Repeatability and Reproducibility Uncertainty in Magnetic Resonance-Based Electric Properties Tomography of a Homogeneous Phantom.

Uncertainty assessment is a fundamental step in quantitative magnetic resonance imaging because it makes comparable, in a strict metrological sense, the results of different scans, for example during a longitudinal study. Magnetic resonance-based electric properties tomography (EPT) is a quantitative imaging technique that retrieves, non-invasively, a map of the electric properties inside a human body. Although EPT has been used in some early clinical studies, a rigorous experimental assessment of the associated uncertainty has not yet been performed. This paper aims at evaluating the repeatability and reproducibility uncertainties in phase-based Helmholtz-EPT applied on homogeneous phantom data acquired with a clinical 3 T scanner. The law of propagation of uncertainty is used to evaluate the uncertainty in the estimated conductivity values starting from the uncertainty in the acquired scans, which is quantified through a robust James-Stein shrinkage estimator to deal with the dimensionality of the problem. Repeatable errors are detected in the estimated conductivity maps and are quantified for various values of the tunable parameters of the EPT implementation. The spatial dispersion of the estimated electric conductivity maps is found to be a good approximation of the reproducibility uncertainty, evaluated by changing the position of the phantom after each scan. The results underpin the use of the average conductivity (calculated by weighting the local conductivity values by their uncertainty and taking into account the spatial correlation) as an estimate of the conductivity of the homogeneous phantom.

Interlaboratory comparison of the intensity of drinking water odor and taste by two-way ordinal analysis of variation without replication.

A case study of ordinal data from human organoleptic examination (sensory analysis) of drinking water obtained in an interlaboratory comparison of 49 ecological laboratories is described. The recently developed two-way ordinal analysis of variation (ORDANOVA) is applied for the first time for the treatment of responses on the intensity of chlorine and sulfurous odor of water at 20 and 60 °C, which is classified into the six categories from 'imperceptible' to 'very strong'. The one-way ORDANOVA is used for the analysis of the 'salty taste' intensity of the water. A decomposition of the total variation of the ordinal data and simulation of the multinomial distribution of the data-relative frequencies in different categories allowed the determination of the statistical significance of the difference between laboratories in classifying chlorine or sulfurous odor intensity by categories, while the effect of temperature was not significant. No statistical difference was found between laboratories on salty taste intensity. The capabilities of experts to identify different categories of the intensity of the odor and taste are also evaluated. A comparison of the results obtained with ORDANOVA and ANOVA showed that ORDANOVA is a more useful and reliable tool for understanding categorical data such as the intensity of drinking water odor and taste.

Total risk of a false decision on conformity of an alloy due to measurement uncertainty and correlation of test results.

Total risk (probability) of a false decision on conformity of an alloy due to measurement uncertainty and correlation of test results is quantified. As an example, a dataset of test results of a PtRh alloy is studied when contents of four components of the alloy composition are under control. There are specification limits for contents of 1) Pt and 2) Rh; 3) three precious impurities - Au, Ir and Pd, and 4) eight impurities, both precious Au, Ir, Pd, and non-precious Fe, Pb, Si, Sn, Zn. Test results of 100 batches of the alloy produced at the same plant, obtained by X-ray fluorescence and optical atomic emission spectrometry methods at the plant laboratory, were in the dataset. The Pt content was tested based on the mass balance. Measurement uncertainties of the test results are estimated summarizing data of validation reports of the measurement procedures for different elements/analytes. These test results are correlated because of the natural chemical origin of the raw materials used in the alloy production and mass balance constraints. Correlations between test results for two pairs of the components (Pt vs. Rh, and the three vs. the eight impurities) were strong. To assess the correlation effects on the total risk, the study was performed for two scenarios considering 1) correlated test results for all four components, and 2) practically uncorrelated test results for two components only - Rh and the eight impurities. A multiparameter Bayesian approach was applied for total risk evaluation, where the observed correlations are taken into account within the experimental correlation matrix. This matrix influenced all subsequent multivariate calculation results. It was shown that simplification of the testing by reducing the number of components under control leads to a significant increase of the probability of a false decision on conformity of an alloy batch randomly drawn from a statistical population of such batches. Core of the developed R code, used for the risk calculations, is presented.

