Precise estimate of fundamental in-vivo MT parameters in human brain in clinically feasible times

146

Purpose: To accelerate the quantitative ultrashort echo time imaging using a time-efficient 3D multispoke Cones sequence with magnetization transfer (3D UTE-Cones-MT) and signal modeling. Theory and Methods: A 3D UTE-Cones-MT acquisition scheme with multispoke per MT preparation and a modified rectangular pulse (RP) approximation was developed for twopool MT modeling of macromolecular and water components including their relative fractions, relaxation times and exchange rates. Numerical simulation and cadaveric specimens, including human Achilles tendon and bovine cortical bone, were investigated using a clinical 3T scanner. Results: Numerical simulation showed that the modified RP model provided accurate estimation of MT parameters when multispokes were acquired per MT preparation. For the experiment with the Achilles tendon and cortical bone samples, the macromolecular fractions were 20.4 6 2.0% and 59.4 6 5.3%, respectively. Conclusion: The 3D multispoke UTE-Cones-MT sequence can be used for fast volumetric assessment of macromolecular and water components in short T 2 tissues.

Section: Two-pool Mt Modelingmentioning

confidence: 99%

Quantitative magnetization transfer ultrashort echo time imaging using a time‐efficient 3D multispoke Cones sequence

Chang

Carl³

et al. 2017

146

“…binary spin-bath model) as described in detail elsewhere (9)(10)(11)(12). In contrast to common MT prepared SPGR methods, the RF pulse train used for imaging is responsible for the MT effect with bSSFP.…”

Section: Two-pool Bloch Simulationmentioning

confidence: 99%

Finite RF pulse correction on DESPOT2

Crooijmans

Scheffler

Bieri

2010

Magnetization transfer and finite radiofrequency (RF) pulses affect the steady state of balanced steady state free precession. As quantification of transverse relaxation (T 2 ) with driven equilibrium single pulse observation of T 2 is based on two balanced steady state free precession acquisitions, both effects can influence the outcome of this method: a short RF pulse per repetition time (T RF /TR ( 1) leads to considerable magnetization transfer effects, whereas prolonged RF pulses (T RF /TR > 0.2) minimize magnetization transfer effects, but lead to increased finite pulse effects. A correction for finite pulse effects is thus implemented in the driven equilibrium single pulse observation of T 2 theory to compensate for reduced transverse relaxation effects during excitation. It is shown that the correction successfully removes the driven equilibrium single pulse observation of T 2 dependency on the RF pulse duration. A reduction of the variation in obtained T 2 from over 50% to less than 10% is achieved. We hereby provide a means of acquiring magnetization transfer-free balanced steady state free precession images to yield accurate T 2 values using elongated RF pulses. Magn Reson Med 65:858-862,

“…The MT ratio is a semiquantitative index that presents a limited view of the MT effect. More detailed analysis of pulsed, off-resonance MT data using the two-pool model of tissue (6,7) has been extended to in vivo imaging, in particular in human WM (8)(9)(10). The resulting method, termed quantitative MT imaging (QMTI), allows mapping of the parameters of the two-pool (liquid and semisolid) model of tissue: the ratio of semisolid to liquid protons F, the first-order forward and reverse exchange rate constants k f and k r (where k r ϭ k f /F), the spin-lattice relaxation rate R 1f of the free pool (R 1f ϭ 1/T 1f ), the spin-spin relaxation time constant of the free pool T 2f , and the "T 2 " of the restricted pool, T 2r (inversely related to the width of the restricted pool resonance).…”

mentioning

confidence: 99%

Characterizing healthy and diseased white matter using quantitative magnetization transfer and multicomponent T₂ relaxometry: A unified view via a four‐pool model

Levesque

Pike

2009

Nuclear magnetic resonance relaxation and magnetization transfer in cerebral white matter can be described using a four-pool model: two for water protons (in separate myelin and intra/extracellular compartments) and two for protons associated with the lipids and proteins of biologic membranes (of myelin and nonmyelin semisolids). This model was used to gain insight into the observations from multicomponent quantitative T 2 relaxometry and quantitative magnetization transfer imaging, both based on simplified white matter models and experimentally feasible in vivo. The sensitivity of MRI to white matter (WM) damage in diseases such as multiple sclerosis (MS) has made it indispensable in diagnosis, but its lack of pathologic specificity remains problematic. In response, investigators have turned to quantitative MRI techniques to identify putative indicators of specific pathologic features, such as myelin loss. Quantitative analysis of spin-spin relaxation data using T 2 distributions (QT2), also known as myelin water imaging, can notably distinguish two major T 2 components in human WM (1,2). In particular, QT2 yields an estimate of the myelin water fraction (MWF), the fraction of water contained between the layers of myelin in WM. Magnetization transfer (MT) imaging (3,4), most often measured as the MT ratio, is a widely available technique that is sensitive to the semisolid constituents of tissue (e.g., lipids, proteins), and in WM the MT effect is believed to be dominated by myelin (5). The MT ratio is a semiquantitative index that presents a limited view of the MT effect. More detailed analysis of pulsed, off-resonance MT data using the two-pool model of tissue (6,7) has been extended to in vivo imaging, in particular in human WM (8-10). The resulting method, termed quantitative MT imaging (QMTI), allows mapping of the parameters of the two-pool (liquid and semisolid) model of tissue: the ratio of semisolid to liquid protons F, the first-order forward and reverse exchange rate constants k f and k r (where k r ϭ k f /F), the spin-lattice relaxation rate R 1f of the free pool (R 1f ϭ 1/T 1f ), the spin-spin relaxation time constant of the free pool T 2f , and the "T 2 " of the restricted pool, T 2r (inversely related to the width of the restricted pool resonance). Separating the fundamental parameters of the two-pool model requires an additional measurement of the "long" observed T 1 (T 1obs ), from which the free pool R 1f can then be computed (6). The MWF, MT ratio, and certain QMTI parameters have respectively been shown to correlate with myelin content and demyelination (11-13).QT2 and QMTI techniques each present a different limited view of WM characteristics. QT2 imaging relies on the fundamental assumptions that water exists in isolated compartments and that variations in the estimated MWF are equal to variations in myelin. On the other hand, the two-pool model for MT neglects the existence of multiple water pools. A more comprehensive model for WM that includes four communicating proton pools (myelin soli...