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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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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Postmortem validation of breast density using dual-energy mammography

Purpose: Mammographic density has been shown to be an indicator of breast cancer risk and also reduces the sensitivity of screening mammography. Currently, there is no accepted standard for measuring breast density. Dual energy mammography has been proposed as a technique for accurate measurement of breast density. The purpose of this study is to validate its accuracy in postmortem breasts and compare it with other existing techniques. Methods: Forty postmortem breasts were imaged using a dual energy mammography system. Glandular and adipose equivalent phantoms of uniform thickness were used to calibrate a dual energy basis decomposition algorithm. Dual energy decomposition was applied after scatter correction to calculate breast density. Breast density was also estimated using radiologist reader assessment, standard histogram thresholding and a fuzzy C-mean algorithm. Chemical analysis was used as the reference standard to assess the accuracy of different techniques to measure breast composition. Results: Breast density measurements using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm, and dual energy were in good agreement with the measured fibroglandular volume fraction using chemical analysis. The standard error estimates using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean, and dual energy were 9.9%, 8.6%, 7.2%, and 4.7%, respectively. Conclusions: The results indicate that dual energy mammography can be used to accurately measure breast density. The variability in breast density estimation using dual energy mammography was lower than reader assessment rankings, standard histogram thresholding, and fuzzy C-mean algorithm. Improved quantification of breast density is expected to further enhance its utility as a risk factor for breast cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Evaluation of Matrix9 silicon photomultiplier array for small-animal PET

Purpose: The MatrixSL-9-30035-OEM (Matrix9) from SensL is a large-area silicon photomultiplier (SiPM) photodetector module consisting of a 3 × 3 array of 4 × 4 element SiPM arrays (total of 144 SiPM pixels) and incorporates SensL’s front-end electronics board and coincidence board. Each SiPM pixel measures 3.16 × 3.16 mm{sup 2} and the total size of the detector head is 47.8 × 46.3 mm{sup 2}. Using 8 × 8 polished LSO/LYSO arrays (pitch 1.5 mm) the performance of this detector system (SiPM array and readout electronics) was evaluated with a view for its eventual use in small-animal positron emission tomography (PET). Methods: Measurements of noise, signal, signal-to-noise ratio, energy resolution, flood histogram quality, timing resolution, and array trigger error were obtained at different bias voltages (28.0–32.5 V in 0.5 V intervals) and at different temperatures (5 °C–25 °C in 5 °C degree steps) to find the optimal operating conditions. Results: The best measured signal-to-noise ratio and flood histogram quality for 511 keV gamma photons were obtained at a bias voltage of 30.0 V and a temperature of 5 °C. The energy resolution and timing resolution under these conditions were 14.2% ± 0.1% and 4.2 ± 0.1 ns, respectively. The flood histograms show that all the crystals in the 1.5 mm pitch LSO array can be clearly identified and that smaller crystal pitches can also be resolved. Flood histogram quality was also calculated using different center of gravity based positioning algorithms. Improved and more robust results were achieved using the local 9 pixels for positioning along with an energy offset calibration. To evaluate the front-end detector readout, and multiplexing efficiency, an array trigger error metric is introduced and measured at different lower energy thresholds. Using a lower energy threshold greater than 150 keV effectively eliminates any mispositioning between SiPM arrays. Conclusions: In summary, the Matrix9 detector system can resolve high-resolution scintillator arrays common in small-animal PET with adequate energy resolution and timing resolution over a large detector area. The modular design of the Matrix9 detector allows it to be used as a building block for simple, low channel-count, yet high performance, small animal PET or PET/MRI systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

SU-F-I-45: An Automated Technique to Measure Image Contrast in Clinical CT Images

