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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-C-207A-07: Cumulative 18F-FDG Uptake Histogram Relative to Radiation Dose Volume Histogram of Lung After IMRT Or PSPT and Their Association with Radiation Pneumonitis

Purpose: To determine whether the difference in cumulative 18F-FDG uptake histogram of lung treated with either IMRT or PSPT is associated with radiation pneumonitis (RP) in patients with inoperable stage II and III NSCLC. Methods: We analyzed 24 patients from a prospective randomized trial to compare IMRT (n=12) with vs. PSPT (n=12) for inoperable NSCLC. All patients underwent PET-CT imaging between 35 and 88 days post-therapy. Post-treatment PET-CT was aligned with planning 4D CT to establish a voxel-to-voxel correspondence between post-treatment PET and planning dose images. 18F-FDG uptake as a function of radiation dose to normal lung was obtained for each patient. Distribution of the standard uptake value (SUV) was analyzed using a volume histogram method. The image quantitative characteristics and DVH measures were correlated with clinical symptoms of pneumonitis. Results: Patients with RP were present in both groups: 5 in the IMRT and 6 in the PSPT. The analysis of cumulative SUV histograms showed significantly higher relative volumes of the normal lung having higher SUV uptake in the PSPT patients for both symptomatic and asymptomatic cases (VSUV=2: 10% for IMRT vs 16% for proton RT and VSUV=1: 10% for IMRT vs 23% for proton RT). In addition, the SUV histograms for symptomatic cases in PSPT patients exhibited a significantly longer tail at the highest SUV. The absolute volume of the lung receiving the dose >70 Gy was larger in the PSPT patients. Conclusion: 18F-FDG uptake – radiation dose response correlates with RP in both groups of patients by means of the linear regression slope. SUV is higher for the PSPT patients for both symptomatic and asymptomatic cases. Higher uptake after PSPT patients is explained by larger volumes of the lung receiving high radiation dose.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-BRC-08: Evaluation of Dose Mass Histogram as a More Representative Dose Description Method Than Dose Volume Histogram in Lung Cancer Patients

Purpose: Dose-volume-histogram (DVH) is widely used for plan evaluation in radiation treatment. The concept of dose-mass-histogram (DMH) is expected to provide a more representative description as it accounts for heterogeneity in tissue density. This study is intended to assess the difference between DVH and DMH for evaluating treatment planning quality. Methods: 12 lung cancer treatment plans were exported from the treatment planning system. DVHs for the planning target volume (PTV), the normal lung and other structures of interest were calculated. DMHs were calculated in a similar way as DVHs expect that the voxel density converted from the CT number was used in tallying the dose histogram bins. The equivalent uniform dose (EUD) was calculated based on voxel volume and mass, respectively. The normal tissue complication probability (NTCP) in relation to the EUD was calculated for the normal lung to provide quantitative comparison of DVHs and DMHs for evaluating the radiobiological effect. Results: Large differences were observed between DVHs and DMHs for lungs and PTVs. For PTVs with dense tumor cores, DMHs are higher than DVHs due to larger mass weighing in the high dose conformal core regions. For the normal lungs, DMHs can either be higher or lower than DVHs depending on the target location within the lung. When the target is close to the lower lung, DMHs show higher values than DVHs because the lower lung has higher density than the central portion or the upper lung. DMHs are lower than DVHs for targets in the upper lung. The calculated NTCPs showed a large range of difference between DVHs and DMHs. Conclusion: The heterogeneity of lung can be well considered using DMH for evaluating target coverage and normal lung pneumonitis. Further studies are warranted to quantify the benefits of DMH over DVH for plan quality evaluation.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1976

AHIMSA - Ad hoc histogram information measure sensing algorithm for feature selection in the context of histogram inspired clustering techniques

An algorithm is proposed for dimensionality reduction in the context of clustering techniques based on histogram analysis. The approach is based on an evaluation of the hills and valleys in the unidimensional histograms along the different features and provides an economical means of assessing the significance of the features in a nonparametric unsupervised data environment. The method has relevance to remote sensing applications.

