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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Mortality and Rates of Secondary Intervention After EVAR in an Unselected Population: Influence of Simple Clinical Categories and Implications for Surveillance

IntroductionPost-EVAR surveillance has a major impact upon patients, carers and healthcare resources. We hypothesised that elective indication, on-IFU anatomy, use of a modern device or normal first CTA, or a combination of these categories, might predict a rate of secondary intervention low enough to alter current surveillance protocols.MethodsPatients undergoing EVAR in our institution between 01.05.2007 and 28.02.2013 were assessed. Data on indication (elective, emergency), anatomy relative to IFU, device, first month CTA result, secondary intervention and mortality were obtained. Kaplan–Meier charts of mortality and freedom from secondary intervention were produced. Statistical analysis was by log-rank test and Cox proportional hazard modelling.Results234 patients underwent EVAR (188 elective, 208 on-IFU). Most implants were Endurant (106) or Talent (98). 151 patients had a normal first CTA. By median follow-up of 38.6 months, 39 patients underwent secondary intervention. A normal first CTA and elective indication were significantly associated with reduced risk of secondary intervention (p < 0.001 and p = 0.042 respectively), but device type and placement on- or off-IFU were not. Elective placement with a normal first CTA was 93 % predictive of freedom from secondary intervention by 32 months post-EVAR. Of nine patients undergoing secondary intervention in this group, eight presented symptomatically.DiscussionIn optimal procedural circumstances with normal post-procedural imaging, only 7 % of patients undergoing EVAR require secondary intervention, a minority of which is driven by surveillance. These data support a change to surveillance more tailored to the individual patient, and highlight the need for further qualitative and quantitative research.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

A Technique for Generating Volumetric Cine-Magnetic Resonance Imaging

Purpose: The purpose of this study was to develop a techique to generate on-board volumetric cine-magnetic resonance imaging (VC-MRI) using patient prior images, motion modeling, and on-board 2-dimensional cine MRI. Methods and Materials: One phase of a 4-dimensional MRI acquired during patient simulation is used as patient prior images. Three major respiratory deformation patterns of the patient are extracted from 4-dimensional MRI based on principal-component analysis. The on-board VC-MRI at any instant is considered as a deformation of the prior MRI. The deformation field is represented as a linear combination of the 3 major deformation patterns. The coefficients of the deformation patterns are solved by the data fidelity constraint using the acquired on-board single 2-dimensional cine MRI. The method was evaluated using both digital extended-cardiac torso (XCAT) simulation of lung cancer patients and MRI data from 4 real liver cancer patients. The accuracy of the estimated VC-MRI was quantitatively evaluated using volume-percent-difference (VPD), center-of-mass-shift (COMS), and target tracking errors. Effects of acquisition orientation, region-of-interest (ROI) selection, patient breathing pattern change, and noise on the estimation accuracy were also evaluated. Results: Image subtraction of ground-truth with estimated on-board VC-MRI shows fewer differences than image subtraction of ground-truth with prior image. Agreement between normalized profiles in the estimated and ground-truth VC-MRI was achieved with less than 6% error for both XCAT and patient data. Among all XCAT scenarios, the VPD between ground-truth and estimated lesion volumes was, on average, 8.43 ± 1.52% and the COMS was, on average, 0.93 ± 0.58 mm across all time steps for estimation based on the ROI region in the sagittal cine images. Matching to ROI in the sagittal view achieved better accuracy when there was substantial breathing pattern change. The technique was robust against noise levels up to SNR = 20. For patient data, average tracking errors were less than 2 mm in all directions for all patients. Conclusions: Preliminary studies demonstrated the feasibility of generating real-time VC-MRI for on-board localization of moving targets in radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

UAVs for Radiological Monitoring: Determining Ideal Operational Parameters From GEANT4 Simulations - 18025

