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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Accelerated Over-The-Air Neural Receiver Training Using Self-Contrastive Learning

Self-contrastive learning (SCL), a self-supervised learning method, has been shown to improve image and signal classifier accuracies and reduce the training time for neural communications receivers. In particular, prior work has shown that SCL applied as a pre-training step can improve simulated performance of OFDM in 3GPP TDL channel models by reducing the training time of the downstream classification task (demodulation and demapping). In this work a practical implementation demonstrating SCL pre-training using software defined radios (SDRs) is proposed.

Cooke, Corey [ORNL] (ORCID:0000000234263672)↗
DOE OSTI2016

High-spectral-contrast symmetric modes in photonic crystal dual nanobeam resonators

Here, we demonstrate accurate control of mode symmetry in suspended dual-nanobeam resonators on a silicon-on-insulator chip. Each nanobeam consists of a Fabry-Perot nanocavity bounded by tapered 1-D photonic crystals. Even and odd cavity-modes are formed due to lateral evanescent coupling between the two nanobeams. The odd cavity-mode can be excited by mode-symmetry-transforming Mach-Zehnder couplers. Modal contrasts over 27 dB are measured in fabricated structures. The influence of the optical field in the middle air slot on the background transmission and quality factors is discussed. The observed peak wavelength separations of the modes at various nanobeam spacings are in good agreement with simulation results. These nanobeam resonators are potentially useful in applications, such as ultrafast all-optical modulation, filtering, and switching.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

4D Multimodal Co-attention Fusion Network with Latent Contrastive Alignment for Alzheimer’s Diagnosis

Multimodal neuroimaging provides complementary structural and functional insights into both human brain organization and disease-related dynamics. Recent studies demonstrate enhanced diagnostic sensitivity for Alzheimer’s disease (AD) through synergistic integration of neuroimaging data (e.g., sMRI, fMRI) with tabular data (e.g., behavioral and cognitive tests). However, the intrinsic heterogeneity across modalities (e.g., 4D spatiotemporal fMRI dynamics vs. 3D anatomical sMRI structure) presents critical challenges for discriminative feature fusion, often leading to information loss or biased fusion. To bridge this gap, we propose M2M-AlignNet: a multimodal co-attention network with latent alignment for early AD diagnosis using sMRI and fMRI. At the core of our approach is a multi-patch-to-multi-patch (M2M) contrastive loss function that quantifies and reduces representational discrepancies via weighted patch correspondence, explicitly aligning fMRI components across brain regions with their sMRI structural substrates without one-to-one constraints. Additionally, we propose a latent-as-query co-attention module to autonomously discover fusion patterns, circumventing modality prioritization biases while minimizing feature redundancy. We conduct extensive experiments to confirm the effectiveness of our method and highlight the correspondence between fMRI and sMRI as AD biomarkers.

Wei, Yuxiang [Georgia Institute of Technology]↗
DOE OSTI2026

Contrasting Carbon–Water–Energy Dynamics in Perennial and Annual Bioenergy Agroecosystems Using Eddy Covariance and Interpretable Machine Learning

Understanding how agroecosystems respond to environmental variability is fundamental to predicting productivity and sustainability under a changing climate. We analyzed 55 site-years of high-frequency eddy covariance observations from five agroecosystems—two perennial grasses (miscanthus and switchgrass), two annual rotation systems (maize–soybean and sorghum–soybean), and a restored native prairie—to examine ecosystem-scale carbon, water, and energy fluxes. Using an interpretable machine-learning framework with regression tree ensembles, Shapley Additive Explanations, and Accumulated Local Effects, we quantified how environmental and temporal factors regulate gross primary productivity (GPP), evapotranspiration (ET), water-use efficiency, and the Bowen ratio. Perennials exhibited stronger physiological buffering and maintained fluxes across a broader range of temperature and moisture conditions, reflecting deeper rooting and persistent canopy cover. Annuals, in contrast, showed greater short-term variability and stronger coupling to atmospheric demand, with GPP and ET declining rapidly under low humidity or soil moisture. Differences in temperature sensitivity of Bowen ratio further revealed that perennials sustained proportionally greater sensible heat flux under cool conditions, whereas annuals exhibited constrained energy exchange when evaporative demand was low. Together, these results demonstrate that crop life cycle and canopy structure are fundamental determinants of ecosystem-scale carbon–water–energy coupling. By integrating long-term flux observations with interpretable machine learning, this study identifies the environmental drivers that shape agroecosystem function and highlights how conversion from annual to perennial feedstocks can enhance climatic resilience and alter land–atmosphere energy feedbacks. These findings provide a data-driven basis for improving crop and Earth-system models and for guiding bioenergy landscape design under future climate scenarios.

