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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Differences in muscle contraction onset as determined by ultrasound and electromyography

ABSTRACT Introduction We characterize the agreement between the timing of muscle contraction onset detected by surface electromyography (sEMG), fine wire EMG (fwEMG), and motion‐mode (M‐mode) ultrasound for improved interpretations of clinical outcomes. Methods Eighteen healthy adults participated. Differences in contraction onset were compared between sEMG, fwEMG, and M‐mode ultrasound collected during concentric contractions of the vastus lateralis and biceps brachii. Results The mean difference of 13.1 ms (‐33.3–59.9) between sEMG and fwEMG was non‐significant (intraclass correlation [ICC] = 0.60). Ultrasound was significantly different from surface and fine wire EMG (ICC = 0.65 and ICC = 0.40, respectively), occurring 98.6 ms (72.3–124.9) and 111.7 (60.3–163.0) before sEMG and fwEMG, respectively. Nonparametric interquartile ranges were also wide. Conclusions Due to high variability, comparisons between EMG methods should be interpreted with caution. Ultrasound detected onset before either EMG method, which may indicate motion from adjacent muscles during voluntary contractions. Muscle Nerve 59:494–500, 2019

Tweedell, Andrew J.↗
DOE OSTI2019

Diffusion and perfusion MR parameters to assess preoperative short-course radiotherapy response in locally advanced rectal cancer: a comparative explorative study among Standardized Index of Shape by DCE-MRI, intravoxel incoherent motion- and diffusion kurtosis imaging-derived parameters

Purpose: To assess preoperative short-course radiotherapy (SCR) tumor response in locally advanced rectal cancer (LARC) by means of Standardized Index of Shape (SIS) by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) parameters derived from diffusion-weighted MRI (DW-MRI). Materials and methods: Thirty-four patients with LARC who underwent MRI scans before and after SCR followed by delayed surgery, retrospectively, were enrolled. SIS, ADC, IVIM parameters [tissue diffusion (D{sub t}), pseudo-diffusion (D{sub p}), perfusion fraction (f{sub p})] and DKI parameters [mean diffusivity (MD), mean of diffusional kurtosis (MK)] were calculated for each patient. IVIM parameters were estimated using two methods, namely conventional biexponential fitting (CBFM) and variable projection (VARPRO). After surgery, the pathological TNM and tumor regression grade (TRG) were estimated. For each parameter, percentage changes between before and after SCR were evaluated. Furthermore, an artificial neural network was trained for outcome prediction. Nonparametric sample tests and receiver operating characteristic curve (ROC) analysis were performed. Results: Fifteen patients were classified as responders (TRG ≤ 2) and 19 as not responders (TRG > 3). Seven patients had TRG 1 (pathological complete response, pCR). Mean and standard deviation values of pre-treatment CBFM D{sub p} and mean value of VARPRO D{sub p} pre-treatment showed statistically significant differences to predict pCR. (p value at Mann–Whitney test was 0.05, 0.03 and 0.008, respectively.) Exclusively SIS percentage change showed significant differences between responder and non-responder patients after SCR (p value << 0.001) and to assess pCR after SCR (p value << 0.001). The best results to predict pCR were obtained by VARPRO Fp mean value pre-treatment with area under ROC of 0.84, a sensitivity of 96.4%, a specificity of 71.4%, a positive predictive value (PPV) of 92.9%, a negative predictive value (NPV) of 83.3% and an accuracy of 91.2%. The best results to assess after treatment complete pathological response were obtained by SIS with an area under ROC of 0.89, a sensitivity of 85.7%, a specificity of 92.6%, a PPV of 75.0%, a NPV of 96.1% and an accuracy of 91.2%. Moreover, the best results to differentiate after treatment responders vs. non-responders were obtained by SIS with an area under ROC of 0.94, a sensitivity of 93.3%, a specificity of 84.2%, a PPV of 82.4%, a NPV of 94.1% and an accuracy of 88.2%. Promising initial results were obtained using a decision tree tested with all ADC, IVIM and DKI extracted parameter: we reached high accuracy to assess pathological complete response after SCR in LARC (an accuracy of 85.3% to assess pathological complete response after SCR using VARPRO D{sub p} mean value post-treatment, ADC standard deviation value pre-treatment, MD standard deviation value post-treatment). Conclusion: SIS is a hopeful DCE-MRI angiogenic biomarker to assess preoperative treatment response after SCR with delayed surgery. Furthermore, an important prognostic role was obtained by VARPRO F{sub p} mean value pre-treatment and by a decision tree composed by diffusion parameters derived by DWI and DKI to assess pathological complete response.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Recurrence of Lower Urinary Tract Symptoms Following Prostate Artery Embolization for Benign Hyperplasia: Single Center Experience Comparing Two Techniques

