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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

SU-F-303-13: Initial Evaluation of Four Dimensional Diffusion- Weighted MRI (4D-DWI) and Its Effect On Apparent Diffusion Coefficient (ADC) Measurement

Purpose: Diffusion-weighted imaging(DWI) has been shown to have superior tumor-to-tissue contrast for cancer detection.This study aims at developing and evaluating a four dimensional DWI(4D-DWI) technique using retrospective sorting method for imaging respiratory motion for radiotherapy planning,and evaluate its effect on Apparent Diffusion Coefficient(ADC) measurement. Materials/Methods: Image acquisition was performed by repeatedly imaging a volume of interest using a multi-slice single-shot 2D-DWI sequence in the axial planes and cine MRI(served as reference) using FIESTA sequence.Each 2D-DWI image were acquired in xyz-diffusion-directions with a high b-value(b=500s/mm2).The respiratory motion was simultaneously recorded using bellows.Retrospective sorting was applied in each direction to reconstruct 4D-DWI.The technique was evaluated using a computer simulated 4D-digital human phantom(XCAT),a motion phantom and a healthy volunteer under an IRB-approved study.Motion trajectories of regions-of-interests(ROI) were extracted from 4D-DWI and compared with reference.The mean motion trajectory amplitude differences(D) between the two was calculated.To quantitatively analyze the motion artifacts,XCAT were controlled to simulate regular motion and the motions of 10 liver cancer patients.4D-DWI,free-breathing DWI(FB- DWI) were reconstructed.Tumor volume difference(VD) of each phase of 4D-DWI and FB-DWI from the input static tumor were calculated.Furthermore, ADC was measured for each phase of 4D-DWI and FB-DWI data,and mean tumor ADC values(M-ADC) were calculated.Mean M-ADC over all 4D-DWI phases was compared with M-ADC calculated from FB-DWI. Results: 4D-DWI of XCAT,the motion phantom and the healthy volunteer demonstrated the respiratory motion clearly.ROI D values were 1.9mm,1.7mm and 2.0mm,respectively.For motion artifacts analysis,XCAT 4D-DWI images show much less motion artifacts compare to FB-DWI.Mean VD for 4D-WDI and FB-DWI were 8.5±1.4% and 108±15%,respectively.Mean M-ADC for ADC measured from 4D-DWI and M-ADC measured from FB-DWI were (2.29±0.04)*0.001*mm2/s and (3.80±0.01)*0.001*mm2/s,respectively.ADC value ground-truth is 2.24*0.001*mm2/s from the input of the simulation. Conclusion: A respiratory correlated 4D-DWI technique has been initially evaluated in phantoms and a human subject.Comparing to free breathing DWI,4D-DWI can lead to more accurate measurement of ADC.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2018

Evaluation of MODIS and Sentinel-3 SLSTR Thermal Emissive Bands Calibration Consistency Using Dome C

Over the years, data from different satellites has provided invaluable information about Earth's atmosphere, land and oceans. The thermal emissive bands (TEB) on the Moderate Resolution Imaging Spectroradiometer (MODIS) are comprised of 16 spectral bands with wavelengths ranging from 3.7 to 14.4 μm. MODIS TEB are calibrated on orbit on a scan-by-scan basis using an on-board blackbody (BB). Sentinel-3 Sea and Land Surface Temperature Radiometer (SLSTR), launched on 16 February 2016, has 11 spectral bands with wavelengths from 0.55 to 12 μm. In this study, we compare the observed brightness temperature from MODIS bands 31 and 32 and SLSTR bands S8 and S9 over Dome C using a 20 × 20 km region of interest (ROI) centered at (75.102 °S,123.395 °E). A total of 2989 scenes for Terra, 2963 for Aqua and 1961 for SLSTR from November, 2016 to January 2018 are analyzed. The relative bias between MODIS and SLSTR is evaluated using the near-surface temperature measurements from an Automatic Weather Station (AWS).

