Free-breathing radial 3D fat-suppressed T1-weighted gradient echo (r-VIBE) sequence for assessment of pulmonary lesions: a prospective comparison of CT and MRI

Purpose To determine whether the pulmonary MR imaging with free-breathing radial 3D fat-suppressed T1-weighted gradient echo (r-VIBE) sequence can detect lung lesions and display lesion profiles with an accuracy comparable to that of computed tomography (CT), which is the reference standard in this study. Population Sixty-three consecutive patients were prospectively enrolled between October, 2016 and March, 2017. All the patients received both 3T MRI scanning with a free-breathing r-VIBE sequence and chest standard CT. Morphologic features of lesions were evaluated by two radiologists with a 5-point system. Chest standard CT were used as reference standard. Weighted kappa analysis and chi-squared test were used to determine both inter-observer agreement and inter-method agreement. Results A total of 210 solid pulmonary nodules or masses and 1 ground-glass nodule were detected by CT. Compared to CT, r-VIBE correctly detected 95.7% of pulmonary nodules, including 100% of detection rate with diameter greater than 6 mm, 92.3% of pulmonary nodules with diameter between 4 and 6 mm, and 83.3% of pulmonary nodules with diameter less than 4 mm The inter-method agreements between r-VIBE and standard-dose CT were either “substantial” or “excellent” in the evaluation of following features of pulmonary nodules with diameter more than 10mm: including lobulation, spiculation, convergence of vessels, bubble-like attenuation, cavitation and mediastinal lymph node enlargement (0.605≤K≤1.000; P<0.0001). However, K values for inter-method agreements were significant but “moderate” or “poor” for evaluating pleural tag, halo, and calcification (0.355≤ K≤0.451; P<0.0001). Conclusion The use of pulmonary MR imaging with r-VIBE showed high detection rate of pulmonary nodules and inter-method agreement with CT. It is also useful for nodule morphologic assessment.

A comparison of PCR and ELISA methods to detect different stages of Plasmodium vivax in Anopheles arabiensis

Background In characterizing malaria epidemiology, measuring mosquito infectiousness informs the entomological inoculation rate, an important metric of malaria transmission. PCR-based methods have been touted as more sensitive than the current “gold-standard” circumsporozoite (CSP) ELISA. Wider application of PCR-based methods has been limited by lack of specificity for the infectious sporozoite stage. We compared a PCR method for detecting the parasite’s mitochondrial (mt) cytochrome oxidase I (COX-I) gene with ELISA for detecting circumsporozoite protein for identification of different life stages of the parasite during development within a mosquito. Methods A PCR-based method targeting the Plasmodium mt COX-I gene was compared with the CSP ELISA method to assess infectivity in Anopheles arabiensis colony mosquitoes fed on blood from patients infected with Plasmodium vivax. Mosquitoes were tested at six post-infection time points (days 0.5, 1, 6, 9, 12, 15). The head and thorax and the abdomen for each specimen were tested separately with each method. Agreement between methods at each infection stage was measured using Cohen’s kappa measure of test association. Results Infection status of mosquitoes was assessed in approximately 90 head/thorax and 90 abdomen segments at each time point; in total, 538 head/thorax and 534 abdomen segments were tested. In mosquitoes bisected after 0.5, 1, and 6 days post-infection (dpi), the mt COX-I PCR detected Plasmodium DNA in both the abdomen (88, 78, and 67%, respectively) and head/thorax segments (69, 60, and 44%, respectively), whilst CSP ELISA detected sporozoites in only one abdomen on day 6 post-infection. PCR was also more sensitive than ELISA for detection of Plasmodium in mosquitoes bisected after 9, 12, and 15 dpi in both the head and thorax and abdomen. There was fair agreement between methods for time points 9–15 dpi (κ = 0.312, 95% CI: 0.230–0.394). Conclusions The mt COX-I PCR is a highly sensitive, robust method for detecting Plasmodium DNA in mosquitoes, but its limited Plasmodium life-stage specificity cannot be overcome by bisection of the head and thorax from the abdomen prior to PCR. Thus, the mt COX-I PCR is a poor candidate for identifying infectious mosquitoes. Graphical Abstract

