Skip to main content

Organ Deformation and Navigation

  • Chapter
  • First Online:
Book cover Imaging and Visualization in The Modern Operating Room

Abstract

As image-guided surgery expands beyond intracranial neurosurgery, it takes on additional challenges . Organs other than the brain lack the encompassing bone of the skull which allows them to move and deform as a result of operative pose, respiratory and cardiac motion, and tractions placed on the tissue during the interventional process. Additionally, the skull was easily accessible via a minor incision into the skin. That allowed for the implantation of rigid reference points, or fiducial markers, which allowed for easy registration of tomographic spaces and physical space. In other organs that rigid platform was not available. So both additional ways of using image information to guide procedures and techniques to account for deformation had to be developed.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Howard MA III, Dobbs MB, Simonson TM, LaVelle WE, Granner MA. A noninvasive, reattachable skull fiducial marker system. Technical note. J Neurosurg. 1995;83:372–6.

    Article  PubMed  Google Scholar 

  2. Ammirati M, Gross JD, Ammirati G, Dugan S. Comparison of registration accuracy of skin- and bone-implanted fiducials for frameless stereotaxis of the brain: a prospective study. Skull Base. 2002;12(3):125–30.

    Article  PubMed Central  PubMed  Google Scholar 

  3. Maurer CR, Fitzpatrick JM, Wang MY, Galloway RL, Maciunas RJ, Allen GS. Registration of head volume images using implantable fiducial markers. IEEE TMI. 1997;16(4):447–62.

    Google Scholar 

  4. Jacob AL, Messmer P, Kaim A, Suhm N, Regazzoni P, Baumann B. A whole-body registration-free navigation system for image-guided surgery and interventional radiology. Invest Radiol. 2000;35(5):279–88.

    Article  CAS  PubMed  Google Scholar 

  5. Boctor EM, Iordachita I, Choti MA, Hager G, Fichtinger G. Bootstrapped ultrasound calibration. Stud Health Technol Inform. 2006;119:61–6.

    PubMed  Google Scholar 

  6. Muratore DM, Galloway RL. Beam calibration without a phantom for creating a 3-D freehand ultrasound system. Ultrasound Med Biol. 2001;27(11):1557–66.

    Article  CAS  PubMed  Google Scholar 

  7. Brandenberger D, Birkfellner W, Baumann B, et al. Positioning accuracy in a registration-free CT-based navigation system. Phys Med Biol. 2007;52:7073–86.

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  9. Wiles AD, Likholyot A, Frantz DD, Peters TM. A statistical model for point-based target registration error with anisotropic fiducial localizer error. IEEE TMI. 2008;27(3):378–90.

    Google Scholar 

  10. Fitzpatrick JM, West JB. The distribution of target registration error in rigid-body point-based registration. IEEE Trans Med Imaging. 2001;20(9):917–27.

    Article  CAS  PubMed  Google Scholar 

  11. Herline AJ, Herring JL, Stefansic JD, Chapman WC, Galloway RL Jr, Dawant BM. Surface registration for use in interactive, image-guided liver surgery. Comput Aided Surg. 2000;5(1):11–7.

    CAS  PubMed  Google Scholar 

  12. Nolte LP, Zamorano LJ, Jiang Z, Wang Q, Langlotz F, Berlemann U. Image-guided insertion of transpedicular screws: a laboratory set-up. Spine. 1995;20:497–500.

    Article  CAS  PubMed  Google Scholar 

  13. Lange T, Papenberg N, Heldmann S, et al. 3D ultrasound-CT registration of the liver using combined landmark-intensity information. Int J Comput Assist Radiol Surg. 2009;4(1):79–88.

    Article  PubMed  Google Scholar 

  14. Porter BC, Rubens DJ, Strang JG, Smith J, et al. Three-dimensional registration and fusion of ultrasound and MRI using major vessels as fiducial markers. IEEE TMI. 2001;20(4):354–9.

    CAS  Google Scholar 

  15. Maurer CR, Maciunas RJ, Fitzpatrick JM. Registration of head CT images to physical space using a weighted combination of points and surfaces [image-guided surgery]. IEEE-TMI. 1998;17(5):753–61.

