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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Software for High-Resolution Flood Mapping With Sentinel-1 and Sentinel-2 via Misalignment-Robust Cross-Sensor Learning and Generative Despeckling

SF-26-078 This software provides a high-level workflow for satellite-based flood and surface-water mapping using Sentinel-1 SAR and Sentinel-2 multispectral imagery. It supports preparation of remote-sensing data, training and evaluation of deep-learning models, and generation of high-resolution water extent predictions, including methods to improve robustness to SAR speckle noise and cross-sensor image misalignment.

Feinstein, Jeremy [Argonne National Laboratory (AN↗
DOE OSTI2019

Indocyanine Green Fluorescence Imaging with Lymphoscintigraphy for Sentinel Node Biopsy in Melanoma: Increasing the Sentinel Lymph Node-Positive Rate

Introduction: The goal of this study was to analyze patients who underwent a sentinel lymph node biopsy (SLNB) in melanoma with the combination of radioisotope lymphoscintigraphy and indocyanine green (ICG) fluorescence imaging to compare our true positive (TP) rate, a means to perform immediate analysis of the SLNB, with that of the literature. Methods: Consecutive cutaneous melanoma patients who underwent SLNB with lymphoscintigraphy and ICG-based fluorescence imaging by the senior author (BG) from 2012 to 2018 were prospectively enrolled. The average expected SLN-positive rate per T stage was calculated based on three studies and compared with our SLN-positive rate. Results: Overall, 574 consecutive patients were analyzed. Average Breslow thickness was 1.9 mm. A total of 1754 sentinel nodes were sampled; 1497 were identified by gamma probe signaling and ICG, 241 were identified by gamma probe signaling only, and 16 were identified by ICG only. There were 123 (21.4%) patients with at least one positive SLN; 113 (91.9%) had at least one positive node identified with both gamma probe signaling and ICG, 8 (6.5%) had positive node(s) identified with gamma probe signaling only, and 2 (1.6%) had positive node(s) identified with ICG only. There was an overall 21.4% SLN-positive rate, with 8% T1, 18.5% T2, 41.1% T3, and 52.4% T4, which is higher than the predicted rates for each stage. Conclusions: With the largest cohort of patients reported who underwent a melanoma SLNB with lymphoscintigraphy and ICG, we demonstrated that this technique results in higher SLN-positive rates than predicted. Patients are being followed but, given the TP data, knowledge of our results may foster the use of this modality to improve staging and treatment options.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Regional Recurrence Risk Following a Negative Sentinel Node Procedure Does Not Approximate the False-Negative Rate of the Sentinel Node Procedure in Breast Cancer Patients Not Receiving Radiotherapy or Systemic Treatment

Background: Although the false-negative rate of the sentinel lymph node biopsy (SLNB) in breast cancer patients is 5–7%, reported regional recurrence (RR) rates after negative SLNB are much lower. Adjuvant treatment modalities probably contribute to this discrepancy. This study assessed the 5-year RR risk after a negative SLNB in the subset of patients who underwent breast amputation without radiotherapy or any adjuvant treatment. Methods: All patients operated for primary unilateral invasive breast cancer between 2005 and 2008 were identified in the Netherlands Cancer Registry. Patients with a negative SLNB who underwent breast amputation and who were not treated with axillary lymph node dissection, radiotherapy, or any adjuvant systemic treatment were selected. The cumulative 5-year RR rate was estimated by Kaplan–Meier analysis. Results: A total of 13,452 patients were surgically treated for primary breast cancer and had a negative SLNB, and 2012 patients fulfilled the selection criteria. Thirty-eight RRs occurred during follow-up. Multifocal disease was associated with a higher risk of developing RR (P = 0.04). The median time to RR was 27 months and was significantly shorter in patients with estrogen receptor-negative (ER−) breast cancer (9.5 months; P = 0.003). The 5-year RR rate was 2.4% in the study population compared with 1.1% in the remainder of 11,440 SLNB-negative patients (P = 0.0002). Conclusions: Excluding the effect of radiotherapy and systemic treatment resulted in a twofold 5-year RR risk in breast cancer patients with a tumor-free SLNB. This 5-year RR rate was still much lower than the reported false-negative rate of the SLNB procedure.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Overall and cause‐specific mortality in the Sentinel system: A power analysis

