Electricity: measuring and testing – Particle precession resonance – Using a nuclear resonance spectrometer system
Reexamination Certificate
2001-04-03
2004-08-03
Arana, Louis M. (Department: 2859)
Electricity: measuring and testing
Particle precession resonance
Using a nuclear resonance spectrometer system
C324S309000
Reexamination Certificate
active
06771067
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates generally to magnetic resonance imaging (MRI), and more particularly relates to the cancellation of ghost artifacts in MRI imaging caused by a variety of distortion mechanisms.
BACKGROUND
Magnetic Resonance Imaging is based on the absorption and emission of energy in the radio frequency range. To obtain the necessary MR images, a patient (or other target) is placed in a magnetic resonance scanner. The scanner provides a uniform magnetic field that causes individual magnetic moments of spins in the patient or target to align with the magnetic field. The scanner also includes multiple coils that apply a transverse magnetic field. RF pulses (called “shots”) are applied to the coils that cause the aligned moments to be rotated or tipped. In response to the RF pulses, a signal is emitted by the excited spins that is detected by receiver coils.
The resulting data obtained by the receiver coils corresponds to the spatial frequency domain and is called k-space data. The k-space data includes multiple lines called phase encodes or echoes. Each line is digitized by collecting a number of samples (e.g., 128-256). A set of k-space data is acquired for each image frame, and each k-space data set is converted to an image by passing the data through a fast Fourier transform (FFT).
FIG. 1A
shows an example of a full k-space data set with all of the phase encodes (1, 2, 3 . . . N) acquired.
In several applications of MRI, a time series or sequence of images are obtained in order to resolve temporal variations experienced by the imaged object. For example, in cardiac imaging it is desirable to obtain a sequence of images to study the dynamic aspects of the heart. Unfortunately, image distortion such as ghost artifacts or blurring may interfere with the ability to properly interpret the image. An artifact is a feature that appears in the resultant image even though it is not actually present in the target object. Amplitude and/or phase distortion in the acquired k-space data causes distortion in the resultant reconstructed image. The order of k-space acquisition (phase encode order) is an important factor in determining the type of image distortion. Periodic distortion of k-space data causes periodic ghosts artifacts. A ghost artifact appears as part of the target object shifted an offset amount and superimposed on the final image.
There are a wide variety of mechanisms that cause distortion of the acquired k-space data and that may result in ghost and/or blurring artifacts. If the phase encode order results in distortion that is periodic or has a periodic component, the image will have periodic ghost artifacts. In this context, distortion is described herein as periodic if it has a periodic component (which causes image domain ghosts), even if the distortion is not purely periodic since it may contain other non-periodic components. Examples of distortion mechanisms include off-resonance due to chemical shift or susceptibility variation, flow (e.g., blood flow), motion of the imaged object (e.g., breathing, heart, etc.), EPI delay or phase misalignment, and T2* amplitude decay. Ghosts may also result from periodic undersampling of k-space, which is used in a number of reduced field of view methods for accelerated imaging.
Distortion may be space invariant or space variant. Space invariant distortion refers to the case where each pixel in the image has been affected by the same distortion, while the more general case of space variant distortion refers to the case where the distortion may vary depending on the pixel location. With a space invariant ghost, all pixels in the image have a corresponding ghost with a fixed separation and same relative amplitude. In the case of space variant ghost distortion, the relative amplitude and/or separation of the ghost may depend on the pixel location.
FIG. 2A
shows an example of multi-shot echo-planar imaging (EPI) with a non-interleaved phase encode order that cause distortion. The phase encodes are shown indicating the direction of a scan (indicated by arrow), such as shown at
10
. As can be seen, the echoes are taken sequentially from each shot (e.g., echo
1
, echo
2
, echo
3
, etc.). In this example, each shot has 4 echoes. Because the echo time (TE) for each echo is different, the amplitude and phase are different for each echo, which creates a distortion of the k-space data. Consequently, this non-interleaved ordering causes periodic distortion of the k-space data, which causes periodic ghosts in the resultant reconstructed image. For this reason, multi-shot non-interleaved phase encode ordering is not typically used to avoid ghost artifacts.
In this multi-shot EPI example, many prior art techniques eliminate the ghosts by acquiring the k-space data using an interleaved phase encode order to ensure that the distortion is not periodic and is a slowly varying function of k-space. Furthermore, a technique known as echo-shifting is also used to linearize the echo time (TE) versus phase encode number (ky) which also reduces blur distortion at the cost of increased overall acquisition time.
FIG. 2B
shows an example of an interleaved phase encode order. In the illustrated example, each shot has four echoes. The line of k-space are acquired in an interleaved manner such that groups of adjacent lines in k-space are acquired at the same echo time (TE). For example, the first echoes from each shot are grouped together, as shown at
12
. Likewise, all of the echos from the second shot are grouped together, as shown at
14
. Grouping together similar echoes in this interleaved manner eliminates the rapid variation of echo time versus k-space, and, therefore, eliminates widely spaced ghost artifacts in favor of a more subtle blurring and/or geometric distortion.
Echo-planar imaging (EPI) is used in many MR rapid imaging applications and ghost reduction for EPI has received considerable attention. Many techniques on the prior art are based on compensating (equalizing) periodic k-space distortion. These methods first estimate the periodic phase (or other) distortion, and then apply compensating phase function to eliminate or reduce the distortions. Numerous schemes have been developed for estimating the phase errors. However, these methods only cope with the case of space invariant distortion, therefore, residual distortion will remain, due to a number of space variant mechanisms that cannot be compensated for in this manner. Ghost artifacts due to local effects such as flow and off-resonance are space variant and are not mitigated by k-space phase compensation methods.
Methods have been developed which address certain cases of space variant distortion, such as local off-resonance effects. These rely on estimating the space variant distortion by means of a measurement of the field map, followed by applying the inverse to remove the space variant distortion. It is difficult to obtain accurate field maps, particularly in cases where the susceptibility (field) is time varying, such as in cardiac imaging applications. These methods are often quite sensitive to error cause by noise.
Phase array combining methods have been used for accelerated imaging (e.g., methods known as SENSE and SMASH) to cancel space invariant ghosts that arise from periodic undersampling. SMASH has also been applied to more general EPI ghost cancellation but still only handles space invariant distortion. An example of a technique using the SENSE method applied to single shot EPI ghost cancellation is shown in Kuhara et al.,
A Novel EPI Reconstruction Technique using Multiple RF Coil Sensitivity Maps
. This application acquired multi-coil full field-of-view (FOV) k-space data and separates the k-space data into even and odd lines. The even lines are passed through a first fast Fourier transform image reconstruction component, while the odd lines are passed through a second fast Fourier transform component. The even and odd lines are separately processed using the SENSE method. The outputs of each of the separate SENSE reconstructions are t
Kellman Peter
McVeigh Elliot
Arana Louis M.
Klarquist & Sparkman, LLP
The United States of America as represented by the Department of
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