The Automatic Proportionator Estimator Is Highly Efficient for Estimation of Total Number of Sparse Cell Populations

• Main Authors: Rogely W. Boyce, Hans J. G. Gundersen
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2018-03-01
• Series: Frontiers in Neuroanatomy
• Subjects: proportionator; nonuniform sampling; cell number; image analysis; fractionator
• Online Access: http://journal.frontiersin.org/article/10.3389/fnana.2018.00019/full

Estimation of total number of a population of cells that are sparsely distributed in an organ or anatomically-defined region of interest represents a challenge for conventional stereological methods. In these situations, classic fractionator approaches that rely on systematic uniform random sampling are highly inefficient and, in many cases, impractical due to the intense sampling of the organ and tissue sections that is required to obtain sufficient counts for an acceptable level of precision. The proportionator, an estimator based on non-uniform sampling theory, marries automated image analysis with stereological principles and is the only estimator that provides a highly efficient and precise method to address these challenging quantification problems. In this paper, the practical considerations of the proportionator estimator and its implementation with Proportionator™ software and digital slide imaging are reviewed. The power of the proportionator as a stereological tool is illustrated in its application to the estimation of the total number of a very rare (~50/vertebrae) and sparsely distributed population of osteoprogenitor cells in mouse vertebral body. The proportionator offers a solution to neuroscientists interested in quantifying total cell number of sparse cell populations in the central and peripheral nervous system where systematic uniform random sampling-based stereological estimators are impractical.