Magnetic resonance imaging method with sub-sampled acquisition

Details Magnetic resonance imaging method with sub-sampled acquisition Magnetic resonance imaging method with sub-sampled acquisition

2001-07-30

2003-02-11

Lefkowitz, Edward (Department: 2862)

Electricity: measuring and testing

Particle precession resonance

Using a nuclear resonance spectrometer system

C324S309000, C324S318000

Reexamination Certificate

active

06518760

ABSTRACT:

TECHNICAL DESIGNATION
The invention relates to a magnetic resonance imaging method comprising the steps of
acquisition of sub-sampled magnetic resonance signals with a system of receiver antennae
the system of receiver antennae having a spatial sensitivity profile
reconstruction of a magnetic resonance image on the basis of
the sub-sampled magnetic resonance signals
the spatial sensitivity profile and
a priori image information
optimization of the reconstruction with respect to a pre-selected aspect of distribution of sampled data included in the sub-sampled magnetic resonance signals over the reconstructed magnetic resonance image.
PRIOR ART DOCUMENT
Such a magnetic resonance imaging method is known from the paper ‘
SENSE: Sensitivity encoding for fast MR-imaging’
in Magnetic Resonance in Medicine 42 (1999) 952.
DISCUSSION OF PRIOR ART
This magnetic resonance imaging method is commonly known as the ‘SENSE-method’ in the field of MR-imaging. In the known magnetic resonance imaging method the number of phase-encoding steps is reduced so as to reduce the time required for the acquisition of magnetic resonance signals. Consequently, the acquired magnetic resonance signals are built-up as superpositions of contributions from several positions in the scanned volume. The spatial sensitivity profile of the system of receiver antennae is employed to decompose the superposed contributions into signal amplitudes relating to separate positions in the scanned volume. These signal amplitudes represent the brightness values in the magnetic resonance image at full sampling. In other words, part of the spatial encoding of the magnetic resonance signals is performed on the basis of the spatial sensitivity profile. The decomposition of the sub-sampled magnetic resonance signals into signal amplitudes involves a reconstruction matrix which relates the signal amplitudes to the sub-sampled magnetic resonance signals.
The cited reference mentions that different optimizations may be employed in the reconstruction. The so-called strong reconstruction derives the reconstruction matrix from a close approximation to a pre-selected spatial encoding. In particular the strong reconstruction is carried out as a least-squares approximation to a pre-selected set of voxel functions which represent the pre-selected spatial encoding. The so-called weak reconstruction derives the reconstruction matrix from a close approximation to a pre-selected noise distribution in the reconstructed magnetic resonance image.
The known SENSE-method employs a priori knowledge in the reconstruction in that for positions which are outside the object to be examined the pixel-value is set to zero in the reconstructed magnetic resonance image. However, this a priori information is difficult to acquire and the cited reference hardly provides any effective measures to obtain this a priori information. Furthermore, it appears in practice that the this use of a priori information gives rise to artefacts in the reconstructed magnetic resonance image.
OBJECT OF THE INVENTION
An object of the invention is to provide a magnetic resonance imaging method in which artefacts are more effectively avoided in the magnetic resonance image reconstructed from the sub-sampled magnetic resonance signals.
STATEMENT OF THE INVENTION
This object is achieved by the magnetic resonance imaging method according to the invention wherein said a priori information is taken into account as a constraint in said optimization.
DESCRIPTION OF THE INVENTION
The invention is based on the insight that the known method produces artefacts in the form of ugly cut-line effects and that these are effects due to the blunt setting to zero of pixel values without taking into account the unfolding of sub-sampled magnetic resonance signals in the decomposition process. According to the invention the a priori information is taken into account in the optimization as a constraint which is implemented, for example, mathematically while using one or several Lagrange multipliers. This results in more gradual employment of the a priori information in the decomposition or unfolding of the image information in the sub-sampled magnetic resonance signals. A simple optimization procedure consists of a least-squares fit method that is quite reliable and easy to implement.
The a priori information, for example, includes accurate information on the position of the object to be examined with respect to the field-of-view of the magnetic resonance imaging system. Notably the position of the patient's chest wall and its motion due to breathing are taken into account in the a priori information as to for which pixel-positions (almost) zero pixel values are expected. The a priori information may also include information relating to the manner of the acquisition of magnetic resonance signals and effective filter settings from which information on the expected pixel-values can already be derived. The a priori information be may made available in the form of pre-set pixel values for the magnetic resonance image to be reconstructed. The a priori information may also pertain to a local permissible noise level in the reconstructed magnetic resonance image. In another example the a priori information stipulates that pixel values cannot exceed a preset ceiling value.
It is noted that the present invention is advantageously used in conjunction with several different forms of sub-sampling. The time required for the acquisition of the magnetic resonance (MR) signals is reduced by employing sub-sampling of the MR-signals. Such sub-sampling involves a reduction in k-space of the number of sampled points that can be achieved in various ways. Notably, the MR signals are picked-up through signal channels pertaining to several receiver antennae, such as receiver coils that are preferably surface coils. Acquisition through several signal channels enables parallel acquisition of signals so as to achieve a further reduction of the signal acquisition time.
Owing to the sub-sampling, sampled data contain contributions from several positions in the object being imaged. The magnetic resonance image is reconstructed from the sub-sampled MR-signals while using a sensitivity profile associated with the signal channels. Notably, the sensitivity profile is, for example, the spatial sensitivity profile of the receiver antennae, such as receiver coils. Preferably, surface coils are employed as the receiver antennae. The reconstructed magnetic resonance image may be considered as being composed of a large number of spatial harmonic components which are associated with brightness/contrast variations at respective wavelengths. The resolution of the magnetic resonance image is determined by the smallest wavelength, that is by the highest wavenumber (k-value). The largest wavelength, i.e. the smallest wavenumber, involved, is the size of the field-of-view (FOV) of the magnetic resonance image. The resolution is determined by the ratio of the field-of-view to the number of samples. In the event that the SENSE technique is employed, said ratio is referred to as the SENSE-factor which indicates the degree of sub-sampling.
The sub-sampling may be achieved in that respective receiver antennae acquire MR signals such that their resolution in k-space is coarser than required for the size of the field-of-view of the magnetic resonance image. The smallest wavenumber sampled, i.e. the minimum step-size in k-space, is increased while the largest wavenumber sampled is maintained. Hence, the image resolution remains the same when applying sub-sampling, whereas the minimum k-space step increases, i.e. the field-of-view decreases. The sub-sampling may be achieved by reducing of the sample density in k-space, for example by skipping lines in the scanning of k-space, so that lines in k-space are scanned that are spaced apart further than required for the size of the field-of-view of the magnetic resonance image. The sub-sampling may be achieved by reducing the field-of-view while maintaining the largest k-value so that the number of sampled points

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