Reproducibility of MRI Features of Uterine Leiomyomas: A Study on Interobserver Agreement and Inter-Method Agreement With Surgery

Purpose: To evaluate interobserver agreement in the interpretation of different MRI features of uterine leiomyomas (UL) according to observers’ experience, and to assess the inter-method reproducibility (MRI versus surgery) regarding the International Federation of Gynecology and Obstetrics (FIGO) classification. Methods: Retrospective study including UL patients who underwent MRI and surgical treatment. Four blinded observers (2 vs >10 years of experience) assessed UL regarding dimensions and volume; inner and outer mantles; FIGO classification; vascularization; degeneration; and diffusion-weighted imaging features. Uterine dimensions and volume were calculated. FIGO classification as ascertained by observers was compared to surgical findings. Intraclass correlation coefficient (ICC) estimates were used for interobserver comparison of numerical variables, and kappa statistic for categorical variables. Results: Thirty-five patients (26y-73y) with 61 UL were included in the interobserver analyses, and 31 patients (54 UL) had available data allowing retrospective surgical FIGO classification for assessment of inter-method reproducibility. Both groups of observers had good to excellent agreement in assessing UL (ICC = 0.980-0.994) and uterine volumes (ICC = 0.857-0.914), mantles measurement (ICC = 0.797-0.920), and apparent diffusion coefficient calculation (ICC = 0.787-0.883). There was substantial agreement for both groups regarding FIGO classification (κ = 0.645-0.767). Vascularization, degeneration and restricted diffusion had lower agreement, varying from reasonable to moderate. Inter-method agreement was reasonable (κ = 0.341-0.395). Conclusions: Interobserver agreement of MRI for UL was higher for quantitative than qualitative features, with a little impact of observers’ experience for most features. MRI agreement with surgery was reasonable. Further efforts should be taken to improve interobserver and inter-method reproducibility for MRI in this scenario.

Extracellular volume-guided late gadolinium enhancement analysis for non-ischemic cardiomyopathy: The Women’s Interagency HIV Study

Background Quantification of non-ischemic myocardial scar remains a challenge due to the patchy diffuse nature of fibrosis. Extracellular volume (ECV) to guide late gadolinium enhancement (LGE) analysis may achieve a robust scar assessment. Methods Three cohorts of 80 non-ischemic-training, 20 non-ischemic-validation, and 10 ischemic-validation were prospectively enrolled and underwent 3.0 Tesla cardiac MRI. An ECV cutoff to differentiate LGE scar from non-scar was identified in the training cohort from the receiver-operating characteristic curve analysis, by comparing the ECV value against the visually-determined presence/absence of the LGE scar at the highest signal intensity (SI) area of the mid-left ventricle (LV) LGE. Based on the ECV cutoff, an LGE semi-automatic threshold of n-times of standard-deviation (n-SD) above the remote-myocardium SI was optimized in the individual cases ensuring correspondence between LGE and ECV images. The inter-method agreement of scar amount in comparison with manual (for non-ischemic) or full-width half-maximum (FWHM, for ischemic) was assessed. Intra- and inter-observer reproducibility were investigated in a randomly chosen subset of 40 non-ischemic and 10 ischemic cases. Results The non-ischemic groups were all female with the HIV positive rate of 73.8% (training) and 80% (validation). The ischemic group was all male with reduced LV function. An ECV cutoff of 31.5% achieved optimum performance (sensitivity: 90%, specificity: 86.7% in training; sensitivity: 100%, specificity: 81.8% in validation dataset). The identified n-SD threshold varied widely (range 3 SD–18 SD), and was independent of scar amount (β = −0.01, p = 0.92). In the non-ischemic cohorts, results suggested that the manual LGE assessment overestimated scar (%) in comparison to ECV-guided analysis [training: 4.5 (3.2–6.4) vs. 0.92 (0.1–2.1); validation: 2.5 (1.2–3.7) vs. 0.2 (0–1.6); P < 0.01 for both]. Intra- and inter-observer analyses of global scar (%) showed higher reproducibility in ECV-guided than manual analysis with CCC = 0.94 and 0.78 versus CCC = 0.86 and 0.73, respectively (P < 0.01 for all). In ischemic validation, the ECV-guided LGE analysis showed a comparable scar amount and reproducibility with the FWHM. Conclusions ECV-guided LGE analysis is a robust scar quantification method for a non-ischemic cohort. Trial registration ClinicalTrials.gov; NCT00000797, retrospectively-registered 2 November 1999; NCT02501811, registered 15 July 2015.

