Development of in vitro methods to test acetabular prosthetic reconstructions (messa a punto di metodi in vitro per la caratterizzazione biomeccanica di ricostruzioni acetabolari)

The revision hip arthroplasty is a surgical procedure, consisting in the reconstruction of the hip joint through the replacement of the damaged hip prosthesis. Several factors may give raise to the failure of the artificial device: aseptic loosening, infection and dislocation represent the principal causes of failure worldwide. The main effect is the raise of bone defects in the region closest to the prosthesis that weaken the bone structure for the biological fixation of the new artificial hip. For this reason bone reconstruction is necessary before the surgical revision operation. This work is born by the necessity to test the effects of bone reconstruction due to particular bone defects in the acetabulum, after the hip prosthesis revision. In order to perform biomechanical in vitro tests on hip prosthesis implanted in human pelvis or hemipelvis a practical definition of a reference frame for these kind of bone specimens is required. The aim of the current study is to create a repeatable protocol to align hemipelvic samples in the testing machine, that relies on a reference system based on anatomical landmarks on the human pelvis. In chapter 1 a general overview of the human pelvic bone is presented: anatomy, bone structure, loads and the principal devices for hip joint replacement. The purpose of chapters 2 is to identify the most common causes of the revision hip arthroplasty, analysing data from the most reliable orthopaedic registries in the world. Chapter 3 presents an overview of the most used classifications for acetabular bone defects and fractures and the most common techniques for acetabular and bone reconstruction. After a critical review of the scientific literature about reference frames for human pelvis, in chapter 4, the definition of a new reference frame is proposed. Based on this reference frame, the alignment protocol for the human hemipelvis is presented as well as the statistical analysis that confirm the good repeatability of the method.

Edge-aware Graph Attention Networks: Joint Reasoning On Text and Knowledge Graphs for Biomedical Question Answering

Much of the real-world dataset, including textual data, can be represented using graph structures. The use of graphs to represent textual data has many advantages, mainly related to maintaining a more significant amount of information, such as the relationships between words and their types. In recent years, many neural network architectures have been proposed to deal with tasks on graphs. Many of them consider only node features, ignoring or not giving the proper relevance to relationships between them. However, in many node classification tasks, they play a fundamental role. This thesis aims to analyze the main GNNs, evaluate their advantages and disadvantages, propose an innovative solution considered as an extension of GAT, and apply them to a case study in the biomedical field. We propose the reference GNNs, implemented with methodologies later analyzed, and then applied to a question answering system in the biomedical field as a replacement for the pre-existing GNN. We attempt to obtain better results by using models that can accept as input both node and edge features. As shown later, our proposed models can beat the original solution and define the state-of-the-art for the task under analysis.