We apply label-free imaging using digital holographic microscopy to analyze different cancer cell lines. Separation of cell lines based on extraction of amplitude and phase map variations along with post-processed, population specific parameters, was accomplished using machine learning. These data are used to train a neural network algorithm that attains accurate discrimination of non-adherent cancer cells.
In order to advance quantitative phase microscopy as a significant clinical tool, we have implemented a new modality, holographic cytometry, which provides high resolution phase maps at high frame rates using several novel advances such as high speed line scan cameras integrated with microfluidic and illuminated with pulsed light source. The system is used to examine carcinogenic changes in epithelial cells which have been exposed to heavy metals in population sizes that are diagnostically relevant.
Cellular viscoelasticity is a biomarker for cancer type and toxin exposure. Current standard methods for probing cellular stiffness are slow, laborious, and utilize complex or indirect detection. These limitations prevent effective study of changes to viscoelasticity over time as well as longitudinal study of single cells. To enable direct and non-contact measurement of stiffness, we developed a quantitative phase imaging (QPI) based method to directly measure mechanical displacement in living cells in response to static loading. We calculated mechanical parameters, including shear stiffness, to discriminate between different cancer types and cell types that were exposed to varied levels of environmental and pharmacological toxins. We also demonstrated a correlation between our shear stiffness parameter and disorder strength, a measure of cellular refractive index homogeneity acquired via a single QPI image, showing the feasibility of high-throughput, nondestructive mechanical measurements.
Now, we compare our methods to atomic force microscopy (AFM), the gold standard for measuring cellular viscoelastic characteristics. We evaluate multiple breast cancer cell lines that are dosed with varying concentrations of cytochalasin B, an actin network-disrupting toxin. Each group is characterized by a commercial AFM to measure Young’s modulus and indentation stiffness. The same groups are analyzed using our QPI system to simultaneously measure shear stiffness and disorder strength. Relationships between all four measurements are analyzed to determine the correlation between the QPI derived parameters and those found using the commercial AFM, and to explore the feasibility of using QPI as a high-throughput alternative to AFM for measurements of cellular viscoelasticity.
Quantitative phase imaging provides nanometer scale sensitivity and has been previously used to study spectral and temporal characteristics of individual cells in vitro, especially red blood cells. Here we extend this work to study the mechanical responses of individual cells due to the influence of external stimuli. Cell stiffness may be characterized by analyzing the inherent thermal fluctuations of cells but by applying external stimuli, additional information can be obtained. The time dependent response of cells due to external shear stress is examined with high speed quantitative phase imaging and found to exhibit characteristics that relate to their stiffness. However, analysis beyond the cellular scale also reveals internal organization of the cell and its modulation due to pathologic processes such as carcinogenesis. Further studies with microfluidic platforms point the way for using this approach in high throughput assays.
We present a dual-modality system for both structural and molecular cell imaging based on coregistered quantitative phase imaging (QPI) and photoacoustic microscopy (PAM). The QPI system was based on off-axis holography, whereas the PAM system comprised a sinusoidally modulated optical source for excitation and a narrow-band low profile and low-cost ring ultrasonic transducer for detection. This approach facilitated a simple confocal alignment of the excitation beams of both modalities and the ultrasonic detector. This system was demonstrated by imaging endogenous molecules in red blood cells (RBCs) as well as by imaging exogenous molecular labels on cancer cells using gold nanoparticles (GNPs) functionalized to target epidermal growth factor receptor. QPI provided high resolution imaging of the cellular structures while PAM provided molecular contrast. This dual-modality microscopy method can potentially be implemented as a compact and low cost cellular diagnostic assay.
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