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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

TH-E-BRF-04: Characterizing the Response of Texture-Based CT Image Features for Quantification of Radiation-Induced Normal Lung Damage

Purpose: Radiation induced lung damage (RILD) is an important dose-limiting toxicity for patients treated with radiation therapy. Scoring systems for RILD are subjective and limit our ability to find robust predictors of toxicity. We investigate the dose and time-related response for texture-based lung CT image features that serve as potential quantitative measures of RILD. Methods: Pre- and post-RT diagnostic imaging studies were collected for retrospective analysis of 21 patients treated with photon or proton radiotherapy for NSCLC. Total lung and selected isodose contours (0–5, 5–15, 15–25Gy, etc.) were deformably registered from the treatment planning scan to the pre-RT and available follow-up CT studies for each patient. A CT image analysis framework was utilized to extract 3698 unique texture-based features (including co-occurrence and run length matrices) for each region of interest defined by the isodose contours and the total lung volume. Linear mixed models were fit to determine the relationship between feature change (relative to pre-RT), planned dose and time post-RT. Results: Seventy-three follow-up CT scans from 21 patients (median: 3 scans/patient) were analyzed to describe CT image feature change. At the p=0.05 level, dose affected feature change in 2706 (73.1%) of the available features. Similarly, time affected feature change in 408 (11.0%) of the available features. Both dose and time were significant predictors of feature change in a total of 231 (6.2%) of the extracted image features. Conclusion: Characterizing the dose and time-related response of a large number of texture-based CT image features is the first step toward identifying objective measures of lung toxicity necessary for assessment and prediction of RILD. There is evidence that numerous features are sensitive to both the radiation dose and time after RT. Beyond characterizing feature response, further investigation is warranted to determine the utility of these features as surrogates of clinically significant lung injury.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-AB-BRA-06: Texture Feature Reproducibility Between PET/CT and PET/MR Imaging Modalities

Purpose: Radiomics involves the extraction of texture features from different imaging modalities with the purpose of developing models to predict patient treatment outcomes. The purpose of this study is to investigate texture feature reproducibility across [18F]FDG PET/CT and [18F]FDG PET/MR imaging in patients with primary malignancies. Methods: Twenty five prospective patients with solid tumors underwent clinical [18F]FDG PET/CT scan followed by [18F]FDG PET/MR scans. In all patients the lesions were identified using nuclear medicine reports. The images were co-registered and segmented using an in-house auto-segmentation method. Fifty features, based on the intensity histogram, second and high order matrices, were extracted from the segmented regions from both image data sets. One-way random-effects ANOVA model of the intra-class correlation coefficient (ICC) was used to establish texture feature correlations between both data sets. Results: Fifty features were classified based on their ICC values, which were found in the range from 0.1 to 0.86, in three categories: high, intermediate, and low. Ten features extracted from second and high-order matrices showed large ICC ≥ 0.70. Seventeen features presented intermediate 0.5 ≤ ICC ≤ 0.65 and the remaining twenty three presented low ICC ≤ 0.45. Conclusion: Features with large ICC values could be reliable candidates for quantification as they lead to similar results from both imaging modalities. Features with small ICC indicates a lack of correlation. Therefore, the use of these features as a quantitative measure will lead to different assessments of the same lesion depending on the imaging modality from where they are extracted. This study shows the importance of the need for further investigation and standardization of features across multiple imaging modalities.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-R-17: Advancing Glioblastoma Multiforme (GBM) Recurrence Detection with MRI Image Texture Feature Extraction and Machine Learning

