Fully automated screening of immunocytochemically stained specimens for early cancer detection

Cytopathological cancer diagnoses can be obtained less invasive than histopathological investigations. Cells containing specimens can be obtained without pain or discomfort, bloody biopsies are avoided, and the diagnosis can, in some cases, even be made earlier. Since no tissue biopsies are necessary these methods can also be used in screening applications, e.g., for cervical cancer. Among the cytopathological methods a diagnosis based on the analysis of the amount of DNA in individual cells achieves high sensitivity and specificity. Yet this analysis is time consuming, which is prohibitive for a screening application. Hence, it will be advantageous to retain, by a preceding selection step, only a subset of suspicious specimens. This can be achieved using highly sensitive immunocytochemical markers like p16ink4a for preselection of suspicious cells and specimens. We present a method to fully automatically acquire images at distinct positions at cytological specimens using a conventional computer controlled microscope and an autofocus algorithm. Based on the thus obtained images we automatically detect p16ink4a-positive objects. This detection in turn is based on an analysis of the color distribution of the p16ink4a marker in the Lab-colorspace. A Gaussian-mixture-model is used to describe this distribution and the method described in this paper so far achieves a sensitivity of up to 90%.