    Google Scholar 

  16. Pelizzari CA, Chen GTY, Spelbring DR, Weischelbaum RR, Chen CT. Accurate three-dimensional registration of CT, PET and/or MR images of the brain. JCAT. 1989;13(1):20–6.

    CAS  Google Scholar 

  17. Besl PJ, McKay ND. A method for registration of 3D shape. IEEE-Trans PAMI. 1992;14(2):239–57.

    Article  Google Scholar 

  18. Herline AJ, Stefansic JD, Debelak JP, Hartmann SL, et al. Image-guided surgery preliminary feasibility studies of frameless stereotactic liver surgery. JAMA Surg. 1999;134(6):644–50.

    CAS  Google Scholar 

  19. Kwartowitz DM, Herrell SD, Galloway RL. Update: toward image-guided robotic surgery: determining the intrinsic accuracy of the daVinci-S robot. Int J Comput Assist Radiol Surg. 2007;1(5):301–4.

    Article  Google Scholar 

  20. Herrell SD, Kwartowitz DM, Milhoua PM, Galloway RL. Towards image guided robotic surgery: system validation. J Urol. 2009;181(2):783–9. Discussion 789–90.

    Article  PubMed  Google Scholar 

  21. Ong RE, Glisson C, Altamar H, Viprakasit D, et al. Intraprocedural registration for image-guided kidney surgery. IEEE/ASME Trans Mechatron. 2010;15(6):847–52.

    Article  Google Scholar 

  22. Herrell SD. The fantastic voyage: advances in robotic surgery. American Urological Society Meeting. Chicago Ill. 2011.

    Google Scholar 

  23. Cash DM, Sinha TK, Chapman WC, Terawaki H. et al. Incorporation of a laser range scanner into image-guided liver surgery: surface acquisition, registration, and tracking. Med Phys. 2003;30:1671–82.

    Article  PubMed Central  PubMed  Google Scholar 

  24. Sinha TK, Miga MI, Cash DM, Weil RJ. Intraoperative cortical surface characterization using laser range scanning: preliminary results. Neurosurgery. 2006;59(4 Suppl. 2):368–76.

    Google Scholar 

  25. Pheiffer TS, Simpson AL, Lennon B, Thompson RC, Miga MI. Design and evaluation of an optically-tracked single-CCD laser range scanner. Med Phys. 2012;39(2):636–42.

    Article  PubMed Central  PubMed  Google Scholar 

  26. Clements LW, Chapman WC, Dawant BM, Galloway RL, Miga MI. Robust surface registration using salient anatomical features for image-guided liver surgery: algorithm and validation. Med Phys. 2008;35(6):2528–40.

    Article  PubMed Central  PubMed  Google Scholar 

  27. Lathrop RA, Hackworth DM, Webster RJ 3rd. Minimally invasive holographic surface scanning for soft-tissue image registration. IEEE Trans Biomed Eng. 2010;57(6):1497–506.

    Article  PubMed Central  PubMed  Google Scholar 

  28. Burgner J, Simpson AL, Fitzpatrick JM, Lathrop RA, et al. A study on the theoretical and practical accuracy of conoscopic holography-based surface measurements: toward image registration in minimally invasive surgery. Med Robot Comput Assist Surg. 2013;9(2):190–203.

    Article  CAS  Google Scholar 

  29. Simpson AL, Burgner J, Glisson CL, Herrell SD, et al. Comparison study of contact and non-contact intraoperative surface acquisition methods for surgical navigation. IEEE Trans Biomed Eng. 2013;60(4):1090–9.

    Article  PubMed  Google Scholar 

  30. Glisson CL, Ong R, Simpson AL, Clark P, et al. The use of virtual fiducials in image-guided kidney surgery. Proc SPIE Med Imaging. 2011:7964(2). doi:10.1117/12.877092.

    Google Scholar 

  31. Kwoh YS, Hou J, Jonckheere EA, Hayati S. A robot with improved absolute positioning accuracy for CT guided stereotactic brain surgery. IEEE Trans Biomed Eng. 1988;35:153–60.

