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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Advanced Power Electronics Designs - Reliability and Prognostics (Keystone Project 1)

The primary deliverable for this project will be to construct a power electronics package utilizing an organic electrically insulating substrate material with a direct chip-to-chip interconnect technology and demonstrate superior thermal performance and greater reliability under thermal cycling, thermal aging, vibration, power cycling, and electrical high-potential evaluation over traditional packages.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Advanced Power Electronics Designs - Reliability and Prognostics (Keystone Project 1)

The primary deliverable for this project will be to construct a power electronics package utilizing an organic electrically insulating substrate material with a direct chip-to-chip interconnect technology and demonstrate superior thermal performance and greater reliability under thermal cycling, thermal aging, vibration, power cycling, and electrical high-potential evaluation over traditional packages.

ADVANCED PROPULSION SYSTEMS,ENGINEERING↗
DOE OSTI2024

Errant Beam Prognostics with Machine Leaning at SNS Accelerator

Particle Accelerators are complex machine with many pieces of equipment running in synchronization to deliver required beam. However, faults in particle accelerators reduce the availability of the beam for experiments affecting the overall science output. To avoid these faults, we apply anomaly detection techniques to predict any unusual behavior and perform preemptive actions to improve the total availability. Many researchers have adopted semi-supervised Machine Learning (ML) methods such as auto-encoders and variational auto-encoders for such tasks. However, supervised ML techniques designed for similarity learning such as Siamese Neural Network (SNN) can outperform semi-supervised or unsupervised methods for anomaly prediction. One of the challenges associated with application of ML models to particle accelerators is the variability in observed data over time due to system configuration changes. We employ conditional models such as Conditional Siamese Neural Networks (CSNN), and Conditional-VAE (CVAE) to learn the variability in the data by using beam configuration parameters as conditional input. We apply these models for errant beam prediction at Spallation Neutron Source accelerator under different system configurations and compare their performance. We demonstrate that CSNN outperforms CVAE in our application. This talk will present the data source, collection, analysis, data-preparation, model development, hyper-parameter studies and the results.

Rajput, Kishansingh↗
DOE OSTI2024

Power Module Precursors and Prognostics

The ongoing work involves 1) the identification and evaluation of various electric signals as indicators to module failure and precursors to aging, and 2) the development of corresponding detection techniques. In the current phase, 1) the increase of on-state resistance is selected as the precursor to the power cycle aging of silicon carbide power MOSFET modules based on review and rest data. 2) A detection method leveraging the gate voltage fluctuations magnitude during commutation transients to inform the on-state resistance increase is investigated which has the benefit of being able to be integrated into the gate driver. A dedicated detection circuit for implementation is designed and simulated and is currently in fabrication.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Power Module Precursors and Prognostics

This project focuses on finding and utilizing electrical properties (precursors) of power electronic devices and modules whose changes have strong correlations with different modes and levels of degradations in order to realize online and lightweight state of health evaluation and fault diagnosis. Results from this project will contribute to higher safety, reliability, and power density of power electronic components. The approaches mainly include reviewing academic literature and industry practices for state of the art precursor identification and extraction, accelerated life cycles (ALC) of various power modules to create different degradations in-house, and developing techniques for gate-driver-integratable precursor detection circuit. In FY24, the results includes two sets of definitively detected aging precursors (on-state resistance and gate threshold voltage) for two sets of power modules respectively, controlled accelerated lifetime cycling of multiple silicon carbide (SiC) metal-oxide-semiconductor field-effect transistor (MOSFET) modules, and the development and validation of a gate voltage detection system.

ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2005

Diagnosis and Prognosis of Weapon Systems

The Prognostics Framework is a set of software tools with an open architecture that affords a capability to integrate various prognostic software mechanisms and to provide information for operational and battlefield decision-making and logistical planning pertaining to weapon systems. The Prognostics NASA Tech Briefs, February 2005 17 Framework is also a system-level health -management software system that (1) receives data from performance- monitoring and built-in-test sensors and from other prognostic software and (2) processes the received data to derive a diagnosis and a prognosis for a weapon system. This software relates the diagnostic and prognostic information to the overall health of the system, to the ability of the system to perform specific missions, and to needed maintenance actions and maintenance resources. In the development of the Prognostics Framework, effort was focused primarily on extending previously developed model-based diagnostic-reasoning software to add prognostic reasoning capabilities, including capabilities to perform statistical analyses and to utilize information pertaining to deterioration of parts, failure modes, time sensitivity of measured values, mission criticality, historical data, and trends in measurement data. As thus extended, the software offers an overall health-monitoring capability.

Nolan, Mary↗
DOE OSTI2012

An Assessment of Integrated Health Management (IHM) Frameworks

In order to meet the ever increasing demand for energy, the United States nuclear industry is turning to life extension of existing nuclear power plants (NPPs). Economically ensuring the safe, secure, and reliable operation of aging nuclear power plants presents many challenges. The 2009 Light Water Reactor Sustainability Workshop identified online monitoring of active and structural components as essential to the better understanding and management of the challenges posed by aging nuclear power plants. Additionally, there is increasing adoption of condition-based maintenance (CBM) for active components in NPPs. These techniques provide a foundation upon which a variety of advanced online surveillance, diagnostic, and prognostic techniques can be deployed to continuously monitor and assess the health of NPP systems and components. The next step in the development of advanced online monitoring is to move beyond CBM to estimating the remaining useful life of active components using prognostic tools. Deployment of prognostic health management (PHM) on the scale of a NPP requires the use of an integrated health management (IHM) framework - a software product (or suite of products) used to manage the necessary elements needed for a complete implementation of online monitoring and prognostics. This paper provides a thoughtful look at the desirable functions and features of IHM architectures. A full PHM system involves several modules, including data acquisition, system modeling, fault detection, fault diagnostics, system prognostics, and advisory generation (operations and maintenance planning). The standards applicable to PHM applications are indentified and summarized. A list of evaluation criteria for PHM software products, developed to ensure scalability of the toolset to an environment with the complexity of a NPP, is presented. Fourteen commercially available PHM software products are identified and classified into four groups: research tools, PHM system development tools, deployable architectures, and peripheral tools.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Image analysis reveals differences in tumor multinucleations in Black and White patients with human papillomavirus‐associated oropharyngeal squamous cell carcinoma

Background Understanding biological differences between different racial groups of human papillomavirus (HPV)‐associated oropharyngeal squamous cell carcinoma (OPSCC) patients, who have differences in terms of incidence, survival, and tumor morphology, can facilitate accurate prognostic biomarkers, which can help develop personalized treatment strategies. Methods This study evaluated whether there were morphologic differences between HPV‐associated tumors from Black and White patients in terms of multinucleation index (MuNI), an image analysis‐derived metric that measures density of multinucleated tumor cells within epithelial regions on hematoxylin–eosin images and previously has been prognostic in HPV‐associated OPSCC patients. In this study, the authors specifically evaluated whether the same MuNI cutoff that was prognostic of overall survival (OS) and disease‐free survival in their previous study, T TR , is valid for Black and White patients, separately. We also evaluated population‐specific cutoffs, T B for Blacks and T W for Whites, for risk stratification. Results MuNI was statistically significantly different between Black (mean, 3.88e–4; median, 3.67e–04) and White patients (mean, 3.36e–04; median, 2.99e–04), with p = .0078. Using T TR , MuNI was prognostic of OS in the entire population with hazard ratio (HR) of 1.71 ( p = .002; 95% confidence interval [CI], 1.21–2.43) and in White patients with HR of 1.72 ( p = .005; 95% CI, 1.18–2.51). Population‐specific cutoff, T W , yielded improved HR of 1.77 ( p = .003; 95% CI, 1.21–2.58) for White patients, whereas T B did not improve risk‐stratification in Black patients with HR of 0.6 ( p = .3; HR, 0.6; 95% CI, 0.2–1.80). Conclusions Histological difference between White and Black patient tumors in terms of multinucleated tumor cells suggests the need for considering population‐specific prognostic biomarkers for personalized risk stratification strategies for HPV‐associated OPSCC patients.