Owing in no small part to the enormous advances in radiation detector technology (size, sensitivity and spectral-resolution), there has been an increased drive and requirement to accurately map both the spatial extent and magnitude of radiological contamination at the greatest possible spatial resolutions. To undertake this, a range of different methods have been devised and include the use of cars and human, but also planes (and more recently) unmanned aerial vehicles (UAVs). However, critical to the remote sensing using such UAVs in contrast to ground-based sensing, is (i) the selection of the ideal operational parameters to attain the best on-ground resolution in addition to, (ii) understanding the correct normalisation procedures and other influences on results that surveys at these reduced altitudes might present. Resulting from earlier works, through employing combined modelling and experimental data, the optimal height for a UAV survey using the more realistic 'area' radioactive source term (opposed to an infinitely-small 'point-source') is determined to be approximately 5 m - suitably maximizing cross detector counts. At greater altitudes than this, the influence of variations in neighboring topology / topography and nearby structures are observed to be negligible. However, at this and further-reduced altitudes (where optimal count-rates exists), small height-related variations are observed to result, and impact considerably on the complexity of the data normalisation. Whilst not occurring as a tool to entirely replace ground-based surveys, UAV systems are able to perform in challenging or dangerous environments, inadvisable or problematic to send humans. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2012

DHS Summary Report -- Robert Weldon

This summer I worked on benchmarking the Lawrence Livermore National Laboratory fission multiplicity capability used in the Monte Carlo particle transport code MCNPX. This work involved running simulations and then comparing the simulation results with experimental experiments. Outlined in this paper is a brief description of the work completed this summer, skills and knowledge gained, and how the internship has impacted my planning for the future. Neutron multiplicity counting is a neutron detection technique that leverages the multiplicity emissions of neutrons from fission to identify various actinides in a lump of material. The identification of individual actinides in lumps of material crossing our boarders, especially U-235 and Pu-239, is a key component for maintaining the safety of the country from nuclear threats. Several multiplicity emission options from spontaneous and induced fission already existed in MCNPX 2.4.0. These options can be accessed through use of the 6th entry on the PHYS:N card. Lawrence Livermore National Laboratory (LLNL) developed a physics model for the simulation of neutron and gamma ray emission from fission and photofission that was included in MCNPX 2.7.B as an undocumented feature and then was documented in MCNPX 2.7.C. The LLNL multiplicity capability provided a different means for MCNPX to simulate neutron and gamma-ray distributions for neutron induced, spontaneous and photonuclear fission reactions. The original testing on the model for implementation into MCNPX was conducted by Gregg McKinney and John Hendricks. The model is an encapsulation of measured data of neutron multiplicity distributions from Gwin, Spencer, and Ingle, along with the data from Zucker and Holden. One of the founding principles of MCNPX was that it would have several redundant capabilities, providing the means of testing and including various physics packages. Though several multiplicity sampling methodologies already existed within MCNPX, the LLNL fission multiplicity was included to provide a separate capability for computing multiplicity as well as including several new features not already included in MCNPX. These new features include: (1) prompt gamma emission/multiplicity from neutron-induced fission; (2) neutron multiplicity and gamma emission/multiplicity from photofission; and (3) an option to enforce energy correlation for gamma neutron multiplicity emission. These new capabilities allow correlated signal detection for identifying presence of special nuclear material (SNM). Therefore, these new capabilities help meet the missions of the Domestic Nuclear Detection Office (DNDO), which is tasked with developing nuclear detection strategies for identifying potential radiological and nuclear threats, by providing new simulation capability for detection strategies that leverage the new available physics in the LLNL multiplicity capability. Two types of tests were accomplished this summer to test the default LLNL neutron multiplicity capability: neutron-induced fission tests and spontaneous fission tests. Both cases set the 6th entry on the PHYS:N card to 5 (i.e. use LLNL multiplicity). The neutron-induced fission tests utilized a simple 0.001 cm radius sphere where 0.0253 eV neutrons were released at the sphere center. Neutrons were forced to immediately collide in the sphere and release all progeny from the sphere, without further collision, using the LCA card, LCA 7j -2 (therefore density and size of the sphere were irrelevant). Enough particles were run to ensure that the average error of any specific multiplicity did not exceed 0.36%. Neutron-induced fission multiplicities were computed for U-233, U-235, Pu-239, and Pu-241. The spontaneous fission tests also used the same spherical geometry, except: (1) the LCA card was removed; (2) the density of the sphere was set to 0.001 g/cm3; and (3) instead of emitting a thermal neutron, the PAR keyword was set to PAR=SF. The purpose of the small density was to ensure that the spontaneous fission neutrons would not further interact and induce fissions (i.e. the mean free path greatly exceeded the size of the sphere). Enough particles were run to ensure that the average error of any specific spontaneous multiplicity did not exceed 0.23%. Spontaneous fission multiplicities were computed for U-238, Pu-238, Pu-240, Pu-242, Cm-242, and Cm-244. All of the computed results were compared against experimental results compiled by Holden at Brookhaven National Laboratory.