Comparison of different methods used in drugs of abuse for sample validity testing including pH methods, specific gravity methods, TECO™ Drug Adulteration Test Strip and oxidant assay

Objectives In the absence of sample validity testing, a healthcare provider may fail to identify a patient’s adulteration of their urine sample. This study compared different methods for specific gravity (SG), pH, TECO™ Drug Adulteration Test Strip (dipstick) and oxidant assay to explain the differences and also make an informative decision on method selection. Methods Creatinine, SG and pH measurements are essential in sample validity testing. SG and pH automated chemical methods are compared against pH meter method, SG refractometer and dipstick method. Also, oxidant assay was compared against dipstick method. Results SG chemical method agreement with refractometer is 81.9% and with dipstick method is 64.7%. The refractometer method agreement with dipstick method is 66.1%. pH chemical method agreement with pH Meter method is 74.3% and with dipstick method is 81.4%. pH meter method agreement is 85.7% with dipstick method. Results were analysed using Deming regression analysis and F-test. SG chemical method correlated better with refractometer than the dipstick method. Oxidant assay correlated well with dipstick method in detecting adulterants such as pyridinium chlorochromate, nitrite and bleach. Conclusions Varying degrees of differences were seen in the SG and pH measurements. These differences were both method and instrument dependent. The automated chemical methods are recommended alongside oxidant assay for consistency, accuracy and faster turn-around time as part of sample validity testing for drugs of abuse.

Extracellular Volume-Guided Late Gadolinium Enhancement Analysis for Non-Ischemic Cardiomyopathy: The Women’s Interagency HIV Study.

BACKGROUND: Quantification of non-ischemic myocardial scar remains a challenge due to the patchy diffuse nature of fibrosis. Extracellular volume (ECV) to guide late gadolinium enhancement (LGE) analysis may achieve a robust scar assessment.METHODS: Three cohorts of 80 non-ischemic-training, 20 non-ischemic-validation, and 10 ischemic-validation were prospectively enrolled and underwent 3.0 Tesla cardiac MRI. An ECV cutoff to differentiate LGE scar from non-scar was identified in the training cohort from the receiver-operating characteristic (ROC) curve analysis, by comparing the ECV value against the visually-determined presence/absence of the LGE scar at the highest signal intensity (SI) area of the mid-left ventricle (LV) LGE. Based on the ECV cutoff, an LGE semi-automatic threshold of n-times of standard-deviation (n-SD) above the remote-myocardium SI was optimized in the individual cases ensuring correspondence between LGE and ECV images. The inter-method agreement of scar amount in comparison with manual (for non-ischemic) or full-width half-maximum (FWHM, for ischemic) was assessed. Intra- and inter-observer reproducibility were investigated in a randomly chosen subset of 40 non-ischemic and 10 ischemic cases. RESULTS: The non-ischemic groups were all female with the HIV positive rate of 73.8% (training) and 80% (validation). The ischemic group was all male with reduced LV function. An ECV cutoff of 31.5% achieved optimum performance (sensitivity: 90%, specificity:86.7% in training; sensitivity: 100%, specificity: 81.8% in validation dataset). The identified n-SD threshold varied widely (range 3SD to 18SD), and was independent of scar amount (β= -0.01, p=0.92). In the non-ischemic cohorts, results suggested that the manual LGE assessment overestimated scar (%) in comparison to ECV-guided analysis (training: 4.5 [3.2 – 6.4] vs. 0.92 [0.1 – 2.1]; validation: 2.5 [1.2 – 3.7] vs. 0.2 [0 – 1.6]; P<0.01 for both). Intra- and inter-observer analyses of global scar (%) showed higher reproducibility in ECV-guided than manual analysis with CCC=0.94 and 0.78 vs. CCC=0.86 and 0.73, respectively (P<0.01 for all). In ischemic validation, the ECV-guided LGE analysis showed a comparable scar amount and reproducibility with the FWHM. CONCLUSIONS: ECV-guided LGE analysis is a robust scar quantification method for a non-ischemic cohort. Trial-Registration: ClinicalTrials.gov; NCT00000797, retrospectively-registered 2 November 1999; NCT02501811, registered 15 July 2015.

