Label-free, high-throughput holographic screening and enumeration of tumor cells in blood

Abstract

We introduce inline digital holographic microscopy (in-line DHM) as a label-free technique for detecting tumor cells in blood. The optimized DHM platform fingerprints every cell flowing through a microchannel at 10 000 cells per second, based on three features - size, maximum intensity and mean intensity. To identify tumor cells in a background of blood cells, we developed robust gating criteria using machine-learning approaches. We established classifiers from the features extracted from 100 000-cell training sets consisting of red blood cells, peripheral blood mononuclear cells and tumor cell lines. The optimized classifier was then applied to targeted features of a single cell in a mixed cell population to make quantitative cell-type predictions. We tested our classification system with tumor cells spiked at different levels into a background of lysed blood that contained predominantly peripheral blood mononuclear cells. Results show that our holographic screening method can readily detect as few as 10 tumor cells per mL, and can identify tumor cells at a false positive rate of at most 0.001%. This purely optical approach obviates the need for antibody labeling and allows large volumes of sample to be quickly processed. Moreover, our in-line DHM approach can be combined with existing circulation tumor cell enrichment strategies, making it a promising tool for label-free analysis of liquid-biopsy samples.

Quantitative Phase Imaging for Label-Free Analysis of Cancer Cells—Focus on Digital Holographic Microscopy

“…However, the majority of studies use more features. The inline-DH microscopy method used by Singh et al [19,20] to achieve large-scale fingerprinting capabilities was useful for characterizing circulating tumor cells (CTC) in bulk flow. The authors were able to characterize tumor cell lines with different metastatic potential, and to distinguish drug resistant tumor cells from their normal counterparts.…”

Machine learning‐based in‐line holographic sensing of unstained malaria‐infected red blood cells

“…Therefore, the throughput is relatively higher than that of QPI techniques. The throughput can be enhanced and malaria parasites can be detected, especially at an extremely low infection rate, if this diagnostic system is incorporated with a microchannel flow of Newtonian or viscoelastic fluids . Especially, RBCs can be focused on the mid‐plane of a rectangular microchannel of viscoelastic fluid flows .…”

“…Digital in-line holographic microscopy (DIHM) has been utilized for analyzing various microscale flows and for identifying microscale objects [27][28][29][30][31][32]. Compared with QPI techniques, DIHM has a simple optical setup because the reference and object beam use the same path.…”

Large field-of-view phase and fluorescence mesoscope with microscopic resolution

“…The FOV of our 1× magnification system allowed performing statistical studies of cells. This can be seen as a highthroughput 45 single-shot imaging system. We demonstrated the capabilities of our system for statistical study of blood cells and adherent cell imaging with the goal of laying some groundwork for potential future studies in cell biology and hematology fields.…”