42 ENGINEERING↗
DOE OSTI2014

Alpha image reconstruction (AIR): A new iterative CT image reconstruction approach using voxel-wise alpha blending

Purpose: Iterative image reconstruction gains more and more interest in clinical routine, as it promises to reduce image noise (and thereby patient dose), to reduce artifacts, or to improve spatial resolution. Among vendors and researchers, however, there is no consensus of how to best achieve these aims. The general approach is to incorporatea priori knowledge into iterative image reconstruction, for example, by adding additional constraints to the cost function, which penalize variations between neighboring voxels. However, this approach to regularization in general poses a resolution noise trade-off because the stronger the regularization, and thus the noise reduction, the stronger the loss of spatial resolution and thus loss of anatomical detail. The authors propose a method which tries to improve this trade-off. The proposed reconstruction algorithm is called alpha image reconstruction (AIR). One starts with generating basis images, which emphasize certain desired image properties, like high resolution or low noise. The AIR algorithm reconstructs voxel-specific weighting coefficients that are applied to combine the basis images. By combining the desired properties of each basis image, one can generate an image with lower noise and maintained high contrast resolution thus improving the resolution noise trade-off. Methods: All simulations and reconstructions are performed in native fan-beam geometry. A water phantom with resolution bar patterns and low contrast disks is simulated. A filtered backprojection (FBP) reconstruction with a Ram-Lak kernel is used as a reference reconstruction. The results of AIR are compared against the FBP results and against a penalized weighted least squares reconstruction which uses total variation as regularization. The simulations are based on the geometry of the Siemens Somatom Definition Flash scanner. To quantitatively assess image quality, the authors analyze line profiles through resolution patterns to define a contrast factor for contrast-resolution plots. Furthermore, the authors calculate the contrast-to-noise ratio with the low contrast disks and the authors compare the agreement of the reconstructions with the ground truth by calculating the normalized cross-correlation and the root-mean-square deviation. To evaluate the clinical performance of the proposed method, the authors reconstruct patient data acquired with a Somatom Definition Flash dual source CT scanner (Siemens Healthcare, Forchheim, Germany). Results: The results of the simulation study show that among the compared algorithms AIR achieves the highest resolution and the highest agreement with the ground truth. Compared to the reference FBP reconstruction AIR is able to reduce the relative pixel noise by up to 50% and at the same time achieve a higher resolution by maintaining the edge information from the basis images. These results can be confirmed with the patient data. Conclusions: To evaluate the AIR algorithm simulated and measured patient data of a state-of-the-art clinical CT system were processed. It is shown, that generating CT images through the reconstruction of weighting coefficients has the potential to improve the resolution noise trade-off and thus to improve the dose usage in clinical CT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Multienergy CT acquisition and reconstruction with a stepped tube potential scan

