Search NASA⌕ Search

SEARCH · Search NASA

Results for “Estimation method”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Identification and localization of rotational spectra using recurrent neural networks

A method of identifying molecular parameters in a complex mixture may include receiving a set of combined transition frequencies and analyzing the set of combined transition frequencies using a first trained artificial neural network to generate a plurality of separated transition frequency sets. Each of the plurality of separated frequency sets may be analyzed using a second trained artificial neural network to generate a respective set of estimated spectral parameters. The method may include identifying a set of molecular parameters corresponding to the set of separated transition frequencies.

Prozuments, Kirills↗
DOE OSTI2018

Microstructural analysis of undoped and moderately Sc-doped TiO2 anatase nanoparticles using Scherrer equation and Debye function analysis

Highlights: • UV light sensitive undoped and moderate Sc-doped anatase nanocrystallites were prepared without post-synthesis annealing. • Elongated nanocrystallites were found by Scherrer equation and Debye Function Analysis applied to XRD data and also HRTEM. • 4 at.% Sc doping reduced the amount of Ti vacancies by half. • Doping showed ~0.3% growth of lattice parameters. - Abstract: UV light sensitive undoped and moderate (4 at.%) Sc-doped anatase nanocrystallites were prepared by an efficient and environmentally benign method based on homogeneous hydrolysis of TiOSO{sub 4} and Sc{sub 2}(C{sub 2}O{sub 4}){sub 3.5}H{sub 2}O aqueous solutions using urea as a precipitation agent, without post-synthesis calcination or annealing. X-ray diffraction study of the obtained powders revealed single phase anatase in both samples. Two different methods were applied to estimate the anatase crystallite size and shape from the X-ray diffraction data. The first one is based on the more conventional Scherrer equation (as implanted in GSAS-II program) while the second one is based on Debye function analysis (as implanted in DUBUSSY suite version 2.2), which is considered to be more adequate for nanocrystallites. Although each program has its own shape models, both methods indicated similar results of elongated nanocrystallite geometry for Sc-doped TiO{sub 2}: (i) GSAS-II confirmed ellipsoid shape with equatorial size of 5.1(0) nm and axial size of 6.8(0), (ii) DEBUSSY suite 2.2 showed cylinder shape with diameter of equivalent circle in the ab-plane, D{sub ab} = 4.9(1.0) nm and crystallite length along the c-axis, L{sub c} = 5.4(3.2) nm. For the undoped TiO{sub 2} sample, equatorial size of 5.5(0) nm and axial size of 7.3(0) nm for the ellipsoid shape was determined according to GSAS-II, while D{sub ab} = 5.5(1.3) nm and L{sub c} = 6.0(2.2) nm for the cylinder shape was determined by DEBUSSY suite 2.2. These outcomes were found to corroborate with HRTEM analysis. Doping with 4 at.% Sc caused ~0.3% growth of lattice parameters from a = 3.7979 [4] Å, c = 9.4995 [9] Å for the undoped sample to a = 3.8110 [7] Å, c = 9.5274 [16] Å for the moderately Sc doped sample, while reduction in the Ti vacancies by half was confirmed by both methods. The introducing of Sc as electronically active secondary species into the crystal lattice of TiO{sub 2} can greatly alter its optical absorption. The incorporation of Sc into the crystal lattice of TiO{sub 2} favors the substitution of Ti, as both have approximately the same ionic size, and generates surface oxygen vacancies which can act as trapping center for the photogenerated electrons and reduce the recombination of electron–hole pairs. We can expect Sc doped TiO{sub 2} nanomaterials to have applications as effective photocatalysts for selective photocatalytic oxidation of various environmental organic pollutants.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2017

Renal Function Outcomes of High-risk Neuroblastoma Patients Undergoing Radiation Therapy

