Prioritizing river basins for nutrient studies.

Increases in fluxes of nitrogen (N) and phosphorus (P) in the environment have led to negative impacts affecting drinking water, eutrophication, harmful algal blooms, climate change, and biodiversity loss. Because of the importance, scale, and complexity of these issues, it may be useful to consider methods for prioritizing nutrient research in representative drainage basins within a regional or national context. Two systematic, quantitative approaches were developed to (1) identify basins that geospatial data suggest are most impacted by nutrients and (2) identify basins that have the most variability in factors affecting nutrient sources and transport in order to prioritize basins for studies that seek to understand the key drivers of nutrient impacts. The "impact" approach relied on geospatial variables representing surface-water and groundwater nutrient concentrations, sources of N and P, and potential impacts on receptors (i.e., ecosystems and human health). The "variability" approach relied on geospatial variables representing surface-water nutrient concentrations, factors affecting sources and transport of nutrients, model accuracy, and potential receptor impacts. One hundred and sixty-three drainage basins throughout the contiguous United States were ranked nationally and within 18 hydrologic regions. Nationally, the top-ranked basins from the impact approach were concentrated in the Midwest, while those from the variability approach were dispersed across the nation. Regionally, the top-ranked basin selected by the two approaches differed in 15 of the 18 regions, with top-ranked basins selected by the variability approach having lower minimum concentrations and larger ranges in concentrations than top-ranked basins selected by the impact approach. The highest ranked basins identified using the variability approach may have advantages for exploring how landscape factors affect surface-water quality and how surface-water quality may affect ecosystems. In contrast, the impact approach prioritized basins in terms of human development and nutrient concentrations in both surface water and groundwater, thereby targeting areas where actions to reduce nutrient concentrations could have the largest effect on improving water availability and reducing ecosystem impacts.

Prioritizing water availability study settings to address geogenic contaminants and related societal factors.

Water availability for human and ecological uses depends on both water quantity and water quality. The U.S. Geological Survey (USGS) is developing strategies for prioritizing regional-scale and watershed basin-scale studies of water availability across the nation. Previous USGS ranking processes for basin-scale studies incorporated primarily water quantity factors but are now considering additional water quality factors. This study presents a ranking based on the potential impacts of geogenic constituents on water quality and consideration of societal factors related to water quality. High-concentration geogenic constituents, including trace elements and radionuclides, are among the most prevalent contaminants limiting water availability in the USA and globally. Geogenic constituents commonly occur in groundwater because of subsurface water-rock interactions, and their distributions are controlled by complex geochemical processes. Geogenic constituent mobility can also be affected by human activities (e.g., mining, energy production, irrigation, and pumping). Societal factors and relations to drinking water sources and water quality information are often overlooked when evaluating research priorities. Sociodemographic characteristics, data gaps resulting from historical data-collection disparities, and infrastructure condition/age are examples of factors to consider regarding environmental justice. This paper presents approaches for ranking and prioritizing potential basin-scale study areas across the contiguous USA by considering a suite of conventional physical and geochemical variables related to geogenic constituents, with and without considering variables related to societal factors. Simultaneous consideration of societal and conventional factors could provide decision makers with more diverse, interdisciplinary tools to increase equity and reduce bias in prioritizing focused research areas and future water availability studies.

Anterior Skull Base Osteoradionecrosis in the Age of Intensity-Modulated Radiation Therapy: A Case Series.

Background Despites advances in radiation technology, skull base osteoradionecrosis (ORN) continues to be a rare, devastating, and hard to treat complication of radiotherapy. We present three cases of anterior skull base ORN in a cohort treated with intensity-modulated radiation therapy (IMRT). Case Series Three patients developed anterior skull base ORN after receiving at least one round of IMRT. ORN was diagnosed through either nasal endoscopy or imaging findings. The first was a 59-year-old woman with a sinonasal squamous cell carcinoma. Her chemoradiation history was notable for reirradiation and a high dose of radiation (143.3 Gy). The second was a 55-year-old man with recurrent nasopharyngeal carcinoma, whose history was notable for a high dose of radiation (∼140 Gy) and for being reirradiated. The final patient was a 37-year-old woman with an unremarkable history who received radiotherapy (65.0 Gy) for an esthesioneuroblastoma. One patient was asymptomatic and did not receive ORN-specific therapy. The other two were treated with a combination of medical and surgical intervention with successful short-term outcomes (no evidence of infection). Conclusion Anterior skull base ORN can be treated through conservative and surgical means to achieve successful short-term outcomes. Further investigation of long-term outcomes is warranted.

