MAGNETIC RESONANCE IMAGING METHOD WITH HYBRID FILLING OF K-SPACE

Abstract

A method for generating an image data set of an image area located in a measurement volume of a magnetic resonance system comprising a gradient system and an RF transmission/reception system, comprises the following method steps: —reading out k-space corresponding to the imaging area, by: (a) activating a frequency encoding gradient in a predetermined spatial direction and with a predetermined strength G0 by means of said gradient system, (b) after the activated frequency encoding gradient achieves its strength G0, radiating a non-slice-selective RF excitation pulse by means of said RF transmission/reception system, (c) after a transmit-receive switch time ΔtTR following the radiated excitation pulse, acquiring FID signals with said RF transmission/reception system and storing said FID signals as raw data points in k-space along a radial k-space trajectory that is predetermined by the direction and strength G0 of the frequency encoding gradient, (d) repeating (a) through (c) with respectively different frequency encoding gradient directions in each repetition until k-space corresponding to the image area is read out in an outer region of k-space along radial k-space trajectories, said radial k-space trajectories each having a radially innermost limit kgap which depends on said switch time ΔtTR, (e) reading out a remainder of k-space that corresponds to the imaging area, said remainder being an inner region of k-space not being filled by said first region and including at least a center of k-space, in a read out procedure that is different from (a) through (d), and storing all data points read out in (d) and (e); and —reconstructing image data from the read out data points ink-space by implementing a reconstruction algorithm; In order to constrain image fidelity and optimize scan duration under given circumstances, the inner k-space region is subdivided into a core region and at least one radially adjacent shell region.

Description

FIELD OF THE INVENTION

The present invention generally relates to a method of magnetic resonance (MR) imaging. More specifically, it relates to a zero echo time imaging method useful for MRI of tissues with short coherence lifetimes.

BACKGROUND OF THE INVENTION

Direct imaging of tissues with short transverse relaxation times (T₂ or T₂*) is interesting both from a scientific and also from a clinical point of view (see [1] and references cited therein). It is known that imaging of samples with relaxation times shorter than a few milliseconds requires specialized imaging methods, which most notably include zero echo time (ZTE) based techniques such as algebraic ZTE, PETRA (Pointwise Encoding Time Reduction with Radial Acquisition) and WASPI (Water And Fat Suppressed Proton Projection MRI) [2-4].

U.S. Pat. No. 8,878,533 B1 is directed to a method for generating an image data set of an image area located in a measurement volume of a magnetic resonance system, the magnetic resonance system comprising a gradient system and an RF transmission/reception system, the method comprising:

• • reading out k-space corresponding to the imaging area, by:
  • (a) activating a frequency encoding gradient in a predetermined spatial direction and with a predetermined strength G₀ by means of said gradient system,
  • (b) after the activated frequency encoding gradient achieves its strength G₀, radiating a non-slice-selective RF excitation pulse by means of said RF transmission/reception system,
  • (c) after a transmit-receive switch time Δt_TR following the radiated excitation pulse, acquiring FID signals with said RF transmission/reception system and storing said FID signals as raw data points in k-space along a radial k-space trajectory that is predetermined by the direction and strength G₀ of the frequency encoding gradient,
  • (d) repeating (a) through (c) with respectively different frequency encoding gradient directions in each repetition until k-space corresponding to the image area is read out in an outer region of k-space along radial k-space trajectories, said radial k-space trajectories each having a radially innermost limit k_gap which depends on said switch time Δt_TR,
  • (e) reading out a remainder of k-space that corresponds to the imaging area, said remainder being an inner region of k-space not being filled by said first region and including at least a center of k-space, in a read out procedure that is different from (a) through (d), and storing all data points read out in (d) and (e); and
  • reconstructing image data from the read out data points in k-space by implementing a reconstruction algorithm.

According to the above, the k-space region corresponding to the imaging area is subdivided into an inner region and an outer region, wherein the outer region surrounds the inner region, the inner region containing the center of k-space. Different read out procedures are used in the inner and outer regions. In the outer region, the read out is conveniently done along radial k-space trajectories using a gradient strength G₀, whereas in the inner region some different read out procedure is adopted.

