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At least 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Identifying key factors of the seawater intrusion model of Dagu river basin, Jiaozhou Bay

Highlights: • The key factors of seawater intrusion model is identified by mutual entropy analysis. • Precipitation rate and groundwater pumping are the key factors for seawater intrusion. • The hydraulic conductivity of zone 1 has significant influence on seawater intrusion. Seawater intrusion is a complex groundwater - seawater interaction process, and it is influenced by many factors from ground surface to underground, from groundwater to seawater. Generally, for seawater intrusion model, some model parameters and boundary conditions are always specified by model users’ personal experiences or literature's reference value. The defective model would damage the groundwater management for controlling and preventing seawater intrusion when making decisions are based on this model. In order to improve the reliability of seawater intrusion model, the influences of model inputs on output should be identified prior at optimizing model inputs. Dagu river basin, Jiaozhou Bay is one of the most serious areas of seawater intrusion in China, and it is chosen as the study area in this study. The seawater intrusion model of Dagu river basin is built based on a general program SEAWAT4. The key influence factors of model output are analyzed by two sensitivity analysis methods, i.e., stepwise regression and mutual entropy. The results demonstrated that the most important influence factors which have largest sensitivities to groundwater Cl{sup -} concentration are the precipitation rate and groundwater pumping in agriculture area. In addition, the hydraulic conductivity of zone 1 has a non-negligible influence on seawater intrusion process. Stepwise regression analysis is capable of identifying most important influence factor, and it can’t handle complicated nonlinear input-output relationship. Mutual entropy analysis is reliable for identifying the influence factors for complex seawater intrusion model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Modeling forest site productivity using mapped geospatial attributes within a South Carolina Landscape, USA

Spatially explicit mapping of forest productivity is important to assess many forest management alternatives. We assessed the relationship between mapped variables and site index of forests ranging from southern pine plantations to natural hardwoods on a 74,000-ha landscape in South Carolina, USA. Mapped features used in the analysis were soil association, land use condition in 1951, depth to groundwater, slope and aspect. Basal area, species composition, age and height were the tree variables measured. Linear modelling identified that plot basal area, depth to groundwater, soils association and the interactions between depth to groundwater and forest group, and between land use in 1951 and forest group were related to site index (SI) (R 2 =0.37), but this model had regression attenuation. We then used structural equation modeling to incorporate error-in-measurement corrections for basal area and groundwater to remove bias in the model. We validated this model using 89 independent observations and found the 95% confidence intervals for the slope and intercept of an observed vs. predicted site index error-corrected regression included zero and one, respectively, indicating a good fit. With error in measurement incorporated, only basal area, soil association, and the interaction between forest groups and land use were important predictors (R2 =0.57). Thus, we were able to develop an unbiased model of SI that could be applied to create a spatially explicit map based primarily on soils as modified by past (land use and forest type) and recent forest management (basal area).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Collaborative simulations and experiments for a novel yield model of coal devolatilization in oxy-coal combustion conditions

Oxy-coal combustion is an emerging low-cost “clean coal” technology for emissions reduction and Carbon Capture and Sequestration (CCS). The use of Computational Fluid Dynamics (CFD) tools is crucial for the development of cost-effective oxy-fuel technologies and the minimization of environmental concerns at industrial scale. The coupling of detailed chemistry models and CFD simulations is still challenging, especially for large-scale plants, because of the high computational efforts required. The development of scale-bridging models is therefore necessary, to find a good compromise between computational efforts and the physical-chemical modeling precision. This paper presents a procedure for scale-bridging modeling of coal devolatilization, in the presence of experimental error, that puts emphasis on the thermodynamic aspect of devolatilization, namely the final volatile yield of coal, rather than kinetics. The procedure consists of an engineering approach based on dataset consistency and Bayesian methodology including Gaussian-Process Regression (GPR). Experimental data from devolatilization tests carried out in an oxy-coal entrained flow reactor were considered and CFD simulations of the reactor were performed. Jointly evaluating experiments and simulations, a novel yield model was validated against the data via consistency analysis. In parallel, a Gaussian-Process Regression was performed, to improve the understanding of the uncertainty associated to the devolatilization, based on the experimental measurements. Potential model forms that could predict yield during devolatilization were obtained. The set of model forms obtained via GPR includes the yield model that was proven to be consistent with the data. Finally, the overall procedure has resulted in a novel yield model for coal devolatilization and in a valuable evaluation of uncertainty in the data, in the model form, and in the model parameters.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2018

