas case, we examine collimator rotation. Compared to the default angle of 0 degrees (i.e. leaf motion perpendicular to gantry rotation direction), a well‐chosen single collimator angle (23° in this case) can reduce the delivery time by an additional 8%. Conclusions: Although the VMAT problem is fundamentally non‐convex, due to the non‐convex mapping from leaf positions to voxel doses, we can use a modified SPG function, which is convex, to compute VMAT plans that correctly slow down the beam where it should. Our method is exact for leaves that move infinitely fast, and practically useful in the finite leaf speed case. It can straightforwardly be embedded into a multi‐criteria system allowing the user to explore the trade‐offs of target coverage, organ sparing, and delivery time.Funding support from NIH R01 Grant
TU‐A‐BRB‐02: An Estimator of Deformable Organ Variation Probability Density Function in IMRT of H&N Cancers
Authors: Nie X , Liang J , Yan D 
Published: November 2011

Purpose: To create a deformable organ variation probability density function (PDF) estimator for the purpose of treatment dose estimation and adaptive inverse planning optimization in the clinical applications of adaptive radiotherapy.Methods: Principle Component Analysis (PCA) was applied to variations of organs of interest manifested on multiple treatment CBCT images. Utilizing the PCA model for deformable organ PDF estimation includes the determination of the eigenvectors and the corresponding coefficients. The coefficients can be either random variables or random functions of treatment time depending on the characteristics of organ deformation as stationary or non‐stationary random process. The least square regression method with time‐varying weighting parameters was applied on the pre‐collected patient images to determine the function form of the coefficients. Seven h&n cancer patients, 31 images per patient, were included in the construction of the estimator and the optimization of the corresponding weighting factor in the estimator. The estimator was evaluated using total 19 organs of interest of another eight patients. Results: The deformable variation of organ can be accurately represented by 3 to 4 eigenvectors. These vectors change and need to be updated with the new image observations during the treatment course. The estimation error in the mean of the organ PDF is less than 3 mm for cord and CTV for elective nodes, and less than 2 mm for the other organs of interest. The estimation error in the standard deviation of the organ PDF is less than 1 mm for all organs of interest. Conclusions: Deformable organ variation estimator is feasible to perform acceptable estimation for deformable organ PDF during the h&n cancer radiation treatment. This estimator will provide an important role in the treatment course of adaptive radiotherapy.This study is partially supported by the research grant from Elekta Oncology System, Inc.
TU‐A‐BRB‐06: Evolving and Optimizing IMRT Treatment Plans with PARETO ‐ a Novel Treatment Planning System Based on a Multi‐Objective Genetic Algorithm
Authors: Fiege J , Potrebko P , Champion H , Cull A , McCurdy B 
Published: November 2011

Purpose: We introduce a novel multi‐objective treatment planning system called PARETO (Pareto‐Aware Radiotherapy Evolutionary Treatment Optimization), which simultaneously optimizes beam angles and fluence patterns by treating the PTV conformity and dose to OARs as separate objectives that are optimized by a powerful multi‐objective parallel genetic algorithm (GA).Methods: PARETO treats radiotherapy treatment planning as a single monolithic optimization problem, in which beam angle configurations and fluence patterns are explored to simultaneously optimize the PTV dose conformity and a dose objective for each OAR. We use a Pareto‐ranking scheme to discover necessary compromises between objectives. A final non‐dominated database of solutions is compiled from all plans evaluated during the run such that no solution in the database is superior to any other solution in all objectives. A graphical tool allows rapid navigation of the pre‐optimized database to select a final treatment option for the patient.Results: PARETO is at the stage of a working prototype. Solutions are of high quality, as judged by DVH curves and dose distribution, and consistent results are obtained between runs. Only minor differences in trade‐off surfaces result from four different fluence parameterizations of varying complexity, but they differ by a factor of ∼4 in speed. A novel feature allows optimization of the number of beams and a realistic test case shows that no further improvements in conformity are found for more than ∼9 beams. A newly implemented GPU‐based ray tracer, including convolution with a patient dose kernel, results in a speedup factor of ∼3 compared to CPU‐based computation. Conclusions: This work demonstrates PARETOˈs feasibility as a treatment‐planning tool, which replaces manual iterative optimization of treatment plans with a rapid graphical exploration of pre‐optimized solutions. Clinically acceptable run times of less than an hour appear within reach by combining several of our GPU‐based systems in parallel.J. Fiege discloses authorship of the Ferret GA (used by PARETO) and ownership of nQube Technical Computing Corporation, which distributes this optimization software.
TU‐A‐BRB‐07: VMAT and IMRT: The Best of Both Worlds
Authors: Matuszak M , McShan D , Fraass B 
Published: November 2011