According to an advantageous embodiment defined in U.S. Pat. No. 8,878,533 B1, the raw data points in the inner region are acquired as Cartesian raw data. This implementation is generally known as the PETRA technique.

A somewhat different approach is used in the case of WASPI, where the raw data in the inner region are also acquired along radial k-space trajectories, but with a lower gradient strength G<G₀. The two datasets, i.e. the inner dataset and the outer dataset are combined with optional linear merging in an overlap region [1].

While the use of algebraic ZTE is favorable at small dead-time gaps, direct measurement of missing data is required when more than 3 Nyquist dwells are missed (a dwell corresponds to the inverse of the imaging bandwidth in time domain or to the inverse of the field of view in k-space). In this case, PETRA is usually preferred over WASPI due to its robustness against short-T2 related artifacts [1]. However, its scan efficiency decreases quickly with gap size.

Accordingly, it would be desirable to provide an improved MR imaging method. It is thus an object of the present invention to provide a zero echo time imaging method useful for MRI of tissues with short coherence lifetimes which can overcome some of the limitations of the presently used methods such as algebraic ZTE, WASPI and PETRA.

SUMMARY OF THE INVENTION

According to the present invention, a method for generating an image data set of an image area located in a measurement volume of a magnetic resonance system comprising a gradient system and an RF transmission/reception system, comprises the following method steps:

• • reading out k-space corresponding to the imaging area, by:
  • (a) activating a frequency encoding gradient in a predetermined spatial direction and with a predetermined strength G₀ by means of said gradient system,
  • (b) after the activated frequency encoding gradient achieves its strength G₀, radiating a non-slice-selective RF excitation pulse by means of said RF transmission/reception system,
  • (c) after a transmit-receive switch time Δt_TR following the radiated excitation pulse, acquiring FID signals with said RF transmission/reception system and storing said FID signals as raw data points in k-space along a radial k-space trajectory that is predetermined by the direction and strength G₀ of the frequency encoding gradient,
  • (d) repeating (a) through (c) with respectively different frequency encoding gradient directions in each repetition until k-space corresponding to the image area is read out in an outer region of k-space along radial k-space trajectories, said radial k-space trajectories each having a radially innermost limit k_gap which depends on said switch time Δt_TR,
  • (e) reading out a remainder of k-space that corresponds to the imaging area, said remainder being an inner region of k-space not being filled by said first region and including at least a center of k-space, in a read out procedure that is different from (a) through (d), and storing all data points read out in (d) and (e); and
  • reconstructing image data from the read out data points in k-space by implementing a reconstruction algorithm.

By virtue of the fact that the inner k-space region is subdivided into a core region and at least one radially adjacent shell region, with raw data points in the core region being acquired as Cartesian raw data, and raw data points in the shell region being acquired along radial k-space trajectories using a gradient strength G that is smaller than the gradient strength G₀, it is possible to optimize image fidelity and scan duration under given circumstances.

The method of the present invention will henceforth be addressed as hybrid filling and abbreviated as “HYFI”. The HYFI approach improves scan efficiency at large gaps with minimum loss of image quality.

The method of the present invention can be implemented in a conventional MR imaging apparatus.

According to step c), the acquisition of FID signals is started after a transmit-receive switch time Δt_TR in order to avoid measurement artifacts. This shall include embodiments using the shortest reasonably possible waiting time given by the switch time of the MRI apparatus, but it shall also include embodiments with a somewhat extended waiting time. In the later cases, there will be an increase of scan time because of the need to recover missing information and signal intensity will be lower due nuclear spin relaxation.

Further details and definitions are given in the section “Theory” further below.

Advantageous embodiments are defined in the dependent claims.

According to one embodiment (claim 2), wherein the boundary k_gap subdividing the inner and outer k-space regions is given by the product of bandwidth BW and dead time Δt₀, wherein the dead time Δt₀ is given by Δt_RF, which is a part of the RF pulse, particularly half of the RF pulse for symmetric RF pulses, plus the transmit-receive switch time Δt_TR.

