We report the integrated use of 3D second harmonic generation (SHG) imaging microscopy and Monte Carlo simulation as a combined metric to quantifiably differentiate normal and diseased tissues based on the physical properties of the respective extracellular matrix. To achieve this, we have identified a set of parameters comprised of the SHG creation attributes and the bulk optical parameters, which are used collectively via comparative analysis. Monte Carlo simulations of the SHG axial directional and attenuation responses allow their decomposition into the underlying factors that are not readily obtainable through experimental techniques. Specifically, this approach allows for estimation of the SHG creation attributes (directionality and relative conversion efficiency) and separation of primary and secondary filter effects, collectively that form the observed SHG contrast. The quantitative metric is shown for the connective tissue disorder Osteogenesis Imperfecta (characterized by abnormal assembly of type I collagen) using a murine model that expresses the disease in the dermis layer of skin. Structural dissimilarities between the osteogenesis imperfecta mouse and wild-type tissues lead to significant differences in the SHG depth-dependent directionality and signal attenuation. The Monte Carlo simulations of these responses using measured bulk optical parameters reproduce the experimental data trends, and the extracted emission directionality and conversion efficiencies are consistent with independent determinations. The simulations also illustrate the dominance of primary filter affects on overall SHG generation and attenuation. Thus, the combined method of 3D SHG imaging and modeling forms an essential foundation for parametric description of the matrix properties that are not distinguishable by sole consideration of either bulk optical parameters or SHG alone. Moreover, due to the quasi-coherence of the SHG process in tissues, we submit that this approach contains unique information not possible by purely scattering based methods and that these methods will be applicable in the general case where the complex fibrillar structure is difficult to fully quantify via morphological analysis.
