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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Clinical evaluations of an amplitude-based binning algorithm for 4DCT reconstruction in radiation therapy

Purpose: Phase-binning algorithms are commonly utilized in 4DCT image reconstruction for characterization of tumor or organ shape and respiration motion, but breathing irregularities occurring during 4DCT acquisition can cause considerable image distortions. Recently, amplitude-binning algorithms have been evaluated as a potential improvement to phase-binning algorithms for 4DCT image reconstruction. The purpose of this study was to evaluate the performance of the first commercially available on-line retrospective amplitude-binning algorithm for comparison to the traditional phase-binning algorithm. Methods: Both phantom and clinical data were used for evaluation. A phantom of known geometry was mounted on a 4D motion platform programmed with seven respiratory waves (two computer generated and five patient trajectories) and scanned with a Philips Brilliance Big bore 16-slice CT simulator. 4DCT images were reconstructed using commercial amplitude- and phase-binning algorithms. Image quality of the amplitude- and phase-binned image sets was compared by evaluation of shape and volume distortions in reconstructed images. Clinical evaluations were performed on 64 4DCT patient image sets in a blinded review process. The amplitude- and phase-binned 4DCT maximum intensity projection (MIP) images were further evaluated for 28 stereotactic body radiation therapy (SBRT) cases of total 64 cases. A preliminary investigation of the effects of respiratory amplitude and pattern irregularities on motion artifact severity was conducted. Results: The phantom experiments illustrated that, as expected, maximum inhalation occurred at the 0% amplitude and maximum exhalation occurred at the 50% amplitude of the amplitude-binned 4DCT image sets. The phantom shape distortions were more severe in the images reconstructed from the phase-binning algorithm. In the clinical study, compared to the phase-binning algorithm, the amplitude-binning algorithm yielded fewer or less severe motion artifacts in 37.5% of the cases (24/64), comparable artifacts in 54.7% of the cases (35/64), and slightly greater artifacts in 7.8% of the cases (5/64). Evaluation of SBRT cases demonstrated that the reconstructed tumor sizes and locations were comparable in 96% (1/28) of the MIP image pairs generated from both amplitude- and phase-binning algorithms. In this case the amplitude-binned image set rendered a smaller tumor size, which was likely due to very shallow respiratory amplitudes occurring over several breathing cycles. Conclusions: Overall, the amplitude-binning algorithm for 4DCT reconstruction reduced the severity of tumor distortion and image artifacts compared to the phase-binning algorithm. However, the full range of motion may not be characterized using amplitude-binning algorithms. Despite superior performance, amplitude binning can still be susceptible to motion artifacts caused by large variations in amplitude of respiratory waves.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

WE-A-201-00: Anne and Donald Herbert Distinguished Lectureship On Modern Statistical Modeling

Chris Marshall: Memorial Introduction Donald Edmonds Herbert Jr., or Don to his colleagues and friends, exemplified the “big tent” vision of medical physics, specializing in Applied Statistics and Dynamical Systems theory. He saw, more clearly than most, that “Making models is the difference between doing science and just fooling around [ref Woodworth, 2004]”. Don developed an interest in chemistry at school by “reading a book” - a recurring theme in his story. He was awarded a Westinghouse Science scholarship and attended the Carnegie Institute of Technology (later Carnegie Mellon University) where his interest turned to physics and led to a BS in Physics after transfer to Northwestern University. After (voluntary) service in the Navy he earned his MS in Physics from the University of Oklahoma, which led him to Johns Hopkins University in Baltimore to pursue a PhD. The early death of his wife led him to take a salaried position in the Physics Department of Colorado College in Colorado Springs so as to better care for their young daughter. There, a chance invitation from Dr. Juan del Regato to teach physics to residents at the Penrose Cancer Hospital introduced him to Medical Physics, and he decided to enter the field. He received his PhD from the University of London (UK) under Prof. Joseph Rotblat, where I first met him, and where he taught himself statistics. He returned to Penrose as a clinical medical physicist, also largely self-taught. In 1975 he formalized an evolving interest in statistical analysis as Professor of Radiology and Head of the Division of Physics and Statistics at the College of Medicine of the University of South Alabama in Mobile, AL where he remained for the rest of his career. He also served as the first Director of their Bio-Statistics and Epidemiology Core Unit working in part on a sickle-cell disease. After retirement he remained active as Professor Emeritus. Don served for several years as a consultant to the Nuclear Regulatory Commission and may be remembered for his critique of the National Academy of Sciences BEIR III report (stating that their methodology “imposes a Delphic quality to the .. risk estimates”.) This led to his appointment as a member of the BEIR V committee. Don presented refresher courses at the AAPM, ASTRO and RSNA meetings and was active in the AAPM as a member or chair of several committees. He was the principal author of AAPM Report 43, which is essentially a critique of established clinical studies prior to 1992. He was co-editor of the Proceedings of many symposia on Time, Dose and Fractionation held in Madison, Wisconsin. He received the AAPM lifetime Achievement award in 2004. Don’s second wife of 46 years, Ann, predeceased him and he is survived by daughters Hillary and Emily, son John and two grandsons. Don was a true gentleman with a unique and erudite writing style illuminated by pithy quotations. If he had a fault it was, perhaps, that he did not realize how much smarter he was than the rest of us. This presentation draws heavily on a biography and video interview in the History and Heritage section of the AAPM website. The quote is his own. Andrzej Niemierko: Statistical modeling plays an essential role in modern medicine for quantitative evaluation of the effect of treatment. This session will feature an overview of statistical modeling techniques used for analyzing the many types of research data and an exploration of recent advances in new statistical modeling methodologies. Learning Objectives: To learn basics of statistical modeling methodology. To discuss statistical models that are frequently used in radiation oncology To discuss advanced modern statistical modeling methods and applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-A-201-01: Memorial Introduction

