摘要：Estimation of the postmortem interval (PMI) is a complicated task in forensic medicine, especially during homicide and unwitnessed death investigations. Many biological, chemical, and physical indicators can be used to determine the postmortem interval, but most are not accurate. Here, we present a novel matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) method that can be used for the estimation of PMI using molecular images and multivariate analyses. In this study, we demonstrate that both rat and human liver tissues of various PMIs (0, 2, 4, and 6days) can be discriminated using MALDI imaging and principal component analysis (PCA). Using genetic algorithm (GA), supervised neural network (SNN), and quick classifier (QC) methods, we built 6 classification models, which showed high recognition capability and good cross-validation. The histological changes in all the samples at different time points were also consistent with the changes seen in MALDI imaging. Our work suggests that MALDI-TOF MS, along with multivariate analysis, can be used to determine intermediate PMIs.
