Approximation of Antemortem Axial Temperature Distribution for Death-time Estimation
Description
Preliminary investigations suggest that antemortem axial temperature distribution in a body predicts the character of postmortem cooling by causing presence/absence of the postmortem temperature plateau. Antemortem axial temperature distribution is thus a less appreciated source of uncertainty in death-time estimation. Empiric methods of thermometric death-time estimation apply a 37°C single-point (rectal) approximation to represent antemortem body temperature. Numerical methods of death-time estimation apply 3D human phantoms of often relatively low anatomical segmentation, as well as varying bioheat techniques when approximating antemortem temperature distribution. Often, simulation of postmortem cooling used to estimate the death interval is conducted in continuity with approximation of antemortem body temperature distribution. This paper proposes separation of approximation of antemortem temperature distribution by using a high-definition 3D human computational phantom with 247 anatomically segmented organs, by applying the Pennes bioheat model, and by applying metabolic heat-generation and blood perfusion rates as additional organ parameters. Results indicated that the approximated antemortem temperature was inhomogeneous, with wide temperature variations documented on the skin. The approximated axial temperature varied according to location, size, shape and metabolic rate of organs in a given axial section. Regions of heart muscle, kidneys and extra-pelvic muscles showed high temperatures in axial planes of the chest, abdomen and pelvis, respectively. Axial temperature transition from the body core to skin was nonlinear. This paper proposes approximation of the antemortem physical exertion from death scene investigation, determination of its metabolic equivalent value, and proportional distribution to exertion-involved organs.
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Approximation of Antemortem Axial Temperature Distribution for Death-time Estimation.pdf
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