A New Strategy for Fast MRI-Based Quantification of the Myelin Water Fraction: Application to Brain Imaging in Infants

Sofya Kulikova, Lucie Hertz-Pannier, Ghislaine Dehaene-Lambertz, Cyril Poupon and Jessica Dubois

PLOS ONE, 2016, vol. 11, issue 10, 1-24

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

Date: 2016
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0163143 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 63143&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0163143

DOI: 10.1371/journal.pone.0163143

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().