Purpose: To analyze the renal function outcomes in patients undergoing radiation therapy for neuroblastoma. Methods and Materials: The clinical metrics of renal function were analyzed in patients undergoing radiation therapy for high-risk neuroblastoma from 2000 to 2015. The blood urea nitrogen (BUN) and creatinine values before radiation therapy were compared with last available follow-up values and analyzed with the clinical circumstances, including follow-up length, age at primary irradiation, nephrectomy, and radiation technique. The creatinine clearance was estimated using the Shull method. Results: With a median follow-up period of 3.5 years, none of the 266 patients studied developed a chronic renal insufficiency. For all patients, the creatinine level increased from 0.44 to 0.51 mg/dL and the BUN increased from 10.53 to 15.52 mg/dL. Three patients required antihypertensive medication. The patients who underwent intensity modulated radiation therapy did not experience increased creatinine levels during the follow-up period; however, they had a reduced median follow-up length compared with patients treated with anteroposterior/posteroanterior beams (4.7 vs 3.3 years). A longer follow-up length was associated with an increased creatinine level. The preradiation therapy creatinine level increased with patient age, similar to that of the last follow-up creatinine level, suggesting that the changes in creatinine could likely be explained by physiologic increases associated with aging rather than radiation-induced renal damage. The creatinine clearance did not decrease in any circumstance. Conclusions: The present cohort had excellent renal outcomes after radiation therapy for neuroblastoma. No patient developed chronic renal insufficiency, and the small increases in BUN and creatinine we observed correlated, as expected, with increases in patient age. The results of the present study revealed a possible advantage for intensity modulated radiation therapy in preserving renal function; however, the follow-up length is a recognized confounding variable. The kidneys are vital structures to consider when planning radiation therapy for neuroblastoma patients, and we have found encouraging evidence that modern techniques to spare them in the setting of multiple treatment-related insults have been successful.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Robust PV Degradation Methodology and Application

The degradation rate plays an important role in predicting and assessing the long-term energy generation of PV systems. Many methods have been proposed for extracting the degradation rate from operational data of PV systems, but most of the published approaches are susceptible to bias due to inverter clipping, module soiling, temporary outages, seasonality, and sensor degradation. In this manuscript, we propose a methodology for determining PV degradation leveraging available modeled clear-sky irradiance data rather than site sensor data, and a robust year-over-year (YOY) rate calculation. We show the method to provide reliable degradation rate estimates even in the case of sensor drift, data shifts, and soiling. Compared with alternate methods, we demonstrate that the proposed method delivers the lowest uncertainty in degradation rate estimates for a fleet of 486 PV systems.

14 SOLAR ENERGY↗
DOE OSTI2020

Two-particle correlation functions in cluster perturbation theory: Hubbard spin susceptibilities

Cluster perturbation theory (CPT) is a computationally economic method commonly used to estimate the momentum- and energy-resolved single-particle Green's function. It has been used extensively in direct comparisons with experiments that effectively measure the single-particle Green's function, e.g., angle-resolved photoemission spectroscopy. However, many experimental observables are given by two-particle correlation functions. CPT can be extended to compute two-particle correlation functions by approximately solving the Bethe-Salpeter equation. We implement this method and focus on the transverse spin susceptibility, measurable via inelastic neutron scattering or with optical probes of atomic gases in optical lattices. Finally, we benchmark the method with the one-dimensional Fermi-Hubbard model by comparing with known results.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Sequential Learning of Active Subspaces

This study shows that in recent years, active subspace methods (ASMs) have become a popular means of performing subspace sensitivity analysis on black-box functions. Naively applied, however, ASMs require gradient evaluations of the target function. In the event of noisy, expensive, or stochastic simulators, evaluating gradients via finite differencing may be infeasible. In such cases, often a surrogate model is employed, on which finite differencing is performed. When the surrogate model is a Gaussian process (GP), we show that the ASM estimator is available in closed form, rendering the finite-difference approximation unnecessary. We use our closed-form solution to develop acquisition functions focused on sequential learning tailored to sensitivity analysis on top of ASMs. We also show that the traditional ASM estimator may be viewed as a method of moments estimator for a certain class of GPs. We demonstrate how uncertainty on GP hyperparameters may be propagated to uncertainty on the sensitivity analysis, allowing model-based confidence intervals on the active subspace. Our methodological developments are illustrated on several examples.