Dasarathy, B. V.↗
NASA NTRS2006

Using the Bootstrap Method for a Statistical Significance Test of Differences between Summary Histograms

A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries-Matusita distance and the Kuiper distance. The data used in testing the bootstrap method are satellite measurements of cloud systems called cloud objects. Each cloud object is defined as a contiguous region/patch composed of individual footprints or fields of view. A histogram of measured values over footprints is generated for each parameter of each cloud object and then summary histograms are accumulated over all individual histograms in a given cloud-object size category. The results of statistical hypothesis tests using all three distances as test statistics are generally similar, indicating the validity of the proposed method. The Euclidean distance is determined to be most suitable after comparing the statistical tests of several parameters with distinct probability distributions among three cloud-object size categories. Impacts on the statistical significance levels resulting from differences in the total lengths of satellite footprint data between two size categories are also discussed.

Xu, Kuan-Man↗
DOE OSTI2016

Histogram Analysis of CT Perfusion of Hepatocellular Carcinoma for Predicting Response to Transarterial Radioembolization: Value of Tumor Heterogeneity Assessment

PurposeTo evaluate in patients with hepatocellular carcinoma (HCC), whether assessment of tumor heterogeneity by histogram analysis of computed tomography (CT) perfusion helps predicting response to transarterial radioembolization (TARE).Materials and MethodsSixteen patients (15 male; mean age 65 years; age range 47–80 years) with HCC underwent CT liver perfusion for treatment planning prior to TARE with Yttrium-90 microspheres. Arterial perfusion (AP) derived from CT perfusion was measured in the entire tumor volume, and heterogeneity was analyzed voxel-wise by histogram analysis. Response to TARE was evaluated on follow-up imaging (median follow-up, 129 days) based on modified Response Evaluation Criteria in Solid Tumors (mRECIST). Results of histogram analysis and mean AP values of the tumor were compared between responders and non-responders. Receiver operating characteristics were calculated to determine the parameters’ ability to discriminate responders from non-responders.ResultsAccording to mRECIST, 8 patients (50 %) were responders and 8 (50 %) non-responders. Comparing responders and non-responders, the 50th and 75th percentile of AP derived from histogram analysis was significantly different [AP 43.8/54.3 vs. 27.6/34.3 mL min{sup −1} 100 mL{sup −1}); p < 0.05], while the mean AP of HCCs (43.5 vs. 27.9 mL min{sup −1} 100 mL{sup −1}; p > 0.05) was not. Further heterogeneity parameters from histogram analysis (skewness, coefficient of variation, and 25th percentile) did not differ between responders and non-responders (p > 0.05). If the cut-off for the 75th percentile was set to an AP of 37.5 mL min{sup −1} 100 mL{sup −1}, therapy response could be predicted with a sensitivity of 88 % (7/8) and specificity of 75 % (6/8).ConclusionVoxel-wise histogram analysis of pretreatment CT perfusion indicating tumor heterogeneity of HCC improves the pretreatment prediction of response to TARE.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Microscopic theory, analysis, and interpretation of conductance histograms in molecular junctions

Molecular electronics break-junction experiments are widely used to investigate fundamental physics and chemistry at the nanoscale. Reproducibility in these experiments relies on measuring conductance on thousands of freshly formed molecular junctions, yielding a broad histogram of conductance events. Experiments typically focus on the most probable conductance, while the information content of the conductance histogram has remained unclear. Here we develop a microscopic theory for the conductance histogram by merging the theory of force-spectroscopy with molecular conductance. The procedure yields analytical equations that accurately fit the conductance histogram of a wide range of molecular junctions and augments the information content that can be extracted from them. Our formulation captures contributions to the conductance dispersion due to conductance changes during the mechanical elongation inherent to the experiments. In turn, the histogram shape is determined by the non-equilibrium stochastic features of junction rupture and formation. The microscopic parameters in the theory capture the junction’s electromechanical properties and can be isolated from separate conductance and rupture force (or junction-lifetime) measurements. The predicted behavior can be used to test the range of validity of the theory, understand the conductance histograms, design molecular junction experiments with enhanced resolution and molecular devices with more reproducible conductance properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

SU-F-R-50: Radiation-Induced Changes in CT Number Histogram During Chemoradiation Therapy for Pancreatic Cancer

