Mathematical modeling and analysis for tissue curvature correction in near-infrared spectroscopy imaging

Near-infrared spectroscopy (NIRS) imaging modalities are used to provide noncontact measurements of tissue oxygenation in diabetic foot ulcers. However, the curved surface of the diabetic foot introduces inaccurate tissue oxygenation measurement. The changes in spatial NIRS optical measurements may result from variations in the underlying physiology or from the curvature of the tissue surface. Therefore, the effect of tissue curvature must be accounted for to ensure the accurate measurement of tissue oxygenation (or hemoglobin parameters) in clinical applications.

Our aim is to develop and validate mathematical curvature correction models to account for the effects of tissue curvature on diffuse reflectance (DR) in NIRS imaging and assess their effect on the hemoglobin parameters as well.

Monte-Carlo-based light propagation simulations were performed to develop correction models and applied to three-layered curved geometries in MCMatlab. Four curvature correction models based on height and/or angle were developed via Monte Carlo simulation studies. All the correction models were applied to the simulated DR signals obtained from various curved geometries (concave, convex, and wound-mimicking) using Gaussian light sources at 690 and 830 nm. The effect of correction models on DR signals and hemoglobin parameters was determined.

Simulation results showed that a concave curved surface did not require correction, whereas convex and wound-mimicking geometries showed a reduced median error upon using an empirical height/angle correction model. In addition, the correction model also reduced the median error significantly for the oxygen-saturation-based hemoglobin parameter in both the convex and wound-mimicking geometries.

The developed mathematical model effectively corrected tissue curvature effects in NIRS DR signals and hemoglobin parameters for wound-mimicking irregular geometry. Ongoing work focuses on experimental validation of these correction models on curved phantoms, prior to in vivo imaging studies.