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.

Improving B1+ parametric estimation in the brain from multispin-echo sequences using a fusion bootstrap moves solver.

PURPOSE: To simultaneously estimate the B1+ field (along with the T2 ) in the brain with multispin-echo (MSE) sequences and dictionary matching. METHODS: T2 mapping provides clinically relevant information such as in the assessment of brain degenerative diseases. It is commonly obtained with MSE sequences, and accuracy can be further improved by matching the MSE signal to a precomputed dictionary of echo-modulation curves. For additional T1 quantification, transmit B1+ field knowledge is also required. Preliminary work has shown that although simultaneous brain B1+ estimation along with T2 is possible, it presents a bimodal distribution with the main peak coinciding with the true value. By taking advantage of this, the B1+ maps are expected to be spatially smooth by applying an iterative method that takes into account each pixel neighborhood known as the fusion bootstrap moves solver (FBMS). The effect of the FBMS on B1+ accuracy and piecewise smoothness is investigated and different spatial regularization levels are compared. Total variation regularization was used for both B1+ and T2 simultaneous estimation because of its simplicity as an initial proof-of-concept; future work could explore non edge-preserving regularization independently for B1+ . RESULTS: Improvements in B1+ accuracy (up to 45.37% and 16.81% B1+ error decrease) and recovery of spatially homogeneous maps are shown in simulations and in vivo 3.0T brain data, respectively. CONCLUSION: Accurate B1+ estimated values can be obtained from widely available MSE sequences while jointly estimating T2 maps with the use of echo-modulation curve matching and FBMS at no further cost.

Phenotyping the Preterm Brain: Characterizing Individual Deviations From Normative Volumetric Development in Two Large Infant Cohorts.

The diverse cerebral consequences of preterm birth create significant challenges for understanding pathogenesis or predicting later outcome. Instead of focusing on describing effects common to the group, comparing individual infants against robust normative data offers a powerful alternative to study brain maturation. Here we used Gaussian process regression to create normative curves characterizing brain volumetric development in 274 term-born infants, modeling for age at scan and sex. We then compared 89 preterm infants scanned at term-equivalent age with these normative charts, relating individual deviations from typical volumetric development to perinatal risk factors and later neurocognitive scores. To test generalizability, we used a second independent dataset comprising of 253 preterm infants scanned using different acquisition parameters and scanner. We describe rapid, nonuniform brain growth during the neonatal period. In both preterm cohorts, cerebral atypicalities were widespread, often multiple, and varied highly between individuals. Deviations from normative development were associated with respiratory support, nutrition, birth weight, and later neurocognition, demonstrating their clinical relevance. Group-level understanding of the preterm brain disguises a large degree of individual differences. We provide a method and normative dataset that offer a more precise characterization of the cerebral consequences of preterm birth by profiling the individual neonatal brain.

Modelling brain development to detect white matter injury in term and preterm born neonates.

Premature birth occurs during a period of rapid brain growth. In this context, interpreting clinical neuroimaging can be complicated by the typical changes in brain contrast, size and gyrification occurring in the background to any pathology. To model and describe this evolving background in brain shape and contrast, we used a Bayesian regression technique, Gaussian process regression, adapted to multiple correlated outputs. Using MRI, we simultaneously estimated brain tissue intensity on T1- and T2-weighted scans as well as local tissue shape in a large cohort of 408 neonates scanned cross-sectionally across the perinatal period. The resulting model provided a continuous estimate of brain shape and intensity, appropriate to age at scan, degree of prematurity and sex. Next, we investigated the clinical utility of this model to detect focal white matter injury. In individual neonates, we calculated deviations of a neonate's observed MRI from that predicted by the model to detect punctate white matter lesions with very good accuracy (area under the curve > 0.95). To investigate longitudinal consistency of the model, we calculated model deviations in 46 neonates who were scanned on a second occasion. These infants' voxelwise deviations from the model could be used to identify them from the other 408 images in 83% (T2-weighted) and 76% (T1-weighted) of cases, indicating an anatomical fingerprint. Our approach provides accurate estimates of non-linear changes in brain tissue intensity and shape with clear potential for radiological use.