97 MATHEMATICS AND COMPUTING↗
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 OSTI2017

Galaxy Cluster Mass Reconstruction Project – III. The impact of dynamical substructure on cluster mass estimates

With the advent of wide-field cosmological surveys, we are approaching samples of hundreds of thousands of galaxy clusters. While such large numbers will help reduce statistical uncertainties, the control of systematics in cluster masses is crucial. Here we examine the effects of an important source of systematic uncertainty in galaxy-based cluster mass estimation techniques: the presence of significant dynamical substructure. Dynamical substructure manifests as dynamically distinct subgroups in phase-space, indicating an ‘unrelaxed’ state. This issue affects around a quarter of clusters in a generally selected sample. We employ a set of mock clusters whose masses have been measured homogeneously with commonly used galaxy-based mass estimation techniques (kinematic, richness, caustic, radial methods). We use these to study how the relation between observationally estimated and true cluster mass depends on the presence of substructure, as identified by various popular diagnostics. We find that the scatter for an ensemble of clusters does not increase dramatically for clusters with dynamical substructure. However, we find a systematic bias for all methods, such that clusters with significant substructure have higher measured masses than their relaxed counterparts. This bias depends on cluster mass: the most massive clusters are largely unaffected by the presence of significant substructure, but masses are significantly overestimated for lower mass clusters, by ~ 10 percent at 10 14 and ≳ 20 percent for ≲ 10 13.5 . Finally, the use of cluster samples with different levels of substructure can therefore bias certain cosmological parameters up to a level comparable to the typical uncertainties in current cosmological studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Impact of correlated data in validation procedures - 14483

The increasing demand on accuracy of criticality calculations leads to the question, how to treat correlated data of benchmark experiments correctly. Correlations in the process of validation arise for example if a configuration in a series of experiments shares certain components, e.g. fuel rods. Traditional methods of code validation do not treat correlations explicitly, but give a more conservative estimation of the bias. Including correlations can lead to a more precise estimation. In the work at hand, a method is discussed based on Bayes theorem to include correlations in the experimental data when estimating an application case k{sub eff}. After a short introduction to the applied method and the demonstration of the general capability of it to predict the k{sub eff} correctly, it is shown how the calculated k{sub eff} of an application case depends on correlations in experimental data for a simple Toy Model. The impact of ignoring correlations and taking to account lower and higher correlations is shown and discussed. Further results are shown using a database of correlated experimental data from the International Handbook of Criticality Safety Experiments to estimate the bias of two application cases. The experiments were chosen following the suggestion of the OECD/NEA EGUACSA Benchmark phase IV and consists of 21 experiments from the LEU-COMP-THERM series 007 and 039. With the extracted data results the calculated k{sub eff} values of the application cases are shown and discussed for different examples of correlations. The calculations were done by applying Monte-Carlo sampling methods with the GRS tool SUnCISTT, using ORNL's SCALE 6.1.2. This work discusses a possible way of treating correlations in the recalculation of critical experiments to get a more precise bias estimation of the used code system. It will be shown, that the presented method is capable to treat similarities in experimental setups of data used to calculate the bias correctly, independent of the size of similarities. The presented method is in principle capable of assessing regimes with little experimental data to estimate a bias. (authors)

42 ENGINEERING↗
DOE OSTI2016

Multivariate analysis for the estimation of target localization errors in fiducial marker-based radiotherapy