Chris Marshall: Memorial Introduction Donald Edmonds Herbert Jr., or Don to his colleagues and friends, exemplified the “big tent” vision of medical physics, specializing in Applied Statistics and Dynamical Systems theory. He saw, more clearly than most, that “Making models is the difference between doing science and just fooling around [ref Woodworth, 2004]”. Don developed an interest in chemistry at school by “reading a book” - a recurring theme in his story. He was awarded a Westinghouse Science scholarship and attended the Carnegie Institute of Technology (later Carnegie Mellon University) where his interest turned to physics and led to a BS in Physics after transfer to Northwestern University. After (voluntary) service in the Navy he earned his MS in Physics from the University of Oklahoma, which led him to Johns Hopkins University in Baltimore to pursue a PhD. The early death of his wife led him to take a salaried position in the Physics Department of Colorado College in Colorado Springs so as to better care for their young daughter. There, a chance invitation from Dr. Juan del Regato to teach physics to residents at the Penrose Cancer Hospital introduced him to Medical Physics, and he decided to enter the field. He received his PhD from the University of London (UK) under Prof. Joseph Rotblat, where I first met him, and where he taught himself statistics. He returned to Penrose as a clinical medical physicist, also largely self-taught. In 1975 he formalized an evolving interest in statistical analysis as Professor of Radiology and Head of the Division of Physics and Statistics at the College of Medicine of the University of South Alabama in Mobile, AL where he remained for the rest of his career. He also served as the first Director of their Bio-Statistics and Epidemiology Core Unit working in part on a sickle-cell disease. After retirement he remained active as Professor Emeritus. Don served for several years as a consultant to the Nuclear Regulatory Commission and may be remembered for his critique of the National Academy of Sciences BEIR III report (stating that their methodology “imposes a Delphic quality to the .. risk estimates”.) This led to his appointment as a member of the BEIR V committee. Don presented refresher courses at the AAPM, ASTRO and RSNA meetings and was active in the AAPM as a member or chair of several committees. He was the principal author of AAPM Report 43, which is essentially a critique of established clinical studies prior to 1992. He was co-editor of the Proceedings of many symposia on Time, Dose and Fractionation held in Madison, Wisconsin. He received the AAPM lifetime Achievement award in 2004. Don’s second wife of 46 years, Ann, predeceased him and he is survived by daughters Hillary and Emily, son John and two grandsons. Don was a true gentleman with a unique and erudite writing style illuminated by pithy quotations. If he had a fault it was, perhaps, that he did not realize how much smarter he was than the rest of us. This presentation draws heavily on a biography and video interview in the History and Heritage section of the AAPM website. The quote is his own. Andrzej Niemierko: Statistical modeling plays an essential role in modern medicine for quantitative evaluation of the effect of treatment. This session will feature an overview of statistical modeling techniques used for analyzing the many types of research data and an exploration of recent advances in new statistical modeling methodologies. Learning Objectives: To learn basics of statistical modeling methodology. To discuss statistical models that are frequently used in radiation oncology To discuss advanced modern statistical modeling methods and applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-A-201-02: Modern Statistical Modeling

Chris Marshall: Memorial Introduction Donald Edmonds Herbert Jr., or Don to his colleagues and friends, exemplified the “big tent” vision of medical physics, specializing in Applied Statistics and Dynamical Systems theory. He saw, more clearly than most, that “Making models is the difference between doing science and just fooling around [ref Woodworth, 2004]”. Don developed an interest in chemistry at school by “reading a book” - a recurring theme in his story. He was awarded a Westinghouse Science scholarship and attended the Carnegie Institute of Technology (later Carnegie Mellon University) where his interest turned to physics and led to a BS in Physics after transfer to Northwestern University. After (voluntary) service in the Navy he earned his MS in Physics from the University of Oklahoma, which led him to Johns Hopkins University in Baltimore to pursue a PhD. The early death of his wife led him to take a salaried position in the Physics Department of Colorado College in Colorado Springs so as to better care for their young daughter. There, a chance invitation from Dr. Juan del Regato to teach physics to residents at the Penrose Cancer Hospital introduced him to Medical Physics, and he decided to enter the field. He received his PhD from the University of London (UK) under Prof. Joseph Rotblat, where I first met him, and where he taught himself statistics. He returned to Penrose as a clinical medical physicist, also largely self-taught. In 1975 he formalized an evolving interest in statistical analysis as Professor of Radiology and Head of the Division of Physics and Statistics at the College of Medicine of the University of South Alabama in Mobile, AL where he remained for the rest of his career. He also served as the first Director of their Bio-Statistics and Epidemiology Core Unit working in part on a sickle-cell disease. After retirement he remained active as Professor Emeritus. Don served for several years as a consultant to the Nuclear Regulatory Commission and may be remembered for his critique of the National Academy of Sciences BEIR III report (stating that their methodology “imposes a Delphic quality to the .. risk estimates”.) This led to his appointment as a member of the BEIR V committee. Don presented refresher courses at the AAPM, ASTRO and RSNA meetings and was active in the AAPM as a member or chair of several committees. He was the principal author of AAPM Report 43, which is essentially a critique of established clinical studies prior to 1992. He was co-editor of the Proceedings of many symposia on Time, Dose and Fractionation held in Madison, Wisconsin. He received the AAPM lifetime Achievement award in 2004. Don’s second wife of 46 years, Ann, predeceased him and he is survived by daughters Hillary and Emily, son John and two grandsons. Don was a true gentleman with a unique and erudite writing style illuminated by pithy quotations. If he had a fault it was, perhaps, that he did not realize how much smarter he was than the rest of us. This presentation draws heavily on a biography and video interview in the History and Heritage section of the AAPM website. The quote is his own. Andrzej Niemierko: Statistical modeling plays an essential role in modern medicine for quantitative evaluation of the effect of treatment. This session will feature an overview of statistical modeling techniques used for analyzing the many types of research data and an exploration of recent advances in new statistical modeling methodologies. Learning Objectives: To learn basics of statistical modeling methodology. To discuss statistical models that are frequently used in radiation oncology To discuss advanced modern statistical modeling methods and applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

