Tomographic flow cytometry by Digital Holography is an emerging imaging modality capable of collecting multiple views of moving and rotating cells with the aim of recovering their refractive index distribution...

The most recent discoveries in the biochemical field are highlighting the increasingly important role of lipid droplets (LDs) in several regulatory mechanisms in living cells. LDs are dynamic organelles and therefore their complete characterization in terms of number, size, spatial positioning and relative distribution in the cell volume can shed light on the roles played by LDs. Until now, fluorescence microscopy and transmission electron microscopy are assessed as the gold standard methods for identifying LDs due to their high sensitivity and specificity. However, such methods generally only provide 2D assays and partial measurements. Furthermore, both can be destructive and with low productivity, thus limiting analysis of large cell numbers in a sample. Here we demonstrate for the first time the capability of 3D visualization and the full LD characterization in high-throughput with a tomographic phase-contrast flow-cytometer, by using ovarian cancer cells and monocyte cell lines as models. A strategy for retrieving significant parameters on spatial correlations and LD 3D positioning inside each cell volume is reported. The information gathered by this new method could allow more in depth understanding and lead to new discoveries on how LDs are correlated to cellular functions.

In recent years, intracellular LDs have been discovered to play an important role in several pathologies. Therefore, detection of LDs would provide an in-demand diagnostic tool if coupled with flow-cytometry to give significant statistical analysis and especially if the diagnosis is made in full non-invasive mode. Here we combine the experimental results of in-flow tomographic phase microscopy with a suited numerical simulation to demonstrate that intracellular LDs can be easily detected through a label-free approach based on the direct analysis of the 2D quantitative phase maps recorded by a holographic flow cytometer. In fact, we demonstrate that the presence of LDs affects the optical focusing lensing features of the embracing cell, which can be considered a biological lens. The research was conducted on white blood cells (i.e., lymphocytes and monocytes) and ovarian cancer cells. Results show that the biolens properties of cells can be a rapid biomarker that aids in boosting the diagnosis of LDs-related pathologies by means of the holographic flow-cytometry assay for fast, non-destructive, and high-throughput screening of statistically significant number of cells.

Digital holography is a technique that provides a non-invasive, label-free, quantitative, and high-resolution imaging employable in biological and science of matter fields, but not only. In the last decade, digital holography (DH) has undergone very significant signs of progress that made it one of the most powerful metrology tools. However, one of the most important issues to be afforded and solved for obtaining quantitative phase information about the analyzed specimen is related to phase aberrations. Sources of aberrations can be diverse, and several strategies have been developed and tested to make DH a reliable optical system with submicron resolution. This paper reviews the most effective and robust methods to remove or compensate phase aberrations in retrieved quantitative phase imaging by DH. Different strategies are presented and discussed in detail on how to remove or compensate for such disturbing aberrations. Among the various methods improvements in the optical setups are considered the numerical algorithms, the hybrid methods, and the very recent Artificial Intelligence (AI) approaches to compensate for all aberrations which affect the setups to improve the imaging quality and the accuracy of the reconstruction images’ procedures.