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Development of an in silico model for prediction of in vivo human bone fracture healing using micro-finite element analysis

Descrizione del progetto

Un modello per prevedere la guarigione ossea

Nell’ambito delle fratture ossee, agli strumenti di valutazione esistenti manca la risoluzione necessaria per individuare e isolare i siti iniziali di frattura, soprattutto se questa si verifica nella parte distale dell’osso denominata metafisi. L’obiettivo del progetto HealinguFE, finanziato dall’UE, è sviluppare uno strumento per individuare queste microfratture e prevederne il percorso di guarigione. Grazie a dati di tomografia computerizzata periferica a risoluzione elevata provenienti da pazienti con fratture del polso, gli scienziati svilupperanno un modello in silico in grado di rilevare le modifiche strutturali dell’osso. Lo strumento realizzato farà progredire le conoscenze esistenti sui meccanismi alla base della guarigione delle ossa trabecolari e alimenterà la ricerca futura verso la realizzazione di interventi innovativi.

Obiettivo

Current knowledge of fracture healing is based on experimental animal studies of diaphyseal bone, despite 20% of fractures occurring in the metaphysis of the distal forearm. Moreover, current fracture healing assessment tools lack the resolution to identify and isolate the initial fracture site in cases involving a crushing fracture.

The objectives of this project are to (1) develop a micro-finite element (μFE) model for fracture site identification, (2) develop an in silico model for human bone fracture healing capable of tracking local microstructural changes, and (3) test the predictive power of the in silico model using clinical data. μFE models will be generated from high-resolution peripheral computed tomography (HRpQCT) data of the distal radius from wrist fracture patients. The μFE models will be generated from HRpQCT data collected at the early stages of fracture healing and compared to remodelling maps in order to determine if μFE models can be used to isolate the site of the initial fracture. Adaptations will be made to an existing in silico model based on the findings of the μFE analysis. The resulting in silico model will be applied to clinical HRpQCT data to predict endpoint microstructural changes as well as patterns in fracture healing and remodelling. The predictive power of this in silico model will be determined by comparing the simulation results to observed behavior in vivo.

The proposed project merges recent advances in bone mechanobiology, μFE simulations, and medical imaging to develop novel image analysis and registration methods as well as a tool for predicting if, when, and where fracture healing will occur. The proposed work will provide insights into the local behavior of trabecular bone fracture healing and help the fellow achieve professional maturity. Further, the in silico model has the potential to change the landscape of fracture healing research, particularly in areas of preclinical testing and personalized medicine.

Coordinatore

EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Contribution nette de l'UE
€ 191 149,44
Indirizzo
Raemistrasse 101
8092 Zuerich
Svizzera

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Regione
Schweiz/Suisse/Svizzera Zürich Zürich
Tipo di attività
Higher or Secondary Education Establishments
Collegamenti
Altri finanziamenti
€ 0,00