Reproducible Semi-Automated Quantification of Vascularization in Bone Sections Using CD31 Immunohistochemistry and Trainable Weka Segmentation

Résumé fourni par la source

Quantitative assessment of vascularization is important in bone regeneration research, but CD31-immunohistochemically stained sections are often evaluated manually or semi-quantitatively, limiting reproducibility and comparability. The aim of this study was to establish and validate a reproducible, open-source workflow for semi-automated quantification of CD31-positive area fraction in bone sections using Fiji/ImageJ and Trainable Weka Segmentation (TWS). CD31-immunohistochemically stained rat bone sections from defect/regenerating tissue, femur, tibia, and spine were analyzed. The workflow combined standardized image acquisition, predefined regions of interest, pixel-based TWS classification, extraction of the CD31-positive class, and CD31-positive area normalized to tissue area (CD31.Ar/T.Ar). Manual reference measurements were performed by two independent observers in repeated runs. Manual CD31.Ar/T.Ar measurements showed good retest reliability, with mean coefficients of variation (CV) of 7.17% and 6.84% for observer 1 and observer 2, respectively, and good interobserver agreement. Independently trained TWS classifiers produced highly stable CD31.Ar/T.Ar values, with an overall mean CV of 1.98%. Manual assessment required 3:17 ± 1:35 min per section, whereas the TWS-based workflow separated an initial classifier training step from rapid repeated analysis of larger image sets. This study provides a transparent, reproducible, and time-efficient open-source workflow for semi-automated quantification of CD31-positive vascular area fraction in bone sections and supports its use as a scalable method for vascular histomorphometry in preclinical bone regeneration research.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.