Application and Validation of Semiautomatic Quantification of Immunohistochemically Stained Sections for Low Cellular Tissue Such as Intervertebral Disc Using QuPath.

Background: Immunohistochemistry (IHC) is a widely used method for localizing and semi-quantifying proteins in tissue samples. Traditional IHC analysis often relies on manually counting 200 cells within a designated area, a time-intensive and subjective process that can compromise reproducibility and accuracy. Advances in digital scanning and bioimage analysis tools, such as the open-source software QuPath, enable semi-automated cell counting, reducing subjectivity and increasing efficiency.

Aims: This project developed a QuPath-based script and detailed guide for semi-automatic cell counting, specifically for tissues with low cellularity, such as intervertebral discs and cartilage.

Methods And Results: The methodology was validated by demonstrating no significant differences between the manual counting and the semi-automatic quantification ( = 0.783,  = 0.386) while showing a strong correlation between methods for both collagen type II staining ( = 0.9602,  < 0.0001) and N-cadherin staining ( = 0.9044,  = 0.0001). Furthermore, a strong correlation (intraclass correlation coefficient (ICC) single raters = 0.853) between 3 individual raters with varying academic ranks and experiences in IHC analysis was shown using the semi-automatic quantification method.

Discusssion: The approach ensures high reproducibility and accuracy, with reduced variability between raters and laboratories. This semi-automated method is particularly suited for tissues with a high extracellular matrix to cell ratio and low cellularity. By minimizing subjectivity and evaluation time, it provides a robust alternative to manual counting, making it ideal for applications where reproducibility and standardization are critical. While the methodology was effective in low-cellularity tissues, its application in other tissue types warrants further exploration.

Conclusions: These findings underscore the potential of QuPath to streamline IHC analysis and enhance inter-laboratory comparability.