    Article  CAS  PubMed  Google Scholar 

  32. Roberts DW, Strohbehn JW, Hatch JF, Murray W, Kettenberger H. A frameless stereotaxic integration of computerized tomographic imaging and the operating microscope. J Neurosurg. 1986;65:545–9.

    Article  CAS  PubMed  Google Scholar 

  33. Watanabe E, Watanabe T, Manaka S, Mayanagi Y, Takakura K. Three-dimensional digitizer (neuronavigator): new equipment for computed tomography-guided stereotaxic surgery. Surg Neurol. 1987;27:543–7.

    Article  CAS  PubMed  Google Scholar 

  34. Kelly PJ, Kall B, Goerss S, Earnest FI. Computer-assisted stereotaxic laser resection of intra-axial brain neoplasms. J Neurosurg. 1986;64:427–39.

    Article  CAS  PubMed  Google Scholar 

  35. Nauta HJ. Error assessment during “image guided” and “imaging interactive” stereotactic surgery. Comput Med Imaging Graph. 1994;18:279–87.

    Article  CAS  PubMed  Google Scholar 

  36. Roberts DW, Hartov A, Kennedy FE, Miga MI, Paulsen KD. Intraoperative brain shift and deformation: a quantitative analysis of cortical displacement in 28 cases. Neurosurgery. 1998;43:749–58.

    Article  CAS  PubMed  Google Scholar 

  37. Hill DLG, Mauer CR, Maciunas RJ, Barwise JA, Fitzpatric JM, Wang MY. Measurement of intraoperative brain surface deformation under a craniotomy. Neurosurgery. 1998;43:514–26.

    Article  CAS  PubMed  Google Scholar 

  38. Nabavi A, Black PM, Gering DT, Westin CF, et al. Serial intraoperative magnetic resonance imaging of brain shift. Neurosurgery. 2001;48:787–97.

    CAS  PubMed  Google Scholar 

  39. Nimsky C, Ganslandt O, Cerny S, Hastreiter P, Greiner G, Fahlbusch R. Quantification of, visualization of, and compensation for brain shift using intraoperative magnetic resonance imaging. Neurosurgery. 2000;47:1070–9.

    Article  CAS  PubMed  Google Scholar 

  40. Bucholz RD, Yeh DD, Trobaugh J, McDurmont LL, et al. The correction of stereotactic inaccuracy caused by brain shift using an intraoperative ultrasound device. Cvrmed-Mrcas’97. 1997;1205:459–66.

    Article  Google Scholar 

  41. Hartkens T, Hill DLG, Castellano-Smith AD, Hawkes DJ, et al. Measurement and analysis of brain deformation during neurosurgery. IEEE Trans Med Imaging. 2003;22:82–92.

    Article  CAS  PubMed  Google Scholar 

  42. Sillay KA, Kumbier LM, Ross C, Brady M, et al. Perioperative brain shift and deep brain stimulating electrode deformation analysis: implications for rigid and non-rigid devices. Ann Biomed Eng. 2013;41:293–304.

    Article  PubMed  Google Scholar 

  43. Hall WA. Convection-enhanced delivery: neurosurgical issues. Curr Drug Targets. 2009;10:126–30.

    Article  CAS  PubMed  Google Scholar 

  44. Heizmann O, Zidowitz S, Bourquain H, Potthast S, et al. Assessment of intraoperative liver deformation during hepatic resection: prospective clinical study. World J Surg. 2010;34:1887–93.

    Article  PubMed  Google Scholar 

  45. Schulz C, Waldeck S, Mauer UM. Intraoperative image guidance in neurosurgery: development, current indications, and future trends. Radiol Res Pract. 2012;197364.

    Google Scholar 

  46. Lunsford LD, Martinez AJ. Stereotactic exploration of the brain in the era of computed tomography. Surg Neurol. 1984;22:222–30.

    Article  CAS  PubMed  Google Scholar 

  47. King E, Daly MJ, Chan H, Bachar G, et al. Intraoperative cone-beam CT for head and neck surgery: Feasibility of clinical implementation using a prototype mobile C-arm. Head Neck. 2013;35:959–67.

