Absolute Percentage Difference Research Articles

First-in-Humans Brain PET Imaging of the GluN2B-Containing N-methyl-d-aspartate Receptor with (R)-11C-Me-NB1.

The N-methyl-d-aspartate receptor (NMDAR) plays a crucial role in neurodegenerative diseases such as Alzheimer disease and in the treatment of major depression by fast-acting antidepressants such as ketamine. Given their broad implications, GluN2B-containing NMDARs have been of interest as diagnostic and therapeutic targets. Recently, (R)-11C-Me-NB1 was investigated preclinically and shown to be a promising radioligand for imaging GluN2B subunits. Here, we report on the performance characteristics of this radioligand in a first-in-humans PET study. Methods: Six healthy male subjects were scanned twice on a fully integrated PET/MR scanner with (R)-11C-Me-NB1 for 120 min. Brain uptake and tracer distribution over time were investigated by SUVs. Test-retest reliability was assessed with the absolute percentage difference and the coefficient of variation. Exploratory total volumes of distribution (VT) were computed using an arterial input function and the Logan plot as well as a constrained 2-tissue-compartment model with the ratio of rate constants between plasma and tissue compartments (K1/k2) coupled (2TCM). SUV was correlated with VT to investigate its potential as a surrogate marker of GluN2B expression. Results: High and heterogeneous radioligand uptake was observed across the entire gray matter with reversible kinetics within the scan time. SUV absolute percentage difference ranged from 6.9% to 8.5% and coefficient of variation from 4.9% to 6.0%, indicating a high test-retest reliability. A moderate correlation was found between SUV averaged from 70 to 90 min and VT using Logan plot (Spearman ρ = 0.44). Correlation between VT Logan and 2TCM was r = 0.76. Conclusion: The radioligand (R)-11C-Me-NB1 was highly effective in mapping GluN2B-enriched NMDARs in the human brain. With a heterogeneous uptake and a high test-retest reliability, this radioligand offers promise to deepen our understanding of the GluN2B-containing NMDAR in the pathophysiology and treatment of neuropsychiatric disease such as Alzheimer disease and major depression. Additionally, it could help in the selection of appropriate doses of GluN2B-targeting drugs.

A combined semi-analytical algorithm for retrieving total suspended sediment concentration from multiple missions: a case study of the China Eastern Coastal Zone

ABSTRACT A new semi-analytical algorithm that retrieves the total concentration of suspended matter (TSM) was derived from the China Eastern Coastal Zone using multiple ocean colour instruments including the Visible Infrared Imaging Radiometer (VIIRS), the Moderate-resolution Imaging Spectroradiometer (MODIS), and the Medium Resolution Spectral Imager II (MERSI II). The algorithm in one model derives TSM concentration (CTSM) from satellite inherent optical properties products for clear and moderately turbid water. For turbid waters, a second model with a four-band approach was used. The two model algorithms were combined into one algorithm using a linking weighted function to generate a smooth CTSM for clear and turbid water and for water with intermediate transparency. Compared to eight existing algorithms, our new algorithm performed better with a wide dynamic range for the CTSM retrievals. The mean absolute percent difference was 28.22% for the CECZ data and the CTSM varied from 0.5 mg l−1 to 2435.4 mg l−1. New algorithm decreased the MAPD by >11% for the CTSM retrievals compared to the eight existing algorithms. Furthermore, when new algorithm was tested with a synthetic data set that had been contaminated with residual error, it exhibited more residual error tolerance than the other algorithms when retrieving CTSM, which agreed well with the results provided by a multi-mission consistency analysis. These results indicate that new algorithm could provide accurate and consistent multi-mission CTSM from turbid coastal water with a widely varying range of CTSM.

Cyanobacterial pigment concentrations in inland waters: Novel semi-analytical algorithms for multi- and hyperspectral remote sensing data

Cyanobacteria are notorious for producing harmful algal blooms that present an ever-increasing serious threat to aquatic ecosystems worldwide, impacting the quality of drinking water and disrupting the recreational use of many water bodies. Remote sensing techniques for the detection and quantification of cyanobacterial blooms are required to monitor their initiation and spatiotemporal variability. In this study, we developed a novel semi-analytical approach to estimate the concentration of cyanobacteria-specific pigment phycocyanin (PC) and common phytoplankton pigment chlorophyll a (Chl a) from hyperspectral remote sensing data. The PC algorithm was derived from absorbance-concentration relationship, and the Chl a algorithm was devised based on a conceptual three-band structure model. The developed algorithms were applied to satellite imageries obtained by the Hyperspectral Imager for the Coastal Ocean (HICO™) sensor and tested in Lake Kinneret (Israel) during strong cyanobacterium Microcystis sp. bloom and out-of-bloom times. The sensitivity of the algorithms to errors was evaluated. The Chl a and PC concentrations were estimated with a mean absolute percentage difference (MAPD) of 16% and 28%, respectively. Sensitivity analysis shows that the influences of backscattering and other water constituents do not affect the estimation accuracy of PC (~2% MAPD). The reliable PC/Chl a ratios can be obtained at PC concentrations above 10 mg m−3. The computed PC/Chl a ratio depicts the contribution of cyanobacteria to the total phytoplankton biomass and permits investigating the role of ambient factors in the formation of a complex planktonic community. The novel algorithms have extensive practical applicability and should be suitable for the quantification of PC and Chl a in aquatic ecosystems using hyperspectral remote sensing data as well as data from future multispectral remote sensing satellites, if the respective bands are featured in the sensor.

