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Quantification de la perfusion myocardique en imagerie de perfusion par résonance magnétique : modèles et classification non-supervisée

Abstract : Cardiovascular diseases and in particular coronary heart disease are the main cause of death worldwide with 17.9 million deaths in 2012. Cardiac MRI is a particularly interesting tool for understanding and evaluating heart disease, including ischemic heart disease. Its diagnostic contribution is often major and it provides information that is not accessible by other imaging modalities. The work carried out during this thesis focuses more specifically on the so-called myocardium perfusion test, which consists in studying the distribution of a contrast agent within the heart muscle during its first passage. In clinical practice, this examination is often limited to the clinician's visual analysis, allowing him to identify the culprit artery and deduce the impacted territory. However, this technique is relative and does not quantify myocardial blood flow. In recent years, an increasing number of techniques have emerged to enable this quantification at all stages of processing, from acquisition to the measurement itself. We first established a treatment pipeline to combine these approaches and evaluate them using a digital phantom and clinical data. We demonstrated that the Bayesian approach is able to quantify myocardium perfusion and its superiority in evaluating the arrival time of the indicator bolus compared to the Fermi model. In addition, the Bayesian approach provides additional interesting information such as the probability density function of the measurement and the uncertainty of the residual function, which makes it possible to know the reliability of the measurement carried out, in particular by observing the distribution of the probability density function of the measurement. Finally, we proposed an algorithm for segmentation of myocardial lesions, using the spatial and temporal dimensions of infusion data. This technique allows an objective and precise segmentation of the hypoperfused region allowing a measurement of myocardial blood flow over an area of tissue which behavior is homogeneous and which average signal measurement allows an increase in the contrast-to-noise ratio. In the cohort of 30 patients, the variability of myocardial blood flow measurements performed on voxels detected by this technique was significantly lower than that of measurements performed on voxels in manually defined areas (mean difference=0.14, 95% CI[0.07, 0.2]) and those performed on voxels in areas defined using the bullseye method (mean difference=0.25, 95% CI[0.17, 0.36])
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Clément Daviller. Quantification de la perfusion myocardique en imagerie de perfusion par résonance magnétique : modèles et classification non-supervisée. Ingénierie biomédicale. Université de Lyon, 2019. Français. ⟨NNT : 2019LYSE1208⟩. ⟨tel-02454381⟩



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