Purpose: To test the potential of early Glioblastoma Multiforme (GBM) recurrence detection utilizing image texture pattern analysis in serial MR images post primary treatment intervention. Methods: MR image-sets of six time points prior to the confirmed recurrence diagnosis of a GBM patient were included in this study, with each time point containing T1 pre-contrast, T1 post-contrast, T2-Flair, and T2-TSE images. Eight Gray-level co-occurrence matrix (GLCM) texture features including Contrast, Correlation, Dissimilarity, Energy, Entropy, Homogeneity, Sum-Average, and Variance were calculated from all images, resulting in a total of 32 features at each time point. A confirmed recurrent volume was contoured, along with an adjacent non-recurrent region-of-interest (ROI) and both volumes were propagated to all prior time points via deformable image registration. A support vector machine (SVM) with radial-basis-function kernels was trained on the latest time point prior to the confirmed recurrence to construct a model for recurrence classification. The SVM model was then applied to all prior time points and the volumes classified as recurrence were obtained. Results: An increase in classified volume was observed over time as expected. The size of classified recurrence maintained at a stable level of approximately 0.1 cm{sup 3} up to 272 days prior to confirmation. Noticeable volume increase to 0.44 cm{sup 3} was demonstrated at 96 days prior, followed by significant increase to 1.57 cm{sup 3} at 42 days prior. Visualization of the classified volume shows the merging of recurrence-susceptible region as the volume change became noticeable. Conclusion: Image texture pattern analysis in serial MR images appears to be sensitive to detecting the recurrent GBM a long time before the recurrence is confirmed by a radiologist. The early detection may improve the efficacy of targeted intervention including radiosurgery. More patient cases will be included to create a generalizable classification model applicable to a larger patient cohort. NIH R43CA183390 and R01CA188300.NSF Graduate Research Fellowship DGE-1144087.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-R-31: Identification of Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induced Lung Disease

Purpose: Normal lung CT texture features have been used for the prediction of radiation-induced lung disease (radiation pneumonitis and radiation fibrosis). For these features to be clinically useful, they need to be relatively invariant (robust) to tumor size and not correlated with normal lung volume. Methods: The free-breathing CTs of 14 lung SBRT patients were studied. Different sizes of GTVs were simulated with spheres placed at the upper lobe and lower lobe respectively in the normal lung (contralateral to tumor). 27 texture features (9 from intensity histogram, 8 from grey-level co-occurrence matrix [GLCM] and 10 from grey-level run-length matrix [GLRM]) were extracted from [normal lung-GTV]. To measure the variability of a feature F, the relative difference D=|Fref -Fsim|/Fref*100% was calculated, where Fref was for the entire normal lung and Fsim was for [normal lung-GTV]. A feature was considered as robust if the largest non-outlier (Q3+1.5*IQR) D was less than 5%, and considered as not correlated with normal lung volume when their Pearson correlation was lower than 0.50. Results: Only 11 features were robust. All first-order intensity-histogram features (mean, max, etc.) were robust, while most higher-order features (skewness, kurtosis, etc.) were unrobust. Only two of the GLCM and four of the GLRM features were robust. Larger GTV resulted greater feature variation, this was particularly true for unrobust features. All robust features were not correlated with normal lung volume while three unrobust features showed high correlation. Excessive variations were observed in two low grey-level run features and were later identified to be from one patient with local lung diseases (atelectasis) in the normal lung. There was no dependence on GTV location. Conclusion: We identified 11 robust normal lung CT texture features that can be further examined for the prediction of radiation-induced lung disease. Interestingly, low grey-level run features identified normal lung diseases. This work was supported in part by the National Cancer Institute Grants R01CA172638.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-207: Non-Small Cell Lung Cancer Patient Survival Prediction with Quantitative Tumor Textures Analysis in Baseline CT

Purpose: Chemo-radiation therapy (CRT) is widely used in treating patients with locally advanced non-small cell lung cancer (NSCLC). Determination of the likelihood of patient response to treatment and optimization of treatment regime is of clinical significance. Up to date, no imaging biomarker has reliably correlated to NSCLC patient survival rate. This pilot study is to extract CT texture information from tumor regions for patient survival prediction. Methods: Thirteen patients with stage II-III NSCLC were treated using CRT with a median dose of 6210 cGy. Non-contrast-enhanced CT images were acquired for treatment planning and retrospectively collected for this study. Texture analysis was applied in segmented tumor regions using the Local Binary Pattern method (LBP). By comparing its HU with neighboring voxels, the LBPs of a voxel were measured in multiple scales with different group radiuses and numbers of neighbors. The LBP histograms formed a multi-dimensional texture vector for each patient, which was then used to establish and test a Support Vector Machine (SVM) model to predict patients’ one year survival. The leave-one-out cross validation strategy was used recursively to enlarge the training set and derive a reliable predictor. The predictions were compared with the true clinical outcomes. Results: A 10-dimensional LBP histogram was extracted from 3D segmented tumor region for each of the 13 patients. Using the SVM model with the leave-one-out strategy, only 1 out of 13 patients was misclassified. The experiments showed an accuracy of 93%, sensitivity of 100%, and specificity of 86%. Conclusion: Within the framework of a Support Vector Machine based model, the Local Binary Pattern method is able to extract a quantitative imaging biomarker in the prediction of NSCLC patient survival. More patients are to be included in the study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-D-207B-05: Intra-Tumor Partitioning and Texture Analysis of DCE-MRI Identifies Relevant Tumor Subregions to Predict Early Pathological Response of Breast Cancer to Neoadjuvant Chemotherapy

