Intelligent classification of platelet aggregates by agonist type.

Journal: eLife
PMID:

Abstract

Platelets are anucleate cells in blood whose principal function is to stop bleeding by forming aggregates for hemostatic reactions. In addition to their participation in physiological hemostasis, platelet aggregates are also involved in pathological thrombosis and play an important role in inflammation, atherosclerosis, and cancer metastasis. The aggregation of platelets is elicited by various agonists, but these platelet aggregates have long been considered indistinguishable and impossible to classify. Here we present an intelligent method for classifying them by agonist type. It is based on a convolutional neural network trained by high-throughput imaging flow cytometry of blood cells to identify and differentiate subtle yet appreciable morphological features of platelet aggregates activated by different types of agonists. The method is a powerful tool for studying the underlying mechanism of platelet aggregation and is expected to open a window on an entirely new class of clinical diagnostics, pharmacometrics, and therapeutics.

Authors

  • Yuqi Zhou
    Sun Yat-sen University, The Third Affiliated Hospital, Guangzhou, 510640, China. zhouyuqi@mail.sysu.edu.cn.
  • Atsushi Yasumoto
  • Cheng Lei
  • Chun-Jung Huang
    Department of Photonics, National Chiao Tung University, Hsinchu, Taiwan.
  • Hirofumi Kobayashi
  • Yunzhao Wu
    Department of Chemistry, University of Tokyo, Tokyo, Japan.
  • Sheng Yan
    Department of Chemistry, University of Tokyo, Tokyo, Japan.
  • Chia-Wei Sun
    Biomedical Optical Imaging Lab, Department of Photonics, Institute of Electro-Optical Engineering, College of Electrical and Computer Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan.
  • Yutaka Yatomi
  • Keisuke Goda