Quantitative magnetization transfer imaging in human brain at 3 T via selective inversion recovery

Fast magnetization transfer saturation imaging of the brain using MP2RAGE T1 mapping

PURPOSE

Magnetization transfer saturation (MTsat) mapping is commonly used to examine the macromolecular content of brain tissue. This study compared variable flip angle (VFA) T1 mapping against compressed-sensing MP2RAGE (csMP2RAGE) T1 mapping for accelerating MTsat imaging.

METHODS

VFA, MP2RAGE, and csMP2RAGE were compared against inversion-recovery T1 in an aqueous phantom at 3 T. The same 1-mm VFA, MP2RAGE, and csMP2RAGE protocols were acquired in 4 healthy subjects to compare T1 and MTsat. Bloch-McConnell simulations were used to investigate differences between the phantom and in vivo T1 results. Ten healthy controls were imaged twice with the csMP2RAGE MTsat protocol to quantify repeatability.

RESULTS

The MP2RAGE and csMP2RAGE protocols were 13.7% and 32.4% faster than the VFA protocol, respectively. At these scan times, all approaches provided strong repeatability and accurate T1 times (< 5% difference) in the phantom, but T1 accuracy was more impacted by T2 for VFA than for MP2RAGE. In vivo, VFA estimated longer T1 times than MP2RAGE and csMP2RAGE. Simulations suggest that the differences in the T1 measured using VFA, MP2RAGE, and inversion recovery could be explained by the magnetization-transfer effects. In the test-retest experiment, we found that the csMP2RAGE has a minimum detectable change of 2.3% for T1 mapping and 7.8% for MTsat imaging.

CONCLUSIONS

We demonstrated that MP2RAGE can be used in place of VFA T1 mapping in an MTsat protocol. Furthermore, a shorter scan time and high repeatability can be achieved using the csMP2RAGE sequence.

Rapid quantitative magnetization transfer imaging: Utilizing the hybrid state and the generalized Bloch model

PURPOSE

To explore efficient encoding schemes for quantitative magnetization transfer (qMT) imaging with few constraints on model parameters.

THEORY AND METHODS

We combine two recently proposed models in a Bloch-McConnell equation: the dynamics of the free spin pool are confined to the hybrid state, and the dynamics of the semi-solid spin pool are described by the generalized Bloch model. We numerically optimize the flip angles and durations of a train of radio frequency pulses to enhance the encoding of three qMT parameters while accounting for all eight parameters of the two-pool model. We sparsely sample each time frame along this spin dynamics with a three-dimensional radial koosh-ball trajectory, reconstruct the data with subspace modeling, and fit the qMT model with a neural network for computational efficiency.

RESULTS

We extracted qMT parameter maps of the whole brain with an effective resolution of 1.24 mm from a 12.6-min scan. In lesions of multiple sclerosis subjects, we observe a decreased size of the semi-solid spin pool and longer relaxation times, consistent with previous reports.

CONCLUSION

The encoding power of the hybrid state, combined with regularized image reconstruction, and the accuracy of the generalized Bloch model provide an excellent basis for efficient quantitative magnetization transfer imaging with few constraints on model parameters.

Unconstrained quantitative magnetization transfer imaging: disentangling T1 of the free and semi-solid spin pools

Since the inception of magnetization transfer (MT) imaging, it has been widely assumed that Henkelman's two spin pools have similar longitudinal relaxation times, which motivated many researchers to constrain them to each other. However, several recent publications reported a T 1 s of the semi-solid spin pool that is much shorter than T 1 f of the free pool. While these studies tailored experiments for robust proofs-of-concept, we here aim to quantify the disentangled relaxation processes on a voxel-by-voxel basis in a clinical imaging setting, i.e., with an effective resolution of 1.24mm isotropic and full brain coverage in 12min. To this end, we optimized a hybrid-state pulse sequence for mapping the parameters of an unconstrained MT model. We scanned four people with relapsing-remitting multiple sclerosis (MS) and four healthy controls with this pulse sequence and estimated T 1 f ≈ 1.84 s and T 1 s ≈ 0.34 s in healthy white matter. Our results confirm the reports that T 1 s ≪ T 1 f and we argue that this finding identifies MT as an inherent driver of longitudinal relaxation in brain tissue. Moreover, we estimated a fractional size of the semi-solid spin pool of m 0 s ≈ 0.212 , which is larger than previously assumed. An analysis of T 1 f in normal-appearing white matter revealed statistically significant differences between individuals with MS and controls.

Quantitative magnetization transfer MRI unbiased by on-resonance saturation and dipolar order contributions

PURPOSE

To demonstrate the bias in quantitative MT (qMT) measures introduced by the presence of dipolar order and on-resonance saturation (ONRS) effects using magnetization transfer (MT) spoiled gradient-recalled (SPGR) acquisitions, and propose changes to the acquisition and analysis strategies to remove these biases.

METHODS

The proposed framework consists of SPGR sequences prepared with simultaneous dual-offset frequency-saturation pulses to cancel out dipolar order and associated relaxation (T_1D ) effects in Z-spectrum acquisitions, and a matched quantitative MT (qMT) mathematical model that includes ONRS effects of readout pulses. Variable flip angle and MT data were fitted jointly to simultaneously estimate qMT parameters (macromolecular proton fraction [MPF], T_2,f , T_2,b , R, and free pool T₁ ). This framework is compared with standard qMT and investigated in terms of reproducibility, and then further developed to follow a joint single-point qMT methodology for combined estimation of MPF and T₁ .

RESULTS

Bland-Altman analyses demonstrated a systematic underestimation of MPF (-2.5% and -1.3%, on average, in white and gray matter, respectively) and overestimation of T₁ (47.1 ms and 38.6 ms, on average, in white and gray matter, respectively) if both ONRS and dipolar order effects are ignored. Reproducibility of the proposed framework is excellent (ΔMPF = -0.03% and ΔT₁  = -19.0 ms). The single-point methodology yielded consistent MPF and T₁ values with respective maximum relative average bias of -0.15% and -3.5 ms found in white matter.

CONCLUSION

The influence of acquisition strategy and matched mathematical model with regard to ONRS and dipolar order effects in qMT-SPGR frameworks has been investigated. The proposed framework holds promise for improved accuracy with reproducibility.

Rapid whole-brain myelin imaging with selective inversion recovery and compressed SENSE

PURPOSE

Quantitative magnetization transfer (QMT) using selective inversion recovery (SIR) can quantify the macromolecular-to-free proton pool size ratio (PSR), which has been shown to relate closely with myelin content. Currently clinical applications of SIR have been hampered by long scan times. In this work, the acceleration of SIR-QMT using CS-SENSE (compressed sensing SENSE) was systematically studied.

THEORY AND METHODS

Phantoms of varied concentrations of bovine serum albumin and human scans were first conducted to evaluate the SNR, precision of SIR-QMT parameters, and scan time. Based on these results, an optimized CS-SENSE factor of 8 was determined and the test-retest repeatability was further investigated.

RESULTS

A whole-brain SIR imaging of 6 min can be achieved. Bland-Altman analyses indicated excellent agreement between the test and retest sessions with a difference in mean PSR of 0.06% (and a difference in mean R_1f of -0.001 s^-1 ). In addition, the assessment of the intraclass correlation coefficient (ICC) revealed high reliability in nearly all the white matter and gray matter regions. In white matter regions, the ICC was 0.93 (95% confidence interval [CI]: 0.88-0.96, p < 0.001) for PSR, and 0.90 (95% CI: 0.83-0.94, p < 0.001) for R_1f . In gray matter, ICC was 0.84 (95% CI: 0.66-0.93, p < 0.001) in PSR, and 0.98 (95% CI: 0.95-0.99, p < 0.001) for R_1f . The method also showed excellent capability to detect focal lesions in multiple sclerosis.

CONCLUSION

Rapid, reliable, and sensitive whole-brain SIR imaging can be achieved using CS-SENSE, which is expected to significantly promote widespread clinical translation.

High-resolution magnetization-transfer imaging of post-mortem marmoset brain: Comparisons with relaxometry and histology

Cell membranes and macromolecules or paramagnetic compounds interact with water proton spins, which modulates magnetic resonance imaging (MRI) contrast providing information on tissue composition. For a further investigation, quantitative magnetization transfer (qMT) parameters (at 3T), including the ratio of the macromolecular and water proton pools, F, and the exchange-rate constant as well as the (observed) longitudinal and the effective transverse relaxation rates (at 3T and 7T), R₁^obs and R₂^*, respectively, were measured at high spatial resolution (200 µm) in a slice of fixed marmoset brain and compared to histology results obtained with Gallyas' myelin stain and Perls' iron stain. R₁^obs and R₂^* were linearly correlated with the iron content for the entire slice, whereas distinct differences were obtained between gray and white matter for correlations of relaxometry and qMT parameters with myelin content. The combined results suggest that the macromolecular pool interacting with water consists of myelin and (less efficient) non-myelin contributions. Despite strong correlation of F and R₁^obs, none of these parameters was uniquely specific to myelination. Due to additional sensitivity to iron stores, R₁^obs and R₂^* were more sensitive for depicting microstructural differences between cortical layers than F.