Abstract Purpose Mortality data within the Sentinel Death Tables remain generally uncharacterized. Assessment of mortality data within Sentinel will help inform its utility for medical product safety studies. Methods To determine if Sentinel contains sufficient all‐cause and cause‐specific mortality events to power postmarketing safety studies. We calculated crude rates of all‐cause mortality and suicide and proportional mortality from suicide from 2004 to 2012 in seven Sentinel data partners. Results were stratified by data partner, sex, age group, and calendar year and compared with national estimates from Centers for Disease Control and Prevention Wide‐ranging ONline Data for Epidemiologic Research. We performed sample size estimations for all‐cause mortality and 10 leading causes of death. Results We observed 479 694 deaths, including 5811 suicides, during 68 million person‐years of follow‐up. Pooled mean death and suicide rates in the data partners were 710 and 8.6 per 100 000 person‐years, respectively (vs 810 and 11.8 nationally). The mean proportional mortality from suicide among the data partners was 1.2%, compared with 1.5% nationally. National trends of decreasing overall mortality and increasing proportional mortality for suicide were reflected within Sentinel. We estimated that detecting hazard ratios of 1.25 and 3 would require 16 442 and 460 exposed patients, respectively, for overall mortality, and 1.3 million and 37 411, respectively, for suicide. Conclusions This was the first study to investigate mortality data in the Sentinel death tables. We found that all‐cause mortality appeared well powered for use as a safety outcome and cause‐specific mortality outcomes may be adequately powered in certain circumstances. Further investigation into the quality of the Sentinel death data is needed.

Swain, Richard S.↗
DOE OSTI2026

Forest aboveground biomass estimation through integration of sentinel-2 and PALSAR-2 time series: assessing models trained on GEDI and field inventory benchmarks

Accurate and spatially explicit forest Aboveground Biomass (AGB) mapping through remote sensing is critical for quantifying terrestrial carbon stocks and informing effective forest management strategies. However, AGB estimation in dense forests with complex terrain remains challenging due to satellite sensor signal saturation problem (saturation issue occurs in high biomass forests), structural complexity, and limited ground truth for calibration. This study presents a novel framework that integrates multi-temporal Sentinel-2 optical imagery, ALOS PALSAR-2 Synthetic Aperture Radar (SAR) data, and topographic variables with explainable Machine Learning to map AGB across mountainous forests within subtropical and temperate oceanic climate zones of Mexico. We evaluate the effects of temporal granularity and sensor synergy by comparing multiple temporal inputs and sensor configurations (Sentinel-2, PALSAR-2, and their fusion), and assess model performance using two reference datasets: NASA GEDI LiDAR-derived biomass and Mexico’s National Forest and Soil Inventory (INFyS). Our results showed that models trained on INFyS consistently outperformed those trained on GEDI, highlighting limitations in GEDI’s reliability in biomass estimates within this study region. Furthermore, the integration of Sentinel-2 and PALSAR-2 provided improved predictions compared to single-sensor models, particularly when combined with temporally explicit yearly statistics. The best-performing model, which was trained on INFyS data, and considered both Sentinel-2 and PALSAR-2 yearly statistics, as well as topographic variables, achieved an R2 of 0.64, RMSE of 51.10 Mg/ha, and relative RMSE (rRMSE) of 58.69%. Explainable ML analysis identified Sentinel-2 spectral indices and topographic features as key predictors, while PALSAR-2 metrics provided complementary information, partially mitigating saturation effects in high-biomass areas. Specifically, integrating both sensors substantially improved AGB estimation in high biomass forest (≥200 Mg/ha), yielding 98% gains over optical-only model, with resulting estimates exceeding GEDI L4B by 29% and ESA-CCI-BIOMASS by 174%. Terrain-stratified analysis indicated close agreement with GEDI in low-slope areas, with increasing divergence as slope steepness increased, while estimates remained consistently higher than ESA-CCI-BIOMASS across all slope classes. The proposed approach advances multi-sensor fusion and temporal feature engineering for AGB mapping using open-access satellite datasets, providing a scalable and reproducible framework for annual biomass monitoring in topographically complex mountainous forests. The resulting 25 m resolution biomass product has the potential to provide spatially detailed information for forest monitoring and may support applications in carbon accounting and forest management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

