Skip to main content
SpringerLink
Log in

Accuracy considerations in image-guided cardiac interventions: experience and lessons learned

  • Original Article
  • Published:
International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Motivation

Medical imaging and its application in interventional guidance has revolutionized the development of minimally invasive surgical procedures leading to reduced patient trauma, fewer risks, and shorter recovery times. However, a frequently posed question with regard to an image guidance system is “how accurate is it?” On one hand, the accuracy challenge can be posed in terms of the tolerable clinical error associated with the procedure; on the other hand, accuracy is bound by the limitations of the system’s components, including modeling, patient registration, and surgical instrument tracking, all of which ultimately impact the overall targeting capabilities of the system.

Methods

While these processes are not unique to any interventional specialty, this paper discusses them in the context of two different cardiac image guidance platforms: a model-enhanced ultrasound platform for intracardiac interventions and a prototype system for advanced visualization in image-guided cardiac ablation therapy.

Results

Pre-operative modeling techniques involving manual, semi-automatic and registration-based segmentation are discussed. The performance and limitations of clinically feasible approaches for patient registration evaluated both in the laboratory and in the operating room are presented. Our experience with two different magnetic tracking systems for instrument and ultrasound transducer localization is reported. Ultimately, the overall accuracy of the systems is discussed based on both in vitro and preliminary in vivo experience.

Conclusion

While clinical accuracy is specific to a particular patient and procedure and vastly dependent on the surgeon’s experience, the system’s engineering limitations are critical to determine whether the clinical requirements can be met.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Cleary K, Peters TM (2010) Image-guided interventions: technology review and applications. Annu Rev Biomed Eng 12: 119–142

    Article  PubMed  CAS  Google Scholar 

  2. Peters TM, Cleary K (2008) In: Image-guided interventions: technology and applications. Springer, Heidelberg, Germany

  3. Galloway R, Peters TM (2008) Overview and history of image-guided interventions. In: Peters TM, Cleary K (eds) Image-guided interventions: technology and applications. Springer, Heidelberg, pp 1–21

    Chapter  Google Scholar 

  4. Jannin P, Fitzpatrick JM, Hawkes DJ, Pannec X, Shahidi R, Vannier MW (2002) Validation of medical image processing in image-guided therapy. IEEE Trans Med Imaging 21: 1445–1449

    Article  PubMed  Google Scholar 

  5. Viant WJ (2001) The development of an evaluation framework for the quantitative assessment of computer-assisted surgery and augmented reality accuracy performance. Stud Health Technol Inform 81: 534–540

    PubMed  CAS  Google Scholar 

  6. Linte CA, Moore J, Wiles A, Wedlake C, Peters T (2008) Virtual reality-enhanced ultrasound guidance: a novel technique for intracardiac interventions. Comput Aided Surg 13: 82–94

    PubMed  Google Scholar 

  7. Sauer F (2005) Image registration: enabling technology for image-guided surgery and therapy. In: Proceedings of IEEE engineering in medicine and biology society, pp 7242–7245

  8. Rettmann ME, Holmes DR III, Cameron B, Robb RA (2009) An event-driven distributed processing architecture for image-guided cardiac ablation therapy. Comput Methods Programs Biomed 95: 95–104

    Article  PubMed  CAS  Google Scholar 

  9. Rettmann ME, Holmes DR, Su Y, Cameron BM, Camp JJ, Packer DL, Robb RA (2006) An integrated system for real-time image-guided cardiac catheter ablation. In: Proceedings of medicine meets virtual reality, vol 119 of stud health technol inform, pp 455–460

  10. Linte CA, Wierzbicki M, Moore J, Guidardon GM, Jones DL, Peters TM (2007) On enhancing planning and navigation of beating-heart mitral valve surgery using pre-operative cardiac models. In: Proceedings of IEEE engineering in medicine and biology society, pp 475–478

  11. Ma YL, Penney GP, Rinaldi CA, Cooklin M, Razavi R, Rhode KS (2009) Echocardiography to magnetic resonance image registration for use in image-guided cardiac catheterization procedures. Phys Med Biol 54: 5039–5055

    Article  PubMed  Google Scholar 

  12. Damiano RJ Jr (2007) Robotics in cardiac surgery: The emperor’s new clothes. J Thorac Cardiovasc Surg 134: 559–561

    Article  PubMed  Google Scholar 

  13. Cho SD, Linte CA, Chen E, Moore J, Barron J, Kiaii B, Patel R, Peters TM (2010) Predicting target vessel location for improved planning of robot-assisted CABG procedures. In: Proceedings of medical image computing and computer-assisted intervention, vol 6363 of Lecture notes in Computer science, pp 205–212

  14. Linte CA (2010) Virtual and augmented reality techniques for minimally invasive cardiac interventions: concept, design, evaluation and pre-clinical implementation. Phd Dissertation, University of Western Ontario, Canada

  15. Karar ME, Gessat M, Walther T, Falk V, Burgert O (2009) Towards a new image guidance system for assisting transapical minimally invasive aortic valve implantation. In: Proceedings of IEEE engineering in medicine and biology society. pp 3645–3648

