A Stereological Method for the Quantitative Evaluation of Cartilage Repair Tissue

Abstract

Objective: To implement stereological principles to develop an easy applicable algorithm for unbiased and quantitative evaluation of cartilage repair. Design: Design-unbiased sampling was performed by systematically sectioning the defect perpendicular to the joint surface in parallel planes providing 7 to 10 hematoxylin–eosin stained histological sections. Counting windows were systematically selected and converted into image files (40-50 per defect). The quantification was performed by two-step point counting: (1) calculation of defect volume and (2) quantitative analysis of tissue composition. Step 2 was performed by assigning each point to one of the following categories based on validated and easy distinguishable morphological characteristics: (1) hyaline cartilage (rounded cells in lacunae in hyaline matrix), (2) fibrocartilage (rounded cells in lacunae in fibrous matrix), (3) fibrous tissue (elongated cells in fibrous tissue), (4) bone, (5) scaffold material, and (6) others. The ability to discriminate between the tissue types was determined using conventional or polarized light microscopy, and the interobserver variability was evaluated. Results: We describe the application of the stereological method. In the example, we assessed the defect repair tissue volume to be 4.4 mm3 (CE = 0.01). The tissue fractions were subsequently evaluated. Polarized light illumination of the slides improved discrimination between hyaline cartilage and fibrocartilage and increased the interobserver agreement compared with conventional transmitted light. Conclusion: We have applied a design-unbiased method for quantitative evaluation of cartilage repair, and we propose this algorithm as a natural supplement to existing descriptive semiquantitative scoring systems. We also propose that polarized light is effective for discrimination between hyaline cartilage and fibrocartilage.