CalTestBed - Delphire - Testing and Evaluation of Delphire Sentinel System (CRADA Final Report)

The Delphire Sentinel is a modular fire detection and communications system operating as a mobile field unit, with low voltage DC power supplied by onboard photovoltaics (PV) and batteries. The Sentinel addresses several aspects of fire detection, communications and data analysis. The Sentinel's mobility enables it to be rapidly deployed and operate independently of existing power and communications networks. The duration of independent operation depends critically on the energy consumption of the systems and performance of the onboard PV and battery. The purpose of this testing is to ascertain the power draw and energy consumption of the Delphire Sentinel prototype system under several operational states, including various data transfer packet sizes, transmission time and frequencies, and communication pathways (Wi-Fi, cellular, satellite) expected to be encountered in field deployments. It will also include procedures to test the ability of the Sentinel to operate for extended periods without loss of functionality. Based on results from energy and power measurements, and anticipated duty cycles in field deployments, we will model annual system autonomy (e.g. loss of load probability) for off-grid operation in representative locations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Sentinel-1 Input Data for PSInSAR Analysis

Files used to perform the Persistent Scatterer InSAR analysis with SARPROZ. The data is sourced from ESAs Sentinel-1 project and covers Brady Hot Springs and Desert Peak geothermal areas. The original titles are included for the Sentinel-1 data. The naming guide is included as a link in this submission. The data contains SAR (Radar) data from the Sentinel 1A satellite between July 2017 and December 2019. The data is necessary to replicate our results, and can be used for further PSInSAR, DInSAR and other modern interferometric analyses to determine line of sight, vertical and, possibly, East-West horizontal displacement. These displacement analysis show the soil deformation in time (including average displacement velocity), which can be used to indicate subsoil phenomena: temperature changes, subsidence, uplift, and inform other analyses like seismicity and porosity.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Integrating very-high-resolution imagery, Sentinel-2 time-series data, and machine learning to map shrub fractional abundance across arid and semi-arid ecosystems in China

Shrub fractional abundance (SFA), the proportion of shrub cover per unit area, serves as a critical indicator of environmental aridity and ecosystem health in arid and semi-arid regions, particularly across the Mongolian steppe. However, large-scale SFA mapping in Mongolian steppe ecosystems remains challenging due to the small crown size of shrubs, their sparse distribution, and spectral overlap with coexisting low vegetation (e.g., grasses and herbs), which hinders accurate detection using coarser-resolution satellite data or traditional field surveys. To address these challenges, we developed a two-step approach that integrates very-high-resolution (VHR) imagery, time-series Sentinel-2 data, and deep learning techniques. First, we generated high-accuracy benchmark maps of individual shrub crowns from 0.5 m VHR imagery by combining manual segmentation with a hybrid deep learning framework (Dino V2 and convolutional neural networks). Second, we used these shrub crown maps as training data to build an XGBoost model for predicting SFA from 20 m Sentinel-2 time-series data, leveraging phenological information to improve estimation. We validated our approach across 70 sites (1km 2 each) in the Inner Mongolia Autonomous Region, which is representative of Mongolian steppe ecosystems. From VHR imagery, we mapped 1.31 million shrub crowns with an accuracy of R 2 = 0.92. Scaling up with Sentinel-2 data yielded regional SFA maps with an R 2 = 0.60. Further SHAP (SHapley Additive exPlanations) analysis on the developed XGBoost model revealed that phenological metrics (particularly observations in early-May, mid-July, and late-September), which distinguish shrub phenology from that of other land cover types (e.g., grasses and bare soil), were the most influential predictors of SFA. Finally, our regional SFA maps uncovered unimodal relationships between shrub distribution and climate variables, peaking at mean annual minimum temperatures near 0 °C and annual precipitation around 200 mm. Collectively, these findings demonstrate how the integration of multi-source remote sensing and machine learning can overcome historical limitations in SFA mapping, enabling accurate, spatially continuous assessments across vast Inner-Mongolian steppe ecosystems. Our framework has the potential to be applied to other steppe ecosystems and dryland ecosystems across the Mongolian steppe and beyond, offering a foundation for improved monitoring and ecological impact assessments in the face of global climate changes.

