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At least 595 records · Page 33

TU-A-12A-04: Quantitative Texture Features Calculated in Lung Tissue From CT Scans Demonstrate Consistency Between Two Databases From Different Institutions

Purpose: To evaluate the consistency of computed tomography (CT) scan texture features, previously identified as stable in a healthy patient cohort, in esophageal cancer patient CT scans. Methods: 116 patients receiving radiation therapy (median dose: 50.4Gy) for esophageal cancer were retrospectively identified. For each patient, diagnostic-quality pre-therapy (0-183 days) and post-therapy (5-120 days) scans (mean voxel size: 0.8mm×0.8mm×2.5mm) and a treatment planning scan and associated dose map were collected. An average of 501 32x32-pixel ROIs were placed randomly in the lungs of each pre-therapy scan. ROI centers were mapped to corresponding locations in post-therapy and planning scans using the displacement vector field output by demons deformable registration. Only ROIs with mean dose <5Gy were analyzed, as these were expected to contain minimal post-treatment damage. 140 texture features were calculated in pre-therapy and post-therapy scan ROIs and compared using Bland-Altman analysis. For each feature, the mean feature value change and the distance spanned by the 95% limits of agreement were normalized to the mean feature value, yielding normalized range of agreement (nRoA) and normalized bias (nBias). Using Wilcoxon signed rank tests, nRoA and nBias were compared with values computed previously in 27 healthy patient scans (mean voxel size: 0.67mm×0.67mm×1mm) acquired at a different institution. Results: nRoA was significantly (p<0.001) larger in cancer patients than healthy patients. Differences in nBias were not significant (p=0.23). The 20 features identified previously as having nRoA<20% for healthy patients had the lowest nRoA values in the current database, with an average increase of 5.6%. Conclusion: Despite differences in CT scanner type, scan resolution, and patient health status, the same 20 features remained stable (i.e., low variability and bias) in the absence of disease changes for databases from two institutions. Identification of these features is the first step towards quantifying radiation-induced changes between preand post-therapy scans. Supported, in part, by NIH Grant Nos. S10 RR021039, and P30 CA14599, the Virginia and D. K. Ludwig Fund for Cancer Research, Imaging Research Institute, Biological Sciences Division, The University of Chicago, and The Institute for Translational Medicine Pilot Award, The University of Chicago.

60 APPLIED LIFE SCIENCES↗

TU-F-18C-09: Mammogram Surveillance Using Texture Analysis for Breast Cancer Patients After Radiation Therapy

Purpose: To study the feasibility of applying cancer risk model established from treated patients to predict the risk of recurrence on follow-up mammography after radiation therapy for both ipsilateral and contralateral breast. Methods: An extensive set of textural feature functions was applied to a set of 196 Mammograms from 50 patients. 56 Mammograms from 28 patients were used as training set, 44 mammograms from 22 patients were used as test set and the rest were used for prediction. Feature functions include Histogram, Gradient, Co-Occurrence Matrix, Run-Length Matrix and Wavelet Energy. An optimum subset of the feature functions was selected by Fisher Coefficient (FO) or Mutual Information (MI) (up to top 10 features) or a method combined FO, MI and Principal Component (FMP) (up to top 30 features). One-Nearest Neighbor (1-NN), Linear Discriminant Analysis (LDA) and Nonlinear Discriminant Analysis (NDA) were utilized to build a risk model of breast cancer from the training set of mammograms at the time of diagnosis. The risk model was then used to predict the risk of recurrence from mammogram taken one year and three years after RT. Results: FPM with NDA has the best classification power in classifying the training set of the mammogram with lesions versus those without lesions. The model of FPM with NDA achieved a true positive (TP) rate of 82% compared to 45.5% of using FO with 1-NN. The best false positive (FP) rates were 0% and 3.6% in contra-lateral breast of 1-year and 3-years after RT, and 10.9% in ipsi-lateral breast of 3-years after RT. Conclusion: Texture analysis offers high dimension to differentiate breast tissue in mammogram. Using NDA to classify mammogram with lesion from mammogram without lesion, it can achieve rather high TP and low FP in the surveillance of mammogram for patient with conservative surgery combined RT.