Do we need different predictive equations for the acute and late phases of critical illness? A prospective observational study with repeated indirect calorimetry measurements.

BackgroundPredictive equations (PEs) for estimating resting energy expenditure (REE) that have been developed from acute phase data may not be applicable in the late phase and vice versa. This study aimed to assess whether separate PEs are needed for acute and late phases of critical illness and to develop and validate PE(s) based on the results of this assessment.MethodsUsing indirect calorimetry, REE was measured at acute (≤5 days; n = 294) and late (≥6 days; n = 180) phases of intensive care unit admission. PEs were developed by multiple linear regression. A multi-fold cross-validation approach was used to validate the PEs. The best PEs were selected based on the highest coefficient of determination (R2), the lowest root mean square error (RMSE) and the lowest standard error of estimate (SEE). Two PEs developed from paired 168-patient data were compared with measured REE using mean absolute percentage difference.ResultsMean absolute percentage difference between predicted and measured REE was <20%, which is not clinically significant. Thus, a single PE was developed and validated from data of the larger sample size measured in the acute phase. The best PE for REE (kcal/day) was 891.6(Height) + 9.0(Weight) + 39.7(Minute Ventilation)−5.6(Age) – 354, with R2 = 0.442, RMSE = 348.3, SEE = 325.6 and mean absolute percentage difference with measured REE was: 15.1 ± 14.2% [acute], 15.0 ± 13.1% [late].ConclusionsSeparate PEs for acute and late phases may not be necessary. Thus, we have developed and validated a PE from acute phase data and demonstrated that it can provide optimal estimates of REE for patients in both acute and late phases.Trial registrationClinicalTrials.gov NCT03319329.

Atmospheric correction over coastal waters with aerosol properties constrained by multi-pixel observations

We propose an innovative multi-pixel atmospheric correction approach (MPACA) to process high-spatial-resolution satellite measurements over coastal waters based on a revised POLYMER model. MPACA assumes the aerosol type to be uniform within a relatively small region, while the aerosol load and water properties are allowed to vary. Landsat-8 OLI images over six coastal locations with various turbidities were utilized to evaluate the performance of MPACA. The retrieved remote sensing reflectance (Rrs(λ)) by MPACA is validated with in situ matchups obtained from two sources: ship-based field campaigns and the AERONET-OC networks. It is found that, at each of OLI's four visible bands, MPACA provided accurate Rrs(λ) products over such coastal environments, with the Root Mean Square Difference (RMSD) and Mean Absolute Percentage Difference (MAPD) less than 0.0006 sr−1 and 16.2%, respectively. In contrast, the Rrs(λ) values retrieved with NASA's SeaDAS (v7.5), where each pixel was treated independently, showed RMSD and MAPD as ~0.0018 sr−1 and ~38.8%, respectively. Acolite-DSF, which assumed some spatial dependency, obtained MAPD almost two times that of SeaDAS for each visible band. Further, it appears that Acolite-EXP did not perform well for this evaluation dataset, where RMSD is ~0.0062 sr−1 and MAPD is ~228.2%. These results suggest that MPACA is a promising scheme for atmospheric correction in coastal waters, especially for measurements from multi-band satellites that have a high spatial resolution along with at least two bands in the NIR or SWIR domain.

