Water-saturated three-dimensional balanced steady-state free precession for fast abdominal fat quantification

Purpose: To compare the performance of a novel water-saturated b-SSFP sequence with that of a conventional T1-weighted turbo spin echo (T1W TSE) sequence for abdominal fat quantification. Materials and Methods: A water-saturated, segmented, three-dimensional balanced steady-state free precession (b-SSFP) sequence and a traditional T1W TSE sequence were both employed on phantom and human studies. For phantom studies, a dual-layered phantom with known internal/external oil volumes was imaged using the two sequences. Images obtained by the two sequences were both processed using a computer-aided semiautomatic program for oil volume quantification. For human studies, six volunteers were scanned axially, centered at L2-L3 levels. Signal-to-noise ratio (SNR)_fat, contrast-to-noise ratio (CNR) _fat-muscle, CNR_{fat-large bowel}, and CNR _{fat-small bowel} were calculated on hand-drawn regions of interest (ROIs), and averaged over all six slices for each subject. Statistical analyses were then performed to determine the SNR and CNR differences between images obtained by the two techniques. Results: The phantom studies show that water-saturated b-SSFP offers a significantly closer estimation of true oil volumes compared with that of T1W TSE (P < 0.0001), as well as a more accurate internal/external volume ratio (P = 0.0001). In human studies, three-dimensional water-saturated b-SSFP images demonstrated higher CNR than that of T1W TSE (P < 0.0005), and very close SNR_fat (P = 0.045). Conclusion: The proposed three-dimensional water-saturated b-SSFP sequence can generate high quality fat-only abdominal images with high CNR and SNR in shorter scan duration than the conventional T1W TSE approach. As images generated by this sequence suffer from no flow artifacts, and are less sensitive to bulk, respiratory, and bowel motion, three-dimensional water-saturated b-SSFP is a faster and more robust method for improving abdominal fat quantification using MRI.