Arid and semi-arid landscapes↗
DOE OSTI2020

A compact filtered x-ray diode array spectrometer for the National Ignition Facility: SENTINEL

Sentinel is a 16-channel, filtered x-ray diode array spectrometer that has been developed to measure ~1 keV–20 keV x-ray emission generated by the National Ignition Facility (NIF) laser. Unlike the large, fixed-port versions of this diagnostic that currently exist on the NIF (known as Dante), Sentinel is a Diagnostic Instrument Manipulator compatible such that it can be fielded along the polar or equatorial lines-of-sight—an essential new capability for characterizing the often anisotropic x-ray emission from laser-driven sources. Here, we present the diagnostic design along with preliminary diode calibrations and performance results. The novel, small-form-factor x-ray diode design allows for ≳5×–25× increased channel areal density over that of Dante, simultaneously enabling improved diagnostic robustness and fidelity of spectral reconstructions. While the Sentinel diagnostic is anticipated to improve line-of-sight spectral characterization of x-ray sources for a wide variety of programs on the NIF, the compact and portable design is also attractive to small- and mid-scale facilities with limited diagnostic real estate.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Low Risk of Development of a Regional Recurrence After an Unsuccessful Repeat Sentinel Lymph Node Biopsy in Patients with Ipsilateral Breast Tumor Recurrence

Background: Unlike sentinel lymph node biopsy (SLNB) in the primary setting, the repeat SLNB (rSLNB) in patients with ipsilateral breast tumor recurrence (IBTR) is challenging, because it is difficult to visualize and/or harvest a sentinel lymph node in every patient. Regional treatments options and safety in terms of regional disease control after such an unsuccessful rSLNB remain unclear. This study assesses factors associated with the performance of axillary lymph node dissection (ALND) after unsuccessful rSLNB and evaluates the occurrence of regional recurrences. Methods: Data were obtained from the Sentinel Node and Recurrent Breast Cancer (SNARB) study. In 239 patients, the rSLNB was unsuccessful, of whom 60 patients underwent ipsilateral ALND. Results: A shorter time interval between primary treatment and IBTR, and a primary negative SLNB were significantly associated with a higher probability to be treated with ALND after unsuccessful rSLNB (P < 0.001). The 5-year regional-recurrence rate was 0.0% in the ALND group compared with 3.7% in the group treated without ALND (P = 0.113). Of the 179 patients treated without ALND, after a median follow-up of 5.1 years (range 0.3–13.2), 7 (3.9%) developed a regional recurrence as first event after unsuccessful rSLNB. None of the seven recurrences occurred in the ipsilateral axilla. Univariable analysis showed no factors associated with regional recurrence as first event after unsuccessful rSLNB (P > 0.05). Conclusions: The present study demonstrates that the risk of regional recurrence in patients with an IBTR and an unsuccessful rSLNB is negligible, irrespective of the use of ALND. This suggests that there is no need for additional treatment of the axilla after an unsuccessful rSLNB.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

SentimagIC: A Non-inferiority Trial Comparing Superparamagnetic Iron Oxide Versus Technetium-99m and Blue Dye in the Detection of Axillary Sentinel Nodes in Patients with Early-Stage Breast Cancer