Quantitative Magnetization EXchange MRI Measurement of Liver Fibrosis Model in Rodents

BACKGROUND

Quantitative MRI can elucidate the complex microstructural changes in liver disease. The Magnetization EXchange (MEX) method estimates macromolecular fraction, such as collagen, and can potentially aid in this task.

HYPOTHESIS

MEX sequence, and its derived quantitative macromolecular fraction, should correlate with collagen deposition in rodents liver fibrosis model.

STUDY TYPE

Prospective.

ANIMAL MODEL

Sixteen adults Sprague-Dawley rats and 13 adults C57BL/6 strain mice given carbon tetrachloride (CCl₄ ) twice weekly for 6 or 8 weeks.

FIELD STRENGTH/SEQUENCE

A 7 T scanner. MEX sequence (selective suppression and magnetization exchange), spin-echo and gradient-echo scans.

ASSESSMENT

Macromolecular fraction (F) and T₁ were extracted for each voxel and for livers' regions of interest, additional to calculating the percentage of F > 0.1 pixels in F maps (high-F). Histology included staining with hematoxylin and eosin, picrosirius red and Masson trichrome, and inflammation scoring. Quantitative collagen percentage calculated using automatic spectral-segmentation of the staining.

STATISTICAL TESTS

Comparing CCl₄ -treated groups and controls using Welch's t-test and paired t-test between different time points. Pearson's correlation used between ROI MEX parameters or high-F fraction, and quantitative histology. F or T₁ , and inflammation scores were tested with one-sided t-test. P < 0.05 was deemed significant.

RESULTS

Rats: F values were significantly different after 6 weeks of treatment (0.10 ± 0.02) compared to controls (0.080 ± 0.003). After 8 weeks, F significantly increased (0.11 ± 0.02) in treated animals, while controls are not significant (0.0814 ± 0.0008, P = 0.079). F correlated with quantitative histology (R = 0.87), and T₁ was significantly different between inflammation scores (1: 1332 ± 224 msec, 2: 2007 ± 464 msec). Mice: F was significantly higher (0.062 ± 0.006) in treatment group compared to controls (0.042 ± 0.006). F and high-F fraction correlated with quantitative histology (R = 0.88; R = 0.84). T₁ was significantly different between inflammation scores (1:1366 ± 99 msec; 2:1648 ± 45 msec).

DATA CONCLUSION

MEX extracted parameters are sensitive to collagen deposition and inflammation and are correlated with histology results of mouse and rat liver fibrosis model.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 3.

Quantitative magnetization transfer imaging in relapsing-remitting multiple sclerosis: a systematic review and meta-analysis

Myelin-sensitive MRI such as magnetization transfer imaging has been widely used in multiple sclerosis. The influence of methodology and differences in disease subtype on imaging findings is, however, not well established. Here, we systematically review magnetization transfer brain imaging findings in relapsing-remitting multiple sclerosis. We examine how methodological differences, disease effects and their interaction influence magnetization transfer imaging measures. Articles published before 06/01/2021 were retrieved from online databases (PubMed, EMBASE and Web of Science) with search terms including 'magnetization transfer' and 'brain' for systematic review, according to a pre-defined protocol. Only studies that used human in vivo quantitative magnetization transfer imaging in adults with relapsing-remitting multiple sclerosis (with or without healthy controls) were included. Additional data from relapsing-remitting multiple sclerosis subjects acquired in other studies comprising mixed disease subtypes were included in meta-analyses. Data including sample size, MRI acquisition protocol parameters, treatments and clinical findings were extracted and qualitatively synthesized. Where possible, effect sizes were calculated for meta-analyses to determine magnetization transfer (i) differences between patients and healthy controls; (ii) longitudinal change and (iii) relationships with clinical disability in relapsing-remitting multiple sclerosis. Eighty-six studies met inclusion criteria. MRI acquisition parameters varied widely, and were also underreported. The majority of studies examined the magnetization transfer ratio in white matter, but magnetization transfer metrics, brain regions examined and results were heterogeneous. The analysis demonstrated a risk of bias due to selective reporting and small sample sizes. The pooled random-effects meta-analysis across all brain compartments revealed magnetization transfer ratio was 1.17 per cent units (95% CI -1.42 to -0.91) lower in relapsing-remitting multiple sclerosis than healthy controls (z-value: -8.99, P < 0.001, 46 studies). Linear mixed-model analysis did not show a significant longitudinal change in magnetization transfer ratio across all brain regions [β = 0.12 (-0.56 to 0.80), t-value = 0.35, P = 0.724, 14 studies] or normal-appearing white matter alone [β = 0.037 (-0.14 to 0.22), t-value = 0.41, P = 0.68, eight studies]. There was a significant negative association between the magnetization transfer ratio and clinical disability, as assessed by the Expanded Disability Status Scale [r = -0.32 (95% CI -0.46 to -0.17); z-value = -4.33, P < 0.001, 13 studies]. Evidence suggests that magnetization transfer imaging metrics are sensitive to pathological brain changes in relapsing-remitting multiple sclerosis, although effect sizes were small in comparison to inter-study variability. Recommendations include: better harmonized magnetization transfer acquisition protocols with detailed methodological reporting standards; larger, well-phenotyped cohorts, including healthy controls; and, further exploration of techniques such as magnetization transfer saturation or inhomogeneous magnetization transfer ratio.

Generalized Bloch model: A theory for pulsed magnetization transfer

PURPOSE

The paper introduces a classical model to describe the dynamics of large spin-1/2 ensembles associated with nuclei bound in large molecule structures, commonly referred to as the semi-solid spin pool, and their magnetization transfer (MT) to spins of nuclei in water.

THEORY AND METHODS

Like quantum-mechanical descriptions of spin dynamics and like the original Bloch equations, but unlike existing MT models, the proposed model is based on the algebra of angular momentum in the sense that it explicitly models the rotations induced by radiofrequency (RF) pulses. It generalizes the original Bloch model to non-exponential decays, which are, for example, observed for semi-solid spin pools. The combination of rotations with non-exponential decays is facilitated by describing the latter as Green's functions, comprised in an integro-differential equation.

RESULTS

Our model describes the data of an inversion-recovery magnetization-transfer experiment with varying durations of the inversion pulse substantially better than established models. We made this observation for all measured data, but in particular for pulse durations smaller than 300 μs. Furthermore, we provide a linear approximation of the generalized Bloch model that reduces the simulation time by approximately a factor 15,000, enabling simulation of the spin dynamics caused by a rectangular RF-pulse in roughly 2 μs.

CONCLUSION

The proposed theory unifies the original Bloch model, Henkelman's steady-state theory for MT, and the commonly assumed rotation induced by hard pulses (i.e., strong and infinitesimally short applications of RF-fields) and describes experimental data better than previous models.

An in vivo implementation of the MEX MRI for myelin fraction of mice brain

OBJECTIVE

Magnetization EXchange (MEX) sequence measures a signal linearly dependent on the myelin proton fraction by selective suppression of water magnetization and a recovery period. Varying the recovery period enables extraction of the percentile fraction of myelin bound protons. We aim to demonstrate the MEX sequence sensitivity to the fraction of protons associated with myelin in mice brain, in vivo.

METHODS

The cuprizone mouse model was used to manipulate the myelin content. Mice fed cuprizone (n = 15) and normal chow (n = 8) were imaged in vivo using MEX sequence. MR images were segmented into corpus callosum and internal capsule (white matter) and cortical gray matter, and fitted to the recovery equation. Results were analyzed with correlation to MWF and histopathology.

RESULTS

The extracted parameters show significant differences in the corpus callosum between the cuprizone and control groups. The cuprizone group exhibited reduced myelin fraction 26.5% (P < 0.01). The gray matter values were less affected, with 13.5% reduction (P < 0.05); no changes were detected in the internal capsule. Results were validated by MWF scans and good correlation to the histology analysis (R² = 0.685).

CONCLUSION

The results of this first in vivo implementation of the MEX sequence provide a quantitative measure of demyelination in brain white matter.

Rapid parameter estimation for selective inversion recovery myelin imaging using an open-source Julia toolkit

Background

Magnetic resonance imaging (MRI) is used extensively to quantify myelin content, however computational bottlenecks remain challenging for advanced imaging techniques in clinical settings. We present a fast, open-source toolkit for processing quantitative magnetization transfer derived from selective inversion recovery (SIR) acquisitions that allows parameter map estimation, including the myelin-sensitive macromolecular pool size ratio (PSR). Significant progress has been made in reducing SIR acquisition times to improve clinically feasibility. However, parameter map estimation from the resulting data remains computationally expensive. To overcome this computational limitation, we developed a computationally efficient, open-source toolkit implemented in the Julia language.

Methods

To test the accuracy of this toolkit, we simulated SIR images with varying PSR and spin-lattice relaxation time of the free water pool (R 1f) over a physiologically meaningful scale from 5% to 20% and 0.5 to 1.5 s-1, respectively. Rician noise was then added, and the parameter maps were estimated using our Julia toolkit. Probability density histogram plots and Lin's concordance correlation coefficients (LCCC) were used to assess accuracy and precision of the fits to our known simulation data. To further mimic biological tissue, we generated five cross-linked bovine serum albumin (BSA) phantoms with concentrations that ranged from 1.25% to 20%. The phantoms were imaged at 3T using SIR, and data were fit to estimate PSR and R 1f. Similarly, a healthy volunteer was imaged at 3T, and SIR parameter maps were estimated to demonstrate the reduced computational time for a real-world clinical example.

