Quantitative and Qualitative Image Analysis of <i>In Vitro</i> Co-Culture 3D Tumor Spheroid Model by Employing Image-Processing Techniques

Abstract

This work proposes a novel region-estimation (RE) algorithm using the quantification of colon-cancer (HCT-8) and fibroblasts (NIH3T3) cells to estimate the densest region of colon-cancer cells in in vitro 3D co-cultured spheroids. Cells were labelled with different cell tracker dyes to track the cells. The technique involves staining cells with cell trackers The quantification of HCT-8 and NIH3T3 cells by the RE algorithm leads to distribution pattern analysis of cells from the core to the periphery, which ultimately estimates the densest region of HCT-8 cells in an in vitro 3D cell spheroid. Cell quantification by the RE algorithm was compared with the results of cell quantification by ImageJ software. Results demonstrated the distribution patterns of cells from the core to the peripheral region of the in vitro 3D cell spheroid. The overall experimentation showed that the proposed methodology outperformed state-of-the-art approaches in terms of segmentation, quantification, and reducing biasing error.

Keywords

• distribution patterns
• fibroblast cells
• HCT-8 colon-cancer cells
• nature-inspired techniques
• quantification
• segmentation