GAP image-Guided computational and experimental Analysis of fractured Patients

Summary

Age-related bone fractures are a major health concern, resulting worldwide in high economic and psycho-social burden, morbidity and increasing mortality. With aging and in presence of bone pathologies, human bone becomes more brittle and prone to damage. A disruptive clinical hypothesis considers Covid-19 virus as an additional contributing factor in bone deterioration. At the macro-scale, the identification of fragility is assured by the clinical practice: common clinical tools, however, are able to predict only 70% of fractures. For this reason, a deep investigation of the bone micro-architecture would be a fundamental hint for the comprehension of damage mechanisms, improving the reliability of fracture risk indicators and performing more accurate diagnosis of bone pathologies. This knowledge level goes beyond the current state of the art and this is where GAP comes into play, providing attractive, multi-disciplinary and versatile training strategies for multi-scale comprehension, detection and patient-specific treatments of bone fractures. The over-arching aim of GAP proposal is to educate young and talented scientists towards a combined high-level experimental and numerical approach for the early-stage accurate, precise detection and mini-invasive treatments of bone fractures, shedding some light on bone micro-scale alterations due to pathologies. The inter-disciplinary findings, that exploit cutting-edge multi-scale imaging facilities and advanced artificial intelligent-based strategies, will be a crucial aspect in the training of skilled researchers and will enable Europe to overcome the silent paralysis of its healthcare system.

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