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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Tau-REx I: A next generation retrieval code for exoplanetary atmospheres

Spectroscopy of exoplanetary atmospheres has become a well established method for the characterization of extrasolar planets. We here present a novel inverse retrieval code for exoplanetary atmospheres. T-REx(Tau Retrieval for Exoplanets) is a line-by-line radiative transfer fully Bayesian retrieval framework. T-REx includes the following features:(1) the optimized use of molecular line lists from the ExoMol project; (2) an unbiased atmospheric composition prior selection, through custom built pattern recognition software; (3) the use of two independent algorithms to fully sample the Bayesian likelihood space: nested sampling as well as a more classical Markov Chain Monte Carlo approach; (4) iterative Bayesian parameter and model selection using the full Bayesian Evidence as well as the Savage–Dickey Ratio for nested models; and (5) the ability to fully map very large parameter spaces through optimal code parallelization and scalability to cluster computing. In this publication we outline the T-REx framework and demonstrate, using a theoretical hot-Jupiter transmission spectrum, the parameter retrieval and model selection. We investigate the impact of signal-to-noise ratio and spectral resolution on the retrievability of individual model parameters, both in terms of error bars on the temperature and molecular mixing ratios as well as its effect on the model’s global Bayesian evidence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Chebyshev polynomial filtered subspace iteration in the discontinuous Galerkin method for large-scale electronic structure calculations

The Discontinuous Galerkin (DG) electronic structure method employs an adaptive local basis (ALB) set to solve the Kohn-Sham equations of density functional theory in a discontinuous Galerkin framework. The adaptive local basis is generated on-the-fly to capture the local material physics and can systematically attain chemical accuracy with only a few tens of degrees of freedom per atom. A central issue for large-scale calculations, however, is the computation of the electron density (and subsequently, ground state properties) from the discretized Hamiltonian in an efficient and scalable manner. We show in this work how Chebyshev polynomial filtered subspace iteration (CheFSI) can be used to address this issue and push the envelope in large-scale materials simulations in a discontinuous Galerkin framework. We describe how the subspace filtering steps can be performed in an efficient and scalable manner using a two-dimensional parallelization scheme, thanks to the orthogonality of the DG basis set and block-sparse structure of the DG Hamiltonian matrix. The on-the-fly nature of the ALB functions requires additional care in carrying out the subspace iterations. We demonstrate the parallel scalability of the DG-CheFSI approach in calculations of large-scale twodimensional graphene sheets and bulk three-dimensional lithium-ion electrolyte systems. In conclusion, employing 55 296 computational cores, the time per self-consistent field iteration for a sample of the bulk 3D electrolyte containing 8586 atoms is 90 s, and the time for a graphene sheet containing 11 520 atoms is 75 s.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

SU-E-I-89: Assessment of CT Radiation Dose and Image Quality for An Automated Tube Potential Selection Algorithm Using Pediatric Anthropomorphic and ACR Phantoms

Purpose: To assess the impact of General Electrics automated tube potential algorithm, kV assist (kVa) on radiation dose and image quality, with an emphasis on optimizing protocols based on noise texture. Methods: Radiation dose was assessed by inserting optically stimulated luminescence dosimeters (OSLs) throughout the body of a pediatric anthropomorphic phantom (CIRS). The baseline protocol was: 120 kVp, 80 mA, 0.7s rotation time. Image quality was assessed by calculating the contrast to noise ratio (CNR) and noise power spectrum (NPS) from the ACR CT accreditation phantom. CNRs were calculated according to the steps described in ACR CT phantom testing document. NPS was determined by taking the 3D FFT of the uniformity section of the ACR phantom. NPS and CNR were evaluated with and without kVa and for all available adaptive iterative statistical reconstruction (ASiR) settings, ranging from 0 to 100%. Each NPS was also evaluated for its peak frequency difference (PFD) with respect to the baseline protocol. Results: For the baseline protocol, CNR was found to decrease from 0.460 ± 0.182 to 0.420 ± 0.057 when kVa was activated. When compared against the baseline protocol, the PFD at ASiR of 40% yielded a decrease in noise magnitude as realized by the increase in CNR = 0.620 ± 0.040. The liver dose decreased by 30% with kVa activation. Conclusion: Application of kVa reduces the liver dose up to 30%. However, reduction in image quality for abdominal scans occurs when using the automated tube voltage selection feature at the baseline protocol. As demonstrated by the CNR and NPS analysis, the texture and magnitude of the noise in reconstructed images at ASiR 40% was found to be the same as our baseline images. We have demonstrated that 30% dose reduction is possible when using 40% ASiR with kVa in pediatric patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-I-99: Estimation of Effective Charge Distribution by Dual-Energy CT Reconstruction