  16. Walther T, Dewey T, Borger MA, Kempfert J, Linke A, Becht R, Falk V, Schuler G, Moher FW, Mack M (2009) Transapical aortic valve implantation: step by step. Ann Thorac Surg 87: 276–283

    Article  PubMed  Google Scholar 

  17. Lorenzo-Valdés M, Sanchez-Ortiz GI, Mohiaddin D, Rueckert D (2002) Atlas-based segmentation and tracking of 3D cardiac MR images using non-rigid registration. In: Proceedings of medical image computing and computer-assisted intervention, vol 2488 of Lecture Notes in Computer Science, pp 642–650

  18. Wierzbicki M, Drangova M, Guiraudon GM, Peters TM (2004) Validation of dynamic heart models obtained using non-linear registration for virtual reality training, planning, and guidance of minimally invasive cardiac surgeries. Med Image Anal. 8: 387–401

    Article  PubMed  Google Scholar 

  19. Moore J, Drangova M, Barron J, Peters TM (2003) A high-resolution dynamic heart model based on averaged MRI data. In: Proceedings of medical image computing and computer-assisted intervention, vol 2878 of Lecture notes in computer science, pp 549–555

  20. Wierzbicki M, Moore J, Drangova M, Peters TM (2008) Subject-specific models for image-guided cardiac surgery. Phys Med Biol 53: 5295–5312

    Article  PubMed  Google Scholar 

  21. Linte CA, Wierzbicki M, Moore J, Little SH, Guiraudon GM, Peters TM (2007) Towards subject-specific models of the dynamic heart for mitral valve surgery. In: Proceedings of medical image computing and computer-assisted intervention, vol 4792 of Lecture notes in comput science, pp 94–101

  22. Zhu X, Papademetris X, Sinusas AJ, Duncan JS (2010) Segmentation of the left ventricle from cardiac MR images using a subject-specific dynamical model. IEEE Trans Med Imaging 29: 669–687

    Article  PubMed  Google Scholar 

  23. Wierzbicki M (2006) Subject-specific models of the heart from 4D images. PhD Dissertation, University of Western Ontario, Canada

  24. Robb RA, Hanson DP (1990) Analyze: a software system for biomedical image analysis. In: First conference on visualization in biomedical computing, pp 507–518

  25. Rettmann ME, Holmes III DR, Camp JJ, Packer DL, Robb RA (2008) Validation of semi-automatic segmentation of the left atrium. In: Proceedings of SPIE medical imaging symposium: physiology, function and structure from medical images, vol 6916, pp 691625–1–7

  26. Dice L (1945) Measures of the amount of ecologic association between species. Ecology 26: 297–302

    Article  Google Scholar 

  27. Wiles AD, Thompson DG, Frantz DD (2004) Accuracy assessment and interpretation for optical tracking systems. In: Proceedings of SPIE medical imaging 2007: visualization, image-guided procedures and display, vol 5367, pp 421–432

  28. Birkfellner W, Watzinger F, Wanschitz F, Ewers R, Bergmann H (1998) Calibration of tracking systems in a surgical environment. IEEE Trans Med Imaging 17: 737–742

    Article  PubMed  CAS  Google Scholar 

  29. Frantz DD, Wiles AD, Leis SE, Kirsch SR (2003) Accuracy assessment protocols for electromagnetic tracking systems. Phys Med Biol 48: 2241–2251

    Article  PubMed  CAS  Google Scholar 

  30. Hummel JB, Bax MR, Figl ML, Kang Y, Maurer C Jr., Birkfellner WW, Bergmann H, Shahidi R (2005) Design and application of an assessment protocol for electromagnetic tracking systems. Med Phys 32: 2371–2379

    Article  PubMed  Google Scholar 

  31. Nafis C, Jensen V, Beauregard L, Anderson P (2006) Method for estimating dynamic EM tracking accuracy of surgical navigation tools. In: Proceedings of SPIE medical imaging 2006: visualization and image-guided procedures, vol 6141, pp 61410K–16

  32. Wiles AD, Linte CA, Moore J, Wedlake C, Peters TM (2008) Object identification accuracy under ultrasound enhanced virtual reality for minimally invasive cardiac surgery. In: Proceedings of SPIE medical imaging 2008: visualization, image-guided procedures and modeling, vol 6918, pp 69180E1–12

  33. Kwartowitz DM, Rettmann ME, Holmes III DR, Robb RA (2010) A novel technique for analysis of accuracy of magnetic tracking systems used in image-guided surgery. In: SPIE medical imaging symposium: visualization, image-guided procedures and modeling, vol 7625, pp 76251L–1–8

  34. Lang P, Seslija P, Habets D, Chu MWA, Holdsworth DW, Peters TM (2010) Three-dimensional ultrasound probe pose estimation from single-perspective x-ray images for image-guided interventions. In: Proceedings of medical imaging and augmented reality, vol 6326 of Lecture notes in computer science, pp 344–352

  35. Gobbi DG, Comeau RM, Peters TM (1999) Ultrasound probe tracking for real-time ultrasound/MRI overlay and visualization of brain shift. In: Proceedings of medical image computing and computer-assisted intervention, vol 1679 of Lecture notes in computer science, pp 920–927

