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Quantitative mapping of the myelin water content can provide significant insight into the pathophysiology of several white matter diseases, such as multiple sclerosis and leukoencephalopathies, and can potentially become a useful clinical tool for early diagnosis of these diseases. In this study, multicompartment analysis of T* 2 decay (MCAT2*) was used for the quantitative mapping of myelin water fraction (MWF). T* 2 decay of each voxel at multiple slice locations was acquired in fixed human brains using a multigradient-echo (MGRE) pulse sequence with alternating readout gradient polarities. Compared to prior techniques using Carr-Purcell-Meiboom-Gill (CPMG) acquisition, the MGRE acquisition approach has: 1) a very short first echo time (Ϸ2 ms) and echo-spacing (Ϸ1 ms), which allows for the acquisition of multiple sampling points during the fast decay of the myelin water signal; 2) a low RF duty cycle, which is especially important for achieving acceptable specific absorption rate (SAR) levels at high field strengths. Multicompartment analysis was then applied to the T* 2 decay in each pixel using a 3-pool model of white matter to detect the signal arising from the myelin water, myelinated axonal water, and mixed water While conventional MRI methods are sensitive to the various pathologies affecting white matter in the central nervous system, it provides relatively nonspecific information about the nature of the underlying pathology. One approach developed based on multicompartment analysis of T 2 decay provides quantitative measurements of myelin water fraction (MWF) (1). Quantitative mapping of the MWF is a direct indicator of the integrity of the myelin sheath and can provide valuable insights into the pathology of focal and diffuse white matter (WM) diseases, such as in multiple sclerosis (MS).One technique for quantitative in vivo mapping of the MWF was presented by MacKay et al. (2). In this technique the time course of T 2 decay was acquired using a 32-echo single-slice Carr-Purcell-Meiboom-Gill (CPMG) sequence with composite 90°x-180°y-90°x refocusing pulses (3) and big crusher gradients around the refocusing pulses (4). A nonnegative least squares (NNLS) algorithm was used to estimate the MWF from the short T 2 decay compartment (5). This technique has very successfully demonstrated the merit of quantitative MWF measurement in the study of MS (6). However, there are some limitations associated with this technique. First, it is difficult to further shorten the first echo time (TE1) and echo spacing (ES) with this pulse sequence, since the durations of the nonselective refocusing pulses and the crusher gradients (4) substantially increase the minimum TE1 and ES. With the TE1 and ES values typically used, the myelin water signal is effectively detected only in the first 2-3 measurements (i.e., first 2-3 echoes), leading to compromised accuracy in estimating the MWF using multicompartment analysis. For example, the myelin water signal with a T 2 of 15 ms is reduced to 51% at the first echo, 26% at the seco...

The performance of a 16-channel receive-only RF coil for brain imaging at 3.0 Tesla was investigated using a custom-built 16-channel receiver. Both the image signal-to-noise ratio (SNR) and the noise amplification (g-factor) in sensitivity-encoding (SENSE) parallel imaging applications were quantitatively evaluated. Furthermore, the performance was compared with that of hypothetical coils with one, two, four, and eight elements (n) by combining channels in software during image reconstruction. As expected, both the g-factor and SNR improved substantially with n. Compared to an equivalent (simulated) singleelement coil, the 16-channel coil showed a 1.87-fold average increase in brain SNR. This was mainly due to an increase in SNR in the peripheral brain (an up to threefold SNR increase), whereas the SNR increase in the center of the brain was 4%. The incremental SNR gains became relatively small at large n, with a 9% gain observed when n was increased from 8 to 16. Compared to the (larger) product birdcage head coil, SNR increased by close to a factor of 2 in the center, and by up to a factor of 6 in the periphery of the brain. For low SENSE acceleration (rate-2), g-factors leveled off for n > 4, and improved only slightly (1.4% averaged over brain) going from n ‫؍‬ 8 to n ‫؍‬ 16. Improvements in g for n > 8 were larger for higher acceleration rates, with the improvement for rate-3 averaging 12.0%.

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