The 21 Century Anatomist and Histopathologist: Moving from “Smaller, Focal, Widespread, Bigger, Larger and Greater” to Numbers

Traditionally, histologists and histopathologists have relied heavily on verbal and qualitative descriptions of tissue structure. Histological sections are used to define the normal appearances of cells, tissues and organs. These slides, therefore, also define pathological appearances which may be a consequence of a disease affecting an organ. The traditional approach to morphological analyses was mainly descriptive and therefore largely influenced by the researcher or observer and insensitive to minute changes. In certain pathological cases, quantitative analysis may be required to detect subtle morphological changes, such as small changes in cell number. Relatively new design based methods provide the tools for obtaining accurate, precise quantitative structural data from tissue sections. These tools are sensitive enough to detect small changes by combining statistical sampling principles with geometric analysis of the tissue microstructure. The estimates yielded by these methods are statistically valid, truly three-dimensional, and referential of the entire organ. Though, the new unbiased methods (including computer software) have been in use for some years, these tools and their uses are still poorly understood by many researchers. These new tools are commonly referred to as unbiased stereological methods. Stereology being the quantitative study of three-dimensional structures from their two-dimensional images or profiles is ideally suited to the quantitative analysis of tissues and organs.A lot of quantitative estimations encountered in biological science(especially by histologists and histopathologists) often involve estimation of cell population and volume. This paper traces a little of the past of stereology, gives an overview of unbiased stereology and discusses some of the stereological approaches for obtaining unbiased estimation of cell population and volume in biological tissues in very simple and easy-to-apply formats by researchers (based on personal experience acquired in Nigeria teaching Stereology at the postgraduate level for over ten years at the College of Medicine of the University of Lagos and expertise acquired from training at the Morphometry and Stereology Laboratory, Charles R. Drew University of Medicine and Science, Los Angeles, California, USA).When used correctly, these tools offer a statistically relevant and practical approach to achieve number and volume estimation without bias from cell size, shape, or orientation.

Key Words: Stereology, Morphometry, Cell number, Volume estimation, 2-D, 3-D