On the Benefits and Risks of Proton Therapy in Pediatric Craniopharyngioma

Purpose: Craniopharyngioma is a pediatric brain tumor whose volume is prone to change during radiation therapy. We compared photon- and proton-based irradiation methods to determine the effect of tumor volume change on target coverage and normal tissue irradiation in these patients. Methods and Materials: For this retrospective study, we acquired imaging and treatment-planning data from 14 children with craniopharyngioma (mean age, 5.1 years) irradiated with photons (54 Gy) and monitored by weekly magnetic resonance imaging (MRI) examinations during radiation therapy. Photon intensity-modulated radiation therapy (IMRT), double-scatter proton (DSP) therapy, and intensity-modulated proton therapy (IMPT) plans were created for each patient based on his or her pre-irradiation MRI. Target volumes were contoured on each weekly MRI scan for adaptive modeling. The measured differences in conformity index (CI) and normal tissue doses, including functional sub-volumes of the brain, were compared across the planning methods, as was target coverage based on changes in target volumes during treatment. Results: CI and normal tissue dose values of IMPT plans were significantly better than those of the IMRT and DSP plans (p < 0.01). Although IMRT plans had a higher CI and lower optic nerve doses (p < 0.01) than did DSP plans, DSP plans had lower cochlear, optic chiasm, brain, and scanned body doses (p < 0.01). The mean planning target volume (PTV) at baseline was 54.8 cm{sup 3}, and the mean increase in PTV was 11.3% over the course of treatment. The dose to 95% of the PTV was correlated with a change in the PTV; the R{sup 2} values for all models, 0.73 (IMRT), 0.38 (DSP), and 0.62 (IMPT), were significant (p < 0.01). Conclusions: Compared with photon IMRT, proton therapy has the potential to significantly reduce whole-brain and -body irradiation in pediatric patients with craniopharyngioma. IMPT is the most conformal method and spares the most normal tissue; however, it is highly sensitive to target volume changes, whereas the DSP method is not.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Clinical evaluation of the iterative metal artifact reduction algorithm for CT simulation in radiotherapy

Purpose: To clinically evaluate an iterative metal artifact reduction (IMAR) algorithm prototype in the radiation oncology clinic setting by testing for accuracy in CT number retrieval, relative dosimetric changes in regions affected by artifacts, and improvements in anatomical and shape conspicuity of corrected images. Methods: A phantom with known material inserts was scanned in the presence/absence of metal with different configurations of placement and sizes. The relative change in CT numbers from the reference data (CT with no metal) was analyzed. The CT studies were also used for dosimetric tests where dose distributions from both photon and proton beams were calculated. Dose differences and gamma analysis were calculated to quantify the relative changes between doses calculated on the different CT studies. Data from eight patients (all different treatment sites) were also used to quantify the differences between dose distributions before and after correction with IMAR, with no reference standard. A ranking experiment was also conducted to analyze the relative confidence of physicians delineating anatomy in the near vicinity of the metal implants. Results: IMAR corrected images proved to accurately retrieve CT numbers in the phantom study, independent of metal insert configuration, size of the metal, and acquisition energy. For plastic water, the mean difference between corrected images and reference images was −1.3 HU across all scenarios (N = 37) with a 90% confidence interval of [−2.4, −0.2] HU. While deviations were relatively higher in images with more metal content, IMAR was able to effectively correct the CT numbers independent of the quantity of metal. Residual errors in the CT numbers as well as some induced by the correction algorithm were found in the IMAR corrected images. However, the dose distributions calculated on IMAR corrected images were closer to the reference data in phantom studies. Relative spatial difference in the dose distributions in the regions affected by the metal artifacts was also observed in patient data. However, in absence of a reference ground truth (CT set without metal inserts), these differences should not be interpreted as improvement/deterioration of the accuracy of calculated dose. With limited data presented, it was observed that proton dosimetry was affected more than photons as expected. Physicians were significantly more confident contouring anatomy in the regions affected by artifacts. While site specific preferences were detected, all indicated that they would consistently use IMAR corrected images. Conclusions: IMAR correction algorithm could be readily implemented in an existing clinical workflow upon commercial release. While residual errors still exist in IMAR corrected images, these images present with better overall conspicuity of the patient/phantom geometry and offer more accurate CT numbers for improved local dosimetry. The variety of different scenarios included herein attest to the utility of the evaluated IMAR for a wide range of radiotherapy clinical scenarios.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

sUAS Support for Mars 2020

The release of airborne radioactive material presents a health risk hazard to many individuals, including emergency responders and the public. Characterizing the unknown radioactive dangers produced during such incidents is essential. An advantage to utilizing unmanned aerial systems in this effort is the reduction of risk to personnel otherwise tasked with characterization, as well as more quickly obtaining data points during cloud immersion. By pairing a continuous air monitor (CAM) and detector with a drone, quantification of unknown material in the plume can be determined, and thus the extent of dose to people in the area can be estimated. A small, low-flow air sampler with a Geiger-Mueller counter may be characterized using experimental measurements of point sources representing a cloud of material and modelled using the Monte Carlo N-Particle Transport Code (MCNP), a software package for simulating nuclear processes, to find the usefulness and advantages of the system for detection of nuclides of concern in various nuclear plume scenarios. The flying time of small-unmanned aircraft systems (sUASs) is limited; thus, the minimum detectable activity and concentration rates possible must be determined over the system’s window of operation. While the activity concentrations corresponding to external and internal doses of concern can be detected with certainty for 90 Sr and 137 Cs in a plume, those corresponding to 238 Pu are more difficult to detect. The central principle of employing the sUAS is that the cockpit does not have an operator onboard the aircraft; therefore, control of the aircraft must take place by other means. With a sUAS, command and control can be separated into three distinct methods: (1) ground control or remote piloting, (2) semi-autonomous control, and (3) autonomous control. The isotope 238 Pu is used in the space industry, providing long-lived heat generation for fuel in outer space (NASA 2014). Due to the inherent risks with rocket launches to get objects into space, monitoring for release of these hazardous substances is a major undertaking. The current means is through employment of environmental CAMs. It is conceivable, however, that drone monitoring for release of 238 Pu in the event of a space launch mishap would give a greater chance of detection of plutonium particulate, because the particulate’s diffusion in air upon settling to the ground would make the probability of collecting a particle on a filter in a CAM very low.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