Risk of a false decision on conformity of an environmental compartment due to measurement uncertainty of concentrations of two or more pollutants.

Risks of false decisions in conformity assessment of an environmental compartment due to measurement uncertainty of concentrations of two or more pollutants are discussed. Even if the assessment of conformity for each pollutant in the compartment is successful, the total probability of a false decision concerning the compartment as a whole might still be significant. A model of the total probability of a false decision, formulated on the base of the law of total probability, is used, for example, for a study of test results of total suspended particulate matter (TSPM) concentration in ambient air near to three independent stone quarries located in Israel, as the sources of the air pollution. Total probabilities of underestimation of TSPM concentration (total risk of the inhabitants) and overestimation (total risk of the stone producers) are evaluated as a combination of the particular risks of air conformity assessment concerning TSPM concentration for each quarry. These probabilities characterize conformity of the TSPM concentration in the region of the quarries as a whole. Core code developed in R programming environment for the calculations is provided.

Risk of false decision on conformity of a multicomponent material when test results of the components' content are correlated.

The probability of a false decision on conformity of a multicomponent material due to measurement uncertainty is discussed when test results are correlated. Specification limits of the components' content of such a material generate a multivariate specification interval/domain. When true values of components' content and corresponding test results are modelled by multivariate distributions (e.g. by multivariate normal distributions), a total global risk of a false decision on the material conformity can be evaluated based on calculation of integrals of their joint probability density function. No transformation of the raw data is required for that. A total specific risk can be evaluated as the joint posterior cumulative function of true values of a specific batch or lot lying outside the multivariate specification domain, when the vector of test results, obtained for the lot, is inside this domain. It was shown, using a case study of four components under control in a drug, that the correlation influence on the risk value is not easily predictable. To assess this influence, the evaluated total risk values were compared with those calculated for independent test results and also with those assuming much stronger correlation than that observed. While the observed statistically significant correlation did not lead to a visible difference in the total risk values in comparison to the independent test results, the stronger correlation among the variables caused either the total risk decreasing or its increasing, depending on the actual values of the test results.

Conformity assessment of multicomponent materials or objects: Risk of false decisions due to measurement uncertainty - A case study of denatured alcohols.

Risk of a false decision on conformity of a multicomponent material or object due to measurement uncertainty is discussed. Even if conformity assessment for each component of a material sample is successful, the total probability of a false decision (total consumer's risk or producer's risk) concerning the sample as a whole might still be significant. A model of the total probability of such false decisions is formulated based on the law (theorem) of total probability. It is shown that the total risk can be evaluated as a combination of the particular risks of conformity assessment of sample components. For a more complicated task, i.e. for a larger number of components of a sample under control, the total risk is greater. As a case study, the total probability of false conforming (total consumer's risk) is evaluated for customs control of completely denatured alcohols, where conformity assessment is performed by comparison of chemical analytical test results with the regulatory limits.

Uncertainty evaluation for the quantification of low masses of benzo[a]pyrene: Comparison between the Law of Propagation of Uncertainty and the Monte Carlo method.

A proper evaluation of the uncertainty associated to the quantification of micropollutants in the environment, like Polycyclic Aromatic Hydrocarbons (PAHs), is crucial for the reliability of the measurement results. The present work describes a comparison between the uncertainty evaluation carried out according to the GUM uncertainty framework and the Monte Carlo (MC) method. This comparison was carried out starting from real data sets obtained from the quantification of benzo[a]pyrene (BaP), spiked on filters commonly used for airborne particulate matter sampling. BaP was chosen as target analyte as it is listed in the current European legislation as marker of the carcinogenic risk for the whole class of PAHs. MC method, being useful for nonlinear models and when the resulting output distribution for the measurand is non-symmetric, can particularly fit the cases in which the results of intrinsically positive quantities are very small and the lower limit of a desired coverage interval, obtained according to the GUM uncertainty framework, can be dramatically close to zero, if not even negative. In the case under study, it was observed that the two approaches for the uncertainty evaluation provide different results for BaP masses in samples containing different masses of the analyte, MC method giving larger coverage intervals. In addition, in cases of analyte masses close to zero, the GUM uncertainty framework would give even negative lower limit of uncertainty coverage interval for the measurand, an unphysical result which is avoided when using MC method. MC simulations, indeed, can be configured in a way that only positive values are generated thus obtaining a coverage interval for the measurand that is always positive.