Shrestha, Ashish↗
DOE OSTI2015

SU-E-J-94: Geometric and Dosimetric Evaluation of Deformation Image Registration Algorithms Using Virtual Phantoms Generated From Patients with Lung Cancer

Purpose: To generate virtual phantoms with clinically relevant deformation and use them to objectively evaluate geometric and dosimetric uncertainties of deformable image registration (DIR) algorithms. Methods: Ten lung cancer patients undergoing adaptive 3DCRT planning were selected. For each patient, a pair of planning CT (pCT) and replanning CT (rCT) were used as the basis for virtual phantom generation. Manually adjusted meshes were created for selected ROIs (e.g. PTV, lungs, spinal cord, esophagus, and heart) on pCT and rCT. The mesh vertices were input into a thin-plate spline algorithm to generate a reference displacement vector field (DVF). The reference DVF was used to deform pCT to generate a simulated replanning CT (srCT) that was closely matched to rCT. Three DIR algorithms (Demons, B-Spline, and intensity-based) were applied to these ten virtual phantoms. The images, ROIs, and doses were mapped from pCT to srCT using the DVFs computed by these three DIRs and compared to those mapped using the reference DVF. Results: The average Dice coefficients for selected ROIs were from 0.85 to 0.96 for Demons, from 0.86 to 0.97 for intensity-based, and from 0.76 to 0.95 for B-Spline. The average Hausdorff distances for selected ROIs were from 2.2 to 5.4 mm for Demons, from 2.3 to 6.8 mm for intensity-based, and from 2.4 to 11.4 mm for B-Spline. The average absolute dose errors for selected ROIs were from 0.2 to 0.6 Gy for Demons, from 0.1 to 0.5 Gy for intensity-based, and from 0.5 to 1.5 Gy for B-Spline. Conclusion: Virtual phantoms were modeled after patients with lung cancer and were clinically relevant for adaptive radiotherapy treatment replanning. Virtual phantoms with known DVFs serve as references and can provide a fair comparison when evaluating different DIRs. Demons and intensity-based DIRs were shown to have smaller geometric and dosimetric uncertainties than B-Spline. Z Shen: None; K Bzdusek: an employee of Philips Healthcare; J Greskovich: None; P Xia: received research grants from Philips Healthcare and Siemens Healthcare.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Nonlocal atlas-guided multi-channel forest learning for human brain labeling

Purpose: It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. However, due to high complexity of brain structures and ambiguous boundaries between different anatomical regions, the anatomical labeling of MR brain images is still quite a challenging task. In many existing label fusion methods, appearance information is widely used. However, since local anatomy in the human brain is often complex, the appearance information alone is limited in characterizing each image point, especially for identifying the same anatomical structure across different subjects. Recent progress in computer vision suggests that the context features can be very useful in identifying an object from a complex scene. In light of this, the authors propose a novel learning-based label fusion method by using both low-level appearance features (computed from the target image) and high-level context features (computed from warped atlases or tentative labeling maps of the target image). Methods: In particular, the authors employ a multi-channel random forest to learn the nonlinear relationship between these hybrid features and target labels (i.e., corresponding to certain anatomical structures). Specifically, at each of the iterations, the random forest will output tentative labeling maps of the target image, from which the authors compute spatial label context features and then use in combination with original appearance features of the target image to refine the labeling. Moreover, to accommodate the high inter-subject variations, the authors further extend their learning-based label fusion to a multi-atlas scenario, i.e., they train a random forest for each atlas and then obtain the final labeling result according to the consensus of results from all atlases. Results: The authors have comprehensively evaluated their method on both public LONI-LBPA40 and IXI datasets. To quantitatively evaluate the labeling accuracy, the authors use the dice similarity coefficient to measure the overlap degree. Their method achieves average overlaps of 82.56% on 54 regions of interest (ROIs) and 79.78% on 80 ROIs, respectively, which significantly outperform the baseline method (random forests), with the average overlaps of 72.48% on 54 ROIs and 72.09% on 80 ROIs, respectively. Conclusions: The proposed methods have achieved the highest labeling accuracy, compared to several state-of-the-art methods in the literature.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS1984