Purpose: Computed Tomography (CT) is a method to produce slice image of specific volume from the scanned x-ray projection images. The contrast of CT image is correlated with the attenuation coefficients of the x-ray in the object. The attenuation coefficient is strongly dependent on the x-ray energy and the effective charge of the material. The purpose of this presentation is to show the effective charge distribution predicted by CT images reconstructed with kilovoltage(kV) and megavoltage(MV) x-ray energy. Methods: The attenuation coefficients of x-ray can be characterized by cross section of photoionization and Compton scattering for the specific xray energy. In particular, the photoionization cross section is strongly correlated with the effective charge of the object. Hence we can calculate effective charge by solving the coupled equation between the attenuation coefficient and the theoretical cross section. For this study, we use the megavoltage (MV) and kilovoltage (kV) x-rays of Elekta Synergy as the dual source x-ray, and CT image of the Phantom Laboratory CatPhan is reconstructed by the filtered back projection (FBP) and iterative algorithm for cone-beam CT (CBCT). Results: We report attenuation coefficients of each component of the CatPhan specified by each x-ray source. Also the effective charge distribution is evaluated by the MV and kV dual x-ray sources. The predicted effective charges are comparable with the nominal ones. Conclusion: We developed the MV and kV dual-source CBCT reconstruction to yield the effective charge distribution. For more accuracy, it is critical to remove an effect of the scattering photon in the CBCT reconstruction algorithm. The finding will be fine reference of the effective charge of tissue and lead to the more realistic absorbed-dose calculation. This work was partly supported by the JSPS Core-to-Core Program(No. 23003), and this work was partly supported by JSPS KAKENHI 24234567.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Block preconditioning for fault/fracture mechanics saddle-point problems

The efficient simulation of fault and fracture mechanics is a key issue in several applications and is attracting a growing interest by the scientific community. Using a formulation based on Lagrange multipliers, the Jacobian matrix resulting from the Finite Element discretization of the governing equations has a non-symmetric generalized saddle-point structure. In this work, we propose a family of block preconditioners to accelerate the convergence of Krylov methods for such problems. We critically review possible advantages and difficulties of using various Schur complement approximations, based on both physical and algebraic considerations. In conclusion, the proposed approaches are tested in a number of real-world applications, showing their robustness and efficiency also in large-size and ill-conditioned problems.

42 ENGINEERING↗
DOE OSTI2016

WE-AB-207A-04: Random Undersampled Cone Beam CT: Theoretical Analysis and a Novel Reconstruction Method

Purpose: Reducing x-ray exposure and speeding up data acquisition motived studies on projection data undersampling. It is an important question that for a given undersampling ratio, what the optimal undersampling approach is. In this study, we propose a new undersampling scheme: random-ray undersampling. We will mathematically analyze its projection matrix properties and demonstrate its advantages. We will also propose a new reconstruction method that simultaneously performs CT image reconstruction and projection domain data restoration. Methods: By representing projection operator under the basis of singular vectors of full projection operator, matrix representations for an undersampling case can be generated and numerical singular value decomposition can be performed. We compared properties of matrices among three undersampling approaches: regular-view undersampling, regular-ray undersampling, and the proposed random-ray undersampling. To accomplish CT reconstruction for random undersampling, we developed a novel method that iteratively performs CT reconstruction and missing projection data restoration via regularization approaches. Results: For a given undersampling ratio, random-ray undersampling preserved mathematical properties of full projection operator better than the other two approaches. This translates to advantages of reconstructing CT images at lower errors. Different types of image artifacts were observed depending on undersampling strategies, which were ascribed to the unique singular vectors of the sampling operators in the image domain. We tested the proposed reconstruction algorithm on a Forbid phantom with only 30% of the projection data randomly acquired. Reconstructed image error was reduced from 9.4% in a TV method to 7.6% in the proposed method. Conclusion: The proposed random-ray undersampling is mathematically advantageous over other typical undersampling approaches. It may permit better image reconstruction at the same undersampling ratio. The novel algorithm suitable for this random-ray undersampling was able to reconstruct high-quality images.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Plutonium Critical Mass Curve Comparison to Mass at Upper Subcritical Limit (USL) Using Whisper

