Optofluidic bioimaging platform for quantitative phase imaging of lab on a chip devices using digital holographic microscopy

Abstract

We propose a versatile 3D phase-imaging microscope platform for real-time imaging of optomicrofluidic devices based on the principle of digital holographic microscopy (DHM). Lab-on-chip microfluidic devices fabricated on transparent polydimethylsiloxane (PDMS) and glass substrates have attained wide popularity in biological sensing applications. However, monitoring, visualization, and characterization of microfluidic devices, microfluidic flows, and the biochemical kinetics happening in these devices is difficult due to the lack of proper techniques for real-time imaging and analysis. The traditional bright-field microscopic techniques fail in imaging applications, as the microfluidic channels and the fluids carrying biological samples are transparent and not visible in bright light. Phase-based microscopy techniques that can image the phase of the microfluidic channel and changes in refractive indices due to the fluids and biological samples present in the channel are ideal for imaging the fluid flow dynamics in a microfluidic channel at high resolutions. This paper demonstrates three-dimensional imaging of a microfluidic device with nanometric depth precisions and high SNR. We demonstrate imaging of microelectrodes of nanometric thickness patterned on glass substrate and the microfluidic channel. Three-dimensional imaging of a transparent PDMS optomicrofluidic channel, fluid flow, and live yeast cell flow in this channel has been demonstrated using DHM. We also quantify the average velocity of fluid flow through the channel. In comparison to any conventional bright-field microscope, the 3D depth information in the images illustrated in this work carry much information about the biological system under observation. The results demonstrated in this paper prove the high potential of DHM in imaging optofluidic devices; detection of pathogens, cells, and bioanalytes on lab-on-chip devices; and in studying microfluidic dynamics in real time based on phase changes.

White-light diffraction phase microscopy at doubled space-bandwidth product

“…Quantitative phase imaging (QPI) has been receiving intense scientific interest as a new modality for label-free biomedical optical imaging [1]. QPI can investigate unlabeled specimens, by converting optical pathlength data into biologically-relevant information [2][3][4][5][6][7][8][9][10]. Since the optical phase delay introduced by the specimen depends on both its thickness and refractive index, which essentially represents density, QPI has been used in a variety of applications, including topography and volume try of red blood cells [11,12], cell membrane fluctuations [13,14], cell growth [15,16], intracellular mass transport [17][18][19], cancer diagnosis in biopsies [20][21][22].…”

Microfluidic Technology for the Generation of Cell Spheroids and Their Applications

“…Further, digitalizing and integrating of the microfluidics with optofluidics offers a powerful imaging solution for biomedical imaging. For instance, the digital holographic microscope is lens free and facilitates real-time imaging three-dimensional tomography imaging of transparent PDMS opto-microfluidic channel [ 142 ]. Efforts to utilize this technology with microfluidic include 3D sensing of microorganism [ 143 ] and automated cell viability detector [ 144 ].…”

Quantitative phase imaging of live cells with near on-axis digital holographic microscopy using constrained optimization approach

“…The aberration in the system is obtained by finding the coefficients of the Zernike polynomial using phase data. [32][33][34] The coefficients of the Zernike polynomial is calculated by the two-dimensional linear least square fitting algorithm of any order O to the phase data extracted along two-dimensional profiles in the areas of the specimen known to be flat. Using these coefficients, a digital phase mask Γðm; nÞ which is the complex conjugation of aberration introduced in the object wave is calculated by…”