Abstract: Nanoparticle exposure induces significant morphological changes in cellular surfaces, necessitating robust methods for quantitative analysis. Scanning Electron Microscopy (SEM) provides high-resolution imaging of these surfaces, enabling the study of cellular responses to nanoparticle exposure. To objectively quantify these changes, we propose a novel texture analysis framework that leverages fractal dimension and lacunarity analysis, combined with a Quantized Co-Occurrence (QCO) operator and Earth Mover’s Distance (EMD) to capture both local and global textural features directly from grayscale SEM images. The QCO operator enables the discretization of textural features into quantized levels, facilitating the generation of feature distributions that retain spatial information while summarizing surface variability. Using EMD, we assess the differences in these distributions between classes, providing a robust measure to quantify the structural and morphological differences between untreated cells and those exposed to various nanoparticles. This combined framework enables us to visualize and rank nanoparticle-induced changes in cellular morphology, revealing key insights into the differential effects of sensitizers such as nickel oxide (NiO) and irritants such as crystalline silica (CS). Our results demonstrate the effectiveness of the proposed framework in highlighting distributional differences, with rankings validated against expert knowledge using statistical measures such as Cohen’s kappa. This approach not only advances the objective quantification of cellular texture changes, but also establishes a scalable method for analyzing complex morphological features in biomedical imaging.
Publication date: February 2025
Citation: A. Mohan, T. Jefferis, C. Sayes and, J. Peeples, “Texture Analysis of Lung Cell Surface Morphology After Nanoparticle Exposure,” in Proceedings of SPIE-the International Society for Optical Engineering, San Diego, CA, 2025, in Press.