Purpose: To predict early pathological response of breast cancer to neoadjuvant chemotherapy (NAC) based on quantitative, multi-region analysis of dynamic contrast enhancement magnetic resonance imaging (DCE-MRI). Methods: In this institution review board-approved study, 35 patients diagnosed with stage II/III breast cancer were retrospectively investigated using DCE-MR images acquired before and after the first cycle of NAC. First, principal component analysis (PCA) was used to reduce the dimensionality of the DCE-MRI data with a high-temporal resolution. We then partitioned the whole tumor into multiple subregions using k-means clustering based on the PCA-defined eigenmaps. Within each tumor subregion, we extracted four quantitative Haralick texture features based on the gray-level co-occurrence matrix (GLCM). The change in texture features in each tumor subregion between pre- and during-NAC was used to predict pathological complete response after NAC. Results: Three tumor subregions were identified through clustering, each with distinct enhancement characteristics. In univariate analysis, all imaging predictors except one extracted from the tumor subregion associated with fast wash-out were statistically significant (p< 0.05) after correcting for multiple testing, with area under the ROC curve or AUCs between 0.75 and 0.80. In multivariate analysis, the proposed imaging predictors achieved an AUC of 0.79 (p = 0.002) in leave-one-out cross validation. This improved upon conventional imaging predictors such as tumor volume (AUC=0.53) and texture features based on whole-tumor analysis (AUC=0.65). Conclusion: The heterogeneity of the tumor subregion associated with fast wash-out on DCE-MRI predicted early pathological response to neoadjuvant chemotherapy in breast cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Nanoscale engineering and dynamic stabilization of mesoscopic spin textures

Thermalization, while ubiquitous in physics, has traditionally been viewed as an obstacle to be mitigated. In contrast, we demonstrate here the use of thermalization in the generation, control, and readout of “shell-like” spin textures with interacting 13 C nuclear spins in diamond, wherein spins are polarized oppositely on either side of a critical radius. The textures span several nanometers and encompass many hundred spins; they are created and interrogated without manipulating the nuclear spins individually. Long-time stabilization is achieved via prethermalization to a Floquet-engineered Hamiltonian under the electronic gradient field: The texture is therefore metastable and robust against spin diffusion. This enables the state to endure over multiple minutes before it decays. Our work on spin-state engineering paves the way for applications in quantum simulation and nanoscale imaging.

42 ENGINEERING↗
DOE OSTI2026

Uniaxial Spin Texture in a Superconducting Electron Gas Revealed by Exchange Interactions

Two-dimensional (2D) superconductors with spin-textured Fermi surfaces can be a platform for realizing unconventional pairing states and are of substantial interest in the context of quantum information science and superconducting spintronics/orbitronics. We observed an unusual in-plane uniaxial anisotropy in the superconducting 2D electron gas (2DEG) formed at EuOx/KTaO3 (110) interfaces. This anisotropy is not evident in AlOx/KTaO3 (110) where the overlayer is nonmagnetic. Our results are consistent with a highly anisotropic “half-Rashba” spin-textured Fermi surface in 2DEGs formed at the KTaO3 (110) interface that is hidden from external magnetic fields due to a near cancellation between orbital and spin moments but revealed by exchange interactions of the electrons in the 2DEG with Eu moments near the EuOx/KTaO3 (110) interface. The interactions between the uniaxial spin texture and the magnetic overlayer offer previously unexplored ways to explore the interplay between magnetism and 2D superconductivity.