Koyuncu, Can F.↗
DOE OSTI2018

Three differential expression profiles of miRNAs as potential biomarkers for lung adenocarcinoma

Highlights: • To identify the differential miRNAs expression between lung cancer and normal tissues. • Data analysis was based on a computational approach to detect survival-associated signatures. • Three-miRNA signature could be used as a prognostic marker in LACA. Owing to the poor prognosis, novel biomarkers for lung adenocarcinoma (LACA) are needed nowadays. The aim of the study was to identify the differential miRNAs expression between lung cancer and normal tissues and evaluate the prognostic values of the miRNAs. Multidimensional data of 528 samples were retrieved from The Cancer Genome Atlas archive. Data analysis was based on a computational approach to detect survival-associated molecular signatures. A total of 191 differentially expressed miRNAs were identified between LACA tissues and normal tissues, including 88 up-regulated and 103 down-regulated miRNAs. The Kaplan-Meier survival method revealed the prognostic function of the three miRNAs (miR-1293, miR-873 and miR-1914). Cox regression analysis showed that the three-miRNA signature was an independent prognostic factor in LACA. The functional enrichment analysis suggested that the target genes of three miRNAs may be involved in various pathways related to the cancer. This study demonstrated that the three-miRNA signature (miR-1293, miR-873 and miR-1914) could be used as a prognostic marker in LACA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-R-52: A Comparison of the Performance of Radiomic Features From Free Breathing and 4DCT Scans in Predicting Disease Recurrence in Lung Cancer SBRT Patients

Purpose: There is a clinical need to identify patients who are at highest risk of recurrence after being treated with stereotactic body radiation therapy (SBRT). Radiomics offers a non-invasive approach by extracting quantitative features from medical images based on tumor phenotype that is predictive of an outcome. Lung cancer patients treated with SBRT routinely undergo free breathing (FB image) and 4DCT (average intensity projection (AIP) image) scans for treatment planning to account for organ motion. The aim of the current study is to evaluate and compare the prognostic performance of radiomic features extracted from FB and AIP images in lung cancer patients treated with SBRT to identify which image type would generate an optimal predictive model for recurrence. Methods: FB and AIP images of 113 Stage I-II NSCLC patients treated with SBRT were analysed. The prognostic performance of radiomic features for distant metastasis (DM) was evaluated by their concordance index (CI). Radiomic features were compared with conventional imaging metrics (e.g. diameter). All p-values were corrected for multiple testing using the false discovery rate. Results: All patients received SBRT and 20.4% of patients developed DM. From each image type (FB or AIP), nineteen radiomic features were selected based on stability and variance. Both image types had five common and fourteen different radiomic features. One FB (CI=0.70) and five AIP (CI range=0.65–0.68) radiomic features were significantly prognostic for DM (p<0.05). None of the conventional features derived from FB images (range CI=0.60–0.61) were significant but all AIP conventional features were (range CI=0.64–0.66). Conclusion: Features extracted from different types of CT scans have varying prognostic performances. AIP images contain more prognostic radiomic features for DM than FB images. These methods can provide personalized medicine approaches at low cost, as FB and AIP data are readily available within a large number of radiation oncology departments. R.M. had consulting interest with Amgen (ended in 2015).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Immunohistochemical analysis of cyclin A expression in Wilms tumor

