Orientation dependence of inhomogeneous magnetization transfer and dipolar order relaxation rate in phospholipid bilayers

Characterization of the orientation dependence of magnetization transfer measures in single and crossing-fiber white matter

PURPOSE

To fully characterize the orientation dependence of magnetization transfer (MT) and inhomogeneous MT (ihMT) measures in the whole white matter (WM), for both single-fiber and crossing-fiber voxels.

METHODS

A characterization method was developed using the fiber orientation obtained from diffusion MRI (dMRI) with diffusion tensor imaging (DTI) and constrained spherical deconvolution. This allowed for characterization of the orientation dependence of measures in all of WM, regardless of the number of fiber orientation in a voxel. Furthermore, the orientation dependence inside 31 different WM bundles was characterized to evaluate the homogeneity of the effect. Variation of the results within and between-subject was assessed from a 12-subject dataset.

RESULTS

Previous results for single-fiber voxels were reproduced and a novel characterization was produced in voxels of crossing fibers, which seems to follow trends consistent with single-fiber results. Heterogeneity of the orientation dependence across bundles was observed, but homogeneity within similar bundles was also highlighted. Differences in behavior between MT and ihMT measures, as well as the ratio and saturation versions of these, were noted.

CONCLUSION

Orientation dependence characterization was proven possible over the entirety of WM. The vast range of effects and subtleties of the orientation dependence on MT measures showed the need for, but also the challenges of, a correction method.

Quantum dipole interactions and transient hydrogen bond orientation order in cells, cellular membranes and myelin sheath: Implications for MRI signal relaxation, anisotropy, and T1 magnetic field dependence

PURPOSE

Despite significant impact on the study of human brain, MRI lacks a theory of signal formation that integrates quantum interactions involving proton dipoles (a primary MRI signal source) with brain intricate cellular environment. The purpose of the present study is developing such a theory.

METHODS

We introduce the Transient Hydrogen Bond (THB) model, where THB-mediated quantum dipole interactions between water and protons of hydrophilic heads of amphipathic biomolecules forming cells, cellular membranes and myelin sheath serve as a major source of MR signal relaxation.

RESULTS

The THB theory predicts the existence of a hydrogen-bond-driven structural order of dipole-dipole connections within THBs as a primary factor for the anisotropy observed in MRI signal relaxation. We have also demonstrated that the conventional Lorentzian spectral density function decreases too fast at high frequencies to adequately capture the field dependence of brain MRI signal relaxation. To bridge this gap, we introduced a stretched spectral density function that surpasses the limitations of Lorentzian dispersion. In human brain, our findings reveal that at any time point only about 4% to 7% of water protons are engaged in quantum encounters within THBs. These ultra-short (2 to 3 ns), but frequent quantum spin exchanges lead to gradual recovery of magnetization toward thermodynamic equilibrium, that is, relaxation of MRI signal.

CONCLUSION

By incorporating quantum proton interactions involved in brain imaging, the THB approach introduces new insights on the complex relationship between brain tissue cellular structure and MRI measurements, thus offering a promising new tool for better understanding of brain microstructure in health and disease.

CEST and nuclear Overhauser enhancement imaging with deep learning-extrapolated semisolid magnetization transfer reference: Scan-rescan reproducibility and reliability studies

PURPOSE

To develop a novel MR physics-driven, deep-learning, extrapolated semisolid magnetization transfer reference (DeepEMR) framework to provide fast, reliable magnetization transfer contrast (MTC) and CEST signal estimations, and to determine the reproducibility and reliability of the estimates from the DeepEMR.

METHODS

A neural network was designed to predict a direct water saturation and MTC-dominated signal at a certain CEST frequency offset using a few high-frequency offset features in the Z-spectrum. The accuracy, scan-rescan reproducibility, and reliability of MTC, CEST, and relayed nuclear Overhauser enhancement (rNOE) signals estimated from the DeepEMR were evaluated on numerical phantoms and in heathy volunteers at 3 T. In addition, we applied the DeepEMR method to brain tumor patients and compared tissue contrast with other CEST calculation metrics.

