ArticleOsteoarthritis and cartilage open2026
Characterization of calcifications in posterior horn of human meniscus using micro-computed tomography.
Article in Osteoarthritis and cartilage open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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15 authors.
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Abstract
Objective: Meniscal calcifications are associated with meniscal degeneration and osteoarthritis (OA). We investigated micro-computed tomography (μCT) imaging for identification of calcification patterns caused by basic calcium phosphate (BCP) and calcium pyrophosphate (CPP). Design: Posterior horns of human medial and lateral menisci from 19 individuals with medial compartment knee OA and 21 deceased donors were imaged with high-resolution μCT. Raman spectroscopy characterized the calcification types from histological sections, adjacent to μCT piece. Qualitative and quantitative analysis, visualization, and grading were performed using 3D μCT images of meniscal calcifications. Results: Different calcification patterns were observed with BCP and CPP. BCP was found at the borders of meniscal tissue and inside complex tears or fibrillation. In contrast, CPP accumulated as circumferential rod-like structures between collagen bundles, mainly inside the meniscal tissue, and lacked the porous 3D structure observed in BCP calcifications. Quantitatively, CPP samples had a higher calcification volume compared to BCP with a geometric mean ratio of 14 (95%CI; 3,73), and larger particle sizes with a ratio of 7 (95%CI; 2,8). Additionally, BCP calcifications had an organized porous structure with a closed porosity range of 6-19%, while a similar structure was not seen in CPPs (range 1-4.5%). Conclusions: We qualitatively and quantitatively identified volumetric and morphological differences in the calcification deposition patterns between BCP and CPP calcifications in human meniscus. Ultimately, this μCT imaging method supports more detailed characterization of calcifications in OA and helps to pave the way for identifying potential biomarkers and understanding the mechanistic models of disease progression related to pathological calcifications better.
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