Purpose: Based on an energy-dependent property of matter, one may obtain a pseudomonochromatic attenuation map, a material composition image, an electron-density distribution, and an atomic number image using a dual- or multienergy computed tomography (CT) scan. Dual- and multienergy CT scans broaden the potential of x-ray CT imaging. The development of such systems is very useful in both medical and industrial investigations. In this paper, the authors propose a new dual- and multienergy CT system design (segmental multienergy CT, SegMECT) using an innovative scanning scheme that is conveniently implemented on a conventional single-energy CT system. The two-step-energy dual-energy CT can be regarded as a special case of SegMECT. A special reconstruction method is proposed to support SegMECT. Methods: In their SegMECT, a circular trajectory in a CT scan is angularly divided into several arcs. The x-ray source is set to a different tube voltage for each arc of the trajectory. Thus, the authors only need to make a few step changes to the x-ray energy during the scan to complete a multienergy data acquisition. With such a data set, the image reconstruction might suffer from severe limited-angle artifacts if using conventional reconstruction methods. To solve the problem, they present a new prior-image-based reconstruction technique using a total variance norm of a quotient image constraint. On the one hand, the prior extracts structural information from all of the projection data. On the other hand, the effect from a possibly imprecise intensity level of the prior can be mitigated by minimizing the total variance of a quotient image. Results: The authors present a new scheme for a SegMECT configuration and establish a reconstruction method for such a system. Both numerical simulation and a practical phantom experiment are conducted to validate the proposed reconstruction method and the effectiveness of the system design. The results demonstrate that the proposed SegMECT can provide both attenuation images and material decomposition images of reasonable image quality. Compared to existing methods, the new system configuration demonstrates advantages in simplicity of implementation, system cost, and dose control. Conclusions: This proposed SegMECT imaging approach has great potential for practical applications. It can be readily realized on a conventional CT system.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

The Relationship Between Local Recurrence and Radiotherapy Treatment Volume for Soft Tissue Sarcomas Treated With External Beam Radiotherapy and Function Preservation Surgery

Purpose: To examine the geometric relationship between local recurrence (LR) and external beam radiotherapy (RT) volumes for soft-tissue sarcoma (STS) patients treated with function-preserving surgery and RT. Methods and Materials: Sixty of 768 (7.8%) STS patients treated with combined therapy within our institution from 1990 through 2006 developed an LR. Thirty-two received preoperative RT, 16 postoperative RT, and 12 preoperative RT plus a postoperative boost. Treatment records, RT simulation images, and diagnostic MRI/CT data sets of the original and LR disease were retrospectively compared. For LR location analysis, three RT target volumes were defined according to the International Commission on Radiation Units and Measurements 29 as follows: (1) the gross tumor or operative bed; (2) the treatment volume (TV) extending 5 cm longitudinally beyond the tumor or operative bed unless protected by intact barriers to spread and at least 1-2 cm axially (the TV was enclosed by the isodose curve representing the prescribed target absorbed dose [TAD] and accounted for target/patient setup uncertainty and beam characteristics), and (3) the irradiated volume (IRV) that received at least 50% of the TAD, including the TV. LRs were categorized as developing in field within the TV, marginal (on the edge of the IRV), and out of field (occurring outside of the IRV). Results: Forty-nine tumors relapsed in field (6.4% overall). Nine were out of field (1.1% overall), and 2 were marginal (0.3% overall). Conclusions: The majority of STS tumors recur in field, indicating that the incidence of LR may be affected more by differences in biologic and molecular characteristics rather than aberrations in RT dose or target volume coverage. In contrast, only two patients relapsed at the IRV boundary, suggesting that the risk of a marginal relapse is low when the TV is appropriately defined. These data support the accurate delivery of optimal RT volumes in the most precise way using advanced technology and image guidance.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

RADAI: A Large-Scale Realistic Dataset for Radiation Detection Algorithm Development