Cogeneration Technology Alternatives Study (CTAS). Volume 2: Comparison and evaluation of results

CTAS compared and evaluated various advanced energy conversion systems that can use coal or coal-derived fuels for industrial cogeneration applications. The principal aim of the study was to provide information needed by DOE to establish research and development (R&D) funding priorities for advanced-technology systems that could significantly advance the use of coal or coal-derived fuels in industrial cogeneration. Steam turbines, diesel engines, open-cycle gas turbines, combined cycles, closed-cycle gas turbines, Stirling engines, phosphoric acid fuel cells, molten carbonate fuel cells, and thermionics were studied with technology advancements appropriate for the 1985-2000 time period. The various advanced systems were compared and evaluated for a wide diversity of representative industrial plants on the basis of fuel energy savings, annual energy cost savings, emissions savings, and rate of return on investment (ROI) as compared with purchasing electricity from a utility and providing process heat with an on-site boiler.

Source record↗
DOE OSTI2016

SU-F-P-48: The Quantitative Evaluation and Comparison of Image Distortion and Loss of X-Ray Images Between Anti-Scattered Grid and Moire Compensation Processing in Digital Radiography

Purpose: To quantitatively analyze the influence image processing for Moire elimination has in digital radiography by comparing the image acquired from optimized anti-scattered grid only and the image acquired from software processing paired with misaligned low-frequency grid. Methods: Special phantom, which does not create scattered radiation, was used to acquire non-grid reference images and they were acquired without any grids. A set of images was acquired with optimized grid, aligned to pixel of a detector and other set of images was acquired with misaligned low-frequency grid paired with Moire elimination processing algorithm. X-ray technique used was based on consideration to Bucky factor derived from non-grid reference images. For evaluation, we analyze by comparing pixel intensity of acquired images with grids to that of reference images. Results: When compared to image acquired with optimized grid, images acquired with Moire elimination processing algorithm showed 10 to 50% lower mean contrast value of ROI. Severe distortion of images was found with when the object’s thickness was measured at 7 or less pixels. In this case, contrast value measured from images acquired with Moire elimination processing algorithm was under 30% of that taken from reference image. Conclusion: This study shows the potential risk of Moire compensation images in diagnosis. Images acquired with misaligned low-frequency grid results in Moire noise and Moire compensation processing algorithm used to remove this Moire noise actually caused an image distortion. As a result, fractures and/or calcifications which are presented in few pixels only may not be diagnosed properly. In future work, we plan to evaluate the images acquired without grid but based on 100% image processing and the potential risks it possesses.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-248: Contributions of Tumor and Stroma Phenotyping in Computer-Aided Diagnosis

Purpose: To gain insight into the role of parenchyma stroma in the characterization of breast tumors by incorporating computerized mammographic parenchyma assessment into breast CADx in the task of distinguishing between malignant and benign lesions. Methods: This study was performed on 182 biopsy-proven breast mass lesions, including 76 benign and 106 malignant lesions. For each full-field digital mammogram (FFDM) case, our quantitative imaging analysis was performed on both the tumor and a region-of-interest (ROI) from the normal contralateral breast. The lesion characterization includes automatic lesion segmentation and feature extraction. Radiographic texture analysis (RTA) was applied on the normal ROIs to assess the mammographic parenchymal patterns of these contralateral normal breasts. Classification performance of both individual computer extracted features and the output from a Bayesian artificial neural network (BANN) were evaluated with a leave-one-lesion-out method using receiver operating characteristic (ROC) analysis with area under the curve (AUC) as the figure of merit. Results: Lesion characterization included computer-extracted phenotypes of spiculation, size, shape, and margin. For parenchymal pattern characterization, five texture features were selected, including power law beta, contrast, and edge gradient. Merging of these computer-selected features using BANN classifiers yielded AUC values of 0.79 (SE=0.03) and 0.67 (SE=0.04) in the task of distinguishing between malignant and benign lesions using only tumor phenotypes and texture features from the contralateral breasts, respectively. Incorporation of tumor phenotypes with parenchyma texture features into the BANN yielded improved classification performance with an AUC value of 0.83 (SE=0.03) in the task of differentiating malignant from benign lesions. Conclusion: Combining computerized tumor and parenchyma phenotyping was found to significantly improve breast cancer diagnostic accuracy highlighting the need to consider both tumor and stroma in decision making. Funding: University of Chicago Dean Bridge Fund, NCI U24-CA143848-05, P50-CA58223 Breast SPORE program, and Breast Cancer Research Foundation. COI: MLG is a stockholder in R2 technology/Hologic and receives royalties from Hologic, GE Medical Systems, MEDIAN Technologies, Riverain Medical, Mitsubishi, and Toshiba. MLG is a cofounder and stockholder in Quantitative Insights.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Towards a realistic astrophysical interpretation of the gamma-ray Galactic center excess