Results

Estimated SIR parameter maps from our Julia toolkit agreed with simulated values (LCCC > 0.98). This toolkit was further validated using BSA phantoms and a whole brain scan at 3T. In both cases, SIR parameter estimates were consistent with published values using MATLAB. However, compared to earlier work using MATLAB, our Julia toolkit provided an approximate 20-fold reduction in computational time.

Conclusions

Presented here, we developed a fast, open-source, toolkit for rapid and accurate SIR MRI using Julia. The reduction in computational cost should allow SIR parameters to be accessible in clinical settings.

MR fingerprinting for semisolid magnetization transfer and chemical exchange saturation transfer quantification

Chemical exchange saturation transfer (CEST) MRI has positioned itself as a promising contrast mechanism, capable of providing molecular information at sufficient resolution and amplified sensitivity. However, it has not yet become a routinely employed clinical technique, due to a variety of confounding factors affecting its contrast-weighted image interpretation and the inherently long scan time. CEST MR fingerprinting (MRF) is a novel approach for addressing these challenges, allowing simultaneous quantitation of several proton exchange parameters using rapid acquisition schemes. Recently, a number of deep-learning algorithms have been developed to further boost the performance and speed of CEST and semi-solid macromolecule magnetization transfer (MT) MRF. This review article describes the fundamental theory behind semisolid MT/CEST-MRF and its main applications. It then details supervised and unsupervised learning approaches for MRF image reconstruction and describes artificial intelligence (AI)-based pipelines for protocol optimization. Finally, practical considerations are discussed, and future perspectives are given, accompanied by basic demonstration code and data.

Macromolecular Proton Fraction as a Myelin Biomarker: Principles, Validation, and Applications

Macromolecular proton fraction (MPF) is a quantitative MRI parameter describing the magnetization transfer (MT) effect and defined as a relative amount of protons bound to biological macromolecules with restricted molecular motion, which participate in magnetic cross-relaxation with water protons. MPF attracted significant interest during past decade as a biomarker of myelin. The purpose of this mini review is to provide a brief but comprehensive summary of MPF mapping methods, histological validation studies, and MPF applications in neuroscience. Technically, MPF maps can be obtained using a variety of quantitative MT methods. Some of them enable clinically reasonable scan time and resolution. Recent studies demonstrated the feasibility of MPF mapping using standard clinical MRI pulse sequences, thus substantially enhancing the method availability. A number of studies in animal models demonstrated strong correlations between MPF and histological markers of myelin with a minor influence of potential confounders. Histological studies validated the capability of MPF to monitor both demyelination and re-myelination. Clinical applications of MPF have been mainly focused on multiple sclerosis where this method provided new insights into both white and gray matter pathology. Besides, several studies used MPF to investigate myelin role in other neurological and psychiatric conditions. Another promising area of MPF applications is the brain development studies. MPF demonstrated the capabilities to quantitatively characterize the earliest stage of myelination during prenatal brain maturation and protracted myelin development in adolescence. In summary, MPF mapping provides a technically mature and comprehensively validated myelin imaging technology for various preclinical and clinical neuroscience applications.

MP3RAGE: Simultaneous mapping of T1 and B 1 + in human brain at 7T

PURPOSE

To map T₁ and the local flip angle ( B 1 + ) in human brain using a single MP3RAGE sequence with 3 rapid acquisitions of gradient echoes (RAGEs).

THEORY AND METHODS

A third RAGE with a relatively high flip angle was appended to an MP2RAGE sequence. Through curve fitting and a rational approximation for small flip angles and short TR, closed form solutions for T₁ and B 1 + were derived. The influence of different k-space encoding schemes on precision and whether edge enhancement artifacts could be reduced with a saturation pulse applied prior to the third RAGE were explored. Validation of T₁ estimates was performed using single-slice inversion recovery (IR) and a subsequent region-of-interest-based comparison, whereas validation of B 1 + was performed using a whole brain pixelwise comparison to a DREAM flip angle mapping protocol. Lastly, MP3RAGE was compared to T₁ -mapping by MP2RAGE with separate B 1 + correction.

RESULTS

Whole brain maps of T₁ and B 1 + at 1 mm isotropic resolution were obtained with MP3RAGE in 06:37 min. A linear-reverse centric-reverse centric phase-encoding order of the 3 RAGEs improved precision, and artifacts were successfully reduced with the saturation pulse. Estimations of T₁ and B 1 + deviated +2.5 ± 3.1% and -1.7 ± 8.6% from their respective references.

CONCLUSION

T₁ and B 1 + can be mapped simultaneously using MP3RAGE. The approach can be thought of as combining MP2RAGE with a dual flip angle T₁ -mapping protocol. Both maps can be solved for analytically and will be inherently co-registered at the high resolution associated with MPRAGE.

An MR fingerprinting approach for quantitative inhomogeneous magnetization transfer imaging

PURPOSE

Magnetization transfer (MT) and inhomogeneous MT (ihMT) contrasts are used in MRI to provide information about macromolecular tissue content. In particular, MT is sensitive to macromolecules, and ihMT appears to be specific to myelinated tissue. This study proposes a technique to characterize MT and ihMT properties from a single acquisition, producing both semiquantitative contrast ratios and quantitative parameter maps.

THEORY AND METHODS

Building on previous work that uses multiband RF pulses to efficiently generate ihMT contrast, we propose a cyclic steady-state approach that cycles between multiband and single-band pulses to boost the achieved contrast. Resultant time-variable signals are reminiscent of an MR fingerprinting acquisition, except that the signal fluctuations are entirely mediated by MT effects. A dictionary-based low-rank inversion method is used to reconstruct the resulting images and to produce both semiquantitative MT ratio and ihMT ratio maps, as well as quantitative parameter estimates corresponding to an ihMT tissue model.

RESULTS

Phantom and in vivo brain data acquired at 1.5 Tesla demonstrate the expected contrast trends, with ihMT ratio maps showing contrast more specific to white matter, as has been reported by others. Quantitative estimation of semisolid fraction and dipolar T₁ was also possible and yielded measurements consistent with literature values in the brain.

CONCLUSION

By cycling between multiband and single-band pulses, an entirely MT-mediated fingerprinting method was demonstrated. This proof-of-concept approach can be used to generate semiquantitative maps and quantitatively estimate some macromolecular-specific tissue parameters.

Unbiased signal equation for quantitative magnetization transfer mapping in balanced steady-state free precession MRI

Purpose

Quantitative magnetization transfer (qMT) imaging can be used to quantify the proportion of protons in a voxel attached to macromolecules. Here, we show that the original qMT balanced steady‐state free precession (bSSFP) model is biased due to over‐simplistic assumptions made in its derivation.

Theory and Methods

We present an improved model for qMT bSSFP, which incorporates finite radiofrequency (RF) pulse effects as well as simultaneous exchange and relaxation. Furthermore, a correction relating to finite RF pulse effects for sinc‐shaped excitations is derived. The new model is compared to the original one in numerical simulations of the Bloch‐McConnell equations and in previously acquired in vivo data.

Results

Our numerical simulations show that the original signal equation is significantly biased in typical brain tissue structures (by 7%‐20%), whereas the new signal equation outperforms the original one with minimal bias (<1%). It is further shown that the bias of the original model strongly affects the acquired qMT parameters in human brain structures, with differences in the clinically relevant parameter of pool‐size‐ratio of up to 31%. Particularly high biases of the original signal equation are expected in an MS lesion within diseased brain tissue (due to a low T2/T1‐ratio), demanding a more accurate model for clinical applications.

Conclusion

The improved model for qMT bSSFP is recommended for accurate qMT parameter mapping in healthy and diseased brain tissue structures.

Understanding aqueous and non-aqueous proton T1 relaxation in brain

A full picture of longitudinal relaxation in complex heterogeneous environments like white matter brain tissue remains elusive. In tissue, successive approximations, from the solvation layer model to the two pool model, have highlighted how longitudinal magnetization evolution depends on both inter-compartmental exchange and spin-lattice relaxation. In white matter, however, these models fail to capture the behaviour of the two distinct aqueous pools, myelin water and intra/extra-cellular water. A challenge with testing more comprehensive multi-pool models lies in directly observing all pools, both aqueous and non-aqueous. In this work, we advance these efforts by integrating three main experimental and analytical elements: direct observation of the longitudinal relaxation of both the aqueous and the non-aqueous protons in white matter, a wide range of different initial conditions, and application of an analysis pipeline which includes lineshape, CPMG, and fitting of a four pool model. An eigenvector interpretation of the four pool model highlights how longitudinal relaxation in white matter depends on initial conditions. We find that a single set of model parameters is able to describe the entire range of relaxation behaviour observed in all the separable aqueous and non-aqueous pools in experiments involving six different initial conditions. Understanding of the nature and connectedness of the tissue components is crucial in the design and interpretation of many MRI measurements, especially those based on magnetization transfer and longitudinal relaxation. In particular, the dependency of relaxation behaviour on initial conditions is likely the basis for understanding method-dependent discrepancies in in vivo T₁.