    Article  PubMed  Google Scholar 

  48. Ohue S, Kumon Y, Nagato S, Kohno S, et al. Evaluation of intraoperative brain shift using an ultrasound-linked navigation system for brain tumor surgery. Neurol Med Chir. 2010;50:291–9.

    Article  Google Scholar 

  49. Abbott JD, Huang Y, Liu D, Hickey R, Krause DS, Giordano FJ. Stromal cell-derived factor-1alpha plays a critical role in stem cell recruitment to the heart after myocardial infarction but is not sufficient to induce homing in the absence of injury. Circulation. 2004;110:3300–5.

    Article  PubMed  Google Scholar 

  50. Ahmed M, Douek M. Intra-operative ultrasound versus wire-guided localization in the surgical management of non-palpable breast cancers: systematic review and meta-analysis. Breast Cancer Res Treat. 2013;140:435–46.

    Article  CAS  PubMed  Google Scholar 

  51. Haid A, Knauer M, Dunzinger S, Jasarevic Z, Koeberle-Wuehrer R. Intra-operative sonography: a valuable aid during breast-conserving surgery for occult breast cancer. Ann Surg Oncol. 2007;14:3090–101.

    Article  PubMed  Google Scholar 

  52. Pan H, Wu N, Ding H, Ding Q, et al. Intraoperative ultrasound guidance is associated with clear lumpectomy margins for breast cancer: a systematic review and meta-analysis. Plos One. 2013;8(9):e74028.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  53. Roberts DW, Miga MI, Hartov A, Eisner S, et al. Intraoperatively updated neuroimaging using brain modeling and sparse data. Neurosurgery. 1999;45:1199–206.

    Article  CAS  PubMed  Google Scholar 

  54. Miga MI, Dumpuri P, Simpson AL, Weis JA, Jarnagin WR. The sparse data extrapolation problem: strategies for soft-tissue correction for image-guided liver surgery, presented at the medical imaging 2011: visualization, image-guided procedures, and modeling conference, Orlando, 2011.

    Google Scholar 

  55. Miga MI, Roberts DW, Hartov A, Eisner S, et al. Updated neuroimaging using intraoperative brain modeling and sparse data. Stereotact Funct Neurosurg. 1999;72:103–6.

    Article  CAS  PubMed  Google Scholar 

  56. Kumar AN, Pheiffer TS, Simpson AL, Thompson RC, Miga MI, Dawant BM. Phantom-based comparison of the accuracy of point clouds extracted from stereo cameras and laser range scanner, presented at the medical imaging 2013: image-guided procedures, robotic interventions, and modeling, Orlando, 2013.

    Google Scholar 

  57. Skrinjar O, Nabavi A, Duncan JS. A Stereo-guided biomechanical model for volumetric deformation analysis, IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, 2001.

    Google Scholar 

  58. Sun H, Lunn KE, Farid H, Wu Z, et al. Stereopsis-guided brain shift compensation. IEEE Trans Med Imaging. 2005;24:1039–52.

    Article  PubMed  Google Scholar 

  59. Paul P, Morandi X, Jannin PA. Surface registration method for quantification of intraoperative brain deformations in image-guided neurosurgery. IEEE Trans Inf Technol Biomed. 2009;13:976–83.

    Article  PubMed  Google Scholar 

  60. Cash DM, Sinha TK, Chapman WC, Galloway RL, Miga MI. Fast, accurate surface acquisition using a laser range scanner for image-guided liver surgery, medical imaging 2002: visualization, display, and image-guided procedures: Proc. of the SPIE 2002, 4681, 100–110.

    Google Scholar 

  61. Clements LW, Dumpuri P, Chapman WC, Dawant BM, Galloway RL, Miga MI. Organ surface deformation measurement and analysis in open hepatic surgery: method and preliminary results from 12 clinical cases. IEEE Trans Biomed Eng. 2011;58(8):2280–9.

    Article  Google Scholar 

  62. Altamar HO, Ong RE, Glisson CL, Viprakasit DP, et al. Kidney deformation and intraprocedural registration: a study of elements of image-guided kidney surgery. J Endourol. 2011;25:511–7.