According to a further embodiment (claim 3), the core region has an outer limit k_core given by

$k_{\mathrm{core}}=\frac{\Delta t_0}{\Delta t}·s_{\mathrm{Mi}n}$

wherein

• • the dead time to is given by Δt_RF, which is a part of the RF pulse, particularly half of the RF pulse for symmetric RF pulses, plus the transmit-receive switch time Δt_TR,
  • the allowed acquisition duration Δt is given by −T₂ ln(1−A) wherein A is an amplitude parameter selected between 0 and 1.
  • the minimum shell thickness s_Min is selected to be between 0.1 and 10, preferably between 0.5 and 2, particularly about 1.

With the above definition, one can limit Cartesian acquisition to a small core region and thus allow using the more efficient radial acquisition wherever possible.

According to another embodiment (claim 4), the shell region comprises at least two shell regions (S₁, S₂, . . . ), each shell region S_i having a shell thickness s_i given by

$s_i=\frac{\Delta t}{\Delta t_0}·k_{in}$

each shell region having an inner radius k_in defined by the thickness of the next radially inward core or shell region. Starting from the innermost region, i.e. the core region, concentric shell regions are added in an onion-like manner until reaching the boundary between inner k-space region and outer k-space region. In an alternative embodiment (claim 5), the various shell regions are radially overlapping, in which case the signal in the overlap region is subjected to a linear interpolation step.

According to yet another embodiment (claim 6), the reconstruction algorithm comprises a Fourier transformation of the data points.

BRIEF DESCRIPTION OF THE DRAWINGS

The above mentioned and other features and objects of this invention and the manner of achieving them will become more apparent and this invention itself will be better understood by reference to the following description of embodiments of this invention taken in conjunction with the accompanying drawings, wherein:

FIG. 1 shows data acquisition in zero echo time-based techniques:

• • a) the gradient (G) is ramped up (upper trace) before spin excitation (middle trace); The beginning of the resulting FID cannot be probed due to the dead-time gap (Δt₀) (white dots in lower trace);
  • b) between excitations, the gradient direction is changed slowly to acquire different projections in order to fill the k-space volume of interest;
  • c-e) PETRA, WASPI, and HYFI differ in the way they provide the missing data; Left: 1D depiction of k-space T2 weighting; Right: 2D depiction of inner k-space acquisition geometry;
  • c) in PETRA, the inner k-space is acquired single-pointwise in a Cartesian fashion leading to constant T2 weighting;
  • d) in WASPI, a second set of radial acquisitions is performed at lower gradient strength, giving rise to increased and potentially strong T2 weighting;
  • e) HYFI, the method of this invention, is a hybrid between PETRA and WASPI: a combination of Cartesian SPI and multiple sets of radial acquisitions is used to keep the T2 decay in a given range R, wherein R is chosen such as to allow higher scan efficiency with minimum loss of image quality;

FIG. 2 shows relevant timing intervals in relation to the applied RF pulse; Δt₀ includes a part of the pulse Δt_RF, half of the pulse duration for symmetric pulses, and the transmit-receive switch time Δt_TR; and Δt is the time window corresponding to the acquisition of each shell;

FIG. 3 shows some fundamental relations holding for a given temporal decay of transversal magnetization M_xy(t);

FIG. 4 shows an example of HYFI acquisition wherein the inner region of −k space, of radius equal to the gap, is subdivided into a core region surrounded by two radially adjacent shell regions S1 and S2 of thickness equal to respectively s1 and s2;

FIG. 5 shows the number of excitations required by each technique to fill the inner k-space, assuming a T₂ decay of 64 Nyquist dwells; circles at the top illustrate the acquisition geometries; in 3D, the number of excitations evolves with k_gap³ for PETRA and k_gap² for WASPI; in the proposed method, inner k-space is filled by a combination of SPI and radial acquisitions, and thus the green area enclosed by the curves for PETRA and WASPI becomes accessible; green lines represent selected HYFI acquisitions with amplitude coefficients A=0.1 and 0.3;

FIG. 6 shows a simulation of point spread functions: 1D HYFI acquisitions were simulated with the following fixed parameters: image matrix size=128, T2=64 Nyquist dwells. PSFs are displayed for different combinations of gap sizes (a-c) and amplitude coefficients A (0=PETRA, 1=WASPI); and

FIG. 7 shows a comparison of magnetic resonance imaging acquired with PETRA (left column), WASPI (middle column) and HYFI (right column).