National soil organic carbon estimates can improve global estimates

Global inventories of spatial and vertical distribution of soil organic carbon (SOC) stocks are being used in national and global initiatives targeted to mitigate climate change and land degradation impacts. Yet, national level high-resolution estimates of SOC stocks can be useful for improving the accuracy of global SOC inventories. We estimated spatially resolved SOC stocks of surface 0–30 cm and subsurface 30–100 cm layers at a spatial resolution of 30m in tropical Island, Sri Lanka using a legacy harmonized soil database of 122 soil profiles. The national estimates were compared with two global estimates derived from WISE30sec and SoilGrids250m. The tropical Island (land area=64,610 km2) occupying 0.03% of global land area showed a considerable heterogeneity in SOC stocks ranging from 2.0-342.5 Mg ha -1 and 2.7-391.7 Mg ha -1 in the surface and subsurface soil layers, respectively. We found, elevation, precipitation and slope angle as main environmental controllers of the spatial distribution of SOC stocks under tropical climate. Incorporating the pedogenic information (derived from soil series level legacy map, soil orders and suborders) with environmental controllers resulted in better regression models of predicting surface (R 2 =0.61) and subsurface (R 2 =0.81) SOC stocks. Geographically weighted regression kriging derived maps of SOC stocks revealed that 0–100 cm soil layer of the tropical Island stored 500 Tg C contributing for 0.04% of the global SOC stocks. The validation results of our estimates showed low Mean Estimation Error (MEE: surface -1.6 and subsurface -1.6 Mg ha -1 ) and Root Mean Square Error (RMSE: surface 29.5 and subsurface 24.9 Mg ha -1 ) indicating a low bias and satisfactory predictions. The relative improvement of the prediction accuracy of the SOC stocks of our geospatial estimates in the 0–30 cm layer in comparison to SoilGrids250m and WISE30sec data derived SOC stocks were 51.7% and 35.2%, respectively. The SOC stocks predictions of the 30-100 cm soil layer showed even better relative improvement compared to SoilGrids250m (78.4%) and WISE30sec (57.4%) SOC estimates. Compared to estimates of total SOC stocks resulted in this study, WISE30sec data derived SOC stock maps showed 30% over estimation of the C stock in surface 0-30 cm (332 Tg C) and 41% overestimation in 30-100 cm layer (343 Tg C). The over estimation of total SOC stocks by the SoilGrids250 SOC stocks map for the surface 0-30 cm layer was 122% (567 Tg C) and for the 30-100 cm layer it was 209% (750 Tg C). We conclude that the fusion of legacy soil information of SOC stocks with appropriate environmental covariates and pedogenic information derived from legacy area-class soil maps at national level can produce more accurate inventories of spatial and vertical distribution of SOC stocks. As a result, these national inventories have a great potential of upgrading global inventories of SOC stocks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Spatial distribution of soil carbon stocks in a semi-arid region of India

We predicted total carbon (TC) stocks in the 0–30 cm soil depth of two southern states in India using field observations, environmental covariates and geospatial approaches. We compared the Geographically Weighted Regression Kriging (GWRK) with Linear Regression Kriging (LRK) approach to predict the TC stocks. Greater spatial heterogeneity in TC stocks (2–15 kg m –2 ) were predicted with lower estimation errors (RMSE = 2 kg m –2 R 2 = 0.63) in GWRK in comparison to the LRK approach (RMSE = 3 kg m –2 , R 2 = 0.55). The average decrease in the prediction error was 39% in GWRK in comparison to the LRK approach. The total TC stock in the 0–30 cm depth of the study area was estimated at 1.5 Pg C with upper and lower prediction intervals of 1 and 2 Pg C, respectively. The cropland stored largest (65%, 1 Pg C) amount of TC stocks followed by forest (21%, 0.31 Pg C) and plantation (8%, 0.12 Pg C) land cover types. Among soil types the Alfisols stored largest (33%, 0.49 Pg C) amount of TC stocks followed by Inceptisols (23%; 0.35 Pg C) and Entisols (18%, 0.27 Pg C). The uncertainty in TC stock predictions ranged from 41 to 75% and 69 to 91% under various land covers and soil types, respectively. Highest uncertainties in predicted TC stocks were associated with the forest land cover type and Mollisols soil order. Similarly, lowest uncertainties were found in the built up areas and Aridisols soil order. Our results suggest that GWRK is a useful approach to spatially predict the TC stocks at regional scales.

