Identifying reliable ions for the statistical differentiation of structurally similar fentanyl analogs

Definitive identification of fentanyl analogs based on mass spectral comparison is challenging given the high degree of structural and, hence, spectral similarity. To address this, a statistical method was previously developed in which two electron-ionization (EI) mass spectra are compared using the unequal variance t-test. Normalized intensities of corresponding ions are compared, testing the null hypothesis (H0 ) that the difference in intensity is equal to zero. If H0 is accepted at all m/z values, the two spectra are statistically equivalent at the specified confidence level. If H0 is not accepted at any m/z value, then there is a significant difference in intensity at that m/z value between the two spectra. In this work, the statistical comparison method is applied to distinguish EI spectra of valeryl fentanyl, isovaleryl fentanyl, and pivaloyl fentanyl. Spectra of the three analogs were collected over a 9-month period and at different concentrations. At the 99.9% confidence level, the spectra of corresponding isomers were statistically associated. Spectra of different isomers were statistically distinct, and ions responsible for discrimination were identified in each comparison. To account for inherent instrument variations, discriminating ions for each pairwise comparison were ranked based on the magnitude of the calculated t-statistic (tcalc ) value. For a given comparison, ions with higher tcalc values are those with the greatest difference in intensity between the two spectra and, therefore, are considered more reliable for discrimination. Using these methods, objective discrimination among the spectra was achieved and ions considered most reliable for discrimination of these isomers were identified.

Objective Analysis of Impressed Chisel Toolmarks

Historical and recent challenges to the practice of comparative forensic examination have created a driving force for the formation of objective methods for toolmark identification. In this study, fifty sequentially manufactured chisels were used to create impression toolmarks in lead (500 toolmarks total). An algorithm previously used to statistically separate known matching and nonmatching striated screwdriver marks and quasi-striated plier marks was used to evaluate the chisel marks. Impression toolmarks, a more complex form of toolmark, pose a more difficult test for the algorithm that was originally designed for striated toolmarks. Results show in this instance that the algorithm can separate matching and nonmatching impression marks, providing further validation of the assumption that toolmarks are identifiably unique.

Angular Determination of Toolmarks Using a Computer-Generated Virtual Tool

A blind study to determine whether virtual toolmarks created using a computer could be used to identify and characterize angle of incidence of physical toolmarks was conducted. Six sequentially manufactured screwdriver tips and one random screwdriver were used to create toolmarks at various angles. An apparatus controlled tool angle. Resultant toolmarks were randomly coded and sent to the researchers, who scanned both tips and toolmarks using an optical profilometer to obtain 3D topography data. Developed software was used to create virtual marks based on the tool topography data. Virtual marks generated at angles from 30 to 85° (5° increments) were compared to physical toolmarks using a statistical algorithm. Twenty of twenty toolmarks were correctly identified by the algorithm. On average, the algorithm misidentified the correct angle of incidence by -6.12°. This study presents the results, their significance, and offers reasons for the average angular misidentification.

Optimization of a statistical algorithm for objective comparison of toolmarks

Due to historical legal challenges, there is a driving force for the development of objective methods of forensic toolmark identification. This study utilizes an algorithm to separate matching and nonmatching shear cut toolmarks created using fifty sequentially manufactured pliers. Unlike previously analyzed striated screwdriver marks, shear cut marks contain discontinuous groups of striations, posing a more difficult test of algorithm applicability. The algorithm compares correlation between optical 3D toolmark topography data, producing a Wilcoxon rank sum test statistic. Relative magnitude of this metric separates the matching and nonmatching toolmarks. Results show a high degree of statistical separation between matching and nonmatching distributions. Further separation is achieved with optimized input parameters and implementation of a "leash" preventing a previous source of outliers--however complete statistical separation was not achieved. This paper represents further development of objective methods of toolmark identification and further validation of the assumption that toolmarks are identifiably unique.