Method and system for susceptibility weighted magnetic resonance imaging

Abstract

Method for susceptibility weighted magnetic resonance imaging of vasculature, the method comprising the following steps: acquiring multi-echo data containing a time-of-flight signal in at least the first echo (S1); identifying voxels belonging to arteries from the data (S2); andgenerating corresponding information on artery presence (S3); The invention further relates to a corresponding system (10) for susceptibility weighted magnetic resonance imaging of vasculature.

Claims

1. A method for susceptibility weighted magnetic resonance imaging of vasculature, the method comprising: acquiring multi-echo data containing a time-of-flight signal in at least a first echo; identifying voxels belonging to arteries from the multi-echo data; and generating corresponding information on artery presence; performing an echo combination step, or an echo combination step in combination with a phase masking step; using said corresponding information on artery presence to put emphasis on an artery appearance during said echo combination step and to prevent an inclusion of voxels belonging to arteries in the phase masking step; creating an arterial image AI; and identifying the voxels belonging to arteries in said arterial image, wherein in the performing the echo combination step, magnitude information from the echoes is combined using the following non-linear combination: $I=-\sqrt[p]{\frac{1}{N}\underset{i=1}{\overset{N}{.Math.}}{.Math.S_i.Math.}^{-p},}\mathrm{with}$ $p=\{\begin{array}{c}r\left(1-\frac{\mathrm{AI}}{2t}\right)\mathrm{for}\mathrm{AI}t\\ r\left(\frac{\left(1-\mathrm{AI}\right)}{2\left(1-t\right)}\right)\mathrm{for}\mathrm{AI}>t\end{array}$ wherein p is an integer or a non-integer greater than zero, r is a weighting factor from different echoes, and t is a threshold value that separates voxels that are unlikely to contain arteries from voxel that are likely to contain arteries.

2. The method according to claim 1, further comprising creating the arterial image AI by using first echo data or a combination of a first few echoes, or by determining a normalized residual of a linear fit of phase as a function of echo time.

3. The method according to claim 2, wherein the creating the arterial image AI comprises determining AI as follows: $\mathrm{AI}=\frac{.Math.I_{\mathrm{Echo}1}.Math.}{.Math..Math.I_{\mathrm{Echo}1}.Math..Math.}-1,\mathrm{AI}\left(\mathrm{AI}<0\right)=0,\mathrm{AI}\left(\mathrm{AI}>1\right)=1,$ wherein I.sub.Echo1 is a magnitude signal from the first echo or the combination of the first few echoes and |I.sub.Echo1| is a low-pass filtered version of the magnitude signal from the first echo or the combination of the first few echoes.

4. The method according to claim 1, further comprising identifying arteries by determining voxels for which a phase evolution as a function of echo time is not linear.

5. The method according to claim 1, further comprising applying the phase masking step to combined magnitude images using the PADRE algorithm.

6. The method according to claim 5, wherein a Padre mask of the PADRE algorithm is defined as: ${\mathrm{Mask}}_{\mathrm{PADRE}}\left(x\right)=\{\begin{array}{cc}{e}^{-{\left[{\left(1-\mathrm{AI}\right)}^{}\left(.Math.\left(x\right).Math.-\frac{*}{100}\right)\right]}^{}}& \mathrm{for}-\frac{*}{100}\\ 1& \mathrm{for}>-\frac{*}{100}\end{array}$ wherein , and are variables that control a response function of the MASK.sub.PADRE(x), is a weighting factor that controls an importance of an arterial term of the MASK.sub.PADRE(x), and (x) is the phase of the signal.

7. A non-transitory computer readable medium storing instructions that, when executed by a processor, cause the processor to perform a method comprising: identifying voxels belonging to arteries from multi-echo data containing a time-of-flight signal in at least a first echo; generating corresponding information on artery presence; performing an echo combination step or an echo combination step in combination with a phase masking step; and using said corresponding information on artery presence to put emphasis on an artery appearance during said echo combination step and to prevent an inclusion of voxels belonging to arteries in the phase masking step; create an arterial image AI; and identify the voxels belonging to arteries in the arterial image, wherein in the performing the echo combination step, magnitude information from the echoes is combined using the following non-linear combination: $I=-\sqrt[p]{\frac{1}{N}\underset{i=1}{\overset{N}{.Math.}}{.Math.S_i.Math.}^{-p},}\mathrm{with}$ $p=\{\begin{array}{c}r\left(1-\frac{\mathrm{AI}}{2t}\right)\mathrm{for}\mathrm{AI}t\\ r\left(\frac{\left(1-\mathrm{AI}\right)}{2\left(1-t\right)}\right)\mathrm{for}\mathrm{AI}>t\end{array}$ wherein p is an integer or a non-integer greater than zero, r is a weighting factor from different echoes, and t is a threshold value that separates voxels that are unlikely to contain arteries from voxel that are likely to contain arteries.