58 GEOSCIENCES↗
DOE OSTI2013

Use of 4-Dimensional Computed Tomography-Based Ventilation Imaging to Correlate Lung Dose and Function With Clinical Outcomes

Purpose: Four-dimensional computed tomography (4DCT)-based ventilation is an emerging imaging modality that can be used in the thoracic treatment planning process. The clinical benefit of using ventilation images in radiation treatment plans remains to be tested. The purpose of the current work was to test the potential benefit of using ventilation in treatment planning by evaluating whether dose to highly ventilated regions of the lung resulted in increased incidence of clinical toxicity. Methods and Materials: Pretreatment 4DCT data were used to compute pretreatment ventilation images for 96 lung cancer patients. Ventilation images were calculated using 4DCT data, deformable image registration, and a density-change based algorithm. Dose–volume and ventilation-based dose function metrics were computed for each patient. The ability of the dose–volume and ventilation-based dose–function metrics to predict for severe (grade 3+) radiation pneumonitis was assessed using logistic regression analysis, area under the curve (AUC) metrics, and bootstrap methods. Results: A specific patient example is presented that demonstrates how incorporating ventilation-based functional information can help separate patients with and without toxicity. The logistic regression significance values were all lower for the dose–function metrics (range P=.093-.250) than for their dose–volume equivalents (range, P=.331-.580). The AUC values were all greater for the dose–function metrics (range, 0.569-0.620) than for their dose–volume equivalents (range, 0.500-0.544). Bootstrap results revealed an improvement in model fit using dose–function metrics compared to dose–volume metrics that approached significance (range, P=.118-.155). Conclusions: To our knowledge, this is the first study that attempts to correlate lung dose and 4DCT ventilation-based function to thoracic toxicity after radiation therapy. Although the results were not significant at the .05 level, our data suggests that incorporating ventilation-based functional imaging can improve prediction for radiation pneumonitis. We present an important first step toward validating the use of 4DCT-based ventilation imaging in thoracic treatment planning.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

High Nuclear Hypoxia-Inducible Factor 1 Alpha Expression Is a Predictor of Distant Recurrence in Patients With Resected Pancreatic Adenocarcinoma

Purpose: To evaluate nuclear hypoxia-inducible factor 1α (HIF-1α) expression as a prognostic factor for distant recurrence (DR) and local recurrence (LR) after pancreatic adenocarcinoma resection. Methods and Materials: Tissue specimens were collected from 98 patients with pancreatic adenocarcinoma who underwent resection without neoadjuvant therapy between January 2000 and December 2011. Local recurrence was defined as radiographic or pathologic evidence of progressive disease in the pancreas, pancreatic bed, or associated nodal regions. Distant recurrence was defined as radiographically or pathologically confirmed recurrent disease in other sites. Immunohistochemical staining was performed and scored by an independent pathologist blinded to patient outcomes. High HIF-1α overall expression score was defined as high percentage and intensity staining and thus score >1.33. Univariate analysis was performed for HIF-1α score with LR alone and with DR. Multivariate logistic regression was used to determine predictors of LR and DR. Results: Median follow-up time for all patients was 16.3 months. Eight patients (8%) demonstrated isolated LR, 26 patients (26.5%) had isolated DR, and 13 patients had both LR and DR. Fifty-three patients (54%) had high HIF-1α expression, and 45 patients (46%) had low HIF-1α expression. High HIF-1α expression was significantly associated with DR (P=.03), and low HIF-1α expression was significantly associated with isolated LR (P=.03). On multivariate logistic regression analysis, high HIF-1α was the only significant predictor of DR (odds ratio 2.46 [95% confidence interval 1.06-5.72]; P=.03). In patients with a known recurrence, an HIF-1α score ≥2.5 demonstrated a specificity of 100% for DR. Conclusions: High HIF-1α expression is a significant predictor of distant failure versus isolated local failure in patients undergoing resection of pancreatic adenocarcinoma. Expression of HIF-1α may have utility in determining candidates for adjuvant local radiation therapy and systemic chemotherapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Risk of Hippocampal Metastases in Small Cell Lung Cancer Patients at Presentation and After Cranial Irradiation: A Safety Profile Study for Hippocampal Sparing During Prophylactic or Therapeutic Cranial Irradiation

