Fourier series windows on and off resonance using multiple coils and longitudinal modulation and longitudinal modulation

Spatial localization in nuclear magnetic resonance spectroscopy

The ability to select a discrete region within the body for signal acquisition is a fundamental requirement of in vivo NMR spectroscopy. Ideally, it should be possible to tailor the selected volume to coincide exactly with the lesion or tissue of interest, without loss of signal from within this volume or contamination with extraneous signals. Many techniques have been developed over the past 25 years employing a combination of RF coil properties, static magnetic field gradients and pulse sequence design in an attempt to meet these goals. This review presents a comprehensive survey of these techniques, their various advantages and disadvantages, and implications for clinical applications. Particular emphasis is placed on the reliability of the techniques in terms of signal loss, contamination and the effect of nuclear relaxation and J-coupling. The survey includes techniques based on RF coil and pulse design alone, those using static magnetic field gradients, and magnetic resonance spectroscopic imaging. Although there is an emphasis on techniques currently in widespread use (PRESS, STEAM, ISIS and MRSI), the review also includes earlier techniques, in order to provide historical context, and techniques that are promising for future use in clinical and biomedical applications.

In vivo 17O NMR approaches for brain study at high field

17O is the only stable oxygen isotope that can be detected by NMR. The quadrupolar moment of 17O spin (I = 5/2) can interact with local electric field gradients, resulting in extremely short T1 and T2 relaxation times which are in the range of several milliseconds. One unique NMR property of 17O spin is the independence of 17O relaxation times on the magnetic field strength, and this makes it possible to achieve a large sensitivity gain for in vivo 17O NMR applications at high fields. In vivo 17O NMR has two major applications for studying brain function and cerebral bioenergetics. The first application is to measure the cerebral blood flow (CBF) through monitoring the washout of inert H2 17O tracer in the brain tissue following an intravascular bolus injection of the 17O-labeled water. The second application, perhaps the most important one, is to determine the cerebral metabolic rate of oxygen utilization (CMRO2) through monitoring the dynamic changes of metabolically generated H2 17O from inhaled 17O-labeled oxygen gas in the brain tissue. One great merit of in vivo 17O NMR for the determination of CMRO2 is that only the metabolic H2 17O is detectable. This merit dramatically simplifies both CMRO2 measurement and quantification compared to other established methods. There are two major NMR approaches for monitoring H2 17O in vivo, namely direct approach by using 17O NMR detection (referred as direct in vivo 17O NMR approach) and indirect approach by using 1H NMR detection for measuring the changes in T2- or T1rho-weighted proton NMR signals caused by the 17O-1H scalar coupling and proton chemical exchange (referred as indirect in vivo 17O NMR approach). Both approaches are suitable for CBF measurements. However, recent studies indicated that the direct in vivo 17O NMR approach at high/ultrahigh fields appears to offer significant advantages for quantifying and imaging CMRO2. New developments have further demonstrated the feasibility for establishing a completely noninvasive in vivo 17O NMR approach for imaging CMRO2 in a rat brain during a brief 17O2 inhalation. This approach should be promising for studying the central role of oxidative metabolism in brain function and neurological diseases. Finally, the similar approach could potentially be applied to image CMRO2 noninvasively in human brain.

A robust algorithm for reduction of truncation artifact in chemical shift images

A new iterative technique to reduce the ringing artifacts in chemical shift images due to the truncation of the high spatial frequency is presented. In this approach the authors extrapolate the high spatial frequency data guided by the edge information obtained from a high resolution anatomic image of the region of interest. The fact that the edge information obtained from the anatomic image can be off by a few pixels (due to factors such as chemical shift artifact, error in edge detection or misregistration) is taken into account by assuming a confidence interval of several pixels around the anatomic edges. The algorithm is validated on simulated and in vivo data, and excellent results were obtained.

SLIM revisited

SLIM (spectroscopic localization by imaging), a tool for in vivo magnetic resonance spectroscopy that provides compartmental spectra from relatively few phase-encoded data, is limited by the inhomogeneities within each compartment. It is shown that the SLIM-derived spectra approach the average compartmental spectra as the number of phase encoded data approaches infinity, and the convergent rate of the error for each compartment is proportional to the size of the compartment. Numerical simulation studies are conducted to confirm the convergence property. A detailed discussion of the result is provided.

Technique for reduction of truncation artifact in chemical shift images

The authors describe a technique to reduce truncation artifacts in chemical shift images taken for in vivo magnetic resonance spectroscopy by using boundary information available from anatomic images. In this approach, high spatial frequency components are extrapolated from the observed data by making use of the boundary information. This technique has been tested with simulations and phantom experiments. Results obtained show that the technique works very well. The authors present technical details and results of computer simulations and phantom studies.