Recent improvements in parallel imaging have been driven by the use of greater numbers of independent surface coils placed so as to minimize aliasing along the phase encode direction(s). However, gains from increasing the number of coils diminish as coil coupling problems begin to dominate and the ratio of acceleration gain to expense for multiple receiver chains becomes prohibitive. In this work we redesign the spatial encoding strategy in order to gain efficiency, achieving a gradient encoding scheme that is complementary to the spatial encoding provided by the receiver coils. This approach leads to “O-Space” imaging, wherein the gradient shapes are tailored to an existing surface coil array, making more efficient use of the spatial information contained in the coil profiles. In its simplest form, for each acquired echo the Z2 spherical harmonic is used to project the object onto sets of concentric rings, while the X and Y-gradients are used to offset this projection within the imaging plane. The theory is presented, an algorithm is introduced for image reconstruction, and simulations reveal that O-Space encoding achieves high encoding efficiency compared to SENSE, radial projection imaging, and PatLoc imaging, suggesting that O-Space imaging holds great potential for accelerated scanning.

Conventional magnetic resonance methods that provide interior temperature profiles, which find use in clinical applications such as hyperthermic therapy, can develop inaccuracies caused by the inherently inhomogeneous magnetic field within tissues or by probe dynamics, and work poorly in important applications such as fatty tissues. We present a magnetic resonance method that is suitable for imaging temperature in a wide range of environments. It uses the inherently sharp resonances of intermolecular zero-quantum coherences, in this case flipping up a water spin while flipping down a nearby fat spin. We show that this method can rapidly and accurately assign temperatures in vivo on an absolute scale.Temperature, one of the most fundamental intrinsic quantities of matter, is very difficult to measure noninvasively beneath the surface of an object. A general method to image interior temperatures in soft matter could find a wide range of experimental applications in fields ranging from bulk catalysis and process chemistry to clinical treatment. In medicine alone, temperature distributions in the body have been linked to the critical regulation of metabolism, immune function, and longevity. (1) Hyperthermic cancer treatments and radiation therapy are used to kill cancer cells at different stages of growth (2-7), and numerous groups have developed thermally sensitive formulations (e.g., liposomes) that release drugs selectively within a heated region (8-11). In practice, however, the utility of all of this work is compromised by the difficulty of accurate temperature imaging in vivo. (12) In general, current methods break down in the very systems that are of greatest interest, those that are inhomogeneous and that change with time.Here, we present a magnetic resonance imaging approach for rapid, high-resolution in vivo temperature imaging. It involves selective detection of intermolecular multiple quantum coherences (iMQCs), (13-21) which in this case correspond to exciting water spin resonances while simultaneously de-exciting lipid resonances from molecules that are separated by the "correlation distance," typically tens of micrometers. The method is not restricted to biological tissues; in essence, it uses a temperature-insensitive resonance to clean up the response of a temperature-sensitive resonance, with the critical advantage that the two types of spins need not be in the same molecule or even in exactly the same position. It required the development of a new generation of pulse sequences that enable efficient and rapid iMQC detection to reduce the effects of physiological noise. In contrast to existing methods, it is intrinsically insensitive to static and transient inhomogeneity, does not require exogenous contrast, and can rapidly provide accurate temperature measurement on an absolute scale.

Recently, spatial encoding with nonlinear magnetic fields has drawn attention for its potential to achieve faster gradient switching within safety limits, tailored resolution in regions of interest, and improved parallel imaging using encoding fields that complement the sensitivity profiles of radio frequency receive arrays. Proposed methods can broadly be divided into those that use phase encoding (Cartesian-trajectory PatLoc and COGNAC) and those that acquire nonlinear projections (O-Space, Null space imaging, radial PatLoc, and 4D-RIO). Nonlinear projection data are most often reconstructed with iterative algorithms that backproject data using the full encoding matrix. Just like conventional radial sequences that use linear spatial encoding magnetic fields, nonlinear projection methods are more sensitive than phase encoding methods to imperfect calibration of the encoding fields. In this work, voxel-wise phase evolution is mapped at each acquired point in an O-Space trajectory using a variant of chemical shift imaging, capturing all spin dynamics caused by encoding fields, eddy currents, and pulse timing. Phase map calibration is then applied to data acquired from a high-power, 12 cm, Z2 insert coil with an eight-channel radio frequency transmit-receive array on a 3T human scanner. We show the first experimental proof-of-concept O-Space images on in vivo and phantom samples, paving the way for more in-depth exploration of O-Space and similar imaging methods.

To increase image acquisition efficiency, we develop alternative gradient encoding strategies designed to provide spatial encoding complementary to the spatial encoding provided by the multiple receiver coil elements in parallel image acquisitions. Intuitively, complementary encoding is achieved when the magnetic field encoding gradients are designed to encode spatial information where receiver spatial encoding is ambiguous, for example, along sensitivity isocontours. Specifically, the method generates a basis set for the null space of the coil sensitivities with the singular value decomposition (SVD) and calculates encoding fields from the null space vectors. A set of nonlinear gradients is used as projection imaging readout magnetic fields, replacing the conventional linear readout field and phase encoding. Multiple encoding fields are used as projections to capture the null space information, hence the term Null Space Imaging (NSI). The method is compared to conventional Cartesian SENSitivity Encoding (SENSE) as evaluated by mean squared error and robustness to noise. Strategies for developments in the area of nonlinear encoding schemes are discussed. The NSI approach yields a parallel imaging method that provides high acceleration factors with a limited number of receiver coil array elements through increased time efficiency in spatial encoding.