Purpose

The noninvasive assessment of renal oxygenation is of great clinical interest because abnormal tissue oxygenation is associated with common renal injuries, such as ureteral obstruction and renal artery stenosis. The detection of renal oxygenation alterations may enable earlier and more effective treatment. Some recent studies used a single shot asymmetric spin echo (ASE) EPI approach to measure oxygen consumption in the brain.¹ The transverse MR signal decay in the presence of a blood vessel network was model to calculate quantitative oxygen extraction fraction (OEF), as proposed by Haacke and Yablonskiy.² However, the ASE EPI method has not been evaluated in the abdomen due to several considerations. Compared to the brain, the abdomen suffers much larger field inhomogeneity caused by different types of tissues. The kidney is also more subject to respiration induced motion artifacts. In this study, we optimized the ASE EPI sequence for better measuring the OEF in the kidney and performed the feasibility study on healthy volunteers.

Methods

Five healthy volunteers (age 39-45 years old, one female) gave written informed consent to participate in the study. All MRI scans were performed on a 3.0-T MR750 scanner (GE Healthcare, Milwaukee, USA) using an 8-channel phase array torso coil. Instead of shifting 180° RF pulse in the previous approach, the optimized ASE EPI sequence kept the constant position of 180° RF pulse but shifted the position of the readout pulse to reduce TE and hence the susceptibility artifacts in the abdomen (Fig. 1). Scan parameters were as follows: TR=2000ms, FOV=240mm, slice thickness/gap=4/0mm, acquisition matrix=64×64, multi-phase=6, TE=50, 70 (TE_se), 90, 100, 110, 120ms, number of excitations=3. The total acquisition time was 1min to acquire 30 slices. Image post-processing started with a rigid-body registration to correct for respiration induced motion artifacts. The next step was to estimate reciprocal of reversible transverse relaxation rate R2’ and deoxygenated blood volume λ by fitting the acquired images to the model proposed by Haacke and Yablonskiy.² The effect of R2(1/T2) was determined using the first and third echoes acquired symmetrically about the spin echo with the echo spacing equal to 20ms. After R2 was determined, R2’ was calculated using linear least-squares curve fitting with the last four offset echoes with the echo spacing equal to 10ms. Deoxygenated blood volume λ was calculated with the following relationship: λ=ln(S_extrapolated(TE_se)/S(TE_se)) (Eq.1), where the signal S(TE_se) was the spin echo. The amplitude S_extrapolated(TE_se) was the extrapolation to the second echo time according to the last four echoes. Then δω map could be calculated using: 𝛿𝜔=𝑅2′/λ (Eq.2). After that, OEF value was estimated using the following equation: 𝑂𝐸𝐹=𝛿𝜔/(𝛾∙4/3𝜋∙∆χ∙𝐻𝑐𝑡∙𝐵0) (Eq.3), where γ was the gyromagnetic ratio, Δχ represented the susceptibility difference between fully deoxygenated blood vs. fully oxygenated blood and Hct was the hematocrit value.

Results

The raw ASE EPI image shows no noticeable susceptibility artifacts (Fig. 2). The motion artifacts caused by respiration were largely corrected by the rigid-body registration. Fig. 3 shows the corresponding OEF map and the calculated values are in good agreement with the normal range of about 30% as reported in the literature.¹

Discussion and Conclusion

ASE EPI has the potential to provide quantitative OEF maps for the kidney. These results hold promise for some clinical uses to monitor early changes in renal physiology and function. Further investigation is required to assess the sensitivity of OEF measurement in the disease situation.

Acknowledgements

No acknowledgement found.