Perilesional neurodegenerative injury in multiple sclerosis: Relation to focal lesions and impact on disability

BACKGROUND

Axonal injury is the primary source of irreversible neurological decline in persons with multiple sclerosis (pwMS). Identifying and quantifying myelin and axonal loss in lesional and perilesional tissue in vivo is fundamental for a better understanding of multiple sclerosis (MS) outcomes and patient impairment. Using advanced magnetic resonance imaging (MRI) methods, consisting of selective inversion recovery quantitative magnetization transfer imaging (SIR-qMT) and multi-compartment diffusion MRI with the spherical mean technique (SMT), we conducted a cross-sectional pilot study to assess myelin and axonal damage in the normal appearing white matter (NAWM) surrounding chronic black holes (cBHs) and how this pathology correlates with disability in vivo. We hypothesized that lesional axonal transection propagates tissue injury in the surrounding NAWM and that the degree of this injury is related to patient disability.

METHODS

Eighteen pwMS underwent a 3.0 Tesla conventional clinical MRI, inclusive of T1 and T2 weighted protocols, as well as SIR-qMT and SMT. Regions of interests (ROIs) were manually delineated in cBHs, NAWM neighboring cBHs (perilesional NAWM), distant ipsilateral NAWM and contra-lateral distant NAWM. SIR-qMT-derived macromolecular-to-free pool size ratio (PSR) and SMT-derived apparent axonal volume fraction (V_ax) were extracted to infer on myelin and axonal content, respectively. Group differences were assessed using mixed-effects regression models and correlation analyses were obtained by bootstrapping 95% confidence interval.

RESULTS

In comparison to perilesional NAWM, both PSR and V_ax values were reduced in cBHs (p < 0.0001) and increased in distant contra-lateral NAWM ROIs (p < 0.001 for PSR and p < 0.0001 for V_ax) but not ipsilateral NAWM (p = 0.176 for PSR and p = 0.549 for V_ax). V_ax values measured in cBHs correlated with those in perilesional NAWM (Pearson rho = 0.63, p < 0.001). No statistically relevant associations were seen between PSR/V_ax values and clinical and/or MRI metrics of the disease with the exception of cBH PSR values, which correlated with the Expanded Disability Status Scale (Pearson rho = -0.63, p = 0.03).

CONCLUSIONS

Our results show that myelin and axonal content, detected by PSR and V_ax, are reduced in perilesional NAWM, as a function of the degree of focal cBH axonal injury. This finding is indicative of an ongoing anterograde/retrograde degeneration and suggests that treatment prevention of cBH development is a key factor for preserving NAWM integrity in surrounding tissue. It also suggests that measuring changes in perilesional areas over time may be a useful measure of outcome for proof-of-concept clinical trials on neuroprotection and repair. PSR and V_ax largely failed to capture associations with clinical and MRI characteristics, likely as a result of the small sample size and cross-sectional design, however, longitudinal assessment of a larger cohort may unravel the impact of this pathology on disease progression.

Quantitative magnetization transfer imaging for non-contrast enhanced detection of myocardial fibrosis

PURPOSE

To develop a novel gadolinium-free model-based quantitative magnetization transfer (qMT) technique to assess macromolecular changes associated with myocardial fibrosis.

METHODS

The proposed sequence consists of a two-dimensional breath-held dual shot interleaved acquisition of five MT-weighted (MTw) spoiled gradient echo images, with variable MT flip angles (FAs) and off-resonance frequencies. A two-pool exchange model and dictionary matching were used to quantify the pool size ratio (PSR) and bound pool T2 relaxation ( T 2 B ). The signal model was developed and validated using 25 MTw images on a bovine serum albumin (BSA) phantom and in vivo human thigh muscle. A protocol with five MTw images was optimized for single breath-hold cardiac qMT imaging. The proposed sequence was tested in 10 healthy subjects and 5 patients with myocardial fibrosis and compared to late gadolinium enhancement (LGE).

RESULTS

PSR values in the BSA phantom were within the confidence interval of previously reported values (concentration 10% BSA = 5.9 ± 0.1%, 15% BSA = 9.4 ± 0.2%). PSR and T 2 B in thigh muscle were also in agreement with literature (PSR = 10.9 ± 0.3%, T 2 B = 6.4 ± 0.4 us). In 10 healthy subjects, global left ventricular PSR was 4.30 ± 0.65%. In patients, PSR was reduced in areas associated with LGE (remote: 4.68 ± 0.70% vs. fibrotic: 3.12 ± 0.78 %, n = 5, P < .002).

CONCLUSION

In vivo model-based qMT mapping of the heart was performed for the first time, with promising results for non-contrast enhanced assessment of myocardial fibrosis.

Unsupervised learning for magnetization transfer contrast MR fingerprinting: Application to CEST and nuclear Overhauser enhancement imaging

PURPOSE

To develop a fast, quantitative 3D magnetization transfer contrast (MTC) framework based on an unsupervised learning scheme, which will provide baseline reference signals for CEST and nuclear Overhauser enhancement imaging.

METHODS

Pseudo-randomized RF saturation parameters and relaxation delay times were applied in an MR fingerprinting framework to generate transient-state signal evolutions for different MTC parameters. Prospectively compressed sensing-accelerated (four-fold) MR fingerprinting images were acquired from 6 healthy volunteers at 3 T. A convolutional neural network framework in an unsupervised fashion was designed to solve an inverse problem of a two-pool MTC Bloch equation, and was compared with a conventional Bloch equation-based fitting approach. The MTC images synthesized by the convolutional neural network architecture were used for amide proton transfer and nuclear Overhauser enhancement imaging as a reference baseline image.

RESULTS

The fully unsupervised learning scheme incorporated with the two-pool exchange model learned a set of unique features that can describe the MTC-MR fingerprinting input, and allowed only small amounts of unlabeled data for training. The MTC parameter values estimated by the unsupervised learning method were in excellent agreement with values estimated by the conventional Bloch fitting approach, but dramatically reduced computation time by ~1000-fold.

CONCLUSION

Given the considerable time efficiency compared to conventional Bloch fitting, unsupervised learning-based MTC-MR fingerprinting could be a powerful tool for quantitative MTC and CEST/nuclear Overhauser enhancement imaging.

Determination of optimal parameters for 3D single-point macromolecular proton fraction mapping at 7T in healthy and demyelinated mouse brain

PURPOSE

To determine optimal constrained tissue parameters and off-resonance sequence parameters for single-point macromolecular proton fraction (SP-MPF) mapping based on a comprehensive quantitative magnetization transfer (qMT) protocol in healthy and demyelinated living mice at 7T.

METHODS

Using 3D spoiled gradient echo-based sequences, a comprehensive qMT protocol is performed by sampling the Z-spectrum of mice brains, in vivo. Provided additional T₁ , B 1 + and B₀ maps allow for the estimation of qMT tissue parameters, among which three will be constrained, namely the longitudinal and transverse relaxation characteristics of the free pool (R_1,f T_2,f ), the cross-relaxation rate (R) and the bound pool transverse relaxation time (T_2,r ). Different sets of constrained parameters are investigated to reduce the bias between the SP-MPF and its reference based on the comprehensive protocol.

RESULTS

Based on a whole-brain histogram analysis about the constrained parameters, the optimal experimental parameters that minimize the global bias between reference and SP-MPF maps consist of a 600° and 6 kHz off-resonance irradiation pulse. Following a Bland-Altman analysis over regions of interest, optimal constrained parameters were R_1,f T_2,f  = 0.0129, R = 26.5 s^-1 , and T_2,r  = 9.1 µs, yielding an overall MPF bias of 10^-4 (limits of agreement [-0.0068;0.0070]) and a relative variation of 0.64% ± 5.95% between the reference and the optimal single-point method across all mice.

CONCLUSION

The necessity of estimating animal model- and field-dependent constrained parameters was demonstrated. The single-point MPF method can be reliably applied at 7T, as part of routine preclinical in vivo imaging protocol in mice.

qMTNet: Accelerated quantitative magnetization transfer imaging with artificial neural networks

PURPOSE

To develop a set of artificial neural networks, collectively termed qMTNet, to accelerate data acquisition and fitting for quantitative magnetization transfer (qMT) imaging.

METHODS

Conventional and interslice qMT data were acquired with two flip angles at six offset frequencies from seven subjects for developing the networks and from four young and four older subjects for testing the generalizability. Two subnetworks, qMTNet-acq and qMTNet-fit, were developed and trained to accelerate data acquisition and fitting, respectively. qMTNet-2 is the sequential application of qMTNet-acq and qMTNet-fit to produce qMT parameters (exchange rate, pool fraction) from undersampled qMT data (two offset frequencies rather than six). qMTNet-1 is one single integrated network having the same functionality as qMTNet-2. qMTNet-fit was compared with a Gaussian kernel-based fitting. qMT parameters generated by the networks were compared with those from ground truth fitted with a dictionary-driven approach.

RESULTS

The proposed networks achieved high peak signal-to-noise ratio (>30) and structural similarity index (>97) in reference to the ground truth. qMTNet-fit produced qMT parameters in concordance with the ground truth with better performance than the Gaussian kernel-based fitting. qMTNet-2 and qMTNet-1 could accelerate data acquisition at threefold and accelerate fitting at 5800- and 4218-fold, respectively. qMTNet-1 showed slightly better performance than qMTNet-2, whereas qMTNet-2 was more flexible for applications.

