Data-Driven Quantitative Susceptibility Mapping Using Loss Adaptive Dipole Inversion (LADI)

Quantitative susceptibility mapping using plug-and-play alternating direction method of multipliers

Quantitative susceptibility mapping employs regularization to reduce artifacts, yet many recent denoisers are unavailable for reconstruction. We developed a plug-and-play approach to QSM reconstruction (PnP QSM) and show its flexibility using several patch-based denoisers. We developed PnP QSM using alternating direction method of multiplier framework and applied collaborative filtering denoisers. We apply the technique to the 2016 QSM Challenge and in 10 glioblastoma multiforme datasets. We compared its performance with four published QSM techniques and a multi-orientation QSM method. We analyzed magnetic susceptibility accuracy using brain region-of-interest measurements, and image quality using global error metrics. Reconstructions on glioblastoma data were analyzed using ranked and semiquantitative image grading by three neuroradiologist observers to assess image quality (IQ) and sharpness (IS). PnP-BM4D QSM showed good correlation (β = 0.84, R² = 0.98, p < 0.05) with COSMOS and no significant bias (bias = 0.007 ± 0.012). PnP-BM4D QSM achieved excellent quality when assessed using structural similarity index metric (SSIM = 0.860), high frequency error norm (HFEN = 58.5), cross correlation (CC = 0.804), and mutual information (MI = 0.475) and also maintained good conspicuity of fine features. In glioblastoma datasets, PnP-BM4D QSM showed higher performance (IQ_Grade = 2.4 ± 0.4, IS_Grade = 2.7 ± 0.3, IQ_Rank = 3.7 ± 0.3, IS_Rank = 3.9 ± 0.3) compared to MEDI (IQ_Grade = 2.1 ± 0.5, IS_Grade = 2.1 ± 0.6, IQ_Rank = 2.4 ± 0.6, IS_Rank = 2.9 ± 0.2) and FANSI-TGV (IQ_Grade = 2.2 ± 0.6, IS_Grade = 2.1 ± 0.6, IQ_Rank = 2.7 ± 0.3, IS_Rank = 2.2 ± 0.2). We illustrated the modularity of PnP QSM by interchanging two additional patch-based denoisers. PnP QSM reconstruction was feasible, and its flexibility was shown using several patch-based denoisers. This technique may allow rapid prototyping and validation of new denoisers for QSM reconstruction for an array of useful clinical applications.

Magnetic susceptibility and R2* of myocardial reperfusion injury at 3T and 7T

PURPOSE

Magnetic susceptibility (Δχ) alterations have shown association with myocardial infarction (MI) iron deposition, yet there remains limited understanding of the relationship between relaxation rates and susceptibility or the effect of magnetic field strength. Hence, Δχ and R 2 ∗ in MI were compared at 3T and 7T.

METHODS

Subacute MI was induced by coronary artery ligation in male Yorkshire swine. 3D multiecho gradient echo imaging was performed at 1-week postinfarction at 3T and 7T. Quantitative susceptibility mapping images were reconstructed using a morphology-enabled dipole inversion. R 2 ∗ maps and quantitative susceptibility mapping were generated to assess the relationship between R 2 ∗ , Δχ, and field strength. Infarct histopathology was investigated.

RESULTS

Magnetic susceptibility was not significantly different across field strengths (7T: 126.8 ± 41.7 ppb; 3T: 110.2 ± 21.0 ppb, P = NS), unlike R 2 ∗ (7T: 247.0 ± 14.8 Hz; 3T: 106.1 ± 6.5 Hz, P < .001). Additionally, infarct Δχ and R 2 ∗ were significantly higher than remote myocardium. Magnetic susceptibility at 7T versus 3T had a significant association (β = 1.02, R2 = 0.82, P < .001), as did R 2 ∗ (β = 2.35, R2 = 0.98, P < .001). Infarct pathophysiology and iron deposition were detected through histology and compared with imaging findings.

CONCLUSION

R 2 ∗ showed dependence and Δχ showed independence of field strength. Histology validated the presence of iron and supported imaging findings.