Magnetic resonance method and apparatus for artifact prevention in fast 3D spin echo sequences

In a method and magnetic resonance (MR) apparatus for creating an MR 3D image dataset, spin echo sequences are used to acquire two raw datasets that are each undersampled, wherein the excitation pulses or the refocusing pulses radiated in the data acquisitions have an opposite phase for the two raw datasets. These two raw datasets are combined into a combined 3D raw dataset that is not undersampled, and a weighting matrix is calculated for use in calculating the raw data points that were not acquired in the first raw dataset and the raw data points not acquired in the second raw dataset. A first complete raw dataset and second complete raw dataset are thereby calculated, which are then combined. The MR 3D data is then reconstructed from tis combined raw dataset.

BACKGROUND OF THE INVENTION

Field of the Invention

The present invention concerns a method for creating a 3D magnetic resonance (MR) image dataset of a subject under examination, and an associated MR system, and a non-transitory, electronically readable data storage medium.

Description of the Prior Art

In MR imaging, a fast 3D spin echo sequence is known in which, after a radio-frequency (RF) excitation pulse, a refocusing pulse train of up to several hundred refocusing pulses is radiated, some of these refocusing pulses having reduced refocusing flip angles. This imaging sequence was originally designed with non-selective RF excitation pulses, which means that raw MR data can be acquired therewith only from entire volumes can be acquired thereby. In order to be able to use such 3D multi-spin echo sequences in regions under examination such as the spine, hip or pelvis, a selective operating mode for this sequence was introduced, in which a selective RF excitation pulse is used with a train of non-selective refocusing pulses.

Using the non-selective refocusing pulses after the excitation pulse, however, results in FID (free induction decay) signals within the echo train from regions outside the selectively excited volume. This can cause artifacts that interfere with the imaging and make the diagnosis harder.

SUMMARY OF THE INVENTION

An object of the present invention is to improve such fast 3D spin-echo based imaging sequences so that these artifacts resulting from the FID signal are reduced.

According to a first aspect of the invention, this object is achieved by a method for acquiring a 3D MR image dataset for a subject under examination using a number of reception coils. The method includes radiating at least one first RF excitation pulse into the subject under examination followed by one or more first non-frequency-selective RF refocusing pulses in order to generate at least one first spin echo. The one or more first spin echoes are acquired in a first raw dataset in the three-dimensional raw dataspace (k-space) using multiple reception coils, in which process the first raw dataset of the raw dataspace is filled only partially with raw data such that the first raw dataset is not filled (sampled) completely with raw data according to the Nyquist theorem. In addition, at least one second RF excitation pulse is radiated into the subject under examination, followed by one or more second non-selective RF refocusing pulses in order to generate the one or more second spin echoes. In this case, the second RF refocusing pulses each have an opposite phase to the first RF refocusing pulses. Alternatively, it is possible for the first and second RF excitation pulses to have an opposite phase. The one or more second spin echoes are acquired in a second raw dataset in the three-dimensional raw dataspace using the multiple reception coils, in which process, for the second raw dataset, said dataset is filled only partially with raw data such that the second portion is not completely sampled with raw data according to the Nyquist theorem. The first raw dataset and second raw dataset in total fill the raw dataspace with raw data fully according to the Nyquist theorem. The first raw dataset and the second raw dataset are brought together into a combined three-dimensional raw dataset that is filled with raw data fully according to the Nyquist theorem. Then a weighting matrix for parallel imaging is calculated on the basis of the combined 3D raw dataset for use in calculating (estimating) the raw data points that were not acquired in the first raw dataset and the raw data points not acquired in the second raw dataset. The raw data points that were not acquired in the first raw dataset are created (synthesized by estimation) using the weighting matrix and the raw data acquired in the first raw dataset. These calculations for the two raw datasets can be performed both in the raw dataspace and in the image space, for instance in this case using the SENSE technique.