CONCLUSION

The proposed single (qMTNet-1) and two joint neural networks (qMTNet-2) can accelerate qMT workflow for both data acquisition and fitting significantly. qMTNet has the potential to accelerate qMT imaging for clinical applications, which warrants further investigation.

Magnetization transfer in magnetic resonance fingerprinting

PURPOSE

To study the effects of magnetization transfer (MT, in which a semi-solid spin pool interacts with the free pool), in the context of magnetic resonance fingerprinting (MRF).

METHODS

Simulations and phantom experiments were performed to study the impact of MT on the MRF signal and its potential influence on T1 and T2 estimation. Subsequently, an MRF sequence implementing off-resonance MT pulses and a dictionary with an MT dimension, generated by incorporating a two-pool model, were used to estimate the fractional pool size in addition to the B 1 + , T1 , and T2 values. The proposed method was evaluated in the human brain.

RESULTS

Simulations and phantom experiments showed that an MRF signal obtained from a cross-linked bovine serum sample is influenced by MT. Using a dictionary based on an MT model, a better match between simulations and acquired MR signals can be obtained (NRMSE 1.3% vs. 4.7%). Adding off-resonance MT pulses can improve the differentiation of MT from T1 and T2 . In vivo results showed that MT affects the MRF signals from white matter (fractional pool-size ~16%) and gray matter (fractional pool-size ~10%). Furthermore, longer T1 (~1060 ms vs. ~860 ms) and T2 values (~47 ms vs. ~35 ms) can be observed in white matter if MT is accounted for.

CONCLUSION

Our experiments demonstrated a potential influence of MT on the quantification of T1 and T2 with MRF. A model that encompasses MT effects can improve the accuracy of estimated relaxation parameters and allows quantification of the fractional pool size.

Rapid whole-brain quantitative magnetization transfer imaging using 3D selective inversion recovery sequences

Selective inversion recovery (SIR) is a quantitative magnetization transfer (qMT) method that provides estimates of parameters related to myelin content in white matter, namely the macromolecular pool-size-ratio (PSR) and the spin-lattice relaxation rate of the free pool (R1f), without the need for independent estimates of ∆B0, B1+, and T1. Although the feasibility of performing SIR in the human brain has been demonstrated, the scan times reported previously were too long for whole-brain applications. In this work, we combined optimized, short-TR acquisitions, SENSE/partial-Fourier accelerations, and efficient 3D readouts (turbo spin-echo, SIR-TSE; echo-planar imaging, SIR-EPI; and turbo field echo, SIR-TFE) to obtain whole-brain data in 18, 10, and 7 min for SIR-TSE, SIR-EPI, SIR-TFE, respectively. Based on numerical simulations, all schemes provided accurate parameter estimates in large, homogenous regions; however, the shorter SIR-TFE scans underestimated focal changes in smaller lesions due to blurring. Experimental studies in healthy subjects (n = 8) yielded parameters that were consistent with literature values and repeatable across scans (coefficient of variation: PSR = 2.2-6.4%, R1f = 0.6-1.4%) for all readouts. Overall, SIR-TFE parameters exhibited the lowest variability, while SIR-EPI parameters were adversely affected by susceptibility-related image distortions. In patients with relapsing remitting multiple sclerosis (n = 2), focal changes in SIR parameters were observed in lesions using all three readouts; however, contrast was reduced in smaller lesions for SIR-TFE, which was consistent with the numerical simulations. Together, these findings demonstrate that efficient, accurate, and repeatable whole-brain SIR can be performed using 3D TFE, EPI, or TSE readouts; however, the appropriate readout should be tailored to the application.

Selective inversion recovery quantitative magnetization transfer imaging: Toward a 3 T clinical application in multiple sclerosis

BACKGROUND

Assessing the degree of myelin injury in patients with multiple sclerosis (MS) is challenging due to the lack of magnetic resonance imaging (MRI) methods specific to myelin quantity. By measuring distinct tissue parameters from a two-pool model of the magnetization transfer (MT) effect, quantitative magnetization transfer (qMT) may yield these indices. However, due to long scan times, qMT has not been translated clinically.

OBJECTIVES

We aim to assess the clinical feasibility of a recently optimized selective inversion recovery (SIR) qMT and to test the hypothesis that SIR-qMT-derived metrics are informative of radiological and clinical disease-related changes in MS.

METHODS

A total of 18 MS patients and 9 age- and sex-matched healthy controls (HCs) underwent a 3.0 Tesla (3 T) brain MRI, including clinical scans and an optimized SIR-qMT protocol. Four subjects were re-scanned at a 2-week interval to determine inter-scan variability.

RESULTS

SIR-qMT measures differed between lesional and non-lesional tissue (p < 0.0001) and between normal-appearing white matter (NAWM) of patients with more advanced disability and normal white matter (WM) of HCs (p < 0.05). SIR-qMT measures were associated with lesion volumes, disease duration, and disability scores (p ⩽ 0.002).

CONCLUSION

SIR-qMT at 3 T is clinically feasible and predicts both radiological and clinical disease severity in MS.

Does the magnetization transfer effect bias chemical exchange saturation transfer effects? Quantifying chemical exchange saturation transfer in the presence of magnetization transfer

Purpose

Chemical exchange saturation transfer (CEST) is an MRI technique sensitive to the presence of low‐concentration solute protons exchanging with water. However, magnetization transfer (MT) effects also arise when large semisolid molecules interact with water, which biases CEST parameter estimates if quantitative models do not account for macromolecular effects. This study establishes under what conditions this bias is significant and demonstrates how using an appropriate model provides more accurate quantitative CEST measurements.

Methods

CEST and MT data were acquired in phantoms containing bovine serum albumin and agarose. Several quantitative CEST and MT models were used with the phantom data to demonstrate how underfitting can influence estimates of the CEST effect. CEST and MT data were acquired in healthy volunteers, and a two‐pool model was fit in vivo and in vitro, whereas removing increasing amounts of CEST data to show biases in the CEST analysis also corrupts MT parameter estimates.

Results

When all significant CEST/MT effects were included, the derived parameter estimates for each CEST/MT pool significantly correlated (P < .05) with bovine serum albumin/agarose concentration; minimal or negative correlations were found with underfitted data. Additionally, a bootstrap analysis demonstrated that significant biases occur in MT parameter estimates (P < .001) when unmodeled CEST data are included in the analysis.

Conclusions

These results indicate that current practices of simultaneously fitting both CEST and MT effects in model‐based analyses can lead to significant bias in all parameter estimates unless a sufficiently detailed model is utilized. Therefore, care must be taken when quantifying CEST and MT effects in vivo by properly modeling data to minimize these biases.

Background suppressed magnetization transfer MRI

PURPOSE

Up to 30% of the hydrogen atoms in brain tissue are part of molecules ("semisolids") other than water. In MRI, their magnetization is typically not observed directly, but can influence the water magnetization through magnetization transfer (MT). Comparison of MRI scans differentially sensitized to MT allows estimation of the semisolid fraction and potential changes with disease. Here, we present an approach designed to improve this estimate by measuring the size of the MT effect in a single scan.

METHODS

A stimulated echo sequence was used to generate a spatial pattern in the longitudinal water magnetization, which was then given time to exchange with semisolids. After saturating the remaining water magnetization, reverse exchange was allowed to partly re-establish the original water magnetization pattern. The third excitation pulse then formed a stimulated echo out of this pattern.

RESULTS

MT data were obtained on 10 human subjects at 7 T with varying exchange times. The images showed the expected time dependence of signal associated with the forward and reverse exchange processes. Excellent suppression of non-exchanging background signal was achieved. As expected, this suppression came at the price of a substantial reduction in exchange-related signal (by ~75% compared to the signal in saturation recovery MT), in part because of the reliance on a 2-step exchange process.

CONCLUSION

The results demonstrate an MT signal can be observed in a single acquisition without subtraction. This may be advantageous for MT measurements when signal instabilities related to motion and physiological variations exceed thermal noise sources.

Low duty-cycle pulsed irradiation reduces magnetization transfer and increases the inhomogeneous magnetization transfer effect

Intense off-resonant RF irradiation can lead to saturation of the macromolecular pool magnetization and enhance bound pool dipolar order responsible for the inhomogeneous magnetization transfer (ihMT) effect, but the intensity of RF power in human imaging studies is limited by safety constraints on RF heating. High RF intensities can still be achieved if applied in short pulses with low duty-cycle. Here we investigate the benefits of low duty-cycle irradiation for MT and ihMT studies with both theoretical and experimental methods. Solutions for pulsed irradiation of a two-pool model including dipolar order effects were implemented. Experiments were conducted at 3 T in the brain and through the calf of healthy human subjects. 2D echo planar images were acquired following a preparation of RF irradiation with a 2 s train of 5 ms pulses repeated from between 10 to 100 ms for duty-cycles (DCs) of 50% to 5%, and at varying offset frequencies, and time averaged RF powers. MT and ihMT data were measured in regions of interest within gray matter, white matter and muscle, and fit to the model. RF irradiation effects on signal intensity were reduced at 5% relative to 50% DCs. This reduced RF effect was much larger for single than dual frequency irradiation. 5% DC irradiation reduced single and dual frequency MT ratios but increased ihMT ratios up to 3 fold in brain tissues. Muscle ihMT increased by an even larger factor, depending on the frequency and applied power. The model predicted these changes with duty-cycle. The model fit the data well and constrained model parameters. Low duty-cycle pulsed irradiation reduces MT effects and markedly increases dipolar order effects. This approach is an attractive method to enhance ihMT signal-to-noise ratio and demonstrates a measurable ihMT effect in muscle tissue at 3 T under acceptable specific absorption rates. The effects of duty-cycle changes demonstrated in a separate MT/ihMT preparation provide a route for new applications in magnetization-prepared MRI sequences.