Accumulated Local Effects↗
DOE OSTI2026

Transgenic Mixed‐Linkage‐Glucan Enhancement Affects Root Characteristics and Decomposition in Soils of Contrasting Vegetation History

ABSTRACT Development of transgenic bioenergy sorghum [ Sorghum bicolor (L.) Moench] with increased contents of mixed‐linkage (1,3;1,4)‐β‐glucan (MLG) is an important step towards enhancing quality of bioenergy feedstocks. Since MLG‐enhancement leads to greater biomass digestibility, our overarching hypothesis is that root residues of MLG‐enhanced plants may be more readily decomposed in the soil, potentially creating new opportunities for optimizing soil carbon (C) sequestration, nutrient cycling, and overall agricultural sustainability. The study examined morphological, chemical, and enzymatic characteristics of fine and coarse roots of four bioenergy sorghum genotypes. Then, we incubated the roots within soils with contrasting vegetation histories while measuring C mineralization, microbial biomass C (MBC), and activity of hydrolytic enzymes and calculating vector length and vector angle enzymatic stoichiometry parameters. The results indicated that MLG‐enhancing transformations increased root total nitrogen (N) contents, decreased C/N ratios, and were associated with higher MLG concentrations in fine than in coarse roots. Incubations with transgenic roots led to 16%–38% higher MBC and 19%–41% lower microbial metabolic quotient (qCO 2 ). While enzyme activity differed markedly among the studied genotypes, it did not directly respond to MLG levels in root tissues. The increase in MBC without concurrent increases in C mineralization or hydrolytic enzyme activities in transgenic genotypes suggests that MLG enhancement promoted microbial anabolic retention of root‐derived C rather than stimulating catabolic decomposition. Enzymatic vector results indicated that these parameters reflect a variety of drivers behind microbial enzyme production, including availability of specific substrates, such as MLG here, and/or deficiency in specific nutrients, such as phosphorus (P). The study confirms the positive impacts from the roots of engineered MLG‐enhanced bioenergy plants on soil microbial activity and highlights the interactive influences on the MLG‐enhancement effects from root size and inherent soil properties.

Mahmoodabadi, Majid [Department of Plant, Soil, an↗
DOE OSTI2014

Observation of Crack Propagation in Glass Using X-ray Phase Contrast Imaging

High-speed X-ray phase contrast imaging synchronized with a Kolsky bar apparatus was utilized to investigate the cracking behavior of a borosilicate glass, a soda lime glass, and a glass ceramic in front of a cylindrical projectile with an impact velocity of 5ms(-1). For each material, three different surface conditions were prepared for the impacted edge of the specimen. Angular cracking was observed in front of the projectile for borosilicate glass. For soda lime glass, straight cracking was observed. For glass ceramic, curved cracking was observed in front of the projectile. Cracking behavior was observed to be independent of the surface condition on the impacted edge.