Purpose: To develop and validate an automated technique for measuring image contrast in chest computed tomography (CT) exams. Methods: An automated computer algorithm was developed to measure the distribution of Hounsfield units (HUs) inside four major organs: the lungs, liver, aorta, and bones. These organs were first segmented or identified using computer vision and image processing techniques. Regions of interest (ROIs) were automatically placed inside the lungs, liver, and aorta and histograms of the HUs inside the ROIs were constructed. The mean and standard deviation of each histogram were computed for each CT dataset. Comparison of the mean and standard deviation of the HUs in the different organs provides different contrast values. The ROI for the bones is simply the segmentation mask of the bones. Since the histogram for bones does not follow a Gaussian distribution, the 25th and 75th percentile were computed instead of the mean. The sensitivity and accuracy of the algorithm was investigated by comparing the automated measurements with manual measurements. Fifteen contrast enhanced and fifteen non-contrast enhanced chest CT clinical datasets were examined in the validation procedure. Results: The algorithm successfully measured the histograms of the four organs in both contrast and non-contrast enhanced chest CT exams. The automated measurements were in agreement with manual measurements. The algorithm has sufficient sensitivity as indicated by the near unity slope of the automated versus manual measurement plots. Furthermore, the algorithm has sufficient accuracy as indicated by the high coefficient of determination, R2, values ranging from 0.879 to 0.998. Conclusion: Patient-specific image contrast can be measured from clinical datasets. The algorithm can be run on both contrast enhanced and non-enhanced clinical datasets. The method can be applied to automatically assess the contrast characteristics of clinical chest CT images and quantify dependencies that may not be captured in phantom data.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

The Poisson tensor completion non-parametric differential entropy estimator

We introduce the Poisson tensor completion (PTC) estimator, a non-parametric differential entropy estimator. The PTC estimator leverages inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial Poisson process. The Poisson tensor decomposition leads to a completion of the intensity measure over all bins—including those containing few to no samples—and leads to our proposed PTC differential entropy estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values and so can be safely used directly in entropy estimation. Our estimator is the first tensor-based estimator that exploits the underlying spatial Poisson process related to the histogram explicitly when estimating the probability density with low-rank tensor decompositions for the purpose of tensor completion. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.

42 ENGINEERING↗
DOE OSTI2025

A new method for diagnosing effective radiative forcing from aerosol–cloud interactions in climate models

Aerosol–cloud interactions (ACIs) are a leading source of uncertainty in estimates of the historical effective radiative forcing (ERF). One reason for this uncertainty is the difficulty in estimating the ERF from aerosol–cloud interactions (ERFaci) in climate models, which typically requires multiple calls to the radiation code. Most commonly used methods also cannot disentangle the contributions from different processes to ERFaci. Here, we develop a new, computationally efficient method for estimating the shortwave (SW) ERFaci from liquid clouds using histograms of monthly averaged cloud fraction partitioned by cloud droplet effective radius (r e ) and liquid water path (LWP). Multiplying the histograms with SW cloud radiative kernels gives the total SW ERFaci from liquid clouds, which can be decomposed into contributions from the Twomey effect, LWP adjustments, and cloud fraction (CF) adjustments. We test the method with data from five CMIP6-era models, using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument simulator to generate the histograms. Our method gives similar total SW ERFaci estimates to other established methods in regions of prevalent liquid cloud and indicates that the Twomey effect, LWP adjustments, and CF adjustments have contributed -0.34 ± 0.23, -0.22 ± 0.13, and -0.09 ± 0.11 W m -2 , respectively, to the effective radiative forcing of the climate since 1850 in the ensemble mean (95 % confidence). These results demonstrate that widespread adoption of a MODIS r e –LWP joint histogram diagnostic would allow the SW ERFaci and its components to be quickly and accurately diagnosed from climate model outputs, a crucial step for reducing uncertainty in the historical ERF.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Neutron camera employing row and column summations

For each photomultiplier tube in an Anger camera, an R.times.S array of preamplifiers is provided to detect electrons generated within the photomultiplier tube. The outputs of the preamplifiers are digitized to measure the magnitude of the signals from each preamplifier. For each photomultiplier tube, a corresponding summation circuitry including R row summation circuits and S column summation circuits numerically add the magnitudes of the signals from preamplifiers for each row and for each column to generate histograms. For a P.times.Q array of photomultiplier tubes, P.times.Q summation circuitries generate P.times.Q row histograms including R entries and P.times.Q column histograms including S entries. The total set of histograms include P.times.Q.times.(R+S) entries, which can be analyzed by a position calculation circuit to determine the locations of events (detection of a neutron).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Cylindrical Kernel Density Estimators For Monte Carlo Neutron Transport Reactor Physics Problems