Sensitivity regularization of the Cramér-Rao lower bound to minimize B1 nonuniformity effects in quantitative magnetization transfer imaging

PURPOSE

To develop and validate a regularization approach of optimizing B₁ insensitivity of the quantitative magnetization transfer (qMT) pool-size ratio (F).

METHODS

An expression describing the impact of B₁ inaccuracies on qMT fitting parameters was derived using a sensitivity analysis. To simultaneously optimize for robustness against noise and B₁ inaccuracies, the optimization condition was defined as the Cramér-Rao lower bound (CRLB) regularized by the B₁ -sensitivity expression for the parameter of interest (F). The qMT protocols were iteratively optimized from an initial search space, with and without B₁ regularization. Three 10-point qMT protocols (Uniform, CRLB, CRLB+B₁ regularization) were compared using Monte Carlo simulations for a wide range of conditions (e.g., SNR, B₁ inaccuracies, tissues).

RESULTS

The B₁ -regularized CRLB optimization protocol resulted in the best robustness of F against B₁ errors, for a wide range of SNR and for both white matter and gray matter tissues. For SNR = 100, this protocol resulted in errors of less than 1% in mean F values for B₁ errors ranging between -10 and 20%, the range of B₁ values typically observed in vivo in the human head at field strengths of 3 T and less. Both CRLB-optimized protocols resulted in the lowest σ_F values for all SNRs and did not increase in the presence of B₁ inaccuracies.

CONCLUSION

This work demonstrates a regularized optimization approach for improving the robustness of auxiliary measurements (e.g., B₁ ) sensitivity of qMT parameters, particularly the pool-size ratio (F). Predicting substantially less B₁ sensitivity using protocols optimized with this method, B₁ mapping could even be omitted for qMT studies primarily interested in F.

Selective Inversion Recovery Quantitative Magnetization Transfer Brain MRI at 7T: Clinical and Postmortem Validation in Multiple Sclerosis

BACKGROUND AND PURPOSE

An imaging biomarker of myelin integrity is an unmet need in multiple sclerosis (MS). Selective inversion recovery (SIR) quantitative magnetization transfer imaging (qMT) provides assays of myelin content in the human brain. We previously translated the SIR method to 7T and incorporated a rapid turbo field echo (TFE) readout for whole-brain imaging within clinically acceptable scan times. We herein provide histological validation and test in vivo feasibility and applicability of the SIR-TFE protocol in MS.

METHODS

Clinical (T₁ - and T₂ -weighted) and SIR-TFE MRI scans were performed at 7T in a postmortem MS brain and MRI data were acquired in 10 MS patients and 14 heathy volunteers in vivo. The following parameters were estimated from SIR data: the macromolecular-to-free water pool-size-ratio (PSR), the spin-lattice relaxation rate of water (R_1f ), and the MT exchange rate (k_mf ). Differences in SIR parameters across tissue types, eg, white matter lesions (WM-Ls) and normal appearing WM (NAWM) in patients, and normal white matter (NWM) in heathy volunteers were evaluated. Associations between SIR parameters and disability scores were assessed.

RESULTS

For postmortem scans, correspondence was observed between WM-Ls and NAWM from histology and PSR/R_1f values. In vivo differences were detected for PSR, R_1f , and k_mf between WM-Ls and NWM (P ≤ .041). Associations were seen between WM-Ls/ NAWM PSR and disability scores (r ≤ -.671, P ≤ .048).

CONCLUSIONS

SIR-qMT at 7T provides sensitive, quantitative measures of myelin integrity for clinical and research applications.

Optimization of selective inversion recovery magnetization transfer imaging for macromolecular content mapping in the human brain

PURPOSE

To optimize a selective inversion recovery (SIR) sequence for macromolecular content mapping in the human brain at 3.0T.

THEORY AND METHODS

SIR is a quantitative method for measuring magnetization transfer (qMT) that uses a low-power, on-resonance inversion pulse. This results in a biexponential recovery of free water signal that can be sampled at various inversion/predelay times (t_I/ t_D ) to estimate a subset of qMT parameters, including the macromolecular-to-free pool-size-ratio (PSR), the R₁ of free water (R_1f ), and the rate of MT exchange (k_mf ). The adoption of SIR has been limited by long acquisition times (≈4 min/slice). Here, we use Cramér-Rao lower bound theory and data reduction strategies to select optimal t_I /t_D combinations to reduce imaging times. The schemes were experimentally validated in phantoms, and tested in healthy volunteers (N = 4) and a multiple sclerosis patient.

RESULTS

Two optimal sampling schemes were determined: (i) a 5-point scheme (k_mf estimated) and (ii) a 4-point scheme (k_mf assumed). In phantoms, the 5/4-point schemes yielded parameter estimates with similar SNRs as our previous 16-point scheme, but with 4.1/6.1-fold shorter scan times. Pair-wise comparisons between schemes did not detect significant differences for any scheme/parameter. In humans, parameter values were consistent with published values, and similar levels of precision were obtained from all schemes. Furthermore, fixing k_mf reduced the sensitivity of PSR to partial-volume averaging, yielding more consistent estimates throughout the brain.

CONCLUSIONS

qMT parameters can be robustly estimated in ≤1 min/slice (without independent measures of ΔB₀ , B1+, and T₁ ) when optimized t_I -t_D combinations are selected.

Inferring brain tissue composition and microstructure via MR relaxometry

MRI relaxometry is sensitive to a variety of tissue characteristics in a complex manner, which makes it both attractive and challenging for characterizing tissue. This article reviews the most common water proton relaxometry measures, T₁, T₂, and T₂^*, and reports on their development and current potential to probe the composition and microstructure of brain tissue. The development of these relaxometry measures is challenged by the need for suitably accurate tissue models, as well as robust acquisition and analysis methodologies. MRI relaxometry has been established as a tool for characterizing neural tissue, particular with respect to myelination, and the potential for further development exists.

Pool size ratio of the substantia nigra in Parkinson's disease derived from two different quantitative magnetization transfer approaches

PURPOSE

We sought to measure quantitative magnetization transfer (qMT) properties of the substantia nigra pars compacta (SNc) in patients with Parkinson's disease (PD) and healthy controls (HCs) using a full qMT analysis and determine whether a rapid single-point measurement yields equivalent results for pool size ratio (PSR).

METHODS

Sixteen different MT-prepared MRI scans were obtained at 3 T from 16 PD patients and eight HCs, along with B1, B0, and relaxation time maps. Maps of PSR, free and macromolecular pool transverse relaxation times ([Formula: see text], [Formula: see text]) and rate of MT exchange between pools (k _mf ) were generated using a full qMT model. PSR maps were also generated using a single-point qMT model requiring just two MT-prepared images. qMT parameter values of the SNc, red nucleus, cerebral crus, and gray matter were compared between groups and methods.

RESULTS

PSR of the SNc was the only qMT parameter to differ significantly between groups (p < 0.05). PSR measured via single-point analysis was less variable than with the full MT model, provided slightly better differentiation of PD patients from HCs (area under curve 0.77 vs. 0.75) with sensitivity of 0.75 and specificity of 0.87, and was better than transverse relaxation time in distinguishing PD patients from HCs (area under curve 0.71, sensitivity 0.87, and specificity 0.50).

CONCLUSION

The increased PSR observed in the SNc of PD patients may provide a novel biomarker of PD, possibly associated with an increased macromolecular content. Single-point PSR mapping with reduced variability and shorter scan times relative to the full qMT model appears clinically feasible.

CEST imaging of fast exchanging amine pools with corrections for competing effects at 9.4 T

Chemical exchange saturation transfer (CEST) imaging of fast exchanging amine protons at 3 ppm offset from the water resonant frequency is of practical interest, but quantification of fast exchanging pools by CEST is challenging. To effectively saturate fast exchanging protons, high irradiation powers need to be applied, but these may cause significant direct water saturation as well as non-specific semi-solid magnetization transfer (MT) effects, and thus decrease the specificity of the measured signal. In addition, the CEST signal may depend on the water longitudinal relaxation time (T_1w ), which likely varies between tissues and with pathology, further reducing specificity. Previously, an analysis of the asymmetry of saturation effects (MTR_asym ) has been commonly used to quantify fast exchanging amine CEST signals. However, our results show that MTR_asym is greatly affected by the above factors, as well as asymmetric MT and nuclear Overhauser enhancement (NOE) effects. Here, we instead applied a relatively more specific inverse analysis method, named AREX (apparent exchange-dependent relaxation), that has previously been applied only to slow and intermediate exchanging solutes. Numerical simulations and controlled phantom experiments show that, although MTR_asym depends on T_1w and semi-solid content, AREX acquired in steady state does not, which suggests that AREX is more specific than MTR_asym . By combining with a fitting approach instead of using the asymmetric analysis to obtain reference signals, AREX can also avoid contaminations from asymmetric MT and NOE effects. Animal experiments show that these two quantification methods produce differing contrasts between tumors and contralateral normal tissues in rat brain tumor models, suggesting that conventional MTR_asym applied in vivo may be influenced by variations in T_1w , semi-solid content, or NOE effect. Thus, the use of MTR_asym may lead to misinterpretation, while AREX with corrections for competing effects likely enhances the specificity and accuracy of quantification to fast exchanging pools.