Purpose: To assess the target localization error (TLE) in terms of the distance between the target and the localization point estimated from the surrogates (|TMD|), the average of respiratory motion for the surrogates and the target (|aRM|), and the number of fiducial markers used for estimating the target (n). Methods: This study enrolled 17 lung cancer patients who subsequently underwent four fractions of real-time tumor tracking irradiation. Four or five fiducial markers were implanted around the lung tumor. The three-dimensional (3D) distance between the tumor and markers was at maximum 58.7 mm. One of the markers was used as the target (P{sub t}), and those markers with a 3D |TMD{sub n}| ≤ 58.7 mm at end-exhalation were then selected. The estimated target position (P{sub e}) was calculated from a localization point consisting of one to three markers except P{sub t}. Respiratory motion for P{sub t} and P{sub e} was defined as the root mean square of each displacement, and |aRM| was calculated from the mean value. TLE was defined as the root mean square of each difference between P{sub t} and P{sub e} during the monitoring of each fraction. These procedures were performed repeatedly using the remaining markers. To provide the best guidance on the answer with n and |TMD|, fiducial markers with a 3D |aRM ≥ 10 mm were selected. Finally, a total of 205, 282, and 76 TLEs that fulfilled the 3D |TMD| and 3D |aRM| criteria were obtained for n = 1, 2, and 3, respectively. Multiple regression analysis (MRA) was used to evaluate TLE as a function of |TMD| and |aRM| in each n. Results: |TMD| for n = 1 was larger than that for n = 3. Moreover, |aRM| was almost constant for all n, indicating a similar scale for the marker’s motion near the lung tumor. MRA showed that |aRM| in the left–right direction was the major cause of TLE; however, the contribution made little difference to the 3D TLE because of the small amount of motion in the left–right direction. The TLE calculated from the MRA ({sup MRA}TLE) increased as |TMD| and |aRM| increased and adversely decreased with each increment of n. The median 3D {sup MRA}TLE was 2.0 mm (range, 0.6–4.3 mm) for n = 1, 1.8 mm (range, 0.4–4.0 mm) for n = 2, and 1.6 mm (range, 0.3–3.7 mm) for n = 3. Although statistical significance between n = 1 and n = 3 was observed in all directions, the absolute average difference and the standard deviation of the {sup MRA}TLE between n = 1 and n = 3 were 0.5 and 0.2 mm, respectively. Conclusions: A large |TMD| and |aRM| increased the differences in TLE between each n; however, the difference in 3D {sup MRA}TLEs was, at most, 0.6 mm. Thus, the authors conclude that it is acceptable to continue fiducial marker-based radiotherapy as long as |TMD| is maintained at ≤58.7 mm for a 3D |aRM| ≥ 10 mm.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Mechanical behavior analysis using small-size graphite disc compression testing with digital image correlation methods

The ASTM International Standard Test Method for Tensile Stress-Strain of Carbon and Graphite (ASTM C749) requires dog-bone shaped specimens. Unfortunately, specimen sizes required in ASTM C749 are much too large for irradiation within a test reactor and are incompatible with irradiation capsule volumes, molten salt degradation facilities, or oxidation apparatus. The ASTM International Standard Test Method for Tensile Strength Estimate by Disc Compression of Manufactured Graphite (ASTM D8289) was developed as an alternative that provides a means for testing tensile properties using smaller specimens when geometric constraints are present. However, the important stress–strain relation throughout the test loading history that could be recorded using ASTM C749 is lost by using ASTM D8289 because of the difficulties involved with using traditional strain gauges or extensometers on such a small specimen. In this work, a digital image correlation (DIC) method, which uses a full-field noncontact surface displacement measurement technique, was applied along with the ASTM D8289 splitting tensile test on eight small samples of graphite grade Mersen 2114 to track their deformation during compressive loading. Initial results showed that the DIC technique can measure the surface displacement/strain on these small (Ø6 × 3 mm) graphite specimens with high accuracy and good repeatability, indicating that the DIC technique, combined with the small-disc splitting tensile test in ASTM D8289, can capture the strain evolution in the test. In conclusion, further comparison of measured strains with analytical and numerical simulation results provides additional understanding of the mechanical behaviour of this nuclear graphite material in complex stress states.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Impact of cyber attacks on distributed compressive sensing based state estimation in power distribution grids

Modern power distribution grids suffer from multiple vulnerabilities due to the tight integration between the physical system and the cyber infrastructure. Sophisticated and malicious cyber attacks continue to adversely impact the grid operation leading to performance degradation, service interruption, and grid failure. State estimation plays an essential role in grid monitoring and advancing cyber-attack situational awareness. In this regard, this paper first proposes a distributed compressive sensing (CS) state estimation approach for an unobservable distribution grid. Further, the proposed distributed CS approach divides the distribution grid into sub-areas to perform local state estimation. Then an alternating direction method of multipliers (ADMM) based iterative information exchange among neighboring areas is employed to complete the estimation process. In this estimation process, the impact of loss of measurement data, false data injection (FDI), replay, and neighborhood cyber-attacks is analyzed. Extensive simulations are performed on the IEEE 37-bus and IEEE 123-bus standard networks to demonstrate the algorithm’s robustness to the aforementioned cyber-attacks. A quantitative analysis of computational complexity and simulation time of the distributed CS based approach is also presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Lyapunov-Based Iterative Learning of Regions of Attraction for Autonomous Systems