Background: Cyclin A overexpression is found in a variety of human tumors and correlates with unfavorable outcome. We analyzed immunohistochemical expression of cyclin A in Wilms tumor (WT) in relation to clinicopathological characteristics, preoperative chemotherapy (PrOpChTh), and overall survival (OS). Methods: This retrospective study involved 43 patients who underwent nephrectomy from January 1996 to October 2010. Tumor stage and histological subtype were determined by revised Societé International d’Oncologie Pediatrique protocol, based on histological components/alterations caused by PrOpChTh, within the prognostic group of low, intermediate and high risk, and with criteria for anaplasia. The regressive/necrotic changes in total tumor mass of primary tumor and the proportion of epithelial, blastemal, and stromal components in the remaining viable tumor tissue were also determined. Cyclin A expression was evaluated by immunohistochemistry using a polyclonal rabbit, antihuman antibody (H-432). Results: Cyclin A overexpression was found in 34.3% of WTs, with higher frequency in tumors with epithelial (31.3%) and blastemal (37.1%) components than those with stromal component (17.7%). Regarding histological type, cyclin A overexpression was found most often in focal anaplasia (100%), stromal (60%), and diffuse anaplastic (66.7) WTs. The overexpression was also more frequent in stages 3 and 4 (77.8% and 66.7%, respectively) compared to tumors in stages 1 and 2 (13.3% and 12.5%, respectively; p = 0.004) in all components, as well as in blastemal component in stages 3 and 4 (77.8% and 66.7%, respectively) vs. stages 1 and 2 (13.3% and 25%, respectively, p = 0.009). Cyclin A overexpression in all components was 66.7% in WTs with metastasis and 31.3% in WTs without metastasis (p = 0.265, Fisher test). Log-rank testing revealed differences of OS regarding stage (p = 0.000), prognostic groups (p = 0.001), and cyclin A expression in blastemal component (p = 0.025). After univariate analysis, tumor stage (p = 0.001), prognostic group (p = 0.004), and cyclin A expression in blastemal component (p = 0.042) were significant prognostic factors for OS; however, after multivariate analysis, none of these factors were confirmed as independent predictors of survival. Discussion: This study showed that cyclin A overexpression might be associated with the development and progression of WT with anaplasia. Also, cyclin A overexpression was more often observed in advanced stages (3 and 4) of WT, in the group of high-risk WTs, and in focal and diffuse anaplasia WTs. There was no relation of cyclin A overexpression and metastatic ability of WT. Although this study has not confirmed the prognostic value of cyclin A overexpression, its association with unfavorable prognosis should be further evaluated. Copyright 2019 Radojevic-Škodric et al.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Inferred Sea Level Prediction in the NASA GMAO Seasonal Forecasting System

Reliable predictions of sea level anomalies on seasonal timescales with lead times of 1 to 9 months may have relevance to stakeholders – for example, in the advance deployment of resources for coastal flood mitigation. Routine prediction and analysis may also highlight physical processes associated with sea level change and modeling capabilities on seasonal and other timescales. These forecasts may represent interannual changes in the seasonal slope of the ocean surface, teleconnection effects such as the El Niño/Southern Oscillation phenomenon, and variations in seasonal hydrology including precipitation and coastal runoff. Coupled atmosphere/ocean models are routinely used in the seasonal prediction of temperature anomalies, precipitation anomalies, sea ice cover, and climate indices such as the Niño3.4 predictions under the North American Multi-Model Ensemble (NMME) protocol. Within the limits of their configuration, these complex Earth-system models have a potential for depicting regional changes in oceanic column properties, including the sea surface height. Seasonal prediction models generally have no representation of long-term mass contributions from melting land ice, or changes in vertical land motion; their output may be more specifically characterized as predictions of the ocean dynamic sea level. In practice however, the sea surface height prognostic variable is substantially compromised by the forecast model response to initial conditions. Imbalances between the initial, observed hydrologic cycle and the forecast model state produce abrupt adjustments in the model sea surface height. As a result, most seasonal prediction systems employ a constraint on the globally-averaged sea surface height that is applied at each time step. This essentially renders the prognostic sea surface height variable as unserviceable. Several approaches have previously been used to retrieve sea level information from seasonal forecasts beyond the use of the sea surface height variable. Here, we extend a method of relating other prognostic values, including ocean circulation and climate indices, to observed sea level variations. We use the merged altimetry record of the NASA MEaSUREs Gridded Sea Surface Height Anomalies data set and monthly revised local reference gauge observations from the National Oceanography Centre Permanent Service for Mean Sea Level (PSMSL) to evaluate derived prognostic variables from the NASA Global Modeling and Assimilation Office subseasonal-to-seasonal system version 2.1 (GMAO S2S v2.1). We focus on results for the midlatitudes with particular emphasis on US gauge locations. As shown in previous studies, prognostic ENSO-related indices in boreal winter are well correlated with gauge observations for the US west coast, but also for other locations in the southeastern US. Other forecast climate indices such as the North Atlantic Oscillation have relations to sea level that are limited both seasonally and spatially. As expected, surface atmospheric pressure (e.g., inverse barometer effect) is found to be particularly well correlated with observed sea level. We provide a characterization of forecast skill for seasonal sea level with this method.