Sediment Sources and Sealed-Pavement Area Drive Polycyclic Aromatic Hydrocarbon and Metal Occurrence in Urban Streams.

Metals and polycyclic aromatic hydrocarbons (PAHs) are common pollutants in urban streambed sediment, yet their occurrence is highly variable and difficult to predict. To investigate sources of PAHs and metals to streambed sediment, we sampled pavement dust, soil, and streambed sediment in 10 urban watersheds in three regions of the United States and applied a fallout-radionuclide-based sediment-source analysis to quantify the pavement dust contribution to stream sediment (%dust). We also mapped the area of sealcoated pavement in each watershed (%sealed) to investigate the role of coal-tar pavement sealant (CTS) as a PAH source. Median total and carbon-normalized total PAH concentrations were significantly higher in streambed sediment in the Northeast (54.3 mg/kg and 2.71 mg/gOC) and Southeast (5.37 mg/kg and 1.36 mg/gOC), where CTS is commonly used, than in the Northwest (2.11 mg/kg and 0.071 mg/gOC), where CTS is rarely used. Generalized additive models indicated that %sealed and in some cases %dust significantly affected total PAH concentrations in streambed sediments. The %dust was a significant variable for common urban metals: Cu, Pb, and Zn. These findings advance our quantitative understanding of the role of pavement dust as a source and a vector of contaminants to urban streams.

An Automatic Deep Learning-Based Workflow for Glioblastoma Survival Prediction Using Preoperative Multimodal MR Images: A Feasibility Study.

PURPOSE: Most radiomic studies use the features extracted from the manually drawn tumor contours for classification or survival prediction. However, large interobserver segmentation variations lead to inconsistent features and hence introduce more challenges in constructing robust prediction models. Here, we proposed an automatic workflow for glioblastoma (GBM) survival prediction based on multimodal magnetic resonance (MR) images. METHODS AND MATERIALS: Two hundred eighty-five patients with glioma (210 GBM, 75 low-grade glioma) were included. One hundred sixty-three of the patients with GBM had overall survival data. Every patient had 4 preoperative MR images and manually drawn tumor contours. A 3-dimensional convolutional neural network, VGG-Seg, was trained and validated using 122 patients with glioma for automatic GBM segmentation. The trained VGG-Seg was applied to the remaining 163 patients with GBM to generate their autosegmented tumor contours. The handcrafted and deep learning (DL)-based radiomic features were extracted from the autosegmented contours using explicitly designed algorithms and a pretrained convolutional neural network, respectively. One hundred sixty-three patients with GBM were randomly split into training (n = 122) and testing (n = 41) sets for survival analysis. Cox regression models were trained to construct the handcrafted and DL-based signatures. The prognostic powers of the 2 signatures were evaluated and compared. RESULTS: The VGG-Seg achieved a mean Dice coefficient of 0.86 across 163 patients with GBM for GBM segmentation. The handcrafted signature achieved a C-index of 0.64 (95% confidence interval, 0.55-0.73), whereas the DL-based signature achieved a C-index of 0.67 (95% confidence interval, 0.57-0.77). Unlike the handcrafted signature, the DL-based signature successfully stratified testing patients into 2 prognostically distinct groups. CONCLUSIONS: The VGG-Seg generated accurate GBM contours from 4 MR images. The DL-based signature achieved a numerically higher C-index than the handcrafted signature and significant patient stratification. The proposed automatic workflow demonstrated the potential of improving patient stratification and survival prediction in patients with GBM.