Comparison of Bisulfite Pyrosequencing and Methylation-Specific qPCR for Methylation Assessment

Different methodological approaches are available to assess DNA methylation biomarkers. In this study, we evaluated two sodium bisulfite conversion-dependent methods, namely pyrosequencing and methylation-specific qPCR (MS-qPCR), with the aim of measuring the closeness of agreement of methylation values between these two methods and its effect when setting a cut-off. Methylation of tumor suppressor gene p16/INK4A was evaluated in 80 lung cancer patients from which cytological lymph node samples were obtained. Cluster analyses were used to establish methylated and unmethylated groups for each method. Agreement and concordance between pyrosequencing and MS-qPCR was evaluated with Pearson’s correlation, Bland–Altman, Cohen’s kappa index and ROC curve analyses. Based on these analyses, cut-offs were derived for MS-qPCR. An acceptable correlation (Pearson’s R2 = 0.738) was found between pyrosequencing (PYRmean) and MS-qPCR (NMP; normalized methylation percentage), providing similar clinical results when categorizing data as binary using cluster analysis. Compared to pyrosequencing, MS-qPCR tended to underestimate methylation for values between 0 and 15%, while for methylation >30% overestimation was observed. The estimated cut-off for MS-qPCR data based on cluster analysis, kappa-index agreement and ROC curve analysis were much lower than that derived from pyrosequencing. In conclusion, our results indicate that independently of the approach used for estimating the cut-off, the methylation percentage obtained through MS-qPCR is lower than that calculated for pyrosequencing. These differences in data and therefore in the cut-off should be examined when using methylation biomarkers in the clinical practice.

Error propagation in regional geoid computation using spherical splines, least-squares collocation, and Stokes’s formula

Current International Association of Geodesy efforts within regional geoid determination include the comparison of different computation methods in the quest for the “1-cm geoid.” Internal (formal) and external (empirical) approaches to evaluate geoid errors exist, and ideally they should agree. Spherical radial base functions using the spline kernel (SK), least-squares collocation (LSC), and Stokes’s formula are three commonly used methods for regional geoid computation. The three methods have been shown to be theoretically equivalent, as well as to numerically agree on the millimeter level in a closed-loop environment using synthetic noise-free data (Ophaug and Gerlach in J Geod 91:1367–1382, 2017. 10.1007/s00190-017-1030-1). This companion paper extends the closed-loop method comparison using synthetic data, in that we investigate and compare the formal error propagation using the three methods. We use synthetic uncorrelated and correlated noise regimes, both on the 1-mGal ($$=10^{-5}~{\mathrm {m s}}^{-2}$$ = 10 - 5 m s - 2 ) level, applied to the input data. The estimated formal errors are validated by comparison with empirical errors, as determined from differences of the noisy geoid solutions to the noise-free solutions. We find that the error propagations of the methods are realistic in both uncorrelated and correlated noise regimes, albeit only when subjected to careful tuning, such as spectral band limitation and signal covariance adaptation. For the SKs, different implementations of the L-curve and generalized cross-validation methods did not provide an optimal regularization parameter. Although the obtained values led to a stabilized numerical system, this was not necessarily equivalent to obtaining the best solution. Using a regularization parameter governed by the agreement between formal and empirical error fields provided a solution of similar quality to the other methods. The errors in the uncorrelated regime are on the level of $$\sim $$ ∼ 5 mm and the method agreement within 1 mm, while the errors in the correlated regime are on the level of $$\sim $$ ∼ 10 mm, and the method agreement within 5 mm. Stokes’s formula generally gives the smallest error, closely followed by LSC and the SKs. To this effect, we note that error estimates from integration and estimation techniques must be interpreted differently, because the latter also take the signal characteristics into account. The high level of agreement gives us confidence in the applicability and comparability of formal errors resulting from the three methods. Finally, we present the error characteristics of geoid height differences derived from the three methods and discuss them qualitatively in relation to GNSS leveling. If applied to real data, this would permit identification of spatial scales for which height information is preferably derived by spirit leveling or GNSS leveling.

