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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Vehicle Tracking with Crop-based Detection

End-to-end production of vehicle tracking data from video in real-time and with high accuracy remains a challenging problem due to the computational cost of object detection on each frame. In this work we present Tracking with Crop-based Detection, a method for speeding object tracking in constrained contexts (with stable cameras and relatively-predictable object motion) such as vehicle traffic monitoring. We leverage this context to provide a strong prior for object locations, which we use to 1.) boost detection speed by detecting objects only in regions corresponding to object priors on most frames and 2.) inform the selection of the detector output for each object. We evaluate Crop-based Detection as an extension to the KIOU object tracker (Crop-KIOU) on the UA-DETRAC dataset. The proposed tracker outperforms all other reported algorithms in terms of PR-MOTA, PR-MOTP, and mostly tracked objects on the UA-DETRAC benchmark, establishing a new state-of-the-art. Relative to tracking by detection with KIOU, Crop-KIOU achieves a 26% higher frame-rate and increases accuracy. Furthermore, Tracking with Crop-based Detection can be combined with frame skipping; we show a 149% increase in framerate relative to KIOU with no decrease in accuracy using this combination of methods.

Gloudemans, Derek↗
DOE OSTI2020

Detection and Localization of Damaged Photovoltaic Cells and Modules Using Spread Spectrum Time Domain Reflectometry

The operating efficiency of photovoltaic (PV) plants can be improved if damaged or degraded modules can be detected and identified. Currently, string-level power electronics can detect problems with modules or cabling but not locate them, which would facilitate addressing these issues. Here, we investigate the ability of spread spectrum time domain reflectometry (SSTDR) to both detect and locate/identify damaged cells and modules within a series-connected PV string. We tested the ability of SSTDR to detect and locate single-cell mini-modules and full-sized PV modules, which were intentionally damaged by impacts with a hammer (breaking the glass and damaging the silicon below) or by cutting through some or all busbars. Damage to the glass and silicon of cells was detected and located within a small string of minimodules. Busbar damage was detectable only if an open was created by cutting through all intercell busbars. Furthermore, physical impact damage to the glass and silicon of a full-sized PV module could be detected, but further development of signal processing is needed to achieve localization of such damaged modules within a string.

14 SOLAR ENERGY↗
DOE OSTI2023

Cycle-by-cycle Delay Estimation at Signalized Intersections by using Machine Learning and Simulated Video Detection Data

Accurate estimation of delay is crucial for efficient traffic signal operations. Estimation of delay in the real-time manner using traditional loop detectors requires advanced detectors (in addition to stop-bar detection). In cases when this detection layout is not in place, delay estimates are approximated with a lower accuracy. Video detection is one of the most frequently deployed detection systems at signalized intersections in recent years. In most cases video detection operates in the same way as traditional inductive loops. However, when coupled with computer vision algorithms, video detection systems could be used to retrieve additional information (e.g., vehicular arrivals and departures) that cannot be taken out from the conventional systems (e.g., long stop-bar loop detectors). Although present for several decades, video detection data were not frequently examined for delay estimation purposes. In this study, we proposed a novel delay estimation model which can be developed with only data from stop-bar video detectors. Relevant data were collected from a simulation model of 11 signalized intersections at downtown Chattanooga, TN and processed to create needed inputs for model development. With the use of multigene genetic programming the authors developed a delay model that outperforms accuracy of multi regression model. Furthermore, authors evaluated the developed model by comparison with the other benchmark delay models, such as HCM and approach delay model. It was found that the developed MGGP delay model outperforms benchmark models for a wide range of traffic and signal operation conditions.

Erdagi, Ismet Goksad↗
DOE OSTI2022

Real-time Event Detection Using Rank Signatures of Real-world PMU Data

Timely detection of power system events is a crucial task, which can facilitate the implementation of remedial actions to improve reliability, resiliency, and security of the system. Meanwhile, the widespread deployment of phasor measurement units (PMUs) makes it possible to develop data-driven event detection techniques. However, relying purely on data without incorporating domain knowledge for the event detection task in power systems poses substantial security and stability risks due to issues associated with data misinterpretation and model accuracy. In this regard, we propose a real-time event detection method using real-world PMU data by incorporating domain knowledge to adequately capture the event signatures. Specifically, we track the change in rank signatures of PMU data to accurately localize the events. To optimize the detection process, we incorporate an offline Bayesian optimization algorithm to tune the parameters by efficiently searching for the best values. The experiments using the real-world PMU dataset from a U.S. interconnection show that the proposed event detection approach can efficiently detect the events from PMU data streams with high accuracy.

