Automatic detection of circulating tumor cells in darkfield microscopic images of unstained blood using boosting techniques

Circulating tumor cells (CTCs) are nowadays one of the most promising tumor biomarkers. It is well correlated with overall survival and progression-free survival in breast cancer, as well as in many other types of human cancer. In addition, enumeration and analysis of CTCs could be important for monitoring the response to different therapeutic agents, thus guiding the treatment of cancer patients and offering the promise of a more personalized approach. In this article, we present a new method that could be used for the automatic detection of CTC in blood, based on the microscopic appearance of unstained cells. The proposed method is based on the evaluation of image characteristics and boosting techniques. A dataset of 263 dark field microscopy images was constructed and used for our tests, containing blood spiked with three different types of tumor cells. An overall sensitivity of 92.87% and a specificity of 99.98% were obtained for the detection of CTC, performances which proved to be comparable to those obtained by human experts.