Osteoporosis and Covid-19: Detected similarities in bone lacunar-level alterations via combined AI and advanced synchrotron testing
Buccino, Federica; Zagra, Luigi; Longo, Elena; D'Amico, Lorenzo; Banfi, Giuseppe; Berto, Filippo; Tromba, Giuliana; Vergani, Laura Maria
Peer reviewed, Journal article
Published version
Permanent lenke
https://hdl.handle.net/11250/3099653Utgivelsesdato
2023Metadata
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Originalversjon
10.1016/j.matdes.2023.112087Sammendrag
While advanced imaging strategies have improved the diagnosis of bone-related pathologies, early signs of bone alterations remain difficult to detect. The Covid-19 pandemic has brought attention to the need for a better understanding of bone micro-scale toughening and weakening phenomena. This study used an artificial intelligence-based tool to automatically investigate and validate four clinical hypotheses by examining osteocyte lacunae on a large scale with synchrotron image-guided failure assessment. The findings indicate that trabecular bone features exhibit intrinsic variability related to external loading, micro-scale bone characteristics affect fracture initiation and propagation, osteoporosis signs can be detected at the micro-scale through changes in osteocyte lacunar features, and Covid-19 worsens micro-scale porosities in a statistically significant manner similar to the osteoporotic condition. Incorporating these findings with existing clinical and diagnostic tools could prevent micro-scale damages from progressing into critical fractures.