Cardiac MRI visualization for ventricular tachycardia ablation

  • Corine J. Godeschalk-Slagboom
  • Rob J. van der Geest
  • Katja Zeppenfeld
  • Charl P. Botha
Open Access
Original Article

Abstract

Objective

The integrated visualization of cardiac MRI during a ventricular tachycardia (VT) mapping and ablation procedure would provide improved catheter guidance and tissue assessment. We developed a system for and explored the added value of simultaneous visualization of intracardiac voltage measurements and MRI-derived myocardial scar information during VT ablation procedures.

Method

We propose the use of a synchronized 3D and 2D view. In 3D, the catheter will be guided optimally by assessing 3D scar characteristics and its relation to the ventricular anatomy. In 2D, a detailed assessment of the tissue can be made. We developed several 3D visualization techniques, including volume rendering of the scar and myocardial surfaces colored according to the voltage measurements. We also visualized context structures in the heart. For the 2D view, we proposed showing three adjacent slices simultaneously. To link the 3D with the 2D view, we added a linking plane and linking contours; the slice level shown in the 2D view is indicated in the 3D view.

Results

We evaluated our method via a case study during which we simulated the visual environment of an ablation procedure. The MRI-based volume rendering of scar tissue and the linking between the 3D and 2D views were both positively received. However, the visualization of the voltage measurements was found to be hard to interpret, partly due to the perceptually suitable but non-standard colormap.

Conclusions

Based on this study, we can conclude that our approach of displaying MRI data and integrating it with voltage measurements has potential to improve VT ablation procedures.

