Spatial frequency domain imaging for the longitudinal monitoring of vascularization during mouse femoral graft healing

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

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.

Co-registered speckle contrast optical tomography and frequency domain-diffuse optical tomography for imaging of the fifth metatarsal

A co-registered speckle contrast optical tomography and frequency domain-diffuse optical tomography system has been designed for imaging total hemoglobin concentration, blood oxygenation, and blood flow with the future aim of monitoring Jones fractures of the fifth metatarsal. Experimental validation was performed using both in vitro tissue-mimicking phantoms and in vivo cuff occlusion experiments. Results of these tissue phantom experiments ensure accurate recovery of three-dimensional distributions of optical properties and flow. Finally, cuff occlusion experiments performed on one healthy human subject demonstrate the system's ability to recover both decreasing tissue oxygenation and blood flow as caused by an arterial occlusion.

Semiparametric mixed-effects model for analysis of non-invasive longitudinal hemodynamic responses during bone graft healing

When dealing with longitudinal data, linear mixed-effects models (LMMs) are often used by researchers. However, LMMs are not always the most adequate models, especially if we expect a nonlinear relationship between the outcome and a continuous covariate. To allow for more flexibility, we propose the use of a semiparametric mixed-effects model to evaluate the overall treatment effect on the hemodynamic responses during bone graft healing and build a prediction model for the healing process. The model relies on a closed-form expectation–maximization algorithm, where the unknown nonlinear function is estimated using a Lasso-type procedure. Using this model, we were able to estimate the effect of time for individual mice in each group in a nonparametric fashion and the effect of the treatment while accounting for correlation between observations due to the repeated measurements. The treatment effect was found to be statistically significant, with the autograft group having higher total hemoglobin concentration than the allograft group.