Purpose: Neurocognitive impairment (NI) in patients with small cell lung cancer (SCLC) after whole brain radiation treatment (WBRT) is a significant cause of morbidity. Hippocampal avoidance (HA) during WBRT may mitigate or prevent NI in such patients. However, this has not been tested in SCLC patients. The estimated risk of metastases in the HA region (HM) in patients with SCLC at diagnosis or after WBRT is unknown. Our study aimed to determine the risk of HM in patients with SCLC and to assess correlated clinical factors. Methods and Materials: Patients with SCLC who experienced brain metastases (BM) at presentation (de novo) or after WBRT treated at the Saskatoon Cancer Centre between 2005 and 2012 were studied. Relevant neuroimaging was independently reviewed by a neuroradiologist. HM was defined as metastases within 5 mm of the hippocampus. Logistic regression analysis was performed to assess correlation between various clinical variables and HM. Results: Seventy eligible patients were identified. Of 59 patients presenting with de novo BM, 3 patients (5%, 95% confidence interval [CI]: 0%-10.7%) had HM. Collectively there were 359 (range, 1-33) de novo BM with 3 (0.8%, 95% CI: 0%-1.7%) HM deposits. Twenty patients experienced progression of metastatic disease in the brain after WBRT. Of the 20 patients, only 1 patient (5%, 95% CI: 0%-14.5%) experienced HM. On logistic regression, no factors significantly correlated with HM. Conclusion: The overall incidence of HM before or after WBRT in SCLC patients is low, providing preliminary support for the safety of HA during planned clinical trials of HA-WBRT for SCLC.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Hyperfractionated Accelerated Radiation Therapy (HART) of 70.6 Gy With Concurrent 5-FU/Mitomycin C Is Superior to HART of 77.6 Gy Alone in Locally Advanced Head and Neck Cancer: Long-term Results of the ARO 95-06 Randomized Phase III Trial

Purpose: To report the long-term results of the ARO 95-06 randomized trial comparing hyperfractionated accelerated chemoradiation with mitomycin C/5-fluorouracil (C-HART) with hyperfractionated accelerated radiation therapy (HART) alone in locally advanced head and neck cancer. Patients and Methods: The primary endpoint was locoregional control (LRC). Three hundred eighty-four patients with stage III (6%) and IV (94%) oropharyngeal (59.4%), hypopharyngeal (32.3%), and oral cavity (8.3%) cancer were randomly assigned to 30 Gy/2 Gy daily followed by twice-daily 1.4 Gy to a total of 70.6 Gy concurrently with mitomycin C/5-FU (C-HART) or 16 Gy/2 Gy daily followed by twice-daily 1.4 Gy to a total dose of 77.6 Gy alone (HART). Statistical analyses were done with the log-rank test and univariate and multivariate Cox regression analyses. Results: The median follow-up time was 8.7 years (95% confidence interval [CI]: 7.8-9.7 years). At 10 years, the LRC rates were 38.0% (C-HART) versus 26.0% (HART, P=.002). The cancer-specific survival and overall survival rates were 39% and 10% (C-HART) versus 30.0% and 9% (HART, P=.042 and P=.049), respectively. According to multivariate Cox regression analysis, the combined treatment was associated with improved LRC (hazard ratio [HR]: 0.6 [95% CI: 0.5-0.8; P=.002]). The association between combined treatment arm and increased LRC appeared to be limited to oropharyngeal cancer (P=.003) as compared with hypopharyngeal or oral cavity cancer (P=.264). Conclusions: C-HART remains superior to HART in terms of LRC. However, this effect may be limited to oropharyngeal cancer patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Clinical and Dosimetric Predictors of Acute Severe Lymphopenia During Radiation Therapy and Concurrent Temozolomide for High-Grade Glioma

