Single-detector dual-modality imaging flow cytometry for label-free cell analysis with machine learning

• Published in: Optics and lasers in engineering Vol. 168; p. 107665
• Main Authors: Wang, Zhiwen, Liu, Qiao, Chu, Ran, Song, Kun, Su, Xuantao
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.09.2023
• Subjects: Dual-modality; Imaging flow cytometry; Label-free; Light scattering; Machine learning; Dual-modality; Label-free; Imaging flow cytometry; Light scattering; Machine learning
• ISSN: 0143-8166; 1873-0302
• DOI: 10.1016/j.optlaseng.2023.107665

•The first generation of single-detector dual-modality imaging flow cytometry (dIFC) for simultaneous brightfield and light scattering imaging was developed.•The special optical design with a knife-edge right-angle (KERA) prism makes our dIFC compact and convenient.•Compared with current IFC, our dIFC is demonstrated with attractive capability for label-free analysis of single micrometer particles and cells, especially when the light scattering image modality is adopted. A dual-modality imaging flow cytometer (dIFC) that obtains both brightfield and light scattering images of single cells simultaneously on one detector was developed. The unique optical layout of our system with a knife-edge right-angle (KERA) prism is key for single-detector dual-modality imaging. By using our dIFC, label-free brightfield and light scattering images of single micrometer particles and cells (ovarian cancer cell lines A2780 and Hey) were obtained. Automatic classification of ovarian cell subtypes was achieved with an accuracy of 89.52% for light scattering imaging, and 70.25% for brightfield imaging by integration of dIFC with machine learning. Compared with the obtaining of brightfield and fluorescence images in conventional IFC, our dIFC is promising for label-free cellular analysis especially by adopting the light scattering image modality.