An infrared spectroscopy method to detect ammonia in gastric juice.

Ammonia in gastric juice is considered a potential biomarker for Helicobacter pylori infection and as a factor contributing to gastric mucosal injury. High ammonia concentrations are also found in patients with chronic renal failure, peptic ulcer disease, and chronic gastritis. Rapid and specific methods for ammonia detection are urgently required by the medical community. Here we present a method to detect ammonia directly in gastric juice based on Fourier transform infrared spectroscopy. The ammonia dissolved in biological liquid samples as ammonium ion was released in air as a gas by the shifting of the pH equilibrium of the ammonium/ammonia reaction and was detected in line by a Fourier transform infrared spectroscopy system equipped with a gas cell for the quantification. The method developed provided high sensitivity and selectivity in ammonia detection both in pure standard solutions and in a simulated gastric juice matrix over the range of diagnostic concentrations tested. Preliminary analyses were also performed on real gastric juice samples from patients with gastric mucosal injury and with symptoms of H. pylori infection, and the results were in agreement with the clinicopathology information. The whole analysis, performed in less than 10 min, can be directly applied on the sample without extraction procedures and it ensures high specificity of detection because of the ammonia fingerprint absorption bands in the infrared spectrum. This method could be easily used with endoscopy instrumentation to provide information in real time and would enable the endoscopist to improve and integrate gastroscopic examinations.

Monte Carlo simulation of expert judgments on human errors in chemical analysis--a case study of ICP-MS.

Monte Carlo simulation of expert judgments on human errors in a chemical analysis was used for determination of distributions of the error quantification scores (scores of likelihood and severity, and scores of effectiveness of a laboratory quality system in prevention of the errors). The simulation was based on modeling of an expert behavior: confident, reasonably doubting and irresolute expert judgments were taken into account by means of different probability mass functions (pmfs). As a case study, 36 scenarios of human errors which may occur in elemental analysis of geological samples by ICP-MS were examined. Characteristics of the score distributions for three pmfs of an expert behavior were compared. Variability of the scores, as standard deviation of the simulated score values from the distribution mean, was used for assessment of the score robustness. A range of the score values, calculated directly from elicited data and simulated by a Monte Carlo method for different pmfs, was also discussed from the robustness point of view. It was shown that robustness of the scores, obtained in the case study, can be assessed as satisfactory for the quality risk management and improvement of a laboratory quality system against human errors.

Columnar cell lesions associated with breast calcifications on vacuum-assisted core biopsies: clinical, radiographic, and histological correlations.

Columnar cell lesions of the breast are increasingly recognized at mammography for their tendency to calcify. We studied 392 vacuum-assisted core biopsies performed solely for calcifications to evaluate the frequency of columnar cell lesions, their relationship with radiological risk, appearance of calcifications, and clinical data. Management and follow-up of columnar cell lesions without and with atypia (flat epithelial atypia) was analyzed. Cases with architectural atypia (cribriform spaces and/or micropapillae) were excluded from flat epithelial atypia. Calcifications were within the lumen of acini affected by columnar cell lesions in 137 out of 156 biopsies diagnosed with some columnar cell lesions. These represented 37% of vacuum-assisted core biopsies and 62% of low radiological risk (BI-RADS3) calcifications. High-risk (BI-RADS5) calcifications were never associated with columnar cell lesions. Age and menopausal status were comparable in columnar and in not-columnar cell lesions. Atypia was associated with long-term hormone replacement therapy in both lesions. Surgical biopsy was recommended for all cases with atypia. Flat epithelial atypia, as the only histological findings on vacuum-assisted core biopsies, was never associated with malignancy at surgery. In conclusion, we suggest that surgical excision is not mandatory when flat epithelial atypia is found as the most advanced lesion on vacuum-assisted core biopsy performed for low radiological risk calcifications, and that women should be advised of the possible hormone dependency of this entity.