Richard I Cullather↗
DOE OSTI2012

An Assessment of Integrated Health Management Frameworks

In order to meet the ever increasing demand for energy, the United States nuclear industry is turning to life extension of existing nuclear power plants (NPPs). Economically ensuring the safe, secure, and reliable operation of aging NPPs presents many challenges. The 2009 Light Water Reactor Sustainability Workshop identified online monitoring of active and structural components as essential to better understanding and management of the challenges posed by aging NPPs. Additionally, there is increasing adoption of condition-based maintenance (CBM) for active components in NPPs. These techniques provide a foundation upon which a variety of advanced online surveillance, diagnostic, and prognostic techniques can be deployed to continuously monitor and assess the health of NPP systems and components. The next step in the development of advanced online monitoring is to move beyond CBM to estimating the remaining useful life of active components using prognostic tools. Deployment of prognostic health management (PHM) on the scale of an NPP requires the use of an integrated health management (IHM) framework - a software product (or suite of products) used to manage the necessary elements needed for a complete implementation of online monitoring and prognostics. This paper provides a thoughtful look at the desirable functions and features of IHM architectures. A full PHM system involves several modules, including data acquisition, system modeling, fault detection, fault diagnostics, system prognostics, and advisory generation (operations and maintenance planning). The standards applicable to PHM applications are indentified and summarized. A list of evaluation criteria for PHM software products, developed to ensure scalability of the toolset to an environment with the complexity of an NPP, is presented. Fourteen commercially available PHM software products are identified and classified into four groups: research tools, PHM system development tools, deployable architectures, and peripheral tools.

Lybeck, Nancy↗
DOE OSTI2023

Pan-cancer evaluation of clinical value of mitotic network activity index (MNAI) and its predictive value for immunotherapy

Increased mitotic activity is associated with the genesis and aggressiveness of many cancers. To assess the clinical value of mitotic activity as prognostic biomarker, we performed a pan-cancer study on the mitotic network activity index (MNAI) constructed based on 54-gene mitotic apparatus network. Our pan-cancer assessment on TCGA (33 tumor types, 10,061 patients) and validation on other publicly available cohorts (23 tumor types, 9,209 patients) confirmed the significant association of MNAI with overall survival, progression-free survival, and other prognostic endpoints in multiple cancer types, including lower-grade gliomas (LGG), breast invasive carcinoma (BRCA), as well as many others. We also showed significant association between MNAI and genetic instability, which provides a biological explanation of its prognostic impact at pan-cancer landscape. Our association analysis revealed that patients with high MNAI benefitted more from anti-PD-1 and Anti-CTLA-4 treatment. In addition, we demonstrated that multimodal integration of MNAI and the AI-empowered Cellular Morphometric Subtypes (CMS) significantly improved the predictive power of prognosis compared to using MNAI and CMS alone. Our results suggest that MNAI can be used as a potential prognostic biomarker for different tumor types toward different clinical endpoints, and multimodal integration of MNAI and CMS exceeds individual biomarker for precision prognosis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