60 APPLIED LIFE SCIENCES↗

TU-F-12A-09: GLCM Texture Analysis for Normal-Tissue Toxicity: A Prospective Ultrasound Study of Acute Toxicity in Breast-Cancer Radiotherapy

Purpose: To evaluate the morphologic and structural integrity of the breast glands using sonographic textural analysis, and identify potential early imaging signatures for radiation toxicity following breast-cancer radiotherapy (RT). Methods: Thirty-eight patients receiving breast RT participated in a prospective ultrasound imaging study. Each participant received 3 ultrasound scans: 1 week before RT (baseline), and at 6-week and 3-month follow-ups. Patients were imaged with a 10-MHz ultrasound on the four quadrant of the breast. A second order statistical method of texture analysis, called gray level co-occurrence matrix (GLCM), was employed to assess RT-induced breast-tissue toxicity. The region of interest (ROI) was 28 mm × 10 mm in size at a 10 mm depth under the skin. Twenty GLCM sonographic features, ratios of the irradiated breast and the contralateral breast, were used to quantify breast-tissue toxicity. Clinical assessment of acute toxicity was conducted using the RTOG toxicity scheme. Results: Ninety-seven ultrasound studies (776 images) were analyzed; and 5 out of 20 sonographic features showed significant differences (p < 0.05) among the baseline scans, the acute toxicity grade 1 and 2 groups. These sonographic features quantified the degree of tissue damage through homogeneity, heterogeneity, randomness, and symmetry. Energy ratio value decreased from 108±0.05 (normal) to 0.99±0.05 (Grade 1) and 0.84±0.04 (Grade 2); Entropy ratio value increased from 1.01±0.01 to 1.02±0.01 and 1.04±0.01; Contrast ratio value increased from 1.03±0.03 to 1.07±0.06 and 1.21±0.09; Variance ratio value increased from 1.06±0.03 to 1.20±0.04 and 1.42±0.10; Cluster Prominence ratio value increased from 0.98±0.02 to 1.01±0.04 and 1.25±0.07. Conclusion: This work has demonstrated that the sonographic features may serve as imaging signatures to assess radiation-induced normal tissue damage. While these findings need to be validated in a larger cohort, they suggest that ultrasound imaging may be used to improve early detection of normal-tissue toxicity in breast-cancer RT.

60 APPLIED LIFE SCIENCES↗

Three-dimensional texture analysis of contrast enhanced CT images for treatment response assessment in Hodgkin lymphoma: Comparison with F-18-FDG PET

Purpose: To determine the diagnostic performance of three-dimensional (3D) texture analysis (TA) of contrast-enhanced computed tomography (CE-CT) images for treatment response assessment in patients with Hodgkin lymphoma (HL), compared with F-18-fludeoxyglucose (FDG) positron emission tomography/CT. Methods: 3D TA of 48 lymph nodes in 29 patients was performed on venous-phase CE-CT images before and after chemotherapy. All lymph nodes showed pathologically elevated FDG uptake at baseline. A stepwise logistic regression with forward selection was performed to identify classic CT parameters and texture features (TF) that enable the separation of complete response (CR) and persistent disease. Results: The TF fraction of image in runs, calculated for the 45° direction, was able to correctly identify CR with an accuracy of 75%, a sensitivity of 79.3%, and a specificity of 68.4%. Classical CT features achieved an accuracy of 75%, a sensitivity of 86.2%, and a specificity of 57.9%, whereas the combination of TF and CT imaging achieved an accuracy of 83.3%, a sensitivity of 86.2%, and a specificity of 78.9%. Conclusions: 3D TA of CE-CT images is potentially useful to identify nodal residual disease in HL, with a performance comparable to that of classical CT parameters. Best results are achieved when TA and classical CT features are combined.

