Comparison of the Visual Scoring Method and Semi-Automatic Image Analysis for Evaluating Staining Intensity of Human Cartilage Sections

Abstract

Accurate estimation of postmortem interval (PMI) is crucial in forensic medicine. The hyaline cartilage, being predominantly composed of a dense extracellular matrix and partly resistant to factors influencing protein degradation, can be utilized for analyzing PMI intervals. Various staining methods are available for cartilage staining for PMI evaluation; however, the conventional visual scoring method for assessing staining intensity is susceptible to evaluator bias. This study compared the visual scoring method with a modified Bern score with semi-automatic image analysis. The cartilage samples were obtained from three cadavers with known time of death. Forty-five histological slices were prepared and stained using Alcian blue, Safranin-O with Fast green, Safranin-O without Fast green, Masson trichrome, and Sirius red. Ten evaluators visually scored each sample on a scale of 0 to 3. A semi-automatic analysis was conducted on the same images using the deconvolution plugin of the ImageJ software. Linear regression was used to assess the correlation between the mean grey value and the mean Bern score from all evaluators. The results showed strong correlations across all evaluated staining techniques, with Masson trichrome staining exhibiting the highest correlation. Accordingly, semi-automatic image analysis can be a suitable replacement for the visual scoring method, particularly when no procedural artifacts are present.

Keywords

• Bern score
• cartilage
• histology
• postmorterm interval
• semi-automatic analysis
• visual scoring method