Whisper is computational software designed to assist the nuclear criticality safety analyst with validation studies with the MCNP ® Monte Carlo radiation transport package. Standard approaches to validation rely on the selection of benchmarks based upon expert judgment. Whisper uses sensitivity/uncertainty (S/U) methods to select relevant benchmarks to a particular application or set of applications being analyzed. Using these benchmarks, Whisper computes a calculational margin. Whisper attempts to quantify the margin of subcriticality (MOS) from errors in software and uncertainties in nuclear data. The combination of the Whisper-derived calculational margin and MOS comprise the baseline upper subcritical limit (USL), to which an additional margin may be applied by the nuclear criticality safety analyst as appropriate to ensure subcriticality. A series of critical mass curves for plutonium, similar to those found in Figure 31 of LA-10860-MS, have been generated using MCNP6.1.1 and the iterative parameter study software, WORM_Solver. The baseline USL for each of the data points of the curves was then computed using Whisper 1.1. The USL was then used to determine the equivalent mass for plutonium metal-water system. ANSI/ANS-8.1 states that it is acceptable to use handbook data, such as the data directly from the LA-10860-MS, as it is already considered validated (Section 4.3 4) “Use of subcritical limit data provided in ANSI/ANS standards or accepted reference publications does not require further validation.”). This paper attempts to take a novel approach to visualize traditional critical mass curves and allows comparison with the amount of mass for which the k eff is equal to the USL (calculational margin + margin of subcriticality). However, the intent is to plot the critical mass data along with USL, not to suggest that already accepted handbook data should have new and more rigorous requirements for validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Optimal Shielding Design For Minimum Materials Cost or Mass - Paper 128

Material costs dominate some shielding design problems. This is certainly the case for manned nuclear power space applications for which shielding is essential and the cost of launching by rocket from Earth is high. In such situations or in those where shielding volume or mass is constrained, it is important to optimize the design. Although trial and error synthesis methods may succeed, a more systematic approach is warranted. Design automation may also potentially reduce engineering costs. The objective is to automate the design of optimal radiation shielding to meet specified attenuation requirements given a menu of allowed shielding materials, their properties and their delivered costs per unit volume. The cost-optimal design is one which, at each location in the shield, chooses the menu material minimizing a particular functional of forward and adjoint angular fluxes plus material cost. Thus a Boltzmann forward and adjoint angular flux solver with additional calculations can evaluate whether a shield design is optimal or whether improvements are possible. An iterative algorithm based on approximated optimality is proposed to solve for the optimal shield design and numerical experiments with it are discussed. The future use of 3D Boltzmann solvers will allow extending results to shaped shield designs in which material is not wasted to maintain unneeded spherical symmetry. The largest cost savings of automated optimal design of shielding is expected to be for applications involving nuclear powered manned space missions where the required shielding attenuation of radiation and costs are both large. However, less exotic applications such as the shielding of radiation facilities on Earth could also benefit from optimal shielding design, and automation of the design process may reduce engineering costs. (author)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

A DVH-guided IMRT optimization algorithm for automatic treatment planning and adaptive radiotherapy replanning

Purpose: To develop a novel algorithm that incorporates prior treatment knowledge into intensity modulated radiation therapy optimization to facilitate automatic treatment planning and adaptive radiotherapy (ART) replanning. Methods: The algorithm automatically creates a treatment plan guided by the DVH curves of a reference plan that contains information on the clinician-approved dose-volume trade-offs among different targets/organs and among different portions of a DVH curve for an organ. In ART, the reference plan is the initial plan for the same patient, while for automatic treatment planning the reference plan is selected from a library of clinically approved and delivered plans of previously treated patients with similar medical conditions and geometry. The proposed algorithm employs a voxel-based optimization model and navigates the large voxel-based Pareto surface. The voxel weights are iteratively adjusted to approach a plan that is similar to the reference plan in terms of the DVHs. If the reference plan is feasible but not Pareto optimal, the algorithm generates a Pareto optimal plan with the DVHs better than the reference ones. If the reference plan is too restricting for the new geometry, the algorithm generates a Pareto plan with DVHs close to the reference ones. In both cases, the new plans have similar DVH trade-offs as the reference plans. Results: The algorithm was tested using three patient cases and found to be able to automatically adjust the voxel-weighting factors in order to generate a Pareto plan with similar DVH trade-offs as the reference plan. The algorithm has also been implemented on a GPU for high efficiency. Conclusions: A novel prior-knowledge-based optimization algorithm has been developed that automatically adjust the voxel weights and generate a clinical optimal plan at high efficiency. It is found that the new algorithm can significantly improve the plan quality and planning efficiency in ART replanning and automatic treatment planning.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

