Early diagnosis of diseases such as cancer is essential for improving survival rates because treating early-stage cancers is often more straightforward and effective than treating late-stage cancers. Typically, initial cancer diagnosis is performed by visual inspection of dyed tissue biopsies using a bright-field microscope however, this is challenging due to variability in morphological interpretation of the tissues. Therefore, pathologists could benefit in identifying cancer on biopsy or surgical resection sections by using unbiased quantitative automated technologies with high spatial resolution and improved disease specificity.
During cancer initiation and progression, the affected tissue extracellular matrix (ECM) is often deregulated and becomes disorganized. A strategy towards improved cancer diagnosis is to develop technology by which the structural alterations in the ECM during tumor initiation and progression can be identified and quantified. Since collagen is a major constituent of the ECM and it consists of triple helices within fibrils, collagen efficiently produces the second-order nonlinear optical effect, second harmonic generation (SHG). Therefore, SHG microscopy can be applied to visualize collagen in the ECM. Additionally, by performing polarization-sensitive SHG imaging, referred to as polarization-in, polarization-out (PIPO) SHG microscopy, the second-order nonlinear optical susceptibility tensor components ratios, R = χ(2)zzz/χ(2)zxx and C = χ(2)xyz/χ(2)zxx as well as the degree of linear polarization, DOLP, can be measured. R and C are related to the collagen ultrastructure while the DOLP is used to indicate the relative amount of scattering of SHG. Therefore, PIPO SHG microscopy can be used as a quantitative method to extract changes in the structure of collagen in the ECM.
During this talk, I will discuss the application of PIPO SHG microscopy to investigate the ultrastructure of collagen in various types of cancer, including human pancreatic and thyroid cancers, as well as various collagenous assemblies to better our understanding of tissue structure.