Investigation of Postmortem Gases: A Forensic Imaging and Analytical Chemistry Approach

Background: Distinguishing postmortem gas accumulations in the body due to natural decomposition and other phenomena such as gas embolism can prove a difficult task using purely Multi-Detector Computed Tomography (MDCT). The Radiological Alteration Index (RAI) was created with the intention to be able to identify bodies undergoing the putrefaction process based on the quantity of gas detected within the body. The flaw in this approach is the inability to absolutely determine putrefaction as the origin of gas volumes in cases of moderate alteration. The aim of the current study is to identify percentage compositions of O2, N2, CO2 and the presence of gases such as H2 and H2S within these sampling sites in order to resolve this complication. Materials and methods: All cases investigated in our University Center of Legal Medicine are undergoing a Post-Mortem Computed Tomography (PMCT)-scan before external examination or autopsy as a routine investigation. In the obtained images, areas of gas were characterized as 0, I, II or III based on the amount of gas present according to the RAI (1). The criteria for these characterizations were dependent of the site of gas, for example thoracic and abdominal cavities were graded as I (1 - 3cm gas), II (3 - 5cm gas) and III (>5cm gas). Cases showing gaseous sites with grade II or III were selected for this study. The sampling was performed under CT-guidance to target the regions to be punctured. Luer-lock PTFE syringes equipped with a three-way valve and needles were used to sample the gas directly (2). Gaseous samples were then analysed using gas chromatography coupled to a thermal conductivity detector (GC-TCD). The components present in the samples were expressed as a percentage of the overall gas present. Results: Up to now, we have investigated more than 40 cases using our standardized procedure for sampling and analysis of gas. O2, N2 and CO2 were present in most samples. The following distributions were found to correlate to gas origins of gas embolism/scuba diving accidents, trauma and putrefaction: ? Putrefaction → O2 = 1 - 5%; CO2 > 15%; N2 = 10 - 70%; H2 / H2S / CH4 variable presence ? Gas embolism/Scuba diving accidents → O2 and N2= varying percentages; CO2 > 20% ? Trauma → O2 = small percentage; CO2 < 15%; N2 > 65% H2 and H2S indicated levels of putrefaction along with methane which can also gauge environmental conditions or conditions of body storage/burial. Many cases showing large RAI values (advanced alteration) did reveal a radiological diagnosis which was in concordance with the interpretation of the gas composition. However, in certain cases (gas embolism, scuba divers) radiological interpretation was not possible and only chemical gas analysis was found to lead to the correct diagnosis, meaning that it provided complementary information to the radiological diagnosis. Conclusion: Investigation of postmortem gases is a useful tool to determine origin of gas generation which can aid the diagnosis of the cause of death. Levels of gas can provide information on stage of putrefaction and help to perform essential medico-legal diagnosis such as vital gas embolism.

Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science

Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. Includes self-contained introductions to probability and decision theory. Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. Features implementation of the methodology with reference to commercial and academically available software. Presents standard networks and their extensions that can be easily implemented and that can assist in the reader's own analysis of real cases. Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

The application of chemometrics on Infrared and Raman spectra as a tool for the forensic analysis of paints

The aim of this work is to evaluate the capabilities and limitations of chemometric methods and other mathematical treatments applied on spectroscopic data and more specifically on paint samples. The uniqueness of the spectroscopic data comes from the fact that they are multivariate - a few thousands variables - and highly correlated. Statistical methods are used to study and discriminate samples. A collection of 34 red paint samples was measured by Infrared and Raman spectroscopy. Data pretreatment and variable selection demonstrated that the use of Standard Normal Variate (SNV), together with removal of the noisy variables by a selection of the wavelengths from 650 to 1830 cm−1 and 2730-3600 cm−1, provided the optimal results for infrared analysis. Principal component analysis (PCA) and hierarchical clusters analysis (HCA) were then used as exploratory techniques to provide evidence of structure in the data, cluster, or detect outliers. With the FTIR spectra, the Principal Components (PCs) correspond to binder types and the presence/absence of calcium carbonate. 83% of the total variance is explained by the four first PCs. As for the Raman spectra, we observe six different clusters corresponding to the different pigment compositions when plotting the first two PCs, which account for 37% and 20% respectively of the total variance. In conclusion, the use of chemometrics for the forensic analysis of paints provides a valuable tool for objective decision-making, a reduction of the possible classification errors, and a better efficiency, having robust results with time saving data treatments.