RESULTS

The DeepEMR method demonstrated a high degree of accuracy in the estimation of reference MTC signals at ±3.5 ppm for APT and rNOE imaging, and computational efficiency (˜190-fold) compared with a conventional fitting approach. In addition, the DeepEMR method achieved high reproducibility and reliability (intraclass correlation coefficient = 0.97, intersubject coefficient of variation = 3.5%, and intrasubject coefficient of variation = 1.3%) of the estimation of MTC signals at ±3.5 ppm. In tumor patients, DeepEMR-based amide proton transfer images provided higher tumor contrast than a conventional MT ratio asymmetry image, particularly at higher B1 strengths (>1.5 μT), with a distinct delineation of the tumor core from normal tissue or peritumoral edema.

CONCLUSION

The DeepEMR approach is feasible for measuring clean APT and rNOE effects in longitudinal and cross-sectional studies with low scan-rescan variability.

Optimization of acquisition parameters for cortical inhomogeneous magnetization transfer (ihMT) imaging using a rapid gradient echo readout

PURPOSE

Imaging biomarkers with increased myelin specificity are needed to better understand the complex progression of neurological disorders. Inhomogeneous magnetization transfer (ihMT) imaging is an emergent technique that has a high degree of specificity for myelin content but suffers from low signal to-noise ratio (SNR). This study used simulations to determine optimal sequence parameters for ihMT imaging for use in high-resolution cortical mapping.

METHODS

MT-weighted cortical image intensity and ihMT SNR were simulated using modified Bloch equations for a range of sequence parameters. The acquisition time was limited to 4.5 min/volume. A custom MT-weighted RAGE sequence with center-out k-space encoding was used to enhance SNR at 3 T. Pulsed MT imaging was studied over a range of saturation parameters, and the impact of the turbo factor on the effective ihMT resolution was investigated. 1 mm isotropic ihMTsat maps were generated in 25 healthy adults.

RESULTS

Greater SNR was observed for larger number of bursts consisting of 6-8 saturation pulses each, combined with a high readout turbo factor. However, that protocol suffered from a point spread function that was more than twice the nominal resolution. For high-resolution cortical imaging, we selected a protocol with a higher effective resolution at the cost of a lower SNR. We present the first group-average ihMTsat whole-brain map at 1 mm isotropic resolution.

CONCLUSION

This study presents the impact of saturation and excitation parameters on ihMTsat SNR and resolution. We demonstrate the feasibility of high-resolution cortical myelin imaging using ihMTsat in less than 20 min.

Inhomogeneous magnetization transfer imaging: Concepts and directions for further development

Off-resonance radio frequency irradiation can induce the ordering of proton spins in the dipolar fields of their neighbors, in molecules with restricted mobility. This dipolar order decays with a characteristic relaxation time, T_1D , that is very different from the T₁ and T₂ relaxation of the nuclear alignment with the main magnetic field. Inhomogeneous magnetization transfer (ihMT) imaging is a refinement of magnetization transfer (MT) imaging that isolates the MT signal dependence on dipolar order relaxation times within motion-constrained molecules. Because T_1D relaxation is a unique contrast mechanism, ihMT may enable improved characterization of tissue. Initial work has stressed the high correlation between ihMT signal and myelin density. Dipolar order relaxation appears to be much longer in membrane lipids than other molecules. Recent work has shown, however, that ihMT acquisitions may also be adjusted to emphasize different ranges of T_1D . These newer approaches may be sensitive to other microstructural components of tissue. Here, we review the concepts and history of ihMT and outline the requirements for further development to realize its full potential.

Myelin biomarkers in the healthy adult brain: Correlation, reproducibility, and the effect of fiber orientation

PURPOSE

We investigated the correlation, reproducibility, and effect of white matter fiber orientation for three myelin-sensitive MRI techniques: magnetization transfer ratio (MTR), inhomogeneous magnetization transfer ratio (ihMTR), and gradient and spin echo-derived myelin water fraction (MWF).

METHODS

We measured the three metrics in 17 white and three deep grey matter regions in 17 healthy adults at 3 T.