Iterative near-infrared atmospheric correction scheme for global coastal waters

Atmospheric correction (AC) is a key step in ocean color remote sensing for obtaining oceanic and coastal water ecosystem products. However, traditional NIR-based AC scheme (ACNIR) often fails in turbid coastal waters dominated by high suspended particulate matter (SPM). SWIR-based AC is valid for turbid waters, but it cannot be applied to some satellite sensors (e.g., Sea-viewing Wide Field-of-view Sensor (SeaWiFS), MEdium Resolution Imaging Spectrometer (MERIS), and future small satellite sensors) that have no SWIR bands. To obtain reliable data of turbid coastal waters by these sensors without SWIR bands, an improved ACNIR (ACNIR-PRO) scheme is proposed herein based on the frame of traditional ACNIR (ACNIR-STA). The synthesized and in situ datasets are analyzed to extend bio-optical models of absorption and backscattering coefficients in ACNIR-STA to highly turbid waters. ACNIR-PRO utilizes concentrations of both chlorophyll-a ([Chla]) and SPM ([SPM]) to estimate water-leaving contributions at the NIR bands. Similar to NIR-SWIR AC, ACNIR-PRO can obtain the information of global coastal waters with remote sensing reflectance at 862 nm (Rrs(862)) up to 0.025∼0.03sr−1. Rrs of ACNIR-PRO is also validated by AERONET-OC datasets (mean absolute percent difference (MAPD) of Rrs(551) is approximately 16%) for various coastal waters including high colored dissolved organic matter. Further, the magnitude and spatial patterns of [SPM] and [Chla] derived from the Rrs products after performing ACNIR-PRO are significantly better than those from ACNIR-STA, especially for turbid coastal waters.

Global Estimation of Suspended Particulate Matter From Satellite Ocean Color Imagery.

The suspended particulate matter (SPM) concentration (unit: mg l−1) in surface waters is an essential measure of water quality and clarity. Satellite remote sensing provides a powerful tool to derive the SPM with synoptic and repeat coverage. In this study, we developed a new global SPM algorithm utilizing the remote sensing reflectance (R rs (λ)) at near‐infrared (NIR), red, green, and blue bands (NIR‐RGB) as input. The evaluations showed that the NIR‐RGB algorithm could predict SPM with the median absolute percentage difference of ∼35%–39% over a wide range from ∼0.01 to >2,000 mg l−1. The uncertainty is smaller (29%–37%) for turbid waters where R rs (671) ≥ 0.0012 sr−1 and slightly higher (41%–44%) for clear waters where R rs (671) < 0.0012 mg l−1. The algorithm was implemented with the global R rs (λ) data from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar‐orbiting Partnership (SNPP) satellite. We provided a brief characterization of the spatial distribution and temporal trends of the SPM products in global waters based on the monthly SPM composites. Case studies of the SPM time series in coastal and inland waters suggest that the satellite SPM estimations registered spatial and seasonal variation and episodic events in regional scales as well. The VIIRS‐generated global SPM maps provide a valuable addition to the existing ocean color products for environmental and climate applications.

Randomised study within a trial (SWAT) to evaluate personalised versus standard text message prompts for increasing trial participant response to postal questionnaires (PROMPTS)

BackgroundUse of a person’s name in a text message has been shown to be effective in instigating behaviour change. We evaluated the effectiveness of a personalised text message (including the recipient’s name) versus a standardised text message for prompting a response from trial participants to complete and return postal follow-up questionnaires.MethodsUsing a randomised study within a trial (SWAT) embedded within the host GRASP (Getting it Right: Addressing Shoulder Pain) trial, participants who provided a mobile telephone number were randomised (1:1) by a central computer system to receive either (1) a personalised text message which included their name or (2) a standard text message. Text messages were sent by the trial office on the same day as the 6-month GRASP follow-up questionnaire. The primary outcome was questionnaire response rate, defined as the proportion of 6-month GRASP follow-up questionnaires returned by participants. Secondary outcomes included time to response, the proportion of participants sent a reminder follow-up questionnaire, and cost.ResultsBetween March 2017 and May 2019 (recruitment period for GRASP trial), 618 participants were randomised to a personalised (n = 309) or standard (n = 309) text message and all were included in the analysis. The overall questionnaire response rate was 87% (n = 537/618); 90% (n = 277/309) of participants responded in the personalised text message group compared to 84% (n = 260/309) in the standard text message group (relative risk (RR) 1.07; 95% CI 1.00 to 1.13). Participants randomised to receive the personalised text message were more likely to return their initial postal questionnaire than those who received the standard text message (n = 185/309; 60% vs. n = 160/309; 52%) (RR 1.16; 95% CI 1.00 to 1.33); this represents an absolute percentage difference between intervention groups of 8%. Post hoc subgroup analysis showed that males under 65 years were the group most likely to return their initial questionnaire if they received a personalised text message.ConclusionOverall, participants who received a personalised text message were more likely to return their questionnaire than those who received the standard text message.Trial registrationGRASP Trial ISRCTN16539266; SWAT Repository ID 35

Abstract 2620: Ignoring left truncation in overall survival within real-world genomic-phenomic data leads to inflated survival estimates

