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，反复出血；80%的出血发生在肌肉骨骼系统。在这些肌肉骨骼出血中，脚踝的发生率很高。据推测，这是由于在日常活动中踝关节承受的高压力，从24个月大的血友病患者开始活动时开始。临床上，血友病患者表现为早发性骨关节炎。然而，踝关节的发病机制和随疾病进展而发生的形态学变化研究甚少。本项目旨在建立血友病患者踝关节的特定有限元模型，以探索随着疾病的进展，踝关节形态的变化与生物摩擦学的变化之间的关系。踝关节的复杂性导致了对计算方法的挑战，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确定骨形态学的变化，并定义关键的临床特征，以及它们如何以患者特定的方法及时发展。从临床级纵向MR图像数据中开发患者特异性模型还存在进一步的工程挑战，因为需要捕捉每个患者的特异性和患者之间的巨大差异，并抽象成像方案的差异。该项目将研究如何捕捉患者之间特定的形态学变化，同时保持一个可解决患者之间巨大形态学变化的计算模型，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。随着疾病进展，还将开发表征关节生物摩擦学纵向变化的方法，以便将不同患者组的模式与临床结果进行有力的比较。本项目开发的方法将提供一套新的强大的计算工具，可用于开发患者队列方法来检查骨关节炎早期发作的可能性。表征方法也将提供新的信息，哪些临床特征可能是具有挑战性和危险的血友病患者队列中骨关节炎图像标记的良好候选者。这将为更多针对性预防的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.