It is thus possible to calculate a first complete raw dataset from the raw data points created for the first raw dataset and from the raw data acquired in the first raw dataset. In addition, the raw data points not acquired in the second raw dataset are created (synthesized by estimation) using the weighting matrix and the raw data points acquired in the second raw dataset, so a second complete raw dataset is calculated from the raw data points created for the second raw dataset and from the raw data points acquired in the second raw dataset. The first complete raw dataset and the second complete raw dataset are added together to form a combined complete raw dataset, to which a known transformation (reconstruction) algorithm is applied so as to create the 3D MR image dataset.

Acquiring the two raw datasets having the opposite phase so that together they fill the entire raw dataspace means that the acquisition time is shortened, because there is no need to fill the entire raw dataspace twice fully with raw data. Also, it is possible to use the combined 3D raw dataset to calculate the weighting matrix which is then needed for calculating the first complete raw dataset and the second complete raw dataset. It is then possible to combine these two complete raw datasets to create the 3D MR image dataset, in which then the artifacts resulting from the FID signals are reduced or entirely suppressed. Using the refocusing pulses in the second raw dataset with opposite phase, i.e. with a phase rotated through 180°, means that the FID signals outside the excited subject under examination add destructively and cancel out, with the result that now just the spin echoes provide the major signal component. In addition, the measurement time is reduced because both the first raw dataset and the second raw dataset are undersampled.

The first complete raw dataset and the second complete raw dataset can be added by complex addition in the raw dataspace or in the image space (domain).

It is possible to acquire the first and second raw datasets such that they have no shared raw data points. Half of the 3D raw dataset is preferably acquired in the first raw dataset, with the other half acquired in the second raw dataset, resulting overall in the 3D raw dataspace being acquired in full, but only once.

The first complete raw dataset and the second complete raw dataset can be produced using reconstruction techniques (that include the aforementioned estimation of the “missing” data points) from parallel imaging, for instance the GRAPPA technique or using the CAIPIRINHA technique. The missing data points in the two raw datasets are estimated by these techniques and using the weighting matrix that was calculated on the basis of the combined 3D raw dataset.

The first RF excitation pulse and the second RF excitation pulse are preferably frequency-selective excitation pulses, although the method can also be used with non-frequency-selective RF excitation pulses.

The first raw dataset and the second raw dataset can be acquired separately from one another in succession or in what is known as the interleaved pattern, in which portions of the second raw dataset are acquired before the acquisition of the first raw dataset has completely finished.

The first raw dataset and the second raw dataset preferably each occupy half of the entire raw dataspace, and respectively fill each half.

The associated MR system has an MR data acquisition scanner with a number of reception coils, an RF controller, and at least one image sequence controller, which also controls the multiple reception coils and the RF controller such that the acquisition of the raw dataspace is performed as above. The MR system also has a processor that calculates the 3D MR image dataset as described above.

The present invention also encompasses a non-transitory, computer-readable data storage medium that, when the storage medium is loaded into a computer or computer system of a magnetic resonance imaging apparatus, cause the computer or computer system to operate the magnetic resonance imaging apparatus in order to implement any or all embodiments of the method according to the invention, as described above.

The features described above and the features described below can be used not only in the corresponding explicitly presented combinations, but also in other combinations unless explicitly stated otherwise.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention is described in detail below using preferred embodiments with reference to the accompanying drawings. The same reference numbers denote identical or similar elements in the figures. In addition, the figures are schematic representations of various embodiments, and the elements depicted in the figures are not necessarily shown to scale. The elements shown in the figures are depicted in a way that makes their function and purpose clear to those skilled in the art. The connections shown in the figures between functional units or other elements can also be implemented as an indirect connection. Each connection can be wireless or hardwired. Functional units can be implemented as hardware, software or as a combination of hardware and software.