AN EMPIRICAL METHOD FOR IMPROVING THE QUALITY OF RXTE HEXTE SPECTRA

We have developed a correction tool to improve the quality of Rossi X-ray Timing Explorer (RXTE) High Energy X-ray Timing Experiment (HEXTE) spectra by employing the same method we used earlier to improve the quality of RXTE Proportional Counter Array (PCA) spectra. We fit all of the hundreds of HEXTE spectra of the Crab individually to a simple power-law model, some 37 million counts in total for Cluster A and 39 million counts for Cluster B, and we create for each cluster a combined spectrum of residuals. We find that the residual spectrum of Cluster A is free of instrumental artifacts while that of Cluster B contains significant features with amplitudes ∼1%; the most prominent is in the energy range 30–50 keV, which coincides with the iodine K edge. Starting with the residual spectrum for Cluster B, via an iterative procedure we created the calibration tool hexBcorr for correcting any Cluster B spectrum of interest. We demonstrate the efficacy of the tool by applying it to Cluster B spectra of two bright black holes, which contain several million counts apiece. For these spectra, application of the tool significantly improves the goodness of fit, while affecting only slightly the broadband fit parameters. The tool may be important for the study of spectral features, such as cyclotron lines, a topic that is beyond the scope of this paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Bayesian soft X-ray tomography using non-stationary Gaussian Processes

In this study, a Bayesian based non-stationary Gaussian Process (GP) method for the inference of soft X-ray emissivity distribution along with its associated uncertainties has been developed. For the investigation of equilibrium condition and fast magnetohydrodynamic behaviors in nuclear fusion plasmas, it is of importance to infer, especially in the plasma center, spatially resolved soft X-ray profiles from a limited number of noisy line integral measurements. For this ill-posed inversion problem, Bayesian probability theory can provide a posterior probability distribution over all possible solutions under given model assumptions. Specifically, the use of a non-stationary GP to model the emission allows the model to adapt to the varying length scales of the underlying diffusion process. In contrast to other conventional methods, the prior regularization is realized in a probability form which enhances the capability of uncertainty analysis, in consequence, scientists who concern the reliability of their results will benefit from it. Under the assumption of normally distributed noise, the posterior distribution evaluated at a discrete number of points becomes a multivariate normal distribution whose mean and covariance are analytically available, making inversions and calculation of uncertainty fast. Additionally, the hyper-parameters embedded in the model assumption can be optimized through a Bayesian Occam's Razor formalism and thereby automatically adjust the model complexity. This method is shown to produce convincing reconstructions and good agreements with independently calculated results from the Maximum Entropy and Equilibrium-Based Iterative Tomography Algorithm methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

WE-AB-BRA-07: Operating Room Quality Assurance (ORQA) for Spine Surgery Using Known-Component 3D-2D Image Registration

Purpose: Intraoperative x-ray radiography/fluoroscopy is commonly used to qualitatively assess delivery of surgical devices (e.g., spine pedicle screws) but can fail to reliably detect suboptimal placement (e.g., breach of adjacent critical structures). We present a method wherein prior knowledge of the patient and surgical components is leveraged to match preoperative CT and intraoperative radiographs for quantitative assessment of 3D pose. The method presents a new means of operating room quantitative quality assurance (ORQA) that could improve quality and safety, and reduce the frequency of revision surgeries. Methods: The algorithm (known-component registration, KC-Reg) uses patient-specific preoperative CT and parametrically defined surgical component models within a robust 3D-2D registration method to iteratively optimize gradient similarity using the covariance matrix adaptation evolution strategy. Advances from previous work address key challenges to clinical translation: i) absolving the need for offline geometric calibration of the C-arm; and ii) solving multiple component bodies simultaneously, thereby allowing QA in a single step (e.g., spinal construct with 4–20 screws), rather than sequential QA of each component. Performance was tested in a spine phantom with 10 pedicle screws, and first results from clinical studies are reported. Results: Phantom experiments demonstrated median target registration error (TRE) of (1.0±0.3) mm at the screw tip and (0.7°±0.4°) in angulation. The simultaneous multi-body registration approach improved TRE from the previous (sequential) method by 42%, reduced outliers, and fits into the natural workflow. Initial application of KC-Reg in clinical data shows TRE of (2.5±4.5) mm and (4.7°±0.5°). Conclusion: The KC-Reg algorithm offers a potentially valuable method for quantitative QA of the surgical product, using radiographic systems that are already within the surgical arsenal. For spine surgery, the method offers a near-real-time independent check on the quality of surgical product, facilitating immediate revision if necessary and potentially avoiding postoperative morbidity and/or revision surgery. Gerhard Kleinszig and Sebastian Vogt are employees of Siemens Healthcare.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-10: A Moving-Blocker-Based Strategy for Simultaneous Megavoltage and Kilovoltage Scatter Correction in Cone-Beam Computed Tomography Image Acquired During Volumetric Modulated Arc Therapy

