Imaging flow cytometry (ImFC) represents a significant technological advancement in the field of cytometry, effectively merging the high-throughput capabilities of flow analysis with the image-based features of microscopy. In this comprehensive review article, we take a historical perspective and delve into the evolution of this methodology, presenting its past, exploring current state-of-the-art and forecasting potential future advancements. The inception of ImFC arose from the innovative combination of a flow cytometer's hydraulics with the technology of an advanced camera. This synergistic coupling facilitated the morphological analysis of cell populations at a high-throughput scale, effectively evolving the landscape of cytometry. However, the application of ImFC faced several challenges. Among the most prominent ones, is the development and implementation of software systems that can reliably and efficiently handle the robust data acquisition and analysis inherent in ImFC. The scale and complexity of the data generated by ImFC necessitates the creation of novel analytical tools that can effectively manage and interpret this data, thus allowing us to unlock the full potential of ImFC. Interestingly, artificial intelligence (AI) algorithms have begun to be implemented on ImFC, offering a promise for enhancing analytical capabilities. The adaptability and learning capacity of AI may prove to be essential in knowledge mining from high-dimensional data produced by ImFC, potentially enabling more accurate analyses. Looking forward, we project that ImFC may become an indispensable tool, not only in research laboratories but also in clinical settings. Given the unique combination of high-throughput cytometry and detailed imaging offered by ImFC, we foresee a critical role for this technology in the next generation of scientific research and diagnostics. As such, we encourage both current and future scientists to consider the integration of ImFC as an addition to their research toolkit and clinical diagnostic routine.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
,