A spherical-symmetric gamma-ray emission from (the inner region of the Galaxy (at least up to roughly 10° in latitude and longitude)) has been recently identified in Fermi-LAT data, and initially associated to dark matter particle annihilations. Guided by the evidence for a high gas density in the inner kpc of the Galaxy correlated with a very large Supernova rate, and hence with ongoing cosmic-ray acceleration, we investigate instead the possibility of addressing this excess in terms of ordinary cosmic-ray sources and standard steady-state diffusion. We (alter the source term, and consistently the correlated gamma-ray emissions, in the context of a template-fitting analysis. We focus on a region of interest (ROI) defined as: |l| < 20°; 2° < |b| < 20°, with l and b the Galactic longitude and latitude coordinates.) We analyze in detail the overall goodness of the fit of our framework, and perform a detailed direct comparison against data examining profiles in different directions. Remarkably, the test statistic of the fit related to our scenario turns out to be as good as the Dark Matter one in the ROI here considered.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

A new method for tracking organ motion on diagnostic ultrasound images

Purpose: Respiratory-gated irradiation is effective in reducing the margins of a target in the case of abdominal organs, such as the liver, that change their position as a result of respiratory motion. However, existing technologies are incapable of directly measuring organ motion in real-time during radiation beam delivery. Hence, the authors proposed a novel quantitative organ motion tracking method involving the use of diagnostic ultrasound images; it is noninvasive and does not entail radiation exposure. In the present study, the authors have prospectively evaluated this proposed method. Methods: The method involved real-time processing of clinical ultrasound imaging data rather than organ monitoring; it comprised a three-dimensional ultrasound device, a respiratory sensing system, and two PCs for data storage and analysis. The study was designed to evaluate the effectiveness of the proposed method by tracking the gallbladder in one subject and a liver vein in another subject. To track a moving target organ, the method involved the control of a region of interest (ROI) that delineated the target. A tracking algorithm was used to control the ROI, and a large number of feature points and an error correction algorithm were used to achieve long-term tracking of the target. Tracking accuracy was assessed in terms of how well the ROI matched the center of the target. Results: The effectiveness of using a large number of feature points and the error correction algorithm in the proposed method was verified by comparing it with two simple tracking methods. The ROI could capture the center of the target for about 5 min in a cross-sectional image with changing position. Indeed, using the proposed method, it was possible to accurately track a target with a center deviation of 1.54 ± 0.9 mm. The computing time for one frame image using our proposed method was 8 ms. It is expected that it would be possible to track any soft-tissue organ or tumor with large deformations and changing cross-sectional position using this method. Conclusions: The proposed method achieved real-time processing and continuous tracking of the target organ for about 5 min. It is expected that our method will enable more accurate radiation treatment than is the case using indirect observational methods, such as the respiratory sensor method, because of direct visualization of the tumor. Results show that this tracking system facilitates safe treatment in clinical practice.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Laser-Driven Megavolt X-Ray and Neutron Source Optimization