Purpose: Acute severe lymphopenia (ASL) frequently develops during radiation therapy (RT) and concurrent temozolomide (TMZ) for high-grade glioma (HGG) and is associated with decreased survival. The current study was designed to identify potential predictors of ASL, with a focus on actionable RT-specific dosimetric parameters. Methods and Materials: From January 2007 to December 2012, 183 patients with HGG were treated with RT+TMZ and had available data including total lymphocyte count (TLC) and radiation dose-volume histogram parameters. ASL was defined as TLC of <500/μL within the first 3 months from the start of RT. Stepwise logistic regression analysis was used to determine the most important predictors of ASL. Results: Fifty-three patients (29%) developed ASL. Patients with ASL had significantly worse overall survival than those without (median: 12.5 vs 20.2 months, respectively, P<.001). Stepwise logistic regression analysis identified female sex (odds ratio [OR]: 5.30; 95% confidence interval [CI]: 2.46-11.41), older age (OR: 1.05; 95% CI: 1.02-1.09), lower baseline TLC (OR: 0.92; 95% CI: 0.87-0.98), and higher brain volume receiving 25 Gy (V{sub 25Gy}) (OR: 1.03; 95% CI: 1.003-1.05) as the most significant predictors for ASL. Brain V{sub 25Gy} <56% appeared to be the optimal threshold (OR: 2.36; 95% CI: 1.11-5.01), with an ASL rate of 38% versus 20% above and below this threshold, respectively (P=.006). Conclusions: Female sex, older age, lower baseline TLC, and higher brain V{sub 25Gy} are significant predictors of ASL during RT+TMZ therapy for HGG. Maintaining the V{sub 25Gy} of brain below 56% may reduce the risk of ASL.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Impact of Using Audit Data to Improve the Evidence-Based Use of Single-Fraction Radiation Therapy for Bone Metastases in British Columbia

Purpose: To assess the impact of a population-based intervention to increase the consistency and use of single-fraction radiation therapy (SFRT) for bone metastases. Methods and Materials: In 2012, an audit of radiation therapy prescriptions for bone metastases in British Columbia identified significant interphysician and -center (26%-73%) variation in the use of SFRT. Anonymous physician-level and identifiable regional cancer center SFRT use data were presented to all radiation oncologists, together with published guidelines, meta-analyses, and recommendations from practice leaders. The use of SFRT for bone metastases from 2007 through 2011 was compared with use of SFRT in 2013, to assess the impact of the audit and educational intervention. Multilevel logistic regression was used to assess the relationship between the usage of SFRT and the timing of the radiation while controlling for potentially confounding variables. Physician and center were included as group effects to account for the clustered structure of the data. Results: A total of 16,898 courses of RT were delivered from 2007 through 2011, and 3200 courses were delivered in 2013. The rates of SFRT use in 2007, 2008, 2009, 2010, 2011, and 2013 were 50.5%, 50.9%, 48.3%, 48.5%, 48.0%, and 59.7%, respectively (P<.001). Use of SFRT increased in each of 5 regional centers: A: 26% to 32%; B: 36% to 56%; C: 39% to 57%; D: 49% to 56%; and E: 73% to 85.0%. Use of SFRT was more consistent; 3 of 5 centers used SFRT for 56% to 57% of bone metastases RT courses. The regression analysis showed strong evidence that the usage of SFRT increased after the 2012 intervention (odds ratio 2.27, 95% confidence interval 2.06-2.50, P<.0001). Conclusion: Assessed on a population basis, an audit-based intervention increased utilization of SFRT for bone metastases. The intervention reversed a trend to decreasing SFRT use, reduced costs, and improved patient convenience. This suggests that dissemination of programmatic quality indicators in oncology can lead to increased utilization of evidence-based practice.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Thoracic Vertebral Body Irradiation Contributes to Acute Hematologic Toxicity During Chemoradiation Therapy for Non-Small Cell Lung Cancer

