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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Effects of forest structural and compositional change on forest microclimates across a gradient of disturbance severity

Forest structural diversity and community composition are key in regulating forest microclimates. When disturbance affects structural diversity or composition, forest microclimates may be altered due to changes in soil temperature, soil water content, and light availability. It is unclear however which structural or compositional components, when changed or to what extent, result in microclimatic change. To address this question, we used data from a large scale, manipulative stem-girdling experiment in northern, lower Michigan—the Forest Resilience and Threshold Experiment (FoRTE). FoRTE follows a factorial design with multiple levels of disturbance severity (0, 45, 65, 85%) based on targeted reductions in gross leaf area index via stem-girdling induced mortality. These disturbance severity treatments are applied in two ways: either as top-down (largest trees are killed) or bottom-up (small to medium trees killed) treatments. We examined how multiple components of structural diversity and community composition changed as a product of disturbance severity and type, and then tested for resulting effects on forest microclimates (light availability, soil temperature, and soil water), using a multivariate, Random Forest framework. We found that measures of community composition (species richness, species evenness, and Shannon-Wiener Diversity Index) and stand structure (basal area, standard deviation of DBH, tree size diversity) declined more following disturbance than did measures of canopy cover, heterogeneity, arrangement, or height. However, when changes in each variable from pre- to post-disturbance, measured as log change, were employed in a multivariate, Random Forest regression framework, structural diversity measures of heterogeneity (rugosity, top rugosity), cover (canopy cover), and arrangement (porosity) were the most influential variables, but with differences among bottom-up and top-down treatments We found that the death of large trees from disturbance impacts soil temperature, water, and light environments more substantially and uniformly across disturbance gradients than does the death of smaller trees. Furthermore, our results have implications for both statistical and process-based modeling of forest disturbance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Microwave-assisted synthesis of mixed-linker covalent organic frameworks enabling tunable and ultrahigh iodine capture

The use of covalent organic frameworks (COFs) for hazardous radioiodine capture has been highly sought after recently. However, the synthesis of high-performance COF adsorbents while circumventing the limitations of traditional solvothermal methods remains largely unexplored. Herein, we for the first time combine microwave-assisted synthesis and mixed-linker strategy to fabricate multivariate COF adsorbents (X% OMe-TFB-BD COFs, X% = 0, 33, 50, 67, and 100 mol%) with varying ratios of benzidine (BD) and 3,3'-dimethoxylbenzidine (BD-OMe) linkers in a rapid and facile manner. Adjusting the BD-OMe/BD mole ratios has led to distinct variations in density, crystallinity, porosity, morphology, and thermal/chemical stability of the resultant COFs, which empowered fine-tuning of the adsorption performance towards static iodine vapor. Remarkably, the 50% OMe-TFB-BD COF exhibited an ultrahigh iodine adsorption capability of 8.2 g g –1 , surpassing those of single-component COFs, mixed-linker COFs with other methoxy content, physically blended mixtures, and most existing COF adsorbents. Moreover, 50% OMe-TFB-BD COF was recyclable seven times without obvious loss in its adsorption capacity. Finally, this work underscores the substantial potential of microwave-assisted mixed-linker strategy as a viable approach for developing multivariate COFs with shortened reaction times, precisely tailored pore environment, and tunable sorption properties, which are of considerable promise for environmental remediation and other niche applications.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Interpreting mixing relationships in energetic melts to estimate vapor contribution and composition

Heterogeneous, glassy debris can be produced by energetic events such as near surface nuclear explosions and asteroid impacts. In these events, the resultant debris comprises a rapidly-cooled mixture of the projectile or bomb material with proximate materials such as soil and anthropogenic structures. Glasses formed in these events preserve inter and/or intra sample compositional variation reflecting complex mixtures of the precursor materials or their chemically fractionated products. Understanding formation mechanisms and chemical processes relating to energetic glass formation based on study of the end products requires an objective method for calculating the precursor components that mixed together to produce the final product. Here, we compare a set of multivariate linear-least squares approaches to address the unmixing problem of heterogeneous glasses including classical least squares (CLS), principal component analysis (PCA) and two multivariate curve resolution – alternating least squares (MCR-ALS) approaches. We generate a synthetic data set representing spatially resolved, compositional data in a set of heterogeneously mixed glasses to understand model sensitivity to precursor abundance and composition. We explore the impact of incomplete knowledge of the system prior to the formation of the melts on the resulting confidence and accuracy of the solution (i.e., the number, composition, and abundances of the precursor materials). We conclude that a closure and equality constrained MCR-ALS approach succeeds in identifying unrecognized precursor components and is a suitable alternative to CLS approaches when the investigator has incomplete knowledge of the starting precursor chemical compositions. Finally, we demonstrate application of this MCR-ALS approach to measurements of Trinitite.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2018