Open, realistic datasets are essential for developing and benchmarking radiation detection algorithms, yet they remain scarce. The Radiological Anomaly Detection and Identification (RADAI) project was develop to create datasets that meet the training and testing needs for sophisticated radiation detection algorithms. The RADAI dataset is a large-scale synthetic resource that integrates high-fidelity Monte Carlo simulations with realistic urban scenarios to capture both background variability and source signatures. RADAI models construction-material NORM, people and vehicles, urban clutter, and dynamic environmental effects such as cosmic-ray and rain-induced transients, and they provide list-mode detector data with motion and response modeling suitable for algorithm training and evaluation. The RADAI project resulted in three publicly-released complementary datasets together with an online scoring portal for standardized performance assessment and an open software toolkit that supports data access, augmentation, model development, and evaluation. These resources enable reproducible comparisons across methods and promote rigorous studies at the scale required by contemporary machine learning. By grounding algorithm development in realistic, well-documented conditions, RADAI supports progress toward more robust detection, identification, and localization in complex urban environments.

Ghawaly, James M. [Division of Computer Science an↗
DOE OSTI2024

Evaluating Machine Learning-Based MRI Reconstruction Using Digital Image Quality Phantoms

Quantitative and objective evaluation tools are essential for assessing the performance of machine learning (ML)-based magnetic resonance imaging (MRI) reconstruction methods. However, the commonly used fidelity metrics, such as mean squared error (MSE), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR), often fail to capture fundamental and clinically relevant MR image quality aspects. To address this, we propose evaluation of ML-based MRI reconstruction using digital image quality phantoms and automated evaluation methods. Our phantoms are based upon the American College of Radiology (ACR) large physical phantom but created in k-space to simulate their MR images, and they can vary in object size, signal-to-noise ratio, resolution, and image contrast. Our evaluation pipeline incorporates evaluation metrics of geometric accuracy, intensity uniformity, percentage ghosting, sharpness, signal-to-noise ratio, resolution, and low-contrast detectability. We demonstrate the utility of our proposed pipeline by assessing an example ML-based reconstruction model across various training and testing scenarios. The performance results indicate that training data acquired with a lower undersampling factor and coils of larger anatomical coverage yield a better performing model. The comprehensive and standardized pipeline introduced in this study can help to facilitate a better understanding of the performance and guide future development and advancement of ML-based reconstruction algorithms.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Development of computational small animal models and their applications in preclinical imaging and therapy research

The development of multimodality preclinical imaging techniques and the rapid growth of realistic computer simulation tools have promoted the construction and application of computational laboratory animal models in preclinical research. Since the early 1990s, over 120 realistic computational animal models have been reported in the literature and used as surrogates to characterize the anatomy of actual animals for the simulation of preclinical studies involving the use of bioluminescence tomography, fluorescence molecular tomography, positron emission tomography, single-photon emission computed tomography, microcomputed tomography, magnetic resonance imaging, and optical imaging. Other applications include electromagnetic field simulation, ionizing and nonionizing radiation dosimetry, and the development and evaluation of new methodologies for multimodality image coregistration, segmentation, and reconstruction of small animal images. This paper provides a comprehensive review of the history and fundamental technologies used for the development of computational small animal models with a particular focus on their application in preclinical imaging as well as nonionizing and ionizing radiation dosimetry calculations. An overview of the overall process involved in the design of these models, including the fundamental elements used for the construction of different types of computational models, the identification of original anatomical data, the simulation tools used for solving various computational problems, and the applications of computational animal models in preclinical research. The authors also analyze the characteristics of categories of computational models (stylized, voxel-based, and boundary representation) and discuss the technical challenges faced at the present time as well as research needs in the future.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2013