DETAILED DESCRIPTION OF THE INVENTION

Theory

k-Space Acquisition:

The norm of the acquired k-space point {tilde over (k)} is related to the acquisition time t:

{tilde over (k)}(t,G)=γ·G·t[m⁻¹]  (1)

with γ the gyromagnetic ratio [Hz/T], G the gradient [T/m], t the acquisition time [s]. Moreover, it is useful to express the k-space norm in number of Nyquist dwells (1 dwell has a length of

$\frac{1}{FOV}\left[m^{-1}\right]$

with FOV the field of view of the experiment) instead of [m⁻¹]. To do so, {tilde over (k)} should be multiplied by the field of view FOV:

k(t,G)={tilde over (k)}·FOV=γ·G·t·FOV  (2)

In PETRA, WASPI and HYFI, acquisition of the outer k-space is performed with a gradient strength G₀ and the first data point is sampled at k_gap, after the dead time Δt₀:

k _gap =k(Δt₀,G₀)=γ·G₀·Δt₀·FOV  (3)

All k-space points smaller than k_gap are missed during the acquisition of the outer k-space. However, PETRA, WASPI and HYFI recover the missing data with additional acquisitions performed with lower gradient strengths G (G<G₀) such that k-space samples smaller than the gap can be reached after the dead time.

k(Δt₀,G)<k(Δt₀,G₀)=k_gap  (4)

k-Space T2 Weighting:

Lowering the gradient strength decreases the k-space acquisition velocity v_k which express the number of Nyquist dwells acquired per unit time:

$\begin{array}{cc}{v}_k=\frac{\mathrm{dk}}{\mathrm{dt}}=\gamma ·G·\mathrm{FOV}\left[s^{-1}\right]& \left(5\right)\end{array}$

Hence, the k-space regions acquired with a lower gradient strength have a stronger T2 weighting because the amplitude decays faster for a given k-space range.

PETRA vs WASPI:

In PETRA, only one point is acquired per excitation after the dead time Δt₀ and gradient strengths and amplitudes are changed between each excitation in order to acquire the k-space center on a Cartesian grid. Since all points are measured after the same time, the inner k-space has a constant T2 weighting (FIG. 1c). The number of required excitations to fulfil the Nyquist criterion at the gap evolves with the third power of k_gap.

n _PETRA≈4/3·π·k_gap³  (6)

In WASPI, several points are measured radially after each excitation. Due to the use of low gradient strengths, the k-space is acquired slowly and a strong T2 weighting appears in the inner k-space. This lead to large amplitude jumps at the gap (FIG. 1d) which in turns gives rise to unwanted point spread function (PSF) side lobes (FIG. 6), see [1]. However timewise, WASPI acquisitions are more efficient than PETRA and especially at large gaps because the number of required excitation evolves with the second power of k_gap.

n _WASPI≈4·π·k_gap²  (7)

To summarize, the PSF of PETRA is preferred to the PSF of WASPI in view of better image fidelity due to smaller side lobes, but PETRA acquisitions are significantly longer at large gaps.

Detailed HYFI Description:

The goal of HYFI is to optimize scan duration while constraining depiction fidelity.

To this end, a radial acquisition geometry is used whenever possible to optimize scan efficiency but the T2 decay is restricted to a range R (FIG. 1e) to avoid large amplitude jumps and limit PSF side lobes.

The range R is defined proportionally to the amplitude of the transverse magnetization at the dead time M_xy(Δt₀) (FIG. 3).

$\begin{array}{cc}R=\left[1-\exp \left(-\frac{\Delta t}{T_2}\right)\right]·M_{xy}\left(0\right)·\exp \left(­\frac{\Delta t_0}{T_2^{*}}\right)=A·M_{xy}\left(\Delta t_0\right)& \left(8\right)\end{array}$

The amplitude factor A corresponds to the proportion of signal amplitude lost during the acquisition duration Δt due to an exponential decay of time constant T₂.