Keywords

Multi-modal visualization Cardiac MRI Ventricular tachycardia Catheter ablation 

References

  1. 1.
    Aliot EM, Stevenson WG, Almendral-Garrote JM, Bogun F, Calkins CH, Delacretaz E, Della Bella P, Hindricks G, Jaïs P, Josephson ME, Kautzner J, Kay GN, Kuck K-H, Lerman BB, Marchlinski F, Reddy V, Schalij M-J, Schilling R, Soejima K, Wilber D (2009) EHRA/HRS expert consensus on catheter ablation of ventricular arrhythmias. Heart Rhythm 6(6): 886–933PubMedCrossRefGoogle Scholar
  2. 2.
    Bogun FM, Desjardins B, Good E, Gupta S, Crawford T, Oral H, Ebinger M, Pelosi F, Chugh A, Jongnarangsin K, Morady F (2009) Delayed-enhanced magnetic resonance imaging in nonischemic cardiomyopathy: utility for identifying the ventricular arrhythmia substrate. J Am Coll Cardiol 53(13): 1138–1145PubMedCrossRefGoogle Scholar
  3. 3.
    Desjardins B, Crawford T, Good E, Oral H, Chugh A, Pelosi F, Morady F, Bogun F (2009) Infarct architecture and characteristics on delayed enhanced magnetic resonance imaging and electroanatomic mapping in patients with postinfarction ventricular arrhythmia. Heart Rhythm 6(5): 644–651PubMedCrossRefGoogle Scholar
  4. 4.
    Raymond J-M, Sacher F, Winslow R, Tedrow U, Stevenson WG (2009) Catheter ablation for scar-related ventricular tachycardias. Curr Probl Cardiol 34: 225–270PubMedCrossRefGoogle Scholar
  5. 5.
    Haqqani HM, Marchlinski FE (2009) Electrophysiologic substrate underlying postinfarction ventricular tachycardia: characterization and role in catheter ablation. Heart Rhythm 6: S70–S76PubMedCrossRefGoogle Scholar
  6. 6.
    Eckardt L, Breithardt G (2009) Catheter ablation of ventricular tachycardia. From indication to three-dimensional mapping technology. Herz 34(3): 187–196PubMedCrossRefGoogle Scholar
  7. 7.
    Heatlie GJ, Pointon K (2004) Cardiac magnetic resonance imaging. Postgrad Med J 80(939): 19–22PubMedCrossRefGoogle Scholar
  8. 8.
    de Roes SD, Borleffs JW, van der Geest RJ, Westenberg JJM, Marsan NA, Kaandorp TAM, Reiber JHC, Zeppenfeld K, Lamb HJ, Roos A, Schalij MJ, Bax JJ (2009) Infarct tissue heterogeneity assessed with contrast-enhanced MRI predicts spontaneous ventricular arrhythmia in patients with ischemic cardiomyopathy and implantable cardioverter-defibrillator. Circ Cardiovasc Imaging 2: 183–190PubMedCrossRefGoogle Scholar
  9. 9.
    Schmidt A, Azevedo CF, Cheng A, Gupta SN, Bluemke DA, Foo TK, Gerstenblith G, Weiss RG, Marbán E, Tomaselli GF, Lima JAC, Wu KC (2007) Infarct tissue heterogeneity by magnetic resonance imaging identifies enhanced cardiac arrhythmia susceptibility in patients with left ventricular dysfunction. Circulation 115(15): 2006–2014PubMedCrossRefGoogle Scholar
  10. 10.
    Yan AT, Shayne AJ, Brown KA, Gupta SN, Chan CW, Luu TM, Di Carli MF, Reynolds HG, Stevenson WG, Kwong RY (2006) Characterization of the peri-infarct zone by contrast-enhanced cardiac magnetic resonance imaging is a powerful predictor of post-myocardial infarction mortality. Circulation 114(1): 32–39PubMedCrossRefGoogle Scholar
  11. 11.
    Dickfeld T, Tian J, Ahmad G, Jimenez A, Turgeman A, Kuk R, Peters M, Saliaris A, Saba M, Shorofsky S, Jeudy J (2011) MRI-Guided ventricular tachycardia ablation: integration of late gadolinium-enhanced 3D scar in patients with implantable cardioverter-defibrillators. Circ Arrhythmia Electrophysiol 4(2): 172–184CrossRefGoogle Scholar
  12. 12.
    Wijnmaalen AP, van der Geest RJ, van Huls van Taxis CFB, Siebelink H-MJ, Kroft LJM, Bax JJ, Reiber JHC, Schalij MJ, Zeppenfeld K (2011) Head-to-head comparison of contrast- enhanced magnetic resonance imaging and electroanatomical voltage mapping to assess post-infarct scar characteristics in patients with ventricular tachycardias: real-time image integration and reversed registration. Eur Heart J 32(1): 104–114PubMedCrossRefGoogle Scholar
  13. 13.
    Codreanu A, Odille F, Aliot E, Marie P-Y, Magnin-Poull I, Andronache M, Mandry D, Djaballah W, Régent D, Felblinger J, de Chillou C (2008) Electroanatomic characterization of post-infarct scars: comparison with 3-dimensional myocardial scar reconstruction based on magnetic resonance imaging. J Am Coll Cardiol 52(10): 839–842PubMedCrossRefGoogle Scholar
  14. 14.
    Termeer M, Oliván Bescós J, Breeuwer M, Vilanova A, Gerritsen F, Gröller E (2007) CoViCAD: comprehensive visualization of coronary artery disease. IEEE Trans Vis Comput Graph 13(6): 1632–1639PubMedCrossRefGoogle Scholar
  15. 15.
    Oeltze S, Hennemuth A, Glaßer S, Kühnel C, Preim B (2008) Glyph-based visualization of myocardial perfusion data and enhancement with contractility and viability information. In: Spring Eurograph Visual Computer BiomedicineGoogle Scholar
  16. 16.
    Termeer MA (2009) Comprehensive visualization of cardiac MRI data. Vienna University of TechnologyGoogle Scholar
  17. 17.
    van der Geest R, Buller V, Jansen E, Lamb H, Baur L, van der Wall E, de Roos A, Reiber J (1997) Comparison between manual and automated analysis of left ventricular volume parameters from short axis MR images. J Comput Assist Tomogr 21: 756–765PubMedCrossRefGoogle Scholar
  18. 18.
    Drebin RA, Carpenter L, Hanrahan P (1988) Volume rendering. In: Proceedings of SIGGRAPH’88, computer graphics, vol 22, no. 4, pp 65–74Google Scholar
  19. 19.
    Tao Q, Milles J, van Huls van Taxis C, Lamb HJ, Reiber JHC, Zeppenfeld K, van der Geest RJ (2012) Toward magnetic resonance-guided electroanatomical voltage mapping for catheter ablation of scar-related ventricular tachycardia: a comparison of registration methods. J Cardiovasc Electr 23(1): 74–80CrossRefGoogle Scholar
  20. 20.
    Aurenhammer F (1991) Voronoi diagrams—a survey of a fundamental geometric data structure. ACM Cumput Surv 23(3): 345–405CrossRefGoogle Scholar
  21. 21.
    Dijkstra EW (1959) A note on two problems in connexion with graphs. Numer Math 1(1): 269–271CrossRefGoogle Scholar
  22. 22.
    Borland D, Taylor RM (2007) Rainbow color map (still) considered harmful. IEEE Comput Graph. IEEE Computer Society, Los Alamitos, vol 27, pp 14–17Google Scholar
  23. 23.
    Kato H, Billinghurst M (1999) Marker tracking and HMD calibration for a video-based augmented reality conferencing system. In: International workshop on augmented reality (IWAR’99) IEEE Computer Society, vol 85Google Scholar
  24. 24.
    Yin RK (2009) Case study research: design and methods. Sage, Beverly HillsGoogle Scholar
  25. 25.
    Kimmel R, Sethian JA (1998) Computing geodesic paths on manifolds. Proc Natl Acad Sci USA 95(15): 8431–8435PubMedCrossRefGoogle Scholar

Copyright information

© The Author(s) 2012

Authors and Affiliations

  • Corine J. Godeschalk-Slagboom
    • 1
    • 2
  • Rob J. van der Geest
    • 1
  • Katja Zeppenfeld
    • 3
  • Charl P. Botha
    • 1
    • 4
  1. 1.Division of Image Processing, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
  2. 2.Biomedical EngineeringDelft University of TechnologyDelftThe Netherlands
  3. 3.Department of CardiologyLeiden University Medical CenterLeidenThe Netherlands
  4. 4.Computer Graphics and Visualization, Department of Intelligent SystemsDelft University of TechnologyDelftThe Netherlands

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