An MR system9is explained with reference toFIG. 1. The MR system9is operable so as to produce 3D spin-echo based MR images having reduced FID artifacts, as will be explained below. The MR system9has an MR data acquisition scanner with a basic field magnet that generates a polarization field B0, into which a person under examination on a table12is moved in order to acquire spatially encoded magnetic resonance signals from the person13, using a number of reception coils11. The invention uses a technique known as parallel imaging, in which the MR signals are acquired simultaneously by the multiple reception coils11. By applying radio frequency pulses and by switching magnetic field gradients in the scanner10, certain nuclear spins in the patient are given a magnetization that causes those excited nuclear spins to be deflected from the direction dictated by the polarization field B0. As those excited nuclear spins relax, they emit RF signals, called magnetic resonance signals that are detected by the reception coils11. Complex numbers, representing the detected MR signals, are entered into a memory organized as k-space, as raw data, which are then transformed into image data, as described below.

The principles of how MR images are produced by applying RF pulses and switching magnetic field gradients in various combinations and sequences are known to those skilled in the art, and thus need not be explained in more detail herein.

The MR system has a control computer20that controls the MR system9. The control computer20includes an RF controller14that controls and generates the RF pulses for deflecting the magnetization. A gradient controller15is provided that controls and switching of the necessary magnetic field gradients. An image sequence controller16controls the sequence of the magnetic field gradients, the signal detection, and the RF pulses, and hence indirectly operates the gradient controller15, the reception coils11and the RF controller14. An operator can control the MR system9via an input interface17, and MR images and other information needed for control can be displayed on a display monitor18. A processor19is provided for controlling the various components of the control computer20. In addition, a memory21is provided in which program modules and/or program code can be stored that can control the process flow of the MR system9when executed by the processor19. As explained below, the image sequence controller16and the processor19are designed such that a 3D raw dataspace is filled in a specific manner with spin echoes in order to produce a 3D MR image dataset, which prevents the occurrence of FID artifacts, in a shorter acquisition time than the prior art.

FIG. 2schematically shows the 3D MR imaging sequence. After a frequency-selective RF excitation pulse22, a first RF refocusing pulse23is radiated, followed by further non-selective RF refocusing pulses24-26, which can have a smaller focusing angle than 180°, in order to reduce the energy radiated into the person under examination. In the slice-selection direction Gz, the slice-selection gradient27for exciting the desired region in the subject under examination is switched simultaneously with the excitation pulse22. The gradient switchings28and29needed for the phase encoding are additionally performed, likewise the gradient switchings30and31in the phase-encoding direction. In the readout direction, the readout gradients34-36are switched during the signal readouts32,33, wherein the first echo cannot be read out.

It is now explained, with additional reference toFIG. 3, how an imaging sequence of this type is used to acquire the raw dataspace. In a first step, as shown on the left ofFIG. 3, only the first half of the raw dataspace is acquired, where reference sign45is used to represent the raw data lines that are not acquired, which run into the drawing plane in the kxdirection, as it is a 3D dataset. The figure also shows the raw data46that are acquired by a first phase cycle, which means that the refocusing pulses23-26have a first phase relative to the excitation pulse. If the RF excitation pulse is applied in the x direction, for example, all the refocusing pulses can be radiated in the y direction. This is thus a sampling pattern that is similar to the IPAT pattern, but without acquisition of reference lines. This produces a first raw dataset40.

In addition, in a second step, a second raw dataset50is acquired, which is shown on the right inFIG. 3, where in turn55is used to represent the raw data lines that are not acquired, while56represents the data acquired in the second raw dataset50, in which process the phase of the refocusing pulses differs by 180° from the phase of the refocusing pulses for the acquisition of the raw data points46. Referring toFIG. 2, this means that the refocusing pulses are acquired once using a first phase, and a second time for the second raw dataset50using a second, opposite phase, i.e. a phase offset of 180°. For example, if the refocusing pulses23-26are radiated along the +y direction for the first raw dataset, then it is possible when applying the radiation for the second raw dataset, to radiate said pulses along the −y direction. Alternatively, it is possible to have an opposite phase for the excitation pulses.