This paper proposes a novel algorithm for estimating the region of attraction of equilibrium points for nonlinear discrete-time autonomous systems. The method iteratively expands an initial estimate of the region of attraction by constructing unions of sublevel sets of learned functions parametrized as neural networks. Unlike conventional techniques that rely on a single global Lyapunov function, the proposed approach provides a collection of local Lyapunov-like functions, enabling richer representations and potentially larger region of attraction estimates. These functions are trained using sampled state-space data, and their Lipschitz continuity ensures that desirable properties extend beyond the training samples. The devised strategy is tested via numerical simulations, demonstrating the effectiveness of the proposed approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Lyapunov-Based Iterative Learning of the Region of Attraction for Autonomous Systems

This presentation introduces a novel algorithm for estimating the region of attraction of equilibrium points for nonlinear discrete-time autonomous systems. The method iteratively expands an initial estimate of the region of attraction by constructing unions of sublevel sets of learned functions parametrized as neural networks. Unlike conventional techniques that rely on a single global Lyapunov function, the proposed approach provides a collection of local Lyapunov-like functions, enabling richer representations and potentially larger region of attraction estimates. These functions are trained using sampled state-space data, and their Lipschitz continuity ensures that desirable properties extend beyond the training samples. The devised strategy is tested via numerical simulations, demonstrating the effectiveness of the proposed approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Analysis of Automated Fault Detection and Diagnosis Records as an Indicator of HVAC Fault Prevalence: Methodology and Preliminary Results

Faults in commercial buildings can cause energy waste and other performance problems such as reduced occupant comfort, reduced equipment longevity, and increased noise. However, it is currently unknown how commonly faults occur in different equipment types. A method has been developed to estimate the prevalence of faults in air handling units, air terminal units, and rooftop units. This method includes two types of data. The first is data from several automated fault detection and diagnostics (AFDD) software technologies. This type of data provides a large sample that represents a wide range of building types, geographical locations, and equipment types. It includes fault diagnoses from thousands of buildings around the United States, as well as anonymized metadata describing the building and equipment characteristics. The number of fault records is in the order of 107. However, despite the size and richness of the data sample, this data contains some degree of inaccuracy, i.e., false positive and false negative findings. Therefore, the study includes a second type of data, coming from manual inspection of buildings that have had the same AFDD methods applied to them (from the commercial AFDD offerings). Since the field tests are conducted in buildings with AFDD-generated fault prevalence data, they can be combined with the larger sample size to provide insight into the potential biases or lower sensitivity of the AFDD data. Once a library of fault prevalence data is built, it will be studied to provide further insight into the drivers of fault prevalence, for example, whether prevalence is correlated with building type, geographical location (which is tied to climate and to utility rates), building size, etc. This paper describes the methods developed for this study and illustrates them with preliminary data. It discusses some of the challenges of harmonizing disparate outputs from multiple AFDD vendors, application of a unifying fault taxonomy, and fault prevalence metrics.

Ebrahimi Fakhar, Amir↗
DOE OSTI2015

SU-E-T-769: T-Test Based Prior Error Estimate and Stopping Criterion for Monte Carlo Dose Calculation in Proton Therapy

