Quantitative multi-parameter mapping of R1, PD*, MT and R2* at 3T: a multi-center validation

Autor: Nikolaus eWeiskopf, John eSuckling, Guy eWilliams, Marta Morgado Correia, Becky eInkster, Roger eTait, Cinly eOoi, Edward T Bullmore, Antoine eLutti
Jazyk: angličtina
Rok vydání: 2013
Předmět:
Zdroj: Frontiers in Neuroscience, Vol 7 (2013)
Druh dokumentu: article
ISSN: 1662-453X
DOI: 10.3389/fnins.2013.00095
Popis: Multi-center studies using magnetic resonance imaging facilitate studying small effect sizes, global population variance and rare diseases. The reliability and sensitivity of these multi-center studies crucially depend on the comparability of the data generated at different sites and time points. The level of inter-site comparability is still controversial for conventional anatomical T1-weighted MRI data. Quantitative multi-parameter mapping (MPM) was designed to provide MR parameter measures that are comparable across sites and time points, i.e., 1mm high-resolution maps of the longitudinal relaxation rate (R1=1/T1), effective proton density (PD*), magnetization transfer saturation (MT) and effective transverse relaxation rate (R2*=1/T2*). MPM was validated at 3T for use in multi-center studies by scanning five volunteers at three different sites. We determined the inter-site bias, inter-site and intra-site coefficient of variation (CoV) for typical morphometric measures (i.e., gray matter probability maps used in voxel-based morphometry) and the four quantitative parameters. The inter-site bias and CoV were smaller than 3.1% and 8%, respectively, except for the inter-site CoV of R2* (< 20%). The gray matter probability maps based on the MT parameter maps had a 14% higher inter-site reproducibility than maps based on conventional T1-weighted images. The low inter-site bias and variance in the parameters and derived gray matter probability maps confirm the high comparability of the quantitative maps across sites and time points. The reliability, short acquisition time, high resolution and the detailed insights into the brain microstructure provided by MPM makes it an efficient tool for multi-center imaging studies.
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