Purpose: In an effort of early assessment of treatment response, we investigate radiation induced changes in CT number histogram of GTV during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Methods: Diagnostic-quality CT data acquired daily during routine CT-guided CRT using a CT-on-rails for 20 pancreatic head cancer patients were analyzed. All patients were treated with a radiation dose of 50.4 in 28 fractions. On each daily CT set, the contours of the pancreatic head and the spinal cord were delineated. The Hounsfiled Units (HU) histogram in these contourswere extracted and processed using MATLAB. Eight parameters of the histogram including the mean HU over all the voxels, peak position, volume, standard deviation (SD), skewness, kurtosis, energy, and entropy were calculated for each fraction. The significances were inspected using paired two-tailed t-test and the correlations were analyzed using Spearman rank correlation tests. Results: In general, HU histogram in pancreatic head (but not in spinal cord) changed during the CRT delivery. Changes from the first to the last fraction in mean HU in pancreatic head ranged from −13.4 to 3.7 HU with an average of −4.4 HU, which was significant (P<0.001). Among other quantities, the volume decreased, the skewness increased (less skewed), and the kurtosis decreased (less sharp) during the CRT delivery. The changes of mean HU, volume, skewness, and kurtosis became significant after two weeks of treatment. Patient pathological response status is associated with the changes of SD (ΔSD), i.e., ΔSD= 1.85 (average of 7 patients) for good reponse, −0.08 (average of 6 patients) for moderate and poor response. Conclusion: Significant changes in HU histogram and the histogram-based metrics (e.g., meam HU, skewness, and kurtosis) in tumor were observed during the course of chemoradiation therapy for pancreas cancer. These changes may be potentially used for early assessment of treatment response.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1991

Time-cumulated visible and infrared radiance histograms used as descriptors of surface and cloud variations

The spatial and temporal stability of the distributions of satellite-measured visible and infrared radiances, caused by variations in clouds and surfaces, are investigated using bidimensional and monodimensional histograms and time-composite images. Similar analysis of the histograms of the original and time-composite images provides separation of the contributions of the space and time variations to the total variations. The variability of both the surfaces and clouds is found to be larger at scales much larger than the minimum resolved by satellite imagery. This study shows that the shapes of these histograms are distinctive characteristics of the different climate regimes and that particular attributes of these histograms can be related to several general, though not universal, properties of clouds and surface variations at regional and synoptic scales. There are also significant exceptions to these relationships in particular climate regimes. The characteristics of these radiance histograms provide a stable well defined descriptor of the cloud and surface properties.

Seze, Genevieve↗
NASA NTRS2005

Comparison of Histograms for Use in Cloud Observation and Modeling

Cloud observation and cloud modeling data can be presented in histograms for each characteristic to be measured. Combining information from single-cloud histograms yields a summary histogram. Summary histograms can be compared to each other to reach conclusions about the behavior of an ensemble of clouds in different places at different times or about the accuracy of a particular cloud model. As in any scientific comparison, it is necessary to decide whether any apparent differences are statistically significant. The usual methods of deciding statistical significance when comparing histograms do not apply in this case because they assume independent data. Thus, a new method is necessary. The proposed method uses the Euclidean distance metric and bootstrapping to calculate the significance level.

Green, Lisa↗
NASA NTRS2011

Color Histogram Diffusion for Image Enhancement

Various color histogram equalization (CHE) methods have been proposed to extend grayscale histogram equalization (GHE) for color images. In this paper a new method called histogram diffusion that extends the GHE method to arbitrary dimensions is proposed. Ranges in a histogram are specified as overlapping bars of uniform heights and variable widths which are proportional to their frequencies. This diagram is called the vistogram. As an alternative approach to GHE, the squared error of the vistogram from the uniform distribution is minimized. Each bar in the vistogram is approximated by a Gaussian function. Gaussian particles in the vistoram diffuse as a nonlinear autonomous system of ordinary differential equations. CHE results of color images showed that the approach is effective.

Kim, Taemin↗
DOE OSTI2017

Novel Histogram Based Unsupervised Classification Technique to Determine Natural Classes From Biophysically Relevant Fit Parameters to Hyperspectral Data

Hyperspectral image analysis has benefited from an array of methods that take advantage of the increased spectral depth compared to multispectral sensors; however, the focus of these developments has been on supervised classification methods. Lack of a priori knowledge regarding land cover characteristics can make unsupervised classification methods preferable under certain circumstances. An unsupervised classification technique is presented in this paper that utilizes physically relevant basis functions to model the reflectance spectra. These fit parameters used to generate the basis functions allow clustering based on spectral characteristics rather than spectral channels and provide both noise and data reduction. Histogram splitting of the fit parameters is then used as a means of producing an unsupervised classification. Unlike current unsupervised classification techniques that rely primarily on Euclidian distance measures to determine similarity, the unsupervised classification technique uses the natural splitting of the fit parameters associated with the basis functions creating clusters that are similar in terms of physical parameters. The data set used in this work utilizes the publicly available data collected at Indian Pines, Indiana. This data set provides reference data allowing for comparisons of the efficacy of different unsupervised data analysis. The unsupervised histogram splitting technique presented in this paper is shown to be better than the standard unsupervised ISODATA clustering technique with an overall accuracy of 34.3/19.0% before merging and 40.9/39.2% after merging. Finally, this improvement is also seen as an improvement of kappa before/after merging of 24.8/30.5 for the histogram splitting technique compared to 15.8/28.5 for ISODATA.