Purpose: To introduce a hybrid VMAT/IMRT optimization strategy that combines the delivery efficiency of VMAT with the superior intensity modulation possible with IMRT. Methods: A beamlet‐based inverse planning system was enhanced to combine the advantages of VMAT and IMRT into one comprehensive system. In the hybrid system, IMRT plans are created with many beams and optimized to convergence, taking note of the beam intensity map variation (BIMV) at each angle. Second, all beams are converted to VMAT segments and optimized for a set number of cycles. Then, the previous BIMV values and current cost function gradients with respect to the beamlets are used to define a gradient modulation factor (GMF). Beams with the highest GMF are converted from segments to beamlets and optimization proceeds with the mixed variable set until convergence or until additional beams are selected for conversion. This strategy was characterized on phantom and clinical cases. Comparisons were made between the hybrid plans, standard IMRT plans, and VMAT plans. Results: In a simple phantom, a hybrid VMAT/IMRT plan with 3 converted beams achieved superior dosimetric quality and required 30% fewer MU compared to 7‐beam IMRT. The hybrid plan also had a 20% reduction in final cost compared to VMAT. In a pancreas case, a 3 converted beam hybrid plan had improved and equivalent dosimetric quality compared to VMAT and 7‐beam IMRT, respectively. The hybrid and VMAT plans were more delivery efficient than IMRT. Conclusion: A hybrid VMAT/IMRT strategy was implemented to find the best compromise between gantry‐angle and intensity‐based degrees of freedom. This optimization method will allow patients to be simultaneously planned for dosimetric quality and delivery efficiency without switching between delivery techniques. Phantom and clinical examples suggest that the conversion of only 3 VMAT segments to modulated beams results in a good combination of quality and efficiency.Supported by NIH‐P01‐CA59827
TU‐A‐BRC‐02: Hyperpolarized 13C MRSI for Assessing Radiation Response of Prostate Cancer in Transgenic Mice
Authors: Senadheera L , Mayer D , Josan S , Darpolor M , Luong R , Yen Y , Spielman D , Xing L 
Published: November 2011

Purpose: To assess the tumor response to radiation in transgenic mouse model of prostatic adenocarcinoma (TRAMP) by hyperpolarized MR spectroscopic imaging (MRSI) of [1–13C]pyruvate.Methods: The TRAMP mouse model used in this study develops an autochthonous tumor in the prostate at the onset of puberty. The progression of tumors was volumetrically monitored by T2‐weighted MRI at 7 T. Four mice with tumor volumes of 400–1500 mm3 underwent hyperpolarized 13C MRSI at 3 T. Two of them received fractionated X‐ray radiation (200 kV, 20 mA, 1.21 cGy/s, 1 mm Cu HVL) doses of 10 and 20 Gy to the tumors, followed by the 13C MRSI at the fourth day of postirradiation. Dynamic 13C MRSI was performed following an intravenous bolus injection of 300 μL of 80 mM hyperpolarized [1–13C]pyruvate to obtain the transient fate of 13C‐labeled metabolites in a 3D volume encompassing the tumor with a nominal spatial resolution of 2.7×2.7×3 mm3. The average time‐resolved signal intensities of pyruvate and its downstream products lactate and alanine were measured in the tumors from reconstructed metabolic images. Metabolic response was characterized in terms of lactate/pyruvate ratio and apparent rate constant of pyruvate‐to‐lactate conversion, kpl, by fitting data to a two‐site exchange model. Results: Based on MRI volumetry, the TRAMP tumors exponentially grew with doubling time of 7±3 d and shrank in response to radiation by 50% in volume within 4±1 d. The untreated tumors that grew to larger volumes over a similar postirradiation period exhibited increased lactate/pyruvate ratio and kpl compared to the treated tumors. Alanine was in noise levels and hence not considered for analysis. Conclusions: Preliminary data indicate the feasibility of utilizing hyperpolarized 13C MRSI to assess therapeutic response of prostate cancer to radiation in TRAMP mice. Further investigations are underway to obtain additional data.This work is partly supported by DOD PCRP (W81XWH‐10‐10498) research award.
TU‐C‐110‐01: Patient Dose in CT: Calculating Patient Specific Doses in CT(Joint with Education)
Authors: McNitt‐Gray M , Xu X , Samei E 
Published: November 2011