A Monte Carlo approach to validation of FFF VMAT treatment plans for the TrueBeam linac

Purpose: To commission and benchmark a vendor-supplied (Varian Medical Systems) Monte Carlo phase-space data for the 6 MV flattening filter free (FFF) energy mode on a TrueBeam linear accelerator for the purpose of quality assurance of clinical volumetric modulated arc therapy (VMAT) treatment plans. A method for rendering the phase-space data compatible with BEAMnrc/DOSXYZnrc simulation software package is presented. Methods: Monte Carlo (MC) simulations were performed to benchmark the TrueBeam 6 MV FFF phase space data that have been released by the Varian MC Research team. The simulations to benchmark the phase space data were done in three steps. First, the original phase space which was created on a cylindrical surface was converted into a format that was compatible with BEAMnrc. Second, BEAMnrc was used to create field size specific phase spaces located underneath the jaws. Third, doses were calculated with DOSXYZnrc in a water phantom for fields ranging from 1 Multiplication-Sign 1 to 40 Multiplication-Sign 40 cm{sup 2}. Calculated percent depth doses (PDD), transverse profiles, and output factors were compared with measurements for all the fields simulated. After completing the benchmarking study, three stereotactic body radiotherapy (SBRT) VMAT plans created with the Eclipse treatment planning system (TPS) were calculated with Monte Carlo. Ion chamber and film measurements were also performed on these plans. 3D gamma analysis was used to compare Monte Carlo calculation with TPS calculations and with film measurement. Results: For the benchmarking study, MC calculated and measured values agreed within 1% and 1.5% for PDDs and in-field transverse profiles, respectively, for field sizes >1 Multiplication-Sign 1 cm{sup 2}. Agreements in the 80%-20% penumbra widths were better than 2 mm for all the fields that were compared. With the exception of the 1 Multiplication-Sign 1 cm{sup 2} field, the agreement between measured and calculated output factors was within 1%. It is of note that excellent agreement in output factors for all field sizes including highly asymmetric fields was achieved without accounting for backscatter into the beam monitor chamber. For the SBRT VMAT plans, the agreement between Monte Carlo and ion chamber point dose measurements was within 1%. Excellent agreement between Monte Carlo, treatment planning system and Gafchromic film dose distribution was observed with over 99% of the points in the high dose volume passing the 3%, 3 mm gamma test. Conclusions: The authors have presented a method for making the Varian IAEA compliant 6 MV FFF phase space file of the TrueBeam linac compatible with BEAMnrc/DOSXYZnrc. After benchmarking the modified phase space against measurement, they have demonstrated its potential for use in MC based quality assurance of complex delivery techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

On determining dose rate constants spectroscopically

Purpose: To investigate several aspects of the Chen and Nath spectroscopic method of determining the dose rate constants of {sup 125}I and {sup 103}Pd seeds [Z. Chen and R. Nath, Phys. Med. Biol. 55, 6089-6104 (2010)] including the accuracy of using a line or dual-point source approximation as done in their method, and the accuracy of ignoring the effects of the scattered photons in the spectra. Additionally, the authors investigate the accuracy of the literature's many different spectra for bare, i.e., unencapsulated {sup 125}I and {sup 103}Pd sources. Methods: Spectra generated by 14 {sup 125}I and 6 {sup 103}Pd seeds were calculated in vacuo at 10 cm from the source in a 2.7 Multiplication-Sign 2.7 Multiplication-Sign 0.05 cm{sup 3} voxel using the EGSnrc BrachyDose Monte Carlo code. Calculated spectra used the initial photon spectra recommended by AAPM's TG-43U1 and NCRP (National Council of Radiation Protection and Measurements) Report 58 for the {sup 125}I seeds, or TG-43U1 and NNDC(2000) (National Nuclear Data Center, 2000) for {sup 103}Pd seeds. The emitted spectra were treated as coming from a line or dual-point source in a Monte Carlo simulation to calculate the dose rate constant. The TG-43U1 definition of the dose rate constant was used. These calculations were performed using the full spectrum including scattered photons or using only the main peaks in the spectrum as done experimentally. Statistical uncertainties on the air kerma/history and the dose rate/history were Less-Than-Or-Slanted-Equal-To 0.2%. The dose rate constants were also calculated using Monte Carlo simulations of the full seed model. Results: The ratio of the intensity of the 31 keV line relative to that of the main peak in {sup 125}I spectra is, on average, 6.8% higher when calculated with the NCRP Report 58 initial spectrum vs that calculated with TG-43U1 initial spectrum. The {sup 103}Pd spectra exhibit an average 6.2% decrease in the 22.9 keV line relative to the main peak when calculated with the TG-43U1 rather than the NNDC(2000) initial spectrum. The measured values from three different investigations are in much better agreement with the calculations using the NCRP Report 58 and NNDC(2000) initial spectra with average discrepancies of 0.9% and 1.7% for the {sup 125}I and {sup 103}Pd seeds, respectively. However, there are no differences in the calculated TG-43U1 brachytherapy parameters using either initial spectrum in both cases. Similarly, there were no differences outside the statistical uncertainties of 0.1% or 0.2%, in the average energy, air kerma/history, dose rate/history, and dose rate constant when calculated using either the full photon spectrum or the main-peaks-only spectrum. Conclusions: Our calculated dose rate constants based on using the calculated on-axis spectrum and a line or dual-point source model are in excellent agreement (0.5% on average) with the values of Chen and Nath, verifying the accuracy of their more approximate method of going from the spectrum to the dose rate constant. However, the dose rate constants based on full seed models differ by between +4.6% and -1.5% from those based on the line or dual-point source approximations. These results suggest that the main value of spectroscopic measurements is to verify full Monte Carlo models of the seeds by comparison to the calculated spectra.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Parallel beamlet dose calculation via beamlet contexts in a distributed multi‐GPU framework