Parab, Niranjan D.↗
DOE OSTI2016

In situ 3‐D mapping of pore structures and hollow grains of interplanetary dust particles with phase contrast X‐ray nanotomography

Abstract Unlocking the 3‐D structure and properties of intact chondritic porous interplanetary dust particles ( IDP s) in nanoscale detail is challenging, which is also complicated by atmospheric entry heating, but is important for advancing our understanding of the formation and origins of IDP s and planetary bodies as well as dust and ice agglomeration in the outer protoplanetary disk. Here, we show that indigenous pores, pristine grains, and thermal alteration products throughout intact particles can be noninvasively visualized and distinguished morphologically and microstructurally in 3‐D detail down to ~10 nm by exploiting phase contrast X‐ray nanotomography. We have uncovered the surprisingly intricate, submicron, and nanoscale pore structures of a ~10‐μm‐long porous IDP , consisting of two types of voids that are interconnected in 3‐D space. One is morphologically primitive and mostly submicron‐sized intergranular voids that are ubiquitous; the other is morphologically advanced and well‐defined intragranular nanoholes that run through the approximate centers of ~0.3 μm or lower submicron hollow grains. The distinct hollow grains exhibit complex 3‐D morphologies but in 2‐D projections resemble typical organic hollow globules observed by transmission electron microscopy. The particle, with its outer region characterized by rough vesicular structures due to thermal alteration, has turned out to be an inherently fragile and intricately submicron‐ and nanoporous aggregate of the sub‐μm grains or grain clumps that are delicately bound together frequently with little grain‐to‐grain contact in 3‐D space.

Hu, Z. W.↗
DOE OSTI2024

Contrasting coordination of non‐structural carbohydrates with leaf and root economic strategies of alpine coniferous forests

Non-structural carbohydrates (NSCs), as the labile fraction and dominant carbon currency, are essential mediators of plant adaptation to environments. However, whether and how NSC coordinates with plant economic strategy frameworks, particularly the well-recognized leaf economics spectrums (LES) and root economics space (RES), remains unclear. We examined the relationships between NSC and key plant economics traits in leaves and fine roots across 90 alpine coniferous populations on the Tibetan Plateau, China. We observed contrasting coordination of NSC with economics traits in leaves and roots. Leaf total NSC and soluble sugar aligned with the leaf economic spectrum, conveying a trade-off between growth and storage in leaves. However, NSC in roots was independent of the root economic spectrum, but highly coordinated with root foraging, with more starch and less sugar in forage-efficient, thinner roots. Further, NSC-trait coordination in leaves and roots was, respectively, driven by local temperature and precipitation. These findings highlight distinct roles of NSC in shaping the above- and belowground multidimensional economics trait space, and NSC-based carbon economics provides a mechanistic understanding of how plants adapt to heterogeneous habitats and respond to environmental changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Carbon source-sink limitations differ between two species with contrasting growth strategies: Source-sink limitations vary with growth strategy

When we understand how carbon source and sink strengths limit plant growth we realized how critical the knowledge gap is in hindering efforts to maximize crop yield. Here, we investigated how differences in growth rate arise from source–sink limitations, using a model system comparing a fast-growing domesticated annual barley (Hordeum vulgare cv. NFC Tipple) with a slow-growing wild perennial relative (Hordeum bulbosum). Source strength was manipulated by growing plants at sub-ambient and elevated CO 2 concentrations ([CO 2 ]). Limitations on vegetative growth imposed by source and sink were diagnosed by measuring relative growth rate, developmental plasticity, photosynthesis and major carbon and nitrogen metabolite pools. Growth was sink limited in the annual but source limited in the perennial. RGR and carbon acquisition were higher in the annual, but photosynthesis responded weakly to elevated [CO 2 ] indicating that source strength was near maximal at current [CO 2 ]. In contrast, photosynthetic rate and sink development responded strongly to elevated [CO 2 ] in the perennial, indicating significant source limitation. Sink limitation was avoided in the perennial by high sink plasticity: a marked increase in tillering and root:shoot ratio at elevated [CO 2 ], and lower non-structural carbohydrate accumulation. Finally, by alleviating sink limitation during vegetative development could be important for maximizing growth of elite cereals under future elevated [CO 2 ].

