The interaction between water protons and suitable quadrupolar nuclei (QN) can lead to quadrupole relaxation enhancement (QRE) of proton spins, provided the resonance condition between both spin transitions is fulfilled. This effect could be utilized as a frequency selective mechanism in novel, responsive T 1 shortening contrast agents (CAs) for magnetic resonance imaging (MRI). In particular, the proposed contrast mechanism depends on the applied external flux density-a property that can be exploited by special field-cycling MRI scanners. For the design of efficient CA molecules, exhibiting narrow and pronounced peaks in the proton T 1 relaxation dispersion, the nuclear quadrupole resonance (NQR) properties, as well as the spin dynamics of the system QN-1 H, have to be well understood and characterized for the compounds in question. In particular, the energy-level structure of the QN is a central determinant for the static flux densities at which the contrast enhancement appears. The energy levels depend both on the QN and the electronic environment, i.e., the chemical bonding structure in the CA molecule. In this work, the NQR properties of a family of promising organometallic compounds containing 209 Bi as QN have been characterized. Important factors like temperature, chemical structure, and chemical environment have been considered by NQR spectroscopy and ab initio quantum chemistry calculations. The investigated Bi-aryl compounds turned out to fulfill several crucial requirements: NQR transition frequency range applicable to clinical 1.5-and 3 T MRI systems, low temperature dependency, low toxicity, and tunability in frequency by chemical modification.
Contrast agents with a strong R dispersion have been shown to be effective in generating target-specific contrast in MRI. The utilization of this R field dependence requires the adaptation of an MRI scanner for fast field-cycling (FFC). Here, we present the first implementation and validation of FFC-MRI at a clinical field strength of 3 T. A field-cycling range of ±100 mT around the nominal B field was realized by inserting an additional insert coil into an otherwise conventional MRI system. System validation was successfully performed with selected iron oxide magnetic nanoparticles and comparison to FFC-NMR relaxometry measurements. Furthermore, we show proof-of-principle R dispersion imaging and demonstrate the capability of generating R dispersion contrast at high field with suppressed background signal. With the presented ready-to-use hardware setup it is possible to investigate MRI contrast agents with a strong R dispersion at a field strength of 3 T.
Fast field-cycling (FFC) nuclear magnetic resonance relaxometry is a well-established method to determine the relaxation rates as a function of magnetic field strength. This so-called nuclear magnetic relaxation dispersion gives insight into the underlying molecular dynamics of a wide range of complex systems and has gained interest especially in the characterisation of biological tissues and diseases. The combination of FFC techniques with magnetic resonance imaging (MRI) offers a high potential for new types of image contrast more specific to pathological molecular dynamics. This article reviews the progress in FFC-MRI over the last decade and gives an overview of the hardware systems currently in operation. We discuss limitations and error correction strategies specific to FFC-MRI such as field stability and homogeneity, signal-to-noise ratio, eddy currents and acquisition time. We also report potential applications with impact in biology and medicine. Finally, we discuss the challenges and future applications in transferring the underlying molecular dynamics into novel types of image contrast by exploiting the dispersive properties of biological tissue or MRI contrast agents. ARTICLE HISTORY KEYWORDS Field-cycling; FFC-MRI; delta relaxation enhanced MR; dispersion; NMRDCONTACT Markus Bödenler m.boedenler@tugraz.at * These authors have equally contributed to this work. of the scanner. Differences in the underlying relaxation behaviour at B 0 , and therefore changes in image contrast, can be used to distinguish between healthy and pathological tissues for many diseases [1]. However, contrast mechanisms may change dramatically with the applied magnetic field strength, and these changes can be exploited to obtain new information for medical diagnosis. One way to access field-dependant information is by using Fast Field-Cycling (FFC) methods.FFC Nuclear Magnetic Resonance (NMR) relaxometry is an established method to measure the changes
Many smart magnetic resonance imaging (MRI) probes provide response to a biomarker based on modulation of their rotational correlation time. The magnitude of such MRI signal changes is highly dependent on the magnetic field and the response decreases dramatically at high fields (>2 T). To overcome the loss of efficiency of responsive probes at high field, with fast‐field cycling magnetic resonance imaging (FFC‐MRI) we exploit field‐dependent information rather than the absolute difference in the relaxation rate measured in the absence and in the presence of the biomarker at a given imaging field. We report here the application of fast field‐cycling techniques combined with the use of a molecular probe for the detection of Zn 2+ to achieve 166 % MRI signal enhancement at 3 T, whereas the same agent provides no detectable response using conventional MRI. This approach can be generalized to any biomarker provided the detection is based on variation of the rotational motion of the probe.
Various medical examinations are seeing a shift to a more patient centric and personalized view, based on quantitative instead of qualitative observations and comparisons. This trend has also affected medical imaging, and particularly quantitative MRI (qMRI) gained importance in recent years. qMRI aims to identify the underlying biophysical and tissue parameters that determine contrast in an MR imaging experiment. In addition to contrast information, qMRI permits insights into diseases by providing biophysical, microstructural, and functional information in absolute quantitative values. For quantification, biophysical models are used, which describe the relationship between image intensity and physical properties of the tissue for certain scanning sequences and sequence parameters. By performing several measurements with different sequence parameters (e.g. flip angle, repetition time, echo time) the related inverse problem of identifying the tissue parameters sought can be solved.Quantitative MR typically suffers from increased measurement time due to repeated imaging experiments. Therefore, methods to reduce scanning time by means of optimal scanning protocols and subsampled data acquisition have been extensively studied. However, these approaches are typically associated with a reduced SNR, and can suffer from subsampling artifacts. To address both aspects, it has been shown that the inclusion of a biophysical model in the reconstruction process leads to much faster data acquisition, while simultaneously improving image quality. The inverse problem associated with this special reconstruction approach requires dedicated numerical solution strategies (
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