Is there an urban pesticide signature? Urban streams in five U.S. regions share common dissolved-phase pesticides but differ in predicted aquatic toxicity.

Pesticides occur in urban streams globally, but the relation of occurrence to urbanization can be obscured by regional differences. In studies of five regions of the United States, we investigated the effect of region and urbanization on the occurrence and potential toxicity of dissolved pesticide mixtures. We analyzed 225 pesticide compounds in weekly discrete water samples collected during 6-12 weeks from 271 wadable streams; development in these basins ranged from undeveloped to highly urbanized. Sixteen pesticides were consistently detected in 16 urban centers across the five regions-we propose that these pesticides comprise a suite of urban signature pesticides (USP) that are all common in small U.S. urban streams. These USPs accounted for the majority of summed maximum pesticide concentrations at urban sites within each urban center. USP concentrations, mixture complexity, and potential toxicity increased with the degree of urbanization in the basin. Basin urbanization explained the most variability in multivariate distance-based models of pesticide profiles, with region always secondary in importance. The USPs accounted for 83% of pesticides in the 20 most frequently occurring 2-compound unique mixtures at urban sites, with carbendazim+prometon the most common. Although USPs were consistently detected in all regions, detection frequencies and concentrations varied by region, conferring differences in potential aquatic toxicity. Potential toxicity was highest for invertebrates (benchmarks exceeded in 51% of urban streams), due most often to the neonicotinoid insecticide imidacloprid and secondarily to organophosphate insecticides and fipronil. Benchmarks were rarely exceeded in urban streams for plants (at 3% of sites) or fish (<1%). We propose that the USPs identified here would make logical core (nonexclusive) constituents for monitoring dissolved pesticides in U.S. urban streams, and that unique mixtures containing imidacloprid, fipronil, and carbendazim are priority candidates for mixtures toxicity testing.

Multi-region assessment of chemical mixture exposures and predicted cumulative effects in USA wadeable urban/agriculture-gradient streams.

Chemical-contaminant mixtures are widely reported in large stream reaches in urban/agriculture-developed watersheds, but mixture compositions and aggregate biological effects are less well understood in corresponding smaller headwaters, which comprise most of stream length, riparian connectivity, and spatial biodiversity. During 2014-2017, the U.S. Geological Survey (USGS) measured 389 unique organic analytes (pharmaceutical, pesticide, organic wastewater indicators) in 305 headwater streams within four contiguous United States (US) regions. Potential aquatic biological effects were evaluated for estimated maximum and median exposure conditions using multiple lines of evidence, including occurrence/concentrations of designed-bioactive pesticides and pharmaceuticals and cumulative risk screening based on vertebrate-centric ToxCast™ exposure-response data and on invertebrate and nonvascular plant aquatic life benchmarks. Mixed-contaminant exposures were ubiquitous and varied, with 78% (304) of analytes detected at least once and cumulative maximum concentrations up to more than 156,000 ng/L. Designed bioactives represented 83% of detected analytes. Contaminant summary metrics correlated strong-positive (rho (ρ): 0.569-0.719) to multiple watershed-development metrics, only weak-positive to point-source discharges (ρ: 0.225-353), and moderate- to strong-negative with multiple instream invertebrate metrics (ρ: -0.373 to -0.652). Risk screening indicated common exposures with high probability of vertebrate-centric molecular effects and of acute toxicity to invertebrates, respectively. The results confirm exposures to broad and diverse contaminant mixtures and provide convincing multiple lines of evidence that chemical contaminants contribute substantially to adverse multi-stressor effects in headwater-stream communities.

Prioritizing river basins for intensive monitoring and assessment by the US Geological Survey.