The two raw datasets40,50are then acquired such that ultimately the 3D raw dataspace is acquired in full, although once only, since each of the two raw datasets ofFIG. 3is undersampled.

AsFIG. 4shows, it is then possible to combine the two raw datasets40and50to produce a combined 3D raw dataset as represented inFIG. 4by reference numeral60. In this process, the acquired raw data from the two raw datasets40and50are combined. When using an opposite phase for the excitation pulses, the two raw datasets are then subtracted in the combination. From the combined 3D raw dataset60, it is then possible to calculate from a central region61of the combined raw dataset a weighting matrix, for example what is known as the GRAPPA kernel, which can then be used to calculate the missing regions in the two raw datasets40and50, namely the raw data points having reference signs45and55. Hence a first complete raw dataset also is calculated using the weighting matrix, or kernel, and a second complete raw dataset is calculated using the weighting matrix. These two complete raw datasets can then be added in a complex addition in order to prevent the FID artifacts. It is also possible for the two raw dataspaces to be added by complex addition, and then reconstructed.

Since a number of echo trains are normally necessary in order to acquire the raw dataspace in full, the two raw datasets need not be acquired successively in time but can also be acquired with a technique known as an interleaved pattern.

Option A (conventional pattern):

R1,+, R2,−, R3,+, R4,−. . . Rn−1,+, Rn,−where R denotes the number of echo trains, and + and − each ref er to the phase of the refocusing pulse, where N is the number of repetitions.

FIG. 5shows schematically once again the datasets acquired or calculated in the various steps. The first raw dataset40is acquired using the first RF excitation pulses and the first non-frequency-selective refocusing pulses, with the second raw dataset50being acquired using the second spin echoes and the opposite refocusing pulses. These can then be combined into a combined 3D raw dataset60, wherein the weighting matrix can be calculated using the central region61. This weighting matrix can then be used to calculate a first complete raw dataset70using the acquired raw data in the raw dataset40, and likewise the second complete raw dataset80can be calculated using the raw data points measured in the second raw dataset and the weighting matrix. By combining these two complete raw datasets it is possible to produce the 3D raw dataset100, in which process the addition is a complex addition.

In the pattern employed inFIG. 4, raw data points or raw data lines were alternately acquired and not acquired in the kz or ky direction. The method can be applied arbitrarily in the kz or ky direction, however, i.e. the two raw dataspaces40and50can be formed in any way provided they are not filled entirely with raw data and the two raw datasets40and50do not overlap at the raw data points.

For calculating the first complete raw dataset and the second complete raw dataset, other parallel imaging techniques such as CAIPIRINHA can be used other than the GRAPPA technique.

FIG. 6re-summarizes the steps. In a step S61, the first raw dataset40is acquired by applying the first RF excitation pulses and the first non-frequency-selective RF refocusing pulses. This first raw dataset is not filled fully with raw data and is thus undersampled according to the Nyquist theorem. In step S62, the second raw dataset50is likewise acquired, as was explained in association withFIGS. 2 and 3. As explained above, the steps S61and S62need not be performed in succession but can also be performed in parallel in what is known as the interleaved method, in which portions of the first raw dataset40and portions of the second raw dataset50are acquired alternately. Then in the step S63, the acquired raw data is combined into the combined 3D raw dataset60. In the step S64, the weighting matrix, or the kernel, can then be calculated on the basis of the combined 3D raw dataset. It is thereby ultimately possible, in step S65, to calculate the first complete raw dataset70and the second complete raw dataset80respectively, wherein the 3D MR image dataset100can finally be calculated, in the step S66, by adding these complete raw datasets. The MR images produced using this 3D MR image dataset exhibit no FID artifacts or only highly suppressed FID artifacts, with it being possible to reduce the measurement time overall at least by a factor of 2 compared with the prior art.