We have demonstrated a strong potential for rapid breath-hold 3D multi-fat-peak T
-IDEAL as a fat quantification tool, and propose the method as a valuable tool for obesity research. In phantoms, we have shown that the IDEAL fat fraction, a ratio that intrinsically represents the content of fat and water protons, also correlates strongly with the underlying fat volume fraction in a set of emulsion standards (). The robust relationship between the fat fraction metric and fat volume fraction has been verified by other investigators (31
). In the in vivo
experiments, excellent correlation was achieved between FFIDEAL
in the liver (). In the measurement of PFF, only a moderate correlation was obtained between FFIDEAL
. In six out of the eight pancreas data points, MRS estimates were greater than the IDEAL fat fraction ().
We attribute the poor correlation in the pancreas to two reasons. First, placement of an MRS voxel requires operator expertise, due to the small organ’s elongated shape. Voxel prescription is performed on localizer images that are acquired after subject placement within the scanner bore. In our study, pancreas MRS was acquired several minutes after the localizers. During this period, slight motion of the subject could have caused a spatial mismatch between the prescribed voxel and the anatomy. Second, abdominal organs shift during respiration (33
). In our experience, we have observed the pancreas to shift ~15 mm along the superior–inferior axis between inspiration and expiration due to diaphragm motion. Respiratory motion can therefore lead to erroneous fat signal contamination of the MRS spectra from the abundance of visceral fat surrounding the pancreas (). In contrast, a liver MRS voxel can be placed such that the voxel remains confidently within the organ throughout the respiratory cycle.
In a report by Tushuizen et al.
, the coefficient of variation from test–retest of pancreatic MRS was 15.2% in comparison to liver MRS (4.7%) (ref. 35
). The authors reported individual pancreas spectra on occasion exhibited dramatic increases in the fat signal, and attributed such observations to sudden deep breathing of the subject. We observed similar occurrences in this study. Although respiration can be monitored with a bellows transducer to synchronize MRS acquisition with the subject’s breathing motion (36
), gating can further increase scan time, which may cause subject discomfort. It may also not be possible to use in subjects with a large body habitus.
Although the IDEAL algorithm employed in this work accounted for transverse relaxation and intravoxel dephasing (T2
) by acquiring six echoes, we did not perform similar T2
corrections for MRS. Our MRS protocol used a single echo time of 23 ms. For T2
correction, additional spectra at several other echo times would have been required at the expense of increasing scan time. Alternatively, MRS scan time can be reduced by using a single signal average. We utilized eight averages in this work to ensure adequate signal-to-noise ratio and minimal baseline variations in the acquired spectra. Nonetheless, with additional correction for T2
, the correlation between IDEAL and MRS in the liver () could have been even closer to identity. Recent work has also emphasized T2
correction in computing accurate FFMRS
). In both IDEAL and MRS protocols used in this work, minimization of the longitudinal relaxation (T1
-bias) was considered, and was achieved by using a 5° flip angle (31
) and a repetition time of 4 s (8
IDEAL-MRI has several advantages over MRS. IDEAL can be easily performed within a breath-hold and does not require respiratory gating. It does not require a high-level of operator expertise in voxel prescription. The quantitative end point is a voxel-wise fat fraction map of the entire abdomen () that can potentially show heterogeneous distributions and spatial patterns of ectopic fat, along with 3D contiguous anatomical images of the fat and water components (). In this work, IDEAL image reconstruction and fat fraction computation was performed online on the scanner host computer immediately after data acquisition, and took ~2–3 min. Subsequently, manual segmentation of the liver and the pancreas was performed on the fat fraction maps, and care was taken to avoid hepatic vessels and nontissue structures. The benefits and attractiveness of IDEAL in fat quantification have been recognized, and validation studies in several large patient cohorts have been recently reported (23
The IDEAL approach described in this work has some limitations. First, in order to capture the entire abdomen, it requires multiple breath-holds, which may not be realizable in certain patient groups. Second, the reconstruction algorithm requires an accurate model of the fat spectra. In Eq. (1)
, IDEAL requires a prior knowledge of Δfi
values, and utilizes these to reconstruct images of water, fat, and the fat fraction map. In its current implementation, Δfi
values are determined based on subcutaneous adipose tissue (13
). Potential inaccuracies in the fat fraction map may result if the lipid spectral profiles of triglycerides in organs are significantly different from that of subcutaneous adipose tissue. Nonetheless, accurate fat spectral modeling has recently been shown to be a very critical component of accurate fat fraction estimation (26
). Third, the signal model in Eq. (1)
assumes a common T
value for both water and fat components. To improve accuracy further, individual water and fat T
relaxation terms should be adopted (39
), which will potentially require the acquisition of >6 echoes to solve the system of equations in Eq. (1)
In conclusion, 3D IDEAL-MRI is a rapid breath-hold technique that provides robust separation of fat–water signals and accurate estimation of fat fractions. Unlike single-voxel MRS, IDEAL provides greater spatial resolution and anatomical detail, is much less susceptible to respiratory motion effects, and facilitates assessment of fat content in smaller organs, such as the pancreas. IDEAL has the potential to replace gold-standard MRS for noninvasive fat quantification in both clinical and obesity research protocols.