Ghasemkhani, Amir↗
DOE OSTI2013

Evaluating IMRT and VMAT dose accuracy: Practical examples of failure to detect systematic errors when applying a commonly used metric and action levels

Purpose: This study (1) examines a variety of real-world cases where systematic errors were not detected by widely accepted methods for IMRT/VMAT dosimetric accuracy evaluation, and (2) drills-down to identify failure modes and their corresponding means for detection, diagnosis, and mitigation. The primary goal of detailing these case studies is to explore different, more sensitive methods and metrics that could be used more effectively for evaluating accuracy of dose algorithms, delivery systems, and QA devices.Methods: The authors present seven real-world case studies representing a variety of combinations of the treatment planning system (TPS), linac, delivery modality, and systematic error type. These case studies are typical to what might be used as part of an IMRT or VMAT commissioning test suite, varying in complexity. Each case study is analyzed according to TG-119 instructions for gamma passing rates and action levels for per-beam and/or composite plan dosimetric QA. Then, each case study is analyzed in-depth with advanced diagnostic methods (dose profile examination, EPID-based measurements, dose difference pattern analysis, 3D measurement-guided dose reconstruction, and dose grid inspection) and more sensitive metrics (2% local normalization/2 mm DTA and estimated DVH comparisons).Results: For these case studies, the conventional 3%/3 mm gamma passing rates exceeded 99% for IMRT per-beam analyses and ranged from 93.9% to 100% for composite plan dose analysis, well above the TG-119 action levels of 90% and 88%, respectively. However, all cases had systematic errors that were detected only by using advanced diagnostic techniques and more sensitive metrics. The systematic errors caused variable but noteworthy impact, including estimated target dose coverage loss of up to 5.5% and local dose deviations up to 31.5%. Types of errors included TPS model settings, algorithm limitations, and modeling and alignment of QA phantoms in the TPS. Most of the errors were correctable after detection and diagnosis, and the uncorrectable errors provided useful information about system limitations, which is another key element of system commissioning.Conclusions: Many forms of relevant systematic errors can go undetected when the currently prevalent metrics for IMRT/VMAT commissioning are used. If alternative methods and metrics are used instead of (or in addition to) the conventional metrics, these errors are more likely to be detected, and only once they are detected can they be properly diagnosed and rooted out of the system. Removing systematic errors should be a goal not only of commissioning by the end users but also product validation by the manufacturers. For any systematic errors that cannot be removed, detecting and quantifying them is important as it will help the physicist understand the limits of the system and work with the manufacturer on improvements. In summary, IMRT and VMAT commissioning, along with product validation, would benefit from the retirement of the 3%/3 mm passing rates as a primary metric of performance, and the adoption instead of tighter tolerances, more diligent diagnostics, and more thorough analysis.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

Multichannel response analysis on 2D projection views for detection of clustered microcalcifications in digital breast tomosynthesis

Purpose: To investigate the feasibility of a new two-dimensional (2D) multichannel response (MCR) analysis approach for the detection of clustered microcalcifications (MCs) in digital breast tomosynthesis (DBT). Methods: With IRB approval and informed consent, a data set of two-view DBTs from 42 breasts containing biopsy-proven MC clusters was collected in this study. The authors developed a 2D approach for MC detection using projection view (PV) images rather than the reconstructed three-dimensional (3D) DBT volume. Signal-to-noise ratio (SNR) enhancement processing was first applied to each PV to enhance the potential MCs. The locations of MC candidates were then identified with iterative thresholding. The individual MCs were decomposed with Hermite–Gaussian (HG) and Laguerre–Gaussian (LG) basis functions and the channelized Hotelling model was trained to produce the MCRs for each MC on the 2D images. The MCRs from the PVs were fused in 3D by a coincidence counting method that backprojects the MC candidates on the PVs and traces the coincidence of their ray paths in 3D. The 3D MCR was used to differentiate the true MCs from false positives (FPs). Finally a dynamic clustering method was used to identify the potential MC clusters in the DBT volume based on the fact that true MCs of clinical significance appear in clusters. Using two-fold cross validation, the performance of the 3D MCR for classification of true and false MCs was estimated by the area under the receiver operating characteristic (ROC) curve and the overall performance of the MCR approach for detection of clustered MCs was assessed by free response receiver operating characteristic (FROC) analysis. Results: When the HG basis function was used for MCR analysis, the detection of MC cluster achieved case-based test sensitivities of 80% and 90% at the average FP rates of 0.65 and 1.55 FPs per DBT volume, respectively. With LG basis function, the average FP rates were 0.62 and 1.57 per DBT volume at the same sensitivity levels. The difference in the two sets of basis functions for detection of MCs did not show statistical significance. Conclusions: The authors' experimental results indicate that the MCR approach is promising for the detection of MCs on PV images. The HG or LG basis functions are both effective in characterizing the signal response of MCs using the channelized Hotelling model. The coincidence counting method for fusion of the 2D MCR in 3D is an important step for FP reduction. Further study is underway to improve the MCR approach for microcalcification detection in DBT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-E-J-235: Varian Portal Dosimetry Accuracy at Detecting Simulated Delivery Errors