Low dose tomographic fluoroscopy: 4D intervention guidance with running prior

Purpose: Today's standard imaging technique in interventional radiology is the single- or biplane x-ray fluoroscopy which delivers 2D projection images as a function of time (2D+T). This state-of-the-art technology, however, suffers from its projective nature and is limited by the superposition of the patient's anatomy. Temporally resolved tomographic volumes (3D+T) would significantly improve the visualization of complex structures. A continuous tomographic data acquisition, if carried out with today's technology, would yield an excessive patient dose. Recently the authors proposed a method that enables tomographic fluoroscopy at the same dose level as projective fluoroscopy which means that if scanning time of an intervention guided by projective fluoroscopy is the same as that of an intervention guided by tomographic fluoroscopy, almost the same dose is administered to the patient. The purpose of this work is to extend authors' previous work and allow for patient motion during the intervention.Methods: The authors propose the running prior technique for adaptation of a prior image. This adaptation is realized by a combination of registration and projection replacement. In a first step the prior is deformed to the current position via affine and deformable registration. Then the information from outdated projections is replaced by newly acquired projections using forward and backprojection steps. The thus adapted volume is the running prior. The proposed method is validated by simulated as well as measured data. To investigate motion during intervention a moving head phantom was simulated. Real in vivo data of a pig are acquired by a prototype CT system consisting of a flat detector and a continuously rotating clinical gantry.Results: With the running prior technique it is possible to correct for motion without additional dose. For an application in intervention guidance both steps of the running prior technique, registration and replacement, are necessary. Reconstructed volumes based on the running prior show high image quality without introducing new artifacts and the interventional materials are displayed at the correct position.Conclusions: The running prior improves the robustness of low dose 3D+T intervention guidance toward intended or unintended patient motion.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

CONRAD—A software framework for cone-beam imaging in radiology

Purpose: In the community of x-ray imaging, there is a multitude of tools and applications that are used in scientific practice. Many of these tools are proprietary and can only be used within a certain lab. Often the same algorithm is implemented multiple times by different groups in order to enable comparison. In an effort to tackle this problem, the authors created CONRAD, a software framework that provides many of the tools that are required to simulate basic processes in x-ray imaging and perform image reconstruction with consideration of nonlinear physical effects.Methods: CONRAD is a Java-based state-of-the-art software platform with extensive documentation. It is based on platform-independent technologies. Special libraries offer access to hardware acceleration such as OpenCL. There is an easy-to-use interface for parallel processing. The software package includes different simulation tools that are able to generate up to 4D projection and volume data and respective vector motion fields. Well known reconstruction algorithms such as FBP, DBP, and ART are included. All algorithms in the package are referenced to a scientific source.Results: A total of 13 different phantoms and 30 processing steps have already been integrated into the platform at the time of writing. The platform comprises 74.000 nonblank lines of code out of which 19% are used for documentation. The software package is available for download at http://conrad.stanford.edu. To demonstrate the use of the package, the authors reconstructed images from two different scanners, a table top system and a clinical C-arm system. Runtimes were evaluated using the RabbitCT platform and demonstrate state-of-the-art runtimes with 2.5 s for the 256 problem size and 12.4 s for the 512 problem size.Conclusions: As a common software framework, CONRAD enables the medical physics community to share algorithms and develop new ideas. In particular this offers new opportunities for scientific collaboration and quantitative performance comparison between the methods of different groups.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Modeling the Risk of Radiation-Induced Acute Esophagitis for Combined Washington University and RTOG Trial 93-11 Lung Cancer Patients