Purpose Dose calculation is one of the most computationally intensive, yet essential tasks in the treatment planning process. With the recent interest in automatic beam orientation and arc trajectory optimization techniques, there is a great need for more efficient model‐based dose calculation algorithms that can accommodate hundreds to thousands of beam candidates at once. Foundational work has shown the translation of dose calculation algorithms to graphical processing units ( GPU s), lending to remarkable gains in processing efficiency. But these methods provide parallelization of dose for only a single beamlet, serializing the calculation of multiple beamlets and under‐utilizing the potential of modern GPU s. In this paper, the authors propose a framework enabling parallel computation of many beamlet doses using a novel beamlet context transformation and further embed this approach in a scalable network of multi‐ GPU computational nodes. Methods The proposed context‐based transformation separates beamlet‐local density and TERMA into distinct beamlet contexts that independently provide sufficient data for beamlet dose calculation. Beamlet contexts are arranged in a composite context array with dosimetric isolation, and the context array is subjected to a GPU collapsed‐cone convolution superposition procedure, producing the set of beamlet‐specific dose distributions in a single pass. Dose from each context is converted to a sparse representation for efficient storage and retrieval during treatment plan optimization. The context radius is a new parameter permitting flexibility between the speed and fidelity of the dose calculation process. A distributed manager‐worker architecture is constructed around the context‐based GPU dose calculation approach supporting an arbitrary number of worker nodes and resident GPU s. Phantom experiments were executed to verify the accuracy of the context‐based approach compared to Monte Carlo and a reference CPU ‐ CCCS implementation for single beamlets and broad beams composed by addition of beamlets. Dose for representative 4 π beam sets was calculated in lung and prostate cases to compare its efficiency with that of an existing beamlet‐sequential GPU ‐ CCCS implementation. Code profiling was also performed to evaluate the scalability of the framework across many networked GPU s. Results The dosimetric accuracy of the context‐based method displays <1.35% and 2.35% average error from the existing serialized CPU ‐ CCCS algorithm and Monte Carlo simulation for beamlet‐specific PDD s in water and slab phantoms, respectively. The context‐based method demonstrates substantial speedup of up to two orders of magnitude over the beamlet‐sequential GPU ‐ CCCS method in the tested configurations. The context‐based framework demonstrates near linear scaling in the number of distributed compute nodes and GPU s employed, indicating that it is flexible enough to meet the performance requirements of most users by simply increasing the hardware utilization. Conclusions The context‐based approach demonstrates a new expectation of performance for beamlet‐based dose calculation methods. This approach has been successful in accelerating the dose calculation process for very large‐scale treatment planning problems ‐ such as automatic 4 π IMRT beam orientation and VMAT arc trajectory selection, with hundreds of thousands of beamlets ‐ in clinically feasible timeframes. The flexibility of this framework makes it as a strong candidate for use in a variety of other very large‐scale treatment planning tasks and clinical workflows.

Neph, Ryan↗
DOE OSTI2015

Data consistency conditions for truncated fanbeam and parallel projections

Purpose: In image reconstruction from projections, data consistency conditions (DCCs) are mathematical relationships that express the overlap of information between ideal projections. DCCs have been incorporated in image reconstruction procedures for positron emission tomography, single photon emission computed tomography, and x-ray computed tomography (CT). Building on published fanbeam DCCs for nontruncated projections along a line, the authors recently announced new DCCs that can be applied to truncated parallel projections in classical (two-dimensional) image reconstruction. These DCCs take the form of polynomial expressions for a weighted backprojection of the projections. The purpose of this work was to present the new DCCs for truncated parallel projections, to extend these conditions to truncated fanbeam projections on a circular trajectory, to verify the conditions with numerical examples, and to present a model of how DCCs could be applied with a toy problem in patient motion estimation with truncated projections. Methods: A mathematical derivation of the new parallel DCCs was performed by substituting the underlying imaging equation into the mathematical expression for the weighted backprojection and demonstrating the resulting polynomial form. This DCC result was extended to fanbeam projections by a substitution of parallel to fanbeam variables. Ideal fanbeam projections of a simple mathematical phantom were simulated and the DCCs for these projections were evaluated by fitting polynomials to the weighted backprojection. For the motion estimation problem, a parametrized motion was simulated using a dynamic version of the mathematical phantom, and both noiseless and noisy fanbeam projections were simulated for a full circular trajectory. The fanbeam DCCs were applied to extract the motion parameters, which allowed the motion contamination to be removed from the projections. A reconstruction was performed from the corrected projections. Results: The mathematical derivation revealed the anticipated polynomial behavior. The conversion to fanbeam variables led to a straight-forward weighted fanbeam backprojection which yielded the same function and therefore the same polynomial behavior as occurred in the parallel case. Plots of the numerically calculated DCCs showed polynomial behavior visually indistinguishable from the fitted polynomials. For the motion estimation problem, the motion parameters were satisfactorily recovered and ten times more accurately for the noise-free case. The reconstructed images showed that only a faint trace of the motion blur was still visible after correction from the noisy motion-contaminated projections. Conclusions: New DCCs have been established for fanbeam and parallel projections, and these conditions have been validated using numerical experiments with truncated projections. It has been shown how these DCCs could be applied to extract parameters of unwanted physical effects in tomographic imaging, even with truncated projections.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Correlation between model observer and human observer performance in CT imaging when lesion location is uncertain

