Dark field optical imaging reveals vascular changes in an inducible hamster cheek pouch model during carcinogenesis

In this study, we propose a low-cost cross-polarized dark field microscopy system for in vivo vascular imaging to detect head and neck cancer. A simple-to-use Gabor-filter-based image processing technique was developed to objectively and automatically quantify several important vascular features, including tortuosity, length, diameter and area fraction, from vascular images. Simulations were performed to evaluate the accuracies of vessel segmentation and feature extraction for our algorithm. Sensitivity and specificity for vessel segmentation of the Gabor masks both remained above 80% at all contrast levels when compared to gold-standard masks. Errors for vascular feature extraction were under 5%. Moreover, vascular contrast and vessel diameter were identified to be the two primary factors which affected the segmentation accuracies. After our algorithm was validated, we monitored the blood vessels in an inducible hamster cheek pouch carcinogen model over 17 weeks and quantified vascular features during carcinogenesis. A significant increase in vascular tortuosity and a significant decrease in vessel length were observed during carcinogenesis.