This 4-month feasibility study assessed the options, trade-offs and major issues in using National Ignition Facility (NIF) and Advanced Radiographic Capability (ARC)-class laser beams for multipulse MeV x-ray and neutron radiography of high explosives (HE) driven experiments. It was performed in close collaboration with a second FS evaluating future HE radiography requirements and expected laser-based source data quality with respect to existing and alternate radiography sources. The study first reviewed the existing published data on MeV x-ray and neutron sources compared to requirements on yield (10 14 /sr for X-rays, > 10 13 /sr for neutrons), spot size (< 1 mm) and duration (< 20 ns). For MeV neutron sources, the preferred options are DTfilled exploding pusher targets or stagnating DT plasmas, each source requiring 50 kJ level. few ns beam irradiation at 0.5 or 0.35 micron wavelength. The preferred X-ray MeV source option to be fully assessed by a follow-up SI is an angularly and temporally-multiplexed multi-burst version of a Bremsstrahlung source (Courtois et al. 2011) irradiated by up to 7 10 ps, kJ-class 1 micron wavelength lasers beams. This multi-burst laser mode, submitted as an ROI and patent, should increase final laser optics damage energy thresholds based on 2 pulse tests and hence allow near full extraction of the 15 kJ of 1 micron laser energy available on a NIF beamline. Hydrodynamic simulations were used to evaluate the effects of preceding pulse irradiation on target integrity, and show that this can be mitigated by using 3D structured targets.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Estimating Return on Investment for Energy Technical Assistance Programs

The U.S. Department of Energy's Office of State and Community Energy Programs engaged the National Laboratory of the Rockies to assess the return on investment (ROI) of technical assistance (TA) programs that support state, local, and Tribal energy planning. Although TA delivers value through capacity building, stakeholder engagement, and knowledge transfer, these benefits are often intangible and challenging to monetize. This study reviews existing ROI frameworks and synthesizes the most relevant elements into a hybrid approach tailored to energy TA programs. The proposed framework integrates monetary and non-monetary outcomes through early logic model development, baseline data collection, and the use of proxies for intangible benefits. As a case study, this paper applies this approach to the Communities Local Energy Action Program (Communities LEAP), demonstrating how ROI can inform program design, data strategy, and performance assessment. Findings underscore that ROI should be applied selectively and planned from the outset to ensure data alignment and attribution accuracy. The framework offers TA practitioners a structured approach that can be leveraged for future programs to evaluate and communicate the multifaceted value of TA investments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

A kernel machine method for detecting higher order interactions in multimodal datasets: Application to schizophrenia

Technological advances are enabling us to collect multimodal datasets at an increasing depth and resolution while with decreasing labors. Understanding complex interactions among multimodal datasets, however, is challenging. Here in this study, we tested the interaction effect of multimodal datasets using a novel method called the kernel machine for detecting higher order interactions among biologically relevant multimodal data. Using a semiparametric method on a reproducing kernel Hilbert space, we formulated the proposed method as a standard mixed-effects linear model and derived a score-based variance component statistic to test higher order interactions between multimodal datasets. The method was evaluated using extensive numerical simulation and real data from the Mind Clinical Imaging Consortium with both schizophrenia patients and healthy controls. Our method identified 13-triplets that included 6 gene-derived SNPs, 10 ROIs, and 6 gene-specific DNA methylations that are correlated with the changes in hippocampal volume, suggesting that these triplets may be important for explaining schizophrenia-related neurodegeneration. The performance of the proposed method is compared with the following methods: test based on only first and first few principal components followed by multiple regression, and full principal component analysis regression, and the sequence kernel association test. With strong evidence (p-value ≤0.000001), the triplet (MAGI2, CRBLCrus1.L, FBXO28) is a significant biomarker for schizophrenia patients. This novel method can be applicable to the study of other disease processes, where multimodal data analysis is a common task.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