PurposeTo compare recurrence of lower urinary tract symptoms (LUTS) recurrence at 12 months following original prostate artery embolization (oPAE) or “proximal embolization first, then embolize distal” (PErFecTED) PAE for benign prostatic hyperplasia (BPH).Materials and Methods105 consecutive patients older than 45 years, with prostate size greater than 30 cm{sup 3}, International Prostate Symptom Score (IPSS) ≥ 8, quality of life (QoL) index ≥ 3, and refractory status or intolerance of medical management were prospectively enrolled between June 2008 and August 2013. The study was IRB-approved, and all patients provided informed consent. Patients underwent oPAE or PErFecTED PAE and were followed for at least 12 months. Technical success was defined as bilateral embolization and clinical success (non-recurrence) was defined as removal of the Foley catheter in patients with urinary retention, IPSS < 8 and QoL index < 3 at 12 months of follow-up. Nonparametric statistics were used to compare the study groups due to the size of the study population and distributions of clinical data.Results97 patients had 12-month data and were categorized as oPAE without recurrence (n = 46), oPAE with recurrence (n = 13), PErFecTED without recurrence (n = 36), or PErFecTED with recurrence (n = 2). Recurrence was significantly more common in oPAE patients (χ{sup 2}, p = 0.026). Unilateral embolization was significantly associated with recurrence among patients who underwent oPAE (χ{sup 2}, p = 0.032).ConclusionsBoth oPAE and PErFecTED PAE are safe and effective methods for treatment of LUTS, but PErFecTED PAE is associated with a significantly lower rate of symptom recurrence.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Dietary B group vitamin intake and the bladder cancer risk: a pooled analysis of prospective cohort studies

Abstract Purpose Diet may play an essential role in the aetiology of bladder cancer (BC). The B group complex vitamins involve diverse biological functions that could be influential in cancer prevention. The aim of the present study was to investigate the association between various components of the B group vitamin complex and BC risk. Methods Dietary data were pooled from four cohort studies. Food item intake was converted to daily intakes of B group vitamins and pooled multivariate hazard ratios (HRs), with corresponding 95% confidence intervals (CIs), were obtained using Cox-regression models. Dose–response relationships were examined using a nonparametric test for trend. Results In total, 2915 BC cases and 530,012 non-cases were included in the analyses. The present study showed an increased BC risk for moderate intake of vitamin B1 (HR B1 : 1.13, 95% CI: 1.00–1.20). In men, moderate intake of the vitamins B1, B2, energy-related vitamins and high intake of vitamin B1 were associated with an increased BC risk (HR (95% CI): 1.13 (1.02–1.26), 1.14 (1.02–1.26), 1.13 (1.02–1.26; 1.13 (1.02–1.26), respectively). In women, high intake of all vitamins and vitamin combinations, except for the entire complex, showed an inverse association (HR (95% CI): 0.80 (0.67–0.97), 0.83 (0.70–1.00); 0.77 (0.63–0.93), 0.73 (0.61–0.88), 0.82 (0.68–0.99), 0.79 (0.66–0.95), 0.80 (0.66–0.96), 0.74 (0.62–0.89), 0.76 (0.63–0.92), respectively). Dose–response analyses showed an increased BC risk for higher intake of vitamin B1 and B12. Conclusion Our findings highlight the importance of future research on the food sources of B group vitamins in the context of the overall and sex-stratified diet.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Properties of the Fundamental Optical Functions of Magnesium Silicide

The spectra of 16 optical Mg{sub 2}Si functions in the range from 0 to 11 eV at 77 K are determined. They contain five maxima and shoulders due to interband transitions and metastable excitons, as well as the maxima of bulk and surface plasmons at ~9.56 and ~7.30 eV. Their peculiarities and general patterns of behavior are established. Calculations were performed based on a well-known experimental reflection spectrum in the range from 0 to 11 eV at 77 K. The integral spectra of the imaginary parts of the permittivity ε{sub 2}(E), characteristic bulk (–Im ε{sup –1}), and surface (–Im (1 + ε){sup –1}) energy losses of electrons are expanded into elementary components in the region from 2 to 5 eV. The main parameters of the transition components were determined, including the energies of their maxima and oscillator strengths. Calculations were carried out using computer programs based on the Kramers–Kronig relations and known analytical formulas for the correlation between optical functions, as well as an improved nonparametric method of combined Argand diagrams taking into account the effective number of valence electrons participating in the formation of individual bands. Instead of five maxima and shoulders of the integral spectra, 17 elementary bands with oscillator strengths in the range from 0.0003 to 1.92 were established. They are due to transverse and longitudinal type excitonic and interband transitions. Based on known theoretical calculations, we propose herein the localization and assumed nature of the optical transition bands.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Asymptotic Efficiency of New Distribution-Free Tests of Symmetry for Generalized Skew Alternatives