A continuous analogue of the tensor-train decomposition

We develop new approximation algorithms and data structures for representing and computing with multivariate functions using the functional tensor-train (FT), a continuous extension of the tensor-train (TT) decomposition. The FT represents functions using a tensor-train ansatz by replacing the three-dimensional TT cores with univariate matrix-valued functions. The main contribution of this paper is a framework to compute the FT that employs adaptive approximations of univariate fibers, and that is not connected to any tensorized discretization. The algorithm can be coupled with any univariate linear or nonlinear approximation procedure. We demonstrate that this approach can generate multivariate function approximations that are several orders of magnitude more accurate, for the same cost, than those based on the conventional approach of compressing the coefficient tensor of a tensor-product basis. Our approach is in the spirit of other continuous computation packages such as Chebfun, and yields an algorithm which requires the computation of “continuous” matrix factorizations such as the LU and QR decompositions of vector-valued functions. To support these developments, we describe continuous versions of an approximate maximum-volume cross approximation algorithm and of a rounding algorithm that re-approximates an FT by one of lower ranks. We demonstrate that our technique improves accuracy and robustness, compared to TT and quantics-TT approaches with fixed parameterizations, of high-dimensional integration, differentiation, and approximation of functions with local features such as discontinuities and other nonlinearities.

42 ENGINEERING↗
DOE OSTI2024

PlasmoData.jl — A Julia framework for modeling and analyzing complex data as graphs

Datasets encountered in scientific and engineering applications appear in complex formats (e.g., images, multivariate time series, molecules, video, text strings, networks). Graph theory provides a unifying framework to model such datasets and enables the use of powerful tools that can help analyze, visualize, and extract value from data. In this work, we present PlasmoData.jl, an open-source, Julia framework that uses concepts of graph theory to facilitate the modeling and analysis of complex datasets. The core of our framework is a general data modeling abstraction, which we call a DataGraph. We show how the abstraction and software implementation can be used to represent diverse data objects as graphs and to enable the use of tools from topology, graph theory, and machine learning (e.g., graph neural networks) to conduct a variety of tasks. We illustrate the versatility of the framework by using real datasets: (i) an image classification problem using topological data analysis to extract features from the graph model to train machine learning models; (ii) a disease outbreak problem where we model multivariate time series as graphs to detect abnormal events; and (iii) a technology pathway analysis problem where we highlight how we can use graphs to navigate connectivity. Further, our discussion also highlights how PlasmoData.jl leverages native Julia capabilities to enable compact syntax, scalable computations, and interfaces with diverse packages. Overall, we show that the DataGraph abstraction and PlasmoData.jl Julia package are able to model data within graphs and enable useful analysis.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

A susceptibility gene signature for ERBB2-driven mammary tumour development and metastasis in collaborative cross mice

