Comparison of compressed SENSE and SENSE for quantitative liver MRI in children and young adults.

OBJECTIVE

Compressed SENSE (C-SENSE) allows more rapid MRI acquisition through incoherent, pseudorandom k-space undersampling. The purpose of our study was to compare conventional sensitivity encoded imaging (SENSE) quantitative MR images to those obtained using C-SENSE for measurement of liver proton density fat fraction (PDFF), T2*, and stiffness.

METHODS AND MATERIALS

Clinical liver MRI examinations that included SENSE and C-SENSE quantitative MRI sequences were retrospectively identified. Patient age, gender, liver PDFF (%), T2* (ms), and stiffness (kPa) were recorded. Spearman's rank-order correlation (r) was used to evaluate association between methods, and Bland-Altman analysis was used to determine the mean bias and 95% limits of agreement.

RESULTS

Clinical liver MRI examinations that included SENSE and C-SENSE quantitative MRI sequences were retrospectively identified. Patient age, gender, liver PDFF (%), T2* (ms), and stiffness (kPa) were recorded. Spearman's rank-order correlation (r) was used to evaluate association between methods, and Bland-Altman analysis was used to determine the mean bias and 95% limits of agreement. Thirty-six examinations met the inclusion criteria. Mean patient age was 15.7 ± 7.7 years; twelve exams (33%) were in female patients. Liver PDFF showed very strong positive correlation (r = 0.98) between sequences, with a mean bias of 0.28% (95% LOA: -0.85, 1.41%). T2* showed moderate positive correlation (r = 0.53), with a mean bias of - 3.0 ms (95% LOA: - 12.0, 6.0 ms). Stiffness showed very strong positive correlation (r = 0.97), with a mean bias of 0.13 kPa (95% LOA: - 0.37, 0.63 kPa) that increased with increasing liver stiffness.

CONCLUSION

There were strong positive correlations between SENSE and C-SENSE MRI measurements of liver PDFF and stiffness, with no to minimal bias. However, there was moderate correlation and greater negative mean bias between T2* measurements. Our results demonstrate the potential of compressed sensing to reliably measure PDFF and stiffness in the clinic.