Empirical field mapping for gradient nonlinearity correction of multi-site diffusion weighted MRI

BackgroundAchieving inter-site / inter-scanner reproducibility of diffusion weighted magnetic resonance imaging (DW-MRI) metrics has been challenging given differences in acquisition protocols, analysis models, and hardware factors.PurposeMagnetic field gradients impart scanner-dependent spatial variations in the applied diffusion weighting that can be corrected if the gradient nonlinearities are known. However, retrieving manufacturer nonlinearity specifications is not well supported and may introduce errors in interpretation of units or coordinate systems. We propose an empirical approach to mapping the gradient nonlinearities with sequences that are supported across the major scanner vendors.Study typeProspective observational study.SubjectsA spherical isotropic diffusion phantom, and a single human control volunteer.Field strength/sequence3 T (two scanners). Stejskal-Tanner spin echo sequence with b-values of 1000, 2000 s/mm² with 12, 32, and 384 diffusion gradient directions per shell.AssessmentWe compare the proposed correction with the prior approach using manufacturer specifications against typical diffusion pre-processing pipelines (i.e., ignoring spatial gradient nonlinearities). In phantom data, we evaluate metrics against the ground truth. In human and phantom data, we evaluate reproducibility across scans, sessions, and hardware.Statistical testsWilcoxon rank-sum test between uncorrected and corrected data.ResultsIn phantom data, our correction method reduces variation in mean diffusivity across sessions over uncorrected data (p < 0.05). In human data, we show that this method can also reduce variation in mean diffusivity across scanners (p < 0.05).ConclusionOur method is relatively simple, fast, and can be applied retroactively. We advocate incorporating voxel-specific b-value and b-vector maps should be incorporated in DW-MRI harmonization preprocessing pipelines to improve quantitative accuracy of measured diffusion parameters.     

Accuracy and repeatability of QRAPMASTER and MRF-vFA

Our purpose is to evaluate bias and repeatability of the quantitative MRI sequences QRAPMASTER, based on steady-state imaging, and variable Flip Angle MRF (MRF-VFA), based on the transient response.Both techniques are assessed with a standardized phantom and five volunteers on 1.5 T and 3 T clinical scanners. All scans were repeated eight times in consecutive weeks.In the phantom, the mean bias±95% confidence interval for T1 values with QRAPMASTER was 10 ± 10% on 1.5 T and 4 ± 13% on 3.0 T. The mean bias for T1 values with MRF-vFA was 21 ± 17% on 1.5 T and 9 ± 9% on 3.0 T. For T2 values the mean bias with QRAPMASTER was 12 ± 3% on 1.5 T and 23 ± 1% on 3.0 T. For T2 values the mean bias with MRF-vFA was 17 ± 1% on 1.5 T and 19 ± 2% on 3.0 T. QRAPMASTER estimated lower T1 and T2 values than MRF-vFA. Repeatability was good with low coefficients of variation (CoV). Mean CoV ± 95% confidence interval for T1 were 3.2 ± 0.4% on 1.5 T and 4.5 ± 0.8% on 3.0 T with QRAPMASTER and 2.7% ± 0.2% on 1.5 T and 2.5 ± 0.2% on 3.0 T with MRF-vFA. For T2 were 3.3 ± 1.9% on 1.5 T and 3.2 ± 0.6% on 3.0 T with QRAPMASTER and 2.0 ± 0.4% on 1.5 T and 5.7 ± 1.0% on 3.0 T with MRF-vFA.The in-vivo T1 and T2 are in the range of values previously reported by other authors.The in-vivo mean CoV ± 95% confidence interval in gray matter were for T1 1.7 ± 0.2% using QRAPMASTER and 0.7 ± 0.5% using MRF-vFA and for T2 were 0.9 ± 0.4% using QRAPMASTER and 2.4 ± 0.5% using MRF-vFA. In white matter were for T1 0.9 ± 0.3% using QRAPMASTER and 1.3 ± 1.1% using MRF-vFA and for T2 were 0.7 ± 0.4% using QRAPMASTER and 2.4 ± 0.4% using MRF-vFA. A GLM analysis showed that the variations in T1 and T2 mainly depend on the field strength and the subject, but not on the follow-up repetition in different days. This confirms the high repeatability of QRAPMASTER and MRF-vFA.In summary, QRAPMASTER and MRF-vFA on both systems were highly repeatable with moderate accuracy, providing results comparable to standard references. While repeatability was similar for both methods, QRAPMASTER was more accurate. QRAPMASTER is a tested commercial product but MRF-vFA is 4.77 times faster, which would ease the inclusion of quantitative relaxometry.     

On a sufficient condition for a Fano manifold to be covered by rational N-folds

In this paper, we prove a conjecture by T. Suzuki, which says if a smooth Fano manifold satisfies some positivity condition on its Chern characters, then it can be covered by rational N-folds. We prove this conjecture by using purely combinatorial properties of Bernoulli numbers.     

Blankets at birth: Transitional objects: Commentary on “The growth of cognition: Free energy minimization and the embryogenesis of cortical computation” by Wright and Bourke

Birth is accompanied by a complete reset of metabolic flows in the neonate, challenging the brain to fulfill the basic needs of life through action – breathing, feeding, crying. The perinatal period is fundamentally a transitional one, such that the basic conditions for thermodynamic self-regulation are re-established ex utero. Wright and Bourke lay out the core tenants of these conditions [1]; the emergence of regularities in cortical geometry and activity that allow “crisp” states. Before this can occur – in the immediate perinatal phase – electrical recordings of neonatal cortex suggest it passes through a highly critical regime - a phase transition - with disordered statistical fingerprints. The resolution of this state is a necessary condition for the more stable metabolic conditions that support the conjectures of Wright and Bourke.     

The Plasticity of the Carbohydrate Recognition Domain Dictates the Exquisite Mechanism of Binding of Human Macrophage Galactose-Type Lectin

The human macrophage galactose-type lectin (MGL), expressed on macrophages and dendritic cells (DCs), modulates distinct immune cell responses by recognizing N-acetylgalactosamine (GalNAc) containing structures present on pathogens, self-glycoproteins, and tumor cells. Herein, NMR spectroscopy and molecular dynamics (MD) simulations were used to investigate the structural preferences of MGL against different GalNAc-containing structures derived from the blood group A antigen, the Forssman antigen, and the GM2 glycolipid. NMR spectroscopic analysis of the MGL carbohydrate recognition domain (MGL-CRD, C181-H316) in the absence and presence of methyl α-GalNAc (α-MeGalNAc), a simple monosaccharide, shows that the MGL-CRD is highly dynamic and its structure is strongly altered upon ligand binding. This plasticity of the MGL-CRD structure explains the ability of MGL to accommodate different GalNAc-containing molecules. However, key differences are observed in the recognition process depending on whether the GalNAc is part of the blood group A antigen, the Forssman antigen, or GM2-derived structures. These results are in accordance with molecular dynamics simulations that suggest the existence of a distinct MGL binding mechanism depending on the context of GalNAc moiety presentation. These results afford new perspectives for the rational design of GalNAc modifications that fine tune MGL immune responses in distinct biological contexts, especially in malignancy.