Purpose: To determine the relationships between radiation doses to the thoracic bone marrow and declines in blood cell counts in non-small cell lung cancer (NSCLC) patients treated with chemoradiation therapy (CRT). Methods and Materials: We included 52 patients with NSCLC treated with definitive concurrent carboplatin–paclitaxel and RT. Dose-volume histogram (DVH) parameters for the thoracic vertebrae (TV), sternum, scapulae, clavicles, and ribs were assessed for associations with changes in blood counts during the course of CRT. Linear and logistic regression analyses were performed to identify associations between hematologic nadirs and DVH parameters. A DVH parameter of Vx was the percentage of the total organ volume exceeding x radiation dose. Results: Grade ≥3 hematologic toxicity including neutropenia developed in 21% (n=11), leukopenia in 42% (n=22), anemia in 6% (n=3), and throbocytopenia in 2% (n=1) of patients. Greater RT dose to the TV was associated with higher risk of grade ≥3 leukopenia across multiple DVH parameters, including TV V{sub 20} (TVV) (odds ratio [OR] 1.06; P=.025), TVV{sub 30} (OR 1.07; P=.013), and mean vertebral dose (MVD) (OR 1.13; P=.026). On multiple regression analysis, TVV{sub 30} (β = −0.004; P=.018) and TVV{sub 20} (β = −0.003; P=.048) were associated with white blood cell nadir. Additional bone marrow sites (scapulae, clavicles, and ribs) did not affect hematologic toxicity. A 20% chance of grade ≥3 leukopenia was associated with a MVD of 13.5 Gy and a TTV{sub 30} of 28%. Cutoff values to avoid grade ≥3 leukopenia were MVD ≤23.9 Gy, TVV{sub 20} ≤56.0%, and TVV{sub 30} ≤52.1%. Conclusions: Hematologic toxicity is associated with greater RT doses to the TV during CRT for NSCLC. Sparing of the TV using advanced radiation techniques may improve tolerance of CRT and result in improved tolerance of concurrent chemotherapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Surveillance and Radiation Therapy for Stage I Seminoma—Have We Learned From the Evidence?

Purpose: To analyze, in the setting of stage I seminoma, the factors affecting adjuvant treatment decisions and resulting survival outcomes, using a national dataset. Methods and Materials: We identified 33,094 stage I seminoma patients after orchiectomy from 1998 to 2012 from the National Cancer Data Base. Factors affecting treatment selection (active surveillance [AS] vs adjuvant treatment [AT]) were identified using a parsimonious multivariate logistic regression model. Propensity scores for treatment decision were generated and incorporated into a multivariate Cox regression analysis of overall survival. This process was then repeated within the AT cohort for factors predictive for chemotherapy [CT] versus radiation therapy [RT]. Results: Only 33% of patients received AS, and 65% received AT (89% RT and 11% CT). From 1998 to 2012 the proportion receiving AS increased from 23% to 60%, whereas RT utilization decreased from 73% to 21%, and CT utilization increased from 2% to 17%. Utilization of low-dose RT increased from 1.5% in 1999 to 34% in 2012. There was a small absolute overall survival advantage to AT over AS at 10 years (95.0% vs 93.4%, propensity adjusted hazard ratio 0.58, P<.0005). Conclusions: There has been a significant increase in use of AS for stage I seminoma, influenced by both sociodemogrpahic and clinicopathologic factors. Between AT options, there has been significant increase in use of CT, mirrored by a decline in use of RT. Although overall survival remains high for all 3 treatment strategies, AT seems to be associated with a small absolute survival advantage over AS up to 10 years out from diagnosis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Very High-Risk Localized Prostate Cancer: Outcomes Following Definitive Radiation