Background: Sentinel lymph node biopsy (SLNB) is a highly accurate method for staging the axilla in early breast cancer. Superparamagnetic iron oxide mapping agents have been explored to overcome the disadvantages of the standard SLNB technique, which uses a radioisotope tracer with or without blue dye. One such agent, Sienna+, was shown to be non-inferior to the standard technique for SLNB in a number of studies. The SentimagIC trial was designed to establish the non-inferiority of a new formulation of this magnetic tracer, Magtrace (formerly SiennaXP). Methods: Patients with clinically node-negative early-stage breast cancer were recruited from six centers in the US. Patients received radioisotope and isosulfan blue dye injections, followed by an intraoperative injection of magnetic tracer, prior to SLNB. The sentinel node identification rate was compared between the magnetic and standard techniques to evaluate non-inferiority and concordance. Results: Data were collected for 146 procedures in 146 patients. The per patient detection rate was 99.3% (145/146) when using the magnetic tracer and 98.6% (144/146) when using the standard technique, while the nodal detection rate was 94.3% (348/369 nodes) when using the magnetic tracer and 93.5% (345/369) when using the standard technique (difference 0.8%, 95% binomial confidence interval lower bound − 2.1%). Of the 22 patients with positive sentinel lymph nodes (SLNs), 21 (95.4%) were detected by both the magnetic tracer and the standard technique. All malignant nodes detected by standard technique were also identified by the magnetic technique. Conclusion: The magnetic technique is non-inferior to the standard technique of radioisotope and blue dye for axillary SLN detection in early-stage breast cancer. The magnetic technique is therefore a viable alternative.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Evaluation of camera-based freehand SPECT in preoperative sentinel lymph node mapping for melanoma patients

Assessment of lymphatic status via sentinel lymph node (SLN) biopsy is an integral and crucial part of melanoma surgical oncology. The most common technique for sentinel node mapping is preoperative planar scintigraphy of an injected gamma-emitting lymphatic tracer followed by intraoperative node localization using a non-imaging gamma probe with auditory feedback. In recent years, intraoperative visualization of SLNs in 3D has become possible by coupling the probe to an external system capable of tracking its location and orientation as it is read out, thereby enabling computation of the 3D distribution of the tracer (freehand SPECT). In this project, the non-imaging probe of the fhSPECT system was replaced by a unique handheld gamma camera containing an array of sodium iodide crystals optically coupled to an array of silicon photomultipliers (SiPMs). A feasibility study was performed in which preoperative SLN mapping was performed using camera fhSPECT and the number of detected nodes was compared to that visualized by lymphoscintigraphy, probe fhSPECT, and to the number ultimately excised under non-imaging probe guidance. Among five subjects, SLNs were detected in nine lymphatic basins, with one to five SLNs detected per basin. A basin-by-basin comparison showed that the number of SLNs detected using camera fhSPECT exceeded that using lymphoscintigraphy and probe fhSPECT in seven of nine basins and five of five basins, respectively. (Probe fhSPECT scans were not performed for four basins.) It exceeded the number excised under non-imaging probe guidance for seven of nine basins and equaled the number excised for the other two basins. Freehand SPECT using a prototype SiPM-based gamma camera demonstrates high sensitivity for detection of SLNs in a preoperative setting. Camera fhSPECT is a potential means for efficiently obtaining real-time 3D activity distribution maps in applications such as image-guided percutaneous biopsy, and surgical SLN biopsy or radioguided tumor excision.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Envisat Track 349 and Sentinel-1A Track 64 Interferometric Synthetic Aperture Radar Data of Coso Geothermal Field, California, USA, 2004-2016

