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9 March 2020 Label-free classification of T cell activation (Conference Presentation)
Melissa C. Skala, Alex J. Walsh, Kelsey Tweed, Katie Mueller, Isabel Jones, Steven M. Trier, Krishanu Saha
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Proceedings Volume 11244, Multiphoton Microscopy in the Biomedical Sciences XX; 112440A (2020) https://doi.org/10.1117/12.2546366
Event: SPIE BiOS, 2020, San Francisco, California, United States
Abstract
Current methods to assess T cell function use labels that prevent non-destructive quality control of T cell infusions. Here, we use autofluorescence imaging of NAD(P)H and FAD, co-enzymes of metabolism, in quiescent and activated T cells for label-free, non-destructive determination of T cell activation state and subtype. Logistic regression models achieved 97-99% accuracy for classification of T cell activation, and random forest models of achieved >97% accuracy for four-group classification of quiescent and activated CD3+CD8+ and CD3+CD4+ T cells. These results indicate that NAD(P)H and FAD imaging is a powerful method for label-free, non-destructive quality control of T cell infusions.
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Melissa C. Skala, Alex J. Walsh, Kelsey Tweed, Katie Mueller, Isabel Jones, Steven M. Trier, and Krishanu Saha "Label-free classification of T cell activation (Conference Presentation)", Proc. SPIE 11244, Multiphoton Microscopy in the Biomedical Sciences XX, 112440A (9 March 2020); https://doi.org/10.1117/12.2546366
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KEYWORDS
Nondestructive evaluation
Auto-fluorescence imaging
Blood
Cancer
Feature selection
Machine learning
Microscopes
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