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A recently published Dixon-based MRI method for quantifying liver fat content using dual-echo breath-hold gradient echo imaging was validated by phantom experiments and compared with results of biopsy in two patients (Radiology 2005;237:1048-1055). We applied this method in ten healthy volunteers and compared the outcomes with the results of MR spectroscopy (MRS), the gold standard in quantifying liver fat content. Novel was the use of spectroscopic imaging yielding the variations in fat content across the liver rather than a single value obtained by single voxel MRS. Compared with the results of MRS, liver fat content according to MRI was too high in nine subjects (range 3.3-10.7% vs. 0.9-7.7%) and correct in one (21.1 vs. 21.3%). Furthermore, in one of the ten subjects the MRI fat content according to the Dixon-based MRI method was incorrect due to a (100-x) versus x percent lipid content mix-up. The second problem was fixed by a minor adjustment of the MRI algorithm. Despite systematic overestimation of liver fat contents by MRI, Spearman's correlation between the adjusted MRI liver fat contents with MRS was high (r = 0.927, P < 0.001). Even after correction of the algorithm, the problem remaining with the Dixon-based MRI method for the assessment of liver fat content,is that, at the lower end range, liver fat content is systematically overestimated by 4%.

Primary progressive multiple sclerosis (ppMS; n=4) patients and controls (n=4) were examined by 1H magnetic resonance spectroscopy (MRS) and diffusion tensor imaging (DTI) in order to map choline (Cho), creatine and N-acetylaspartate (NAA), the fractional anisotropy (FA) and the apparent diffusion constant (ADC). After chemical shift imaging (point-resolved spectroscopy, repetition time/echo time 1,500 ms/135 ms) of a supraventricular volume of interest of 8x8x2 cm3 (64 voxels) MRS peak areas were matched to the results of DTI for the corresponding volume elements. Mean FA and NAA values were reduced in the ppMS patients (P<0.01, both) and the ADC increased (P<0.02). The spatial distribution of NAA showed strong correlation to ADC in both ppMS patients and controls (r =-0.74 and r= -0.70; P<0.00001, both), and weaker correlations to FA (r=0.49 and r=0.41; P<0.00001, all). FA and ADC also correlated significantly with Cho in patients and controls (P<0.00001, all). The relationship of Cho and NAA to the ADC and the FA and thus to the content of neuronal structures suggests that these metabolite signals essentially originate from axons (NAA) and the myelin sheath (Cho). This is of interest in view of previous reports in which Cho increases were associated with demyelination and the subsequent breakdown of neurons.

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