60 APPLIED LIFE SCIENCES↗

TU-CD-BRB-01: Normal Lung CT Texture Features Improve Predictive Models for Radiation Pneumonitis

Purpose: Existing normal tissue complication probability (NTCP) models for radiation pneumonitis (RP) traditionally rely on dosimetric and clinical data but are limited in terms of performance and generalizability. Extraction of pre-treatment image features provides a potential new category of data that can improve NTCP models for RP. We consider quantitative measures of total lung CT intensity and texture in a framework for prediction of RP. Methods: Available clinical and dosimetric data was collected for 198 NSCLC patients treated with definitive radiotherapy. Intensity- and texture-based image features were extracted from the T50 phase of the 4D-CT acquired for treatment planning. A total of 3888 features (15 clinical, 175 dosimetric, and 3698 image features) were gathered and considered candidate predictors for modeling of RP grade≥3. A baseline logistic regression model with mean lung dose (MLD) was first considered. Additionally, a least absolute shrinkage and selection operator (LASSO) logistic regression was applied to the set of clinical and dosimetric features, and subsequently to the full set of clinical, dosimetric, and image features. Model performance was assessed by comparing area under the curve (AUC). Results: A simple logistic fit of MLD was an inadequate model of the data (AUC∼0.5). Including clinical and dosimetric parameters within the framework of the LASSO resulted in improved performance (AUC=0.648). Analysis of the full cohort of clinical, dosimetric, and image features provided further and significant improvement in model performance (AUC=0.727). Conclusions: To achieve significant gains in predictive modeling of RP, new categories of data should be considered in addition to clinical and dosimetric features. We have successfully incorporated CT image features into a framework for modeling RP and have demonstrated improved predictive performance. Validation and further investigation of CT image features in the context of RP NTCP modeling is warranted. This work was supported by the Rosalie B. Hite Fellowship in Cancer research awarded to SPK.

60 APPLIED LIFE SCIENCES↗

TU-F-CAMPUS-J-05: Effect of Uncorrelated Noise Texture On Computed Tomography Quantitative Image Features

Purpose: To investigate the relationship between quantitative image features (i.e. radiomics) and statistical fluctuations (i.e. electronic noise) in clinical Computed Tomography (CT) using the standardized American College of Radiology (ACR) CT accreditation phantom and patient images. Methods: Three levels of uncorrelated Gaussian noise were added to CT images of phantom and patients (20) acquired in static mode and respiratory tracking mode. We calculated the noise-power spectrum (NPS) of the original CT images of the phantom, and of the phantom images with added Gaussian noise with means of 50, 80, and 120 HU. Concurrently, on patient images (original and noise-added images), image features were calculated: 14 shape, 19 intensity (1st order statistics from intensity volume histograms), 18 GLCM features (2nd order statistics from grey level co-occurrence matrices) and 11 RLM features (2nd order statistics from run-length matrices). These features provide the underlying structural information of the images. GLCM (size 128x128) was calculated with a step size of 1 voxel in 13 directions and averaged. RLM feature calculation was performed in 13 directions with grey levels binning into 128 levels. Results: Adding the electronic noise to the images modified the quality of the NPS, shifting the noise from mostly correlated to mostly uncorrelated voxels. The dramatic increase in noise texture did not affect image structure/contours significantly for patient images. However, it did affect the image features and textures significantly as demonstrated by GLCM differences. Conclusion: Image features are sensitive to acquisition factors (simulated by adding uncorrelated Gaussian noise). We speculate that image features will be more difficult to detect in the presence of electronic noise (an uncorrelated noise contributor) or, for that matter, any other highly correlated image noise. This work focuses on the effect of electronic, uncorrelated, noise and future work shall examine the influence of changes in quantum noise on the features. J. Oliver was supported by NSF FGLSAMP BD award HRD #1139850 and the McKnight Doctoral Fellowship.