Purpose: To evaluate a moving-blocker-based approach in estimating and correcting megavoltage (MV) and kilovoltage (kV) scatter contamination in kV cone-beam computed tomography (CBCT) acquired during volumetric modulated arc therapy (VMAT). Methods: XML code was generated to enable concurrent CBCT acquisition and VMAT delivery in Varian TrueBeam developer mode. A physical attenuator (i.e., “blocker”) consisting of equal spaced lead strips (3.2mm strip width and 3.2mm gap in between) was mounted between the x-ray source and patient at a source to blocker distance of 232mm. The blocker was simulated to be moving back and forth along the gantry rotation axis during the CBCT acquisition. Both MV and kV scatter signal were estimated simultaneously from the blocked regions of the imaging panel, and interpolated into the un-blocked regions. Scatter corrected CBCT was then reconstructed from un-blocked projections after scatter subtraction using an iterative image reconstruction algorithm based on constraint optimization. Experimental studies were performed on a Catphan 600 phantom and an anthropomorphic pelvis phantom to demonstrate the feasibility of using moving blocker for MV-kV scatter correction. Results: MV scatter greatly degrades the CBCT image quality by increasing the CT number inaccuracy and decreasing the image contrast, in addition to the shading artifacts caused by kV scatter. The artifacts were substantially reduced in the moving blocker corrected CBCT images in both Catphan and pelvis phantoms. Quantitatively, CT number error in selected regions of interest reduced from 377 in the kV-MV contaminated CBCT image to 38 for the Catphan phantom. Conclusions: The moving-blockerbased strategy can successfully correct MV and kV scatter simultaneously in CBCT projection data acquired with concurrent VMAT delivery. This work was supported in part by a grant from the Cancer Prevention and Research Institute of Texas (RP130109) and a grant from the American Cancer Society (RSG-13-326-01-CCE)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

A physics-motivated Centroidal Voronoi Particle domain decomposition method

In this paper, we propose a novel domain decomposition method for large-scale simulations in continuum mechanics by merging the concepts of Centroidal Voronoi Tessellation (CVT) and Voronoi Particle dynamics (VP). The CVT is introduced to achieve a high-level compactness of the partitioning subdomains by the Lloyd algorithm which monotonically decreases the CVT energy. The number of computational elements between neighboring partitioning subdomains, which scales the communication effort for parallel simulations, is optimized implicitly as the generated partitioning subdomains are convex and simply connected with small aspect-ratios. Moreover, Voronoi Particle dynamics employing physical analogy with a tailored equation of state is developed, which relaxes the particle system towards the target partition with good load balance. Since the equilibrium is computed by an iterative approach, the partitioning subdomains exhibit locality and the incremental property. Numerical experiments reveal that the proposed Centroidal Voronoi Particle (CVP) based algorithm produces high-quality partitioning with high efficiency, independently of computational-element types. Thus it can be used for a wide range of applications in computational science and engineering.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

iCycle: Integrated, multicriterial beam angle, and profile optimization for generation of coplanar and noncoplanar IMRT plans

