Statistical multivariate analysis of biomarkers for circulating tumor cell detection (Conference Presentation)

Gregory L. Futia; Isabel R. Schlaepfer; Lubna Qamar; Kian Behbakht; Emily A. Gibson

doi:10.1117/12.2514487

4 March 2019 Statistical multivariate analysis of biomarkers for circulating tumor cell detection (Conference Presentation)

Gregory L. Futia, Isabel R. Schlaepfer, Lubna Qamar, Kian Behbakht, Emily A. Gibson

Author Affiliations +

Proceedings Volume 10889, High-Speed Biomedical Imaging and Spectroscopy IV; 108890A (2019) https://doi.org/10.1117/12.2514487
Event: SPIE BiOS, 2019, San Francisco, California, United States

Abstract

Detection of circulating tumor cells with image cytometry is limited by the sensitivity and specificity of the biomarker panel. We collected confocal images of ~100,000 cells labeled for DNA, lipids, CD45, and Cytokeratin on a model system of MCF7 and WBCs representing disease positive, D+ and disease negative, D- populations. We computed spatial image metrics and performed multivariable regression and feature selection, increasing the separation of the D+ and D- populations to 7 standard deviations with detection limit of ~1 in 480. In conclusion, simple regression analysis holds promise to improve the separation of rare cells in cytometry applications.

Conference Presentation

Citation Download Citation

Gregory L. Futia, Isabel R. Schlaepfer, Lubna Qamar, Kian Behbakht, and Emily A. Gibson "Statistical multivariate analysis of biomarkers for circulating tumor cell detection (Conference Presentation)", Proc. SPIE 10889, High-Speed Biomedical Imaging and Spectroscopy IV, 108890A (4 March 2019); https://doi.org/10.1117/12.2514487

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