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

X-Ray Phase Contrast Imaging of Liquid Film and Spray Development Inside an Aircraft Engine Swirler

Modern aircraft engines combine liquid fuel and air using an intricate flow device with many fuel and air flow passages. To date, the process by which the fuel atomizes within this swirler set has not been examined directly due to optical access limitations. In this work, high-speed X-ray phase-contrast imaging of a liquid spray inside a gas turbine engine swirler geometry is presented. Measurements were carried out at the 7-BM beamline of the Advanced Photon Source at Argonne National Laboratory using the high-energy broadband X-ray beam. The synchrotron X-ray source provides the necessary photon energy and flux to capture time-resolved fluid phenomena within the confines of the relevant geometry while liquid and air are flowing. Spray nozzle hardware and geometries were provided by the National Jet Fuels Combustion Program (NJFCP), allowing for characterization of the spray using a commercially relevant configuration. Modified swirlers were three-dimensional printed with acrylic to improve imaging access while maintaining influential internal features. Water was used as a surrogate fluid for these studies to demonstrate the visualization capabilities. The experiments were conducted at atmospheric exit pressure conditions with a pressure drop of 6% across the swirler. High-speed imaging of the pilot spray cone revealed sheet breakup several millimeters downstream of the orifice exit, upon interaction with the radial assist air flow. These droplets and ligaments were observed to impinge on the inner filming surface of the swirler and flow toward the exit while developing a tangential flow. Under these conditions, the liquid film grows up to several hundred microns in thickness on the filming surface, and subsequently forms ligaments up to several millimeters in length before breaking up. This work demonstrates the capability of X-ray diagnostics in visualizing liquid flows within solid geometries of technical relevance. Furthermore, the spatial quantification of filming flows and liquid interaction with the swirler air provides validation data for modeling of the multiphase flows and surface interactions within the swirler.

Sforzo, Brandon A.↗
DOE OSTI2018

Factor analysis in automated face detection: gender, occlusion, eyewear, brightness, contrast, and focus measure

Computer-based facial recognition algorithms exploit the unique characteristics of faces in images. However, in non-cooperative situations these unique characteristics are often disturbed. In this study, we examine the effect of six different factors on face detection in an unconstrained imaging environment: image brightness, image contrast, focus measure, eyewear, gender, and occlusion. The aim of this study is twofold: first, to quantify detection rates of conventional Haar cascade algorithms across these six factors; and second, to propose methods for automatically labeling datasets whose size prohibits manual labeling. First, we manually classify a uniquely challenging dataset comprising 9,688 images of passengers in vehicles acquired from a roadside camera system. Next, we quantify how each of the aforementioned factors affect face detection on this dataset. Of the six factors studied, occlusion had the most significant impact, resulting in a 54% decrease in detection rate between unoccluded and severely occluded faces in our unique dataset. Finally, we provide a methodology for data analytics of large datasets where manual labeling of the whole dataset is not possible.

Jafek, Benjamin↗
DOE OSTI2010

Optimization of a dual-energy contrast-enhanced technique for a photon-counting digital breast tomosynthesis system: I. A theoretical model

