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Towards navigation on the heart surface during coronary arterty bypass grafting

Abstract

Object

Coronary artery bypass grafting (CABG) is the standard treatment for advanced coronary artery diseases. In a preoperative MSCT, both wall plaque formations and resulting optimal anastomotic site are visible to the surgeon. During surgery, the identification of this position on the surface of the heart is of utmost importance for an effective revascularisation procedure. To assist the surgeon in this matter, a surgical navigation system for the open heart is desirable. This work focusses on an appropriate method for registration of a patient-specific map of the coronaries extracted from preoperative MSCT data with optical tracking data recorded intraoperatively at the ischaemic heart.

Methods

The proposed registration process is based on mutually shared anatomical point landmarks and vessel paths on the heart surface utilised in an enhanced weighted ICP algorithm. Bypass grafting predominantly takes place at the ischaemic heart which is significantly distorted compared to its preoperative shape. To account for that, the method includes corrections for the effects of muscle relaxation and torsion of the ischaemic heart.

Results

The registration process was tested retrospectively on real patient data recorded at the ischaemic heart during bypass grafting. After registration, the vessel paths and point landmarks recorded intraoperatively by the surgeon showed good accordance with the preoperative map of the coronaries.

Conclusion

The registration method presented here is capable of matching the relevant parts of a preoperatively extracted map of the coronaries with intraoperatively recorded optical tracking data. Thus, it can be used as a basis for a surgical navigation system intended to assist the surgeon in the localisation of the optimal anastomotic site during CABG.

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References

  1. Klotz S, Scheld HH (2007) Modern therapeutic strategies for coronary artery bypass grafting (CABG). Dtsch Arztebl 104(48)

  2. Peters TM (2000) Image-guided surgery: from X-rays to virtual reality. Comput Methods Biomech Biomed Eng 4(1): 27–57

    Article  CAS  Google Scholar 

  3. DiGioia AM, Picard F, Jaramaz B, Sell D, Moody JC, Playkseychuk A, Levison TJ, Nikou C, LaBarca RS, Muir P (2001) Computer assisted navigation systems for hip and knee reconstructive surgery, ASME 2001 design engineering technical conferences and computers and information in engineering conference

  4. Coste-Manière È, Adhami L, Mourgues F, Bantiche O (2004) Optimal planning of robotically assisted heart surgery: first results on the transfer precision in the operating room. Int J Robot Res 23(4–5): 539–548

    Article  Google Scholar 

  5. Alperin N, Levin DN, Pelizzari CA (1994) Retrospective registration of X-ray angiograms with MR images by using vessels as intrinsic landmarks. J Magn Resonan Imaging 4: 139–144

    Article  CAS  Google Scholar 

  6. Mourges F, Vieville T, Falk V, Coste-Manière È (2003) Interactive guidance by image overlay in robot assisted coronary artery bypass. MICCAI 2003, LNCS 2878, pp 173–181

  7. Mäkelä T et al (2002) A Review of Cardiac Image Registration Methods. IEEE Trans Med Imaging 21(9): 1011–1021

    PubMed  Article  Google Scholar 

  8. Hill DL et al (1991) Registration of MR and CT images for skull base surgery using point-like anatomical features. Br J Radiol 64(767): 1030–1035

    PubMed  CAS  Article  Google Scholar 

  9. Gower JC, Dijksterhuis GB (2004) Procrustes problems. Oxford University Press, NY

    Book  Google Scholar 

  10. Besl PJ, McKay ND (1992) A method for registration of 3-D shapes. IEEE Trans Pattern Anal Mach Intell 14(2): 239–256

    Article  Google Scholar 

  11. Zinsser T, Schmidt J, Niemann H (2003) A Refined ICP Algorithm for Robust 3-D Correspondence Estimation. Proc IEEE Int Conf Image Process 2: 695–698

    Google Scholar 

  12. Zhang Z (1994) Iterative Point Matching for Registration of Free-Form Curves and Surfaces. Int J Comput Vis 13: 119–152

    Article  Google Scholar 

  13. Gruen A, Akca D (2005) Least squares 3D surface and curve matching. ISPRS J Photogramm Remote Sens 59(3): 151–174

    Google Scholar 

  14. Rusinkiewicz S, Levoy M (2001) Efficient variants of the ICP algorithm. Proceedings of the third international conference on 3D digital imaging and modeling, pp 145–152

  15. Fitzpatrick JM, West JB, Maurer CR Jr (1998) Predicting error in rigid-body point-based registration. IEEE Trans Med Imaging 17(5): 694–702

    PubMed  Article  CAS  Google Scholar 

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Correspondence to Claudia Gnahm.

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Gnahm, C., Hartung, C., Friedl, R. et al. Towards navigation on the heart surface during coronary arterty bypass grafting. Int J CARS 4, 105 (2009). https://doi.org/10.1007/s11548-008-0273-y

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  • DOI: https://doi.org/10.1007/s11548-008-0273-y

Keywords

  • CABG
  • Registration
  • Decision support
  • Optical tracking system
  • MSCT