High-resolution three-dimensional macromolecular proton fraction mapping for quantitative neuroanatomical imaging of the rodent brain in ultra-high magnetic fields

A well-known problem in ultra-high-field MRI is generation of high-resolution three-dimensional images for detailed characterization of white and gray matter anatomical structures. T₁-weighted imaging traditionally used for this purpose suffers from the loss of contrast between white and gray matter with an increase of magnetic field strength. Macromolecular proton fraction (MPF) mapping is a new method potentially capable to mitigate this problem due to strong myelin-based contrast and independence of this parameter of field strength. MPF is a key parameter determining the magnetization transfer effect in tissues and defined within the two-pool model as a relative amount of macromolecular protons involved into magnetization exchange with water protons. The objectives of this study were to characterize the two-pool model parameters in brain tissues in ultra-high magnetic fields and introduce fast high-field 3D MPF mapping as both anatomical and quantitative neuroimaging modality for small animal applications. In vivo imaging data were obtained from four adult male rats using an 11.7T animal MRI scanner. Comprehensive comparison of brain tissue contrast was performed for standard R₁ and T₂ maps and reconstructed from Z-spectroscopic images two-pool model parameter maps including MPF, cross-relaxation rate constant, and T₂ of pools. Additionally, high-resolution whole-brain 3D MPF maps were obtained with isotropic 170µm voxel size using the single-point synthetic-reference method. MPF maps showed 3-6-fold increase in contrast between white and gray matter compared to other parameters. MPF measurements by the single-point synthetic reference method were in excellent agreement with the Z-spectroscopic method. MPF values in rat brain structures at 11.7T were similar to those at lower field strengths, thus confirming field independence of MPF. 3D MPF mapping provides a useful tool for neuroimaging in ultra-high magnetic fields enabling both quantitative tissue characterization based on the myelin content and high-resolution neuroanatomical visualization with high contrast between white and gray matter.

Rapid measurement of brain macromolecular proton fraction with transient saturation transfer MRI

PURPOSE

To develop an efficient MRI approach to estimate the nonwater proton fraction (f) in human brain.

METHODS

We implement a brief, efficient magnetization transfer (MT) pulse that selectively saturates the magnetization of the (semi-) solid protons, and monitor the transfer of this saturation to the water protons as a function of delay after saturation.

RESULTS

Analysis of the transient MT effect with two-pool model allowed robust extraction of f at both 3 and 7 T. This required estimating the longitudinal relaxation rate constant (R_1,MP and R_1,WP ) for both proton pools, which was achieved with the assumption of uniform R_1,MP and R_1,WP across brain tissues. Resulting values of f were approximately 50% higher than reported previously, which is partly attributed to MT-pulse efficiency and R_1,MP being higher than assumed previously.

CONCLUSION

Experiments performed on human brain in vivo at 3 and 7 T demonstrate the ability of the method to robustly determine f in a scan time of approximately 5 min. Magn Reson Med 77:2174-2185, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Fast macromolecular proton fraction mapping of the human liver in vivo for quantitative assessment of hepatic fibrosis

The macromolecular proton fraction (MPF) is a quantitative MRI parameter determining the magnetization transfer (MT) effect in tissues, and is defined as the relative amount of immobile macromolecular protons involved in magnetization exchange with mobile water protons. MPF has the potential to provide a quantitative assessment of fibrous tissue because of the intrinsically high MPF specific for collagen. The goal of this study was to investigate the relationship between histologically determined fibrosis stage and MPF in the liver parenchyma measured using a recently developed fast single-point clinically targeted MPF mapping method. Optimal saturation parameters for single-point liver MPF measurements were determined from the analysis of liver Z spectra in vivo based on the error propagation model. Sixteen patients with chronic hepatitis C viral infection underwent 3-T MRI using an optimized liver MPF mapping protocol. Fourteen patients had prior liver biopsy with histologically staged fibrosis (METAVIR scores F0-F3) and two patients had clinically diagnosed cirrhosis (score F4 was assigned). The protocol included four breath-hold three-dimensional scans with 2 × 3 × 6-mm(3) resolution and 10 transverse sections: dynamic acquisition of MT-weighted and reference images; dynamic acquisition of three images for variable flip angle T1 mapping; dual-echo B0 map; and actual flip angle imaging B1 map. The average liver MPF was determined as the mode of the MPF histograms. MPF was significantly increased in patients with clinically significant fibrosis (scores F2-F4, n = 6) relative to patients with no or mild fibrosis (scores F0-F1, n = 10): 6.49 ± 0.36% versus 5.94 ± 0.26%, p < 0.01 (Mann-Whitney test). MPF and fibrosis scores were strongly positively correlated, with a Spearman's rank correlation coefficient of 0.80 (p < 0.001). This study demonstrates the feasibility of fast MPF mapping of the human liver in vivo and confirms the hypothesis that MPF is increased in hepatic fibrosis and associated with fibrosis stage. MPF may be useful as a non-invasive imaging biomarker of hepatic fibrosis.

Analysis and correction of biases in cross-relaxation MRI due to biexponential longitudinal relaxation

PURPOSE

Cross-relaxation imaging (CRI) is a family of quantitative magnetization transfer techniques that utilize images obtained with off-resonance saturation and longitudinal relaxation rate (R1) maps reconstructed by the variable flip angle (VFA) method. It was demonstrated recently that a significant bias in an apparent VFA R1 estimation occurs in macromolecule-rich tissues due to magnetization transfer (MT)-induced biexponential behavior of longitudinal relaxation of water protons. The purpose of this article is to characterize theoretically and experimentally the resulting bias in the CRI maps and propose methods to correct it.

THEORY

The modified CRI algorithm is proposed, which corrects for such biases and yields accurate parametric bound pool fraction f, cross-relaxation rate k, and R1 maps. Additionally, an analytical correction procedure is introduced to recalculate previously obtained parameter values.

RESULTS

The systematic errors due to unaccounted MT-induced biexponential relaxation can be characterized as an overestimation of R1, f, and k, with a relative bias comparable with the magnitude of f. The phantom and human in vivo experiments demonstrate that both proposed modified CRI and analytical correction approaches significantly improve the accuracy of the CRI method.

CONCLUSION

The accuracy of the CRI method can be considerably improved by taking into account the contribution of MT-induced biexponential longitudinal relaxation into variable flip angle R1 measurements.

Influence of water compartmentation and heterogeneous relaxation on quantitative magnetization transfer imaging in rodent brain tumors

PURPOSE

The goal of this study was to investigate the influence of water compartmentation and heterogeneous relaxation properties on quantitative magnetization transfer (qMT) imaging in tissues, and in particular whether a two-pool model is sufficient to describe qMT data in brain tumors.

METHODS

Computer simulations and in vivo experiments with a series of qMT measurements before and after injection of Gd-DTPA were performed. Both off-resonance pulsed saturation (pulsed) and on-resonance selective inversion recovery (SIR) qMT methods were used, and all data were fit with a two-pool model only.

RESULTS

Simulations indicated that a two-pool fitting of four-pool data yielded accurate measures of pool size ratio (PSR) of macromolecular versus free water protons when there were fast transcytolemmal exchange and slow R1 recovery. The fitted in vivo PSR of both pulsed and SIR qMT methods showed no dependence on R1 variations caused by different concentrations of Gd-DTPA during wash-out, whereas the fitted kex (magnetization transfer exchange rate) changed significantly with R1 .

CONCLUSION

A two-pool model provides reproducible estimates of PSR in brain tumors independent of relaxation properties in the presence of relatively fast transcytolemmal exchange, whereas estimates of kex are biased by relaxation variations. In addition, estimates of PSR in brain tumors using the pulsed and SIR qMT methods agree well with one another. Magn Reson Med 76:635-644, 2016. © 2015 Wiley Periodicals, Inc.

Biexponential longitudinal relaxation in white matter: Characterization and impact on T1 mapping with IR-FSE and MP2RAGE

PURPOSE

Magnetization transfer in white matter (WM) causes biexponential relaxation, but most quantitative T1 measurements fit data assuming monoexponential relaxation. The resulting monoexponential T1 estimate varies based on scan parameters and represents a source of variation between studies, especially at high fields. In this study, we characterized WM T1 relaxation and performed simulations to determine how to minimize this deviation.

METHODS

To characterize biexponential relaxation, four volunteers were scanned at 3T and 7T using inversion recovery fast spin echo (IR-FSE) with 13 inversion times (TIs). Three volunteers were scanned with IR-FSE using TIs chosen by simulations to reduce T1 deviation, and with MP2RAGE.