Background: Deeper insights into ERBB2-driven cancers are essential to develop new treatment approaches for ERBB2+ breast cancers (BCs). We employed the Collaborative Cross (CC) mouse model to unearth genetic factors underpinning Erbb2-driven mammary tumour development and metastasis. Methods: 732 F1 hybrid female mice between FVB/N MMTV-Erbb2 and 30 CC strains were monitored for mammary tumour phenotypes. GWAS pinpointed SNPs that influence various tumour phenotypes. Multivariate analyses and models were used to construct the polygenic score and to develop a mouse tumour susceptibility gene signature (mTSGS), where the corresponding human ortholog was identified and designated as hTSGS. The importance and clinical value of hTSGS in human BC was evaluated using public datasets, encompassing TCGA, METABRIC, GSE96058, and I-SPY2 cohorts. The predictive power of mTSGS for response to chemotherapy was validated in vivo using genetically diverse MMTV-Erbb2 mice. Findings: Distinct variances in tumour onset, multiplicity, and metastatic patterns were observed in F1-hybrid female mice between FVB/N MMTV-Erbb2 and 30 CC strains. Besides lung metastasis, liver and kidney metastases emerged in specific CC strains. GWAS identified specific SNPs significantly associated with tumour onset, multiplicity, lung metastasis, and liver metastasis. Multivariate analyses flagged SNPs in 20 genes (Stx6, Ramp1, Traf3ip1, Nckap5, Pfkfb2, Trmt1l, Rprd1b, Rer1, Sepsecs, Rhobtb1, Tsen15, Abcc3, Arid5b, Tnr, Dock2, Tti1, Fam81a, Oxr1, Plxna2, and Tbc1d31) independently tied to various tumour characteristics, designated as a mTSGS. hTSGS scores (hTSGSS) based on their transcriptional level showed prognostic values, superseding clinical factors and PAM50 subtype across multiple human BC cohorts, and predicted pathological complete response independent of and superior to MammaPrint score in I-SPY2 study. The power of mTSGS score for predicting chemotherapy response was further validated in an in vivo mouse MMTV-Erbb2 model, showing that, like findings in human patients, mouse tumours with low mTSGS scores were most likely to respond to treatment. Interpretation: Our investigation has unveiled many new genes predisposing individuals to ERBB2-driven cancer. Translational findings indicate that hTSGS holds promise as a biomarker for refining treatment strategies for patients with BC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Multi-Objective design of interlocking metasurfaces using conditional diffusion models

Unit cell design remains a major challenge for interlocking metasurfaces, a promising joining technology for dissimilar materials, due to the complex, competing, multivariate design space and the need for rapid adaptation to varying performance requirements. This study explores Conditional Diffusion Models as a design optimization tool for interlocking metasurfaces. Given the complex, competing, multivariate design space for interlocking metasurfaces, unit cell design remains a major challenge for this joining technology. We trained a conditional diffusion model on 25,000 finite element analysis-simulated interlocking metasurface unit cells to generate designs with tailored thermo-mechanical properties (tensile strength, shear strength, and thermal conductivity) based on specified performance criteria. The model demonstrated a success rate of approximately 72 % in producing designs that met specified property bounds. The conditional diffusion model generated both thermally resistive and conductive designs, revealing clear trends in design characteristics: taller, dendritic structures were advantageous for tensile loads, while shorter, robust designs excelled in shear applications. Our findings indicate that the model's performance is more influenced by the breadth of the design space than by the quantity of training data, highlighting the importance of expansive design domains for generating innovative solutions. This work establishes conditional diffusion models as a highly efficient and adaptable tool for rapid interlocking metasurface unit cell design, paving the way for advancements in multi-material joining technologies, as well as highlighting the justification to leverage conditional diffusion models as design tools across complex design domains.

