Morphological investigation of astrocyte brain cells using quantitative phase imaging.

Astrocytes are star-shaped glial cells whose elaborate soma-process architecture supports neuronal functions, regulates ions as well as water homeostasis, and contributes to brain structural organization. This paper presents a quantitative imaging technique for comprehensive morphological analysis of astrocytes, including their somata and branches, using a custom-built common-path quantitative phase microscope. The microscope employs a common-path off-axis configuration, splitting the sample beam using a grating, and a dual-lens system combined with a spatial filter to produce a reference beam required for hologram generation. This microscope enables a label-free, high-temporal-stability, and real-time 3D visualization of biological samples by measuring optical path length difference (OPD). Astrocyte cells were imaged, and their morphometric properties were quantified in near real time using the developed microscope. The reconstructed optical path length difference (OPD) maps were used to perform multistage deep learning segmentation of entire astrocyte cells, and the corresponding soma and branches were segmented using an optical thickness-based clustering approach. The segmented soma and process regions were compared as well as correlated by their phase-derived and geometrical morphological parameters. To the best of our knowledge, this is the first report of using the proposed digital holographic approach with an AI model to segment and measure the morphometrics of astrocyte cells, including their somata and branches separately.