Investigating Brain Tissue Microstructure using Quantitative Magnetic Resonance Imaging

In recent years there has been a considerable research effort in improving the specificity of magnetic resonance imaging (MRI) techniques by employing quantitative methods. These methods offer greater reproducibility over traditional acquisitions, and hold the potential for obtaining improved information at the microstructural level. However, they typically require a longer duration for the experiments as the quantitative information is often obtained from multiple acquisitions. Here, a multi-echo extension of the MP2RAGE pulse sequence for the simultaneous mapping of T1, T2* (and magnetic susceptibility) is introduced, optimized and validated. This acquisition technique can be faster than the separate acquisition of T1 and T2*, and has the advantage of producing intrinsically co-localized maps. This is helpful in reducing the preprocessing complexity, but most importantly it removes the need for image alignment (registration) which is shown to introduce significant bias in quantitative MRI maps. One of the reasons why the knowledge of T1 and T2* is of relevance in neuroscience is because their reciprocal, R1 and R2*, have been shown to predict quantitatively myelin and iron content in ex vivo experiments using a linear model of relaxation. However, the post-mortem results cannot be applied directly to the in vivo case. Therefore, an adaptation of the linear relaxation model to the in vivo case is proposed. This is capable of predicting (with some limitations) the myelin and iron contents of the brain under in vivo conditions, by using prior knowledge from the literature to calibrate the linear coefficients. The dependence of the relaxation parameters from the biochemical composition in brain tissues is further explored with ex vivo experiments. In particular, the hyaluronan component of the extracellular matrix is investigated. The contribution to T1 and T2* is measured with a sophisticated experiments that allow for a greater control over experimental conditions compared to a typical MRI experiment. The result indicate a small but appreciable contribution of hyaluronan to the relaxation parameters. In conclusion, this work develops a method for measuring T1 and T2* maps simultaneously. These are then used to quantify myelin and iron under in vivo conditions using a linear model of relaxation. In parallel, the hyaluronan-based extracellular matrix was shown to be a marginal but measurable component in T1 and T2* relaxation maps in ex vivo experiments

Investigating Brain Tissue Microstructure using Quantitative Magnetic Resonance Imaging

In recent years there has been a considerable research effort in improving the specificity of magnetic resonance imaging (MRI) techniques by employing quantitative methods. These methods offer greater reproducibility over traditional acquisitions, and hold the potential for obtaining improved information at the microstructural level. However, they typically require a longer duration for the experiments as the quantitative information is often obtained from multiple acquisitions. Here, a multi-echo extension of the MP2RAGE pulse sequence for the simultaneous mapping of T1, T2* (and magnetic susceptibility) is introduced, optimized and validated. This acquisition technique can be faster than the separate acquisition of T1 and T2*, and has the advantage of producing intrinsically co-localized maps. This is helpful in reducing the preprocessing complexity, but most importantly it removes the need for image alignment (registration) which is shown to introduce significant bias in quantitative MRI maps. One of the reasons why the knowledge of T1 and T2* is of relevance in neuroscience is because their reciprocal, R1 and R2*, have been shown to predict quantitatively myelin and iron content in ex vivo experiments using a linear model of relaxation. However, the post-mortem results cannot be applied directly to the in vivo case. Therefore, an adaptation of the linear relaxation model to the in vivo case is proposed. This is capable of predicting (with some limitations) the myelin and iron contents of the brain under in vivo conditions, by using prior knowledge from the literature to calibrate the linear coefficients. The dependence of the relaxation parameters from the biochemical composition in brain tissues is further explored with ex vivo experiments. In particular, the hyaluronan component of the extracellular matrix is investigated. The contribution to T1 and T2* is measured with a sophisticated experiments that allow for a greater control over experimental conditions compared to a typical MRI experiment. The result indicate a small but appreciable contribution of hyaluronan to the relaxation parameters. In conclusion, this work develops a method for measuring T1 and T2* maps simultaneously. These are then used to quantify myelin and iron under in vivo conditions using a linear model of relaxation. In parallel, the hyaluronan-based extracellular matrix was shown to be a marginal but measurable component in T1 and T2* relaxation maps in ex vivo experiments

Investigating Brain Tissue Microstructure using Quantitative Magnetic Resonance Imaging