The US Geological Survey (USGS) is currently (2020) integrating its water science programs to better address the nation's greatest water resource challenges now and into the future. This integration will rely, in part, on data from 10 or more intensively monitored river basins from across the USA. A team of USGS scientists was convened to develop a systematic, quantitative approach to prioritize candidate basins for this monitoring investment to ensure that, as a group, the 10 basins will support the assessment and forecasting objectives of the major USGS water science programs. Candidate basins were the level-4 hydrologic units (HUC04) with some of the smaller HUC04s being combined; median candidate-basin area is 46,600 km2. Candidate basins for the contiguous United States (CONUS) were grouped into 18 hydrologic regions. Ten geospatial variables representing land use, climate change, water use, water-balance components, streamflow alteration, fire risk, and ecosystem sensitivity were selected to rank candidate basins within each of the 18 hydrologic regions. The two highest ranking candidate basins in each of the 18 regions were identified as finalists for selection as "Integrated Water Science Basins"; final selection will consider input from a variety of stakeholders. The regional framework, with only one basin selected per region, ensures that as a group, the basins represent the range in major drivers of the hydrologic cycle. Ranking within each region, primarily based on anthropogenic stressors of water resources, ensures that settings representing important water-resource challenges for the nation will be studied.

Biofilms Provide New Insight into Pesticide Occurrence in Streams and Links to Aquatic Ecological Communities.

Streambed sediment is commonly analyzed to assess occurrence of hydrophobic pesticides and risks to aquatic communities. However, stream biofilms also have the potential to accumulate pesticides and may be consumed by aquatic organisms. To better characterize risks to aquatic life, the U.S. Geological Survey Regional Stream Quality Assessment measured 93 current-use and 3 legacy pesticides in bed sediment and biofilm from 54 small streams in California across a range of land-use settings. On average, 4 times as many current-use pesticides were detected in biofilm at a site (median of 2) as in sediment (median of 0.5). Of 31 current-use pesticides detected, 20 were detected more frequently in biofilm than in sediment and 10 with equal frequency. Pyrethroids as a class were the most potentially toxic to benthic invertebrates, and of the 9 pyrethroids detected, 7 occurred more frequently in biofilm than sediment. We constructed general additive models to investigate relations between pesticides and 6 metrics of benthic community structure. Pesticides in biofilm improved fit in 4 of the 6 models, and pesticides in sediment improved fit in 2. The results indicate that the sampling of stream biofilms can complement bed-sediment sampling by identification of more current-use pesticides present and better estimation of ecological risks.

Self-channel-and-spatial-attention neural network for automated multi-organ segmentation on head and neck CT images.

Accurate segmentation of organs at risk (OARs) is necessary for adaptive head and neck (H&N) cancer treatment planning, but manual delineation is tedious, slow, and inconsistent. A self-channel-and-spatial-attention neural network (SCSA-Net) is developed for H&N OAR segmentation on CT images. To simultaneously ease the training and improve the segmentation performance, the proposed SCSA-Net utilizes the self-attention ability of the network. Spatial and channel-wise attention learning mechanisms are both employed to adaptively force the network to emphasize the meaningful features and weaken the irrelevant features simultaneously. The proposed network was first evaluated on a public dataset, which includes 48 patients, then on a separate serial CT dataset, which contains ten patients who received weekly diagnostic fan-beam CT scans. On the second dataset, the accuracy of using SCSA-Net to track the parotid and submandibular gland volume changes during radiotherapy treatment was quantified. The Dice similarity coefficient (DSC), positive predictive value (PPV), sensitivity (SEN), average surface distance (ASD), and 95% maximum surface distance (95SD) were calculated on the brainstem, optic chiasm, optic nerves, mandible, parotid glands, and submandibular glands to evaluate the proposed SCSA-Net. The proposed SCSA-Net consistently outperforms the state-of-the-art methods on the public dataset. Specifically, compared with Res-Net and SE-Net, which is constructed from squeeze-and-excitation block equipped residual blocks, the DSC of the optic nerves and submandibular glands is improved by 0.06, 0.03 and 0.05, 0.04 by the SCSA-Net. Moreover, the proposed method achieves statistically significant improvements in terms of DSC on all and eight of nine OARs over Res-Net and SE-Net, respectively. The trained network was able to achieve good segmentation results on the serial dataset, but the results were further improved after fine-tuning of the model using the simulation CT images. For the parotids and submandibular glands, the volume changes of individual patients are highly consistent between the automated and manual segmentation (Pearson's correlation 0.97-0.99). The proposed SCSA-Net is computationally efficient to perform segmentation (sim 2 s/CT).