Yang, Junyi↗
DOE OSTI2021

Atomic-scale visualization of topological spin textures in the chiral magnet MnGe

Peeking into magnetic textures Topological spin textures hold promise as robust carriers of information and have been observed in bulk materials with a specific crystal structure. One of these materials, manganese germanide (MnGe), exhibits unusual textures in bulk form. Repicky et al . used spin-polarized scanning tunneling microscopy to study surface magnetism in thin films of MnGe. Achieving high spatial resolution, the researchers observed stripe-like features consistent with a helical state. In regions where the film was slightly curved due to strain, the intersection of domain walls led to characteristic closed patterns that could be manipulated with current/voltage pulses. —JS

Science & Technology - Other Topics↗
DOE OSTI2022

Correlations between Texture Profile Analysis and Sensory Evaluation of Cured Largemouth Bass Meat (Micropterus salmoides)

Texture is an important factor in evaluating the quality of aquatic products. To evaluate the texture properties of cured large mouth bass, edible sodium chloride (0, 1.0, 2.0, and 3.0%) was smeared to the bass meat. Texture profile analysis (TPA) and sensory evaluation were performed to evaluate the quality of the cured samples, and the correlations of the indexes in the two methods were analyzed. Two principal components were obtained from the TPA indexes and sensory evaluation indexes, and the cumulative variance contribution rates were 73.87% and 72.99%, respectively. Results from the principal component analysis showed that the main indicators that affected the TPA were gumminess and springiness, while those that affected sensory evaluation were chewiness and adhesiveness. The TPA index and sensory evaluation could be effectively improved when the sodium chloride added to the bass meat was 1%. In the correlation analysis, sensory springiness was negatively correlated with TPA hardness ( P < 0.05 , r = −0.553) but positively correlated with TPA chewiness ( P < 0.05 , r = 0.596). After stepwise regression analysis, the prediction equation between the sensory springiness and TPA hardness was obtained as SSp=5.770−0.002Ha. These results provide a basis for predicting the quality of large mouth bass cured products.

Li, Meijin↗
DOE OSTI2015

Crystallographic texture engineering through novel melt strategies via electron beam melting: Inconel 718

Preliminary research has demonstrated the ability to utilise novel scan strategies in the electron beam melting (EBM) process to establish control of crystallographic texture within Inconel 718 deposits. Conventional EBM scan strategies and process parameters yield coarse columnar grains aligned parallel to the build direction. Through varying process parameters such as beam power, beam velocity, beam focus and scan strategy, the behaviour of the electron beam can be manipulated from a line source to a point source. The net effect of these variations is that the resulting crystallographic texture is controlled in a manner to produce either epitaxial deposits or fully equiaxed deposits. Furthermore, this research demonstrates the ability to change the crystallographic texture on the macroscale indicating that EBM technology can be used to create complex geometric components with both site-specific microstructures and material properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Development of Multi-Filament Textured-Powder Bi-2212/Ag Wire with Enhanced Local Area Ratio (Final Technical Report)

ATC has successfully developed a new method for making high-performance Bi-2212/Ag su-perconducting wire with a favorable local area ratio (LAR)=Ag:Bi-2212. The method begins by texturing a fine powder of Bi-2212: the powder is loaded uniformly into an open-sided silver foil channel, the flaps of foil are folded over the powder filling, and the package is hydraulically com-pressed in a die set to form a textured-powder (TP) bar. XRD analysis of the interior powder in a compressed bar shows a texture of 80% after 200 MPa compression.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Investigation of topologically trivial and non-trivial spin textures and their relationships with the topological Hall effect

This proposal has two main goals: (1) to investigate ways to create a variety of spin textures, both topologically trivial and non-trivial, and (2) to establish the relationships between the created spin textures and the topological Hall effect (THE) signal. The approach is achieved by utilizing the van der Waals (vdW) two-dimensional (2D) magnetic materials, such as CrX 3 (X=I, Br, and Cl) and Fe 3 GeTe 2 , transferred onto various substrates with different interactions to create a wide range of spin textures; and utilize Spin helical system, such as Eu metal, and the impact of the thickness.

