Department of Chemistry, University of Tokyo, Tokyo 113-0033, Japan.
Department of Chemistry, University of Tokyo, Tokyo 113-0033, Japan; Kanagawa Institute of Industrial Science and Technology, Kanagawa 213-0012, Japan.
Trends Biotechnol. 2021 Oct;39(10):978-989. doi: 10.1016/j.tibtech.2020.12.012. Epub 2021 Jan 25.
Technological advances in image-based platelet analysis or platelet morphometry are critical for a better understanding of the structure and function of platelets in biological research as well as for the development of better clinical strategies in medical practice. Recently, the advent of high-throughput optical imaging and deep learning has boosted platelet morphometry to the next level by providing a new set of capabilities beyond what is achievable with traditional platelet morphometry, shedding light on the unexplored domain of platelet analysis. This Opinion article introduces emerging opportunities in 'intelligent' platelet morphometry, which are expected to pave the way for a new class of diagnostics, pharmacometrics, and therapeutics.
基于图像的血小板分析或血小板形态计量学的技术进步，对于更好地理解生物研究中血小板的结构和功能，以及在医学实践中开发更好的临床策略，至关重要。最近，高通量光学成像和深度学习的出现，通过提供一套超越传统血小板形态计量学所能实现的新能力，将血小板形态计量学提升到了一个新的水平，揭示了血小板分析中尚未探索的领域。本文观点介绍了“智能”血小板形态计量学的新兴机遇，有望为一类新的诊断学、药物计量学和治疗学铺平道路。
