Multiexponential T₂ relaxometry is a powerful research tool for detecting brain structural changes due to demyelinating diseases such as multiple sclerosis. However, because of unusually high signal-to-noise ratio requirement compared with other MR modalities and ill-posedness of the underlying inverse problem, the T₂ distributions obtained with conventional approaches are frequently prone to noise effects. In this article, a novel multivoxel Bayesian algorithm using spatial prior information is proposed. This prior takes into account the expectation that volume fractions and T₂ relaxation times of tissue compartments change smoothly within coherent brain regions. Three-dimensional multiecho spin echo MRI data were collected from five healthy volunteers at 1.5 T and myelin water fraction maps were obtained using the conventional and proposed algorithms. Compared with the conventional method, the proposed method provides myelin water fraction maps with improved depiction of brain structures and significantly lower coefficients of variance in white matter.

Quantitative assessment of myelination is important for characterizing tissue damage and evaluating response to therapy in white matter diseases such as multiple sclerosis. Conventional multicomponent T 2 relaxometry based on the twodimensional (2D) multiecho spin echo sequence is a promising method to measure myelin water fraction, but its clinical utility is impeded by the prohibitively long data acquisition and limited brain coverage. The objective of this study was to develop a signal-to-noise ratio efficient 3D T 2 prep spiral gradient echo (3D SPIRAL) sequence for full brain T 2 relaxometry and to validate this sequence using 3D multiecho spin echo as reference standard in healthy brains at 1.5 T. 3D SPIRAL was found to provide similar myelin water fraction in six selected white and gray matter areas using region-of-interest signal averaging analysis (N 5 7, P > 0.05). While 3D multiecho spin echo only provided partial brain coverage, 3D SPI-RAL enabled whole brain coverage with a fivefold higher acquisition speed per imaging slice and similar signal-tonoise ratio efficiency. Both 3D sequences provided superior signal-to-noise ratio efficiency when compared to the conventional 2D multiecho spin echo approach. Magn Reson Med 67:614-621, 2012. V C 2012 Wiley Periodicals, Inc. Key words: T 2 relaxometry; white matter; myelin water fraction; spiral sampling; 3D acquisition Quantitative assessment of myelin content is important for characterizing tissue damage and evaluating response to therapy of demyelinating diseases such as multiple sclerosis. Currently, multicomponent T 2 relaxometry (1,2) is considered one of the most promising noninvasive in vivo imaging biomarkers for myelin content. In this approach, multiple magnetic resonance images are acquired with different T 2 weightings, from which a T 2 distribution can be obtained for each voxel using a multiexponential analysis (3). The signal of the myelin water peak (typically corresponding to T 2 components of less than 50 ms at 1.5 T) relative to the total water signal is called the myelin water fraction (MWF) and has been proposed as an indirect measurement of the degree of myelination (4). MWF has been shown to correlate with histological myelin measurement in animal models (5,6) as well as in ex vivo human brains (7), and may be useful clinically (4,8).Accurate multicomponent T 2 relaxometry requires a large number of T 2 -weighted images with high signal-tonoise ratio (SNR; 9), resulting in lengthy acquisition. In the conventional method, image data are collected using a two-dimensional (2D) Carr-Purcell-Meiboom-Gill multiecho spin echo (MESE) sequence at various echo times (TEs; 2,8,10). The utility of 2D MESE for clinical practice is impeded by prohibitively long acquisition time of approximately 26 min for each 5 mm slice (10). 3D MESE acquisition with echo planar readout has been proposed to achieve whole brain coverage efficiently (11), but a direct comparison with the standard 2D MESE method is not available. MESE also uses a large number of 180...

PurposeTo assess neuroprotection and remyelination in Multiple Sclerosis (MS), we applied a more robust myelin water imaging (MWI) processing technique, including spatial priors into image reconstruction, which allows for lower SNR, less averages and shorter acquisition times. We sought to evaluate this technique in MS-patients and healthy controls (HC).Materials and MethodsSeventeen MS-patients and 14 age-matched HCs received a 3T Magnetic Resonance Imaging (MRI) examination including MWI (8 slices, 12 minutes acquisition time), T2w and T1mprage pre and post gadolinium (GD) administration. Black holes (BH), contrast enhancing lesions (CEL) and T2 lesions were marked and registered to MWI. Additionally, regions of interest (ROI) were defined in the frontal, parietal and occipital normal appearing white matter (NAWM)/white matter (WM), the corticospinal tract (CST), the splenium (SCC) and genu (GCC) of the corpus callosum in patients and HCs. Mean values of myelin water fraction (MWF) were determined for each ROI.ResultsSignificant differences (p≤0.05) of the MWF were found in all three different MS-lesion types (BH, CEL, T2 lesions), compared to the WM of HCs. The mean MWF values among the different lesion types were significantly differing from each other. Comparing MS-patients vs. HCs, we found a significant (p≤0.05) difference of the MWF in all measured ROIs except of GCC and SCC. The mean reduction of MWF in the NAWM of MS-patients compared to HCs was 37%. No age, sex, disability score and disease duration dependency was found for the NAWM MWF.ConclusionMWF measures were in line with previous studies and lesions were clearly visible in MWI. MWI allows for quantitative assessment of NAWM and lesions in MS, which could be used as an additional sensitive imaging endpoint for larger MS studies. Measurements of the MWF also differ between patients and healthy controls.

The proposed algorithm provides more noise-robust fits to T2-decay data and improves MWF-quantifications in white matter structures especially in the sub-cortical white matter and major white matter tract regions.