Steady-state imaging with inhomogeneous magnetization transfer contrast using multiband radiofrequency pulses.

PURPOSE: Inhomogeneous magnetization transfer (ihMT) is an emerging form of MRI contrast that may offer high specificity for myelinated tissue. Existing ihMT and pulsed MT sequences often use separate radiofrequency pulses for saturation and signal excitation. This study investigates the use of nonselective multiband radiofrequency pulses for simultaneous off-resonance saturation and on-resonance excitation specifically for generation of ihMT contrast within rapid steady-state pulse sequences. THEORY AND METHODS: A matrix-based signal modeling approach was developed and applied for both balanced steady state free precession and spoiled gradient echo sequences, accounting specifically for multiband pulses. Phantom experiments were performed using a combination of balanced steady state free precession and spoiled gradient echo sequences, and compared with model fits. A human brain imaging exam was performed using balanced steady state free precession sequences to demonstrate the achieved contrast. RESULTS: A simple signal model derived assuming instantaneous radiofrequency pulses was shown to agree well with full integration of the governing equations and provided fits to phantom data for materials with strong ihMT contrast (PL161 root mean square error = 0.9%, and hair conditioner root mean square error = 2.4%). In vivo ihMT ratio images showed the expected white matter contrast that has been seen by other ihMT investigations, and the observed ihMT ratios corresponded well with predictions. CONCLUSIONS: ihMT contrast can be generated by integrating multiband radiofrequency pulses directly into both spoiled gradient echo and balanced steady state free precession sequences, and the presented signal modeling approach can be used to understand the acquired signals.

Magnetization transfer and frequency distribution effects in the SSFP ellipse.

PURPOSE: To demonstrate that quantitative magnetization transfer (qMT) parameters can be extracted from steady-state free-precession (SSFP) data with no external T1 map or banding artifacts. METHODS: SSFP images with multiple MT weightings were acquired and qMT parameters fitted with a two-stage elliptical signal model. RESULTS: Monte Carlo simulations and data from a 3T scanner indicated that most qMT parameters could be recovered with reasonable accuracy. Systematic deviations from theory were observed in white matter, consistent with previous literature on frequency distribution effects. CONCLUSIONS: qMT parameters can be extracted from SSFP data alone, in a manner robust to banding artifacts, despite several confounds.

Inherent and unpredictable bias in multi-component DESPOT myelin water fraction estimation.

Multicomponent driven equilibrium steady-state observation of T1 and T2 (mcDESPOT) aims to quantify the Myelin Water Fraction (MWF) using a two-pool microstructural model. The MWF has been used to track neurodevelopment and neurodegeneration and has been histologically correlated to myelin content. mcDESPOT has a clinically feasible acquisition time and high signal-to-noise ratio (SNR) relative to other MWF techniques. However, disagreement exists in the literature between experimental studies that show MWF maps with plausible grey matter-white matter (GM-WM) contrast and theoretical work that questions the accuracy and precision of mcDESPOT. We demonstrate that mcDESPOT parameter estimation is inaccurate and imprecise if intercompartmental exchange is included in the microstructural model, but that significant bias results if exchange is neglected. The source of apparent MWF contrast is likely due to the complex convergence behaviour of the Stochastic Region Contraction (SRC) method commonly used to fit the mcDESPOT model. mcDESPOT-derived parameter estimates are hence not directly relatable to the underlying microstructural model and are only comparable to others using similar acquisition schemes and fitting constraints.

Multi-modal functional MRI to explore placental function over gestation.

PURPOSE: To investigate, visualize and quantify the physiology of the human placenta in several dimensions - functional, temporal over gestation, and spatial over the whole organ. METHODS: Bespoke MRI techniques, combining a rich diffusion protocol, anatomical data and T2* mapping together with a multi-modal pipeline including motion correction and extracted quantitative features were developed and employed on pregnant women between 22 and 38 weeks gestational age including two pregnancies diagnosed with pre-eclampsia. RESULTS: A multi-faceted assessment was demonstrated showing trends of increasing lacunarity, and decreasing T2* and diffusivity over gestation. CONCLUSIONS: The obtained multi-modal acquisition and quantification shows promising opportunities for studying evolution, adaptation and compensation processes.