Purpose: The purpose of this study was to investigate the correlation between model observer and human observer performance in CT imaging for the task of lesion detection and localization when the lesion location is uncertain.Methods: Two cylindrical rods (3-mm and 5-mm diameters) were placed in a 35 × 26 cm torso-shaped water phantom to simulate lesions with −15 HU contrast at 120 kV. The phantom was scanned 100 times on a 128-slice CT scanner at each of four dose levels (CTDIvol = 5.7, 11.4, 17.1, and 22.8 mGy). Regions of interest (ROIs) around each lesion were extracted to generate images with signal-present, with each ROI containing 128 × 128 pixels. Corresponding ROIs of signal-absent images were generated from images without lesion mimicking rods. The location of the lesion (rod) in each ROI was randomly distributed by moving the ROIs around each lesion. Human observer studies were performed by having three trained observers identify the presence or absence of lesions, indicating the lesion location in each image and scoring confidence for the detection task on a 6-point scale. The same image data were analyzed using a channelized Hotelling model observer (CHO) with Gabor channels. Internal noise was added to the decision variables for the model observer study. Area under the curve (AUC) of ROC and localization ROC (LROC) curves were calculated using a nonparametric approach. The Spearman's rank order correlation between the average performance of the human observers and the model observer performance was calculated for the AUC of both ROC and LROC curves for both the 3- and 5-mm diameter lesions.Results: In both ROC and LROC analyses, AUC values for the model observer agreed well with the average values across the three human observers. The Spearman's rank order correlation values for both ROC and LROC analyses for both the 3- and 5-mm diameter lesions were all 1.0, indicating perfect rank ordering agreement of the figures of merit (AUC) between the average performance of the human observers and the model observer performance.Conclusions: In CT imaging of different sizes of low-contrast lesions (−15 HU), the performance of CHO with Gabor channels was highly correlated with human observer performance for the detection and localization tasks with uncertain lesion location in CT imaging at four clinically relevant dose levels. This suggests the ability of Gabor CHO model observers to meaningfully assess CT image quality for the purpose of optimizing scan protocols and radiation dose levels in detection and localization tasks for low-contrast lesions.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2012

Liver motion during cone beam computed tomography guided stereotactic body radiation therapy

Purpose: Understanding motion characteristics of liver such as, interfractional and intrafractional motion variability, difference in motion within different locations in the organ, and their complex relationship with the breathing cycles are particularly important for image-guided liver SBRT. The purpose of this study was to investigate such motion characteristics based on fiducial markers tracked with the x-ray projections of the CBCT scans, taken immediately prior to the treatments. Methods: Twenty liver SBRT patients were analyzed. Each patient had three fiducial markers (2 Multiplication-Sign 5-mm gold) percutaneously implanted around the gross tumor. The prescription ranged from 2 to 8 fractions per patient. The CBCT projections data for each fraction ({approx}650 projections/scan), for each patient, were analyzed and the 2D positions of the markers were extracted using an in-house algorithm. In total, >55 000 x-ray projections were analyzed from 85 CBCT scans. From the 2D extracted positions, a 3D motion trajectory of the markers was constructed, from each CBCT scans, resulting in left-right (LR), anterior-posterior (AP), and cranio-caudal (CC) location information of the markers with >55 000 data points. The authors then analyzed the interfraction and intrafraction liver motion variability, within different locations in the organ, and as a function of the breathing cycle. The authors also compared the motion characteristics against the planning 4DCT and the RPM Trade-Mark-Sign (Varian Medical Systems, Palo Alto, CA) breathing traces. Variations in the appropriate gating window (defined as the percent of the maximum range at which 50% of the marker positions are contained), between fractions were calculated as well. Results: The range of motion for the 20 patients were 3.0 {+-} 2.0 mm, 5.1 {+-} 3.1 mm, and 17.9 {+-} 5.1 mm in the planning 4DCT, and 2.8 {+-} 1.6 mm, 5.3 {+-} 3.1 mm, and 16.5 {+-} 5.7 mm in the treatment CBCT, for LR, AP, and CC directions, respectively. The range of respiratory period was 3.9 {+-} 0.7 and 4.2 {+-} 0.8 s during the 4DCT simulation and the CBCT scans, respectively. The authors found that breathing-induced AP and CC motions are highly correlated. That is, all markers moved cranially also moved posteriorly and vice versa, irrespective of the location. The LR motion had a more variable relationship with the AP/CC motions, and appeared random with respect to the location. That is, when the markers moved toward cranial-posterior direction, 58% of the markers moved to the patient-right, 22% of the markers moved to the patient-left, and 20% of the markers had minimal/none motion. The absolute difference in the motion magnitude between the markers, in different locations within the liver, had a positive correlation with the absolute distance between the markers (R{sup 2}= 0.69, linear-fit). The interfractional gating window varied significantly for some patients, with the largest having 29.4%-56.4% range between fractions. Conclusions: This study analyzed the liver motion characteristics of 20 patients undergoing SBRT. A large variation in motion was observed, interfractionally and intrafractionally, and that as the distance between the markers increased, the difference in the absolute range of motion also increased. This suggests that marker(s) in closest proximity to the target be used.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

A technique for estimating 4D-CBCT using prior knowledge and limited-angle projections