Purpose: Dual-energy (DE) iodine contrast-enhanced x-ray imaging of the breast has been shown to identify cancers that would otherwise be mammographically occult. In this article, theoretical modeling was performed to obtain optimally enhanced iodine images for a photon-counting digital breast tomosynthesis (DBT) system using a DE acquisition technique. Methods: In the system examined, the breast is scanned with a multislit prepatient collimator aligned with a multidetector camera. Each detector collects a projection image at a unique angle during the scan. Low-energy (LE) and high-energy (HE) projection images are acquired simultaneously in a single scan by covering alternate collimator slits with Sn and Cu filters, respectively. Sn filters ranging from 0.08 to 0.22 mm thickness and Cu filters from 0.11 to 0.27 mm thickness were investigated. A tube voltage of 49 kV was selected. Tomographic images, hereafter referred to as DBT images, were reconstructed using a shift-and-add algorithm. Iodine-enhanced DBT images were acquired by performing a weighted logarithmic subtraction of the HE and LE DBT images. The DE technique was evaluated for 20-80 mm thick breasts. Weighting factors, w{sub t}, that optimally cancel breast tissue were computed. Signal-difference-to-noise ratios (SDNRs) between iodine-enhanced and nonenhanced breast tissue normalized to the square root of the mean glandular dose (MGD) were computed as a function of the fraction of the MGD allocated to the HE images. Peak SDNR/{radical}(MGD) and optimal dose allocations were identified. SDNR/{radical}(MGD) and dose allocations were computed for several practical feasible system configurations (i.e., determined by the number of collimator slits covered by Sn and Cu). A practical system configuration and Sn-Cu filter pair that accounts for the trade-off between SDNR, tube-output, and MGD were selected. Results: w{sub t} depends on the Sn-Cu filter combination used, as well as on the breast thickness; to optimally cancel 0% with 50% glandular breast tissue, w{sub t} values were found to range from 0.46 to 0.72 for all breast thicknesses and Sn-Cu filter pairs studied. The optimal w{sub t} values needed to cancel all possible breast tissue glandularites vary by less than 1% for 20 mm thick breasts and 18% for 80 mm breasts. The system configuration where one collimator slit covered by Sn is alternated with two collimator slits covered by Cu delivers SDNR/{radical}(MGD) nearest to the peak value. A reasonable compromise is a 0.16 mm Sn-0.23 mm Cu filter pair, resulting in SDNR values between 1.64 and 0.61 and MGD between 0.70 and 0.53 mGy for 20-80 mm thick breasts at the maximum tube current. Conclusions: A DE acquisition technique for a photon-counting DBT imaging system has been developed and optimized.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

A method for patient dose reduction in dynamic contrast enhanced CT study

Purpose: In dynamic contrast enhanced CT (DCE-CT) study, prolonged CT scanning with high temporal resolution is required to give accurate and precise estimates of kinetic parameters. However, such scanning protocol could lead to substantial radiation dose to the patient. A novel method is proposed to reduce radiation dose to patient, while maintaining high accuracy for kinetic parameter estimates in DCE-CT study. Methods: The method is based on a previous investigation that the arterial impulse response (AIR) in DCE-CT study can be predicted using a population-based scheme. In the proposed method, DCE-CT scanning is performed with relatively low temporal resolution, hence, giving rise to reduction in patient dose. A novel method is proposed to estimate the arterial input function (AIF) based on the coarsely sampled AIF. By using the estimated AIF in the tracer kinetic analysis of the coarsely sampled DCE-CT study, the calculated kinetic parameters are able to achieve a high degree of accuracy. The method was tested on a DCE-CT data set of 48 patients with cervical cancer scanned at high temporal resolution. A random cohort of 34 patients was chosen to construct the orthonormal bases of the AIRs via singular value decomposition method. The determined set of orthonormal bases was used to fit the AIFs in the second cohort (14 patients) at varying levels of down sampling. For each dataset in the second cohort, the estimated AIF was used for kinetic analyses of the modified Tofts and adiabatic tissue homogeneity models for each of the down-sampling schemes between intervals from 2 to 15 s. The results were compared with analyses done with the ''raw'' down-sampled AIF. Results: In the first group of 34 patients, there were 11 orthonormal bases identified to describe the AIRs. The AIFs in the second group were estimated in high accuracy based on the 11 orthonormal bases established in the first group along with down-sampled AIFs. Using the 11 orthonormal bases, the estimated AIFs for the second group were found to have an averaged maximal percentage error of 3.4%{+-} 7.5% in all sampling schemes up to 15 s. The results of kinetic analysis with the proposed method compared with down sampling alone showed that the proposed method is superior in maintaining the accuracy in volume transfer constant (K{sup trans} ) after 9 s down-sampling interval, blood volume (v{sub b} ) for almost all down-sampling intervals, and blood flow (F) after 11 s down-sampling interval. The preliminary results suggested that the proposed method is able to support scanning intervals of 10-15 s at a cost of 6.2%-10.0% loss in accuracy of K{sup trans} and 10.9%-19.4% in v{sub b}, and the scanning intervals of 12-15 s at a cost of 9.7%-14.6% for F in DEC-CT studies for patients with cervix cancer. Conclusions: The proposed method of AIF estimation allows low scanning frequency in DCE-CT study to reduce radiation dose to patient, while maintaining relatively high accuracy in the kinetic parameter estimates. The initial results suggested that the method is applicable for DCE-CT studies for patients with cervical cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Prediction of human observer performance in a 2-alternative forced choice low-contrast detection task using channelized Hotelling observer: Impact of radiation dose and reconstruction algorithms