Hence, restricting the decay range R amounts to limiting A which is done by limiting the acquisition duration Δt.

Typically, the factor A can be optimized with preliminary acquisitions or simulations as illustrated in FIGS. 5 and 6. In this case, limiting A to 10-30% strongly decreases the number of excitations to be performed and largely preserves the PSF lineshape.

After optimization, the allowed acquisition duration can be calculated as (FIG. 3)

Δt=−T₂·ln(1−A)  (9)

However, the allowed acquisition duration may not be long enough to acquire the full inner k-space. Therefore, the inner k-space is split in an onion-like fashion with a core surrounded by one or several shells.

The gradient strength required to reach the core (or 0^th shell) corresponds to such a low k-space speed that the signal amplitude of the second point would be outside of the allowed range R at the time of its acquisition. Hence, the core is acquired single-pointwise on a Cartesian grid.

On the other hand, in the shells surrounding the core, several points can be measured after each excitation. Thus, in this case, k-space is acquired radially (FIG. 4).

Calculation of Shell Thickness:

The shell thickness, is given by the allowed acquisition duration Δt and the k-space acquisition velocity v_k.

s=Δt·v _k =Δt·γ·G·FOV=Δt·BW  (10)

with BW the imaging bandwidth.

The k-space acquisition velocity, v_k, is proportional to the gradient G (Eq. 5) which is determined by the inner radius of the shell, k_in. The inner radius k_in is by definition always acquired after the dead time Δt₀ and given by:

$\begin{array}{cc}\gamma ·G·\Delta t_0·\mathrm{FOV}=k_{in}& \left(11\right)\\ \to G=\frac{k_{in}}{\gamma \Delta t_0FOV}\left[T/m\right]& \left(12\right)\end{array}$

From Equ. 11 and Equ. 12, we can rewrite the shell thickness, s, as follow

$\begin{array}{cc}s=\frac{\Delta t}{\Delta t_0}·k_{in}& \left(13\right)\end{array}$

Note: shell thickness increases linearly with inner radius k_in.

HYFI Step by Step:

• 1) Define targeted transverse relaxation time T₂
• 2) Define maximum allowed decay range R within the shell (optimize amplitude parameter A).
• 3) Calculate maximum acquisition duration

Δt=−T₂·ln(1−A)

• 4) Define s_Min, the minimum shell thickness required to do radial acquisitions. Generally, s_Min is selected to be between 0.1 and 10, preferably between 0.5 and 2, and is typically chosen to be 1.
• 5) Calculate core radius, k_core, delimiting the boundary between SPI and radial acquisitions.

$\mathrm{Acquisition}\mathrm{geometry}=\{\begin{array}{cc}\mathrm{Cartesian}\mathrm{SPI},& k\le k_{\mathrm{core}}\\ \mathrm{radial},& k>k_{\mathrm{core}}\end{array}k_{\mathrm{core}}=\frac{\Delta t_0}{\Delta t}·s_{\mathrm{Mi}n}$

• 6) Calculate inner radius k_inj and outer radius k_{out j} for each shell j.

$k_{in_1}=k_{\mathrm{core}}s_j=\frac{\Delta t}{\Delta t_0}·k_{in_j}$ $k_{out_j}=k_{in_j}+s_j$ $k_{in_{j+1}}=k_{out_j}+\delta k\mathrm{with}0\le \mathrm{\delta k}\le 1\mathrm{and}\left\{\forall j|k_{in}j<k_{gap}\right\}.$

Note:

• • if δk=0, Nyquist criterion is fulfilled everywhere.
  • If δk=1, Nyquist criterion is not strictly fulfilled at shell boundaries.
  • As an option, it would also be possible to linearly merge shells over an overlap region in order to decrease irregularities in the k-space weighting.
• 7) Calculate k-space directions
  • a. SPI
    • i. All k-space point on Cartesian grid fulfilling

|k|≤k_core

• • b. Radial
    • i. Calculate number of shots (or radial spokes) to fulfill Nyquist criterion on the outer surface of each shell j

n=4·π·k_outj²

• • • ii. Calculate the directions of each shot by spreading these points on the surface of each shell following a suitable trajectory with approximately equal density.
• 8) Measure data on calculated trajectory
• 9) Reconstruct image

