Pulsed Z‐spectroscopic imaging of cross‐relaxation parameters in tissues for human MRI: Theory and clinical applications

Pulsed magnetization transfer (MT) imaging has been applied to quantitatively assess brain pathology in several diseases, especially multiple sclerosis (MS). To date, however, because of the high power deposition associated with the use of short, rapidly repeating MT prepulses, clinical application has been limited to lower field strengths. The contrast-to-noise ratio (CNR) of MT is limited, and this method would greatly benefit from the use of higher magnetic fields and phased-array coil reception. However, power deposition is proportional to the square of the magnetic field and scales with coil size, and MT experiments are already close to the SAR limit at 1.5T even when smaller transmit coils are used instead of the body coil. Here we show that these seemingly great obstacles can be ameliorated by the increased T 1 of tissue water at higher field, which allows for longer maintenance of sufficiently high saturation levels while using a reduced duty cycle. This enables a fast (5-6 min) high-resolution (1.5 mm isotropic) whole-brain Magnetization transfer ratio (MTR) imaging (1-5) has been used as a noninvasive method to quantitatively assay white matter (WM) degeneration in multiple sclerosis (MS) (4,6 -14) and more recently in neuropsychiatric diseases such as Alzheimer's disease and bipolar disorder (15)(16)(17). Since MT imaging is exquisitely sensitive to the solid-like macromolecular content of central nervous system (CNS) tissue, it can detect subtle pathological changes and sometimes even conventionally unobserved pathology (18,19). Pulsed MT imaging (1,20) employs a series of short (ϳ10 -30 ms), high-amplitude pulses, and relies on the build-up of a saturation steady state over multiple TR periods (1) as opposed to the large saturation induced by continuous wave (CW) experiments within a single TR. The increased speed provided by pulsed MT has allowed investigators to survey the frequency dependence of the MT effect and to determine MT-based parameters, such as fractional pool sizes and exchange rates, within a reasonable clinical scan time (4,10 -12,21-23). However, this comes at the price of a reduced contrast-to-noise ratio (CNR) and increased power deposition, which comes close to maximum specific absorption rate (SAR) levels, even when the transmit/receive head coil is used at a field strength of 1.5T. To harness the power of parallel imaging (24) and further reduce the scan time, it is necessary to use a larger coil (i.e., a body coil in standard sensitivity encoding (SENSE) imaging) for transmission, which unfortunately exacerbates the power-deposition problem. This SAR restriction also appears to be a prohibitive barrier for translating pulsed MT to higher field strengths (e.g., 3T), where a higher signal-to-noise ratio (SNR) would allow faster scan times or an improved contrast-to-noise ratio. MT acquisition with excellent anatomical visualization of gray matter (GM) and white matter (WM) structures, and even substructures. The method is demonstrated in nine normal volunteers and five patients...

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confidence: 86%

Pulsed magnetization transfer imaging with body coil transmission at 3 Tesla: Feasibility and application

Smith

Farrell

Jones

et al. 2006

“…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).…”

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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...

“…24 into Eq. 12, we obtain: [25] where g͑ d Ϫ ,T 2d ͒ represents the line-shape function (Lorentzian) and is commonly replaced with a gaussian or super-Lorentzian line-shape function to model the MT effect of macromolecule-bound water (30,31). In the current work, Eq.…”

Section: Appendixmentioning

confidence: 99%

“…The underlying mechanism of MT has been described successfully using a two-pool or three-pool model, including a pool of free protons and one or more pools of bound protons (27)(28)(29)(30)(31). To describe the MT effect in tissue, the line shape of the macromolecular component is best described using a super-Lorentzian or gaussian line shape in the Bloch equations rather than a Lorentzian line shape (29)(30)(31).…”

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confidence: 99%

“…To describe the MT effect in tissue, the line shape of the macromolecular component is best described using a super-Lorentzian or gaussian line shape in the Bloch equations rather than a Lorentzian line shape (29)(30)(31). We have previously presented a four-pool model to describe how the inherent MT effect can affect the in vivo off-resonance detection sensitivity of PARACEST agents (23,32).…”

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confidence: 99%

See 1 more Smart Citation

Optimized MRI contrast for on‐resonance proton exchange processes of PARACEST agents in biological systems

Suchý

Jones

et al. 2009

Image contrast associated with paramagnetic chemical exchange saturation transfer agents can be generated by off-resonance irradiation of agent-bound water or amide protons or on-resonance irradiation of bulk water. Previously, a four-pool model was developed to describe an in vivo system. The model incorporated the magnetization transfer effect from macromolecules when using off-resonance irradiation. In the current study, this four-pool model is modified to describe the in vivo system when using on-resonance irradiation. The influences of pulse power, pulse duration, the chemical shift of bound water, the proton exchange rate between bulk water and bound water, and agent concentration on the on-resonance paramagnetic agent chemical exchange effects were simulated using a WALTZ-16 pulse train in the absence and presence of the macromolecule pool. The results demonstrated that while contrast increases with pulse duration in aqueous solution, there is an optimal pulse duration that maximizes on-resonance paramagnetic agent chemical exchange effects contrast in vivo. Diamagnetic and paramagnetic chemical exchange saturation transfer (PARACEST) (1-12) agents have many possible medical and biologic applications, including the measurement of tissue pH based on the pH dependence of the exchange rate of amide protons with bulk water protons (13-15), the measurement of tissue temperature using the linear dependence of the bound water chemical shift on temperature (16,17), enzymatic activity (18), and metabolite levels (19-21). The CEST detection sensitivity (or CEST effect) is defined as the change in the bulk water signal intensity of the agent solution following irradiation of the exchangeable protons. The PARACEST effect and the chemical shift of bound protons can be modified using different metals in the lanthanide series or ligands (22). Currently, the most efficient PARACEST agents are europium (Eu 3ϩ ) based, with a bound water chemical shift around 45 parts per million (ppm) and visible CEST contrast from millimolar concentrations.Despite the large chemical shift of the bound water and amide protons associated with PARACEST agents, the relatively high saturation power needed for in vivo PARAC-EST imaging results in the simultaneous observation of inherent magnetization transfer (MT) from macromolecule-bound protons (17,23). Though dysprosium-, thulium (Tm 3ϩ )-, and ytterbium-based PARACEST agents have bound water chemical shifts beyond the MT effect range, the fast proton exchange between the bound water of these compounds and the bulk water results in an undetectable CEST signal within specific absorption rate power limits. However, the irradiation of bulk water (on-resonance) in solutions with fast proton exchange between bound water and bulk water may also produce contrast due to chemical exchange (24).The detected effect of a PARACEST agent based on the radiofrequency (RF) excitation of bulk water was previously described as the on-resonance paramagnetic agent chemical exchange effect (OPARACHEE) to differe...