Purpose: To develop a technique to estimate onboard 4D-CBCT using prior information and limited-angle projections for potential 4D target verification of lung radiotherapy.Methods: Each phase of onboard 4D-CBCT is considered as a deformation from one selected phase (prior volume) of the planning 4D-CT. The deformation field maps (DFMs) are solved using a motion modeling and free-form deformation (MM-FD) technique. In the MM-FD technique, the DFMs are estimated using a motion model which is extracted from planning 4D-CT based on principal component analysis (PCA). The motion model parameters are optimized by matching the digitally reconstructed radiographs of the deformed volumes to the limited-angle onboard projections (data fidelity constraint). Afterward, the estimated DFMs are fine-tuned using a FD model based on data fidelity constraint and deformation energy minimization. The 4D digital extended-cardiac-torso phantom was used to evaluate the MM-FD technique. A lung patient with a 30 mm diameter lesion was simulated with various anatomical and respirational changes from planning 4D-CT to onboard volume, including changes of respiration amplitude, lesion size and lesion average-position, and phase shift between lesion and body respiratory cycle. The lesions were contoured in both the estimated and “ground-truth” onboard 4D-CBCT for comparison. 3D volume percentage-difference (VPD) and center-of-mass shift (COMS) were calculated to evaluate the estimation accuracy of three techniques: MM-FD, MM-only, and FD-only. Different onboard projection acquisition scenarios and projection noise levels were simulated to investigate their effects on the estimation accuracy.Results: For all simulated patient and projection acquisition scenarios, the mean VPD (±S.D.)/COMS (±S.D.) between lesions in prior images and “ground-truth” onboard images were 136.11% (±42.76%)/15.5 mm (±3.9 mm). Using orthogonal-view 15°-each scan angle, the mean VPD/COMS between the lesion in estimated and “ground-truth” onboard images for MM-only, FD-only, and MM-FD techniques were 60.10% (±27.17%)/4.9 mm (±3.0 mm), 96.07% (±31.48%)/12.1 mm (±3.9 mm) and 11.45% (±9.37%)/1.3 mm (±1.3 mm), respectively. For orthogonal-view 30°-each scan angle, the corresponding results were 59.16% (±26.66%)/4.9 mm (±3.0 mm), 75.98% (±27.21%)/9.9 mm (±4.0 mm), and 5.22% (±2.12%)/0.5 mm (±0.4 mm). For single-view scan angles of 3°, 30°, and 60°, the results for MM-FD technique were 32.77% (±17.87%)/3.2 mm (±2.2 mm), 24.57% (±18.18%)/2.9 mm (±2.0 mm), and 10.48% (±9.50%)/1.1 mm (±1.3 mm), respectively. For projection angular-sampling-intervals of 0.6°, 1.2°, and 2.5° with the orthogonal-view 30°-each scan angle, the MM-FD technique generated similar VPD (maximum deviation 2.91%) and COMS (maximum deviation 0.6 mm), while sparser sampling yielded larger VPD/COMS. With equal number of projections, the estimation results using scattered 360° scan angle were slightly better than those using orthogonal-view 30°-each scan angle. The estimation accuracy of MM-FD technique declined as noise level increased.Conclusions: The MM-FD technique substantially improves the estimation accuracy for onboard 4D-CBCT using prior planning 4D-CT and limited-angle projections, compared to the MM-only and FD-only techniques. It can potentially be used for the inter/intrafractional 4D-localization verification.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

A virtual trial framework for quantifying the detectability of masses in breast tomosynthesis projection data

Purpose: Digital breast tomosynthesis (DBT) is a promising breast cancer screening tool that has already begun making inroads into clinical practice. However, there is ongoing debate over how to quantitatively evaluate and optimize these systems, because different definitions of image quality can lead to different optimal design strategies. Powerful and accurate tools are desired to extend our understanding of DBT system optimization and validate published design principles. Methods: The authors developed a virtual trial framework for task-specific DBT assessment that uses digital phantoms, open-source x-ray transport codes, and a projection-space, spatial-domain observer model for quantitative system evaluation. The authors considered evaluation of reconstruction algorithms as a separate problem and focused on the information content in the raw, unfiltered projection images. Specifically, the authors investigated the effects of scan angle and number of angular projections on detectability of a small (3 mm diameter) signal embedded in randomly-varying anatomical backgrounds. Detectability was measured by the area under the receiver-operating characteristic curve (AUC). Experiments were repeated for three test cases where the detectability-limiting factor was anatomical variability, quantum noise, or electronic noise. The authors also juxtaposed the virtual trial framework with other published studies to illustrate its advantages and disadvantages. Results: The large number of variables in a virtual DBT study make it difficult to directly compare different authors' results, so each result must be interpreted within the context of the specific virtual trial framework. The following results apply to 25% density phantoms with 5.15 cm compressed thickness and 500 {mu}m{sup 3} voxels (larger 500 {mu}m{sup 2} detector pixels were used to avoid voxel-edge artifacts): 1. For raw, unfiltered projection images in the anatomical-variability-limited regime, AUC appeared to remain constant or increase slightly with scan angle. 2. In the same regime, when the authors fixed the scan angle, AUC increased asymptotically with the number of projections. The threshold number of projections for asymptotic AUC performance depended on the scan angle. In the quantum- and electronic-noise dominant regimes, AUC behaviors as a function of scan angle and number of projections sometimes differed from the anatomy-limited regime. For example, with a fixed scan angle, AUC generally decreased with the number of projections in the electronic-noise dominant regime. These results are intended to demonstrate the capabilities of the virtual trial framework, not to be used as optimization rules for DBT. Conclusions: The authors have demonstrated a novel simulation framework and tools for evaluating DBT systems in an objective, task-specific manner. This framework facilitates further investigation of image quality tradeoffs in DBT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Dosimetric and deformation effects of image-guided interventions during stereotactic body radiation therapy of the prostate using an endorectal balloon

Purpose: During stereotactic body radiation therapy (SBRT) for the treatment of prostate cancer, an inflatable endorectal balloon (ERB) may be used to reduce motion of the target and reduce the dose to the posterior rectal wall. This work assessed the dosimetric impact of manual interventions on ERB position in patients receiving prostate SBRT and investigated the impact of ERB interventions on prostate shape. Methods: The data of seven consecutive patients receiving SBRT for the treatment of clinical stage T1cN0M0 prostate cancer enrolled in a multi-institutional, IRB-approved trial were analyzed. The SBRT dose was 50 Gy in five fractions to a planning target volume (PTV) that included the prostate (implanted with three fiducial markers) with a 3-5 mm margin. All plans were based on simulation images that included an ERB inflated with 60 cm{sup 3} of air. Daily kilovoltage cone-beam computed tomography (CBCT) imaging was performed to localize the PTV, and an automated fusion with the planning images yielded displacements required for PTV relocalization. When the ERB volume and/or position were judged to yield inaccurate repositioning, manual adjustment (ERB reinflation and/or repositioning) was performed. Based on all 59 CBCT image sets acquired, a deformable registration algorithm was used to determine the dose received by, displacement of, and deformation of the prostate, bladder (BLA), and anterior rectal wall (ARW). This dose tracking methodology was applied to images taken before and after manual adjustment of the ERB (intervention), and the delivered dose was compared to that which would have been delivered in the absence of intervention. Results: Interventions occurred in 24 out of 35 (69%) of the treated fractions. The direct effect of these interventions was an increase in the prostate radiation dose that included 95% of the PTV (D95) from 9.6 {+-} 1.0 to 10.0 {+-} 0.2 Gy (p = 0.06) and an increase in prostate coverage from 94.0% {+-} 8.5% to 97.8% {+-} 1.9% (p = 0.03). Additionally, ERB interventions reduced prostate deformation in the anterior-posterior (AP) direction, reduced errors in the sagittal rotation of the prostate, and increased the similarity in shape of the prostate to the radiotherapy plan (increased Dice coefficient from 0.76 {+-} 0.06 to 0.80 {+-} 0.04, p = 0.01). Postintervention decreases in prostate volume receiving less than the prescribed dose and decreases in the voxel-wise displacement of the prostate, bladder, and anterior rectal wall were observed, which resulted in improved dose-volume histogram (DVH) characteristics. Conclusions: Image-guided interventions in ERB volume and/or position during prostate SBRT were necessary to ensure the delivery of the dose distribution as planned. ERB interventions resulted in reductions in prostate deformations that would have prevented accurate localization of patient anatomy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

