Evaluating the effects of causes of death on postmortem interval estimation by ATR-FTIR spectroscopy

Estimating postmortem interval (PMI) is one of the most challenging tasks in forensic practice due to the effects of many factors. Here, attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy combined with chemometrics was utilized to evaluate the effects of causes of death when estimating PMI and to establish a partial least square (PLS) regression model, which can precisely predict PMI under different causes of death. First, the sensitivities to causes of death (brainstem injury, mechanical asphyxia, and hemorrhage shock) of seven kinds of organs were evaluated based on their degrees of cohesion and separation. Then, the liver was selected as the most sensitive organ to establish a PMI estimation model to compare the predicted deviations from different causes of death. It turns out that the cause of death has no significant effect on estimating PMI. Next, a PLS regression model was built with kidney tissues, which have the lowest sensitivity, and this model showed a satisfactory predictive ability and wide applicability. This study demonstrates the feasibility of using ATR-FTIR spectroscopy in conjunction with chemometrics as a powerful alternative for detecting changes in biochemistry and estimating PMI. A new perspective was also provided for evaluating the effect of causes of death when predicting PMI.