The Bahadur efficiency of new nonparametric tests of symmetry recently proposed by Nikitin and Ahsanullah is calculated. In contrast to this result, where only location alternatives were discussed, in the present paper generalized skew alternatives are of interest. It is shown that the new tests are highly efficient for a large class of skew alternatives. The problem of most favorable alternatives is also studied.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A Comparative Study of the Efficacy of Local/Global and Parametric/Nonparametric Machine Learning Methods for Establishing Structure–Property Linkages in High-Contrast 3D Elastic Composites

Reduced-order structure–property (S-P) linkages play a pivotal role in the tailored design of materials for advanced engineering components. There is a critical need to distill these from the simulation datasets aggregated using sophisticated, computationally expensive, physics-based numerical tools (e.g., finite element methods). The recent emergence of materials data science approaches has opened new avenues for addressing this challenge. In this paper, we critically compare the relative merits of the application of four distinct machine learning approaches for their efficacy in extracting microstructure-property linkages from the finite element simulation data aggregated on high-contrast elastic composites with different microstructures. The machine learning approaches selected for the study have included different combinations of local/global and parametric/nonparametric approaches. Furthermore, the nonparametric approaches selected for this study are based on Gaussian Process (GP) models that allow for a formal treatment of uncertainty quantification in the predicted values. The predictive performances of these different approaches have been compared against each other using rigorous cross-validation error metrics. Furthermore, their sensitivity to both the dataset size and dimensionality has been investigated.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Using ultrasonic attenuation in cortical bone to infer distributions on pore size

Here, in this work we infer the underlying distribution on pore radius in human cortical bone samples using ultrasonic attenuation data. We first discuss how to formulate polydisperse attenuation models using a probabilistic approach and the Waterman Truell model for scattering attenuation. We then compare the Independent Scattering Approximation and the higher-order Waterman Truell models’ forward predictions for total attenuation in polydisperse samples. Following this, we formulate an inverse problem under the Prohorov Metric Framework coupled with variational regularization to stabilize this inverse problem. We then use experimental attenuation data taken from human cadaver samples and solve inverse problems resulting in nonparametric estimates of the probability density function on pore radius. We compare these estimates to the “true” microstructure of the bone samples determined via microCT imaging. We find that our methodology allows us to reliably estimate the underlying microstructure of the bone from attenuation data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Stochastic nonlinear analysis of unidirectional fiber composites using image-based microstructural uncertainty quantification

Here, we present a data-driven nonlinear uncertainty quantification and propagation framework to study the microstructure-induced stochastic performance of unidirectional (UD) carbon fiber reinforced polymer (CFRP) composites. The proposed approach integrates (1) microscopic image characterization, (2) stochastic microstructure reconstruction, and (3) efficient multiscale finite element simulations enabled by self-consistent clustering (SCA) analysis. To model the complex microstructural variability, the proposed UQ methods take the non-Gaussian uncertainty sources into account through a distribution-free sampling approach leveraging nonparametric and asymptotic statistical tools. A hierarchical conditional sampling strategy enables the simultaneous sampling of multiple sources of uncertainties. Our approach provides insights into the impact of microstructural variabilities, which are shown to have an increasing impact on the nonlinear responses of UD CFRP parts under progressive compression loading and ultimately on the failure rate over time. We discover that before CFRP parts start to fail, a characteristic time period emerges with distinctive uncertainty distributions specific to the microstructure variability and the probability of failure. Identifying the failure time period is crucial to the reliability prediction, which is an essential component of CFRP design.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Dynamic analysis environment for nuclear forensic analyses

