Poster S2 - Label-free and high-speed imaging of cell morphology dynamics using single-shot quantitative phase gradient microscopy

Introduction: Advancements in quantitative phase imaging (QPI) have revolutionized our understanding of cell biology. QPI generates high-contrast images for numerous biological samples that are translucent in the visible light range, all without the need for labeling. Its images represent quantitative maps of phase delay of transmitted light, proportional to the local thickness and refractive index of specimens [1]. To reconstruct the phase of light field based on the nonlinear relationship between phase and intensity, various methods utilize either interferometry [2] or multiple-frame measurements [3,4]. Each approach has its limitations: a high coherence source in interferometry is prone to speckle noise [1], while multiple-frame measurements compromise imaging speed [4].
Single-shot quantitative phase gradient microscopy (ss-QPGM) is a powerful method that can implement real-time phase measurements from single, speckle-free images [5]. In this research, we increase computational speed compared to the previous research [5] with a direct integrating algorithm for phase images by adopting Tikhonov regularization. We characterize ss-QPGM by using a standard sample, USAF 1951 resolution phase target. Various imaging performances are quantitatively measured, such as spatial resolution, modulation transfer function, and fidelity to physical properties. We apply the instrument to observe dynamics in cellular morphology over progression of cell death in real-time. In addition, we report the observation for response of human cancer live cells to a novel anti-cancer drug, ErSO.

Materials and

Methods: The instrumentation of ss-QPGM is a functional extension of a differential interference contrast microscope (DIC) (Fig. 1(a)). Instead of an analyzer in DIC, a quarter-wave plate is utilized to convert the polarization states of the two beams from the linearly orthogonal polarization states to the circular ones. A polarization filter array in front of the CMOS sensor array then allows to simultaneously measure intensity of the four polarization channels, resulting in a mosaicked raw data. The workflow of image processing for ss-QPGM is presented in Fig. 1(b). The full size of image for each polarization channel is reconstituted by applying Newton’s polynomial interpolation. Based on those reconstituted images, the quantitative phase gradient image is computed using ∇∅(r)=〖tan〗^(-1) ((I_0-I_90)/(I_45-I_135 )). While the previous research [5] utilized the alternative direction method of multipliers (ADMM)-based algorithms that require extensive computational workforce, we adopt a direct deconvolution method to integrate the phase gradient. To stabilize the deconvolution process, Tikhonov regularization is applied, and the quantitative phase image then can be computed by using ∅(r)=F^(-1) (((H_r ) ̃(u)∙∇_r ∅ ̃(u))/(〖|(H_r ) ̃(u)|〗^2+α)), where is the regularization parameter; indicates the spatial frequency coordinates; and are the Fourier transform of phase gradient and the phase, respectively; represents Fourier transform of gradient operator, and is Fourier transform [6]. To observe the drug response to ErSO, MCF7 cancer cell line was utilized [7].

Results, Conclusions, and Discussions: In Fig. 2, the characteristics of ss-QPGM in image performance are presented. They are based on data from phase-calibrated USAF 1951 microscopy targets with different thicknesses. Fig. 2a shows the representative phase image of 300 nm thickness obtained with 20x/0.4 NA of the objective lens, while Fig. 2b shows the magnified region where the fine features are positioned. The line profiles presented in Fig. 2c explain that 912.3 lp/mm (element 6 in Group 9) of spatial frequency can be resolved at approximately 20% contrast for both x- and y-axis. We will report the fidelity of ss-QPGM across different thicknesses of the phase targets. The estimated phase value at a given thickness can be calculated as ∅_est=2π(n_(su-8)-n_air )t/λ, where n_(su-8) and n_air are refractive indexes of target and air (n_(su-8)=1.52,n_air=1 ); t is thickness of a target; λ is wavelength of a light source. In addition, we will determine the spatial fidelity in phase measurements by reproducing modulation transfer function (MTF). Based on these characterizations and slowly varying object approximation [8], we will validate high imaging performances of ss-QPGM for single cell regime.
We firstly applied the phase imaging with the presented ss-QPGM to examine intracellular changes of live MCF7 cells induced by the cancer drug, ErSO (Fig. 3). Along the time sequence after treatment, prominent changes in morphology, including cell membrane rupture (red shaded area) and the enhanced granular features (green shaded area), were observed. Both are well known morphological features for programmed cell death, apoptosis [9]. To correlate these alterations in cell morphology with biochemical changes, we will assess cell viability using fluorescence imaging. Based on the correlation, we will validate the potential of ss-QPGM that can define various stages of cellular events in label-free manner.
In conclusion, we demonstrated rapid quantitative phase imaging with an ss-QPGM system. We will report characterizations of the presented method using a phase-calibrated USAF target to demonstrate its imaging performance. Through the application in imaging the procession of the drug response of the cancer cells, we observed the high spatial sensitivity, allowing the detection of minor subcellular alterations.

Acknowledgements (Optional): This study is dedicated to Prof. Gabriel Popescu and builds on his work in using QPI for cell imaging studies. We are grateful to Prof. K.V. Prasanth for providing cells used in the cultures in this paper. Research reported in this publication was supported by the National Institute for Bioimaging and Bioengineering of the National Institutes of Health under award number P41EB031772. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.