RESULTS

At 3T, the biexponential relaxation has a short component of T1  = 48 ms (9%) and a long component of T1  = 939 ms. At 7T the short component is T1  = 57 ms (11%) and the long component is 1349 ms (89%). For IR-FSE, acquiring four TIs with a minimum of 150 ms (3T) or 200 ms (7T) yielded monoexponential T1 estimates that match the long component to within 10 ms. For MP2RAGE, significant differences (90 ms at 3T, 125 ms at 7T) remain at all parameter values.

CONCLUSION

Many T1 mapping sequences yield robust estimates of the long T1 component with suitable choice of TIs, allowing reproducible, sequence-independent T1 values to be measured. However, this is not true of MP2RAGE in its current implementation. Magn Reson Med 75:2265-2277, 2016. © 2015 Wiley Periodicals, Inc.

Variable flip angle T1 mapping in the human brain with reduced T2 sensitivity using fast radiofrequency-spoiled gradient echo imaging

PURPOSE

Variable flip angle (VFA) T1 quantification using three-dimensional (3D) radiofrequency (RF) spoiled gradient echo imaging offers the acquisition of whole-brain T1 maps in clinically acceptable times. However, conventional VFA T1 relaxometry is biased by incomplete spoiling (i.e., residual T2 dependency). A new postprocessing approach is proposed to overcome this T2-related bias.

METHODS

T1 is quantified from the signal ratio of two spoiled gradient echo (SPGR) images acquired at different flip angles using an analytical solution for the RF-spoiled steady-state signal in combination with a global T2 guess. T1 accuracy is evaluated from simulations and in vivo 3D SPGR imaging of the human brain at 3 Tesla.

RESULTS

The simulations demonstrated that the sensitivity of VFA T1 mapping to T2 can considerably be reduced using a global T2 guess. The method proved to deliver reliable and accurate T1 values in vivo for white and gray matter in good agreement with inversion recovery reference measurements.

CONCLUSION

Based on a global T2 estimate, the accuracy of VFA T1 relaxometry in the human brain can substantially be improved compared with conventional approaches which rely on the generally wrong assumption of ideal spoiling.

Differentiation and quantification of inflammation, demyelination and axon injury or loss in multiple sclerosis

Axon injury/loss, demyelination and inflammation are the primary pathologies in multiple sclerosis lesions. Despite the prevailing notion that axon/neuron loss is the substrate of clinical progression of multiple sclerosis, the roles that these individual pathological processes play in multiple sclerosis progression remain to be defined. An imaging modality capable to effectively detect, differentiate and individually quantify axon injury/loss, demyelination and inflammation, would not only facilitate the understanding of the pathophysiology underlying multiple sclerosis progression, but also the assessment of treatments at the clinical trial and individual patient levels. In this report, the newly developed diffusion basis spectrum imaging was used to discriminate and quantify the underlying pathological components in multiple sclerosis white matter. Through the multiple-tensor modelling of diffusion weighted magnetic resonance imaging signals, diffusion basis spectrum imaging resolves inflammation-associated cellularity and vasogenic oedema in addition to accounting for partial volume effects resulting from cerebrospinal fluid contamination, and crossing fibres. Quantitative histological analysis of autopsied multiple sclerosis spinal cord specimens supported that diffusion basis spectrum imaging-determined cellularity, axon and myelin injury metrics closely correlated with those pathologies identified and quantified by conventional histological staining. We demonstrated in healthy control subjects that diffusion basis spectrum imaging rectified inaccurate assessments of diffusion properties of white matter tracts by diffusion tensor imaging in the presence of cerebrospinal fluid contamination and/or crossing fibres. In multiple sclerosis patients, we report that diffusion basis spectrum imaging quantitatively characterized the distinct pathologies underlying gadolinium-enhanced lesions, persistent black holes, non-enhanced lesions and non-black hole lesions, a task yet to be demonstrated by other neuroimaging approaches. Diffusion basis spectrum imaging-derived radial diffusivity (myelin integrity marker) and non-restricted isotropic diffusion fraction (oedema marker) correlated with magnetization transfer ratio, supporting previous reports that magnetization transfer ratio is sensitive not only to myelin integrity, but also to inflammation-associated oedema. Our results suggested that diffusion basis spectrum imaging-derived quantitative biomarkers are highly consistent with histology findings and hold promise to accurately characterize the heterogeneous white matter pathology in multiple sclerosis patients. Thus, diffusion basis spectrum imaging can potentially serve as a non-invasive outcome measure to assess treatment effects on the specific components of underlying pathology targeted by new multiple sclerosis therapies.

A combined analytical solution for chemical exchange saturation transfer and semi-solid magnetization transfer

Off-resonant RF irradiation in tissue indirectly lowers the water signal by saturation transfer processes: on the one hand, there are selective chemical exchange saturation transfer (CEST) effects originating from exchanging endogenous protons resonating a few parts per million from water; on the other hand, there is the broad semi-solid magnetization transfer (MT) originating from immobile protons associated with the tissue matrix with kilohertz linewidths. Recently it was shown that endogenous CEST contrasts can be strongly affected by the MT background, so corrections are needed to derive accurate estimates of CEST effects. Herein we show that a full analytical solution of the underlying Bloch-McConnell equations for both MT and CEST provides insights into their interaction and suggests a simple means to isolate their effects. The presented analytical solution, based on the eigenspace solution of the Bloch-McConnell equations, extends previous treatments by allowing arbitrary lineshapes for the semi-solid MT effects and simultaneously describing multiple CEST pools in the presence of a large MT pool for arbitrary irradiation. The structure of the model indicates that semi-solid MT and CEST effects basically add up inversely in determining the steady-state Z-spectrum, as previously shown for direct saturation and CEST effects. Implications for existing previous CEST analyses in the presence of a semi-solid MT are studied and discussed. It turns out that, to accurately quantify CEST contrast, a good reference Z-value, the observed longitudinal relaxation rate of water, and the semi-solid MT pool size fraction must all be known.

Multi-parametric MRI characterization of healthy human thigh muscles at 3.0 T - relaxation, magnetization transfer, fat/water, and diffusion tensor imaging

Muscle diseases commonly have clinical presentations of inflammation, fat infiltration, fibrosis, and atrophy. However, the results of existing laboratory tests and clinical presentations are not well correlated. Advanced quantitative MRI techniques may allow the assessment of myo-pathological changes in a sensitive and objective manner. To progress towards this goal, an array of quantitative MRI protocols was implemented for human thigh muscles; their reproducibility was assessed; and the statistical relationships among parameters were determined. These quantitative methods included fat/water imaging, multiple spin-echo T2 imaging (with and without fat signal suppression, FS), selective inversion recovery for T1 and quantitative magnetization transfer (qMT) imaging (with and without FS), and diffusion tensor imaging. Data were acquired at 3.0 T from nine healthy subjects. To assess the repeatability of each method, the subjects were re-imaged an average of 35 days later. Pre-testing lifestyle restrictions were applied to standardize physiological conditions across scans. Strong between-day intra-class correlations were observed in all quantitative indices except for the macromolecular-to-free water pool size ratio (PSR) with FS, a metric derived from qMT data. Two-way analysis of variance revealed no significant between-day differences in the mean values for any parameter estimate. The repeatability was further assessed with Bland-Altman plots, and low repeatability coefficients were obtained for all parameters. Among-muscle differences in the quantitative MRI indices and inter-class correlations among the parameters were identified. There were inverse relationships between fractional anisotropy (FA) and the second eigenvalue, the third eigenvalue, and the standard deviation of the first eigenvector. The FA was positively related to the PSR, while the other diffusion indices were inversely related to the PSR. These findings support the use of these T1 , T2 , fat/water, and DTI protocols for characterizing skeletal muscle using MRI. Moreover, the data support the existence of a common biophysical mechanism, water content, as a source of variation in these parameters.

Quantitative magnetization transfer imaging of rodent glioma using selective inversion recovery

Magnetization transfer (MT) provides an indirect means to detect noninvasively variations in macromolecular contents in biological tissues, but, so far, there have been only a few quantitative MT (qMT) studies reported in cancer, all of which used off-resonance pulsed saturation methods. This article describes the first implementation of a different qMT approach, selective inversion recovery (SIR), for the characterization of tumor in vivo using a rodent glioma model. The SIR method is an on-resonance method capable of fitting qMT parameters and T1 relaxation time simultaneously without mapping B0 and B1 , which is very suitable for high-field qMT measurements because of the lower saturation absorption rate. The results show that the average pool size ratio (PSR, the macromolecular pool versus the free water pool) in rat 9 L glioma (5.7%) is significantly lower than that in normal rat gray matter (9.2%) and white matter (17.4%), which suggests that PSR is potentially a sensitive imaging biomarker for the assessment of brain tumor. Despite being less robust, the estimated MT exchange rates also show clear differences from normal tissues (19.7 Hz for tumors versus 14.8 and 10.2 Hz for gray and white mater, respectively). In addition, the influence of confounding effects, e.g. B1 inhomogeneity, on qMT parameter estimates is investigated with numerical simulations. These findings not only help to better understand the changes in the macromolecular contents of tumors, but are also important for the interpretation of other imaging contrasts, such as chemical exchange saturation transfer of tumors.