Abstract Studies linking genomic and phenomic data are subject to selection biases, including delayed entry or immortal time bias. Delayed entry can be problematic for time-to-event analyses, but utilization of appropriate statistical methods to account for delayed entry are underutilized. Delayed entry commonly occurs when genomic sequencing results are obtained after the start time for survival estimation. To evaluate the impact of left truncation on overall survival (OS) estimates, we explored outcomes in patients with de novo stage IV non-small cell lung cancer (NSCLC) and colorectal cancer (CRC) from the AACR GENIE Biopharma Collaborative, who had genomic sequencing within a specified timeframe. We analyzed OS from diagnosis and from start of the most common first-line regimen, carboplatin/pemetrexed for NSCLC (N = 212 patients) and FOLFOX for CRC (N = 369 patients). We compared median OS using standard Kaplan-Meier methods to median OS using left truncation methods to account for delayed entry. All NSCLC and CRC patients underwent genomic sequencing after their diagnosis date. Among NSCLC patients on carboplatin/pemetrexed, 41% and among CRC patients on FOLFOX, 14% had sequencing determined after starting first-line regimen. The survfit function in R package survival was used, and the absolute differences and percent differences in median OS estimates were calculated. Failure to account for delayed entry leads to an overestimation of OS, regardless of cohort and start date. Adjusting survival outcomes using left truncation methods reduces the influence of some aspects of selection bias and results in better estimates of time to event outcomes. Analyses from these cohorts can provide meaningful insights about survival outcomes outside the clinical trial setting and may support trial design and reliable selection of control arms. As such, it is imperative that analytic methods to account for the inflated survival estimates are incorporated. EstimateCRC Stage IV (N = 658)NSCLC Stage IV (N = 722)Unadjusted Median (IQR) Overall Survival from Diagnosis (Years)3.2 (2.9, 3.4)2.3 (2.0, 2.5)Median (IQR) Overall Survival from Diagnosis in Years, Adjusting for Delayed Entry2.1 (1.9, 2.4)1.3 (1.1, 1.6)Difference in Medians (Years)1.11.0% Difference in Medians34%44%EstimateCRC Stage IV (N = 369)NSCLC Stage IV (N = 212)Unadjusted Median (IQR) Overall Survival from Most Common First-Line Regimen (Years)2.9 (2.6, 3.4)1.3 (1.0, 1.6)Median (IQR) Overall Survival from Most Common First-Line Regimen in Years, Adjusting for Delayed Entry2.1 (1.8, 2.5)0.9 (0.7, 1.2)Difference in Medians (Years)0.80.4% Difference in Medians28%31% Citation Format: Samantha Brown, Jessica A. Lavery, Eva M. Lepisto, Caroline McCarthy, Hira Rizvi, Celeste Yu, Kenneth L. Kehl, Shawn M. Sweeney, Julia E. Rudolph, Nikolaus Schultz, Ritika Kundra, Brooke Mastrogiacomo, Phillipe Bedard, Jeremy L. Warner, Gregory J. Riely, Deborah Schrag, Katherine S. Panageas, The AACR Project GENIE Consortium. Ignoring left truncation in overall survival within real-world genomic-phenomic data leads to inflated survival estimates [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2620.

Radiographic and fluoroscopic X-ray systems: Quality control of the X-ray tube and automatic exposure control using theoretical spectra to determine air kerma and dose to a homogenous phantom.

PurposeTo develop a method to perform quality control (QC) of X‐ray tubes and automatic exposure control (AEC) as a part of the QC of the radiographic and fluoroscopic X‐ray system. Our aim is to verify the output from the X‐ray tube by comparing the measured radiation output, or air kerma, to the theoretical output given the applied exposure settings and geometry, in addition to comparing the measured kV to the nominal kV. The AEC system for fluoroscopic and conventional X‐ray systems is assessed by determining the absorbed dose to a homogenous phantom with different thicknesses.MethodThis study presents a model to verify the X‐ray tube measurement results and a method to determine the dose to a homogenous phantom (Dphantom). The following input is needed: a parameterized model of the X‐ray spectrum, the X‐ray tube measurements using a multifunctional X‐ray meter, the exposure parameters recorded via imaging of polymethyl methacrylate (PMMA) slabs of different thickness that simulate the patient using AEC, and a parameterized model for calculating the dose to water from Monte Carlo simulations. The output is the entrance surface dose (ESD) and absorbed dose in the phantom, Dphantom (µGy). In addition, the parameterized X‐ray spectrum is used to compare theoretical and measured air kerma as a part of the QC of the X‐ray tube. To verify the proposed method, the X‐ray spectrum provided in this study, SPECTRUM, was compared to two commercially available spectra, SpekCalc and Institute of Physics and Engineering in Medicine (IPEM) 78. The fraction of energy imparted to the homogenous phantom was compared to the imparted fraction calculated by PCXMC.ResultsThe spectrum provided in this study was in good agreement with two previously published X‐ray spectra. The absolute percentage differences of the spectra varied from 0.05% to 3.9%, with an average of 1.4%, compared to SpekCalc. Similarly, the deviation from IPEM report 78 varied from 0.02% to 2.3%, with an average of 0.74%. The SPECTRUM was parameterized for calculation of the imparted fraction for target angles of 10°, 12°, and 15°, kV (50–150 kV) with the materials Al (2.2–8 mm), Cu (0–1 mm), and any combination of the filters, PMMA and water. The deviation of energy imparted from the results by PCXMC was less than 8% for all measurements across different kV, filtration, and vendors, obtained by using PMMA to record the exposure parameters, while the dose was calculated based on water with same thicknesses as the PMMA.ConclusionThis study presents an accurate and suitable method to perform a part of the QC of fluoroscopic and conventional X‐ray systems with respect to the X‐ray tube and the associated AEC system. The method is suitable for comparing protocols within and between systems via the absorbed dose.

