Development of a protocol aimed at the creation of patient-specific knee geometries and atlases from magnetic resonance images including cartilaginous tissue mapping based on quantitative magnetic resonance images signals

Stefanizzi, Fabio

Development of a protocol aimed at the creation of patient-specific knee geometries and atlases from magnetic resonance images including cartilaginous tissue mapping based on quantitative magnetic resonance images signals

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Stefanizzi, F. Development of a protocol aimed at the creation of patient-specific knee geometries and atlases from magnetic resonance images including cartilaginous tissue mapping based on quantitative magnetic resonance images signals. 2018. handle: http://hdl.handle.net/10230/46602

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Abstract

This work cannot be considered to stand alone, in fact it is part of a larger national project called HOLOA, which stands for Holistic Osteoarthritis. In the HOLOA project, the study of Osteoarthritis disease begins with the clinical information of each patient and ends with the multiphysics simulations of the specific OA knee joints. Nowadays, a large number of people suffer from Osteoarthritis (OA), which is a joint disease that affects the knee joint in particular. This disease leads to the partial or complete loss of the articular cartilage tissue. Because of the pain experienced, the motor functions of the patient become limited and lead to medical treatments that, in most cases, include arthroplasty surgery. The most diffuse OA classification method foresees the radiography image technique to detect the loss of cartilage, however, this method can only detect an already ongoing loss of cartilage. In this case, an early diagnosis can help to slow or stop the ongoing cartilage loss by avoiding surgery. This can be achieved with new medical imaging methodologies which include Magnetic Resonance Images (MRI) and quantitative MRIs. The first imaging method gives us information on the geometry of the joint, which we exploit for the first purpose of this study: to create patient specific knee 3D models. To achieve this first goal, we label each image pixel giving it a biological meaning, and this process is called segmentation. Once an MRI is segmented and validated from a trained expert, it will represent a training OA knee image called an atlas. This work, that lies in the first part of the HOLOA project, is aimed to create a procedure that lead to the creation of an atlas. In order to do this, we develop two protocols. The first one foresees the segmentation of the principal bones and then the intervention of a trained expert to complete and validate the labels. In the second protocol, instead, we perform the complete segmentation and the expert have just to validate the quality of our outcomes. In order to make this process replicable we also create a guideline to follow in order to achieve our same results. The second imaging method, the quantitative MRI, is used to obtain information on the composition of the cartilage. Once a representative 3D knee model is created, we need to assign biochemical information to the cartilaginous tissues of this model realistic. This is the second purpose of this work and it can be reached with a procedure called mapping. This procedure will be discussed in the second section of this work. From the whole project, we hope to obtain useful information linking the tissue composition and the progressive degeneration caused by OA within reasonable clinical times. The ultimate goal is to provide an effective standard method for early diagnosis and a better treatment.