Quantification of tissue healing in a murine model using enhanced thermal imaging (ETI) and MCmatlab simulations

Tissue ischemia caused by the inadequate reperfusion of capillary beds is a fundamental cause of complications following reconstructive microsurgery. Clinicians have historically relied on visual and tactile assessment to evaluate perfusion. Recently, indocyanine green angiography (ICGA) has been implemented during some procedures to map blood vessels in real-time. ICGA requires the IV administration of a fluorescent dye that can be expensive and poorly tolerated by some patients. There is a need for a cheaper, more versatile tool that can image vasculature intraoperatively and help monitor healing at the bedside. Enhanced thermal imaging (ETI) is an infrared imaging technique that uses green LEDs to induce a natural thermal contrast between blood and surrounding water-rich tissue. A previous study demonstrated the potential of ETI to detect capillary growth as an indicator of early wound healing within skin flaps in a murine model. In this study, MCmatlab—a MATLAB-interfaced Monte Carlo simulation with a 3D finite element solver—was used to model heat deposition and diffusion in a model containing vessels embedded in a water-rich tissue. The relationship between vessel density and the thermal signal observed at the tissue surface suggests the response captured by ETI is related to the angiogenetic burst intrinsic to the healing process. ETI offers a promising solution for intraoperative guidance and point-of-care diagnosis of tissue perfusion.