    Article  PubMed  Google Scholar 

  63. Conley RH, Meszoely I, Pheiffer TS, Weis JA, Yankeelov TE, Miga MI. Image to physical space registration of supine MRI for image guided breast surgery, presented at the SPIE medical imaging 2014: image-guided procedures, robotic interventions, and modeling conference, San Diego.

    Google Scholar 

  64. Dumpuri P, Thompson RC, Sinha TK, Miga MI. Automated brain shift correction using a pre-computed deformation atlas. Proc SPIE Med Imaging. 2006; 614.1–8.

    Google Scholar 

  65. DeLorenzo C, Papademetris X, Staib LH, Vives KP, Spencer DD, Duncan JS. Image-guided intraoperative cortical deformation recovery using game theory: application to neocortical epilepsy surgery. IEEE Trans Med Imaging. 2010;29:322–38.

    Article  PubMed Central  PubMed  Google Scholar 

  66. Lunn KE, Paulsen KD, Liu FH, Kennedy FE, Hartov A, Roberts DW. Data-guided brain deformation modeling: evaluation of a 3-D adjoint inversion method in porcine studies. IEEE Trans Biomed Eng. 2006;53:1893–900.

    Article  PubMed  Google Scholar 

  67. Sun K, Pheiffer TS, Simpson AL, Weis JA, Thompson RC, Miga MI. Real-time computer assisted surgery for brain shift correction using biomechanical models. IEEE J Transl Eng Health Med. 2013 (Accepted).

    Google Scholar 

  68. Lange T, Wenckebach TH, Lamecker H, Seebass M, et al. Registration of portal and hepatic venous phase of MR/CT data for computer-assisted liver surgery planning. Comput Assist Radiol Surg. 2005;1281:768–72.

    Google Scholar 

  69. Lange T, Wenckebach TH, Lamecker H, Seebass M, et al. Registration of different phases of contrast-enhanced CT/MRI data for computer-assisted liver surgery planning: evaluation of state-of-the-art methods. Int J Med Robot Comput Assist Surg. 2005;1:6–20.

    Article  CAS  Google Scholar 

  70. Cash DM, Miga MI, Sinha TK, Galloway RL, Chapman WC. Compensating for intraoperative soft-tissue deformations using incomplete surface data and finite elements. IEEE Trans Med Imaging. 2005;24:1479–91.

    Article  PubMed  Google Scholar 

  71. Clements LW, Dumpiri P, Chapman WC, Galloway RL Jr, Miga MI. Atlas-based method for model updating in image-guided liver surgery, in SPIE medical imaging 2007: visualization, image-guided procedures, and modeling, San Diego, 2007.

    Google Scholar 

  72. Dumpuri P, Clements LW, Dawant BM, Miga MI. Model-updated image-guided liver surgery: preliminary results using surface characterization. Prog Biophys Mol Biol. 2010;103:197–207.

    Article  PubMed  Google Scholar 

  73. Rucker DC, Wu YF, Clements LW, Ondrake JE, et al. A mechanics-based nonrigid registration method for liver surgery using sparse intraoperative data. IEEE Trans Med Imaging. 2014;33:147–58.

    Article  PubMed Central  PubMed  Google Scholar 

  74. Acerbi F, Broggi M, Eoli M, Anghileri E, et al. Is fluorescein-guided technique able to help in resection of high-grade gliomas? Neurosurg Focus. 2014;36:E5.

    Article  PubMed  Google Scholar 

  75. Valdes PA, Kim A, Leblond F, Conde OM, et al. Combined fluorescence and reflectance spectroscopy for in vivo quantification of cancer biomarkers in low- and high-grade glioma surgery. J Biomed Optics. 2011;16:116007.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Robert L. Galloway Jr. PhD .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer Science+Business Media New York

About this chapter

Cite this chapter

Galloway, R., Miga, M. (2015). Organ Deformation and Navigation. In: Fong, Y., Giulianotti, P., Lewis, J., Groot Koerkamp, B., Reiner, T. (eds) Imaging and Visualization in The Modern Operating Room. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2326-7_9

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-2326-7_9

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4939-2325-0

  • Online ISBN: 978-1-4939-2326-7

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics