Square sampling. An easy method of estimating numerical densities of cells or particles within a tissue

Area of Science:

• Biomedical Engineering
• Quantitative Pathology
• Cell Biology

Background:

• Accurate quantification of cell numbers in tissues is crucial for disease diagnosis and research.
• Traditional methods for cell counting can be time-consuming and labor-intensive.

Purpose of the Study:

• To introduce and evaluate a novel parametric method, termed "square sampling," for rapid cell or particle estimation in randomly distributed tissue samples.

Main Methods:

• The square sampling method involves subdividing a biopsy into numerous small, equal-sized squares.
• Cell estimation is performed by counting "positive" squares (those containing at least one cell of interest), assuming a binomial distribution.

Main Results:

• Square sampling yielded results comparable to exact cell counts in bone marrow biopsies (r = .97).
• The method halved the total investigation time (25.1 vs. 55.3 hours, P < .00005).
• Estimated cell numbers showed similar variance to exact counts (P > .05).

Conclusions:

• Square sampling offers an easy, fast, and effective alternative to nonparametric methods for quantifying cell density in tissues.
• The method is also applicable for testing random distribution hypotheses and quantifying cell clustering.