Conditional diffusion models↗
DOE OSTI2014

Cadmium, type 2 diabetes, and kidney damage in a cohort of middle-aged women

Background: It has been proposed that diabetic patients are more sensitive to the nephrotoxicity of cadmium (Cd) compared to non-diabetics, but few studies have examined this in humans, and results are inconsistent. Aim: To test the hypothesis that women with type 2 diabetes mellitus (DM) or impaired glucose tolerance (IGT) have higher risk of kidney damage from cadmium compared to women with normal glucose tolerance (NGT). Methods: All 64-year-old women in Gothenburg, Sweden, were invited to a screening examination including repeated oral glucose tolerance tests. Random samples of women with DM, IGT, and NGT were recruited for further clinical examinations. Serum creatinine was measured and used to calculate estimated glomerular filtration rate (eGFR). Albumin (Alb) and retinol-binding protein (RBP) were analyzed in a 12 h urine sample. Cadmium in blood (B-Cd) and urine (U-Cd) was determined using inductively coupled plasma mass spectrometry. Associations between markers of kidney function (eGFR, Alb, and RBP) and quartiles of B-Cd and U-Cd were evaluated in models, including also blood pressure and smoking habits. Results: The mean B-Cd (n=590) was 0.53 µg/L (median 0.34 µg/L). In multivariable models, a significant interaction was seen between high B-Cd (upper quartile, >0.56 µg/L) and DM (point estimate +0.40 mg Alb/12 h, P=0.04). In stratified analyzes, the effect of high B-Cd on Alb excretion was significant in women with DM (53% higher Alb/12 h, P=0.03), but not in women with IGT or NGT. Models with urinary albumin adjusted for creatinine showed similar results. In women with DM, the multivariable odds ratio (OR) for microalbuminuria (>15 mg/12 h) was increased in the highest quartile of B-Cd vs. B-Cd quartiles 1–3 in women with DM (OR 4.2, 95% confidence interval 1.1–12). No such effect was found in women with IGT or NGT. There were no associations between B-Cd and eGFR or excretion of RBP, and no differences between women with DM, IGT, or NGT regarding effect of B-Cd on eGFR or RBP. Conclusion: The present study provides support for the hypothesis that women with DM have higher risk of renal glomerular damage from cadmium exposure compared to women without DM. - Highlights: • Cadmium in blood, kidney function, and glucose tolerance was examined in 590 women. • Blood cadmium was associated with albumin excretion in women with type 2 diabetes. • No such associations with cadmium were found in women without diabetes. • Women with type 2 diabetes have increased sensitivity to kidney damage from cadmium.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Exposure to lithium through drinking water and calcium homeostasis during pregnancy: A longitudinal study

There is increasing evidence of adverse health effects due to elevated lithium exposure through drinking water but the impact on calcium homeostasis is unknown. This study aimed at elucidating if lithium exposure through drinking water during pregnancy may impair the maternal calcium homeostasis. In a population-based mother-child cohort in the Argentinean Andes (n=178), with elevated lithium concentrations in the drinking water (5–1660 μg/L), blood lithium concentrations (correlating significantly with lithium in water, urine and plasma) were measured repeatedly during pregnancy by inductively coupled plasma mass spectrometry and used as exposure biomarker. Markers of calcium homeostasis included: plasma 25-hydroxyvitamin D{sub 3}, serum parathyroid hormone (PTH), and calcium, phosphorus and magnesium concentrations in serum and urine. The median maternal blood lithium concentration was 25 μg/L (range 1.9–145). In multivariable-adjusted mixed-effects linear regression models, blood lithium was inversely associated with 25-hydroxyvitamin D{sub 3} (−6.1 nmol/L [95%CI −9.5; −2.6] for a 25 μg/L increment in blood lithium). The estimate increased markedly with increasing percentiles of 25-hydroxyvitamin D{sub 3}. In multivariable-adjusted mixed-effects logistic regression models, the odds ratio of having 25-hydroxyvitamin D3<30 nmol/L (19% of the women) was 4.6 (95%CI 1.1; 19.3) for a 25 μg/L increment in blood lithium. Blood lithium was also positively associated with serum magnesium, but not with serum calcium and PTH, and inversely associated with urinary calcium and magnesium. In conclusion, our study suggests that lithium exposure through drinking water during pregnancy may impair the calcium homeostasis, particularly vitamin D. The results reinforce the need for better control of lithium in drinking water, including bottled water. - Highlights: • Elevated drinking water lithium (Li) concentrations are increasingly reported. • We studied a Li-exposed population-based mother-child cohort in northern Argentina. • Li exposure during pregnancy affected maternal calcium homeostasis. • Blood Li was consistently inversely associated with maternal plasma vitamin D{sub 3}. • Associations were independent of season of sampling and lifestyle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

On the quantification and efficient propagation of imprecise probabilities with copula dependence