58 GEOSCIENCES↗
DOE OSTI2016

TH-CD-209-03: Feasibility of CBCT-Based Proton Dose Calculation Using a Histogram-Matching Algorithm in Proton Beam Therapy

Purpose: The aim of this study was to confirm On-Board Imager cone-beam computed tomography (CBCT) using a histogram-matching algorithm as a useful method for proton dose calculation in head and neck radiotherapy. Methods: We studied one head and neck phantom and ten patients with head and neck cancer treated using intensity-modulated radiation therapy (IMRT) and proton beam therapy. We modified Hounsfield unit (HU) values of CBCT (mCBCT) using a histogram-matching algorithm. In order to evaluate the accuracy of the proton dose calculation, we compared dose differences in dosimetric parameters (Dmean) for clinical target volume (CTV), planning target volume (PTV) and left parotid and proton ranges (PR) between the planning CT (reference) and CBCT or mCBCT, and gamma passing rates of CBCT and mCBCT. To minimize the effect of organ deformation, we also performed image registration. Results: For patients, the average differences in Dmean for CTV, PTV, and left parotid between planning CT and CBCT were 1.63 ± 2.34%, 3.30 ± 1.02%, and 5.42 ± 3.06%, respectively. Similarly, the average differences between planning CT and mCBCT were 0.20 ± 0.19%, 0.58 ±0.43%, and 3.53 ±2.40%, respectively. The average differences in PR between planning CT and CBCT or mCBCT of a 50° beam for ten patients were 2.1 ± 2.1 mm and 0.3 ± 0.5 mm, respectively. Similarly, the average differences in PR of a 120° beam were 2.9 ± 2.6 mm and 1.1 ± 0.9 mm, respectively. The average dose and PR differences of mCBCT were smaller than those of CBCT. Additionally, the average gamma passing rates of mCBCT were larger than those of CBCT. Conclusion: We evaluated the accuracy of the proton dose calculation in CBCT and mCBCT with the image registration for ten patients. Our results showed that HU modification using a histogram-matching algorithm could improve the accuracy of the proton dose calculation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Open Radiation Monitoring: Histogram Builder Module Design

The Open Radiation Monitoring Project seeks to develop and demonstrate a modular radiation detection architecture designed specifically for use in arms control treaty verification (ACTV) applications that will facilitate rapid development of trusted systems to meet the needs of potential future treaties. A modular architecture can be used to reduce more complex systems to a series of single purpose building blocks, thereby facilitating equipment inspection and in turn building trust in the equipment by all treaty parties. Furthermore, a modular architecture can be used to control data flow within the measurement system, reducing the risk of "hidden switches" and constraining the amount of sensitive information that could potentially be inadvertently leaked. This report details the first revision of a prototype circuit that will convert analog pulses directly into a histogrammed data set for further processing. The circuit was designed with both spectroscopy and multiplicity analysis in mind but can, in principle, be used to reduce any raw data stream into a histogram. The number of output channels is limited, and the histogram bin ranges are user configurable to allow for non-uniform and discontinuous bins, which makes it possible to restrict the information being passed down stream if desired. Pulse processing relies entirely on analog circuitry and non- programmable logic, which enables operation without the need for a central processor or other programmable control unit. The circuit remains untested under the Open Radiation Monitoring project due to the closure of the sponsoring program. However, further development and testing is scheduled to take place in support of a purpose-built trusted verification system development effort known as COGNIZANT, which demonstrates the potential benefit of developing a suite of modular trusted system components.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1983

Histogram deconvolution - An aid to automated classifiers

It is shown that N-dimensional histograms are convolved by the addition of noise in the picture domain. Three methods are described which provide the ability to deconvolve such noise-affected histograms. The purpose of the deconvolution is to provide automated classifiers with a higher quality N-dimensional histogram from which to obtain classification statistics.

