Monte Carlo simulations and phantom modeling for spatial frequency domain imaging of surgical wound monitoring

J Biomed Opt. 2023 Dec;28(12):126003. doi: 10.1117/1.JBO.28.12.126003. Epub 2023 Dec 14.

Abstract

Significance: Postoperative surgical wound infection is a serious problem around the globe, including in countries with advanced healthcare systems, and a method for early detection of infection is urgently required.

Aim: We explore spatial frequency domain imaging (SFDI) for distinguishing changes in surgical wound healing based on the tissue scattering properties and surgical wound width measurements.

Approach: A comprehensive numerical method is developed by applying a three-dimensional Monte Carlo simulation to a vertical heterogeneous wound model. The Monte Carlo simulation results are validated using resin phantom imaging experiments.

Results: We report on the SFDI lateral resolution with varying reduced scattering value and wound width and discuss the partial volume effect at the sharp vertical boundaries present in a surgical incision. The detection sensitivity of this method is dependent on spatial frequency, wound reduced scattering coefficient, and wound width.

Conclusions: We provide guidelines for future SFDI instrument design and explanation for the expected error in SFDI measurements.

Keywords: Monte Carlo; biomedical imaging; photon diffusion; spatial frequency domain imaging; surgical wound.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computer Simulation
  • Diagnostic Imaging
  • Humans
  • Monte Carlo Method
  • Phantoms, Imaging
  • Surgical Wound*