Fat ViP MRI: Virtual Phantom Magnetic Resonance Imaging of water-fat systems - Archive ouverte HAL Access content directly
Journal Articles Magnetic Resonance Imaging Year : 2016

Fat ViP MRI: Virtual Phantom Magnetic Resonance Imaging of water-fat systems

(1) , (1) , (1) , (1, 2) , (1)
1
2

Abstract

OBJECT: Virtual Phantom Magnetic Resonance Imaging (ViP MRI) is a method to generate reference signals on MR images, using external radiofrequency (RF) signals. The aim of this study was to assess the feasibility of ViP MRI to generate complex-data images of phantoms mimicking water-fat systems. MATERIALS AND METHODS: Various numerical phantoms with a given fat fraction, T2* and field map were designed. The k-space of numerical phantoms was converted into RF signals to generate virtual phantoms. MRI experiments were performed at 4.7T using a multi-gradient-echo sequence on virtual and physical phantoms. The data acquisition of virtual and physical phantoms was simultaneous. Decomposition of the water and fat signals was performed using a complex-based water-fat separation algorithm. RESULTS: Overall, a good agreement was observed between the fat fraction, T2* and phase map values of the virtual and numerical phantoms. In particular, fat fractions of 10.5±0.1 (vs 10% of the numerical phantom), 20.3±0.1 (vs 20%) and 30.4±0.1 (vs 30%) were obtained in virtual phantoms. CONCLUSION: The ViP MRI method allows for generating imaging phantoms that i) mimic water-fat systems and ii) can be analyzed with water-fat separation algorithms based on complex data
Embargoed file
Embargoed file
Ne sera jamais visible
Loading...

Dates and versions

hal-01260571 , version 1 (06-03-2016)

Identifiers

Cite

Roberto Salvati, Eric Hitti, Jean-Jacques Bellanger, Hervé Saint-Jalmes, Giulio Gambarota. Fat ViP MRI: Virtual Phantom Magnetic Resonance Imaging of water-fat systems. Magnetic Resonance Imaging, 2016, 34 (5), pp.617-623. ⟨10.1016/j.mri.2015.12.002⟩. ⟨hal-01260571⟩
125 View
4 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More