36 MATERIALS SCIENCE↗
NASA NTRS1974

Texturing and residual stress in metals as a result of sliding

Pole figures of the texturing produced by friction in the alloys Cu - 10 at. % Sn, Cu - 10 at. % Si, 440 C stainless steel, and AISI 52100 bearing steel were obtained with an energy-dispersive X-ray diffractometer. While the texturing behavior of these alloys is generally similar to that of pure metals, the 52100 steel and the Cu5Si phase of Cu - 10 at. % Si show no texturing at the loads and speeds used in this experiment. Photographic methods were used in an attempt to measure the uniform residual stress in the wear tracks produced on some pure metals. The stress in copper and iron was, however, below the limit of detectability - about 4.3 x 10 to the 7th power N/sq m (6000 psi). Line broadening under all test conditions in the case of copper and at high load and speed conditions in iron is attributed, at least in part, to the reduction of crystallite size and, perhaps, to nonuniform residual stress, as well.

Wheeler, D. R.↗
NASA NTRS1977

Dynamic crystallization experiments bearing on the origin of textures in impact-generated liquids

Dynamic crystallization experiments on a synthetic glass of 14310 composition show that the density and distribution of crystals present at the initiation of cooling can drastically affect the texture of the crystallized product. Experiments were performed in one-atmosphere gas-mixing furnaces at an oxygen fugacity slightly below iron-wustite, and precooling crystallization, cooling history, and melt history were systematically varied. When cooled from a complete liquid, the experimental charges were porphyritic with 1-2 mm phenocrysts set in a very fine-grained matrix (less than 0.1 mm). This result suggests that 14310 did not cool from a complete melt. When cooled from a crystal-liquid mixture, the experimental charges had widely varying textures depending on the density and distribution of crystals that act as nucleation sites. It is suggested that the close spatial association of widely divergent textures in the matrices of some breccias and rocks might arise in this manner; local variations in cooling rates are not required.

Lofgren, G. E.↗
NASA NTRS1978

Adhesive bonding of ion beam textured metals and fluoropolymers

An electron bombardment argon ion source was used to ion etch various metals and fluoropolymers. The metal and fluoropolymers were exposed to (0.5 to 1.0) keV Ar ions at ion current densities of (0.2 to 1.5) mA/sq cm for various exposure times. The resulting surface texture is in the form of needles or spires whose vertical dimensions may range from tenths to hundreds of micrometers, depending on the selection of beam energy, ion current density, and etch time. The bonding of textured surfaces is accomplished by ion beam texturing mating pieces of either metals or fluoropolymers and applying a bonding agent which wets in and around the microscopic cone-like structures. After bonding, both tensile and shear strength measurements were made on the samples. Also tested, for comparison's sake, were untextured and chemically etched fluoropolymers. The results of these measurements are presented.

Mirtich, M. J.↗
NASA NTRS1978

Adhesive bonding of ion beam textured metals and fluoropolymers

An electron-bombardment argon ion source was used to ion-etch various metals and fluoropolymers. The metal and fluoropolymers were exposed to (0.5 to 1.0)-keV Ar ions at ion current densities of 0.2 to 1.5 mA/sq cm for various exposure times. The resulting surface texture is in the form of needles or spires whose vertical dimensions may range from tenths to hundreds of micrometers, depending on the selection of beam energy, ion current density, and etch time. The bonding of textured surfaces is accomplished by ion-beam texturing mating pieces of either metals or fluoropolymers and applying a bonding agent which wets in and around the microscopic conelike structures. After bonding, both tensile and shear strength measurements were made on the samples. Also tested, for comparison's sake, were untextured and chemically etched fluoropolymers. The results of these measurements are presented in this paper.

Mirtich, M. J.↗
NASA NTRS1978

Nucleation and growth of plagioclase and the development of textures in a high-alumina basaltic melt

Detailed experiments on the nucleation and growth of plagioclase from an igneous melt are carried out to characterize the magma prior to cooling. It is shown that the nature of the melt directly preceding cooling has a strong effect on texture development, regardless of the origin of the melt. The number, size, and shape of the crystals present in a melt upon extrusion can have a drastic effect on the final textures present in the resulting rocks. Conditions necessary for the formation of poikilitic, intersertal, and porphyritic textures in basaltic rocks are defined.

Nabelek, P. I.↗