Fat-Water Swaps in Iterative Decomposition of Water and Fat With Echo Asymmetry and Least-Squares Estimation Magnetic Resonance Imaging for Postinstrumentation Spine

Spectrally selective and interleaved water imaging and fat imaging (siWIFI)

PURPOSE

To develop a novel imaging sequence that independently acquires water and fat images while being inherently insensitive to motion.

METHODS

The new sequence, termed spectrally selective and interleaved water imaging and fat imaging (siWIFI), uses a narrow bandwidth RF pulse for selective excitation of water and fat separately. The interleaved acquisition method ensures that the obtained water and fat images are inherently coregistered. A radial sampling strategy further reduces motion-induced artifacts. Phantoms with lipid concentrations ranging from 0% to 50% were scanned to measure fat fraction. Moreover, healthy volunteers were scanned to assess the in vivo feasibility of fat fraction measurement at the hip, knee, and liver. In vivo fat fraction measurements were compared with those from vendor-provided iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) scans. Furthermore, a magnetization transfer (MT) preparation module was incorporated to demonstrate the feasibility of simultaneous measurement of fat fraction and MT ratio utilizing the siWIFI framework.

RESULTS

The phantom fat fractions measured by siWIFI showed excellent correlation with lipid concentrations (R2 = 0.9995, p < 0.0001). In vivo studies demonstrated that the fat fractions obtained from siWIFI were comparable to those from IDEAL. Additionally, siWIFI demonstrates reduced motion artifacts from pulsatile flow in knee imaging compared to IDEAL scans and exhibits less sensitivity to respiratory motion in liver imaging compared to IDEAL scans without breath-hold. The knee imaging study demonstrated that MT-prepared siWIFI is capable of generating fat fraction and MT ratio maps simultaneously.

CONCLUSION

The proposed siWIFI sequence allows selective water-fat imaging and quantification with reduced motion artifacts.

Prediction of treatment response to intravenous glucocorticoid in patients with thyroid-associated ophthalmopathy using T2 mapping and T2 IDEAL

PURPOSE

To investigate the performance of combined T2 mapping and T2 iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) in orbital tissues to predict the therapeutic efficacy of intravenous glucocorticoids (IVGCs) for active and moderate-to-severe thyroid-associated ophthalmopathy (TAO).

METHOD

Sixty-three active and moderate-to-severe TAO patients (responsive group, n = 35; unresponsive group, n = 28) who underwent orbital MRI before receiving IVGCs were retrospectively enrolled. Baseline clinical characteristics and imaging parameters were analyzed and compared between the two groups of different therapeutic efficacy. Binary logistic regression analysis was conducted to determine the independent predictors, the predictive performance of which was evaluated using receiver operating characteristic curve analysis.

RESULTS

The mean T2 relaxation time of extraocular muscle (EOM-T2RT_mean) (P = 0.001), maximum T2RT of EOM (EOM-T2RT_max) (P = 0.001), mean water fraction of EOM (EOM-WF_mean) (P < 0.001), maximum WF of EOM (EOM-WF_max) (P < 0.001) and exophthalmos (P = 0.007) were significantly higher in the responsive group than in the unresponsive group. EOM-T2RT_mean (P < 0.001) and EOM-WF_max (P < 0.001) were determined as independent predictors for responsive patients with TAO in the multivariable analysis. Combining EOM-T2RT_mean ≥ 77.1 and EOM-WF_max ≥ 91.52 demonstrated optimal efficiency for prediction (area under the curve = 0.844) and optimal predictive sensitivity (77.1%). Setting EOM-WF_max ≥ 91.52 achieved the optimal predictive specificity (89.3%).

CONCLUSIONS

Pretherapeutic quantitative measurements, based on combining T2 mapping and T2 IDEAL in orbital tissues, are valuable for predicting IVGC treatment response in active and moderate-to-severe TAO. EOM-T2RT_mean and EOM-WF_max may become promising IVGC treatment response predictors.