We report a Dynamic Analysis Environment (DAE) software package is introduced to facilitate group inclusion/exclusion method testing, evaluation and comparison for pre-detonation nuclear forensics applications. Employing DAE, the multivariate signatures of a questioned material can be compared to the signatures for different, known groups, enabling the linking of the questioned material to its potential process, location, or fabrication facility. Advantages of using DAE for group inclusion/exclusion include built-in query tools for retrieving data of interest from a database, the recording and documentation of all analysis steps, a clear visualization of the analysis steps intelligible to a non-expert, and the ability to integrate analysis tools developed in different programming languages. Two group inclusion/exclusion methods are implemented in DAE: principal component analysis, a parametric feature extraction method, and k nearest neighbors, a nonparametric pattern recognition method. Spent Fuel Isotopic Composition (SFCOMPO), an open source international database of isotopic compositions for spent nuclear fuels (SNF) from 14 reactors, is used to construct PCA and KNN models for known reactor groups, and 20 simulated SNF samples are utilized in evaluating the performance of these group inclusion/exclusion models. For all 20 simulated samples, PCA in conjunction with the Q statistic correctly excludes a large percentage of reactor groups and correctly includes the true reactor of origination. As a result, employing KNN, 14 of the 20 simulated samples are classified to their true reactor of origination.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

When physics-informed data analytics outperforms black-box machine learning: A case study in thickness control for additive manufacturing

Aerosol jet printing (AJP) has emerged as a promising noncontact additive manufacturing method for high-resolution printing for a wide range of material systems. A key challenge limiting the broader adoption of AJP in the material science community is the lack of methods to precisely control thickness. Herein, we develop a model-based design of experiment (MBDoE) framework that integrates physics-informed models, nonlinear regression, and information criteria to postulate, select and calibrate the best model to describe and optimize the AJP manufacturing process. Starting with already available data from system commissioning (e.g., prior single variable sensitivity analysis), four candidate physics-informed models are postulated and trained. MBDoE identifies a single additional optimal experiment to validate these predictive models with quantified uncertainties, which are then used to determine the best experimental conditions to control printed film thickness. As a comparative benchmark, the analysis is repeated using the same dataset with nonparametric Gaussian process regression (GPR) model that does not incorporate physical information. Using MBDoE principles, we find that only five experiments are necessary to calibrate the nonlinear physics-informed parametric model, and with said limited data, this model outperforms the black-box machine learning GPR model. This key result underscores an emerging trend in the data science community: incorporating physical information into predictive models often drastically reduces the data requirements. Leveraging MBDoE further increased the data efficiency. By design, the proposed data science framework is general in nature and can be easily extended to other experimental and additive manufacturing systems beyond AJP.

Aerosol jet printing↗
DOE OSTI2018

Socioeconomic and particulate air pollution correlates of heart disease risk

Highlights: • Heart disease risk varies with age, sex, smoking, income, education, and particulate (PM2.5) air pollution. • How these risk factors interact is unclear. • We examine correlates of self-reported heart disease risk in a large data set. • Income is negatively associated with both PM2.5 exposure and heart disease risk. • Income is an important confounder of air pollution-heart disease associations. • Nonparametric methods can quantify associations and suggest causal interpretations. How does risk of heart disease depend on age, sex, smoking, income, education, marital status, and outdoor concentrations of fine particulate matter (PM2.5)? We join data available from the Centers for Disease Control and Prevention (CDC) Behavioral Risk Factor Surveillance (BRFSS) System for years 2008–2012 to US Environmental Protection Agency (EPA) data on county-specific concentrations of fine particulate matter (PM2.5) to quantify associations among these variables and to explore possible causal interpretations. Low income is identified as a direct cause of increased heart disease risk in this data set. The effect depends on age and sex: it is most pronounced for men under age 70 and for women under age 80. Income is significantly associated with all of the other variables examined and confounds the association between PM2.5 and heart disease risk. This association is significant in regression models that exclude income, but not in regression models that include it, both in the data set as a whole and in the subset of observations with PM2.5 < 15 μg/m{sup 3}. Causal directed acyclic graph (DAG) models and non-parametric model ensemble partial dependence plots confirm that higher incomes reduce heart disease risk, consistent with previous observations of socioeconomic gradients in health risks. They support interpretation of this as a robust causal relation apparent in non-parametric analyses, and hence independent of any specific parametric modeling assumptions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A reforecasting-based dynamic reserve estimation for variable renewable generation and demand uncertainty

