The dramatic increase in fragility fractures and the related health and economic burden rise the urge of a cutting-edge perspective to anticipate catastrophic fracture propagation in human bones. Recent studies address the issue from a multi-scale perspective, elevating the micro-scale phenomena as the key for detecting early damage occurrence. However, several limitations arise specifically for defining a quantitative framework to assess the contribution of lacunar micro pores to fracture initiation and propagation. Moreover, the need for high resolution imaging imposes time-demanding post-processing phases. Here, we exploit synchrotron scans in combination with micro-mechanical tests, to offer a fracture mechanics-based approach for quantifying the critical stress intensification in healthy and osteoporotic trabecular human bones. This is paired with a morphological and densitometric framework for capturing lacunar network differences in presence of pathological alterations. To address the current time-consuming and computationally expensive manual/semi-automatic segmenting steps, we implement convolutional neural network to detect the initiation and propagation of micro-scale damages. The results highlight the intimate cross talks between toughening and weakening phenomena at micro-scale as a fundamental aspect for fracture prevention.

Assessing the intimate mechanobiological link between human bone micro-scale trabecular architecture and micro-damages

D'Amico, Lorenzo;
2022-01-01

Abstract

The dramatic increase in fragility fractures and the related health and economic burden rise the urge of a cutting-edge perspective to anticipate catastrophic fracture propagation in human bones. Recent studies address the issue from a multi-scale perspective, elevating the micro-scale phenomena as the key for detecting early damage occurrence. However, several limitations arise specifically for defining a quantitative framework to assess the contribution of lacunar micro pores to fracture initiation and propagation. Moreover, the need for high resolution imaging imposes time-demanding post-processing phases. Here, we exploit synchrotron scans in combination with micro-mechanical tests, to offer a fracture mechanics-based approach for quantifying the critical stress intensification in healthy and osteoporotic trabecular human bones. This is paired with a morphological and densitometric framework for capturing lacunar network differences in presence of pathological alterations. To address the current time-consuming and computationally expensive manual/semi-automatic segmenting steps, we implement convolutional neural network to detect the initiation and propagation of micro-scale damages. The results highlight the intimate cross talks between toughening and weakening phenomena at micro-scale as a fundamental aspect for fracture prevention.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3067761
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