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Statistical multivariate analysis of biomarkers for circulating tumor cell detection (Conference Presentation)
Author(s): Gregory L. Futia; Isabel R. Schlaepfer; Lubna Qamar; Kian Behbakht; Emily A. Gibson
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Paper 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.

Paper Details

Date Published: 4 March 2019
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Proc. SPIE 10889, High-Speed Biomedical Imaging and Spectroscopy IV, 108890A (4 March 2019); doi: 10.1117/12.2514487
Show Author Affiliations
Gregory L. Futia, Univ. of Colorado Denver (United States)
Isabel R. Schlaepfer, Univ. of Colorado Denver (United States)
Lubna Qamar, Univ. of Colorado Denver (United States)
Kian Behbakht, Univ. of Colorado Denver (United States)
Emily A. Gibson, Univ. of Colorado Denver (United States)


Published in SPIE Proceedings Vol. 10889:
High-Speed Biomedical Imaging and Spectroscopy IV
Kevin K. Tsia; Keisuke Goda, Editor(s)

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