MO-FG-204-08: Optimization-Based Image Reconstruction From Unevenly Distributed Sparse Projection Views

Purpose: Optimization-based reconstruction has been proposed and investigated for reconstructing CT images from sparse views, as such the radiation dose can be substantially reduced while maintaining acceptable image quality. The investigation has so far focused on reconstruction from evenly distributed sparse views. Recognizing the clinical situations wherein only unevenly sparse views are available, e.g., image guided radiation therapy, CT perfusion and multi-cycle cardiovascular imaging, we investigate the performance of optimization-based image reconstruction from unevenly sparse projection views in this work. Methods: The investigation is carried out using the FORBILD and an anthropomorphic head phantoms. In the study, 82 views, which are evenly sorted out from a full (360°) axial CT scan consisting of 984 views, form sub-scan I. Another 82 views are sorted out in a similar manner to form sub-scan II. As such, a CT scan with sparse (164) views at 1:6 ratio are formed. By shifting the two sub-scans relatively in view angulation, a CT scan with unevenly distributed sparse (164) views at 1:6 ratio are formed. An optimization-based method is implemented to reconstruct images from the unevenly distributed views. By taking the FBP reconstruction from the full scan (984 views) as the reference, the root mean square (RMS) between the reference and the optimization-based reconstruction is used to evaluate the performance quantitatively. Results: In visual inspection, the optimization-based method outperforms the FBP substantially in the reconstruction from unevenly distributed, which are quantitatively verified by the RMS gauged globally and in ROIs in both the FORBILD and anthropomorphic head phantoms. The RMS increases with increasing severity in the uneven angular distribution, especially in the case of anthropomorphic head phantom. Conclusion: The optimization-based image reconstruction can save radiation dose up to 12-fold while providing acceptable image quality for advanced clinical applications wherein only unevenly distributed sparse views are available. Research Grants: W81XWH-12-1-0138 (DoD), Sinovision Technologies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Directional fractal signature methods for trabecular bone texture in hand radiographs: Data from the Osteoarthritis Initiative

Purpose: To develop directional fractal signature methods for the analysis of trabecular bone (TB) texture in hand radiographs. Problems associated with the small size of hand bones and the orientation of fingers were addressed. Methods: An augmented variance orientation transform (AVOT) and a quadrant rotating grid (QRG) methods were developed. The methods calculate fractal signatures (FSs) in different directions. Unlike other methods they have the search region adjusted according to the size of bone region of interest (ROI) to be analyzed and they produce FSs defined with respect to any chosen reference direction, i.e., they work for arbitrary orientation of fingers. Five parameters at scales ranging from 2 to 14 pixels (depending on image size and method) were derived from rose plots of Hurst coefficients, i.e., FS in dominating roughness (FS{sub Sta}), vertical (FS{sub V}) and horizontal (FS{sub H}) directions, aspect ratio (StrS), and direction signatures (StdS), respectively. The accuracy in measuring surface roughness and isotropy/anisotropy was evaluated using 3600 isotropic and 800 anisotropic fractal surface images of sizes between 20 × 20 and 64 × 64 pixels. The isotropic surfaces had FDs ranging from 2.1 to 2.9 in steps of 0.1, and the anisotropic surfaces had two dominating directions of 30° and 120°. The methods were used to find differences in hand TB textures between 20 matched pairs of subjects with (cases: approximate Kellgren-Lawrence (KL) grade ≥2) and without (controls: approximate KL grade <2) radiographic hand osteoarthritis (OA). The OA Initiative public database was used and 20 × 20 pixel bone ROIs were selected on 5th distal and middle phalanges. The performance of the AVOT and QRG methods was compared against a variance orientation transform (VOT) method developed earlier [M. Wolski, P. Podsiadlo, and G. W. Stachowiak, “Directional fractal signature analysis of trabecular bone: evaluation of different methods to detect early osteoarthritis in knee radiographs,” Proc. Inst. Mech. Eng., Part H 223, 211–236 (2009)]. Results: The AVOT method correctly quantified the isotropic and anisotropic surfaces for all image sizes and scales. Values of FS{sub Sta} were significantly different (P < 0.05) between the isotropic surfaces. Using the VOT and QRG methods no differences were found at large scales for the isotropic surfaces that are smaller than 64 × 64 and 48 × 48 pixels, respectively, and at some scales for the anisotropic surfaces with size 48 × 48 pixels. Compared to controls, using the AVOT and QRG methods the authors found that OA TB textures were less rough (P < 0.05) in the dominating and horizontal directions (i.e., lower FS{sub Sta} and FS{sub H}), rougher in the vertical direction (i.e., higher FS{sub V}) and less anisotropic (i.e., higher StrS) than controls. No differences were found using the VOT method. Conclusions: The AVOT method is well suited for the analysis of bone texture in hand radiographs and it could be potentially useful for early detection and prediction of hand OA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-F-BRB-03: Quantifying Patient Motion During Deep-Inspiration Breath-Hold Using the ABC System with Simultaneous Surface Photogrammetry