Kernel Density Estimators (KDEs) have been investigated as an alternative to histogram tallies in Monte Carlo radiation transport simulations for capturing spatially-resolved quantities such as scalar flux and reaction rate densities. KDEs are non-parametric estimators that show potential for producing smooth estimates of quantities of interest with reduced variance compared to traditional histogram tallies. Furthermore, KDEs obtain estimates of the underlying distribution at user-defined points without requiring an underlying mesh, thus making KDEs an attractive potential alternative to histogram tallies. Recent work has introduced the Mean Free Path based KDE (MFP KDE) in order to capture distributions with large curvature at material interfaces, e.g. absorption reaction rates in UO{sub 2} fuel in light water reactors. However, the multivariate MFP KDE produces inaccuracies in the form of localized spikes in problems with material cross sections that contain large resonances. Since the MFP KDE works well in one dimension, it is hypothesized that a different MFP KDE formulation where the normalization coefficient only contains one factor of the cross section would be able to capture these distributions with large curvature without producing spikes in the estimate. This can be accomplished by using a cylindrical KDE whose 2-D support area is wedge-shaped and applying the MFP KDE to the radial component of the cylindrical KDE. These cylindrical KDEs use 2-D (r,θ) cylindrical coordinates with no dependence in axial dimension z. This paper derives the cylindrical KDE and the cylindrical MFP KDE and tests them on a reactor physics pin-cell benchmark problem, producing accurate estimates of flux and reaction rate densities with differences less than 0.5% when compared to a reference histogram. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

An Efficient Pipeline for Abdomen Segmentation in CT Images

Computed tomography (CT) scans usually include some disadvantages due to the nature of the imaging procedure, and these handicaps prevent accurate abdomen segmentation. Discontinuous abdomen edges, bed section of CT, patient information, closeness between the edges of the abdomen and CT, poor contrast, and a narrow histogram can be regarded as the most important handicaps that occur in abdominal CT scans. Currently, one or more handicaps can arise and prevent technicians obtaining abdomen images through simple segmentation techniques. In other words, CT scans can include the bed section of CT, a patient’s diagnostic information, low-quality abdomen edges, low-level contrast, and narrow histogram, all in one scan. These phenomena constitute a challenge, and an efficient pipeline that is unaffected by handicaps is required. In addition, analysis such as segmentation, feature selection, and classification has meaning for a real-time diagnosis system in cases where the abdomen section is directly used with a specific size. A statistical pipeline is designed in this study that is unaffected by the handicaps mentioned above. Intensity-based approaches, morphological processes, and histogram-based procedures are utilized to design an efficient structure. Performance evaluation is realized in experiments on 58 CT images (16 training, 16 test, and 26 validation) that include the abdomen and one or more disadvantage(s). The first part of the data (16 training images) is used to detect the pipeline’s optimum parameters, while the second and third parts are utilized to evaluate and to confirm the segmentation performance. The segmentation results are presented as the means of six performance metrics. Thus, the proposed method achieves remarkable average rates for training/test/validation of 98.95/99.36/99.57% (jaccard), 99.47/99.67/99.79% (dice), 100/99.91/99.91% (sensitivity), 98.47/99.23/99.85% (specificity), 99.38/99.63/99.87% (classification accuracy), and 98.98/99.45/99.66% (precision). In summary, a statistical pipeline performing the task of abdomen segmentation is achieved that is not affected by the disadvantages, and the most detailed abdomen segmentation study is performed for the use before organ and tumor segmentation, feature extraction, and classification.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

The role of nuclear medicine in assessments of cardiac dyssynchrony

Radionuclide imaging has an advantage for quantitative analyses of the tracer concentration and its temporal changes. Myocardial perfusion and function have been adapted for synchrony analyses. Extracted parameters have been demonstrated to measure ventricular synchrony and even to predict CRT outcomes. ERNA has the advantages of higher temporal resolution, greater reproducibility, and the volumetric analysis of both ventricles that can be applied for analyses of intraventricular synchrony and interventricular synchrony. Several software packages such as Quantitative Gated SPECT, the Emory Cardiac Toolbox, cardioREPO, and Heart Function View are available to assess the LV dyssynchrony parameters from GSPECT. A count-based method is applied to extract the amplitude and phase from each of the reconstructed GSPECT short-axis datasets throughout the cardiac cycle and then subjected to a Fourier analysis, the results of which are displayed on a polar map and histogram. Some of the parameters such as the bandwidth (expressed as the 95% width of the phase histogram) and the standard deviation of the phase are obtained by the phase histogram to assess the intraventricular synchrony. This review paper focuses on the application of the LV dyssynchrony parameters estimated by cardiac SPECT in patients with a heart disease.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