The Percent of Positive Biopsy Cores Improves Prediction of Prostate Cancer-Specific Death in Patients Treated With Dose-Escalated Radiotherapy

Purpose: To examine the prognostic utility of the percentage of positive cores (PPC) at the time of prostate biopsy for patients treated with dose-escalated external beam radiation therapy. Methods and Materials: We performed a retrospective analysis of patients treated at University of Michigan Medical Center to at least 75 Gy. Patients were stratified according to PPC by quartile, and freedom from biochemical failure (nadir + 2 ng/mL), freedom from metastasis (FFM), cause-specific survival (CSS), and overall survival (OS) were assessed by log-rank test. Receiver operator characteristic (ROC) curve analysis was used to determine the optimal cut point for PPC stratification. Finally, Cox proportional hazards multivariate regression was used to assess the impact of PPC on clinical outcome when adjusting for National Comprehensive Cancer Network (NCCN) risk group and androgen deprivation therapy. Results: PPC information was available for 651 patients. Increasing-risk features including T stage, prostate-specific antigen, Gleason score, and NCCN risk group were all directly correlated with increasing PPC. On log-rank evaluation, all clinical endpoints, except for OS, were associated with PPC by quartile, with worse clinical outcomes as PPC increased, with the greatest impact seen in the highest quartile (>66.7% of cores positive). ROC curve analysis confirmed that a cut point using two-thirds positive cores was most closely associated with CSS (p = 0.002; area under ROC curve, 0.71). On univariate analysis, stratifying patients according to PPC less than or equal to 66.7% vs. PPC greater than 66.7% was prognostic for freedom from biochemical failure (p = 0.0001), FFM (p = 0.0002), and CSS (p = 0.0003) and marginally prognostic for OS (p = 0.055). On multivariate analysis, after adjustment for NCCN risk group and androgen deprivation therapy use, PPC greater than 66.7% increased the risk for biochemical failure (p = 0.0001; hazard ratio [HR], 2.1 [95% confidence interval (CI), 1.4-3.0]) and FFM (p = 0.05; HR, 1.7 [95% CI, 1.1-2.9]) and marginally increased the risk for CSS (p = 0.057; HR, 2.1 [95% CI, 1.0-4.6]). Conclusion: PPC at the time of biopsy adds prognostic value for clinically meaningful endpoints for patients treated with dose-escalated radiation therapy. This was particularly true for NCCN-defined intermediate- and high-risk patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Outcomes of Chemoradiotherapy in Cervical Cancer-The Western Australian Experience

Purpose: A retrospective review of patients with Stage IB1-IVA cervical cancer treated with combined chemoradiotherapy in Western Australia was conducted with the aim of assessing outcomes and patterns of recurrence. Multivariate analysis was performed to identify potential prognostic factors. Methods and Materials: Patients treated with radical chemoradiotherapy for cervical cancer in Western Australia between June 2005 and November 2008 were analyzed. Treatment consisted of external-beam radiotherapy with concurrent weekly cisplatin (40 mg/m{sup 2}), followed by high-dose-rate brachytherapy. The Kaplan-Meier method was used to determine overall survival and disease-free survival, and Cox regression analysis was used to identify potential prognostic factors. Results: Sixty-nine patients were included in the analysis. All patients completed external-beam radiotherapy; however, only 43.5% of patients completed the planned course of brachytherapy. At a median follow-up of 27 months, 24- and 48-month overall survival were 68.8% and 61.1%, respectively. Disease-free survival at 24 and 48 months was 59.4% and 56.7%, respectively. The 2-year local control rate was 70.1%. Nodal involvement resulted in increased risk of disease recurrence (hazard ratio [HR] 6.26, p = 0.002) and death (HR 5.15, p = 0.013). Pretreatment hemoglobin <120 g/L was a negative prognostic factor for disease recurrence (HR 4.20, p = 0.031) and death (HR 8.19, p = 0.020). Completion of brachytherapy improved overall survival (p = 0.039), with a trend to reducing disease recurrence (p = 0.052). The risk of relapse increased with treatment time over 8 weeks (HR 8.18, p = 0.019), however treatment time did not affect the risk of death (p = 0.245). Conclusion: The overall survival outcomes in this group of women with locally advanced cervical carcinomas treated with chemoradiotherapy are comparable to worldwide data. Despite the use of modern treatment protocols, a significant proportion of women developed locoregional recurrences and distant failures. Many poor prognostic factors have been identified as contributors to this, including pelvic nodal involvement, incomplete brachytherapy, pretreatment hemoglobin <120 g/L, and treatment time over 8 weeks.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Baseline Serum Lactate Dehydrogenase Levels for Patients Treated With Intensity-Modulated Radiotherapy for Nasopharyngeal Carcinoma: A Predictor of Poor Prognosis and Subsequent Liver Metastasis