Purpose: Active breathing control (ABC) has been used to reduce treatment margin due to respiratory organ motion by enforcing temporary breath-holds. However, in practice, even if the ABC device indicates constant lung volume during breath-hold, the patient may still exhibit minor chest motion. Consequently, therapists are given a false sense of security that the patient is immobilized. This study aims at quantifying such motion during ABC breath-holds by monitoring the patient chest motion using a surface photogrammetry system, VisionRT. Methods: A female patient with breast cancer was selected to evaluate chest motion during ABC breath-holds. During the entire course of treatment, the patient’s chest surface was monitored by a surface photogrammetry system, VisionRT. Specifically, a user-defined region-of-interest (ROI) on the chest surface was selected for the system to track at a rate of ∼3Hz. The surface motion was estimated by rigid image registration between the current ROI image captured and a reference image. The translational and rotational displacements computed were saved in a log file. Results: A total of 20 fractions of radiation treatment were monitored by VisionRT. After removing noisy data, we obtained chest motion of 79 breath-hold sessions. Mean chest motion in AP direction during breath-holds is 1.31mm with 0.62mm standard deviation. Of the 79 sessions, the patient exhibited motion ranging from 0–1 mm (30 sessions), 1–2 mm (37 sessions), 2–3 mm (11 sessions) and >3 mm (1 session). Conclusion: Contrary to popular assumptions, the patient is not completely still during ABC breath-hold sessions. In this particular case studied, the patient exhibited chest motion over 2mm in 14 out of 79 breath-holds. Underestimating treatment margin for radiation therapy with ABC could reduce treatment effectiveness due to geometric miss or overdose of critical organs. The senior author receives research funding from NIH, VisionRT, Varian Medical Systems and Elekta.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

A stilbene - CdZnTe based radioxenon detection system

Atmospheric monitoring of radioxenon is one of the most widely used methods by the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) to detect elevated levels of 131m Xe, 133/133m Xe, and 135 Xe. The ratios of these radionuclides help discriminate between peaceful use of nuclear technology and nuclear weapon explosions. Radioxenon detection systems often use plastic scintillators in the capacity of an electron detector and a gas cell, plastic gas cells are responsible for introducing high memory effect in these systems. This work presents the design of a new detection system for radioxenon monitoring that utilizes silicon photomultipliers, a stilbene gas cell, and a CdZnTe detector. This detector was evaluated using xenon radioisotope samples produced in the TRIGA reactor at Oregon State University. Here, a 48-h background was collected and calculations of the Minimum Detectable Concentration (MDC) were carried out using the Region of Interest (ROI) approach. An MDC of less than 1 mBq/m 3 was obtained for 131m Xe, 133 Xe, and 133m Xe in accordance with the sensitivity limits set by the CTBTO and performs respectably when compared to state-of-the-art radioxenon detection systems. Using 131m Xe, this study indicates that the stilbene gas cell exhibits a memory effect of 0.045 ±0.017%, this is almost a two-order magnitude improvement compared to plastic scintillators. The main purpose of this work is to explore the use of new stilbene detection media for radioxenon application and addressing the problem of memory effect.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2016