SAMBA: Sparse Approximation of Moment-Based Arbitrary Polynomial Chaos

A new arbitrary Polynomial Chaos (aPC) method is presented for moderately high-dimensional problems characterised by limited input data availability. The proposed methodology improves the algorithm of aPC and extends the method, that was previously only introduced as tensor product expansion, to moderately high-dimensional stochastic problems. The fundamental idea of aPC is to use the statistical moments of the input random variables to develop the polynomial chaos expansion. This approach provides the possibility to propagate continuous or discrete probability density functions and also histograms (data sets) as long as their moments exist, are finite and the determinant of the moment matrix is strictly positive. For cases with limited data availability, this approach avoids bias and fitting errors caused by wrong assumptions. In this work, an alternative way to calculate the aPC is suggested, which provides the optimal polynomials, Gaussian quadrature collocation points and weights from the moments using only a handful of matrix operations on the Hankel matrix of moments. It can therefore be implemented without requiring prior knowledge about statistical data analysis or a detailed understanding of the mathematics of polynomial chaos expansions. The extension to more input variables suggested in this work, is an anisotropic and adaptive version of Smolyak's algorithm that is solely based on the moments of the input probability distributions. It is referred to as SAMBA (PC), which is short for Sparse Approximation of Moment-Based Arbitrary Polynomial Chaos. It is illustrated that for moderately high-dimensional problems (up to 20 different input variables or histograms) SAMBA can significantly simplify the calculation of sparse Gaussian quadrature rules. SAMBA's efficiency for multivariate functions with regard to data availability is further demonstrated by analysing higher order convergence and accuracy for a set of nonlinear test functions with 2, 5 and 10 different input distributions or histograms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Is Molecular Rectification Caused by Asymmetric Electrode Couplings or by a Molecular Bias Drop?

In this study, we investigate possible causes of molecular rectification in electrode-molecule-electrode junctions. By using a simple model and simulated conductance histograms, we show that a molecular bias drop is responsible for rectification; conversely, asymmetric molecule electrode couplings do not directly result in rectification. Instead, the degree of coupling (a)symmetry can be observed in the line shapes of the conductance histograms used to experimentally assess the current voltage properties of such molecular junctions. Finally, more coupling asymmetry leads to less positively skewed histogram peaks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

“Plug-and-Play” potentials: Investigating quantum effects in (H{sub 2}){sub 2}–Li{sup +}–benzene

Quantum and anharmonic effects are investigated in (H{sub 2}){sub 2}–Li{sup +}–benzene, a model for hydrogen adsorption in metal-organic frameworks and carbon-based materials, using rigid-body diffusion Monte Carlo (RBDMC) simulations. The potential-energy surface (PES) is calculated as a modified Shepard interpolation of M05-2X/6-311+G(2df,p) electronic structure data. The RBDMC simulations yield zero-point energies (ZPE) and probability density histograms that describe the ground-state nuclear wavefunction. Binding a second H{sub 2} molecule to the H{sub 2}–Li{sup +}–benzene complex increases the ZPE of the system by 5.6 kJ mol{sup −1} to 17.6 kJ mol{sup −1}. This ZPE is 42% of the total electronic binding energy of (H{sub 2}){sub 2}–Li{sup +}–benzene and cannot be neglected. Our best estimate of the 0 K binding enthalpy of the second H{sub 2} to H{sub 2}–Li{sup +}–benzene is 7.7 kJ mol{sup −1}, compared to 12.4 kJ mol{sup −1} for the first H{sub 2} molecule. Anharmonicity is found to be even more important when a second (and subsequent) H{sub 2} molecule is adsorbed; use of harmonic ZPEs results in significant error in the 0 K binding enthalpy. Probability density histograms reveal that the two H{sub 2} molecules are found at larger distance from the Li{sup +} ion and are more confined in the θ coordinate than in H{sub 2}–Li{sup +}–benzene. They also show that both H{sub 2} molecules are delocalized in the azimuthal coordinate, ϕ. That is, adding a second H{sub 2} molecule is insufficient to localize the wavefunction in ϕ. Two fragment-based (H{sub 2}){sub 2}–Li{sup +}–benzene PESs are developed. These use a modified Shepard interpolation for the Li{sup +}–benzene and H{sub 2}–Li{sup +}–benzene fragments, and either modified Shepard interpolation or a cubic spline to model the H{sub 2}–H{sub 2} interaction. Because of the neglect of three-body H{sub 2}, H{sub 2}, Li{sup +} terms, both fragment PESs lead to overbinding of the second H{sub 2} molecule by 1.5 kJ mol{sup −1}. Probability density histograms, however, indicate that the wavefunctions for the two H{sub 2} molecules are effectively identical on the “full” and fragment PESs. This suggests that the 1.5 kJ mol{sup −1} error is systematic over the regions of configuration space explored by our simulations. Notwithstanding this, modified Shepard interpolation of the weak H{sub 2}–H{sub 2} interaction is problematic and we obtain more accurate results, at considerably lower computational cost, using a cubic spline interpolation. Indeed, the ZPE of the fragment-with-spline PES is identical, within error, to the ZPE of the full PES. This fragmentation scheme therefore provides an accurate and inexpensive method to study higher hydrogen loading in this and similar systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Characterizing the Stability of NISQ Devices

