Critical comparison of image analysis workflows for quantitative cell morphological evaluation in assessing cell response to biomaterials.

Quantitative image analysis is an important tool in understanding cell fate processes through the study of cell morphological changes in terms of size, shape, number, and orientation. In this context, this work explores systematically the main challenges involved in the quantitative analysis of fluorescence microscopy images and also proposes a new protocol while comparing its outcome with the widely used Image J analysis. It is important to mention that fluorescence microscopy is by far most widely used in biocompatibility analysis (observing cell fate changes) of implantable biomaterials. In this study, we employed two different image analyses toolsets: (i) the conventionally employed ImageJ software, and (ii) a recently developed automated digital image analyses framework, called ImageMKS. While ImageJ offers a powerful toolset for image analyses, it requires sophisticated user expertise to design and iteratively refine the analyses workflow. This workflow primarily comprises a sequence of image transformations that typically involve de-noising and labelling of features. On the other hand, ImageMKS automates the image analyses protocol to a large extent, and thereby mitigates the influence of the user bias on the final results. This aspect is addressed using a case study of C2C12 mouse myoblast cells grown on Poly(vinyldiene difluoride) based polymeric substrates in the presence of an external electric field. In particular, we used a number of fluorescence microscopy images of murine myoblasts (muscle precursor cells) grown on Poly (vinylidene difluoride), PVDF based nanobiocomposites under the influence of electric field. It was observed that when compared with the findings obtained from ImageJ, ImageMKS workflows consistently produced more reliable results that correlated better with the prior studies. Furthermore, the MKS workflows required much less user time, because of their automation.