This paper addresses the problem of quantification and propagation of uncertainties associated with dependence modeling when data for characterizing probability models are limited. Practically, the system inputs are often assumed to be mutually independent or correlated by a multivariate Gaussian distribution. However, this subjective assumption may introduce bias in the response estimate if the real dependence structure deviates from this assumption. In this work, we overcome this limitation by introducing a flexible copula dependence model to capture complex dependencies. Here, a hierarchical Bayesian multimodel approach is proposed to quantify uncertainty in dependence model-form and model parameters that result from small data sets. This approach begins by identifying, through Bayesian multimodel inference, a set of candidate marginal models and their corresponding model probabilities, and then estimating the uncertainty in the copula-based dependence structure, which is conditional on the marginals and their parameters. The overall uncertainties integrating marginals and copulas are probabilistically represented by an ensemble of multivariate candidate densities. A novel importance sampling reweighting approach is proposed to efficiently propagate the overall uncertainties through a computational model. Through an example studying the influence of constituent properties on the out-of-plane properties of transversely isotropic E-glass fiber composites, we show that the composite property with copula-based dependence model converges to the true estimate as data set size increases, while an independence or arbitrary Gaussian correlation assumption leads to a biased estimate.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

Classification System for Identifying Women at Risk for Altered Partial Breast Irradiation Recommendations After Breast Magnetic Resonance Imaging

Purpose: To study the utility of preoperative breast MRI for partial breast irradiation (PBI) patient selection, using multivariable analysis of significant risk factors to create a classification rule. Methods and Materials: Between 2002 and 2009, 712 women with newly diagnosed breast cancer underwent preoperative bilateral breast MRI at Mayo Clinic Florida. Of this cohort, 566 were retrospectively deemed eligible for PBI according to the National Surgical Adjuvant Breast and Bowel Project Protocol B-39 inclusion criteria using physical examination, mammogram, and/or ultrasound. Magnetic resonance images were then reviewed to determine their impact on patient eligibility. The patient and tumor characteristics were evaluated to determine risk factors for altered PBI eligibility after MRI and to create a classification rule. Results: Of the 566 patients initially eligible for PBI, 141 (25%) were found ineligible because of pathologically proven MRI findings. Magnetic resonance imaging detected additional ipsilateral breast cancer in 118 (21%). Of these, 62 (11%) had more extensive disease than originally noted before MRI, and 64 (11%) had multicentric disease. Contralateral breast cancer was detected in 28 (5%). Four characteristics were found to be significantly associated with PBI ineligibility after MRI on multivariable analysis: premenopausal status (P=.021), detection by palpation (P<.001), first-degree relative with a history of breast cancer (P=.033), and lobular histology (P=.002). Risk factors were assigned a score of 0-2. The risk of altered PBI eligibility from MRI based on number of risk factors was 0:18%; 1:22%; 2:42%; 3:65%. Conclusions: Preoperative bilateral breast MRI altered the PBI recommendations for 25% of women. Women who may undergo PBI should be considered for breast MRI, especially those with lobular histology or with 2 or more of the following risk factors: premenopausal, detection by palpation, and first-degree relative with a history of breast cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Comparison of 2 Common Radiation Therapy Techniques for Definitive Treatment of Small Cell Lung Cancer

Purpose: Two choices are widely used for radiation delivery, 3-dimensional conformal radiation therapy (3DCRT) and intensity modulated radiation therapy (IMRT). No randomized comparisons have been conducted in the setting of lung cancer, but theoretical concerns suggest that IMRT may negatively impact disease control. We analyzed a large cohort of limited-stage small-cell lung cancer (LS-SCLC) patients treated before and after institutional conversion from 3DCRT to IMRT to compare outcomes. Methods and Materials: Patients with LS-SCLC treated with definitive radiation at our institution between 2000 and 2009 were retrospectively reviewed. Both multivariable Cox regression and propensity score matching were used to compare oncologic outcomes of 3DCRT and IMRT in the context of other clinically relevant covariables. Acute and chronic toxicities associated with the 2 techniques were compared using Fisher exact and log–rank tests, respectively. Results: A total of 223 patients were treated during the study period, with 119 receiving 3DCRT and 104 receiving IMRT. Their median age was 64 years (range, 39-90 years). Median follow-up times for 3DCRT and IMRT were 27 months (range, 2-147 months) and 22 months (range, 4-83 months), respectively. Radiation modality was not associated with differences in overall survival or disease-free survival in either multivariable or propensity score-matched analyses. IMRT patients required significantly fewer percutaneous feeding tube placements (5% vs 17%, respectively, P=.005). Conclusions: IMRT was not associated with worse oncologic outcomes than those of 3DCRT. IMRT was associated with a lower rate of esophagitis-related percutaneous feeding tube placements.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Symptomatic Pericardial Effusion After Chemoradiation Therapy in Esophageal Cancer Patients