60 APPLIED LIFE SCIENCES↗

Scaling, rotation, and channeling behavior of helical and skyrmion spin textures in thin films of Te-doped Cu 2 OSeO 3

Topologically nontrivial spin textures such as vortices, skyrmions, and monopoles are promising candidates as information carriers for future quantum information science. Their controlled manipulation including creation and annihilation remains an important challenge toward practical applications and further exploration of their emergent phenomena. Here, we report controlled evolution of the helical and skyrmion phases in thin films of multiferroic Te-doped Cu 2 OSeO 3 as a function of material thickness, dopant, temperature, and magnetic field using in situ Lorentz phase microscopy. We report two previously unknown phenomena in chiral spin textures in multiferroic Cu 2 OSeO 3 : anisotropic scaling and channeling with a fixed-Q state. The skyrmion channeling effectively suppresses the recently reported second skyrmion phase formation at low temperature. Our study provides a viable way toward controlled manipulation of skyrmion lattices, envisaging chirality-controlled skyrmion flow circuits and enabling precise measurement of emergent electromagnetic induction and topological Hall effects in skyrmion lattices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The Influence of Powder Ferritization Technology on the Degree of Magnetic Texture in Plates of BaFe{sub 12}O{sub 19} and SrFe{sub 12}O{sub 19} Hexaferrites

We have studied the influence of a technology used for ferritization of the powders of barium and strontium hexaferrites on the degree of magnetic texture in pressed plates based on these powders. It is established that, in comparison to the traditional ceramic technology, the use of a chemical deposition method allows hexaferrite plates with a 19–22% higher degree of magnetic texture to be obtained by pressing raw blanks at the same values of magnetic field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Data for "Soil texture and environmental conditions influence the biogeochemical responses of soils to drought and flooding"

This dataset contains data used for the paper "Soil texture and environmental conditions influence the biogeochemical responses of soils to drought and flooding". The Related References field will be updated with a full citation when available.Climate change is intensifying the global water cycle, with increased frequency of drought and flood. Water is an important driver of soil carbon dynamics, and it is crucial to understand how moisture disturbances will affect carbon availability and fluxes in soils. Here we investigate the role of water in substrate-microbe connectivity and soil carbon cycling under extreme moisture conditions. We collected soils from Alaska, Florida, and Washington USA, and incubated them under Drought and Flood conditions. Drought had a stronger effect on soil respiration, pore-water carbon, and microbial community composition than flooding. Soil response was not consistent across sites, and was influenced by site-level pedological and environmental factors. Soil texture and porosity can influence microbial access to substrates through the pore network, driving the chemical response. Further, the microbial communities are adapted to the historic stress conditions at their sites and therefore show site-specific responses to drought and flood.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv and .txt format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/kaizadp/TES_3Soils_2021 (DOI: 10.5281/zenodo.4792655).

54 ENVIRONMENTAL SCIENCES↗

Spin Textures at Conformal Surfaces and Interfaces: CRADA Final Report

The scientific and technological exploration of artificially designed three-dimensional magnetic nanostructures opens the path to exciting novel physical phenomena, originating from the increased complexity in spin textures, topology, and frustration in three dimensions. Theory predicts that the equilibrium magnetic ground state of two-dimensional systems which reflects the competition between symmetric (Heisenberg) and antisymmetric (Dzyaloshinskii-Moriya interaction (DMI)) exchange interaction is significantly modified on curved surfaces when the radius of local curvature becomes comparable to fundamental magnetic length scales. In this CRADA we performed collaboratively an experimental study of the spin texture in an 8 nm thin magnetic multilayer with growth-induced in-plane anisotropy and DMI deposited onto the curved surface of a 1.8µm long non-magnetic carbon nanowire with a 67 nm radius. The sample was fabricated in Juelich and with collaborators at BESSY in Berlin. Using magnetic soft x-ray tomography at the ALBA synchrotron in Spain, the three-dimensional spin configuration in this nanotube was retrieved with about 30nm spatial resolution. The transition between two vortex configurations on the two ends of the nanotube with opposite circulation occurs through a domain wall that is aligned at an inclined angle relative to the wire axis. Three-dimensional micromagnetic simulations support the experimental observations and represent a visualization of the curvature-mediated DMI. They also allow a quantitative estimate of the DMI value for the magnetic multilayered nanotube.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Phase Evolution and Textural Changes during the Direct Conversion and Storage of CO 2 to Produce Calcium Carbonate from Calcium Hydroxide

