Prediction of neural differentiation fate of rat mesenchymal stem cells by quantitative morphological analyses using image processing techniques.

Abstract

Differentiation of bone marrow mesenchymal stem cells (BMSCs) into neural cells has received significant attention in recent years. However, there is still no practical method to evaluate differentiation process non-invasively and practically. The cellular quality evaluation method is still limited to conventional techniques, which are based on extracting genes or proteins from the cells. These techniques are invasive, costly, time consuming, and should be performed by relevant experts in equipped laboratories. Moreover, they cannot anticipate the future status of cells. Recently, cell morphology has been introduced as a feasible way of monitoring cell behavior because of its relationship with cell proliferation, functions and differentiation. In this study, rat BMSCs were induced to differentiate into neurons. Subsequently, phase contrast images of cells taken at certain intervals were subjected to a series of image processing steps and cell morphology features were calculated. In order to validate the viability of applying image-based approaches for estimating the quality of differentiation process, neural-specific markers were measured experimentally throughout the induction. The strong correlation between quantitative imaging metrics and experimental outcomes revealed the capability of the proposed approach as an auxiliary method of assessing cell behavior during differentiation.