8. The non-transitory computer readable medium of claim 7, wherein the instructions, when executed by a processor, further cause the processor to create an arterial image AI by using first echo data or a combination of a first few echoes, or by determining a normalized residual of a linear fit of phase as a function of an echo time.

9. The non-transitory computer readable medium according to claim 8, wherein the instructions, when executed by a processor, further cause the processor to the arterial image AI by determining AI as follows: $\mathrm{AI}=\frac{.Math.I_{Echo1}.Math.}{.Math.I{.Math.}_{\mathrm{Echo}1}.Math..Math.}-1,\mathrm{AI}\left(\mathrm{AI}<0\right)=0,\mathrm{AI}\left(\mathrm{AI}>1\right)=1,$ wherein I.sub.Echo1 is a magnitude signal from the first echo or a combination of a first few echoes and |I.sub.Echo1| is a low-pass filtered version of the magnitude signal from the first echo or a combination of the first few echoes.

10. A system for susceptibility weighted magnetic resonance imaging of vasculature, the system comprising: a magnetic resonance device comprising: a pulse generator module configured to generate an excitation signal; and a data acquirer module, communicatively coupled with the pulse generator module and configured to acquire multi-echo data containing a time-of-flight signal in at least a first echo; and a post-processor module, communicatively coupled with the magnetic resonance device and configured: to post-process the multi-echo data including an echo combination step and a phase masking step, to identify voxels belonging to arteries from the multi-echo data; to generate corresponding information on artery presence, wherein said corresponding information puts emphasis on an artery appearance during said echo combination step and prevents an inclusion of voxels belonging to arteries in the phase masking step; create an arterial image AI; identity the voxels belonging to arteries in the arterial image; and determine magnitude information from the echoes is combined using the following non-linear combination: $I=-\sqrt[p]{\frac{1}{N}\underset{i=1}{\overset{N}{.Math.}}{.Math.S_i.Math.}^{-p},}\mathrm{with}$ $p=\{\begin{array}{c}r\left(1-\frac{\mathrm{AI}}{2t}\right)\mathrm{for}\mathrm{AI}t\\ r\left(\frac{\left(1-\mathrm{AI}\right)}{2\left(1-t\right)}\right)\mathrm{for}\mathrm{AI}>t\end{array}$ wherein p is an integer or a non-integer greater than zero, r is a weighting factor from different echoes, and t is a threshold value that separates voxels that are unlikely to contain arteries from voxel that are likely to contain arteries.

11. The system according to claim 10, wherein the post-processor module is further configured to generate an image of vasculature from the post-processed multi-echo data.

12. The system according to claim 10, further comprising a display generator module communicatively coupled with the post-processor module and configured to display an image of vasculature generated from the post-processed multi-echo data.

13. The system according to claim 10, wherein the post-processor module is further configured to create arterial image AI by using first echo data or a combination of a first few echoes, or by determining a normalized residual of a linear fit of phase as a function of an echo time.

14. The system according to claim 13, wherein the post-processor module is further configured to determine the arterial image AI as follows: $\mathrm{AI}=\frac{.Math.I_{Echo1}.Math.}{.Math.I{.Math.}_{\mathrm{Echo}1}.Math..Math.}-1,\mathrm{AI}\left(\mathrm{AI}<0\right)=0,\mathrm{AI}\left(\mathrm{AI}>1\right)=1$ wherein I.sub.Echo1 is a magnitude signal from the first echo or a combination of a first few echoes and |I.sub.Echo1| is a low-pass filtered version of the magnitude signal from the first echo or a combination of the first few echoes.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) These and other aspects of the invention will be apparent from and elucidated with reference to the embodiments described hereinafter.

(2) In the drawings:

(3) FIG. 1 shows a schematic representation of a system for susceptibility weighted magnetic resonance imaging according to a preferred embodiment of the invention;

(4) FIG. 2 shows a flow chart of a process for susceptibility weighted magnetic resonance imaging according to preferred embodiments of the invention;

(5) FIGS. 3a and 3b show two arterial images (AIs) for identifying voxels belonging to arteries;

(6) FIG. 4 shows a diagram depicting the variable p as a function of the arterial image AI; and

(7) FIGS. 5a and 5b show two susceptibility weighted images processed by use of different susceptibility weighted magnetic resonance imaging processes.