Purpose: We investigated clinical and treatment-related factors as predictors of symptomatic pericardial effusion in esophageal cancer patients after concurrent chemoradiation therapy. Methods and Materials: We reviewed 214 consecutive primary esophageal cancer patients treated with concurrent chemoradiation therapy between 2001 and 2010 in our institute. Pericardial effusion was detected on follow-up computed tomography. Symptomatic effusion was defined as effusion ≥grade 3 according to Common Terminology Criteria for Adverse Events v4.0 criteria. Percent volume irradiated with 5 to 65 Gy (V5-V65) and mean dose to the pericardium were evaluated employing dose-volume histograms. To evaluate dosimetry for patients treated with two-dimensional planning in the earlier period (2001-2005), computed tomography data at diagnosis were transferred to a treatment planning system to reconstruct three-dimensional plans without modification. Optimal dosimetric thresholds for symptomatic pericardial effusion were calculated by receiver operating characteristic curves. Associating clinical and treatment-related risk factors for symptomatic pericardial effusion were detected by univariate and multivariate analyses. Results: The median follow-up was 29 (range, 6-121) months for eligible 167 patients. Symptomatic pericardial effusion was observed in 14 (8.4%) patients. Dosimetric analyses revealed average values of V30 to V45 for the pericardium and mean pericardial doses were significantly higher in patients with symptomatic pericardial effusion than in those with asymptomatic pericardial effusion (P<.05). Pericardial V5 to V55 and mean pericardial doses were significantly higher in patients with symptomatic pericardial effusion than in those without pericardial effusion (P<.001). Mean pericardial doses of 36.5 Gy and V45 of 58% were selected as optimal cutoff values for predicting symptomatic pericardial effusion. Multivariate analysis identified mean pericardial dose as the strongest risk factor for symptomatic pericardial effusion. Conclusions: Dose-volume thresholds for the pericardium facilitate predicting symptomatic pericardial effusion. Mean pericardial dose was selected based not only on the optimal dose-volume threshold but also on the most significant risk factor for symptomatic pericardial effusion.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Do Angiotensin-Converting Enzyme Inhibitors Reduce the Risk of Symptomatic Radiation Pneumonitis in Patients With Non-Small Cell Lung Cancer After Definitive Radiation Therapy? Analysis of a Single-Institution Database

Purpose: Preclinical studies have suggested that angiotensin-converting enzyme inhibitors (ACEIs) can mitigate radiation-induced lung injury. We sought here to investigate possible associations between ACEI use and the risk of symptomatic radiation pneumonitis (RP) among patients undergoing radiation therapy (RT) for non–small cell lung cancer (NSCLC). Methods and Materials: We retrospectively identified patients who received definitive radiation therapy for stages I to III NSCLC between 2004 and 2010 at a single tertiary cancer center. Patients must have received a radiation dose of at least 60 Gy for a single primary lung tumor and have had imaging and dosimetric data available for analysis. RP was quantified according to Common Terminology Criteria for Adverse Events, version 3.0. A Cox proportional hazard model was used to assess potential associations between ACEI use and risk of symptomatic RP. Results: Of 413 patients analyzed, 65 were using ACEIs during RT. In univariate analysis, the rate of RP grade ≥2 seemed lower in ACEI users than in nonusers (34% vs 46%), but this apparent difference was not statistically significant (P=.06). In multivariate analysis of all patients, ACEI use was not associated with the risk of symptomatic RP (hazard ratio [HR] = 0.66; P=.07) after adjustment for sex, smoking status, mean lung dose (MLD), and concurrent carboplatin and paclitaxel chemotherapy. Subgroup analysis showed that ACEI use did have a protective effect from RP grade ≥2 among patients who received a low (≤20-Gy) MLD (P<.01) or were male (P=.04). Conclusions: A trend toward reduction in symptomatic RP among patients taking ACEIs during RT for NSCLC was not statistically significant on univariate or multivariate analyses, although certain subgroups may benefit from use (ie, male patients and those receiving low MLD). The evidence at this point is insufficient to establish whether the use of ACEIs does or does not reduce the risk of RP.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Galectin-1 Is an Independent Prognostic Factor for Local Recurrence and Survival After Definitive Radiation Therapy for Patients With Squamous Cell Carcinoma of the Uterine Cervix