In this study, we focus on the question of stability of NISQ devices. The parameters that define the device stability profile are motivated by the work of DiVincenzo in [9] where the requirements for physical implementation of quantum computing are discussed. We develop the metrics and theoretical framework to quantify the DiVincenzo requirements and study the stability of those key metrics. The basis of our assessment is histogram similarity (in time and space). For identical experiments, devices which produce reproducible histograms in time, and similar histograms in space, are considered more reliable. To investigate such reliability concerns robustly, we propose a moment-based distance (MBD) metric. We illustrate our methodology using data collected from IBM's Yorktown device. Two types of assessments are discussed: spatial stability and temporal stability.

Dasgupta, Samudra↗
DOE OSTI2014

Effects of reflector and crystal surface on the performance of a depth-encoding PET detector with dual-ended readout

Purpose: Depth encoding detectors are required to improve the spatial resolution and spatial resolution uniformity of small animal positron emission tomography (PET) scanners, as well as dedicated breast and brain scanners. Depth of interaction (DOI) can be measured by using dual-ended readout of lutetium oxyorthosilicate (LSO) scintillator arrays with position-sensitive avalanche photodiodes. Inter-crystal reflectors and crystal surface treatments play important roles in determining the performance of dual-ended detectors. In this paper, the authors evaluated five LSO arrays made with three different intercrystal reflectors and with either polished or unpolished crystal surfaces. Methods: The crystal size in all arrays was 1.5 mm, which is typical of the detector size used in small animal and dedicated breast scanners. The LSO arrays were measured with dual-ended readout and were compared in terms of flood histogram, energy resolution, and DOI resolution performance. Results: The four arrays using enhanced specular reflector (ESR) and Toray reflector provided similar quality flood histograms and the array using Crystal Wrap reflector gave the worst flood histogram. The two arrays using ESR reflector provided the best energy resolution and the array using Crystal Wrap reflector yielded the worst energy resolution. All arrays except the polished ESR array provided good DOI resolution ranging from 1.9 mm to 2.9 mm. DOI resolution improved as the gradient in light collection efficiency with depth (GLCED) increased. The geometric mean energies were also calculated for these dual-ended readout detectors as an alternative to the conventional summed total energy. It was shown that the geometric mean energy is advantageous in that it provides more uniform photopeak amplitude at different depths for arrays with high GLCED, and is beneficial in event selection by allowing a fixed energy window independent of depth. A new method of DOI calculation that improved the linearity of DOI ratio vs depth and simplifies the DOI calibration procedure also was developed and tested. Conclusions: The results of these studies provide useful guidance in selecting the proper reflectors and crystal surface treatments when LSO arrays are used for high-resolution PET applications in small animal scanners or dedicated breast and brain scanners.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-F-CAMPUS-J-01: Dosimetric Effects of HU Changes During the Course of Proton Therapy for Lung Cancer

Purpose: To characterize the changes in Hounsfield unit (HU) in lung radiotherapy with proton beams during the course of treatment and to study the effect on the proton plan dose distribution. Methods: Twenty consecutive patients with non-small cell lung cancer treated with proton radiotherapy who underwent multiple CT scans including the planning CT and weekly verification CTs were studied. HU histograms were computed for irradiated lung volumes in beam paths for all scans using the same treatment plan. Histograms for un-irradiated lung volume were used as control to characterize inter-scan variations. HU statistics were calculated for both irradiated and un-irradiated lung volumes for each patient scan. Further, multiple CT scans based on the same planning CT were generated by replacing the HU of the lung based on the verification CT scans HU values. Using the same beam arrangement, we created plans for each of the altered CT scans to study the dosimetric effect using the dose volume histogram. Results: Lung HU decreased for irradiated lung volume during the course of radiotherapy. The magnitude of this change increased with total irradiation dose. On average, HU changed by −53.8 in the irradiated volume. This change resulted in less than 0.5mm of beam overshoot in tissue for every 1cm beam traversed in the irradiated lung. The dose modification is about +3% for the lung, and less than +1% for the primary tumor. Conclusion: HU of the lung decrease throughout the course of radiation therapy. This change results in a beam overshoot (e.g. 3mm for 6cm of lung traversed) and causes a small dose modification in the overall plan. However, this overshoot does not affect the quality of plans since the margins used in planning, based on proton range uncertainty, are greater. HU needs to change by 150 units before re-planning is warranted.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