The increasing use of energy resources recovered from subsurface environments and the resulting carbon imbalance in the environment has motivated the need to develop thermodynamically downhill pathways to convert and store CO 2 as water-insoluble calcium or magnesium carbonates. While previous studies extensively explored aqueous routes to produce calcium and magnesium carbonates from CO 2 , there is limited scientific understanding of the phase evolution and textural changes during the direct gas–solid conversion routes to produce calcium carbonate from calcium hydroxide, which is one of the abundant constituents of alkaline industrial residues. With increasing interest in developing integrated pathways for capturing, converting, and storing CO 2 from dilute flue gases, understanding the composition of product phases as they evolve is essential for evaluating the efficacy of a given processing route. Therefore, in this study, we investigate the phase evolution and the corresponding textural changes as calcium hydroxide is converted to calcium carbonate under the continuous flow of CO 2 at an ambient pressure of 1 atm with continuous heating from 30 °C to 500 °C using in-operando wide angle X-ray scattering (WAXS), small angle X-ray scattering (SAXS), and ultrasmall angle X-ray scattering (USAXS) measurements.

Liu, Meishen↗

Influence of Supplementary Blue and Far-Red Light on the Morphology and Texture of Ocimum basilicum L. Grown in Controlled Environments

Basil (Ocimum basilicum L.) is highly sensitive to environmental conditions and is an ideal candidate for cultivation in controlled environment agriculture (CEA). Light-emitting diode technology has become essential in CEA, offering precise control over light intensity, spectrum, and duration. This study investigated how supplemental blue light, far-red light, or their combination influences basil biomass, morphology, texture, and color when added to a white + red light spectrum. Basil ’Prospera’ and ’Amethyst’ were exposed to five light treatments for 14–28 days: white + red at 180 µmol∙m−2∙s−1 (W) as the control, and four treatments with an additional 60 µmol∙m−2∙s−1 of either white + red (+W60), blue (+B60), far-red (+FR60), or a combination of B and FR (+B30+FR30), for a total photon flux density of 240 µmol∙m−2∙s−1. The results demonstrated that +B60 and +W60 light treatments increased leaf thickness by 17–20% compared to the +FR60 treatment. Conversely, texture analysis revealed that +FR60-treated leaves had higher puncture resistance, with ’Amethyst’ and ’Prospera’ requiring 1.57 ± 0.43 N and 1.45 ± 0.35 N of force, respectively, compared to 1.19 ± 0.32 N and 1.1 ± 0.21 N under +B60. These findings suggest that tailored light recipes in CEA can optimize basil quality, allowing growers to modify traits like leaf color, thickness, and toughness.

Oehler, Madison A. (ORCID:0000000297919667)↗

Textural features for image classification

Description of some easily computable textural features based on gray-tone spatial dependances, and illustration of their application in category-identification tasks of three different kinds of image data - namely, photomicrographs of five kinds of sandstones, 1:20,000 panchromatic aerial photographs of eight land-use categories, and ERTS multispectral imagery containing several land-use categories. Two kinds of decision rules are used - one for which the decision regions are convex polyhedra (a piecewise-linear decision rule), and one for which the decision regions are rectangular parallelpipeds (a min-max decision rule). In each experiment the data set was divided into two parts, a training set and a test set. Test set identification accuracy is 89% for the photomicrographs, 82% for the aerial photographic imagery, and 83% for the satellite imagery. These results indicate that the easily computable textural features probably have a general applicability for a wide variety of image-classification applications.