Comparing Methods to Constrain Future European Climate Projections Using a Consistent Framework

Political decisions, adaptation planning, and impact assessments need reliable estimates of future climate change and related uncertainties. To provide these estimates, different approaches to constrain, filter, or weight climate model projections into probabilistic distributions have been proposed. However, an assessment of multiple such methods to, for example, expose cases of agreement or disagreement, is often hindered by a lack of coordination, with methods focusing on a variety of variables, time periods, regions, or model pools. Here, a consistent framework is developed to allow a quantitative comparison of eight different methods; focus is given to summer temperature and precipitation change in three spatial regimes in Europe in 2041–60 relative to 1995–2014. The analysis draws on projections from several large ensembles, the CMIP5 multimodel ensemble, and perturbed physics ensembles, all using the high-emission scenario RCP8.5. The methods’ key features are summarized, assumptions are discussed, and resulting constrained distributions are presented. Method agreement is found to be dependent on the investigated region but is generally higher for median changes than for the uncertainty ranges. This study, therefore, highlights the importance of providing clear context about how different methods affect the assessed uncertainty—in particular, the upper and lower percentiles that are of interest to risk-averse stakeholders. The comparison also exposes cases in which diverse lines of evidence lead to diverging constraints; additional work is needed to understand how the underlying differences between methods lead to such disagreements and to provide clear guidance to users.

Agree to disagree: Examining the psychometrics of cybervetting

PurposeDue to the paucity of research on web-based job applicant screening (i.e. cybervetting), the purpose of the current study was to examine the psychometric properties of cybervetting, including an examination of the impact of adding structure to the rating process.Design/methodology/approachUsing a mixed-factorial design, 122 supervisors conducted cybervetting evaluations of applicant personality, cognitive ability, written communication skills, professionalism, and overall suitability. Cross-method agreement (i.e. the degree of similarity between cybervetting ratings and other assessment methods), as well as interrater reliability and agreement were examined, and unstructured versus structured cybervetting rating formats were compared.FindingsCybervetting assessments demonstrated high interrater reliability and interrater agreement, but only limited evidence of cross-method agreement was provided. In addition, adding structure to the cybervetting process did not enhance the psychometric properties of this assessment technique.Practical implicationsThis study highlighted that whereas cybervetting raters demonstrated a high degree of consensus in cybervetting-based attributions, there may be concerns regarding assessment accuracy, as cybervetting-based ratings generally differed from applicant test scores and self-assessment ratings. Thus, employers should use caution when utilizing this pre-employment screening technique.Originality/valueWhereas previous research has suggested that cybervetting ratings demonstrate convergence with other traditional assessments (albeit with relatively small effects), these correlational links do not provide information regarding cross-method agreement or method interchangeability. Thus, this study bridges a crucial gap in the literature by examining cross-method agreement for a variety of job-relevant constructs, as well as empirically testing the impact of adding structure to the cybervetting rating process.