An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities

1. Session – Parallel Imaging: Stretching the Limit #549 An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities Jason P. Stockmann and R. Todd Constable

2. An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities #549 Introduction Theory/Methods Results Conclusion Declaration of Conflict of Interest or Relationship Jason P. Stockmann: I have no conflicts of interest to disclose with regard to the subject matter of this presentation.

3. An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities #549 Introduction Theory/Methods Results Conclusion O-Space imaging • Motivation • Parallel imaging developments have focused on coil arrays with ever-larger numbers of RX coils • Problem of diminishing returns • New Approach : O-Space Imaging • Examine parallel imaging with attention to: • Encoding provided by receiver coils • Encoding provided by spatial magnetic field gradients

4. An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities #549 Introduction Theory/Methods Results Conclusion Tailor gradient shapes to coil profiles Instead of tailoring coil profiles to conventional gradients…. …design gradients to provide complementary information.

5. An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities #549 Introduction Theory/Methods Results Conclusion Tailor gradient shapes to coil profiles ProjectionImagingalong Rings • Frequency is encoded radially • (2D coverage) • 2. Eliminate phase encoding • 3. Use multiple Center Placements (CPs) and projection reconstruction Instead of encoding frequency incolumns

6. An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities #549 Introduction Theory/Methods Results Conclusion Parallel imaging with spherical harmonics X Y Z2 • Choose gradient shape to optimally complement coil profiles • Select a subset of spherical harmonics in the axial plane: • Dynamic Shim Updating XY X2-Y2 Z2X De Graaf RA, MRM, 2003;49:409-416. Z2Y X3 Y3 PatLoc Hennig J et al, MAGMA, 2008;21:5-14. ISMRM 2009 #564, #762,#4557, #3052, #3061, #3073

7. An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities #549 Introduction Theory/Methods Results Conclusion Acceleration performance Stockmann JP et al., MRM, 2010, in press.

8. An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities #549 Introduction Theory/Methods Results Conclusion Noise performance Stockmann JP et al., MRM, 2010, in press.

9. An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities #549 Introduction Theory/Methods Results Conclusion Effects of ring density Stockmann JP et al., MRM, 2010, in press.

10. An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities #549 Choosing an encoding scheme Introduction Theory/Methods Results Conclusion + + + B0 offset = FFT Echo r2 Projection Multiple center placements take the place of phase encodes See E-poster #4556

11. An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities #549 Introduction Theory/Methods Results Conclusion Image reconstruction Express integral equation as a matrix problem and solve using Kaczmarz iterative projection algorithm Non-linear gradient Coil Echo Flexible approach that works for all gradient functions, coil profiles, and gradient pulse shapes Kaczmarz S. Angenäherte Auflösung von Systemen linearer Gleichungen. Bull. Internat. Acad. Polon.Sci. Lettres A, pages 335-357, 1937. See poster #2857 Herman GT et al. Comput. Biol. Med. 1976;6:273-294.

12. An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities #549 Sensitivity to B0 inhomogeneity Introduction Theory/Methods Results Conclusion Reference Model Incorporate Tikhonov regularization (truncated SVD) into Kaczmarz reconstruction

13. An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities #549 Sensitivity to B0 inhomogeneity Introduction Theory/Methods Results Conclusion (Break up into smaller figures for improved visibility) Bpeak 250 Hz 0 Hz 50 Hz 150 Hz Unreg. R = 16 r = 0.6 Unreg. R = 8 r = 0.6 Unreg. R = 4 r = 0.6

14. An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities #549 Introduction Theory/Methods Results Conclusion Experimental Data 3T Tim Trio System 180 90 90 … RF Resonance Research Z2 gradient insert 18,000 Hz/cm2 120 s rise time GZ … GY … GX … GZ2 … In-house 8-channel microstrip transceive array DAQ … TE

15. An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities #549 Obstacles Introduction Theory/Methods Results Conclusion • Low Z2 gradient strength (0.07 g/cm2)= long readout window (50 ms) • B0 Inhomogeneity • B0 Offset • Eddy currents • Solution: Build dedicated high-strength, shielded gradient coil for O-Space imaging.

16. An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities #549 Introduction Theory/Methods Results Conclusion Outlook • O-space shows promise for highly accelerated imaging • Design spatial gradients to be more complementary to coil spatial encoding for highly-efficient parallel imaging [Leo Tam, ISMRM 2009, Abstract #3072] PatLoc: [Fa-Hsuan Lin, ISMSM 2009, Abstract #4557] • Currently seeking optimal gradient shapes and trajectories for non-linear projection imaging

17. An Assessment of O-Space Imaging Robustness to Local Field Inhomogeneities #549 Thank you Introduction Theory/Methods Results Conclusion O-space abstracts at ISMRM: This work would not have been possible without the following people: Christoph Juchem Robin de Graaf Hemant Tagare Douglas Rothman Laura Sacolick Terry Nixon Peter Brown NIH Neuroengineering Training Grant 5T90DK070068-05 • #4556Pelin Aksit Ciris, "O-Space Imaging: Tailoring Encoding Gradients to Coil Profiles for Highly Accelerated Imaging“ • #2857Jason Stockmann, “Kaczmarz Iterative Reconstruction for Arbitrary Hybrid Encoding Functions” • #3072Leo Tam, “Non-linear encoding gradient optimization for O-Space imaging with a microstrip coil array” • #3078Jason Stockmann, “Refocusing Method for Mapping Imaging Gradients with High SNR” • #564, #762Gerrit Schultz, • #3052, #3061, #3073Anna Welz • #2859, #2676Maxim Zaitsev • #4557Fa-Hsuan Lin PatLoc-related Abstracts: Slides available at: mri.med.yale.edu/individual/stockmann