In light of recent events involving dose to patients undergoing CT exams, many efforts to record patient dose have been initiated. Many national and international groups (FDA, NIBIB, ACR, IAEA, and NIH intramural programs) have called for recording “dose”, or required that CT equipment report dose. In California, a state law [SB1237] was recently passed that requires (as of July 1, 2012) the reporting of one of the following: “The computed tomography index volume (CTDIvol) and dose length product (DLP), as defined by the International Electrotechnical Commission (IEC) and recognized by the federal Food and Drug Administration (FDA); The dose unit as recommended by the American Association of Physicists in Medicine”.While these reporting/recording efforts are well‐meaning, the only dose metrics currently available for reporting are CTDIvol and DLP. While CTDIvol values are highly standardized and recognized around the world, they actually are measures of scanner output, and as such they do not reflect the actual patient dose or the irradiation burden of the exam. This misconception of CTDI is commonplace and has led to misinterpretation of the dosimetry values being reported at the scanner and recorded into patient records.The purpose of this symposium is to describe methods to more accurately estimate the radiation dose to various organs, and ultimately the radiation risk, to patients undergoing CT exams. The symposium covers methods aimed towards more patient‐specific estimates that take into account: (a) scanner related factors (CT manufacturer and model specifics), (b) exam related specifics (anatomic coverage, use of dose reduction methods such as tube current modulation) and (c) patient related factors such as age, gender, size, and shape.The learning objectives of this symposium include the following:1. To understand the limitations of current metrics (e.g. CTDIvol) and methods in estimating patient dose2. To understand the methods to more accurately estimate radiation dose that take into account scanner, exam and patient specific factors3. To understand the role of Computational Phantoms and Monte Carlo simulation methods in developing patient‐specific organ dose estimates4. To understand methods to estimate patient‐specific organ doses, effective doses, and radiation risk for comparison and optimization purposes
TU‐C‐211‐01: Automatic Digital Gain Control for a New Dual EMCCD‐Based Modular Fluoroscopic Detector Using An Arbitrary‐Shaped Operator‐Selected Region of Interest
Authors: Qu B , Huang Y , Wang W , Panse A , Cartwright A , Titus A , Bednarek D , Rudin S 
Published: November 2011

Purpose: To report on the design and operation of a fluoroscopic automatic gain control (AGC) system with arbitrary‐shaped operator‐selected region of interest (ROI) for a new high resolution detector consisting of an array of two EMCCD‐based modules. Methods: A solid‐state x‐ray imager consisting of dual EMCCD‐based modules was built to provide high resolution (effective pixel size 26.4 um) and wide dynamic range (55dB) in fluoroscopy. A graphic user interface was employed based on LabVIEW to display the 2K × 1K 12‐bit digital images. The image from the second sensor was digitally rotated and shifted so as to maintain image registration with the image from the first sensor. The AGC system consisting of a real‐ time feed‐back loop and a universal asynchronous receiver/transmitter platform was implemented to enable control by comparing the current average digital values in the operator‐selected ROI with a preset desired value resulting in a step by step change of the EMCCD built‐in gains to achieve the desired image brightness. A standard aluminum step wedge was used to demonstrate the response speed and a head phantom was employed to provide a realistic complex structure, rich in contrast variations. Results: The operator‐selected ROI was able to be positioned anywhere in the full 1K × 2K field of view, even with parts in each module. The settling time for smoothly reaching stable brightness was in the range of 10 to 20 frames. A video sequence demonstrates a smooth brightness transition to the desired value when the head phantom is arbitrarily moved across the field of view of the detector. Conclusions: We introduce a new real‐time AGC design for a unique custom‐built high resolution modular array detector. Stable levels of brightness within the ROI were demonstrated. Operators can set up an arbitrary shaped ROI in advance or during the procedure.Support: NIH Grants R01‐EB008425, R01‐EB002873
TU‐C‐211‐02: Characterizing the Dynamic Range and Noise Performance of a High‐Resolution EMCCD‐Based X‐Ray Detector Having Large Variable Electronic Gain Enabling Use in Both Fluoroscopy and Angiography
Authors: Huang Y , Qu B , Jain A , Wang W , Bednarek D R , Titus A H , Rudin S 
Published: November 2011

