An in vivo study of the orientation‐dependent and independent components of transverse relaxation rates in white matter

Gil, Rita; Khabipova, Diana; Zwiers, Marcel P.; Hilbert, Tom; Kober, Tobias; Marques, José P.

doi:10.1002/nbm.3616

Cited by 38 publications

(58 citation statements)

References 44 publications

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“…The results are displayed in Figure 6, where no clear relationship between Ê[X] and peak orientation was observed for any of the extracted metrics. This observation is in contrast with previous in vivo brain MRI studies where a relationship between the R 2 rates of myelinated fibres and their orientation relative to B 0 (Gil et al, 2016;Knight et al, 2015;McKinnon & Jensen, 2019) has been reported. In particular, Gil and co-workers (Gil et al, 2016) have estimated an angular variation of DR 2 ~ 1.5 s -1 for healthy WM tissue.…”

Section: In Vivo Orientation-resolved R 2 -D Metricscontrasting

confidence: 99%

“…It should furthermore be noted that transverse relaxation time T2 differences between distinct tissue types are often ignored, which can further bias the quantification of tissue fractions with a single fibre response kernel. The possible existence of a variation of T 2 in anisotropic structures with respect to the orientation of the main magnetic field B 0 (Lindblom, Wennerström, & Arvidson, 1977), well known in studies of cartilage structure (Henkelman, Stanisz, Kim, & Bronskill, 1994) and more recently reported in in vivo human WM studies (Gil et al, 2016;Knight, Wood, Couthard, & Kauppinen, 2015;McKinnon & Jensen, 2019), would introduce an additional T 2 dispersion and further complicate the quantification of sub-voxel signal fractions. The possible existence of T 2 differences between distinct fibre bundles has motivated the recent development of methods allowing for the measurement of fibre-specific estimates of the transverse relaxation time (de Almeida Martins & Topgaard, 2018;Ning, Gagoski, Szczepankiewicz, Westin, & Rathi, 2020;Schiavi et al, 2019).…”

Section: Main Text Introductionmentioning

confidence: 99%

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Visualizing orientation-specific relaxation-diffusion features mapped onto orientation distribution functions estimated via nonparametric Monte Carlo MRI signal inversion

Martins

Tax

Reymbaut

et al. 2020

Preprint

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Diffusion MRI techniques are widely used to study in vivo changes in the human brain connectome. However, to resolve and characterise white matter fibres in heterogeneous diffusion MRI voxels remains a challenging problem typically approached with signal models that rely on prior information and restrictive constraints. We have recently introduced a 5D relaxation-diffusion correlation framework wherein multidimensional diffusion encoding strategies are used to acquire data at multiple echo-times in order to increase the amount of information encoded into the signal and ease the constraints needed for signal inversion. Nonparametric Monte Carlo inversion of the resulting datasets yields 5D relaxation-diffusion distributions where contributions from different sub-voxel tissue environments are separated with minimal assumptions on their microscopic properties. Here, we build on the 5D correlation approach to derive fibre-specific metrics that can be mapped throughout the imaged brain volume. Distribution components ascribed to fibrous tissues are resolved, and subsequently mapped to a dense mesh of overlapping orientation bins in order to define a smooth orientation distribution function (ODF). Moreover, relaxation and diffusion measures are correlated to each independent ODF coordinate, thereby allowing the estimation of orientation-specific relaxation rates and diffusivities. The proposed method is tested on a healthy volunteer, where the estimated ODFs were observed to capture major WM tracts, resolve fibre crossings, and, more importantly, inform on the relaxation and diffusion features along distinct fibre bundles. If combined with fibre-tracking algorithms, the methodology presented in this work may be useful for investigating the microstructural properties along individual white matter pathways.