Purpose: To investigate the role of galectin-1 in patients with cervical cancer after definitive radiation therapy. Methods and Materials: We reviewed 154 patients with International Federation of Gynecology and Obstetrics stage I-II squamous cell carcinoma. Patients underwent curative-intent radiation therapy. Paraffin-embedded tissues were analyzed using immunohistochemistry staining for galectin-1. The rates of cancer-specific survival (CSS), local recurrence (LR), and distant metastasis were compared among patient tissue samples with no, weak, and strong galectin-1 expression. The Kaplan-Meier method and the Cox proportional hazard model with hazard ratios and 95% confidence intervals (CIs) were used for univariate and multivariate analyses, respectively. Results: The areas under the curve for the intracellular expression scores of galectin-1 for both LR and CSS were significantly higher than those for stromal expression. There were no significant differences in the demographic data, such as stage and serum tumor markers, between patients with and without intracellular expression of galectin-1 in cancer tissue samples. Using multivariate analyses, the hazard ratios of LR and CSS were 2.60 (95% CI 1.50-4.52) (P=.001) and 1.94 (95% CI 1.18-3.19) (P=.010), respectively. Conclusion: Galectin-1 is an independent prognostic factor associated with LR and CSS in stage I-II cervical cancer patients undergoing definitive radiation therapy. Further studies targeting galectin-1 may improve the local control of cervical cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Patterns and Predictors of Early Biochemical Recurrence After Radical Prostatectomy and Adjuvant Radiation Therapy in Men With pT{sub 3}N{sub 0} Prostate Cancer: Implications for Multimodal Therapies

Purpose: The aim of our study was to evaluate patterns and predictors of early biochemical recurrence (eBCR) after radical prostatectomy (RP) and adjuvant radiation therapy (aRT) in order to identify which individuals might benefit from additional treatments. Methods and Materials: We evaluated 390 patients with pT{sub 3}N{sub 0} prostate cancer (PCa) receiving RP and aRT at 6 European centers between 1993 and 2006. Patients who were free from BCR at <2 years' follow-up were excluded. This resulted in 374 assessable patients. Early BCR was defined as 2 consecutive prostate-specific antigen (PSA) test values >0.2 ng/mL within 2 or 3 years after aRT. Uni- and multivariable Cox regression analyses predicting overall and eBCR after aRT were fitted. Covariates consisted of preoperative PSA results, surgical margins, pathological stage, Gleason score, and aRT dose. Results: Overall, 5- and 8-year BCR-free survival rates were 77.1% and 70.8%, respectively. At a median follow-up of 86 months after aRT, 33 (8.8%) and 55 (14.6%) men experienced BCR within 2 or 3 years after aRT, respectively. In multivariable analyses, Gleason scores of 8 to 10 represented the only independent predictor of eBCR after aRT (all, P≤.01). The risk of BCR was significantly higher in patients with a Gleason score of 8 to 10 disease than in those with Gleason 2 to 6 within 24 months after treatment, after adjusting for all covariates (all, P≤.04). However, given a 24-month BCR free period, the risk of subsequent BCR for men with poorly differentiated disease was equal to that of men with less aggressive disease (all, P≥.3). Conclusions: High Gleason score represents the only predictor of eBCR after RP and aRT in patients affected by pT{sub 3}N{sub 0} PCa. Given the association between early PSA recurrence, clinical progression, and mortality, these patients might be considered candidates for adjuvant medical therapy and/or prophylactic whole-pelvis radiation therapy in addition to aRT, delivered to the prostatic bed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Local Recurrence in Women With Stage I Breast Cancer: Declining Rates Over Time in a Large, Population-Based Cohort