  36. Lang P, Seslija P, Bainbridge D, Guiraudon GM, Jones DL, Chu MW, Holdsworth DW, Peters TM (2011) Accuracy assessment of fluoroscopy-transesophageal echocardiography registration. In: Proceedings of SPIE medical imaging: visualization, image-guided procedures, and modeling, vol 7964, pp 79641Y–8

  37. Linte CA, Moore J, Wedlake C, Bainbridge D, Guitaudon GM, Jones DL, Peters TM (2009) Inside the beating heart: an in vivo feasibility study on fusing pre- and intra-operative imaging for minimally invasive therapy. Int J CARS 4: 113–122

    Article  Google Scholar 

  38. Lang P, Chen E, Guiraudon GM, Jones DL, Bainbridge D, Chu MW, Drangove M, Hata N, Jain A, Peters TM (2011) Feature-based US to CT registration of the aortic root. In: Proceedings of SPIE medical imaging: visualization, image-guided procedures, and modeling, vol 7964, pp 79641G–8

  39. Su Y, Holmes III DR, Rettmann ME, Robb RA (2006) A piecewise function-to-structural registration algorithm for image-guided cardiac ablation. In: SPIE medical imaging 2006: visualization and image-guided procedures, vol 6141, pp 614117–1–7

  40. Rettmann ME, Holmes III DR, Dalegrave C, Stanton CM, Johnson SB, Packer DL, Robb RA (2009) A combined surface and volume-based approach for registration of patient specific models into left atrial cardiac ablation procedures. In: IEEE international symposium on biomedical imaging (ISBI), pp 1087–90

  41. Linte CA, Moore J, Wedlake CMPT (2010) Evaluation of model-enhanced ultrasound-assisted interventional guidance in a cardiac phantom. IEEE Trans Biomed Eng 57: 2209–2218

    Article  PubMed  Google Scholar 

  42. Ma YL, Rhode K, King AP, Cauldfield D, Cooklin M, Razavi R, Penney GP (2009) Echocardiography to magnetic resonance image registration for use in image-guide electrophysiology procedures. In: Proceedings of SPIE medical imaging 2009: visualization, image-guided procedures and modeling, vol 7261, pp 72610Q–8

  43. Linte CA, Moore J, Wiles AD, Wedlake C, Peters TM (2009) Targeting accuracy under model-to-subject misalignments in model-guided cardiac surgery. In: Proceedings of medical image computing and computer-assisted intervention, vol 5761 of Lecture notes in computer science, pp 361–368

  44. Rettmann ME, Holmes III DR, Cameron BM, Robb RA (2007) Interactive visualization of cardiac anatomy in catheter-based ablation therapy. In: MICCAI 2008 workshop on interaction in medical image analysis

  45. Holmes III DR, Rettmann M, Cameron B, Camp J, Robb R (2008) Developing patient-specific anatomic models for validation of cardiac ablation guidance procedures. In: Proceedings of SPIE medical imaging 2008: visualization, image-guided procedures and modeling, vol 6918, pp 69181W–8

  46. Rettmann ME, Holmes III DR, Dalegrave C, Johnson SB, Camp JJ, Cameron BM, Packer DL, Robb RA (2008) Integration of patient-specific left atrial models for guidance in cardiac catheter ablation procedures. In: MICCAI 2008 workshop on image guidance and computer assistance for soft-tissue interventions

  47. Simpson AL, Ma B, Ellis RE, Stewart J, Miga MI (2011) Uncertainty propagation and analysis of image-guided surgery. In: Proceeings of SPIE medical imaging: visualization, image-guided procedures, and modeling, vol 7964, pp 79640H–7

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

    Article  PubMed  CAS  Google Scholar 

  49. Wiles AD, Likholyot A, Frantz DD, Peters TM (2008) A statistical model for point-based target registration error with anisotropic fiducial localizer error. IEEE Trans Med Imaging 27: 378–390

    Article  PubMed  Google Scholar 

  50. Sauer F, Vogt S, Khamene A (2008) Augmented reality. In: Peters TM, Cleary K (eds) Image-guided interventions: technology and applications. Springer, Germany, pp 81–119

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Biomedical Imaging Resource, Mayo Clinic, Rochester, MN, USA

    Cristian A. Linte, Maryam E. Rettmann, David R. Holmes III & Richard A. Robb

  2. Imaging Research Laboratories, Robarts Research Institute, University of Western Ontario, London, ON, Canada

    Pencilla Lang, Daniel S. Cho & Terry M. Peters

Authors
  1. Cristian A. Linte
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pencilla Lang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Maryam E. Rettmann
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Daniel S. Cho
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. David R. Holmes III
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Richard A. Robb
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Terry M. Peters
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Cristian A. Linte.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Linte, C.A., Lang, P., Rettmann, M.E. et al. Accuracy considerations in image-guided cardiac interventions: experience and lessons learned. Int J CARS 7, 13–25 (2012). https://doi.org/10.1007/s11548-011-0621-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11548-011-0621-1

Keywords

Search

Navigation