Predictive equation to estimate post-mortem interval using spectrophotometric blood-colour values

Yosuke Usumoto, Keiko Kudo, Akiko Tsuji, Yoko Ihama, Noriaki Ikeda

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Forensic pathologists use post-mortem phenomena to estimate the post-mortem interval (PMI). We have reported on the usefulness of post-mortem lividity spectrophotometric values to estimate PMIs. Here, we focused on blood colour, looking for associations between blood colour, age and PMI. We generated predictive equations for blood-colour values and the PMI. We included data from a total of 129 cadavers (84 males and 45 females). We measured the colour of 124 left ventricular blood (L*l, a*l, b*l), 123 right ventricular blood (L*r, a*r, b*r) and 57 femoral blood (L*f, a*f, b*f) samples. We found no significant associations between blood colour and age or between blood colour and the PMI, but the values of a*l, b*l, a*r and b*r were significantly increased with increased age, and those of L*f, a*f and b*f were significantly decreased with increased PMI. We created equations to estimate blood colour. The equations for femoral blood colour had higher adjusted R2 values and lower root mean square error values than those for left and right ventricular blood colours. We generated equations to estimate PMIs using blood-colour values and autopsy findings. Our estimated PMIs up to 67 hours had accuracies within 8.84 hours, without measuring post-mortem lividity colour or considering the age of the deceased. This is the first study to estimate PMIs based on blood-colour spectrophotometric values.

Original languageEnglish
Pages (from-to)36-41
Number of pages6
JournalMedicine, Science and the Law
Issue number1
Publication statusPublished - Jan 1 2019

All Science Journal Classification (ASJC) codes

  • Issues, ethics and legal aspects
  • Health Policy
  • Law


Dive into the research topics of 'Predictive equation to estimate post-mortem interval using spectrophotometric blood-colour values'. Together they form a unique fingerprint.

Cite this