Purpose: To use receiver operating characteristic (ROC) analysis to quantify the Varian Portal Dosimetry (VPD) application's ability to detect delivery errors in IMRT fields. Methods: EPID and VPD were calibrated/commissioned using vendor-recommended procedures. Five clinical plans comprising 56 modulated fields were analyzed using VPD. Treatment sites were: pelvis, prostate, brain, orbit, and base of tongue. Delivery was on a Varian Trilogy linear accelerator at 6MV using a Millenium120 multi-leaf collimator. Image pairs (VPD-predicted and measured) were exported in dicom format. Each detection test imported an image pair into Matlab, optionally inserted a simulated error (rectangular region with intensity raised or lowered) into the measured image, performed 3%/3mm gamma analysis, and saved the gamma distribution. For a given error, 56 negative tests (without error) were performed, one per 56 image pairs. Also, 560 positive tests (with error) with randomly selected image pairs and randomly selected in-field error location. Images were classified as errored (or error-free) if percent pixels with γ<κ was < (or ≥) τ. (Conventionally, κ=1 and τ=90%.) A ROC curve was generated from the 616 tests by varying τ. For a range of κ and τ, true/false positive/negative rates were calculated. This procedure was repeated for inserted errors of different sizes. VPD was considered to reliably detect an error if images were correctly classified as errored or error-free at least 95% of the time, for some κ+τ combination. Results: 20mm{sup 2} errors with intensity altered by ≥20% could be reliably detected, as could 10mm{sup 2} errors with intensity was altered by ≥50%. Errors with smaller size or intensity change could not be reliably detected. Conclusion: Varian Portal Dosimetry using 3%/3mm gamma analysis is capable of reliably detecting only those fluence errors that exceed the stated sizes. Images containing smaller errors can pass mathematical analysis, though may be detected by visual inspection. This work was not funded by Varian Oncology Systems. Some authors have other work partly funded by Varian Oncology Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Ghost marker detection and elimination in marker-based optical tracking systems for real-time tracking in stereotactic body radiotherapy

Purpose: To propose a simple model to explain the origin of ghost markers in marker-based optical tracking systems (OTS) and to develop retrospective strategies to detect and eliminate ghost markers. Methods: In marker-based OTS, ghost markers are virtual markers created due to the cross-talk between the two camera sensors, which can lead to system execution failure or inaccuracy in patient tracking. As a result, the users have to limit the number of markers and avoid certain marker configurations to reduce the chances of ghost markers. In this work, the authors propose retrospective strategies to detect and eliminate ghost markers. The two camera sensors were treated as mathematical points in space. The authors identified the coplanar within limit (CWL) condition as the necessary condition for ghost marker occurrence. A simple ghost marker detection method was proposed based on the model. Ghost marker elimination was achieved through pattern matching: a ghost marker-free reference set was matched with the optical marker set observed by the OTS; unmatched optical markers were eliminated as either ghost markers or misplaced markers. The pattern matching problem was formulated as a constraint satisfaction problem (using pairwise distances as constraints) and solved with an iterative backtracking algorithm. Wildcard markers were introduced to address missing or misplaced markers. An experiment was designed to measure the sensor positions and the limit for the CWL condition. The ghost marker detection and elimination algorithms were verified with samples collected from a five-marker jig and a nine-marker anthropomorphic phantom, rotated with the treatment couch from −60° to +60°. The accuracy of the pattern matching algorithm was further validated with marker patterns from 40 patients who underwent stereotactic body radiotherapy (SBRT). For this purpose, a synthetic optical marker pattern was created for each patient by introducing ghost markers, marker position uncertainties, and marker displacement. Results: The sensor positions and the limit for the CWL condition were measured with excellent reproducibility (standard deviation ≤ 0.39 mm). The ghost marker detection algorithm had perfect detection accuracy for both the jig (1544 samples) and the anthropomorphic phantom (2045 samples). Pattern matching was successful for all samples from both phantoms as well as the 40 patient marker patterns. Conclusions: The authors proposed a simple model to explain the origin of ghost markers and identified the CWL condition as the necessary condition for ghost marker occurrence. The retrospective ghost marker detection and elimination algorithms guarantee complete ghost marker elimination while providing the users with maximum flexibility in selecting the number of markers and their configuration to meet their clinic needs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-15: Automatically Detect Patient Treatment Position and Orientation in KV Portal Images