This submission contains tarred pair directories for interferometric synthetic aperture radar (InSAR) data covering Coso Geothermal Field in California, USA. Explanation of pair subdirectories: Pairs are formed using the InSAR processing software GMT5SAR (Sandwell et al., 2011). Pair subdirectories are named by starting and ending epochs in YYYYMMDD_YYYYMMDD format. Each tarred pair directory contains GRD files for phase data (radians), unwrapped range change (drhomaskd, in m), and unwrapped range change rate (drange, in m/yr). The data are given in both latitude/longitude and Universal Transverse Mercator (Zone 11N). Raw Synthetic Aperture Radar (SAR) data from the Envisat satellite mission operated by the European Space Agency (ESA) are copyrighted by ESA and were provided through the WInSAR consortium at the UNAVCO facility. Raw Synthetic Aperture Radar (SAR) data from the Sentinel-1A satellite mission operated by ESA were available free of charge through the Distributed Active Archive Center (DAAC) at the Alaska Satellite Facility (ASF) and through the Sentinels Scientific Data Hub. References: Farr, T.G.; Rosen, P.A.; Caro, E.; Crippen, R.; Duren, R.; Hensley, S.; Kobrick, M.; Paller, M.; Rodriguez, E.; Roth, L.; Seal, D.; Shaffer, S.; Shimada, J.; Umland, J.; Werner, M.; Oskin, M.; Burbank, D.; Alsdorf, D. The Shuttle Radar Topography Mission. Reviews of Geophysics 2007, 45, RG2004. doi:10.1029/2005RG000183. Sandwell, D.; Mellors, R.; Tong, X.; Wei, M.; Wessel, P. Open radar interferometry software for mapping surface deformation. Eos, Transactions American Geophysical Union 2011, 92, 234?234. http://dx.doi.org/10.1029/2011EO280002. doi:10.1029/2011EO280002.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Performance of Landsat-8 and Sentinel-2 surface reflectance products for river remote sensing retrievals of chlorophyll-a and turbidity

Rivers and other freshwater systems play a crucial role in ecosystems, industry, transportation and agriculture. Despite the > 40 years of inland water observations made possible by optical remote sensing, a standardized reflectance product for inland waters is yet forthcoming. The aim of this work is to compare the standard USGS land surface reflectance product to two Landsat-8 and Sentinel-2 aquatic remote sensing reflectance products over the Amazon, Columbia and Mississippi rivers. Landsat-8 reflectance products from all three routines are then evaluated for their comparative performance in retrieving chlorophyll-a and turbidity in reference to ship- borne, underway in situ validation measurements. The land surface product shows the best agreement (4% Mean Absolute Percent Difference) with field measurements of radiometry collected on the Amazon River and gen- erates 36% higher reflectance values in the visible bands compared to aquatic methods (ACOLITE and SeaDAS) with larger differences between land and aquatic products observed in Sentinel-2 (0.01sr-1) compared to Landsat-8 (0.001 sr-1). Choice of atmospheric correction routine can bias Landsat-8 retrievals of chlorophyll-a and turbidity by as much as 59% and 35% respectively. Using a more restrictive time window for matching in situ and satellite imagery can reduce differences by 5–31% depending on correction technique. This work highlights the challenges of satellite retrievals over rivers and underscores the need for future optical and biogeochemical research aimed at improving our understanding of the absorbing and scattering properties of river water and their relationships to remote sensing reflectance.

Amazon↗
DOE OSTI2024

Sentinel

Network intrusion detection systems (NIDS) are commonplace in network security but they frequently employ algorithms that are computational demanding requiring hardware and software with significant power requirements. Two examples of such resource-intensive algorithms used for network security are regular expression matching and broader signature pattern matching which are commonly used in deep packet inspection (DPI). Network security algorithms that have large power requirements may be a challenge for low-power internet-of-things (IoT) environments, which generally lack the power resources to implement complex security measures like computationally expensive DPI at the edge. Furthermore, IoT environments incorporating 5G standalone networks have network latency constraints beyond just power that make DPI at the edge even more difficult. Programmable logic is ideally suited for machine learning inference for DPI because of its deep instruction level parallelism and single-cycle memory access. Machine learning approaches for DPI have been explored before using the programmable logic of field programmable gate arrays (FPGA) as a potential solution for NIDS approaches that would be power-suitable for IoT. However, those previous programmable logic NIDS approaches utilize either a supervised or unsupervised learning model. Sentinel utilizes the ensemble of these two machine learning approaches known as a semi-supervised approach which has shown promise in NIDS implementations. Sentinel provides a programmable logic implementation of a semi-supervised approach for DPI which operates at much lower power and latency than a GPU implementation with negligible loss of accuracy due to quantization through a logistic regressor.