Purpose: To construct a maximally predictive model of the risk of severe acute esophagitis (AE) for patients who receive definitive radiation therapy (RT) for non-small-cell lung cancer. Methods and Materials: The dataset includes Washington University and RTOG 93-11 clinical trial data (events/patients: 120/374, WUSTL = 101/237, RTOG9311 = 19/137). Statistical model building was performed based on dosimetric and clinical parameters (patient age, sex, weight loss, pretreatment chemotherapy, concurrent chemotherapy, fraction size). A wide range of dose-volume parameters were extracted from dearchived treatment plans, including Dx, Vx, MOHx (mean of hottest x% volume), MOCx (mean of coldest x% volume), and gEUD (generalized equivalent uniform dose) values. Results: The most significant single parameters for predicting acute esophagitis (RTOG Grade 2 or greater) were MOH85, mean esophagus dose (MED), and V30. A superior-inferior weighted dose-center position was derived but not found to be significant. Fraction size was found to be significant on univariate logistic analysis (Spearman R = 0.421, p < 0.00001) but not multivariate logistic modeling. Cross-validation model building was used to determine that an optimal model size needed only two parameters (MOH85 and concurrent chemotherapy, robustly selected on bootstrap model-rebuilding). Mean esophagus dose (MED) is preferred instead of MOH85, as it gives nearly the same statistical performance and is easier to compute. AE risk is given as a logistic function of (0.0688 Asterisk-Operator MED+1.50 Asterisk-Operator ConChemo-3.13), where MED is in Gy and ConChemo is either 1 (yes) if concurrent chemotherapy was given, or 0 (no). This model correlates to the observed risk of AE with a Spearman coefficient of 0.629 (p < 0.000001). Conclusions: Multivariate statistical model building with cross-validation suggests that a two-variable logistic model based on mean dose and the use of concurrent chemotherapy robustly predicts acute esophagitis risk in combined-data WUSTL and RTOG 93-11 trial datasets.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Induced Radioactivity in Lead Shielding at the National Synchrotron Light Source

The National Synchrotron Light Source (NSLS) at Brookhaven National Laboratory was shut down in September 2014. Lead bricks used as radiological shadow shielding within the accelerator were exposed to stray radiation fields during normal operations. The FLUKA code, a fully integrated Monte Carlo simulation package for the interaction and transport of particles and nuclei in matter, was used to estimate induced radioactivity in this shielding and stainless steel beam pipe from known beam losses. The FLUKA output was processed using MICROSHIELD® to estimate on-contact exposure rates with individually exposed bricks to help design and optimize the radiological survey process. This entire process can be modeled using FLUKA, but use of MICROSHIELD® as a secondary method was chosen because of the project’s resource constraints. Due to the compressed schedule and lack of shielding configuration data, simple FLUKA models were developed in this paper. FLUKA activity estimates for stainless steel were compared with sampling data to validate results, which show that simple FLUKA models and irradiation geometries can be used to predict radioactivity inventories accurately in exposed materials. During decommissioning 0.1% of the lead bricks were found to have measurable levels of induced radioactivity. Finally, post-processing with MICROSHIELD® provides an acceptable secondary method of estimating residual exposure rates.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2014

A novel adaptive discrete cosine transform-domain filter for gap-inpainting of high resolution PET scanners

Purpose: Several positron emission tomography (PET) scanners with special detector block arrangements have been developed in recent years to improve the resolution of PET images. However, the discontinuous detector blocks cause gaps in the sinogram. This study proposes an adaptive discrete cosine transform-based (aDCT) filter for gap-inpainting. Methods: The gap-corrupted sinogram was morphologically closed and subsequently converted to the DCT domain. A certain number of the largest coefficients in the DCT spectrum were identified to determine the low-frequency preservation region. The weighting factors for the remaining coefficients were determined by an exponential weighting function. The aDCT filter was constructed and applied to two digital phantoms and a simulated phantom introduced with various levels of noise. Results: For the Shepp-Logan head phantom, the aDCT filter filled the gaps effectively. For the Jaszczak phantom, no secondary artifacts were induced after aDCT filtering. The percent mean square error and mean structure similarity of the aDCT filter were superior to those of the DCT2 filter at all noise levels. For the simulated striatal dopamine innervation study, the aDCT filter recovered the shape of the striatum and restored the striatum to reference activity ratios to the ideal value. Conclusions: The proposed aDCT filter can recover the missing gap data in the sinogram and improve the image quality and quantitative accuracy of PET images.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

SU-D-209-05: Sensitivity of the Diagnostic Radiological Index of Protection (DRIP) to Procedural Factors in Fluoroscopy

