Quantitative Characterization of Pulmonary Fat Emboli by Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) Spectroscopy and Partial Least-Squares (PLS) Regression: A Preliminary Study

Abstract

Fat emboli are a serious complication of trauma and bone fracture and may cause sudden death in affected patients. In forensic practice, fat emboli are commonly diagnosed based on a traditional method, adipose staining of lung tissues which is time-consuming and unquantitative. To address these concerns, attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) was employed in this study to diagnose fat emboli at different postmortem intervals. The absorption peak area ratio at 1743 cm⁻¹ and 2922 cm⁻¹ (A₁₇₄₃/A₂₉₂₂) was used to study the relationship among different emboli doses. This approach contributed to estimating the fat emboli dose when applied to fresh samples but failed for decomposed samples. However, satisfactory prediction performances were obtained using partial least-squares (PLS) regression with determination coefficients of prediction (R_p²) of 0.888 and 0.829 and root mean square errors of prediction (RMSEPs) of 0.115 and 0.139 ml/kg for fresh and decomposed samples, respectively. The spectral regions at approximately 2922 cm⁻¹, 2852 cm⁻¹, 1743 cm⁻¹, and 1159 cm⁻¹ played important roles in this model and were associated with asymmetrical and symmetrical lipid C-H stretching, C = O stretching, and C-O stretching modes, respectively. This study demonstrated the feasibility of utilizing FTIR spectroscopy and chemometrics as an attractive alternative for estimating the fat emboli dose and has potential their detection in forensic practice.

Keywords:

• Attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy
• fat embolism
• partial least-squares (PLS) regression
• peak area ratio

Disclosure statement

The authors declare that they have no conflicts of interest.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (81730056) and the Shanghai Key Lab of Forensic Medicine of Ministry of Justice National Science Foundation (KF202004).