The Benefits of Including Clinical Factors in Rectal Normal Tissue Complication Probability Modeling After Radiotherapy for Prostate Cancer

Purpose: To study the impact of clinical predisposing factors on rectal normal tissue complication probability modeling using the updated results of the Dutch prostate dose-escalation trial. Methods and Materials: Toxicity data of 512 patients (conformally treated to 68 Gy [n = 284] and 78 Gy [n = 228]) with complete follow-up at 3 years after radiotherapy were studied. Scored end points were rectal bleeding, high stool frequency, and fecal incontinence. Two traditional dose-based models (Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) and a logistic model were fitted using a maximum likelihood approach. Furthermore, these model fits were improved by including the most significant clinical factors. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminating ability of all fits. Results: Including clinical factors significantly increased the predictive power of the models for all end points. In the optimal LKB, RS, and logistic models for rectal bleeding and fecal incontinence, the first significant (p = 0.011-0.013) clinical factor was 'previous abdominal surgery.' As second significant (p = 0.012-0.016) factor, 'cardiac history' was included in all three rectal bleeding fits, whereas including 'diabetes' was significant (p = 0.039-0.048) in fecal incontinence modeling but only in the LKB and logistic models. High stool frequency fits only benefitted significantly (p = 0.003-0.006) from the inclusion of the baseline toxicity score. For all models rectal bleeding fits had the highest AUC (0.77) where it was 0.63 and 0.68 for high stool frequency and fecal incontinence, respectively. LKB and logistic model fits resulted in similar values for the volume parameter. The steepness parameter was somewhat higher in the logistic model, also resulting in a slightly lower D{sub 50}. Anal wall DVHs were used for fecal incontinence, whereas anorectal wall dose best described the other two endpoints. Conclusions: Comparable prediction models were obtained with LKB, RS, and logistic NTCP models. Including clinical factors improved the predictive power of all models significantly.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2011

Dosimetric impact of image artifact from a wide-bore CT scanner in radiotherapy treatment planning

Purpose: Traditional computed tomography (CT) units provide a maximum scan field-of-view (sFOV) diameter of 50 cm and a limited bore size, which cannot accommodate a large patient habitus or an extended simulation setup in radiation therapy (RT). Wide-bore CT scanners with increased bore size were developed to address these needs. Some scanners have the capacity to reconstruct the CT images at an extended FOV (eFOV), through data interpolation or extrapolation, using projection data acquired with a conventional sFOV. Objects that extend past the sFOV for eFOV reconstruction may generate image artifacts resulting from truncated projection data; this may distort CT numbers and structure contours in the region beyond the sFOV. The purpose of this study was to evaluate the dosimetric impact of image artifacts from eFOV reconstruction with a wide-bore CT scanner in radiotherapy (RT) treatment planning. Methods: Testing phantoms (i.e., a mini CT phantom with equivalent tissue inserts, a set of CT normal phantoms and anthropomorphic phantoms of the thorax and the pelvis) were used to evaluate eFOV artifacts. Reference baseline images of these phantoms were acquired with the phantom centrally positioned within the sFOV. For comparison, the phantoms were then shifted laterally and scanned partially outside the sFOV, but still within the eFOV. Treatment plans were generated for the thoracic and pelvic anthropomorphic phantoms utilizing the Eclipse treatment planning system (TPS) to study the potential effects of eFOV artifacts on dose calculations. All dose calculations of baseline and test treatment plans were carried out using the same MU. Results: Results show that both body contour and CT numbers are altered by image artifacts in eFOV reconstruction. CT number distortions of up to -356 HU for bone tissue and up to 323 HU for lung tissue were observed in the mini CT phantom. Results from the large body normal phantom, which is close to a clinical patient size, show average CT number changes of up to -49 HU. Wider distribution (i.e., standard deviation) of the HU values was seen when the phantom was placed at more than 2.8 cm beyond the 50 cm sFOV. Anthropomorphic phantom studies with several standard beam configurations show that body contour distortion causes tumor dose calculation reduction of 3.0 and 1.9% for 6 and 23 MV x-rays, respectively, when not accounting for tissue heterogeneities during dose computation. When heterogeneity correction is used in planning, the competing effects of the body contour distortion and the CT number distortion cause a smaller error in tumor dose calculation. Less than 0.9% error in calculated dose was observed in volumetric modulated arc therapy (VMAT) treatment plans. Conclusions: The image artifacts from eFOV reconstruction alter the CT numbers and body contours of the imaged objects, which has the potential to produce inaccuracies in dose calculations during radiotherapy treatment planning. The radiation therapy team should be aware of these image artifacts and their effects on target dose calculations during CT simulation as well as treatment planning.

61 RADIATION PROTECTION AND DOSIMETRY↗