Purpose: To evaluate the prognostic value of baseline serum lactate dehydrogenase (LDH) levels in patients with nasopharyngeal carcinoma (NPC) treated with intensity-modulated radiotherapy (IMRT). Methods and Materials: Cases of NPC (n = 465) that involved treatment with IMRT with or without chemotherapy were retrospectively analyzed. Results: The mean ({+-}SD) and median baseline serum LDH levels for this cohort were 172.77 {+-} 2.28 and 164.00 IU/L, respectively. Levels of LDH were significantly elevated in patients with locoregionally advanced disease (p = 0.016). Elevated LDH levels were identified as a prognostic factor for rates of overall survival (OS), disease-free survival (DFS), and distant metastasis-free survival (DMFS), with p values <0.001 in the univariate analysis and p < 0.001, p = 0.004, and p = 0.003, respectively, in the multivariate analysis. Correspondingly, the prognostic impact of patient LDH levels was found to be statistically significant for rates of OS, DFS, and DMFS (p = 0.028, 0.024, and 0.020, respectively). For patients who experienced subsequent liver failure after treatment, markedly higher pretreatment serum LDH levels were detected compared with patients experiencing distant metastasis events at other sites (p = 0.032). Conclusions: Elevated baseline LDH levels are associated with clinically advanced disease and are a poor prognosticator for OS, DFS, and DMFS for NPC patients. These results suggest that elevated serum levels of LDH should be considered when evaluating treatment options.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Impact of Triple-Negative Phenotype on Prognosis of Patients With Breast Cancer Brain Metastases

Purpose: To elucidate survival times and identify potential prognostic factors in patients with triple-negative (TN) phenotype who harbored brain metastases arising from breast cancer and who underwent stereotactic radiosurgery (SRS). Methods and Materials: A total of 103 breast cancer patients with brain metastases were treated with SRS and then studied retrospectively. Twenty-four patients (23.3%) were TN. Survival times were estimated using the Kaplan-Meier method, with a log-rank test computing the survival time difference between groups. Univariate and multivariate analyses to predict potential prognostic factors were performed using a Cox proportional hazard regression model. Results: The presence of TN phenotype was associated with worse survival times, including overall survival after the diagnosis of primary breast cancer (43 months vs. 82 months), neurologic survival after the diagnosis of intracranial metastases, and radiosurgical survival after SRS, with median survival times being 13 months vs. 25 months and 6 months vs. 16 months, respectively (p < 0.002 in all three comparisons). On multivariate analysis, radiosurgical survival benefit was associated with non-TN status and lower recursive partitioning analysis class at the initial SRS. Conclusion: The TN phenotype represents a significant adverse prognostic factor with respect to overall survival, neurologic survival, and radiosurgical survival in breast cancer patients with intracranial metastasis. Recursive partitioning analysis class also served as an important and independent prognostic factor.

62 RADIOLOGY AND NUCLEAR MEDICINE↗