Purpose: In the course of radiation therapy, the complex information processing workflow will Result in potential errors, such as incorrect or inaccurate patient setups. With automatic image check and patient identification, such errors could be effectively reduced. For this purpose, we developed a simple and rapid image processing method, to automatically detect the patient position and orientation in 2D portal images, so to allow automatic check of positions and orientations for patient daily RT treatments. Methods: Based on the principle of portal image formation, a set of whole body DRR images were reconstructed from multiple whole body CT volume datasets, and fused together to be used as the matching template. To identify the patient setup position and orientation shown in a 2D portal image, the 2D portal image was preprocessed (contrast enhancement, down-sampling and couch table detection), then matched to the template image so to identify the laterality (left or right), position, orientation and treatment site. Results: Five day’s clinical qualified portal images were gathered randomly, then were processed by the automatic detection and matching method without any additional information. The detection results were visually checked by physicists. 182 images were correct detection in a total of 200kV portal images. The correct rate was 91%. Conclusion: The proposed method can detect patient setup and orientation quickly and automatically. It only requires the image intensity information in KV portal images. This method can be useful in the framework of Electronic Chart Check (ECCK) to reduce the potential errors in workflow of radiation therapy and so to improve patient safety. In addition, the auto-detection results, as the patient treatment site position and patient orientation, could be useful to guide the sequential image processing procedures, e.g. verification of patient daily setup accuracy. This work was partially supported by research grant from Varian Medical System.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-CD-207-12: Impact of Anatomical Noise On Detection Performance of Microcalcifications in Multi-Contrast Breast Imaging

Purpose: The anatomical noise power spectra (NPS) for differential phase contrast (DPC) and dark field (DF) imaging have recently been characterized using a power-law model with two parameters, alpha and beta, an innovative extension to the methodology used in x-ray attenuation based breast imaging such as mammography, DBT, or cone-beam CT. Beta values of 3.6, 2.6, and 1.3 have been measured for absorption, DPC, and DF respectively for cadaver breasts imaged in the coronal plane; these dramatic differences should be reflected in their detection performance. The purpose of this study was to determine the impact of anatomical noise on breast calcification detection and compare the detection performance of the three contrast mechanisms of a multi-contrast x-ray imaging system. Methods: In our studies, a calcification image object was segmented out of the multi-contrast images of a cadaver breast specimen. 50 measured total NPS were measured from breast cadavers directly. The ideal model observer detectability was calculated for a range of doses (5–100%) and a range of calcification sizes (diameter = 0.25–2.5 mm). Results: Overall we found the highest average detectability corresponded to DPC imaging (7.4 for 1 mm calc.), with DF the next highest (3.8 for 1 mm calc.), and absorption the lowest (3.2 for 1 mm calc.). However, absorption imaging also showed the slowest dependence on dose of the three modalities due to the significant anatomical noise. DPC showed a peak detectability for calcifications ∼1.25 mm in diameter, DF showed a peak for calcifications around 0.75 mm in diameter, and absorption imaging had no such peak in the range explored. Conclusion: Understanding imaging performance for DPC and DF is critical to transition these modalities to the clinic. The results presented here offer new insight into how these modalities complement absorption imaging to maximize the likelihood of detecting early breast cancers. J. Garrett, Y. Ge, K. Li: Nothing to disclose. G.-H. Chen: Research funded, GE Healthcare; Research funded, Siemens AX.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Quantifying the performance of in vivo portal dosimetry in detecting four types of treatment parameter variations

