Parallel transmission RF pulse design with local SAR constraints
A method of designing a parallel transmission radio frequency (RF) pulse for a magnetic resonance imaging (MRI) system includes compressing a model for a subject to be scanned by the MRI system into a plurality of voxel clusters, each voxel cluster defining a virtual observation point with a peak sensitivity to local specific absorption rate (SAR) for the voxel cluster, and defining the parallel transmission RF pulse based on an approximation of a minimization criterion having a local SAR component based on the peak sensitivity of each virtual observation point, the approximation comprising a weighted sum of the local SAR values for each virtual observation point.
1. A method of configuring a magnetic resonance imaging (MRI) system for scanning with a parallel transmission radio frequency (RF) pulse, the method comprising:
compressing a model for a subject to be scanned by the MRI system into a plurality of voxel clusters, each voxel cluster defining a virtual observation point with a peak sensitivity to local specific absorption rate (SAR) for the voxel cluster;
defining the parallel transmission RF pulse based on an approximation of a minimization criterion having a local SAR component based on the peak sensitivity of each virtual observation point, the approximation comprising a weighted sum of local SAR values for the virtual observation points; and
storing the parallel transmission RF pulse for use by the MRI system.
2. The method of claim 1 , wherein the model comprises a number of voxels, and wherein compressing the model comprises:
calculating a spatial matrix for each voxel of the model, the spatial matrix being indicative of absorption sensitivity;
defining an upper bound matrix for each virtual observation point as a sum of the spatial matrix of the virtual observation point and a unit matrix scaled by an overestimation factor that tunes the compressing step.
3. The method of claim 2 , wherein the minimization criterion includes a component indicative of total power of the parallel transmission RF pulse scaled by the overestimation factor.
4. The method of claim 2 , further comprising selecting the overestimation factor.
5. The method of claim 1 , wherein the model comprises a number of voxels, and wherein compressing the model comprises evaluating an eigenvalue of a spatial matrix for each voxel of the model, the spatial matrix being indicative of absorption sensitivity.
6. The method of claim 1 , wherein defining the parallel transmission RF pulse comprises iterating the approximation of the minimization criterion.
7. The method of claim 1 , wherein the approximation of the minimization criterion is based on a set of weighting factors.
8. The method of claim 7 , wherein each weighting factor is applied to the peak sensitivity of a respective one of the virtual observation points.
9. The method of claim 7 , wherein defining the parallel transmission RF pulse comprises updating the set of weighting factors based on local SAR values of the virtual observation points for a given RF pulse and a predicted direction that increases the local SAR values.
10. A method of configuring a magnetic resonance imaging (MRI) system in connection with a model for a subject to be scanned by the MRI system with a parallel transmission radio frequency (RF) pulse, the model being defined via a number of voxels, the method comprising:
calculating a spatial matrix for each voxel of the model, the spatial matrix being indicative of absorption sensitivity;
defining a plurality of clusters of the voxels in the model, each cluster having a virtual observation point representing a maximum sensitivity to local specific absorption rate (SAR) for each voxel in the cluster; and
selecting, for use by the MRI system, the parallel transmission RF pulse that minimizes an approximation of a design criterion having a local SAR component based on the peak sensitivity of each virtual observation point, the approximation comprising a weighted sum of local SAR values for the virtual observation points.
11. The method of claim 10 , wherein defining the plurality of clusters comprises defining an upper bound matrix for each virtual observation point as a sum of the spatial matrix of the virtual observation point and a unit matrix scaled by an overestimation factor that tunes the compressing step.
12. The method of claim 11 , wherein the design criterion includes a component indicative of total power of the parallel transmission RF pulse scaled by the overestimation factor.
13. The method of claim 11 , further comprising selecting the overestimation factor.
14. The method of claim 11 , wherein defining the plurality of clusters comprises evaluating an eigenvalue of the spatial matrix for each voxel of the model.
15. The method of claim 11 , wherein defining the parallel transmission RF pulse comprises iterating the approximation of the design criterion.
16. The method of claim 11 , wherein the approximation of the design criterion is based on a set of weighting factors.
17. The method of claim 16 , wherein each weighting factor is applied to the maximum sensitivity of a respective one of the virtual observation points.
18. The method of claim 11 , wherein selecting the parallel transmission RF pulse comprises updating the set of weighting factors based on local SAR values of the virtual observation points for a given RF pulse and a predicted direction that increases the local SAR values.
19. A magnetic resonance imaging (MRI) system comprising:
a data storage unit to store calibration data for a model for a subject to be scanned, the model having a number of voxels;
a coil array for transmitting a parallel transmission radio frequency (RF) pulse to the subject; and
a control system in communication with the data storage unit and the coil array and configured to select the parallel transmission RF pulse for transmission via the coil array;
wherein the control system is configured to design the parallel transmission RF pulse to control local specific absorption rate (SAR) based on the model, a model compression in which the model is compressed into a plurality of clusters of the voxels of the model, each cluster defining a virtual observation point with a peak sensitivity to local SAR for the voxel cluster, and an approximation of a design criterion having a local SAR component based on the peak sensitivity of each virtual observation point, the approximation comprising a weighted sum of local SAR values for the virtual observation points.
20. The magnetic resonance imaging (MRI) system of claim 19 , wherein the control system is configured to calculate a spatial matrix for each voxel of the model, the spatial matrix being indicative of absorption sensitivity, and further configured to define an upper bound matrix for each virtual observation point as a sum of the spatial matrix of the virtual observation point and a unit matrix scaled by an overestimation factor that tunes the compressing step.
21. The magnetic resonance imaging (MRI) system of claim 20 , wherein the design criterion includes a component indicative of total power of the parallel transmission RF pulse scaled by the overestimation factor.
22. The magnetic resonance imaging (MRI) system of claim 19 , wherein the control system is configured to evaluate an eigenvalue of a spatial matrix for each voxel of the model, the spatial matrix being indicative of absorption sensitivity.
23. The magnetic resonance imaging (MRI) system of claim 19 , wherein the control system is configured to iterate the approximation of the design criterion.
24. The magnetic resonance imaging (MRI) system of claim 19 , wherein the approximation of the design criterion is based on a set of weighting factors.
25. The magnetic resonance imaging (MRI) system of claim 24 , wherein the control system is configured to apply each weighting factor to the peak sensitivity of a respective one of the virtual observation points.
26. The magnetic resonance imaging (MRI) system of claim 24 , wherein the control system is configured to update the set of weighting factors based on local SAR values of the virtual observation points for a given RF pulse and further configured to predict a direction that increases the local SAR values.