Optimized in-phase and opposed-phase MR imaging for accurate detection of small fat or water fractions: theoretical considerations and experimental application in emulsions

Fiber orientation measurements by diffusion tensor imaging improve hydrogen-1 magnetic resonance spectroscopy of intramyocellular lipids in human leg muscles

Twelve healthy subjects underwent hydrogen-1 magnetic resonance spectroscopy ([Formula: see text]) acquisition ([Formula: see text]), diffusion tensor imaging (DTI) with a [Formula: see text]-value of [Formula: see text], and fat-water magnetic resonance imaging (MRI) using the Dixon method. Subject-specific muscle fiber orientation, derived from DTI, was used to estimate the lipid proton spectral chemical shift. Pennation angles were measured as 23.78 deg in vastus lateralis (VL), 17.06 deg in soleus (SO), and 8.49 deg in tibialis anterior (TA) resulting in a chemical shift between extramyocellular lipids (EMCL) and intramyocellular lipids (IMCL) of 0.15, 0.17, and 0.19 ppm, respectively. IMCL concentrations were [Formula: see text], [Formula: see text], and [Formula: see text] in SO, VL, and TA, respectively. Significant differences were observed in IMCL and EMCL pairwise comparisons in SO, VL, and TA ([Formula: see text]). Strong correlations were observed between total fat fractions from [Formula: see text] and Dixon MRI for VL ([Formula: see text]), SO ([Formula: see text]), and TA ([Formula: see text]). Bland-Altman analysis between fat fractions (FFMRS and FFMRI) showed good agreement with small limits of agreement (LoA): [Formula: see text] (LoA: [Formula: see text] to 0.69%) in VL, [Formula: see text] (LoA: [Formula: see text] to 1.33%) in SO, and [Formula: see text] (LoA: [Formula: see text] to 0.47%) in TA. The results of this study demonstrate the variation in muscle fiber orientation and lipid concentrations in these three skeletal muscle types.

Comparing average breast fat content results from two different protocols at 1.5T and 3T: can the data be pooled?

PURPOSE

To compare the total breast fat content computed from two separate studies, performed on different scanners and with different protocols, with the goal of defining a relationship to allow pooling the data.

MATERIALS AND METHODS

Twelve healthy volunteer women were scanned with two different protocols on the same day. The protocols differed in four important aspects: vendors (GE vs. Philips), scanner main magnetic field strengths (1.5T vs. 3T), pulse sequences (2D fast spin-echo vs. 3D spoiled gradient-echo), and water/fat separation techniques. The resulting water and fat maps were processed with in-house software to extract breast tissue slice-wise. Percent fat content was calculated for each breast, per subject.

RESULTS

Total percent fat contents (averaged across both breasts) resulting from both protocols were plotted against each other, on a subject-by-subject basis, revealing a strong correlation (R(2)  > 0.99), with an overestimation of the fat content from Protocol 1 relative to Protocol 2. The proposed T2 TE-correction for Protocol 1 improves the correlation while decreasing the discrepancy between protocols.

CONCLUSION

Total breast fat content of healthy women resulting from the two protocols can be pooled using a linear relationship. The proposed T2 TE-corrected Protocol 1 is expected to yield accurate fat content.

Quantification of low fat contents: a comparison of MR imaging and spectroscopy methods at 1.5 and 3 T

Magnetic resonance spectroscopy (MRS) has long been considered the golden standard for non-invasive measurement of tissue fat content. With improved techniques for fat/water separation, imaging has become an alternative to MRS for fat quantification. Several imaging models have been proposed, but their performance relative to MRS at very low fat contents is yet not fully established. In this work, imaging and spectroscopy were compared at 1.5 T and 3 T in phantoms with 0-3% fat fraction (FF). We propose a multispectral model with individual a priori R(2) relaxation rates for water and fat, and a common unknown R(2)' relaxation. Magnitude and complex image reconstructions were also compared. Best accuracy was obtained with the imaging method at 1.5 T. At 3 T, the FFs were underestimated due to larger fat-water phase shifts. Agreement between measured and true FF was excellent for the imaging method at 1.5 T (imaging: FF(meas)=0.98 FF(true)-0.01%, spectroscopy: FF(meas)=0.77 FF(true)+0.08%), and fair at 3 T (imaging: FF(meas)=0.91 FF(true)-0.19%, spectroscopy: FF(meas)=0.79 FF(true)+0.02%). The imaging method was able to quantify FFs down to approx. 0.5%. We conclude that the suggested imaging model is capable of fat quantification with accuracy and precision similar to or better than spectroscopy and offers an improvement vs. a model with a common R(2)* relaxation only.