Automatic Quantification of Endothelial Nitric Oxide Levels in a Microvessel with and without Tumor Cell Adhesion

Elevated nitric oxide (NO) and endothelial nitric oxide synthase (eNOS) have been observed in cancer patients in malignancy state. We hypothesize that the higher NO production in the microvessels of these patients attracts more tumor cells (TCs) to adhere and accomplished their metastases. Since there are tens to hundreds of endothelial cells (ECs) forming on the microvessel walls, it is unsustainable to let human operators measure NO intensity levels by correlating TC maps with a multitude of microphotographs via manual labor and eyeballing. To achieve effective and scalable quantifications, we developed an automatic algorithm to quantify NO intensity for microphotographs taken from the experiments. Taking account of the special visual and geometric properties of microvessels in the study, the first step performs a novel Markov integrated dynamic programming procedure to single out the microvessel from the microphotograph. The next step applies image processing and morphological operations to identify ECs and TCs on the microvessel detected from the prior step. Finally a normalized cross correlation procedure applies to register the TC map to the microvessel and evaluate the NO ratios in the ECs with and without TC adhesions. With a processing time reduced from hours to seconds, this algorithm evaluates NO ratios exceedingly similar to those by human operatorsa.