Purpose: To quantify the ability of electronic portal imaging device (EPID) dosimetry used during treatment (in vivo) in detecting variations that can occur in the course of patient treatment. Methods: Images of transmitted radiation from in vivo EPID measurements were converted to a 2D planar dose at isocenter and compared to the treatment planning dose using a prototype software system. Using the treatment planning system (TPS), four different types of variability were modeled: overall dose scaling, shifting the positions of the multileaf collimator (MLC) leaves, shifting of the patient position, and changes in the patient body contour. The gamma pass rate was calculated for the modified and unmodified plans and used to construct a receiver operator characteristic (ROC) curve to assess the detectability of the different parameter variations. The detectability is given by the area under the ROC curve (AUC). The TPS was also used to calculate the impact of the variations on the target dose–volume histogram. Results: Nine intensity modulation radiation therapy plans were measured for four different anatomical sites consisting of 70 separate fields. Results show that in vivo EPID dosimetry was most sensitive to variations in the machine output, AUC = 0.70 − 0.94, changes in patient body habitus, AUC = 0.67 − 0.88, and systematic shifts in the MLC bank positions, AUC = 0.59 − 0.82. These deviations are expected to have a relatively small clinical impact [planning target volume (PTV) D{sub 99} change <7%]. Larger variations have even higher detectability. Displacements in the patient’s position and random variations in MLC leaf positions were not readily detectable, AUC < 0.64. The D{sub 99} of the PTV changed by up to 57% for the patient position shifts considered here. Conclusions: In vivo EPID dosimetry is able to detect relatively small variations in overall dose, systematic shifts of the MLC’s, and changes in the patient habitus. Shifts in the patient’s position which can introduce large changes in the target dose coverage were not readily detected.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-471: Simulated External Beam Delivery Errors Detection with a Large Area Ion Chamber Transmission Detector

Purpose: The Integral Quality Monitor (IQM), developed by iRT Systems GmbH (Koblenz, Germany) is a large-area, linac-mounted ion chamber used to monitor photon fluence during patient treatment. Our previous work evaluated the change of the ion chamber’s response to deviations from static 1×1 cm2 and 10×10 cm2 photon beams and other characteristics integral to use in external beam detection. The aim of this work is to simulate two external beam radiation delivery errors, quantify the detection of simulated errors and evaluate the reduction in patient harm resulting from detection. Methods: Two well documented radiation oncology delivery errors were selected for simulation. The first error was recreated by modifying a wedged whole breast treatment, removing the physical wedge and calculating the planned dose with Pinnacle TPS (Philips Radiation Oncology Systems, Fitchburg, WI). The second error was recreated by modifying a static-gantry IMRT pharyngeal tonsil plan to be delivered in 3 unmodulated fractions. A radiation oncologist evaluated the dose for simulated errors and predicted morbidity and mortality commiserate with the original reported toxicity, indicating that reported errors were approximately simulated. The ion chamber signal of unmodified treatments was compared to the simulated error signal and evaluated in Pinnacle TPS again with radiation oncologist prediction of simulated patient harm. Results: Previous work established that transmission detector system measurements are stable within 0.5% standard deviation (SD). Errors causing signal change greater than 20 SD (10%) were considered detected. The whole breast and pharyngeal tonsil IMRT simulated error increased signal by 215% and 969%, respectively, indicating error detection after the first fraction and IMRT segment, respectively. Conclusion: The transmission detector system demonstrated utility in detecting clinically significant errors and reducing patient toxicity/harm in simulated external beam delivery. Future work will evaluate detection of other smaller magnitude delivery errors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Evaluating factors influencing infrasonic signal detection and automatic processing performance utilizing a regional network