Purpose: To evaluate the sensitivity of the Diagnostic Radiological Index of Protection (DRIP) to procedural factors in fluoroscopy in an effort to determine an appropriate set of scatter-mimicking primary beams (SMPB) to be used in measuring the DRIP. Methods: A series of clinical and factorial Monte Carlo simulations were conducted to determine the shape of the scattered X-ray spectra incident on the operator in different clinical fluoroscopy scenarios. Two clinical evaluations studied the sensitivity of the scattered spectrum to gantry angle and patient size while technical factors were varied according to measured automatic dose rate control (ADRC) data. Factorial evaluations studied the sensitivity of the scattered spectrum to gantry angle, field of view, patient size and beam quality for constant technical factors. Average energy was the figure of merit used to condense fluence in each energy bin to a single numerical index. Results: Beam quality had the strongest influence on the scattered spectrum in fluoroscopy. Many procedural factors affected the scattered spectrum indirectly through their effects on primary beam quality through ADRC, e.g., gantry angle and patient size. Lateral C-arm rotation, common in interventional cardiology, increased the energy of the scattered spectrum, regardless of the direction of rotation. The effect of patient size on scattered radiation depended on ADRC characteristics, patient size, and procedure type. Conclusion: The scattered spectrum striking the operator in fluoroscopy, and therefore the DRIP, is most strongly influenced by primary beam quality, particularly kV. Use cases for protective garments should be classified by typical procedural primary beam qualities, which are governed by the ADRC according to the impacts of patient size, anatomical location, and gantry angle. These results will help determine an appropriate set of SMPB to be used for measuring the DRIP.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-201-10: Experimental Determination of Modified TG-43 Dosimetry Parameters for the Xoft Axxent® Electronic Brachytherapy Source

Purpose: The establishment of an air kerma rate standard at NIST for the Xoft Axxent{sup ®} electronic brachytherapy source (Axxent{sup ®} source) motivated the establishment of a modified TG-43 dosimetry formalism. This work measures the modified dosimetry parameters for the Axxent{sup ®} source in the absence of a treatment applicator for implementation in Xoft’s treatment planning system. Methods: The dose-rate conversion coefficient (DRCC), radial dose function (RDF) values, and polar anisotropy (PA) were measured using TLD-100 microcubes with NIST-calibrated sources. The DRCC and RDF measurements were performed in liquid water using an annulus of Virtual Water™ designed to align the TLDs at the height of the anode at fixed radii from the source. The PA was measured at several distances from the source in a PMMA phantom. MCNP-determined absorbed dose energy dependence correction factors were used to convert from dose to TLD to dose to liquid water for the DRCC, RDF, and PA measurements. The intrinsic energy dependence correction factor from the work of Pike was used. The AKR was determined using a NIST-calibrated HDR1000 Plus well-type ionization chamber. Results: The DRCC was determined to be 8.6 (cGy/hr)/(µGy/min). The radial dose values were determined to be 1.00 (1cm), 0.60 (2cm), 0.42 (3cm), and 0.32 (4cm), with agreement ranging from (5.7% to 10.9%) from the work of Hiatt et al. 2015 and agreement from (2.8% to 6.8%) with internal MCNP simulations. Conclusion: This work presents a complete dataset of modified TG-43 dosimetry parameters for the Axxent{sup ®} source in the absence of an applicator. Prior to this study a DRCC had not been measured for the Axxent{sup ®} source. This data will be used for calculating dose distributions for patients receiving treatment with the Axxent{sup ®} source in Xoft’s breast balloon and vaginal applicators, and for intraoperative radiotherapy. Sources and partial funding for this work were provided by Xoft Inc. (a subsidiary of iCAD). This work was also supported by the Radiological Sciences T32 Training Grant through the University of Wisconsin-Madison Medical Physics department (5T32CA009206-37).

60 APPLIED LIFE SCIENCES↗