Accuracy of Weight Estimation Using the Broselow Tape in a Peruvian Pediatric Population.

IntroductionThe Broselow tape (BT) is a useful pediatric tool for weight estimation and dosing reference during emergency care. Many accuracy studies have been performed for various countries and regions of the world but there is very little information for Latin American countries. The primary objective of the study was to assess the accuracy of the BT in a Peruvian pediatric population.MethodsThis was a retrospective cross-sectional study of 1,160 children aged two to 19 years from three outpatient clinics in La Libertad, Lima, and Iquitos, Peru. Patient height and weight were measured and compared with the weight and color zone generated by the 2017 edition of the BT. Accuracy was estimated by statistical comparison of mean absolute percent differences, error within 10% (EW10), and color zone agreement.ResultsComparison of mean differences between measured weight (MW) and estimated BT weight shows that the BT underestimates actual weight for all color zones in this population. Likewise, the Bland-Altman plot of agreement between estimated and measured weights shows an overall underestimation, or bias, equal to 1.60 kg. The overall percent difference was -7.84% with differences gradually increasing for weights over 10 kg. In terms of accuracy, the overall error within 10% was 62.8%.ConclusionThe BT underestimates the actual weight of Peruvian pediatric patients in all color categories, particularly in children with higher body mass indexes. Underestimation of weight may lead to the use of non-therapeutic medication doses or incorrect equipment sizes and, subsequently, ineffective resuscitation.

A three-step semi analytical algorithm (3SAA) for estimating inherent optical properties over oceanic, coastal, and inland waters from remote sensing reflectance

We present a three-step inverse model (3SAA) for estimating the inherent optical properties (IOPs) of surface waters from the remote sensing reflectance spectra, Rrs(λ). The derived IOPs include the total (a(λ)), phytoplankton (aphy(λ)), and colored detrital matter (acdm(λ)), absorption coefficients, and the total (bb(λ)) and particulate (bbp(λ)) backscattering coefficients. The first step uses an improved neural network approach to estimate the diffuse attenuation coefficient of downwelling irradiance from Rrs. a(λ) and bbp(λ) are then estimated using the LS2 model (Loisel et al., 2018), which does not require spectral assumptions on IOPs and hence can assess a(λ) and bb(λ) at any wavelength at which Rrs(λ) is measured. Then, an inverse optimization algorithm is combined with an optical water class (OWC) approach to assess aphy(λ) and acdm(λ) from anw(λ).The proposed model is evaluated using an in situ dataset collected in open oceanic, coastal, and inland waters. Comparisons with other standard semi-analytical algorithms (QAA and GSM), as well as match-up exercises, have also been performed. The applicability of the algorithm on OLCI observations was assessed through the analysis of global IOPs spatial patterns derived from 3SAA and GSM. The good performance of 3SAA is manifested by median absolute percentage differences (MAPD) of 13%, 23%, 34% and 34% for bbp(443), anw(443), aphy(443) and acdm(443), respectively for oceanic waters. Due to the absence of spectral constraints on IOPs in the inversion of total IOPs, and the adoption of an OWC-based approach, the performance of 3SAA is only slightly degraded in bio-optical complex inland waters.

Assessment of Polymer Atmospheric Correction Algorithm for Hyperspectral Remote Sensing Imagery over Coastal Waters.