Lorre, J. J.↗
DOE OSTI2016

Uncertainties in the Standard Moments, the Derivation of the Y1 to Y8 parameters, and the Derivation of w 1 to w 8 for Feynman Histograms

Momentum is a neutron multiplicity analysis software package that calculates a variety of parameters associated with Feynman histograms. While most of these parameters are documented in Cifarelli and Smith-Nelson, there are some parameters which are not. Most prominent of these are the uncertainties in the standard moments, and this paper will explicitly document these parameters. This paper will also document the higher-order Y n parameters and their associated ω n functions because they may be useful for future applications. The generation of what is referred to as Feynman histograms is not explained here.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Temporal Evolution and Dose-Volume Histogram Predictors of Visual Acuity After Proton Beam Radiation Therapy of Uveal Melanoma

Purpose: To perform an in-depth temporal analysis of visual acuity (VA) outcomes after proton beam radiation therapy (PBRT) in a large, uniformly treated cohort of uveal melanoma (UM) patients, to determine trends in VA evolution depending on pretreatment and temporally defined posttreatment VA measurements; and to investigate the relevance of specific patient, tumor and dose-volume parameters to posttreatment vision loss. Methods and Materials: Uveal melanoma patients receiving PBRT were identified from a prospectively maintained database. Included patients (n=645) received 56 GyE in 4 fractions, had pretreatment best corrected VA (BCVA) in the affected eye of count fingers (CF) or better, with posttreatment VA assessment at specified post-PBRT time point(s). Patients were grouped according to the pretreatment BCVA into favorable (≥20/40) or unfavorable (20/50-20/400) and poor (CF) strata. Temporal analysis of BCVA changes was described, and univariate and forward stepwise multivariate logistic regression analyses were performed to identify predictors for VA loss. Results: Median VA follow-up was 53 months (range, 3-213 months). At 60-month follow up, among evaluable treated eyes with favorable pretreatment BCVA, 45% retained BCVA ≥20/40, whereas among evaluable treated eyes with initially unfavorable/poor BCVA, 21% had vision ≥20/100. Among those with a favorable initial BCVA, attaining BCVA of ≥20/40 at any posttreatment time point was associated with subsequent maintenance of excellent BCVA. Multivariate analysis identified volume of the macula receiving 28GyE (P<.0001) and optic nerve (P=.0004) as independent dose-volume histogram predictors of 48-month post-PBRT vision loss among initially favorable treated eyes. Conclusions: Approximately half of PBRT-treated UM eyes with excellent pretreatment BCVA assessed at 5 years after treatment will retain excellent long-term vision. 28GyE macula and optic nerve dose-volume histogram parameters allow for rational treatment planning optimization that may lead to improved visual outcomes. The detailed temporal analysis with intermediate as well as long-term functional prognosis, and the relationship of outcomes with clinical and treatment planning parameters, is critical for informed care of UM patients before and after PBRT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Machine learning using host/guest energy histograms to predict adsorption in metal–organic frameworks: Application to short alkanes and Xe/Kr mixtures

A machine learning (ML) methodology that uses a histogram of interaction energies has been applied to predict gas adsorption in metal–organic frameworks (MOFs) using results from atomistic grand canonical Monte Carlo (GCMC) simulations as training and test data. In this work, the method is first extended to binary mixtures of spherical species, in particular, Xe and Kr. In addition, it is shown that single-component adsorption of ethane and propane can be predicted in good agreement with GCMC simulation using a histogram of the adsorption energies felt by a methyl probe in conjunction with the random forest ML method. Here, the results for propane can be improved by including a small number of MOF textural properties as descriptors. We also discuss the most significant features, which provides physical insight into the most beneficial adsorption energy sites for a given application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Flux Histograms for 2017 Analysis

Flux for 2017 Analysis histograms for FHC and RHC:- The fluxes are integrated over the fiducial volume limited by -176 < X <177, -172 < Y < 179 and 25 < Z < 1150 cm. The fluxes are PPFX corrected, and both, the hadron production and focusing systematics are included (see docs 23441 and 17608 for more details).- These fluxes have been made with the official FHC (RHC) ND MC CAFAna files using the function DeriveFlux from CAFAna/XSec/Flux.*.- The root files have two types of histograms: flux_N and fractional_uncertainty_N, where N is the neutrino type. The entries are normalized by 10^6 POT, m2 and the bin width.- The text files contain tables of the flux normalized by 10^6 POT and m2.- The fractional uncertainties are made by the hadron production and beam focusing uncertainties added in quadrature. This corresponds to the sigma fraction respect to the central value and it meant to be used to make an uncertainty band (the covariance matrix is not included yet).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