Biomechanics and Biotribology of the Haemophilic Ankle - A Computational Study

血友病是一种遗传性疾病，由凝血因子缺乏引起，其中反复出血发生; 80%的这些出血发生在肌肉骨骼系统。在这些肌肉骨骼出血中，踝关节的发病率较高。据推测，这是由于在日常活动中踝关节的高应力，开始作为年轻的24个月时，血友病成为移动的。临床上，血友病患者出现早期发病的骨关节炎。然而，在踝关节的发病机制和形态学变化，随着疾病的进展研究甚少。本项目旨在开发患者特定的血友病踝关节的有限元模型，以探讨如何在踝关节的形态变化与生物摩擦学的变化，随着疾病的进展。踝关节的复杂性导致具有挑战性的计算方法，包括非均匀表面上的非线性接触力学。该项目将根据临床图像识别骨形态的变化，并定义关键的临床特征以及它们如何在患者特定的方法中及时发展。在从临床级纵向MR图像数据开发患者特异性模型方面存在进一步的工程挑战，这是由于需要捕获每个患者的特异性和患者之间的大变化，以及成像协议中的差异的抽象。该项目将研究捕获患者之间特定形态变化的方法，同时保持可解决患者之间形态变化的计算模型，例如通过研究哪些关键临床特征对生物摩擦学变化影响最大。随着疾病的进展，关节生物摩擦学的纵向方差的方法也将被开发，以便不同患者群体的模式可以鲁棒地与临床outcome.The在这个项目中开发的方法相比，将提供一套新的强大的计算工具，可用于开发患者队列的方法来检查骨关节炎早期发病的可能性。表征方法还将提供关于哪些临床特征可能是血友病患者挑战和风险队列中骨关节炎图像标记物的良好候选者的新信息。这将为有针对性的预防方法的更多临床工作提供工具和方法。

Haemophilia is a genetic disorder, caused by a deficiency in coagulation factors, in which recurring bleeds occur; eighty percent of these bleeds occur in the musculoskeletal system. Of these musculoskeletal bleeds, a high number of incidences occurs in the ankle. This is hypothesised to be due to the high stresses on the ankle in everyday activities, starting as young as 24 months when the haemophiliac becomes mobile.Clinically, haemophilia patients present with early onset of osteoarthritis. However the pathogenesis and morphological changes in the ankle as the disease progresses are little studied.This project aims to develop patient-specific finite element models of the haemophilic ankle in order to explore how changes in the morphology of the ankle joint relate to a change in the biotribology as the disease progresses. The complexity of the ankle joint leads to challenging computational approaches including non-linear contact mechanics on non-uniform surfaces. This project will identify changes in bone morphology based on clinical images and define key clinical features and how they develop in time in a patient-specific approach. There are further engineering challenges in developing patient-specific models from clinical-grade longitudinal MR image data due to the necessity to capture both the specificity of each patient and the large variation from patient to patient, with abstraction of the difference in imaging protocols. This project will investigate means to capture the specific morphological changes between patients while keeping a computational model which is solvable for the large variation of morphology between patients, for example by studying which key clinical features have the most impact on biotribology changes. Methods to characterise the longitudinal variance of the joint biotribology as the disease progresses will also be developed so that the pattern of different patient groups can be robustly compared to clinical outcomes.The methods developed in this project will provide a new suite of robust computational tools that can be used to develop patient cohorts approaches to examine the likelihood of early onset of osteoarthritis. The characterisation methods will also provide new information on which clinical features may be good candidates as image markers of osteoarthritis in the challenging and at-risk cohort of haemophilic patients. This will provide tools and methods for more clinical work in targeting prevention methods.