Spaceborne imaging spectroscopy, also called hyperspectral remote sensing, has shown huge potential to improve current water colour retrievals and, thereby, the monitoring of inland and coastal water ecosystems. However, the quality of water colour retrievals strongly depends on successful removal of the atmospheric/surface contributions to the radiance measured by satellite sensors. Atmospheric correction (AC) algorithms are specially designed to handle these effects, but are challenged by the hundreds of narrow spectral bands obtained by hyperspectral sensors. In this paper, we investigate the performance of Polymer AC for hyperspectral remote sensing over coastal waters. Polymer is, in nature, a hyperspectral algorithm that has been mostly applied to multispectral satellite data to date. Polymer was applied to data from the Hyperspectral Imager for the Coastal Ocean (HICO), validated against in situ multispectral (AERONET-OC) and hyperspectral radiometric measurements, and its performance was compared against that of the hyperspectral version of NASA’s standard AC algorithm, L2gen. The match-up analysis demonstrated very good performance of Polymer in the green spectral region. The mean absolute percentage difference across all the visible bands varied between 16% (green spectral region) and 66% (red spectral region). Compared with L2gen, Polymer remote sensing reflectances presented lower uncertainties, greater data coverage, and higher spectral similarity to in situ measurements. These results demonstrate the potential of Polymer to perform AC on hyperspectral satellite data over coastal waters, thus supporting its application in current and future hyperspectral satellite missions.

Reconstruction of remotely sensed daily evapotranspiration data in cloudy-sky conditions

The unavailability of thermal infrared satellite observations in cloudy conditions has limited the spatial distribution and temporal coverage of remotely sensed evapotranspiration (ET) data. As a result, a number of approaches have been developed to reconstruct remotely sensed daily ET data in cloudy-sky conditions. Despite the wide application of these approaches, no work has been conducted to compare their performance over a wide variety of climatic and vegetative conditions. In this study, three commonly used ET reconstruction approaches namely, reference ET fraction (EToF), land surface temperature reconstruction (LSTR), and variational data assimilation (VDA) are used to obtain daily ET data under cloudy conditions. The abovementioned three approaches are applied to the Heihe River Basin (HRB) in the northwest of China during the growing season in 2015. The HRB covers an area of approximately 1,432,000 km2 and contains various land covers. The large aperture scintillometer (LAS) and eddy covariance (EC) measurements are used to evaluate performance of the abovementioned three methods over the grassland, cropland, and riparian forest sites in the HRB. The results show that the EToF approach underestimates ET at the grassland and riparian sites in cloudy days because of the negatively biased ET/ETo (where ETo is the reference evapotranspiration) in clear-sky days. The VDA approach overestimates ET in cloudy-sky conditions because of the overpredicted evaporative fraction values. The LSTR approach overestimates ET due to the under-reconstructed LST in cloudy day. The mean absolute percentage difference (MAPD) and root mean square error (RMSE) statistical metrics are used to compare performance of the three approaches The LSTR (MAPD = 43.1% and RMSE = 1.3 mm/day) and VDA (MAPD = 46.7% and RMSE = 1.4 mm/day) approaches slightly outperform EToF (MAPD = 46.6% and RMSE = 1.5 mm/day). The RMSEs of reconstructed ET values by EToF, VDA, and LSTR increase respectively from 1.6, 1.2, and 1.5 (mm/day) to 2.2, 1.9, and 2.0 (mm/day) as the number of consecutive cloudy days increases from 1 to 3. These outcomes suggest that synergistic use of space-borne microwave and thermal infrared LST observations into remote sensing-based ET methods can improve the reconstruction of ET data under cloudy conditions.

Accuracy of Preoperative Breast MRI Versus Conventional Imaging in Measuring Pathologic Extent of Invasive Lobular Carcinoma.

To determine whether invasive lobular carcinoma (ILC) extent is more accurately depicted with preoperative MRI (pMRI) than conventional imaging (mammography and/or ultrasound). After IRB approval, we retrospectively identified women with pMRIs (February 2005 to January 2014) to evaluate pure ILC excluding those with ipsilateral pMRI BI-RADS 4 or 5 findings or who had neoadjuvant chemotherapy. Agreement between imaging and pathology sizes was summarized using Bland-Altman plots, absolute and percent differences, and the intraclass correlation coefficient (ICC). Rates of underestimation and overestimation were evaluated and their associations with clinical features were explored. Among the 56 women included, pMRI demonstrated better agreement with pathology than conventional imaging by mean absolute difference (1.6 mm versus -7.8 mm, P < 0.001), percent difference (10.3% versus -16.4%, P < 0.001), and ICC (0.88 versus 0.61, P = 0.019). Conventional imaging more frequently underestimated ILC span than pMRI using a 5 mm difference threshold (24/56 (43%) versus 10/56 (18%), P < 0.001), a 25% threshold (19/53 (36%) versus 10/53 (19%), P = 0.035), and T category change (17/56 (30%) versus 7/56 (13%), P = 0.006). Imaging-pathology size concordance was greater for MRI-described solitary masses than other lesions for both MRI and conventional imaging (P < 0.05). Variability of conventional imaging was lower for patients ≥ the median age of 62 years than for younger patients (SD: 12 mm versus 22 mm, P = 0.012). MRI depicts pure ILC more accurately than conventional imaging and may have particular value for younger women.

