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Purpose <p>This study aims to assess the applicability of flow-imaging microscopy (FI) using morphology-derived parameters to the label-free quantitative analysis of natural killer (NK) cells.</p> Methods <p>Serially diluted NK − cells were analyzed in triplicate using FI, an automated cell counter, and fluorescence-activated cell sorting. A morphology-assisted software filter was developed and optimized in FI based on reference parameters obtained from CC and FACS, which included cell size, circularity, aspect ratio, and intensity profile.</p> Results <p>The FI method achieved excellent linearity (R² = 0.9996), accuracy of (98 − 102)%, and precision (CV &lt; 2.5%), confirming its analytical reliability and reproducibility. FI also demonstrated strong correlation with fluorescence-based viability results, accurately distinguishing live, dead, and debris populations without labeling. Importantly, media filtration prior to analysis significantly reduced background particles and improved the consistency of viability and morphological assessments. Particle-size distribution and suspension studies further revealed that debris aggregation and uneven media dispersion can distort apparent viability, emphasizing the importance of pre-filtration and suspension homogeneity.</p> Conclusion <p>The validated FI workflow provides a label-free, image-traceable, and morphology-resolved approach to quantitative NK–cell analysis. The demonstrated relationship between cell viability, linearity, and analytical precision highlights FI’s potential as a robust process-analytical and quality control tool in both research and clinical cell-therapy manufacturing.</p>

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Can label-free flow-imaging microscopy based on morphological parameters be used to quantitatively analyze NK–cells?

  • 期刊论文

  • 发表日期：

    2026年2月9日

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  • Ashish Lamsal,
  • Ho Yoon Shin,
  • Sang-Ki Kim,
  • Ki Taek Kim,
  • Ki Hyun Kim,
  • Jin Woo Park,
  • Ji Eun Yu,
  • Nam Ah Kim

摘要

Purpose

This study aims to assess the applicability of flow-imaging microscopy (FI) using morphology-derived parameters to the label-free quantitative analysis of natural killer (NK) cells.

Methods

Serially diluted NK − cells were analyzed in triplicate using FI, an automated cell counter, and fluorescence-activated cell sorting. A morphology-assisted software filter was developed and optimized in FI based on reference parameters obtained from CC and FACS, which included cell size, circularity, aspect ratio, and intensity profile.

Results

The FI method achieved excellent linearity (R² = 0.9996), accuracy of (98 − 102)%, and precision (CV < 2.5%), confirming its analytical reliability and reproducibility. FI also demonstrated strong correlation with fluorescence-based viability results, accurately distinguishing live, dead, and debris populations without labeling. Importantly, media filtration prior to analysis significantly reduced background particles and improved the consistency of viability and morphological assessments. Particle-size distribution and suspension studies further revealed that debris aggregation and uneven media dispersion can distort apparent viability, emphasizing the importance of pre-filtration and suspension homogeneity.

Conclusion

The validated FI workflow provides a label-free, image-traceable, and morphology-resolved approach to quantitative NK–cell analysis. The demonstrated relationship between cell viability, linearity, and analytical precision highlights FI’s potential as a robust process-analytical and quality control tool in both research and clinical cell-therapy manufacturing.