Evaluates vascular changes in cysts using CD34 and AI-assisted quantification.
BACKGROUND: Inflammatory radicular cysts are lesions of endodontic origin in which chronic inflammation and tissue remodeling may support cyst expansion. AIM: The present study evaluated cluster of differentiation 34 (CD34) immunoexpression as a proxy of vascular remodeling and explored a digital, artificial intelligence (AI)-assisted quantification workflow. MATERIALS AND METHODS: Thirty-nine inflammatory radicular cysts were processed as formalin-fixed paraffin-embedded (FFPE) specimens and immunostained with anti-CD34 antibody. Digital quantification [Deep Learning Inferred ImmunoFluorescence (DeepLIIF) and ImageJ] was performed in selected stromal areas. Lesions were stratified by cyst size (0.5-1.0 cm, 1.0-2.0 cm, >2.0 cm). RESULTS: Twenty-two of 39 cases were CD34-positive. In these cases, the mean proportion of CD34-positive nuclei increased with lesion size (6.67% in 0.5-1.0 cm, 15.98% in 1.0-2.0 cm, and 31.13% in >2.0 cm). Differences among size groups were significant (Kruskal-Wallis H=18.50, p=0.000096). CONCLUSIONS: Larger inflammatory radicular cysts displayed higher CD34-associated vascular signal, supporting an association between cyst size and vascular remodeling.
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Iacov et al. (2026) studied this question.
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