DETAILED DESCRIPTION OF EMBODIMENTS

(8) In the following discussion reference is made to arterial tissue as the object to be imaged. The invention is however applicable to other tissue as well. The arterial tissue is selected merely as a preferred example.

(9) FIG. 1 shows a schematic representation of a system 10 for susceptibility weighted magnetic resonance imaging. The system 10 comprises two main components, namely a magnetic resonance device 12 and a post-processor module 14. The magnetic resonance device 12 comprises a pulse generator module 16 configured to generate an initial excitation signal, and a data acquirer module 18, communicatively coupled with the pulse generator module 16 and configured to acquire multi-echo data containing a time-of-flight signal in at least the first echo. The post-processor module 14 is communicatively coupled with the magnetic resonance device 12 and configured (i) to post-process the data including an echo combination step and a phase masking step, (ii) to identify voxels belonging to arteries from the data; (iii) to generate corresponding information on artery presence, wherein said information on artery presence is used to guide the echo combination and/or phase masking step, and (iv) to generate an image of the vasculature from the post-processed data. The system 10 further comprises a display generator module 20, communicatively coupled with the post-processor module 14 and configured to display the image of the vasculature generated from the post-processed data.

(10) FIG. 2 shows a flow chart of a process for susceptibility weighted magnetic resonance imaging of vasculature. The process comprises the following steps:

(11) Step 1 (S1): acquiring multi-echo data containing a time-of-flight signal in at least the first echo;

(12) Step 2 (S2): identifying voxels belonging to arteries from an image based on first echo data or a combination of the first few echoes; and

(13) Step 3 (S3): generating corresponding information on artery presence;

(14) Step 4 (S4): combining the magnitude information from the echoes by use of a non-linear combination; and

(15) Step 5 (S5): applying a phase masking to the combined magnitude images generated in Step 4 using a suitable mask like e.g. the PADRE mask of the PADRE algorithm, wherein said information on artery presence (generated in step 3) is used to guide said echo combination step S4 and/or the phase masking step S5. In a final step at the end, an image of the vasculature is generated from the post-processed data resulting from steps 4 and 5.

(16) FIGS. 3a and 3b show two images for identifying voxels belonging to arteries (AIs: arterial images). The arteries can be identified by use of the information from the first echo or a combination of the first few echoes to create an arterial image (AI) (FIG. 3a on the left side), or by calculating a normalized residual of the linear fit of the phase as a function of the echo time (FIG. 3b on the right side).

(17) FIG. 4 shows a diagram depicting the variable p as a function of the arterial image AI according to the equation:

(18) $p=\{\begin{array}{cc}r\left(1-\frac{\mathrm{AI}}{2t}\right)& \mathrm{for}\mathrm{AI}t\\ r\left(\frac{1-\mathrm{AI})}{2\left(l-t\right)}-1\right)& \mathrm{for}\mathrm{AI}>t\end{array}$
for r=2 and t=0.5. The parameter p is used to combine the magnitude information from the four echoes using the non-linear combination:

(19) $I=\sqrt[-p]{\frac{1}{N}\underset{i=1}{\overset{N}{.Math.}}{.Math.S_i.Math.}^{-p}}.$

(20) The FIGS. 5a and 5b show two susceptibility weighted images of the same human head. The SWIp image shown in FIG. 5a is processed by use of the susceptibility weighted magnetic resonance imaging process known from the prior art, which is based on the 4-echo multiecho gradient-echo (mFFE) sequence. The image shown in FIG. 5b is processed by use of the susceptibility weighted magnetic resonance imaging process described in FIG. 2. As indicated by the FIGS. 5a and 5b: by using the process depicted in FIG. 2 a better differentiation between arteries and veins can be made.

(21) The use of the proposed combination and phase masking algorithms effectively restores the bright time-of-flight signal even in the largest arteries, thus providing a more reliable differentiation between arteries and veins. The very good susceptibility contrast provided by the SWIp sequence is effectively preserved for all voxels where the AI signal is low.

(22) While the invention has been illustrated and described in detail in the drawings and foregoing description, such illustration and description are to be considered illustrative or exemplary and not restrictive; the invention is not limited to the disclosed embodiments. Other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a study of the drawings, the disclosure, and the appended claims. In the claims, the word comprising does not exclude other elements or steps, and the indefinite article a or an does not exclude a plurality. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage. Any reference signs in the claims should not be construed as limiting the scope.