Assessment of Merged Satellite Precipitation Datasets in Monitoring Meteorological Drought over Pakistan

The current study evaluates the potential of merged satellite precipitation datasets (MSPDs) against rain gauges (RGs) and satellite precipitation datasets (SPDs) in monitoring meteorological drought over Pakistan during 2000–2015. MSPDs evaluated in the current study include Regional Weighted Average Least Square (RWALS), Weighted Average Least Square (WALS), Dynamic Clustered Bayesian model Averaging (DCBA), and Dynamic Bayesian Model Averaging (DBMA) algorithms, while the set of SPDs is Global Precipitation Measurement (GPM)-based Integrated Multi-Satellite Retrievals for GPM (IMERG-V06), Tropical Rainfall Measurement Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA 3B42 V7), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and ERA-Interim (re-analyses dataset). Several standardized precipitation indices (SPIs), including SPI-1, SPI-3, and SPI-12, are used to evaluate the performances of RGs, SPDs, and MSPDs across Pakistan as well as on a regional scale. The Mann–Kendall (MK) test is used to assess the trend of meteorological drought across different climate regions of Pakistan using these SPI indices. Results revealed higher performance of MSPDs than SPDs when compared against RGs for SPI estimates. The seasonal evaluation of SPIs from RGs, MSPDs, and SPDs in a representative drought year (2008) revealed mildly to moderate wetness in monsoon season while mild to moderate drought in winter season across Pakistan. However, the drought severity ranges from mild to severe drought in different years across different climate regions. MAPD (mean absolute percentage difference) shows high accuracy (MAPD &lt;10%) for RWALS-MSPD, good accuracy (10% &lt; MAPD &lt;20%) for WALS-MSPD and DCBA-MSPD, while good to reasonable accuracy (20% &lt; MAPD &lt; 50%) for DCBA in different climate regions. Furthermore, MSPDs show a consistent drought trend as compared with RGs, while SPDs show poor performance. Overall, this study demonstrated significantly improved performance of MSPDs in monitoring the meteorological drought.

Estimating ultraviolet reflectance from visible bands in ocean colour remote sensing

In recent years, ultraviolet (UV) bands have received increasing attention from the ocean colour remote sensing community, as they may contribute to improving atmospheric correction and inherent optical properties (IOPs) retrieval. However, most ocean colour satellite sensors do not have UV bands, and the accurate retrieval of UV remote sensing reflectance (Rrs) from UV satellite data is still a challenge. In order to address this problem, this study proposes a hybrid approach for estimating UV Rrs from the visible bands. The approach was implemented with two popular ocean colour satellite sensors, i.e. GCOM-C SGLI and Sentinel-3 OLCI. In situ Rrs collected globally and simulated Rrs spectra were used to develop UV Rrs retrieval models, and UV Rrs values at 360, 380 and 400 nm were estimated from visible Rrs spectra. The performances of the established models were evaluated using in situ Rrs and satellite data, and applied to a semi-analytical algorithm for IOPs retrieval. The results showed that: (i) UV Rrs retrieval models had low uncertainties with mean absolute percentage differences (MAPD) less than 5%; (ii) the model assessment with in situ Rrs showed high accuracy (r = 0.92–1.00 and MAPD = 1.11%–10.95%) in both clear open ocean and optically complex waters; (iii) the model assessment with satellite data indicated that model-estimated UV Rrs were more consistent with in situ values than satellite-derived UV Rrs; and (iv) model-estimated UV Rrs may improve the decomposition accuracy of absorption coefficients in semi-analytical IOPs algorithm. Thus, the proposed method has great potentials for reconstructing UV Rrs data and improving IOPs retrieval for historical satellite sensors, and might also be useful for UV-based atmospheric correction algorithms.

Thermodilution Cardiac Index Has Poor Agreement with That Measured by the Direct Fick Method in Low-Output States