Concluding Remarks

FIG. 5 illustrates the scan efficiency of the different methods. At large gaps, the number of excitations required to fill the inner k-space is significantly larger in PETRA (4/3*π*k_gap³) than in WASPI (4*pi*k_gap²). In HYFI, relatively low amplitude coefficients (0.1 to 0.3) allow significant reduction of the number of excitations compared to PETRA while preserving satisfactory PSF lineshapes (FIG. 6). For example, at a gap of 30 Nyquist dwells and a T2 of 64 Nyquist dwells, the use of HYFI with A=0.3 reduces the number of shots required to fill the inner k-space by almost 80% (from 1.15 10⁵ to 2.45 10⁴). Assuming repetition times between 1 and 10 ms, this leads to a net gain of 1.5 to 15 minutes per scan.

The HYFI method is evaluated with 1D simulations of point spread functions (PSF), see FIG. 6.

One-dimensional point spread functions (PSF) were simulated by application of the following formula:

P=F·T·E·δ ₀

wherein F is the pseudo inverse of the encoding matrix E, T is the T2 weighting matrix (T2=64 Nyquist dwells) and δ₀ is the Kronecker delta function located in the center of the field of view.

Example

A comparison of magnetic resonance imaging acquired with PETRA (state of the art), WASPI (state of the art) and HYFI (present invention) is shown in FIG. 7. Magnetic resonance imaging was performed with PETRA (equivalent to HYFI with A=0), WASPI (equivalent to HYFI with A=1) and HYFI (A=0.2).

First Row: 1D representations of the signal T2-weighting in k-space. The signal amplitude in the outer k-space region is exponentially decaying and equivalent in all techniques. However, the acquisition of the inner k-space region is specific to each technique. In PETRA, the signal is acquired point by point at a constant time following the spin excitation leading to a constant T2-weighting in the inner k-space region. In WASPI, the inner k-space region is read out radially with a reduced gradient strength causing stronger signal decay and amplitude jumps at the border separating inner and outer k-space regions. In HYFI, the inner k-space region is split into several sub-regions: a core surrounded by shells. The core is read out single-pointwise similarly to PETRA. The shells are read out radially leading exponential decay of the signal amplitude.

Second Row:

• a) Number of spin excitations required for the acquisition of the inner k-space region.
• b) Repetition time (time separating two spin excitations) in milliseconds.
• c) Total scan duration (min:sec). Note: because of the slow acquisition of the inner k-space region, the repetition time of WASPI was increased to 3 milliseconds causing a strong increase in scan time despite the lower number of required excitations.
• d) Images. The sample consists of a stack of erasers (T2≈300 μs) standing on a hockey puck (T2≈100 us). In WASPI, the large amplitude jumps in k-space T2-weighting lead to strong artifacts in the image. HYFI offers similar image quality than PETRA with reduced scan time.

Additional Scanning Parameters:

• • Δt₀=100 μs, k_gap=25 Nyquist dwells, imaging bandwidth=250 kHz, duration of excitation pulse=2 μs

REFERENCES

• [1] Froidevaux, R. et al. (2017), Filling the dead-time gap in zero echo time MRI: Principles compared. Magn Reson Med. 2017 Aug. 30. doi: 10.1002/mrm.26875.
• [2] Wu Y, Dai G, Ackerman J L, Hrovat M I, Glimcher M J, Snyder B D, Nazarian A, Chesler D a. Water- and fat-suppressed proton projection MRI (WASPI) of rat femur bone. Magn Reson Med 2007; 57:554-67.
• [3] Grodzki D M, Jakob P M, Heismann B. Ultrashort echo time imaging using pointwise encoding time reduction with radial acquisition (PETRA). Magn Reson Med 2012; 67:510-8.
• [4] Weiger M, Pruessmann K P. MRI with Zero Echo Time. eMagRes 2012; 1:311-22.
• [5] Froidevaux R, Weiger M, Rösler M B, Wilm B, Hennel F, Luechinger R, Dietrich B E, Reber J, Pruessmann K P. Ultra-high-bandwidth, high-resolution MRI of fast relaxing spins Shot-T2 MRI: requirements High resolution. Proc 26th Annu Meet ISMRM, Honolulu 2017:4037.