In recent years there has been a considerable research effort in improving the specificity of magnetic resonance imaging (MRI) techniques by employing quantitative methods. These methods offer greater reproducibility over traditional acquisitions, and hold the potential for obtaining improved information at the microstructural level. However, they typically require a longer duration for the experiments as the quantitative information is often obtained from multiple acquisitions. Here, a multi-echo extension of the MP2RAGE pulse sequence for the simultaneous mapping of T1, T2* (and magnetic susceptibility) is introduced, optimized and validated. This acquisition technique can be faster than the separate acquisition of T1 and T2*, and has the advantage of producing intrinsically co-localized maps. This is helpful in reducing the preprocessing complexity, but most importantly it removes the need for image alignment (registration) which is shown to introduce significant bias in quantitative MRI maps. One of the reasons why the knowledge of T1 and T2* is of relevance in neuroscience is because their reciprocal, R1 and R2*, have been shown to predict quantitatively myelin and iron content in ex vivo experiments using a linear model of relaxation. However, the post-mortem results cannot be applied directly to the in vivo case. Therefore, an adaptation of the linear relaxation model to the in vivo case is proposed. This is capable of predicting (with some limitations) the myelin and iron contents of the brain under in vivo conditions, by using prior knowledge from the literature to calibrate the linear coefficients. The dependence of the relaxation parameters from the biochemical composition in brain tissues is further explored with ex vivo experiments. In particular, the hyaluronan component of the extracellular matrix is investigated. The contribution to T1 and T2* is measured with a sophisticated experiments that allow for a greater control over experimental conditions compared to a typical MRI experiment. The result indicate a small but appreciable contribution of hyaluronan to the relaxation parameters. In conclusion, this work develops a method for measuring T1 and T2* maps simultaneously. These are then used to quantify myelin and iron under in vivo conditions using a linear model of relaxation. In parallel, the hyaluronan-based extracellular matrix was shown to be a marginal but measurable component in T1 and T2* relaxation maps in ex vivo experiments

Estimation of microstructure parameter from ex-vivo data using realistic WM models

International audienc

Estimation of microstructure parameter from ex-vivo data using realistic WM models

International audienc

inhomogeneity displayed as histograms of the flip-angle accuracy factor inside the brain of six healthy human volunteers.

<p>Voxels outside the head or not containing brain tissue were masked out. The dashed lines indicate the mean (thick line) plus/minus the standard deviations (thin lines) of <i>η</i>_<i>α</i> across subjects.</p

2D correlation histograms showing the effects of registration.

<p>Columns refer to <i>T</i>₁ (a, c), (b, d) and <i>χ</i> (e, f) maps, while rows show either mis-registration (a, b, c) or self-registration (d, e, f) effects, respectively. The mis-registration and the self-registration effects are here illustrated by comparing each map with itself: after the application of a small transformation without registration (mis-registration) or after the application of a large transformation followed by a registration step (self-registration). The <i>x</i>-axis indicate the unmodified map, while the <i>y</i>-axis indicate the transformed or self-registered map. The small tranformation considered for the misregitration is a 0.5px translation followed by a 0.5° rotation. The large transformation considered for the self-registration is a 10° rotation.</p

Group averages, <i>μ</i>_<i>g</i>, and SDs, <i>σ</i>_<i>g</i>, for the ROI-based analysis of ME-MP2RAGE acquisitions.

<p>Abbreviations: WM = White Matter; Fro. = Frontal Lobe; Tem. = Temporal Lobe; Par. = Parietal Lobe; Occ. = Occipital Lobe; Ins. = Insula; Put. = Putamen; Caud. = Caudate; Tha. = Thalamus; Cereb. = Cerebellum. Susceptibility is indicated here by Δ<i>χ</i> as a reminder of the values being referenced to an arbitrary offset, implying that the group average and SD values are expected to be biased by that and, possibly, by the pole artifacts of the phase images.</p

Estimated <i>T</i>₁ values as a function of (a) the ME-MP2RAGE and (b) the MP2RAGE signal intensity parameter <i>ρ</i>.

<p>The green lines correspond to the effective acquisition parameters while red/blue lighter/darker lines indicate, respectively, ±20% and ±40% offsets of . The flip angle values are adjusted for the accuracy factor <i>η</i>_<i>α</i>. Note that the estimated <i>T</i>₁ is limited to an upper value of approximately 3 s for the acquisition parameters that were used for MP2RAGE, which would result in <i>T</i>₁ values exceeding this limit (e.g., in CSF) to be underestimated.</p

Example of the images obtained from an ME-MP2RAGE acquisition.

<p>Each row represents a different echo time. The columns show in order: first inversion magnitude (1st) and phase (2nd); second inversion magnitude (3rd) and phase (4th). Magnitude images are shown in arb.units, while phase image are in radians, both using a gray scale. Note that: <i>(i)</i> the phase images for the first inversion point show an abrupt change in their value corresponding to the zero crossing of the signal in the <i>T</i>₁ recovery curve; <i>(ii)</i> the phase images for the second inversion point present some coil combination pole artifacts resulting in a corresponding degradation of the QSM maps at these locations.</p