1. Image Processing for Interventional MRI Derek Hill Professor of Medical Imaging Sciences King’s College London

2. Image Processing for Interventional MRI Derek Hill Professor of Medical Imaging Sciences University College London

3. The team Kawal Rhode Marc Miquel Redha Berboutkah David Atkinson Maxime Sermesant Rado Andriantsimiavona Kate McLeish Sebastian Kozerke Reza Razavi Vivek Muthurangu Sanjeet Hegde Jas Gill Pier Lambraise Cliff Bucknall Eric Rosenthal Shaqueel Qureshi

4. Context Interventional MRI provides particular opportunities and challenges for image analysis. –Hostile environment for computers –“real time” requirements –Link between acquisition and analysis

5. Overview Background to XMR guided interventions Integrating x-ray and MRI Automatic cathether tracking Integration of image analysis in acquisition

6. XMR X-ray + cylindrical bore MRI in the same room Becoming main platform for MR guided interventions –Resection control in neurosurgery –Endovascular procedures Not ideal for percutaneous procedures

7. Patient Staff XMR suite at Guy’s (funded of JREI, Philips Medical Systems and Charitable Foundation of Guy’s & St Thomas’)

8. XMR System at Guy’s Hospital  XMR = hybrid X-ray/MR imaging  Common sliding patient table  Provides path to MR-guided intervention

9. XMR suite at Guy’s

10. Catheter manipulation

11. Visualizing catheters Fast imaging (70 msec per frame) –TE = 1.3, TR = 2.6 –SSFP sequence (balanced TFE) –Acquisition: 78 x 96, 80% FOV, 80% acq, SENSE factor 2 (ie: only 25 phase encodes!) Carbon dioxide filled balloon as contrast agent

12. Catheter Manipulation Images acquired with standard Philips real time or interactive sequences

13. Catheter Manipulation Miquel et al. Visualization and tracking of an inflatable balloon catheter using SSFP in a flow phantom and in the heart and great vessels of patients. Magn Reson. Med. 51(5):988-95 2004

15. Integrating x-ray and MRI XMR provide rapid transfer between modalities No capability to integrate the images X-ray and MRI provide complementary information Combined x-ray and MR has value in complex interventions eg: electrophysiology

17. T M1M1 Registration Matrix Calculation  Overall registration transform is composed of a series of stages  Calibration + tracking during intervention M2M2 M3M3 3D Image Space X-ray Table Space X-ray C-arm Space 2D Image Space Scanner Space R*P

18. XMR Registration: Software Overview

19. XMR Registration: Calibration  Acrylic calibration object with 14 markers  Interchangeable caps for MR and X-ray imaging  Determine geometric relationship between MR and X-ray system  Determine X-ray projection geometry MR X-ray

20. Calibration (1) Fixing flange for sliding table. (2) Saline-filled acrylic half cylinder with 20 divot cap markers in a helical arrangement. (3) Slot in acrylic base plate to allow sliding of half cylinder. (4) & (5) End stops. (6) Fixing to allow MR surface coil attachment

21. XMR Registration: MR Overlay on X-Ray

22. XMR Registration: 3D Reconstruction

23. XMR Registration: Phantom Validation  T1-weighted MR volume + 5 pairs of tracked x-ray images using calibration object as a phantom  2D RMS Error = 4.2mm (n=35), Range = 1.4 to 8.0 mm  3D RMS Error = 4.6mm (n=17), Range = 1.7 to 9.0 mm  “Registration and Tracking to Integrate X- ray and MR Images in an XMR Facility “, Rhode et al, TMI, Nov 2003.

25. Clinical Example Patient undergoing electrophysiology study prior to RF ablation of heart rhythm abnormality

26. MR Imaging - Anatomy  SSFP three- dimensional multiphase sequence  5 phases  256x256 matrix  152 slices  resolution=1.33 x 1.33 x 1.4 mm  TR=3.0 ms  TE=1.4 ms  flip angle=45 

27. MR Imaging - Motion  SPAMM tagged imaging sequence  59 phases SA & 50 phases LA  256x256 matrix  11 slices SA & 4 slices LA  resolution=1.33 x 1.33 x 8.0 mm  TR=11.0 ms  TE=3.5 ms  flip angle=13   tag spacing=8 mm

28. X-ray Imaging + Electrical Mapping LAO ViewAP View  Contact electrical mapping system  Constellation catheter (Boston Scientific)

29. MR Anatomy Overlay

30. Catheter Reconstruction

31. Refining the Registration  Errors due to limitations of registration technique and patient motion  Basket point cloud meshed  Rigid surface-to-image registration used to realign the basket mesh

32. Visualising the Electrical Data  Cycle 1 - normal  Cycle 2 - ectopic

33. Instantiation of model

34. Simulation results LV volume

35. Catheters re-visited Essential properties of catheters –Clearly visible –Safe mechanically electrically Magnetically Desirable properties –Automatic localization –Tip and length visible CO 2 filled balloon catheters are safe Tip location ambiguous Length not visible Cannot be localized automatically

36. Is there an image analysis solution? Find catheter automatically in modulus image? Is it easier to find in a phase image?

37. Better solution: change nucleus Fluorine is not present in body High NMR sensitivity Safe blood subsitutes available (eg: PFOB)

38. Catheter tracking(a)(b)(c) SSFP proton image plus fluorine projections Phantom setup

39. Catheter tracking(a)(b)(c) Automatic superposition Of catheter tip on proton image Phantom setup

40. Lumen visible

41. Dynamic scan

42. Catheter Tracking and Visualization Using 19 F Nuclear Magnetic Resonance Sebastian Kozerke 1,2, Sanjeet Hegde 3, Tobias Schaeffter 4, Rolf Lamerichs 5, Reza Razavi 3, Derek L. Hill 2 Magn. Reson. Med. 2004 (in press)

43. Image analysis combined with acquisition Real time MRI can provide high temporal resolution, but low quality Can we subsequently combine real time images to generate high image quality?

44. Real time MRI with slice tracking Real time undersampled radial acquisitions Navigator Slice tracking

45. Registration to compensate for motion Rigid body then non-rigid registration to correct motion During scanning

46. Demonstration on gated volunteer heart images (n=4) Undersampled images

47. Demonstration on gated volunteer heart images (n=4) Combined with no registration

48. Demonstration on gated volunteer heart images (n=4) Combined with rigid registration

49. Demonstration on gated volunteer heart images (n=4) Combined with rigid then non-rigid registration

51. Conclusions Interventional MRI is fertile area for image analysis Real time requirements New applications (eg: RF ablation) Improving guidance Novel acquisition and reconstruction incorporating image analysis