<h3>Purpose</h3> The thermodilution (Td) method is routinely used for measurement of cardiac output although its accuracy in low-output states remains uncertain. Criteria for designating heart transplant listing status in the contemporary allocation system is incumbent on meeting strict cardiac index (CI) cutoffs. We aimed to assess the agreement between Td and direct Fick (dFick) CI in patients with low CI. <h3>Methods</h3> In this retrospective analysis of 535 patients who underwent right heart catheterization with dFick CI measurement as part of clinically indicated hemodynamic evaluation using the gold-standard Douglas bag technique, 253 patients had both Td/dFick CI measurements. Three saline injections were typically used and averaged in Td CI measurements. We included 118 patients who specifically had a CI of </= 2.2 L/min/m² by dFick method. Agreement between Td and dFick method was assessed by median absolute percentage difference, Spearman's rank correlation, and Bland-Altman Method. <h3>Results</h3> Among the 118 patients included (Mean [SD] age 60 [12.2] years, 42.3% female), Median (interquartile range, IQR) overall dFick and Td CI values differed significantly (1.86 [1.65, 2.1] and 2.03 [1.78, 2.31] L/min/m², respectively; P<0.001). The two measurements weakly correlated (r_s=0.31, P<0.001), with a systematic error introduced by Td CI expressed a mean difference of 0.21 (-0.61, 1.03) L/min/m² (Figure). Median (IQR) absolute percentage difference between Td and dFick was 16.9 (7.9, 27.9)%. Td and dFick CI's differed by >25% in 33.1% of patients. <h3>Conclusion</h3> The agreement of Td with the gold-standard dFick CI measurements in patients with low CI was suboptimal. These data are important consider in in clinical scenarios such as heart transplant listing status where strict hemodynamic cutoffs guide urgency.

Inter-laboratory comparison of ED-XRF/PIXE analytical techniques in the elemental analysis of filter-deposited multi-elemental certified reference materials representative of ambient particulate matter.

The quantification of the elemental concentration of ambient particulate matter is a challenging task because the observed elemental loadings are not well above the detection limit for most analytical techniques. Although non-destructive nuclear techniques are widely used for the chemical characterization of ambient aerosol, only one multi-element standard reference filter material that mimics ambient aerosol composition has become recently available in the market. To ensure accuracy, reliability and comparability of instruments performance, multiple reference materials with different elemental mass loadings are necessary. In this study, an intercomparison exercise was performed to evaluate the measurement uncertainty and instruments performance using multi-element dust standard reference samples deposited on PTFE filters. The filter samples, produced by means of dust dispersion, were tested in terms of homogeneity, reproducibility and long-term stability (≈40 months). Eight laboratories participated in the exercise. The evaluation of the results reported by the participants was performed by using two sets of reference values: a) the concentrations reported by the Expert Laboratory, b) the robust average concentrations reported by all participants. Most of the reported on the certificate of analysis elements were efficiently detected in the sample loadings prepared as representative for atmospheric samples by the Expert Laboratory. The average absolute relative difference between the reported and the reference values ranged between 0.1% (Ti) and 33.7% (Cr) (CRM-2584). The participants efficiently detected most of the elements except from the elements with atomic number lower than 16 (i.e. P, Al, Mg). The average absolute percentage difference between the participants results and the assigned value as derived by the expert laboratory was 17.5 ± 18.1% (CRM-2583; Cr, Pb excluded) and 16.7 ± 16.7% (CRM-2584; Cr, P excluded). The average "relative robust standard deviation" of the results reported by all participants was 25.1% (CRM-2583) and 22.8% (CRM-2584).

New proxy models for predicting oil recovery factor in waterflooded heterogeneous reservoirs

To predict the recovery factor (RF) in waterflooded layered oil reservoirs, two empirical relationships were derived. Both correlations use four independent variables. These are reservoir heterogeneity (characterized by permeability variation coefficient), permeability anisotropy (ratio of vertical to horizontal permeability), viscosity of the injected water, and water injection rate. One of the correlations estimates RF at water breakthrough time (RFBT) and the other evaluates RF at the end of project (RFEOP). Each correlation comes in an expanded form with more parameters and a reduced form with fewer parameters. Both models are based on the global linear model. Eclipse black-oil simulation was used to determine RF for generic reservoirs with different combinations of permeability variation, permeability anisotropy, injected water viscosities, and water injection rates. A total of 192 data sets have been generated. Out of these, 144 data sets (about 75% of the generated sets) were used for model development and 48 data sets (about 25% of the generated sets) were used for model testing and validation. The expanded forms of the new developed correlations gave reliable estimates of RFBT and RFEOP with absolute average percent difference (AAPCD) of 6.9 and 1.02, respectively. The reduced forms yielded slightly higher AAPCDs of 8.30 and 1.04, respectively. When tested against 48 simulation-generated data sets, the expanded forms yielded excellent fits for RFBT and RFEOP with AAPCDs of 14 and 6.5, respectively. The reduced forms showed comparable fit with AAPCDs of 16.9 and 6.70, respectively. The highest RFEOP of 50.6% was achieved for a generic reservoir with a permeability variation in V = 0.1 and a permeability anisotropy of kz/kx = 1.0. This particular reservoir needs to be waterflooded using a water viscosity of µw = 1.0 cp and a water injection rate of qi = 10,000 bpd. Finally, when tested against the Guthrie–Greenberger and the API statistical study, using a single field data set, the proposed correlations gave higher absolute percent difference of 22.9 and 22.7 compared to 0.758 and 19.2 for Guthrie–Greenberger and the API statistical study, respectively.