Purpose: To quantitatively characterize the dynamic range and noise performance of a new custom‐built, 1k by 1k, 26.4 micron square pixel, high‐resolution, solid‐state EMCCD‐based x‐ray detector. Methods: We performed two sets of experiments: higher‐exposure angiographic imaging with lower gain (< 200), and lower‐exposure fluoroscopic imaging with higher gain (> 200). For each experiment, 150 flat‐field images are acquired over the range of exposures for each multiplication gain. Average signal digital number (DN) versus exposure, and average variance (DN) versus exposure or signal are plotted and linearly fitted to quantitatively characterize the electronic gain, background or dark noise equivalent rms electrons, and instrumentation noise equivalent exposure (INEE), respectively. Results: For the low gain measurements, the noise electron rms value and INEE decreases with increasing gain virtually eliminating the effect of read‐noise, which is the main source of noise for conventional detectors. When the gain is increased for the low exposure measurements, dark noise from dark current and clock induced charge (CIC), which are constant with gain, become dominant and set the detection limit. With the same procedure, an additional experiment is performed to evaluate the dark noise and INEE at high gain with cooling. At room temperature, the dark noise is 1.03 e‐ rms and the INEE is 1.46 microR. Cooling the sensor effectively reduces the noise electrons (0.66 e‐ rms at 200mA pelticooler current and 0.50 e‐ rms at 400mA pelticooler current) and INEE (0.52 microR at 200mA pelticooler current and 0.33 microR at 400mA pelticooler current). Conclusions: The EMCCD‐based x‐ray detector with large variable gain has linear performance over a wide range of exposures with a low noise floor that can be further decreased by moderate cooling. The INEE for this unique detector is substantially less than the 2 to 3 microR of conventional flat panels.Support: NIH Grants R01‐EB008425, R01‐EB002873
TU‐C‐211‐03: Increasing X‐Ray Tube Output for Small Focal Spot, Region‐Of‐Interest Imaging
Authors: Gupta S , Bednarek D , Rudin S 
Published: November 2011

Purpose: High‐resolution region‐of‐interest (ROI) imaging requires the use of a small focal spot with sufficient output to maintain spatial and contrast resolution. We investigate methods to increase the x‐ray output while maintaining the focal‐spot size for a small field‐of‐view (FOV) as needed for endovascular‐image‐guided interventions (EIGIs).Materials and Methods: We evaluated the increase in tube output made possible by reducing the anode angle and lengthening the filament for the small focal spot to maintain a constant effective focal‐spot size. Since the area of heat deposition on the anode is increased, tube‐loading capacity increases and the mA can be increased proportionally if the electron flux density at the target is unchanged. “Spek Calc” software was used to calculate the change in inherent tube filtration and in x‐ray spectrum and intensity as a function of anode angle. The gain in tube output achievable while maintaining focal‐spot size was determined for the small‐FOV of our custom high‐resolution, ROI imager. When the same tube is used for both large‐FOV imager and the small‐FOV ROI imager, angling the tube and adjusting filament length can allow a tradeoff between spatial resolution, tube loading and FOV. Results: For the 5‐cm FOV needed in neurovascular ROI imaging, the x‐ray output could be increased substantially with decreasing anode angle while the focal‐spot size and FOV is maintained. Considering both increased anode‐target area and increased inherent anode filtration, a net output increase of 3.3 times could be achieved with a 2‐ degree anode angle compared to the standard 8‐degree target with an increase of 4 times in filament length. Conclusions: For EIGIs where high resolution is essential but only over a small FOV, higher tube output while maintaining a small focal spot should be achievable with only small modification of standard x‐ray tube geometry.Support: NIH Grants R01‐EB008425, R01‐EB002873