Physical and deployment factors that influence infrasound signal detection and assess automatic detection performance for a regional infrasound network of arrays in the Western U.S. are explored using signatures of ground truth (GT) explosions (yields). Despite these repeated known sources, published infrasound event bulletins contain few GT events. Arrays are primarily distributed toward the south-southeast and south-southwest at distances between 84 and 458 km of the source with one array offering azimuthal resolution toward the northeast. Events occurred throughout the spring, summer, and fall of 2012 with the majority occurring during the summer months. Depending upon the array, automatic detection, which utilizes the adaptive F-detector successfully, identifies between 14% and 80% of the GT events, whereas a subsequent analyst review increases successful detection to 24%–90%. Combined background noise quantification, atmospheric propagation analyses, and comparison of spectral amplitudes determine the mechanisms that contribute to missed detections across the network. This analysis provides an estimate of detector performance across the network, as well as a qualitative assessment of conditions that impact infrasound monitoring capabilities. Finally, the mechanisms that lead to missed detections at individual arrays contribute to network-level estimates of detection capabilities and provide a basis for deployment decisions for regional infrasound arrays in areas of interest.

58 GEOSCIENCES↗
DOE OSTI2022

Out of Distribution Detection with Neural Network Anchoring

This is code to reproduce and build on OOD detection from the paper "Out of Distribution Detection with Neural Network Anchoring". Our goal here is to exploit heteroscedastic temperature scaling as a calibration strategy for out of distribution (OOD) detection. Heteroscedasticity here refers to the fact that the optimal temperature parameter for each sample can be different, as opposed to conventional approaches that use the same value for the entire distribution. To enable this, we propose a new training strategy called anchoring that can estimate appropriate temperature values for each sample, leading to state-of-the-art OOD detection performance across several benchmarks. Using NTK theory, we show that this temperature function estimate is closely linked to the epistemic uncertainty of the classifier, which explains its behavior. In contrast to some of the best-performing OOD detection approaches, our method does not require exposure to additional outlier datasets, custom calibration objectives, or model ensembling. Through empirical studies with different OOD detection settings - far OOD, near OOD, and semantically coherent OOD - we establish a highly effective OOD detection approach.

Thiagarajan, Jayaraman↗
DOE OSTI2019

Long-Term Outcome After Retro-Areolar Versus Peri-Tumoral Injection of Superparamagnetic Iron Oxide Nanoparticles (SPIO) for Sentinel Lymph Node Detection in Breast Cancer Surgery

Background/Objective: SPIO is effective in sentinel node (SN) detection. No nuclear medicine department is needed, and no allergic reactions have occurred. This study aimed to compare retro-areolar and peri-tumoral SPIO injections regarding skin staining, detection rates and number of SNs. Methods: Data on staining size, intensity and cosmetic outcome (0–5; 0 = no problem) were collected by telephone interviews with 258 women undergoing breast conservation. SN detection and the number of SNs were prospectively registered in 332 women. Results: After retro-areolar and peri-tumoral injections, 67.3% and 37.8% (p < 0.001) developed skin staining, with remaining staining in 46.2 vs. 9.4% after 36 months (p < 0.001). Initial mean size was 16.3 vs. 6.8 cm (p < 0.001) and after 36 months, 6.6 vs. 1.8 cm{sup 2} (p < 0.001). At 75.1% of 738 interviews, staining was reported paler. After retro-areolar injections, cosmetic outcome scored worse for 2 years. The mean (median) scores were 1.3(0) vs. 0.5(0) points, and 0.2(0) vs. 0.1(0) points, at 12 and 36 months, respectively. Overall detection rates were 98.3% and 97.4% (p = 0.43) and the number of SNs 1.35 vs. 1.57 (p = 0.02) after retro-areolar and peri-tumoral injections. Injection, regardless of type, 1–27 days before surgery increased detection rates with SPIO, 98.0% vs. 94.2% (p = 0.06) ,and SN numbers, 1.56 vs. 1.27 (p = 0.003). Conclusion: SPIO is effective and facilitates planning for surgery. Peri-tumoral injection reduced staining with a similar detection rate. Staining was not considered a cosmetic problem among most women. Injecting SPIO 1–27 days before surgery increased the detection rate by 3.8% and increased the number of SNs by 0.3.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Membrane insertion for the detection of lipopolysaccharides: Exploring the dynamics of amphiphile-in-lipid assays

