A number of definitions of multivariate selectivity have been proposed in the literature. Arguably, the one that enjoys the greatest chemometric attention has been the net analyte signal (NAS) based definitions of Lorber and Zinn. Recent works have suggested that similar inference can be made for inverse least-squares calibration methods (e.g., principal components regression). However, the properties of inverse calibration methods are markedly different than classical methods, so in many practical cases involving inverse models classically derived figures of merit cannot be transparently interpreted. In Part I of this work, we discuss a selectivity framework that is theoretically consistent regardless of the calibration method. Importantly, it is also experimentally measurable, either through controlled selectivity experiments, or through analysis on opportunistically acquired sample measurements. It is statistically advantageous to use the former if such control is achievable. Selectivity is defined to be a function of the change in predicted analyte concentration that will result from a change in the concentration of an interferant, an approach consistent with traditional definitions of analytical selectivity and National Committee for Clinical Laboratory Standards recommendations for interference testing. Unlike the NAS-based definition of selectivity, the definition discussed herein is relevant to only a particular analyte-interferant pair. The theoretical and experimental aspects of this approach are illustrated with simulated data herein and in Part II of this paper, which investigates several experimental near-infrared data sets.
In Part I of this paper, a framework for multivariate selectivity was introduced that is both calculable from first principles and experimentally tractable. In this part, we employ the proposed selectivity framework for analyzing both in vitro and in vivo near-infrared experimental data. Two in vitro data sets are used to compare different methods for estimating selectivity and to demonstrate the benefits obtained from validation data with expanded interferant concentration ranges. The in vitro data also demonstrate that the experimentally estimated selectivities provide insights into the properties of the calibration models that are difficult or impossible to infer by other means. The merits of the proposed selectivity function are further demonstrated using a complex in vivo application: the noninvasive measurement of ethanol in humans. Results indicate that in vivo calibration model sensitivity, selectivity, and concentration correlations can be systematically interrogated using the proposed selectivity framework and judicious use of experimental measurements. These analyses not only provide selectivity and sensitivity information, but also the variance components of the total MSEP, which is invaluable information for both method development and analytical method characterization.
A diffuse reflectance near-infrared (NIR) spectrometer was evaluated as a noninvasive alternative to breath and blood measurements for in vivo alcohol testing. A hybrid partial least squares (PLS) calibration was constructed using a combination of in vivo and in vitro spectral data. This model was subsequently evaluated for its performance in quantifying alcohol concentrations in vivo using a prospective validation study involving subjects who did not participate in the calibration. The validation study entailed induction of alcohol excursions in ten human subjects and comparison of the noninvasive NIR alcohol measurements to blood and breath alcohol measurements. Blood and breath alcohol measurements were performed at the time of each noninvasive NIR measurement (N = 372), establishing the noninvasive NIR measurement standard error relative to blood alcohol at 4.9 mg/dL (0.0049%). Assessment of the hybrid calibration model's sensitivity and selectivity provided strong evidence that the hybrid calibration yielded measurements that were both sensitive to alcohol and independent of other absorbing analytes in human tissue.
Abstract. Alcohol testing is an expanding area of interest due to the impacts of alcohol abuse that extend well beyond drunk driving. However, existing approaches such as blood and urine assays are hampered in some testing environments by biohazard risks. A noninvasive, in vivo spectroscopic technique offers a promising alternative, as no body fluids are required. The purpose of this work is to report the results of a 36-subject clinical study designed to characterize tissue alcohol measured using near-infrared spectroscopy relative to venous blood, capillary blood, and breath alcohol. Comparison of blood and breath alcohol concentrations demonstrated significant differences in alcohol concentration ͓root mean square of 9.0 to 13.5 mg/ dL͔ that were attributable to both assay accuracy and precision as well as alcohol pharmacokinetics. A first-order kinetic model was used to estimate the contribution of alcohol pharmacokinetics to the differences in concentration observed between the blood, breath, and tissue assays. All pair-wise combinations of alcohol assays were investigated, and the fraction of the alcohol concentration variance explained by pharmacokinetics ranged from 41.0% to 83.5%. Accounting for pharmacokinetic concentration differences, the accuracy and precision of the spectroscopic tissue assay were found to be comparable to those of the blood and breath assays.
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