Anderson, MatthewW [Idaho National Laboratory (INL↗
DOE OSTI2019

Internal Mammary Chain Sentinel Nodes in Early-Stage Breast Cancer Patients: Toward Selective Removal

Background: Removal of internal mammary chain sentinel nodes (IMCSNs) affects prognosis and treatment of breast cancer, and internal mammary chain radiotherapy (IMCRT) can improve survival for selected patients. This study aimed to determine the effect of IMCSN biopsy on recurrence-free survival (RFS) and overall survival (OS) and to identify predictive factors for IMCSN and distant metastasis. Methods: Patients with IMCSNs were selected from a prospective database for the period 1999–2007. Lymphoscintigraphy was performed after intratumoral technetium-99 m injection, and all sentinel nodes were removed. Both RFS and OS were calculated for subgroups with tumor-positive, tumor-negative, or non-removed IMCSNs. Predictive factors were identified for tumor-positive IMCSNs and distant metastasis by regression analysis. Results: For 287 (85%) of 336 patients, IMCSN biopsy was performed, and metastasis was detected in 38 patients (13%). The patients with tumor-positive IMCSNs had poorer OS than the patients with no IMCSN metastasis or non-removed IMCSNs (p = 0.002). These patients also had worse RFS due to distant metastasis (p = 0.002). Axillary metastasis was predictive for tumor-positive IMCSNs (positive predictive value, 38.5%). The predictive factors for distant metastasis were tumor-positive IMCSNs (hazard ratio [HR], 2.5), non-removed IMCSNs (HR, 2.3), tumor diameter greater than 1.5 cm (HR, 3.5), and age older than 65 years (HR, 3.1; reference, < 50 years). Conclusions: Patients with IMCSNs have worse survival due to distant metastasis. The clinically relevant predictive factor for distant metastasis is tumor larger than 1.5 cm. According to the authors’ current protocol, IMCSN biopsy is performed for patients younger than 70 years who have a tumor larger than 1.5 cm, with the cardiotoxicity of the adjuvant IMCRT weighed against the survival benefit.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Validation of the Sentinel-5 Precursor TROPOMI cloud data with Cloudnet, Aura OMI O 2 –O 2 , MODIS, and Suomi-NPP VIIRS

Accurate knowledge of cloud properties is essential to the measurement of atmospheric composition from space. In this work we assess the quality of the cloud data from three Copernicus Sentinel-5 Precursor (S5P) TROPOMI cloud products: (i) S5P OCRA/ROCINN_CAL (Optical Cloud Recognition Algorithm/Retrieval of Cloud Information using Neural Networks;Clouds-As-Layers), (ii) S5P OCRA/ROCINN_CRB (Clouds-as-Reflecting Boundaries), and (iii) S5P FRESCO-S (Fast Retrieval Scheme for Clouds from Oxygen absorption bands – Sentinel). Target properties of this work are cloud-top height and cloud optical thickness (OCRA/ROCINN_CAL), cloud height (OCRA/ROCINN_CRB and FRESCO-S), and radiometric cloud fraction (all three algorithms). The analysis combines (i) the examination of cloud maps for artificial geographical patterns, (ii) the comparison to other satellite cloud data (MODIS, NPP-VIIRS, and OMI O2–O2), and (iii) ground-based validation with respect to correlative observations (30 April 2018 to 27 February 2020) from the Cloudnet network of ceilometers, lidars, and radars. Zonal mean latitudinal variation of S5P cloud properties is similar to that of other satellite data. S5P OCRA/ROCINN_CAL agrees well with NPP VIIRS cloud-top height and cloud optical thickness and with Cloudnet cloud-top height, especially for the low (mostly liquid) clouds. For the high clouds, S5P OCRA/ROCINN_CAL cloud-top height is below the cloud-top height of VIIRS and of Cloudnet, while its cloud optical thickness is higher than that of VIIRS. S5P OCRA/ROCINN_CRB and S5P FRESCO cloud height are well below the Cloudnet cloud mean height for the low clouds but match on average better with the Cloudnet cloud mean height for the higher clouds. As opposed to S5P OCRA/ROCINN_CRB and S5P FRESCO, S5P OCRA/ROCINN_CAL is well able to match the lowest CTH mode of the Cloudnet observations. Peculiar geographical patterns are identified in the cloud products and will be mitigated in future releases of the cloud data products.

54 ENVIRONMENTAL SCIENCES↗