Purpose: Efficient optimization of CT protocols demands a quantitative approach to predicting human observer performance on specific tasks at various scan and reconstruction settings. The goal of this work was to investigate how well a channelized Hotelling observer (CHO) can predict human observer performance on 2-alternative forced choice (2AFC) lesion-detection tasks at various dose levels and two different reconstruction algorithms: a filtered-backprojection (FBP) and an iterative reconstruction (IR) method. Methods: A 35 Multiplication-Sign 26 cm{sup 2} torso-shaped phantom filled with water was used to simulate an average-sized patient. Three rods with different diameters (small: 3 mm; medium: 5 mm; large: 9 mm) were placed in the center region of the phantom to simulate small, medium, and large lesions. The contrast relative to background was -15 HU at 120 kV. The phantom was scanned 100 times using automatic exposure control each at 60, 120, 240, 360, and 480 quality reference mAs on a 128-slice scanner. After removing the three rods, the water phantom was again scanned 100 times to provide signal-absent background images at the exact same locations. By extracting regions of interest around the three rods and on the signal-absent images, the authors generated 21 2AFC studies. Each 2AFC study had 100 trials, with each trial consisting of a signal-present image and a signal-absent image side-by-side in randomized order. In total, 2100 trials were presented to both the model and human observers. Four medical physicists acted as human observers. For the model observer, the authors used a CHO with Gabor channels, which involves six channel passbands, five orientations, and two phases, leading to a total of 60 channels. The performance predicted by the CHO was compared with that obtained by four medical physicists at each 2AFC study. Results: The human and model observers were highly correlated at each dose level for each lesion size for both FBP and IR. The Pearson's product-moment correlation coefficients were 0.986 [95% confidence interval (CI): 0.958-0.996] for FBP and 0.985 (95% CI: 0.863-0.998) for IR. Bland-Altman plots showed excellent agreement for all dose levels and lesions sizes with a mean absolute difference of 1.0%{+-} 1.1% for FBP and 2.1%{+-} 3.3% for IR. Conclusions: Human observer performance on a 2AFC lesion detection task in CT with a uniform background can be accurately predicted by a CHO model observer at different radiation dose levels and for both FBP and IR methods.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Low-dose phase contrast tomography with conventional x-ray sources

Purpose: The edge illumination (EI) x-ray phase contrast imaging (XPCi) method has been recently further developed to perform tomographic and, thus, volumetric imaging. In this paper, the first tomographic EI XPCi images acquired with a conventional x-ray source at dose levels below that used for preclinical small animal imaging are presented. Methods: Two test objects, a biological sample and a custom-built phantom, were imaged with a laboratory-based EI XPCi setup in tomography mode. Tomographic maps that show the phase shift and attenuating properties of the object were reconstructed, and analyzed in terms of signal-to-noise ratio and quantitative accuracy. Dose measurements using thermoluminescence devices were performed. Results: The obtained images demonstrate that phase based imaging methods can provide superior results compared to attenuation based modalities for weakly attenuating samples also in 3D. Moreover, and, most importantly, they demonstrate the feasibility of low-dose imaging. In addition, the experimental results can be considered quantitative within the constraints imposed by polychromaticity. Conclusions: The results, together with the method's dose efficiency and compatibility with conventional x-ray sources, indicate that tomographic EI XPCi can become an important tool for the routine imaging of biomedical samples.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