A collaborative approach for incorporating forensic case data into crime investigation using criminal intelligence analysis and visualisation

There is an increasing awareness that the articulation of forensic science and criminal investigation is critical to the resolution of crimes. However, models and methods to support an effective collaboration between these partners are still poorly expressed or even lacking. Three propositions are borrowed from crime intelligence methods in order to bridge this gap: (a) the general intelligence process, (b) the analyses of investigative problems along principal perspectives: entities and their relationships, time and space, quantitative aspects and (c) visualisation methods as a mode of expression of a problem in these dimensions. Indeed, in a collaborative framework, different kinds of visualisations integrating forensic case data can play a central role for supporting decisions. Among them, link-charts are scrutinised for their abilities to structure and ease the analysis of a case by describing how relevant entities are connected. However, designing an informative chart that does not bias the reasoning process is not straightforward. Using visualisation as a catalyser for a collaborative approach integrating forensic data thus calls for better specifications.

New Horizons in Forensic Imaging: Post Mortem CT Angiography - Benefits and Practical Application.

Puropse/Aim: To learn about the developement of post mortem CT angiography, its indications, benefits, pitfalls and practical application. Content Organization: A. Developement of post mortem CT angiography B. Technical prerequisites C. Practical application of post mortem CT angiography (preparation of the body, injection of contrast agent, examination protocol) D. Indications and benefits (including a comparison with conventional autopsy) E. Interpretation of imaging data (with case demonstrations) F. Artifacts, pitfalls and limitations G. Current and potential future use. Summary: This exhibit demonstrates the developement, application and interpretation of post mortem CT angiography. Teaching points: 1. post mortem CT angiography is feasible and useful for identification of the cause of death 2. depending on the indication it can be superior to autopsy 3. limitations and artifacts need to be known for interpreta

L'éthique et les sciences humaines ne sont pas des sciences vassales. Débat: projet triangulaire des universités lémaniques

Le temps des tours d'ivoire est révolu, constate Denis Müller, professeur d'éthique à l'Université de Lausanne.Il plaide pour une véritable complémentarité entre sciences humaines et sciences de la vie.

Decision-theoretic analysis of forensic sampling criteria using Bayesian decision networks

Sampling issues represent a topic of ongoing interest to the forensic science community essentially because of their crucial role in laboratory planning and working protocols. For this purpose, forensic literature described thorough (Bayesian) probabilistic sampling approaches. These are now widely implemented in practice. They allow, for instance, to obtain probability statements that parameters of interest (e.g., the proportion of a seizure of items that present particular features, such as an illegal substance) satisfy particular criteria (e.g., a threshold or an otherwise limiting value). Currently, there are many approaches that allow one to derive probability statements relating to a population proportion, but questions on how a forensic decision maker - typically a client of a forensic examination or a scientist acting on behalf of a client - ought actually to decide about a proportion or a sample size, remained largely unexplored to date. The research presented here intends to address methodology from decision theory that may help to cope usefully with the wide range of sampling issues typically encountered in forensic science applications. The procedures explored in this paper enable scientists to address a variety of concepts such as the (net) value of sample information, the (expected) value of sample information or the (expected) decision loss. All of these aspects directly relate to questions that are regularly encountered in casework. Besides probability theory and Bayesian inference, the proposed approach requires some additional elements from decision theory that may increase the efforts needed for practical implementation. In view of this challenge, the present paper will emphasise the merits of graphical modelling concepts, such as decision trees and Bayesian decision networks. These can support forensic scientists in applying the methodology in practice. How this may be achieved is illustrated with several examples. The graphical devices invoked here also serve the purpose of supporting the discussion of the similarities, differences and complementary aspects of existing Bayesian probabilistic sampling criteria and the decision-theoretic approach proposed throughout this paper.