Haralick, R. M.↗

Rock 14318 - A polymict lunar breccia with chondritic texture

Rock 14318 is a complex microbreccia consisting of lithic fragments, chondrules, glass spherules, and glass and mineral fragments that are embedded into a fine-grained, partly glassy matrix. Compositions of lithic fragments, glasses and chondrules, in terms of compositional rock and rock suite equivalents, represent members of the ANT (anorthositic-noritic-troctolite) suite; the alkalic high-alumina basalt (KREEP) group; high-alkali quartz basalt; basalt; and dunite. The polymict nature of many lithic fragments suggests that rock 14318 requires at least two, and probably more, impact episodes for its formation. Final agglomeration took place while part of the material was hot, as is indicated by the welded texture, suggesting that the final impact event was a large one, producing a fiery cloud similar to a nuee ardente. The close similarity in texture of lunar rock 14318 to certain polymict-brecciated meteorites such as Siena suggests that meteorites of this type were also formed by complex and successive impact events on the surface of the meteorite parent body, rather than during agglomeration of the parent body.

Kurat, G.↗

Chemical, mineralogical and textural systematics of non-mare melt rocks: Implications for lunar impact and volcanic processes

Based on a synthesis of chemical data for over 200 samples, the nonmare rocks with fine grained melt textures can be classified into 7 major groups: anorthositic basalts, troctolitic basalts, VHA basalts, Apollo 14-type KREEP basalts, Apollo 15-type KREEP basalts, Apollo 17-type KREEP basalts, and aluminous mare basalts. Review of chemical, mineralogical, textural and experimental evidence leads to preferred hypotheses for the origins of these rocks; those hypotheses are discussed in detail.

Irving, A. J.↗

A general model for the textural evolution of lunar soil

The investigation reported is concerned with the qualitative expansion of an earlier model developed by Lindsay (1971, 1972, 1973). Questions regarding the maturity of lunar soils are examined. A multivariate model related to textural maturity is considered, taking into account mean and standard deviations, the asymmetry of the grain size curve, the kurtosis anomaly, and pyroclastic materials. It is concluded that the mean grain size and the standard deviation of the lunar soil can be used as general indicators of the textural maturity of the soil anywhere on the lunar surface.

Lindsay, J. F.↗

Texture measurements for the automatic classification of imagery

The stated purpose is to demonstrate the applicability of texture measurements for making distinctions between classes of imagery. Multispectral images obtained from aircraft and satellites have been successfully delineated into land use classes on the basis of density in the different spectral bands. However, spatial patterns can add additional information to improve classification accuracy. A comparison is made between the results obtained using five texture algorithms for separating land use classes using ERTS imagery. The transforms evaluated are the Karhunen-Loeve, the fast Fourier, the Walsh-Hadamard, the Slant, and a digital matched filter.

Kirvida, L.↗

Textural remanence - A new model of lunar rock magnetism

In reexamining the accumulated magnetic data on lunar rocks, several common patterns of magnetic behavior are recognized. Their joint occurrence strongly suggests a new model of lunar rock magnetism, which is based on partial preferred textural alignment of the spontaneous moments of magnetic grains without requiring the existence of ancient lunar magnetic fields. This magnetic fabric, mimetic to locally oriented petrofabric, gives rise to an apparent 'textural remanent magnetization'. In order to account for the observed intensity of 'stable remanence' in lunar rocks, only a minute fraction (0.001 to 0.00001) of the single-domain iron grains present need be preferentially aligned. Several mechanisms operating on the lunar surface, including shock and diurnal thermal cycling, appear adequate for producing the required type and degree of magnetic alignment in all lunar rock classes. The model is supported by a wide variety of direct and indirect evidence, and its predictions (e.g., regarding anisotropic susceptibility and remanence acquisition) can be experimentally tested.

Brecher, A.↗