A method for normalizing pathology images to improve feature extraction for quantitative pathology

Purpose: With the advent of digital slide scanning technologies and the potential proliferation of large repositories of digital pathology images, many research studies can leverage these data for biomedical discovery and to develop clinical applications. However, quantitative analysis of digital pathology images is impeded by batch effects generated by varied staining protocols and staining conditions of pathological slides. Methods: To overcome this problem, this paper proposes a novel, fully automated stain normalization method to reduce batch effects and thus aid research in digital pathology applications. Their method, intensity centering and histogram equalization (ICHE), normalizes a diverse set of pathology images by first scaling the centroids of the intensity histograms to a common point and then applying a modified version of contrast-limited adaptive histogram equalization. Normalization was performed on two datasets of digitized hematoxylin and eosin (H&E) slides of different tissue slices from the same lung tumor, and one immunohistochemistry dataset of digitized slides created by restaining one of the H&E datasets. Results: The ICHE method was evaluated based on image intensity values, quantitative features, and the effect on downstream applications, such as a computer aided diagnosis. For comparison, three methods from the literature were reimplemented and evaluated using the same criteria. The authors found that ICHE not only improved performance compared with un-normalized images, but in most cases showed improvement compared with previous methods for correcting batch effects in the literature. Conclusions: ICHE may be a useful preprocessing step a digital pathology image processing pipeline.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

SU-F-R-20: Image Texture Features Correlate with Time to Local Failure in Lung SBRT Patients

Purpose: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).Methods and Materials: From an IRB-approved lung SBRT registry for patients treated between 2009–2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7.1 months. Physician-contoured gross tumor volumes (GTV) on the planning CT images were processed and 3D gray-level co-occurrence matrix (GLCM) based texture and histogram features were calculated in Matlab. Data were exported to R and a multiple linear regression model was used to examine the relationship between texture features and time-to-local-failure. Results: Multiple linear regression revealed that entropy (p=0.0233, multiple R2=0.60) from GLCM-based texture analysis and the standard deviation (p=0.0194, multiple R2=0.60) from the histogram-based features were statistically significantly correlated with the time-to-local-failure. Conclusion: Image-based texture analysis can be used to predict certain aspects of treatment outcomes of NSCLC patients treated with SBRT. We found entropy and standard deviation calculated for the GTV on the CT images displayed a statistically significant correlation with and time-to-local-failure in lung SBRT patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-94: Development of a Plug-in Based Image Analysis Tool for Integration Into Treatment Planning

Purpose: To extend the functionality of a commercial treatment planning system (TPS) to support (i) direct use of quantitative image-based metrics within treatment plan optimization and (ii) evaluation of dose-functional volume relationships to assist in functional image adaptive radiotherapy. Methods: A script was written that interfaces with a commercial TPS via an Application Programming Interface (API). The script executes a program that performs dose-functional volume analyses. Written in C#, the script reads the dose grid and correlates it with image data on a voxel-by-voxel basis through API extensions that can access registration transforms. A user interface was designed through WinForms to input parameters and display results. To test the performance of this program, image- and dose-based metrics computed from perfusion SPECT images aligned to the treatment planning CT were generated, validated, and compared. Results: The integration of image analysis information was successfully implemented as a plug-in to a commercial TPS. Perfusion SPECT images were used to validate the calculation and display of image-based metrics as well as dose-intensity metrics and histograms for defined structures on the treatment planning CT. Various biological dose correction models, custom image-based metrics, dose-intensity computations, and dose-intensity histograms were applied to analyze the image-dose profile. Conclusion: It is possible to add image analysis features to commercial TPSs through custom scripting applications. A tool was developed to enable the evaluation of image-intensity-based metrics in the context of functional targeting and avoidance. In addition to providing dose-intensity metrics and histograms that can be easily extracted from a plan database and correlated with outcomes, the system can also be extended to a plug-in optimization system, which can directly use the computed metrics for optimization of post-treatment tumor or normal tissue response models. Supported by NIH - P01 - CA059827.

60 APPLIED LIFE SCIENCES↗