Multi-region assessment of pharmaceutical exposures and predicted effects in USA wadeable urban-gradient streams.

Human-use pharmaceuticals in urban streams link aquatic-ecosystem health to human health. Pharmaceutical mixtures have been widely reported in larger streams due to historical emphasis on wastewater-treatment plant (WWTP) sources, with limited investigation of pharmaceutical exposures and potential effects in smaller headwater streams. In 2014-2017, the United States Geological Survey measured 111 pharmaceutical compounds in 308 headwater streams (261 urban-gradient sites sampled 3-5 times, 47 putative low-impact sites sampled once) in 4 regions across the US. Simultaneous exposures to multiple pharmaceutical compounds (pharmaceutical mixtures) were observed in 91% of streams (248 urban-gradient, 32 low-impact), with 88 analytes detected across all sites and cumulative maximum concentrations up to 36,142 ng/L per site. Cumulative detections and concentrations correlated to urban land use and presence/absence of permitted WWTP discharges, but pharmaceutical mixtures also were common in the 75% of sampled streams without WWTP. Cumulative exposure-activity ratios (EAR) indicated widespread transient exposures with high probability of molecular effects to vertebrates. Considering the potential individual and interactive effects of the detected pharmaceuticals and the recognized analytical underestimation of the pharmaceutical-contaminant (unassessed parent compounds, metabolites, degradates) space, these results demonstrate a nation-wide environmental concern and the need for watershed-scale mitigation of in-stream pharmaceutical contamination.

Prediction of deep learning-based radiomic features for neoadjuvant radiochemotherapy response in locally advanced rectal cancer / 中华放射肿瘤学杂志

Objective:To evaluate the effectiveness of deep learning (DL)-based radiomic features extracted from pre-treatment diffusion-weighted magnetic resonance images (DWI) for predicting neoadjuvant chemoradiation treatment (nCRT) response in patients with locally advanced rectal cancer (LARC).Methods:Forty-three patients receiving nCRT from 2016 to 2017 were included. All patients received DWI before nCRT and total mesorectal excision surgery 6-12 weeks after completion of nCRT. The patient-cohort was split into the responder group ( n=22) and the non-responder group ( n=21) based on the post-nCRT response assessed by postoperative pathology, MRI or colonoscopy. DL-based radiomic features were extracted from the apparent diffusion coefficient map of the DWI using a pre-trained convolution neural network, respectively. Least absolute shrinkage and selection operator-Logistic regression models were constructed using extracted radiomic features for predicting treatment response. The model performance was evaluated with repeated 20 times stratified 4-fold cross-validation using receiver operating characteristic (ROC) curves. Results:The model established with DL-based radiomic features achieved the mean area under the ROC curve of 0.73(SE, 0.58-0.80).Conclusion:DL-based radiomic features extracted from pre-treatment DWI achieve high accuracy for predicting nCRT response in patients with LARC.

Projected urban growth in the southeastern USA puts small streams at risk.

Future land-use development has the potential to profoundly affect the health of aquatic ecosystems in the coming decades. We developed regression models predicting the loss of sensitive fish (R2 = 0.39) and macroinvertebrate (R2 = 0.64) taxa as a function of urban and agricultural land uses and applied them to projected urbanization of the rapidly urbanizing Piedmont ecoregion of the southeastern USA for 2030 and 2060. The regression models are based on a 2014 investigation of water quality and ecology of 75 wadeable streams across the region. Based on these projections, stream kilometers experiencing >50% loss of sensitive fish and invertebrate taxa will nearly quadruple to 19,500 and 38,950 km by 2060 (16 and 32% of small stream kilometers in the region), respectively. Uncertainty was assessed using the 20 and 80% probability of urbanization for the land-use projection model and using the 95% confidence intervals for the regression models. Adverse effects on stream health were linked to elevated concentrations of contaminants and nutrients, low dissolved oxygen, and streamflow alteration, all associated with urbanization. The results of this analysis provide a warning of potential risks from future urbanization and perhaps some guidance on how those risks might be mitigated.

