Quantitative Susceptibility Mapping Using a Multispectral Autoregressive Moving Average Model to Assess Hepatic Iron Overload
Abstract
Background: R2*-MRI is clinically used to noninvasively assess hepatic iron content (HIC) to guide potential iron chelation therapy. However, coexisting pathologies, such as fibrosis and steatosis, affect R2* measurements and may thus confound HIC estimations. Purpose: To evaluate whether a multispectral auto regressive moving average (ARMA) model can be used in conjunction with quantitative susceptibility mapping (QSM) to measure magnetic susceptibility as a confounder-free predictor of HIC. Study Type: Phantom study and in vivo cohort. Subjects: Nine iron phantoms covering clinically relevant R2* range (20–1200/second) and 48 patients (22 male, 26 female, median age 18 years). Field Strength/Sequence: Three-dimensional (3D) and two-dimensional (2D) multi-echo gradient echo (GRE) at 1.5 T. Assessment: ARMA-QSM modeling was performed on the complex 3D GRE signal to estimate R2*, fat fraction (FF), and susceptibility measurements. R2*-based dry clinical HIC values were calculated from the 2D GRE acquisition using a published R2*-HIC calibration curve as reference standard. Statistical Tests: Linear regression analysis was performed to compare ARMA R2* and susceptibility-based estimates to iron concentrations and dry clinical HIC values in phantoms and patients, respectively. Results: In phantoms, the ARMA R2* and susceptibility values strongly correlated with iron concentrations (R2 ≥ 0.9). In patients, the ARMA R2* values highly correlated (R2 = 0.97) with clinical HIC values with slope = 0.026, and the susceptibility values showed good correlation (R2 = 0.82) with clinical dry HIC values with slope = 3.3 and produced a dry-to-wet HIC ratio of 4.8. Data Conclusion: This study shows the feasibility that ARMA-QSM can simultaneously estimate susceptibility-based wet HIC, R2*-based dry HIC and FFs from a single multi-echo GRE acquisition. Our results demonstrate that both, R2* and susceptibility-based wet HIC values estimated with ARMA-QSM showed good association with clinical dry HIC values with slopes similar to published R2*-biopsy HIC calibration and dry-to-wet tissue weight ratio, respectively. Hence, our study shows that ARMA-QSM can provide potentially confounder-free assessment of hepatic iron overload. Level of Evidence: 3. Technical Efficacy: Stage 2.
Publication Title
Journal of Magnetic Resonance Imaging
Recommended Citation
Tipirneni-Sajja, A., Loeffler, R., Hankins, J., Morin, C., & Hillenbrand, C. (2021). Quantitative Susceptibility Mapping Using a Multispectral Autoregressive Moving Average Model to Assess Hepatic Iron Overload. Journal of Magnetic Resonance Imaging, 54 (3), 721-727. https://doi.org/10.1002/jmri.27584