The installed capacity of renewables-based energy sources has been increasing in traditional power systems. In order to accommodate the increased variability and uncertainty associated with the deeper penetration of renewable sources like solar and wind, adjusted amounts of dynamic reserve are needed. Although probabilistic dynamic reserve estimation methods have been previously developed, most of them consider the uncertainty to be represented by parametric density functions that tend to perform poorly under extreme events and, moreover, neglect uncertainty introduced by the forecasting model itself. Toward addressing these limitations, this work presents, for the first time, a dynamic reserve estimation method for flexibility that incorporates nonparametric density estimation and a machine learning based reforecasting to provide a day-ahead prediction of the mean and spread of uncertainty around the base forecast. The prediction is, in turn, used to estimate the up and down reserve relative to the base forecast. Here, the present method takes various endogenous and exogenous features, including the calendar variables, as input to estimate the day-ahead reserve. Using a combination of reforecasting and dynamic reserve estimation techniques, the method is shown to adjust better to the dynamic nature of reserve requirements providing only what is needed to accommodate the expected deviations. Considering California Independent System Operator (CAISO) solar, wind and load data over an 18 month period, up to 67% reduction in the amount of reserve capacity needed for a one day reserve and reserve penalty for solar uncertainty is demonstrated. Additionally, the risk of reserve insufficiency in meeting the net demand is reduced by 20% with the proposed method.

14 SOLAR ENERGY↗
DOE OSTI2023

Profiling overstory survival trends following varying thinning and burning disturbance regimes in a mixed pine-hardwood forest in the US South

Prescribed burning as a silvicultural tool may be effective for achieving various management objectives, yet some practitioners have concerns about inadvertently increasing overstory tree mortality. Using extensive data from a long-term, ongoing study in northcentral Alabama, USA, that systematically applies a variety of thinning and prescribed burning disturbances on mixed pine-hardwood stands, we assess survival trends for different groups of trees. The primary research question is whether more frequent prescribed burns adversely affects overstory survival versus infrequent or no burns; secondary questions explore whether overstory survival trends differ based on thinning level, species group, or size class. Interest is in broad groups of trees, not individual tree survival or mortality; consequently, survival analysis methods are used, including nonparametric Kaplan-Meier (KM) techniques for examining single grouping factors, and parametric accelerated failure time models for analyzing simultaneous effects of multiple covariates. Leveraging relatively recent methodological advances, the statistical techniques are adjusted for interval censored data. KM survival curves showed that more frequent prescribed fires did not result in differing survival trends. Also, trees in unthinned stands had the lowest 14-year survival compared to thinned stands, oaks had the highest survival compared to pines and the others species group, and the smallest size class of overstory trees had the lowest survival. In conclusion, these results support managing transitional mixed pine-hardwoods using thinning and multiple prescribed fires to restore specific species composition and structure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

A Phase II Comparative Study of Gross Tumor Volume Definition With or Without PET/CT Fusion in Dosimetric Planning for Non-Small-Cell Lung Cancer (NSCLC): Primary Analysis of Radiation Therapy Oncology Group (RTOG) 0515

Background: Radiation Therapy Oncology Group (RTOG) 0515 is a Phase II prospective trial designed to quantify the impact of positron emission tomography (PET)/computed tomography (CT) compared with CT alone on radiation treatment plans (RTPs) and to determine the rate of elective nodal failure for PET/CT-derived volumes. Methods: Each enrolled patient underwent definitive radiation therapy for non-small-cell lung cancer ({>=}60 Gy) and had two RTP datasets generated: gross tumor volume (GTV) derived with CT alone and with PET/CT. Patients received treatment using the PET/CT-derived plan. The primary end point, the impact of PET/CT fusion on treatment plans was measured by differences of the following variables for each patient: GTV, number of involved nodes, nodal station, mean lung dose (MLD), volume of lung exceeding 20 Gy (V20), and mean esophageal dose (MED). Regional failure rate was a secondary end point. The nonparametric Wilcoxon matched-pairs signed-ranks test was used with Bonferroni adjustment for an overall significance level of 0.05. Results: RTOG 0515 accrued 52 patients, 47 of whom are evaluable. The follow-up time for all patients is 12.9 months (2.7-22.2). Tumor staging was as follows: II = 6%; IIIA = 40%; and IIIB = 54%. The GTV was statistically significantly smaller for PET/CT-derived volumes (98.7 vs. 86.2 mL; p < 0.0001). MLDs for PET/CT plans were slightly lower (19 vs. 17.8 Gy; p = 0.06). There was no significant difference in the number of involved nodes (2.1 vs. 2.4), V20 (32% vs. 30.8%), or MED (28.7 vs. 27.1 Gy). Nodal contours were altered by PET/CT for 51% of patients. One patient (2%) has developed an elective nodal failure. Conclusions: PET/CT-derived tumor volumes were smaller than those derived by CT alone. PET/CT changed nodal GTV contours in 51% of patients. The elective nodal failure rate for GTVs derived by PET/CT is quite low, supporting the RTOG standard of limiting the target volume to the primary tumor and involved nodes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Tumor Metabolism and Perfusion in Head and Neck Squamous Cell Carcinoma: Pretreatment Multimodality Imaging With {sup 1}H Magnetic Resonance Spectroscopy, Dynamic Contrast-Enhanced MRI, and [{sup 18}F]FDG-PET