Shiga toxin-producing Escherichia coli is an important cause of foodborne illness, with cases attributable to beef, fresh produce and other sources. Many serotypes of the pathogen cause disease, and differentiating one serotype from another requires specific identification of the O antigen located on the lipopolysaccharide (LPS) molecule. The amphiphilic structure of LPS poses a challenge when using classical detection methods, which do not take into account its lipoglycan biochemistry. Typically, detection of LPS requires heat or chemical treatment of samples and relies on bioactivity assays for the conserved lipid A portion of the molecule. Our goal was to develop assays to facilitate the direct and discriminative detection of the entire LPS molecule and its O antigen in complex matrices using minimal sample processing. To perform serogroup identification of LPS, we used a method called membrane insertion on a waveguide biosensor, and tested three serogroups of LPS. The membrane insertion technique allows for the hydrophobic association of LPS with a lipid bilayer, where the exposed O antigen can be targeted for specific detection. Samples of beef lysate were spiked with LPS to perform O antigen specific detection of LPS from E. coli O157. To validate assay performance, we evaluated the biophysical interactions of LPS with lipid bilayers both in- and outside of a flow cell using fluorescence microscopy and fluorescently doped lipids. Our results indicate that membrane insertion allows for the qualitative and reliable identification of amphiphilic LPS in complex samples like beef homogenates. In addition, we also demonstrated that LPS-induced hole formation does not occur under the conditions of the membrane insertion assays. Together, these findings describe for the first time the serogroup-specific detection of amphiphilic LPS in complex samples using a membrane insertion assay, and highlight the importance of LPS molecular conformations in detection architectures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A Frequency-Domain-Based Algorithm for Detecting Microseismicity Using Dense Surface Seismic Arrays

We propose a new frequency-domain-based algorithm for detecting small-magnitude seismic events using dense surface seismic arrays. Our proposed method takes advantage of the high energy carried by S waves, and approximate known source locations, which are used to rotate the horizontal components to obtain the maximum amplitude. By surrounding the known source area with surface geophones, we achieve a favorable geometry for locating the detected seismic events with the backprojection method. To test our new detection method, we used a dense circular array, consisting of 151 5 Hz three-component geophones, over a 5 km aperture that was in operation at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) in southcentral Utah. We apply the new detection method during a small-scale test injection phase at FORGE, and during an aftershock sequence of an Mw 4.1 earthquake located ~30 km north of the geophone array, within the Black Rock volcanic field. We are able to detect and locate microseismic events (Mw<0) during injections, despite the high level of anthropogenic activity, and several aftershocks that are missing from the regional catalog. By comparing our method with known algorithms that operate both in the time and frequency domain, we show that our proposed method performs better in the case of the FORGE injection monitoring, and equally well for the off-array aftershock sequence. Our new method has the potential to improve microseismic event detections even in extremely noisy environments, and the proposed location scheme serves as a direct discriminant between true and false detections.

Geochemistry & Geophysics↗
DOE OSTI2017

Magnetotelluric Detection Thresholds as a Function of Leakage Plume Depth, TDS and Volume

We conducted a synthetic magnetotelluric (MT) data analysis to establish a set of specific thresholds of plume depth, TDS concentration and volume for detection of brine and CO 2 leakage from legacy wells into shallow aquifers in support of Strategic Monitoring Subtask 4.1 of the US DOE National Risk Assessment Partnership (NRAP Phase II), which is to develop geophysical forward modeling tools. 900 synthetic MT data sets span 9 plume depths, 10 TDS concentrations and 10 plume volumes. The monitoring protocol consisted of 10 MT stations in a 2×5 grid laid out along the flow direction. We model the MT response in the audio frequency range of 1 Hz to 10 kHz with a 50 Ωm baseline resistivity and the maximum depth up to 2000 m. Scatter plots show the MT detection thresholds for a trio of plume depth, TDS concentration and volume. Plumes with a large volume and high TDS located at a shallow depth produce a strong MT signal. We demonstrate that the MT method with surface based sensors can detect a brine and CO 2 plume so long as the plume depth, TDS concentration and volume are above the thresholds. However, it is unlikely to detect a plume at a depth larger than 1000 m with the change of TDS concentration smaller than 10%. Simulated aquifer impact data based on the Kimberlina site provides a more realistic view of the leakage plume distribution than rectangular synthetic plumes in this sensitivity study, and it will be used to estimate MT responses over simulated brine and CO 2 plumes and to evaluate the leakage detectability. Integration of the simulated aquifer impact data and the MT method into the NRAP DREAM tool may provide an optimized MT survey configuration for MT data collection. This study presents a viable approach for sensitivity study of geophysical monitoring methods for leakage detection. The results come in handy for rapid assessment of leakage detectability.

58 GEOSCIENCES↗