Claims

1. A method for generating an image data set of an image area located in a measurement volume of a magnetic resonance system, the magnetic resonance system comprising a gradient system and an RF transmission/reception system, the method comprising: reading out k-space corresponding to the imaging area, by:(a) activating a frequency encoding gradient in a predetermined spatial direction and with a predetermined strength G0 via said gradient system,(b) after the activated frequency encoding gradient achieves its strength G0, radiating a non-slice-selective RF excitation pulse via said RF transmission/reception system,(c) after a transmit-receive switch time ΔtTR following the radiated excitation pulse, acquiring FID signals with said RF transmission/reception system and storing said FID signals as raw data points in k-space along a radial k-space trajectory that is predetermined by the direction and strength G0 of the frequency encoding gradient,(d) repeating (a) through (c) with respectively different frequency encoding gradient directions in each repetition until k-space corresponding to the image area is read out in an outer region of k-space along radial k-space trajectories, said radial k-space trajectories each having a radially innermost limit kgap which depends on said switch time ΔtTR,(e) reading out a remainder of k-space that corresponds to the imaging area, said remainder being an inner region of k-space not being filled by said first region and including at least a center of k-space, in a read out procedure that is different from (a) through (d), and storing all data points read out in (d) and (e); andreconstructing image data from the read out data points in k-space by implementing a reconstruction algorithm;whereinthe inner k-space region is subdivided into a core region and at least one radially adjacent shell region with raw data points in the core region being acquired as Cartesian raw data, and raw data points in the shell region (S) being acquired along radial k-space trajectories using a gradient strength G that is smaller than the gradient strength G0.

2. The method according to claim 1, wherein the boundary kgap subdividing the inner and outer k-space regions is given by the product of bandwidth BW and dead time Δt0, wherein the dead time Δt0 is given by ΔtRF, which is a part of the RF pulse plus the transmit-receive switch time ΔtTR.

3. The method according to claim 1, wherein the core region has an outer limit kcore given by:

4. The method according to claim 1, wherein the shell region comprises at least two shell regions (S1, S2, . . . ), each shell region Si having a shell thickness si

5. The method according to claim 1, wherein the shell region comprises at least two shell regions (S1, S2, . . . ), each shell region Si having a shell thickness si given by

6. The method according to claim 1, wherein the reconstruction algorithm comprises a Fourier transformation of the data points.

7. The method according to claim 2, wherein ΔtRF is half of the RF pulse for symmetric RF pulses.

8. The method according to claim 3, wherein ΔtRF is half of the RF pulse for symmetric RF pulses.

9. The method according to claim 3, wherein the minimum shell thickness sMin is between 0.5 and 2.

10. The method according to claim 3, wherein the minimum shell thickness sMin is about 1.

11. The method according to claim 2, wherein the shell region comprises at least two shell regions (S1, S2, . . . ), each shell region S, having a shell thickness si given by

12. The method according to claim 3, wherein the shell region comprises at least two shell regions (S1, S2, . . . ), each shell region S, having a shell thickness si given by

13. The method according to claim 2, wherein the shell region comprises at least two shell regions (S1, S2, . . . ), each shell region Si having a shell thickness si given by

14. The method according to claim 3, wherein the shell region comprises at least two shell regions (S1, S2, . . . ), each shell region Si having a shell thickness si given by

15. The method according to claim 2, wherein the reconstruction algorithm comprises a Fourier transformation of the data points.

16. The method according to claim 3, wherein the reconstruction algorithm comprises a Fourier transformation of the data points.

17. The method according to claim 4, wherein the reconstruction algorithm comprises a Fourier transformation of the data points.

18. The method according to claim 5, wherein the reconstruction algorithm comprises a Fourier transformation of the data points.