Purpose: The Monte Carlo (MC) method is a gold standard for dose calculation in radiotherapy. However, it is not a priori clear how many particles need to be simulated to achieve a given dose accuracy. Prior error estimate and stopping criterion are not well established for MC. This work aims to fill this gap. Methods: Due to the statistical nature of MC, our approach is based on one-sample t-test. We design the prior error estimate method based on the t-test, and then use this t-test based error estimate for developing a simulation stopping criterion. The three major components are as follows.First, the source particles are randomized in energy, space and angle, so that the dose deposition from a particle to the voxel is independent and identically distributed (i.i.d.).Second, a sample under consideration in the t-test is the mean value of dose deposition to the voxel by sufficiently large number of source particles. Then according to central limit theorem, the sample as the mean value of i.i.d. variables is normally distributed with the expectation equal to the true deposited dose.Third, the t-test is performed with the null hypothesis that the difference between sample expectation (the same as true deposited dose) and on-the-fly calculated mean sample dose from MC is larger than a given error threshold, in addition to which users have the freedom to specify confidence probability and region of interest in the t-test based stopping criterion. Results: The method is validated for proton dose calculation. The difference between the MC Result based on the t-test prior error estimate and the statistical Result by repeating numerous MC simulations is within 1%. Conclusion: The t-test based prior error estimate and stopping criterion are developed for MC and validated for proton dose calculation. Xiang Hong and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-EF-207A-05: Feasibility of Applying SMEIR Method On Small Animal 4D Cone Beam CT Imaging

Purpose: Small animal cone beam CT imaging has been widely used in preclinical research. Due to the higher respiratory rate and heat beats of small animals, motion blurring is inevitable and needs to be corrected in the reconstruction. Simultaneous motion estimation and image reconstruction (SMEIR) method, which uses projection images of all phases, proved to be effective in motion model estimation and able to reconstruct motion-compensated images. We demonstrate the application of SMEIR for small animal 4D cone beam CT imaging by computer simulations on a digital rat model. Methods: The small animal CBCT imaging system was simulated with the source-to-detector distance of 300 mm and the source-to-object distance of 200 mm. A sequence of rat phantom were generated with 0.4 mm{sup 3} voxel size. The respiratory cycle was taken as 1.0 second and the motions were simulated with a diaphragm motion of 2.4mm and an anterior-posterior expansion of 1.6 mm. The projection images were calculated using a ray-tracing method, and 4D-CBCT were reconstructed using SMEIR and FDK methods. The SMEIR method iterates over two alternating steps: 1) motion-compensated iterative image reconstruction by using projections from all respiration phases and 2) motion model estimation from projections directly through a 2D-3D deformable registration of the image obtained in the first step to projection images of other phases. Results: The images reconstructed using SMEIR method reproduced the features in the original phantom. Projections from the same phase were also reconstructed using FDK method. Compared with the FDK results, the images from SMEIR method substantially improve the image quality with minimum artifacts. Conclusion: We demonstrate that it is viable to apply SMEIR method to reconstruct small animal 4D-CBCT images.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Current Status of Radiopharmaceutical Therapy

In radiopharmaceutical therapy (RPT), a radionuclide is systemically or locally delivered with the goal of targeting and delivering radiation to cancer cells while minimizing radiation exposure to untargeted cells. Examples of current RPTs include thyroid ablation with the administration of {sup 131}I, treatment of liver cancer with {sup 90}Y microspheres, the treatment of bony metastases with {sup 223}Ra, and the treatment of neuroendocrine tumors with {sup 177}Lu-DOTATATE. New RPTs are being developed where radionuclides are incorporated into systemic targeted therapies. To assure that RPT is appropriately implemented, advances in targeting need to be matched with advances in quantitative imaging and dosimetry methods. Currently, radiopharmaceutical therapy is administered by intravenous or locoregional injection, and the treatment planning has typically been implemented like chemotherapy, where the activity administered is either fixed or based on a patient’s body weight or body surface area. RPT pharmacokinetics are measurable by quantitative imaging and are known to vary across patients, both in tumors and normal tissues. Therefore, fixed or weight-based activity prescriptions are not currently optimized to deliver a cytotoxic dose to targets while remaining within the tolerance dose of organs at risk. Methods that provide dose estimates to individual patients rather than to reference geometries are needed to assess and adjust the injected RPT dose. Accurate doses to targets and organs at risk will benefit the individual patients and decrease uncertainties in clinical trials. Imaging can be used to measure activity distribution in vivo, and this information can be used to determine patient-specific treatment plans where the dose to the targets and organs at risk can be calculated. The development and adoption of imaging-based dosimetry methods is particularly beneficial in early clinical trials. In this work we discuss dosimetric accuracy needs in modern radiation oncology, uncertainties in the dosimetry in RPT, and best approaches for imaging and dosimetry of internal radionuclide therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