RESULTS

We found a strong correlation between ihMTR and MTR (r = 0.70, p < 0.001) and ihMTR and MWF (r = 0.79, p < 0.001), and a weaker correlation between MTR and MWF (r = 0.54, p < 0.001). The dynamic range in white matter was greatest for MWF (2.0%-27.5%), followed by MTR (14.4%-23.2%) and then ihMTR (1.2%-5.4%). The average scan-rescan coefficient of variation for white matter regions was 0.6% MTR, 0.3% ihMTR, and 0.7% MWF in metric units; however, when adjusted by the dynamic range, these became 6.3%, 6.1% and 2.8%, respectively. All three metrics varied with fiber direction: MWF and ihMTR were lower in white matter fibers perpendicular to B₀ by 6% and 1%, respectively, compared with those parallel, whereas MTR was lower by 0.5% at about 40°, with the highest values at 90°. However, separating the apparent orientation dependence by white matter region revealed large dissimilarities in the trends, suggesting that real differences in myelination between regions are confounding the apparent orientation dependence measured using this method.

CONCLUSION

The strong correlation between ihMTR and MWF suggests that these techniques are measuring the same myelination; however, the larger dynamic range of MWF may provide more power to detect small differences in myelin.

Microscopic theory of spin-spin and spin-lattice relaxation of bound protons in cellular and myelin membranes-A lateral diffusion model (LDM)

PURPOSE

Deciphering salient features of biological tissue cellular microstructure in health and diseases is an ultimate goal of MRI. While most MRI approaches are based on studying MR properties of tissue "free" water indirectly affected by tissue microstructure, other approaches, such as magnetization transfer (MT), directly target signals from tissue-forming macromolecules. However, despite three-decades of successful applications, relationships between MT measurements and tissue microstructure remain elusive, hampering interpretation of experimental results. The goal of this paper is to develop microscopic theory connecting the structure of cellular and myelin membranes to their MR properties.

THEORY AND METHODS

Herein we introduce a lateral diffusion model (LDM) that explains the T2 (spin-spin) and T1 (spin-lattice) MRI relaxation properties of the macromolecular-bound protons by their dipole-dipole interaction modulated by the lateral diffusion of long lipid molecules forming cellular and myelin membranes.

RESULTS

LDM predicts anisotropic T1 and T2 relaxation of membrane-bound protons. Moreover, their T2 relaxation cannot be described in terms of a standard R2  = 1/T2 relaxation rate parameter, but rather by a relaxation rate function R2 (t) that depends on time t after RF excitation, having, in the main approximation, a logarithmic behavior: R2 (t) ∼ lnt. This anisotropic non-linear relaxation leads to an absorption lineshape that is different from Super-Lorentzian traditionally used in interpreting MT experiments.

CONCLUSION

LDM-derived analytical equations connect the membrane-bound protons T1 and T2 relaxation with dynamic distances between protons in neighboring membrane-forming lipid molecules and their lateral diffusion. This sheds new light on relationships between MT parameters and microstructure of cellular and myelin membranes.

Comparing myelin-sensitive magnetic resonance imaging measures and resulting g-ratios in healthy and multiple sclerosis brains

The myelin concentration and the degree of myelination of nerve fibers can provide valuable information on the integrity of human brain tissue. Magnetic resonance imaging (MRI) of myelin-sensitive parameters can help to non-invasively evaluate demyelinating diseases such as multiple sclerosis (MS). Several different myelin-sensitive MRI methods have been proposed to determine measures of the degree of myelination, in particular the g-ratio. However, variability in underlying physical principles and different biological models influence measured myelin concentrations, and consequently g-ratio values. We therefore investigated similarities and differences between five different myelin-sensitive MRI measures and their effects on g-ratio mapping in the brains of both MS patients and healthy volunteers. We compared two different estimates of the myelin water fraction (MWF) as well as the inhomogeneous magnetization transfer ratio (ihMTR), magnetization transfer saturation (MTsat), and macromolecular tissue volume (MTV) in 13 patients with MS and 14 healthy controls. In combination with diffusion-weighted imaging, we derived g-ratio parameter maps for each of the five different myelin measures. The g-ratio values calculated from different myelin measures varied strongly, especially in MS lesions. While, compared to normal-appearing white matter, MTsat and one estimate of the MWF resulted in higher g-ratio values within lesions, ihMTR, MTV, and the second MWF estimate resulted in lower lesion g-ratio values. As myelin-sensitive measures provide rough estimates of myelin content rather than absolute myelin concentrations, resulting g-ratio values strongly depend on the utilized myelin measure and model used for g-ratio mapping. When comparing g-ratio values, it is, thus, important to utilize the same MRI methods and models or to consider methodological differences. Particular caution is necessary in pathological tissue such as MS lesions.