Purpose: Existing definitions of high-risk prostate cancer consist of men who experience significant heterogeneity in outcomes. As such, criteria that identify a subpopulation of National Comprehensive Cancer Network (NCCN) high-risk prostate cancer patients who are at very high risk (VHR) for poor survival outcomes following prostatectomy were recently developed at our institution and include the presence of any of the following disease characteristics: multiple NCCN high-risk factors, primary Gleason pattern 5 disease and/or ≥5 biopsy cores with Gleason sums of 8 to 10. Whether these criteria also apply to men undergoing definitive radiation is unclear, as is the optimal treatment regimen in these patients. Methods and Materials: All men consecutively treated with definitive radiation by a single provider from 1993 to 2006 and who fulfilled criteria for NCCN high-risk disease were identified (n=288), including 99 patients (34%) with VHR disease. Multivariate-adjusted competing risk regression models were constructed to assess associations between the VHR definition and biochemical failure (BF), distant metastasis (DM), and prostate cancer–specific mortality (PCSM). Multivariate-adjusted Cox regression analysis assessed the association of the VHR definition with overall mortality (OM). Cumulative incidences of failure endpoints were compared between VHR men and other NCCN high-risk men. Results: Men with VHR disease compared to other NCCN high-risk men experienced a higher 10-year incidence of BF (54.0% vs 35.4%, respectively, P<.001), DM (34.9% vs 13.4%, respectively, P<.001), PCSM (18.5% vs 5.9%, respectively, P<.001), and OM (36.4% vs 27.0%, respectively, P=.04). VHR men with a detectable prostate-specific antigen (PSA) concentration at the end of radiation (EOR) remained at high risk of 10-year PCSM compared to VHR men with an undetectable EOR PSA (31.0% vs 13.7%, respectively, P=.05). Conclusions: NCCN high-risk prostate cancer patients who meet VHR criteria experience distinctly worse outcomes following definitive radiation and long-term androgen deprivation therapy, particularly if an EOR PSA is detectable. Optimal use of local therapies for VHR patients should be explored further, as should novel agents.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Quantitative Analysis of {sup 18}F-Fluorodeoxyglucose Positron Emission Tomography Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated With Stereotactic Body Radiation Therapy

Purpose: To identify prognostic biomarkers in pancreatic cancer using high-throughput quantitative image analysis. Methods and Materials: In this institutional review board–approved study, we retrospectively analyzed images and outcomes for 139 locally advanced pancreatic cancer patients treated with stereotactic body radiation therapy (SBRT). The overall population was split into a training cohort (n=90) and a validation cohort (n=49) according to the time of treatment. We extracted quantitative imaging characteristics from pre-SBRT {sup 18}F-fluorodeoxyglucose positron emission tomography, including statistical, morphologic, and texture features. A Cox proportional hazard regression model was built to predict overall survival (OS) in the training cohort using 162 robust image features. To avoid over-fitting, we applied the elastic net to obtain a sparse set of image features, whose linear combination constitutes a prognostic imaging signature. Univariate and multivariate Cox regression analyses were used to evaluate the association with OS, and concordance index (CI) was used to evaluate the survival prediction accuracy. Results: The prognostic imaging signature included 7 features characterizing different tumor phenotypes, including shape, intensity, and texture. On the validation cohort, univariate analysis showed that this prognostic signature was significantly associated with OS (P=.002, hazard ratio 2.74), which improved upon conventional imaging predictors including tumor volume, maximum standardized uptake value, and total legion glycolysis (P=.018-.028, hazard ratio 1.51-1.57). On multivariate analysis, the proposed signature was the only significant prognostic index (P=.037, hazard ratio 3.72) when adjusted for conventional imaging and clinical factors (P=.123-.870, hazard ratio 0.53-1.30). In terms of CI, the proposed signature scored 0.66 and was significantly better than competing prognostic indices (CI 0.48-0.64, Wilcoxon rank sum test P<1e-6). Conclusion: Quantitative analysis identified novel {sup 18}F-fluorodeoxyglucose positron emission tomography image features that showed improved prognostic value over conventional imaging metrics. If validated in large, prospective cohorts, the new prognostic signature might be used to identify patients for individualized risk-adaptive therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

A new surrogate modeling technique combining Kriging and polynomial chaos expansions – Application to uncertainty analysis in computational dosimetry

In numerical dosimetry, the recent advances in high performance computing led to a strong reduction of the required computational time to assess the specific absorption rate (SAR) characterizing the human exposure to electromagnetic waves. However, this procedure remains time-consuming and a single simulation can request several hours. As a consequence, the influence of uncertain input parameters on the SAR cannot be analyzed using crude Monte Carlo simulation. The solution presented here to perform such an analysis is surrogate modeling. This paper proposes a novel approach to build such a surrogate model from a design of experiments. Considering a sparse representation of the polynomial chaos expansions using least-angle regression as a selection algorithm to retain the most influential polynomials, this paper proposes to use the selected polynomials as regression functions for the universal Kriging model. The leave-one-out cross validation is used to select the optimal number of polynomials in the deterministic part of the Kriging model. The proposed approach, called LARS-Kriging-PC modeling, is applied to three benchmark examples and then to a full-scale metamodeling problem involving the exposure of a numerical fetus model to a femtocell device. The performances of the LARS-Kriging-PC are compared to an ordinary Kriging model and to a classical sparse polynomial chaos expansion. The LARS-Kriging-PC appears to have better performances than the two other approaches. A significant accuracy improvement is observed compared to the ordinary Kriging or to the sparse polynomial chaos depending on the studied case. This approach seems to be an optimal solution between the two other classical approaches. A global sensitivity analysis is finally performed on the LARS-Kriging-PC model of the fetus exposure problem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

A hybrid point-particle force model that combines physical and data-driven approaches

Here this study improves upon the physics-based pairwise interaction extended point-particle (PIEP) model. The PIEP model leverages our physical understanding to predict fluid mediated interactions between solid particles. By considering the relative location of neighboring particles, the PIEP model is able to provide better predictions than existing drag models. While the current physical PIEP model is a powerful tool, its assumptions lead to increased error in flows with higher particle volume fractions. To reduce this error, a regression algorithm makes direct use of the results of direct numerical simulations (DNS) of an array of monodisperse solid particles subjected to uniform ambient flow at varying Reynolds numbers. The resulting statistical model and the physical PIEP model are superimposed to construct a hybrid, physics-based data-driven PIEP model. It must be noted that the performance of a pure data-driven approach without the model-form provided by the physical PIEP model is substantially inferior. The hybrid model's predictive capabilities are analyzed using additional DNS data that was not part of training the data-driven model. In every case tested, the hybrid models resulting from the regression were capable of (1) improving upon the physical PIEP model's prediction and (2) recovering underlying relevant physics from the DNS data. As the particle volume fraction increases, the physical PIEP model loses the ability to approximate the forces experienced by the particles, but the statistical model continues to produce accurate approximations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Data driven investigation to understand the influence of total solids on biological biogas upgrading

In situ biogas upgrading achieves CO 2 conversion to CH 4 via hydrogenotrophic methanogenesis; however, gas-liquid mass transfer constraints limit the upgrading performance. Recognizing that optimization studies often underrepresent the effects of total solids (TS) and organic loading rate (OLR), this study undertook a holistic, statistics driven assessment of operating conditions for in situ H 2 assisted biogas upgrading, centering the analysis on TS and OLR. A dataset of 31 studies was compiled and comprised 99 observations. A rigorous analytical framework was employed, combining data standardization, fixed- and random-effects (REML) weighted regressions with cluster-robust errors, stratified analyses, and machine learning. Mixed-effects meta regression indicated that TS was the main factor explaining differences of methane fraction (CH 4 %) when considering the between studies heterogeneity. Focusing on a near-stoichiometric subset (H 2 /CO 2 ≈ 4:1), TS remained significant. Stratified results showed a stronger negative relationship between TS and CH 4 % in UASB reactors than in CSTRs, with a negative effect under mesophilic conditions and no significant effect under thermophilic conditions. A Random Forest model corroborated the statistical findings, consistently ranking H 2 /CO 2 ratio, OLR, TS, and hydrogen injection rate (HIR) as the most influential predictors. These findings delineate trends across increasing TS levels, particularly between 1% and 10%, and provide preliminary insights for TS above 15% in in situ biogas upgrading. They further provide insights for the influence of TS by reactor type and temperature, thereby advancing the evidence base for implementing biological CO 2 conversion to CH 4 in practice.

In situ biogas upgrading↗