Purpose: To introduce iCycle, a novel algorithm for integrated, multicriterial optimization of beam angles, and intensity modulated radiotherapy (IMRT) profiles. Methods: A multicriterial plan optimization with iCycle is based on a prescription called wish-list, containing hard constraints and objectives with ascribed priorities. Priorities are ordinal parameters used for relative importance ranking of the objectives. The higher an objective priority is, the higher the probability that the corresponding objective will be met. Beam directions are selected from an input set of candidate directions. Input sets can be restricted, e.g., to allow only generation of coplanar plans, or to avoid collisions between patient/couch and the gantry in a noncoplanar setup. Obtaining clinically feasible calculation times was an important design criterium for development of iCycle. This could be realized by sequentially adding beams to the treatment plan in an iterative procedure. Each iteration loop starts with selection of the optimal direction to be added. Then, a Pareto-optimal IMRT plan is generated for the (fixed) beam setup that includes all so far selected directions, using a previously published algorithm for multicriterial optimization of fluence profiles for a fixed beam arrangement Breedveld et al.[Phys. Med. Biol. 54, 7199-7209 (2009)]. To select the next direction, each not yet selected candidate direction is temporarily added to the plan and an optimization problem, derived from the Lagrangian obtained from the just performed optimization for establishing the Pareto-optimal plan, is solved. For each patient, a single one-beam, two-beam, three-beam, etc. Pareto-optimal plan is generated until addition of beams does no longer result in significant plan quality improvement. Plan generation with iCycle is fully automated. Results: Performance and characteristics of iCycle are demonstrated by generating plans for a maxillary sinus case, a cervical cancer patient, and a liver patient treated with SBRT. Plans generated with beam angle optimization did better meet the clinical goals than equiangular or manually selected configurations. For the maxillary sinus and liver cases, significant improvements for noncoplanar setups were seen. The cervix case showed that also in IMRT with coplanar setups, beam angle optimization with iCycle may improve plan quality. Computation times for coplanar plans were around 1-2 h and for noncoplanar plans 4-7 h, depending on the number of beams and the complexity of the site. Conclusions: Integrated beam angle and profile optimization with iCycle may result in significant improvements in treatment plan quality. Due to automation, the plan generation workload is minimal. Clinical application has started.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Framework for 3D histologic reconstruction and fusion with in vivo MRI: Preliminary results of characterizing pulmonary inflammation in a mouse model

Purpose: Pulmonary inflammation is associated with a variety of diseases. Assessing pulmonary inflammation on in vivo imaging may facilitate the early detection and treatment of lung diseases. Although routinely used in thoracic imaging, computed tomography has thus far not been compellingly shown to characterize inflammation in vivo. Alternatively, magnetic resonance imaging (MRI) is a nonionizing radiation technique to better visualize and characterize pulmonary tissue. Prior to routine adoption of MRI for early characterization of inflammation in humans, a rigorous and quantitative characterization of the utility of MRI to identify inflammation is required. Such characterization may be achieved by considering ex vivo histology as the ground truth, since it enables the definitive spatial assessment of inflammation. In this study, the authors introduce a novel framework to integrate 2D histology, ex vivo and in vivo imaging to enable the mapping of the extent of disease from ex vivo histology onto in vivo imaging, with the goal of facilitating computerized feature analysis and interrogation of disease appearance on in vivo imaging. The authors’ framework was evaluated in a preclinical preliminary study aimed to identify computer extracted features on in vivo MRI associated with chronic pulmonary inflammation. Methods: The authors’ image analytics framework first involves reconstructing the histologic volume in 3D from individual histology slices. Second, the authors map the disease ground truth onto in vivo MRI via coregistration with 3D histology using the ex vivo lung MRI as a conduit. Finally, computerized feature analysis of the disease extent is performed to identify candidate in vivo imaging signatures of disease presence and extent. Results: The authors evaluated the framework by assessing the quality of the 3D histology reconstruction and the histology—MRI fusion, in the context of an initial use case involving characterization of chronic inflammation in a mouse model. The authors’ evaluation considered three mice, two with an inflammation phenotype and one control. The authors’ iterative 3D histology reconstruction yielded a 70.1% ± 2.7% overlap with the ex vivo MRI volume. Across a total of 17 anatomic landmarks manually delineated at the division of airways, the target registration error between the ex vivo MRI and 3D histology reconstruction was 0.85 ± 0.44 mm, suggesting that a good alignment of the ex vivo 3D histology and ex vivo MRI had been achieved. The 3D histology-in vivo MRI coregistered volumes resulted in an overlap of 73.7% ± 0.9%. Preliminary computerized feature analysis was performed on an additional four control mice, for a total of seven mice considered in this study. Gabor texture filters appeared to best capture differences between the inflamed and noninflamed regions on MRI. Conclusions: The authors’ 3D histology reconstruction and multimodal registration framework were successfully employed to reconstruct the histology volume of the lung and fuse it with in vivo MRI to create a ground truth map for inflammation on in vivo MRI. The analytic platform presented here lays the framework for a rigorous validation of the identified imaging features for chronic lung inflammation on MRI in a large prospective cohort.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Computer-aided detection of clustered microcalcifications in multiscale bilateral filtering regularized reconstructed digital breast tomosynthesis volume

