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Purpose Hepatic iron content (HIC) quantification via R2*-MRI using multi gradient echo (mGRE) imaging is compromised towards high HIC or at higher fields due to the rapid signal decay. Our study aims at presenting an optimized 2D UTE sequence for R2* quantification to overcome these limitations. Methods 2D UTE imaging was realized via half pulse excitation and radial center-out sampling. The sequence includes CHESS pulses to reduce streaking artifacts from subcutaneous fat and spatial saturation (sSAT) bands to suppress out-of-slice signals. The sequence employs interleaved multi-echo readout trains to achieve dense temporal sampling of rapid signal decays. Evaluation at 1.5T and 3T was done in phantoms and clinical applicability demonstrated in five patients with biopsy-confirmed massively high HIC levels (>25 mg Fe/g dry weight liver tissue). Results In phantoms, the sSAT pulses were found to remove out-of-slice contamination, and R2* results were in excellent agreement to reference mGRE R2* results (slope of linear regression: 1.02/1.00 for 1.5/3T). UTE-based R2* quantification in patients with massive iron overload proved successful at both field strengths and was consistent with biopsy HIC values. Conclusion The UTE sequence provides a means to measure R2* in patients with massive iron overload both, at 1.5T and 3T.

The use of a deflectable catheter with a ferromagnetic tip to target the blood vessels and localize the position of device provides a novel method to use the MR system to image the anatomy and steer an interventional device which helps to increase the precision and speed of endovascular procedures.

Highlights Focal cervical stenosis causes dynamic alterations across the entire cervical cord. Spinal cord tissue becomes object of stretching and compressive effects. Studying spinal cord motion provides information beyond anatomical imaging. Standardized data processing is the key to valid analysis of spinal cord motion.

Purpose Fat suppression (FS) via chemically selective saturation (CHESS) eliminates fat-water oscillations in multi-echo gradient echo (mGRE) R2*-MRI. However, for increasing R2* values as seen with increasing liver iron content (LIC), the water signal spectrally overlaps with the CHESS band, which may alter R2*. Here, we investigate the effect of CHESS on R2* and describe a heuristic correction for the observed CHESS-induced R2* changes. Methods Eighty patients (49/31 female/male, mean age: 18.3±11.7 years) with iron overload were scanned with a non-FS and a CHESS-FS mGRE sequence at 1.5T and 3T. Mean liver R2* values were evaluated using 3 published fitting approaches. Measured and model-corrected R2* values were compared and statistically analyzed. Results At 1.5T, CHESS led to a systematic R2* reduction (P<0.001 for all fitting algorithms) especially toward higher R2*. Our model described the observed changes well and reduced the CHESS-induced R2* bias after correction (linear regression slopes: 1.032/0.927/0.981). No CHESS-induced R2* reductions were found at 3T. Conclusion The CHESS-induced R2* bias at 1.5T needs to be considered when applying R2*-LIC biopsy calibrations for clinical LIC assessment which were established without FS at 1.5T. The proposed model corrects the R2* bias and could therefore improve clinical iron overload assessment based on linear R2*-LIC calibrations.

Background Measuring hepatic R2* by fitting a monoexponential model to the signal decay of a multigradient‐echo (mGRE) sequence noninvasively determines hepatic iron content (HIC). Concurrent hepatic steatosis introduces signal oscillations and confounds R2* quantification with standard monoexponential models. Purpose To evaluate an autoregressive moving average (ARMA) model for accurate quantification of HIC in the presence of fat using biopsy as the reference. Study Type Phantom study and in vivo cohort. Population Twenty iron–fat phantoms covering clinically relevant R2* (30–800 s‐1) and fat fraction (FF) ranges (0–40%), and 10 patients (four male, six female, mean age 18.8 years). Field Strength/Sequence 2D mGRE acquisitions at 1.5 T and 3 T. Assessment Phantoms were scanned at both field strengths. In vivo data were analyzed using the ARMA model to determine R2* and FF values, and compared with biopsy results. Statistical Tests Linear regression analysis was used to compare ARMA R2* and FF results with those obtained using a conventional monoexponential model, complex‐domain nonlinear least squares (NLSQ) fat–water model, and biopsy. Results In phantoms and in vivo, all models produced R2* and FF values consistent with expected values in low iron and low/high fat conditions. For high iron and no fat phantoms, monoexponential and ARMA models performed excellently (slopes: 0.89–1.07), but NLSQ overestimated R2* (slopes: 1.14–1.36) and produced false FFs (12–17%) at 1.5 T; in high iron and fat phantoms, NLSQ (slopes: 1.02–1.16) outperformed monoexponential and ARMA models (slopes: 1.23–1.88). The results with NLSQ and ARMA improved in phantoms at 3 T (slopes: 0.96–1.04). In patients, mean R2*‐HIC estimates for monoexponential and ARMA models were close to biopsy‐HIC values (slopes: 0.90–0.95), whereas NLSQ substantially overestimated HIC (slope 1.4) and produced false FF values (4–28%) with very high SDs (15–222%) in patients with high iron overload and no steatosis. Data Conclusion ARMA is superior in quantifying R2* and FF under high iron and no fat conditions, whereas NLSQ is superior for high iron and concurrent fat at 1.5 T. Both models give improved R2* and FF results at 3 T. Level of Evidence: 2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:1620–1632.

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The figure-of-eight-shaped transformer design reduces both RF field coupling with the MR system and artifact sizes. Anatomical structure close to the figure-of-eight-shaped transformer may be less obscured as with loop-shaped transformers if these transformers are integrated into e.g. intravascular catheters.