Purpose: To correlate proton magnetic resonance spectroscopy ({sup 1}H-MRS), dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), and {sup 18}F-labeled fluorodeoxyglucose positron emission tomography ([{sup 18}F]FDG PET) of nodal metastases in patients with head and neck squamous cell carcinoma (HNSCC) for assessment of tumor biology. Additionally, pretreatment multimodality imaging was evaluated for its efficacy in predicting short-term response to treatment. Methods and Materials: Metastatic neck nodes were imaged with {sup 1}H-MRS, DCE-MRI, and [{sup 18}F]FDG PET in 16 patients with newly diagnosed HNSCC, before treatment. Short-term patient radiological response was evaluated at 3 to 4 months. Correlations among {sup 1}H-MRS (choline concentration relative to water [Cho/W]), DCE-MRI (volume transfer constant [K{sup trans}]; volume fraction of the extravascular extracellular space [v{sub e}]; and redistribution rate constant [k{sub ep}]), and [{sup 18}F]FDG PET (standard uptake value [SUV] and total lesion glycolysis [TLG]) were calculated using nonparametric Spearman rank correlation. To predict short-term responses, logistic regression analysis was performed. Results: A significant positive correlation was found between Cho/W and TLG ({rho} = 0.599; p = 0.031). Cho/W correlated negatively with heterogeneity measures of standard deviation std(v{sub e}) ({rho} = -0.691; p = 0.004) and std(k{sub ep}) ({rho} = -0.704; p = 0.003). Maximum SUV (SUVmax) values correlated strongly with MRI tumor volume ({rho} = 0.643; p = 0.007). Logistic regression indicated that std(K{sup trans}) and SUVmean were significant predictors of short-term response (p < 0.07). Conclusion: Pretreatment multimodality imaging using {sup 1}H-MRS, DCE-MRI, and [{sup 18}F]FDG PET is feasible in HNSCC patients with nodal metastases. Additionally, combined DCE-MRI and [{sup 18}F]FDG PET parameters were predictive of short-term response to treatment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Quality of Life After Palliative Radiation Therapy for Patients With Painful Bone Metastases: Results of an International Study Validating the EORTC QLQ-BM22

Purpose: Radiation therapy (RT) is an effective method of palliating painful bone metastases and can improve function and reduce analgesic requirements. In advanced cancer patients, quality of life (QOL) is the primary outcome of interest over traditional endpoints such as survival. The purpose of our study was to compare bone metastasis-specific QOL scores among patients who responded differently to palliative RT. Methods and Materials: Patients receiving RT for bone metastases across 6 countries were prospectively enrolled from March 2010-January 2011 in a trial validating the QLQ-BM22 and completed the QLQ-BM22 and the core measure (QLQ-C30) at baseline and after 1 month. Pain scores and analgesic intake were recorded, and response to RT was determined according to the latest published guidelines. The Kruskal-Wallis nonparametric and Wilcoxon rank sum tests compared changes in QOL among response groups. A Bonferroni-adjusted P<.003 indicated statistical significance. Results: Of 79 patients who received palliative RT, 59 were assessable. Partial response, pain progression, and indeterminate response were observed in 22, 8, and 29 patients, respectively; there were no patients with a complete response. Patients across all groups had similar baseline QOL scores apart from physical functioning (patients who progressed had better initial functioning). One month after RT, patients who responded had significant improvements in 3 of 4 QLQ-BM22 domains (painful site, P<.0001; painful characteristic, P<.0001; and functional interference, P<.0001) and 3 QLQ-C30 domains (physical functioning, P=.0006; role functioning, P=.0026; and pain, P<.0001). Patients with progression in pain had significantly worse functional interference (P=.0007) and pain (P=.0019). Conclusions: Patients who report pain relief after palliative RT also have better QOL with respect to bone metastasis-specific issues. The QLQ-BM22 and QLQ-C30 are able to discriminate among patients with varying responses and are recommended for use in future bone metastasis clinical trials.

62 RADIOLOGY AND NUCLEAR MEDICINE↗