The field of the invention is systems and methods for magnetic resonance imaging (“MRI”). More particularly, the invention relates to systems and methods for producing a quantitative map of apparent transverse relaxation rate, R2*, while simultaneously performing water-fat separation.
Water-fat separation methods based on chemical-shift-induced phase differences have received considerable interest in the recent years because of their ability to provide robust fat suppression in the presence of B0 and B1 inhomogeneities. In these methods, images are acquired at different echo times, typically using a multi-echo spoiled gradient echo acquisition, so that separated water and fat images can be subsequently reconstructed on the basis of a predefined signal model equation. Using these methods, proton-density fat-fraction, which has been shown to be a quantitative biomarker for non-alcoholic fatty liver disease (“NAFLD”), can be measured by correcting for a number of confounding factors, including T2* decay, T1 bias, complexity of the fat spectrum, noise bias, and eddy-current-induced phase errors. Simultaneous estimation of R2*=1/T2* can provide high signal-to-noise-ratio (“SNR”) measurements of liver iron content, corrected for the presence of both fat and macroscopic B0 inhomogeneities.
In the aforementioned water-fat separation techniques, it is advantageous to use of a very short first echo time to improve the SNR performance of both proton-density fat fraction and R2* measurements, especially in cases where transfusion-related iron overload results in markedly increased iron concentration. In those cases, most of the echoes are dominated by noise and contain very little signal, thereby hampering accurate high-resolution R2* and fat fraction quantification.
Fractional echo acquisitions can be used to obtain shorter echo times without excessively sacrificing spatial resolution. These fractional echo acquisitions are also capable of reducing the first-order moment in the readout direction and actual pulse sequence repetition time (“TR”). In addition, although parallel imaging and optimized k-space sampling have greatly reduced the need for partial Fourier acquisitions to shorten scan time, partial k-space sampling can allow shorter breath-holds and further reduce scan time for free-breathing acquisitions. The use of partial k-space sampling also increases flexibility in the timing of the multiple echoes by allowing more closely spaced echoes. This flexibility in the echo timing may facilitate improvements in the noise performance of the acquisition, including improvements in R2* estimation, and may help avoid water-fat swapping, which is a known challenge for chemical-shift-encoded water-fat separation methods.
Homodyne reconstruction and other related methods that exploit the Hermitian symmetry of k-space to reconstruct fractional-echo and partial Fourier acquisitions demodulate the phase from the complex source images, thus discarding the information required to decompose the water and fat signals. Zero filling can be used to preserve the phase information; however, this results in considerable blurring and thus loss of spatial resolution. Iterative phase-preserving reconstruction algorithms such as POCS (“projection onto convex set”) can be used to reconstruct partial k-space acquisitions while preserving the phase information, but at the expense of increased complexity in the reconstruction. Thus, there remains a need to provide a method for water-fat separation and R2* quantification that can make use of the advantages proffered by fractional-echo and partial Fourier acquisitions.
A method for performing water-fat separation of partial k-space datasets using an iterative least-squares decomposition method (“IDEAL”) and homodyne reconstruction is described by S. B. Reeder, et al., in U.S. Pat. No. 7,298,144. This method was shown to be capable of restoring the resolution loss due to zero filling for qualitative water-fat separation algorithms; however, the method is not capable of accounting for T2*-induced signal decays, nor did the method account for the spectral complexity of fat.
USPTO Backgrounds
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