Purpose: Develop a computer-aided detection (CADe) system for clustered microcalcifications in digital breast tomosynthesis (DBT) volume enhanced with multiscale bilateral filtering (MSBF) regularization. Methods: With Institutional Review Board approval and written informed consent, two-view DBT of 154 breasts, of which 116 had biopsy-proven microcalcification (MC) clusters and 38 were free of MCs, was imaged with a General Electric GEN2 prototype DBT system. The DBT volumes were reconstructed with MSBF-regularized simultaneous algebraic reconstruction technique (SART) that was designed to enhance MCs and reduce background noise while preserving the quality of other tissue structures. The contrast-to-noise ratio (CNR) of MCs was further improved with enhancement-modulated calcification response (EMCR) preprocessing, which combined multiscale Hessian response to enhance MCs by shape and bandpass filtering to remove the low-frequency structured background. MC candidates were then located in the EMCR volume using iterative thresholding and segmented by adaptive region growing. Two sets of potential MC objects, cluster centroid objects and MC seed objects, were generated and the CNR of each object was calculated. The number of candidates in each set was controlled based on the breast volume. Dynamic clustering around the centroid objects grouped the MC candidates to form clusters. Adaptive criteria were designed to reduce false positive (FP) clusters based on the size, CNR values and the number of MCs in the cluster, cluster shape, and cluster based maximum intensity projection. Free-response receiver operating characteristic (FROC) and jackknife alternative FROC (JAFROC) analyses were used to assess the performance and compare with that of a previous study. Results: Unpaired two-tailedt-test showed a significant increase (p < 0.0001) in the ratio of CNRs for MCs with and without MSBF regularization compared to similar ratios for FPs. For view-based detection, a sensitivity of 85% was achieved at an FP rate of 2.16 per DBT volume. For case-based detection, a sensitivity of 85% was achieved at an FP rate of 0.85 per DBT volume. JAFROC analysis showed a significant improvement in the performance of the current CADe system compared to that of our previous system (p = 0.003). Conclusions: MBSF regularized SART reconstruction enhances MCs. The enhancement in the signals, in combination with properly designed adaptive threshold criteria, effective MC feature analysis, and false positive reduction techniques, leads to a significant improvement in the detection of clustered MCs in DBT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

WE-AB-207A-09: Optimization of the Design of a Moving Blocker for Cone-Beam CT Scatter Correction: Experimental Evaluation

Purpose: A moving blocker based strategy has shown promising results for scatter correction in cone-beam computed tomography (CBCT). Different geometry designs and moving speeds of the blocker affect its performance in image reconstruction accuracy. The goal of this work is to optimize the geometric design and moving speed of the moving blocker system through experimental evaluations. Methods: An Elekta Synergy XVI system and an anthropomorphic pelvis phantom CIRS 801-P were used for our experiment. A blocker consisting of lead strips was inserted between the x-ray source and the phantom moving back and forth along rotation axis to measure the scatter signal. Accoriding to our Monte Carlo simulation results, three blockers were used, which have the same lead strip width 3.2mm and different gap between neighboring lead strips, 3.2, 6.4 and 9.6mm. For each blocker, three moving speeds were evaluated, 10, 20 and 30 pixels per projection (on the detector plane). Scatter signal in the unblocked region was estimated by cubic B-spline based interpolation from the blocked region. CBCT image was reconstructed by a total variation (TV) based algebraic iterative reconstruction (ART) algorithm from the partially blocked projection data. Reconstruction accuracy in each condition is quantified as CT number error of region of interest (ROI) by comparing to a CBCT reconstructed image from analytically simulated unblocked and scatter free projection data. Results: Highest reconstruction accuracy is achieved when the blocker width is 3.2 mm, the gap between neighboring lead strips is 9.6 mm and the moving speed is 20 pixels per projection. RMSE of the CT number of ROIs can be reduced from 436 to 27. Conclusions: Image reconstruction accuracy is greatly affected by the geometry design of the blocker. The moving speed does not have a very strong effect on reconstruction result if it is over 20 pixels per projection.

60 APPLIED LIFE SCIENCES↗