title: A New Strategy for Fast MRI-Based Quantification of the Myelin Water Fraction: Application to Brain Imaging in Infants.
abstract: The volume fraction of water related to myelin (fmy) is a promising MRI index for in vivo assessment of brain myelination, that can be derived from multi-component analysis of T1 and T2 relaxometry signals. However, existing quantification methods require rather long acquisition and/or post-processing times, making implementation difficult both in research studies on healthy unsedated children and in clinical examinations. The goal of this work was to propose a novel strategy for fmy quantification within acceptable acquisition and post-processing times. Our approach is based on a 3-compartment model (myelin-related water, intra/extra-cellular water and unrestricted water), and uses calibrated values of inherent relaxation times (T1c and T2c) for each compartment c. Calibration was first performed on adult relaxometry datasets (N = 3) acquired with large numbers of inversion times (TI) and echo times (TE), using an original combination of a region contraction approach and a non-negative least-square (NNLS) algorithm. This strategy was compared with voxel-wise fitting, and showed robust estimation of T1c and T2c. The accuracy of fmy calculations depending on multiple factors was investigated using simulated data. In the testing stage, our strategy enabled fast fmy mapping, based on relaxometry datasets acquired with reduced TI and TE numbers (acquisition <6 min), and analyzed with NNLS algorithm (post-processing <5min). In adults (N = 13, mean age 22.4±1.6 years), fmy maps showed variability across white matter regions, in agreement with previous studies. In healthy infants (N = 18, aged 3 to 34 weeks), asynchronous changes in fmy values were demonstrated across bundles, confirming the well-known progression of myelination.
authors.affiliation: INSERM U1129, CEA/DRF/I2BM/Neurospin/UNIACT, Gif-sur-Yvette, France; Université Paris-Saclay, Université Paris Descartes, Sorbonne Paris Cité, Paris, France.
authors.forename: Sofya
authors.initials: S
authors.lastname: Kulikova
authors.affiliation: INSERM U1129, CEA/DRF/I2BM/Neurospin/UNIACT, Gif-sur-Yvette, France; Université Paris-Saclay, Université Paris Descartes, Sorbonne Paris Cité, Paris, France.
authors.forename: Lucie
authors.initials: L
authors.lastname: Hertz-Pannier
authors.affiliation: INSERM U992, CEA/DRF/I2BM/Neurospin/UNICOG, Gif-sur-Yvette, France; Université Paris Saclay, Université Paris-Sud, Gif-sur-Yvette, France.
authors.forename: Ghislaine
authors.initials: G
authors.lastname: Dehaene-Lambertz
authors.affiliation: CEA/DRF/I2BM/Neurospin/UNIRS, Gif-sur-Yvette, France; Université Paris Saclay, Université Paris-Sud, Gif-sur-Yvette, France.
authors.forename: Cyril
authors.initials: C
authors.lastname: Poupon
authors.affiliation: INSERM U992, CEA/DRF/I2BM/Neurospin/UNICOG, Gif-sur-Yvette, France; Université Paris Saclay, Université Paris-Sud, Gif-sur-Yvette, France.
authors.forename: Jessica
authors.identifier: http://orcid.org/0000-0003-4865-8111
authors.initials: J
authors.lastname: Dubois
mesh_terms: D000328:Adult; D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging*; D001931:Brain Mapping / Q000191:economics / Q000379:methods*; D006801:Humans; D007223:Infant; D008279:Magnetic Resonance Imaging / Q000191:economics / Q000379:methods*; D009186:Myelin Sheath / Q000737:chemistry*; D014867:Water / Q000032:analysis*; D066127:White Matter / Q000000981:diagnostic imaging*
chemical_list: D014867:Water