SIS epidemiological model for adaptive RT: Forecasting the parotid glands shrinkage during tomotherapy treatment

Purpose: A susceptible-infected-susceptible (SIS) epidemic model was applied to radiation therapy (RT) treatments to predict morphological variations in head and neck (H&N) anatomy. Methods: 360 daily MVCT images of 12 H&N patients treated by tomotherapy were analyzed in this retrospective study. Deformable image registration (DIR) algorithms, mesh grids, and structure recontouring, implemented in the RayStation treatment planning system (TPS), were applied to assess the daily organ warping. The parotid’s warping was evaluated using the epidemiological approach considering each vertex as a single subject and its deformed vector field (DVF) as an infection. Dedicated IronPython scripts were developed to export daily coordinates and displacements of the region of interest (ROI) from the TPS. MATLAB tools were implemented to simulate the SIS modeling. Finally, the fully trained model was applied to a new patient. Results: A QUASAR phantom was used to validate the model. The patients’ validation was obtained setting 0.4 cm of vertex displacement as threshold and splitting susceptible (S) and infectious (I) cases. The correlation between the epidemiological model and the parotids’ trend for further optimization of alpha and beta was carried out by Euclidean and dynamic time warping (DTW) distances. The best fit with experimental conditions across all patients (Euclidean distance of 4.09 ± 1.12 and DTW distance of 2.39 ± 0.66) was obtained setting the contact rate at 7.55 ± 0.69 and the recovery rate at 2.45 ± 0.26; birth rate was disregarded in this constant population. Conclusions: Combining an epidemiological model with adaptive RT (ART), the authors’ novel approach could support image-guided radiation therapy (IGRT) to validate daily setup and to forecast anatomical variations. The SIS-ART model developed could support clinical decisions in order to optimize timing of replanning achieving personalized treatments.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-H-207A-02: Attenuation Correction in 4D-PET Using a Single-Phase Attenuation Map

Purpose: 4D-PET imaging has been proposed as a potential solution to the respiratory motion effect in thoracic region. CT-based attenuation correction (AC) is an essential step toward quantitative imaging for PET. However, due to the temporal difference of 4D-PET and a single breath-hold CT, motion artifacts are observed in the attenuation-corrected PET images that can lead to error in tumor shape and uptake. We introduce a practical method for aligning single-phase CT to all other 4D-PET phases using a penalized non-rigid demons registration. Methods: Individual 4D-PET frames were reconstructed without AC. Non-rigid Demons registration was used to derive deformation vector fields (DVFs) between the PET matched with CT phase and other 4D-PET images. While attenuated PET images provide enough useful data for organ borders such as lung and liver, tumors are not distinguishable from background due to loss of contrast. To preserve tumor shape in different phases, from CT image an ROI covering tumor was excluded from non-rigid transformation. Mean DVF of the central region of the tumor was assigned to all voxels in the ROI. This process mimics a rigid transformation of tumor along with a non-rigid transformation of other organs. 4D XCAT phantom with spherical tumors in lung with diameters ranging from 10 to 40 mm was used to evaluate the algorithm. Results: Motion related induced artifacts in attenuation-corrected 4D-PET images were significantly reduced. For tumors smaller than 20 mm, non-rigid transformation was capable to provide quantitative results. However, for larger tumors, where tumor self-attenuation is considerable, our combined method yields superior results. Conclusion: We introduced a practical method for deforming a single CT to match all 4D-PET images for accurate AC. Although 4D-PET data include insignificant anatomical information, we showed that they are still useful to estimate DVFs for aligning attenuation map and accurate AC.

60 APPLIED LIFE SCIENCES↗