Mixed-chemical exposure and predicted effects potential in wadeable southeastern USA streams.

Complex chemical mixtures have been widely reported in larger streams but relatively little work has been done to characterize them and assess their potential effects in headwater streams. In 2014, the United States Geological Survey (USGS) sampled 54 Piedmont streams over ten weeks and measured 475 unique organic compounds using five analytical methods. Maximum and median exposure conditions were evaluated in relation to watershed characteristics and for potential biological effects using multiple lines of evidence. Results demonstrate that mixed-contaminant exposures are ubiquitous and varied in sampled headwater streams. Approximately 56% (264) of the 475 compounds were detected at least once across all sites. Cumulative maximum concentrations ranged 1,922-162,346ngL-1 per site. Chemical occurrence significantly correlated to urban land use but was not related to presence/absence of wastewater treatment facility discharges. Designed bioactive chemicals represent about 2/3rd of chemicals detected, notably pharmaceuticals and pesticides, qualitative evidence for possible adverse biological effects. Comparative Toxicogenomics Database chemical-gene associations applied to maximum exposure conditions indicate >12,000 and 2,900 potential gene targets were predicted at least once across all sites for fish and invertebrates, respectively. Analysis of cumulative exposure-activity ratios provided additional evidence that, at a minimum, transient exposures with high probability of molecular effects to vertebrates were common. Finally, cumulative detections and concentrations correlated inversely with invertebrate metrics from in-stream surveys. The results demonstrate widespread instream exposure to extensive contaminant mixtures and compelling multiple lines of evidence for adverse effects on aquatic communities.

Nutrient enrichment in wadeable urban streams in the Piedmont Ecoregion of the Southeastern United States.

The U.S. Geological Survey (USGS) Southeastern Stream Quality Assessment (SESQA) collected weekly samples for nitrogen and phosphorus in 76 wadeable streams in the urbanized Piedmont Ecoregion of the Southeastern United States, during April-June 2014. Total nitrogen (TN) concentrations in excess of U.S. Environmental Protection Agency (EPA) guidelines and statistically greater than at reference locations indicated nitrogen-nutrient enrichment in streams draining poultry confined animal feeding operations (CAFO) or urban centers. Nitrate plus nitrite (NO3 + NO2) dominated TN species in urban/CAFO-influenced streams. Streams that drained poultry CAFO and Washington DC had statistically higher NO3 + NO2 concentrations than streams draining Atlanta, Charlotte, Greenville, or Raleigh. In contrast, total phosphorus (TP) concentrations in Atlanta and Washington DC streams statistically were comparable to and lower than, respectively, reference stream concentrations. Over 50% of TP concentrations in Greenville, Charlotte, Raleigh and CAFO-influenced streams exceeded the EPA guideline and reference-location mean concentrations, indicating phosphorus-nutrient enrichment. Urban land use, permitted point sources, and soil infiltration metrics best predicted TN exceedances. Elevated TN and NO3 + NO2 concentrations in urban streams during low flow were consistent with reduced in-stream dilution of point-source or groundwater contributions. Urban land use, permitted point sources, and surface runoff metrics best predicted TP exceedances. Elevated TP in CAFO and urban streams during high flow were consistent with non-point sources and particulate transport.

Estimating the High-Arsenic Domestic-Well Population in the Conterminous United States.

Arsenic concentrations from 20 450 domestic wells in the U.S. were used to develop a logistic regression model of the probability of having arsenic >10 µg/L ("high arsenic"), which is presented at the county, state, and national scales. Variables representing geologic sources, geochemical, hydrologic, and physical features were among the significant predictors of high arsenic. For U.S. Census blocks, the mean probability of arsenic >10 µg/L was multiplied by the population using domestic wells to estimate the potential high-arsenic domestic-well population. Approximately 44.1 M people in the U.S. use water from domestic wells. The population in the conterminous U.S. using water from domestic wells with predicted arsenic concentration >10 µg/L is 2.1 M people (95% CI is 1.5 to 2.9 M). Although areas of the U.S. were underrepresented with arsenic data, predictive variables available in national data sets were used to estimate high arsenic in unsampled areas. Additionally, by predicting to all of the conterminous U.S., we identify areas of high and low potential exposure in areas of limited arsenic data. These areas may be viewed as potential areas to investigate further or to compare to more detailed local information. Linking predictive modeling to private well use information nationally, despite the uncertainty, is beneficial for broad screening of the population at risk from elevated arsenic in drinking water from private wells.

High Nitrate Concentrations in Some Midwest United States Streams in 2013 after the 2012 Drought.

Nitrogen sources in the Mississippi River basin have been linked to degradation of stream ecology and to Gulf of Mexico hypoxia. In 2013, the USGS and the USEPA characterized water quality stressors and ecological conditions in 100 wadeable streams across the midwestern United States. Wet conditions in 2013 followed a severe drought in 2012, a weather pattern associated with elevated nitrogen concentrations and loads in streams. Nitrate concentrations during the May to August 2013 sampling period ranged from <0.04 to 41.8 mg L as N (mean, 5.31 mg L). Observed mean May to June nitrate concentrations at the 100 sites were compared with May to June concentrations predicted from a regression model developed using historical nitrate data. Observed concentrations for 17 sites, centered on Iowa and southern Minnesota, were outside the 95% confidence interval of the regression-predicted mean, indicating that they were anomalously high. The sites with a nitrate anomaly had significantly higher May to June nitrate concentrations than sites without an anomaly (means, 19.8 and 3.6 mg L, respectively) and had higher antecedent precipitation indices, a measure of the departure from normal precipitation, in 2012 and 2013. Correlations between nitrate concentrations and watershed characteristics and nitrogen and oxygen isotopes of nitrate indicated that fertilizer and manure used in crop production, principally corn, were the dominant sources of nitrate. The anomalously high nitrate levels in parts of the Midwest in 2013 coincide with reported higher-than-normal nitrate loads in the Mississippi River.

Geometric validation of MV topograms for patient localization on TomoTherapy.

Our goal was to geometrically validate the use of mega-voltage orthogonal scout images (MV topograms) as a fast and low-dose alternative to mega-voltage computed tomography (MVCT) for daily patient localization on the TomoTherapy system. To achieve this, anthropomorphic head and pelvis phantoms were imaged on a 16-slice kilo-voltage computed tomography (kVCT) scanner to synthesize kilo-voltage digitally reconstructed topograms (kV-DRT) in the Tomotherapy detector geometry. MV topograms were generated for couch speeds of 1-4 cm s(-1) in 1 cm s(-1) increments with static gantry angles in the anterior-posterior and left-lateral directions. Phantoms were rigidly translated in the anterior-posterior (AP), superior-inferior (SI), and lateral (LAT) directions to simulate potential setup errors. Image quality improvement was demonstrated by estimating the noise level in the unenhanced and enhanced MV topograms using a principle component analysis-based noise level estimation algorithm. Average noise levels for the head phantom were reduced by 2.53 HU (AP) and 0.18 HU (LAT). The pelvis phantom exhibited average noise level reduction of 1.98 HU (AP) and 0.48 HU (LAT). Mattes Mutual Information rigid registration was used to register enhanced MV topograms with corresponding kV-DRT. Registration results were compared to the known rigid displacements, which assessed the MV topogram localization's sensitivity to daily positioning errors. Reduced noise levels in the MV topograms enhanced the registration results so that registration errors were <1 mm. The unenhanced head MV topograms had discrepancies < 2.1 mm and the pelvis topograms had discrepancies < 2.7 mm. Result were found to be consistent regardless of couch speed. In total, 64.7% of the head phantom MV topograms and 60.0% of the pelvis phantom MV topograms exactly measured the phantom offsets. These consistencies demonstrated the potential for daily patient positioning using MV topogram pairs in the context bony-anatomy based procedures such as total marrow irradiation, total body irradiation, and cranial spinal irradiation.