Purpose: To evaluate whether local recurrence (LR) risk has changed over time among women with stage I breast cancer treated with breast-conserving therapy. Methods and Materials: Subjects were 5974 women aged ≥50 years diagnosis with pT1N0 breast cancer from 1989 to 2006, treated with breast-conserving surgery and radiation therapy. Clinicopathologic characteristics, treatment, and LR outcomes were compared among 4 cohorts stratified by year of diagnosis: 1989 to 1993 (n=1077), 1994 to 1998 (n=1633), 1999 to 2002 (n=1622), and 2003 to 2006 (n=1642). Multivariable analysis was performed, with year of diagnosis as a continuous variable. Results: Median follow-up time was 8.6 years. Among patients diagnosed in 1989 to 1993, 1994 to 1998, 1999 to 2002, and 2003 to 2006, the proportions of grade 1 tumors increased (16% vs 29% vs 40% vs 39%, respectively, P<.001). Surgical margin clearance rates increased from 82% to 93% to 95% and 88%, respectively (P<.001). Over time, the proportions of unknown estrogen receptor (ER) status decreased (29% vs 10% vs 1.2% vs 0.5%, respectively, P<.001), whereas ER-positive tumors increased (56% vs 77% vs 86% vs 86%, respectively, P<.001). Hormone therapy use increased (23% vs 23% vs 62% vs 73%, respectively, P<.001), and chemotherapy use increased (2% vs 5% vs 10% vs 13%, respectively, P<.001). The 5-year cumulative incidence rates of LR over the 4 time periods were 2.8% vs 1.7% vs 0.9% vs 0.8%, respectively (Gray's test, P<.001). On competing risk multivariable analysis, year of diagnosis was significantly associated with decreased LR (hazard ratio, 0.92 per year, P=.0003). Relative to grade 1 histology, grades 2, 3, and unknown were associated with increased LR. Hormone therapy use was associated with reduced LR. Conclusion: Significant changes in the multimodality management of stage I breast cancer have occurred over the past 2 decades. More favorable-risk tumors were diagnosed, and margin clearance and systemic therapy use increased. These changes contributed to the observed declining LR rates among patients treated with breast-conserving therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Prostate-Specific Antigen at 4 to 5 Years After Low-Dose-Rate Prostate Brachytherapy Is a Strong Predictor of Disease-Free Survival

Purpose: To determine (1) the prognostic utility of prostate-specific antigen (PSA) concentration at 45 to 60 months (48mPSA) after low-dose-rate prostate brachytherapy (LDR-PB); (2) the predictors of 48mPSA; and (3) the prognostic utility of directional trends between PSA levels at 24, 36, and 48 months after LDR-PB. Methods and Materials: Between 1998 and 2008, 2223 patients with low- and intermediate-risk prostate cancer received LDR-PB monotherapy. A cohort of 1434 of these patients was identified with a documented 48mPSA and no evidence of disease relapse prior to the 48mPSA. In addition, a subset of this cohort (n=585) was identified with ≥72 months of follow-up and documented PSA values at both 24 and 36 months after implantation. Results: Median follow-up time was 76 months. Eight-year Kaplan-Meier disease-free survival (DFS) rates were 100% vs 73.4% for patients with 48mPSA ≤0.2 vs those with >0.2 ng/mL; 99.1% versus 53.8% for a 48mPSA threshold of ≤0.4 versus >0.4 ng/mL, respectively; and 97.3% versus 0% for a threshold of ≤1.0 versus >1.0 ng/mL, respectively. On multivariate analysis, the only factor predictive of DFS was 48mPSA (P<.0001). On subset analysis (n=585), 29 patients had a PSA rise (defined as >0.2 ng/mL) between 24 and 36 months, 24 patients had a rise between 36 and 48 months, and 11 patients had rises over both intervals. Failure rates in these patients were 52%, 79%, and 100%, respectively. On multivariate analysis, initial PSA, androgen deprivation therapy, and dose to 90% of the prostate significantly correlated with 48mPSA but together accounted for only ∼5% of its total variance. Conclusions: The 48mPSA after LDR-PB is highly predictive of long-term DFS. Patients with 48mPSA ≤0.4 ng/mL had a <1% risk of disease relapse at 8 years, whereas all patients with 48mPSA >1.0 ng/mL relapsed. Consecutive PSA rises of >0.2 ng/mL from 24 to 36 months and from 36 to 48 months were also highly predictive of subsequent failure.

62 RADIOLOGY AND NUCLEAR MEDICINE↗