Intelligent Platelet Morphometry. Issue 10 (October 2021)

• Record Type: Journal Article
• Authors: Zhou, Yuqi; Isozaki, Akihiro; Yasumoto, Atsushi; Xiao, Ting-Hui; Yatomi, Yutaka; Lei, Cheng; Goda, Keisuke
• Is Part Of: Trends in biotechnology. Volume 39:Issue 10(2021)
• Page Start: 978
• Page End: 989
• Publication Date: 2021-10
• Subjects: platelet -- imaging flow cytometry -- deep learning -- thrombosis -- antiplatelet therapy; Biotechnology -- Periodicals; Biochemical engineering -- Periodicals; Genetic engineering -- Periodicals; Industrial microbiology -- Periodicals; 660.605
• DOI: 10.1016/j.tibtech.2020.12.012
• Languages: English
• ISSNs: 0167-7799

Abstract

Abstract : 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. Highlights: Technological advances in platelet analysis are critical for a better understanding of platelets, which are highly complex, dynamic, and multifunctional in nature. The advent of high-throughput imaging and deep learning has boosted traditional image-based platelet analysis or platelet morphometry to the next level, shedding light on the unexplored domain of platelet biology. Key methods for this 'intelligent' platelet morphometry include, but are not limited to, intelligent platelet aggregate classification and intelligent image-activated cell sorting. Intelligent platelet morphometry is expected to pave the way for a new class of diagnostics, pharmacometrics, and therapeutics.