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Section: In Vivo Orientation-resolved R 2 -D Metricscontrasting

confidence: 99%

Section: Main Text Introductionmentioning

confidence: 99%

Visualizing orientation-specific relaxation-diffusion features mapped onto orientation distribution functions estimated via nonparametric Monte Carlo MRI signal inversion

Martins

Tax

Reymbaut

et al. 2020

Preprint

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“…It has been shown that these hyperintensities depend on the angle between the axon’s main direction and the main magnetic field B 0. These effects affect both CPMG‐based and fingerprinting‐based approaches, but potentially to different degrees and in different direction (over‐ vs. under‐estimation). For T 1 values, the single‐pool model agreed better with the reference method (MP2RAGE) than the two‐pool model.…”

Section: Discussionmentioning

confidence: 99%

Magnetization transfer in magnetic resonance fingerprinting

Hilbert

Xia

Block

et al. 2019

Magnetic Resonance in Med

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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 B1+, 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.

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“…To compare the reproducibility of T 2 values in vivo across different degrees of acceleration and different subjects, ROIs were studied. To ensure reproducibility over the whole range of T 2 values found in the brain, the globus pallidus (GPA, exhibiting short T 2 values as a result of its high iron concentration) and the cortical spinal tracts (exhibiting long T 2 values as a result of the large‐sized axons that tend to run parallel to the main magnetic field in the normal supine position) were studied. Additional ROIs were placed in the frontal lobe white matter (FWM), the thalamus, and splenium.…”

Section: Methodsmentioning

confidence: 99%

Fast model‐based T₂ mapping using SAR‐reduced simultaneous multislice excitation

Hilbert

Schulz

Marques

et al. 2019

Magnetic Resonance in Med

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Purpose To obtain whole‐brain high‐resolution T2 maps in 2 minutes by combining simultaneous multislice excitation and low‐power PINS (power independent of number of slices) refocusing pulses with undersampling and a model‐based reconstruction. Methods A multi‐echo spin‐echo sequence was modified to acquire multiple slices simultaneously, ensuring low specific absorption rate requirements. In addition, the acquisition was undersampled to achieve further acceleration. Data were reconstructed by subsequently applying parallel imaging to separate signals from different slices, and a model‐based reconstruction to estimate quantitative T2 from the undersampled data. The signal model used is based on extended phase graph simulations that also account for nonideal slice profiles and B1 inhomogeneity. In vivo experiments with 3 healthy subjects were performed to compare accelerated T2 maps to fully sampled single‐slice acquisitions. The accuracy of the T2 values was assessed with phantom experiments by comparing the T2 values to single‐echo spin‐echo measurements. Results In vivo results showed that conventional multi‐echo spin‐echo, simultaneous multislice, and undersampling result in similar mean T2 values within regions of interest. However, combining simultaneous multislice and undersampling results in higher SDs (about 7 ms) in comparison to a conventional sequence (about 3 ms). The T2 values were reproducible between scan and rescan (SD < 1.2 ms) within subjects and were in similar ranges across subjects (SD < 4.5 ms). Conclusion The proposed method is a fast T2 mapping technique that enables whole‐brain acquisitions at 0.7‐mm in‐plane resolution, 3‐mm slice thickness, and low specific absorption rate in 2 minutes.

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An in vivo study of the orientation‐dependent and independent components of transverse relaxation rates in white matter

Cited by 38 publications

References 44 publications

Visualizing orientation-specific relaxation-diffusion features mapped onto orientation distribution functions estimated via nonparametric Monte Carlo MRI signal inversion

Visualizing orientation-specific relaxation-diffusion features mapped onto orientation distribution functions estimated via nonparametric Monte Carlo MRI signal inversion

Magnetization transfer in magnetic resonance fingerprinting

Fast model‐based T₂ mapping using SAR‐reduced simultaneous multislice excitation

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An in vivo study of the orientation‐dependent and independent components of transverse relaxation rates in white matter

Cited by 38 publications

References 44 publications

Visualizing orientation-specific relaxation-diffusion features mapped onto orientation distribution functions estimated via nonparametric Monte Carlo MRI signal inversion

Visualizing orientation-specific relaxation-diffusion features mapped onto orientation distribution functions estimated via nonparametric Monte Carlo MRI signal inversion

Magnetization transfer in magnetic resonance fingerprinting

Fast model‐based T2 mapping using SAR‐reduced simultaneous multislice excitation

Contact Info

Product

Resources

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Fast model‐based T₂ mapping using SAR‐reduced simultaneous multislice excitation