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↗
DOE OSTI2015

SU-D-303-03: Impact of Uncertainty in T1 Measurements On Quantification of Dynamic Contrast Enhanced MRI

Purpose: Quantification of dynamic contrast enhanced (DCE) MRI requires native longitudinal relaxation time (T1) measurement. This study aimed to assess uncertainty in T1 measurements using two different methods. Methods and Materials: Brain MRI scans were performed on a 3T scanner in 9 patients who had low grade/benign tumors and partial brain radiotherapy without chemotherapy at pre-RT, week-3 during RT (wk-3), end-RT, and 1, 6 and 18 months after RT. T1-weighted images were acquired using gradient echo sequences with 1) 2 different flip angles (50 and 150), and 2) 5 variable TRs (100–2000ms). After creating quantitative T1 maps, average T1 was calculated in regions of interest (ROI), which were distant from tumors and received a total of accumulated radiation doses < 5 Gy at wk-3. ROIs included left and right normal Putamen and Thalamus (gray matter: GM), and frontal and parietal white matter (WM). Since there were no significant or even a trend of T1 changes from pre-RT to wk-3 in these ROIs, a relative repeatability coefficient (RC) of T1 as a measure of uncertainty was estimated in each ROI using the data pre-RT and at wk-3. The individual T1 changes at later time points were evaluated compared to the estimated RCs. Results: The 2-flip angle method produced small RCs in GM (9.7–11.7%) but large RCs in WM (12.2–13.6%) compared to the saturation-recovery (SR) method (11.0–17.7% for GM and 7.5–11.2% for WM). More than 81% of individual T1 changes were within T1 uncertainty ranges defined by RCs. Conclusion: Our study suggests that the impact of T1 uncertainty on physiological parameters derived from DCE MRI is not negligible. A short scan with 2 flip angles is able to achieve repeatability of T1 estimates similar to a long scan with 5 different TRs, and is desirable to be integrated in the DCE protocol. Present study was supported by National Institute of Health (NIH) under grant numbers; UO1 CA183848 and RO1 NS064973.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-I-19: Optimization of Low Contrast Detectability Across Two CT Manufacturers

Purpose: Our goal was to evaluate low contrast detectability (LCD) for abdominal CT protocols across two CT scanner manufacturers, while producing a similar noise texture and CTDIvol for acquired images. Methods: A CIRS tissue equivalent LCD phantom containing three columns of 7 spherical targets, ranging from 10 mm to 2.4 mm, that are 5, 10, and 20 HU below the background matrix (HUBB) was scanned using two a GE HD750 64 slice scanner and a Siemens Somatom Definition AS 64 slice scanner. Protocols were designed to deliver a CTDIvol of 12.26 mGy and images were reconstructed with FBP, ASIR and Sapphire. Comparisons were made with those algorithms that had matching noise power spectrum peaks (NPS). NPS information was extracted from a previously published article that matched NPS peak frequencies across manufacturers by calculating the NPS from uniform phantom images reconstructed with several IR algorithms. Results: The minimum detectable lesion size in the 20 HUBB and 10 HUBB column was 6.3 mm, and 10 mm in the 5 HUBB column for the GE HD 750 scanner. The minimum detectable lesion size in the 20 HUBB column was 4.8 mm, in the 10 HUBB column, 9.5 mm, and the 5 HUBB column, 10 mm for the Siemens Somatom Definition AS. Conclusion: Reducing radiation dose while improving or maintaining LCD is possible with application of IR. However, there are several different IR algorithms, with each generating a different resolution and noise texture. In multi-manufacturer settings, matching only the CTDIvol between manufacturers may Result in a loss of clinically relevant information.

60 APPLIED LIFE SCIENCES↗