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Development of Magnetic Resonance Imaging (MRI) methods for in vivo quantification of lipids in preclinical models.

Abstract : Obesity is associated with increased morbidity and mortality linked to many diseases, including type 2 diabetes, hypertension and disease nonalcoholic fatty liver. Recently, 1H magnetic resonance imaging (MRI) has emerged as the method of choice for non-invasive fat quantification. In this thesis, MRI methodologies were investigated for in vitro (MR phantoms) and in vivo (mice) measurements on a 4.7T preclinical scanner. Two algorithms of fat quantifications – the Dixon’s method and IDEAL algorithm – were considered. The performances of the IDEAL algorithm were analyzed as a function of tissue properties (T2*, fat fraction and fat spectral model), MRI acquisition parameters (echo times, number of echoes) and experimental parameters (SNR and field map). In phantoms, the standard approach of single-T2* IDEAL showed some limitations that could be overcome by optimizing the number of echoes. A novel method to determine the ground truth values of T2* of water and T2* of fat was here proposed. For in vivo measurements, different analyses were performed using the IDEAL algorithm in liver and muscle. Statistical analysis on ROI measurements showed that the optimal choice of the number of echoes was equal to three for fat quantification and six or more for T2* quantification. The fat fraction values, calculated with IDEAL algorithm, were statistically similar to the values obtained with Dixon’s method. Finally, a method for generating reference signals mimicking fat-water systems (Fat Virtual Phantom MRI), without using physical objects, was proposed. These virtual phantoms, which display realistic noise characteristics, represent an attractive alternative to physical phantoms for providing a reference signal in MRI measurements.
Keywords : Fat Water Mri Fat fraction
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Submitted on : Friday, October 21, 2016 - 2:43:06 PM
Last modification on : Friday, January 15, 2021 - 3:33:37 AM
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  • HAL Id : tel-01308529, version 1


Roberto Salvati. Development of Magnetic Resonance Imaging (MRI) methods for in vivo quantification of lipids in preclinical models.. Human health and pathology. Université Rennes 1, 2015. English. ⟨NNT : 2015REN1B026⟩. ⟨tel-01308529⟩



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