LAUSR

BackgroundOvarian cancer remains the most deadly gynecological cancer with a poor aggregate survival rate; however, the specific rates are highly dependent on the stage of the disease upon diagnosis. Current screening and imaging tools are insufficient to detect early lesions and are not capable of differentiating the subtypes of ovarian cancer that may benefit from specific treatments.MethodAs an alternative to current screening and imaging tools, we utilized wavelength dependent collagen-specific Second Harmonic Generation (SHG) imaging microscopy and optical scattering measurements to probe the structural differences in the extracellular matrix (ECM) of normal stroma, benign tumors, endometrioid tumors, and low and high-grade serous tumors.ResultsThe SHG signatures of the emission directionality and conversion efficiency as well as the optical scattering are related to the organization of collagen on the sub-micron size scale and encode structural information. The wavelength dependence of these readouts adds additional characterization of the size and distribution of collagen fibrils/fibers relative to the interrogating wavelengths. We found a strong wavelength dependence of these metrics that are related to significant structural differences in the collagen organization and are consistent with the dualistic classification of type I and II serous tumors. Moreover, type I endometrioid tumors have strongly differing ECM architecture than the serous malignancies. The SHG metrics and optical scattering measurements were used to form a linear discriminant model to classify the tissues, and we obtained high accuracy (>90%) between high-grade serous tumors from the other tissue types. High-grade serous tumors account for ~70% of ovarian cancers, and this delineation has potential clinical applications in terms of supplementing histological analysis, understanding the etiology, as well as development of an in vivo screening tool.ConclusionsSHG and optical scattering measurements provide sub-resolution information and when combined provide superior diagnostic power over clinical imaging modalities. Additionally the measurements are able to delineate the different subtypes of ovarian cancer and may potentially assist in treatment protocols. Understanding the altered collagen assembly can supplement histological analysis and provide new insight into the etiology. These methods could become an in vivo screening tool for earlier detection which is important since ovarian malignancies can metastasize while undetectable by current clinical imaging resolution.