Skip to main content

Advertisement

Log in

3D intra-operative ultrasound and MR image guidance: pursuing an ultrasound-based management of brainshift to enhance neuronavigation

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

Abstract

Background

Brainshift is still a major issue in neuronavigation. Incorporating intra-operative ultrasound (iUS) with advanced registration algorithms within the surgical workflow is regarded as a promising approach for a better understanding and management of brainshift. This work is intended to (1) provide three-dimensional (3D) ultrasound reconstructions specifically for brain imaging in order to detect brainshift observed intra-operatively, (2) evaluate a novel iterative intra-operative ultrasound-based deformation correction framework, and (3) validate the performance of the proposed image-registration-based deformation estimation in a clinical environment.

Methods

Eight patients with brain tumors undergoing surgical resection are enrolled in this study. For each patient, a 3D freehand iUS system is employed in combination with an intra-operative navigation (iNav) system, and intra-operative ultrasound data are acquired at three timepoints during surgery. On this foundation, we present a novel resolution-preserving 3D ultrasound reconstruction, as well as a framework to detect brainshift through iterative registration of iUS images. To validate the system, the target registration error (TRE) is evaluated for each patient, and both rigid and elastic registration algorithms are analyzed.

Results

The mean TRE based on 3D-iUS improves significantly using the proposed brainshift compensation compared to neuronavigation (iNav) before (2.7 vs. 5.9 mm; \(p=0.001\)) and after dural opening (4.2 vs. 6.2 mm, \(p=0.049\)), but not after resection (6.7 vs. 7.5 mm; \(p=0.426\)). iUS depicts a significant (\(p=0.001\)) dynamic spatial brainshift throughout the three timepoints. Accuracy of registration can be improved through rigid and elastic registrations by 29.2 and 33.3%, respectively, after dural opening, and by 5.2 and 0.4%, after resection.

Conclusion

3D-iUS systems can improve the detection of brainshift and significantly increase the accuracy of the navigation in a real scenario. 3D-iUS can thus be regarded as a robust, reliable, and feasible technology to enhance neuronavigation.

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

Access this article

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Notes

  1. http://openigtlink.org/.

References

  1. Bal J, Camp S, Nandi D (2016) The use of ultrasound in intracranial tumor surgery. Acta Neurochir 158(6):1179–1185

    Article  PubMed  Google Scholar 

  2. Barone DG, Lawrie TA, Hart MG (2014) Image guided surgery for the resection of brain tumours. Cochrane Database Syst Rev (1):CD009685. doi:10.1002/14651858.CD009685.pub2

  3. Bucholz RD, Yeh DD, Trobaugh J, McDurmont LL, Sturm CD, Baumann C, Henderson JM, Levy A, Kessman P (1997) The correction of stereotactic inaccuracy caused by brain shift using an intraoperative ultrasound device. In: CVRMed-MRCAS’97. Springer, pp 459–466

  4. Chen SJS, Reinertsen I, Coupé P, Yan CX, Mercier L, Del Maestro DR, Collins DL (2012) Validation of a hybrid Doppler ultrasound vessel-based registration algorithm for neurosurgery. Int J Comput Assist Radiol Surg 7(5):667–685

    Article  PubMed  PubMed Central  Google Scholar 

  5. Claus EB, Horlacher A, Hsu L, Schwartz RB, Dello-Iacono D, Talos F, Jolesz FA, Black PM (2005) Survival rates in patients with low-grade glioma after intraoperative magnetic resonance image guidance. Cancer 103(6):1227–1233

    Article  PubMed  Google Scholar 

  6. Coburger J, König RW, Scheuerle A, Engelke J, Hlavac M, Thal DR, Wirtz CR (2014) Navigated high frequency ultrasound: description of technique and clinical comparison with conventional intracranial ultrasound. World Neurosurg 82(3):366–375

    Article  PubMed  Google Scholar 

  7. Coenen VA, Krings T, Weidemann J, Hans FJ, Reinacher P, Gilsbach JM, Rohde V (2005) Sequential visualization of brain and fiber tract deformation during intracranial surgery with three-dimensional ultrasound: an approach to evaluate the effect of brain shift. Oper Neurosurg 56(1):133–141

    Article  Google Scholar 

  8. Comeau RM, Sadikot AF, Fenster A, Peters TM (2000) Intraoperative ultrasound for guidance and tissue shift correction in image-guided neurosurgery. Med Phys 27(4):787–800

    Article  CAS  PubMed  Google Scholar 

  9. De Lorenzo D, De Momi E, Conti L, Votta E, Riva M, Fava E, Bello L, Ferrigno G (2013) Intraoperative forces and moments analysis on patient head clamp during awake brain surgery. Med Biol Eng Comput 51(3):331–341

    Article  PubMed  Google Scholar 

  10. De Momi E, Ferrigno G, Bosoni G, Bassanini P, Blasi P, Casaceli G, Fuschillo D, Castana L, Cossu M, Russo GL, Cardinale F (2016) A method for the assessment of time-varying brain shift during navigated epilepsy surgery. Int J Comput Assist Radiol Surg 11(3):473–481

    Article  PubMed  Google Scholar 

  11. Fan X, Roberts DW, Ji S, Hartov A, Paulsen KD (2015) Intraoperative fiducial-less patient registration using volumetric 3D ultrasound: a prospective series of 32 neurosurgical cases. J Neurosurg 123(3):721

    Article  PubMed  PubMed Central  Google Scholar 

  12. Fuerst B, Wein W, Müller M, Navab N (2014) Automatic ultrasound-MRI registration for neurosurgery using the 2D and 3D LC 2 metric. Med Image Anal 18(8):1312–1319

    Article  PubMed  Google Scholar 

  13. Gerard IJ, Kersten-Oertel M, Petrecca K, Sirhan D, Hall JA, Collins DL (2017) Brain shift in neuronavigation of brain tumors: a review. Med Image Anal 35:403–420

    Article  PubMed  Google Scholar 

  14. Grady L (2006) Random walks for image segmentation. IEEE Trans Pattern Anal Mach Intell 28(11):1768–1783

    Article  PubMed  Google Scholar 

  15. Hartkens T, Hill DL, Castellano-Smith AD, Hawkes DJ, Maurer C, Martin AJ, Hall WA, Liu H, Truwit CL (2003) Measurement and analysis of brain deformation during neurosurgery. IEEE Trans Med Imaging 22(1):82–92

    Article  CAS  PubMed  Google Scholar 

  16. Hastreiter P, Rezk-Salama C, Soza G, Bauer M, Greiner G, Fahlbusch R, Ganslandt O, Nimsky C (2004) Strategies for brain shift evaluation. Med Image Anal 8(4):447–464

    Article  PubMed  Google Scholar 

  17. Hennersperger C, Baust M, Mateus D, Navab N (2015) Computational sonography. In: International conference on medical image computing and computer-assisted intervention. Springer, pp 459–466

  18. Hennersperger C, Karamalis A, Navab N (2014) Vascular 3D+ T freehand ultrasound using correlation of Doppler and pulse-oximetry data. In: International conference on information processing in computer-assisted interventions. Springer, pp 68–77

  19. Hill DL, Maurer CR Jr, Maciunas RJ, Barwise JA, Fitzpatrick MJ, Wang MY (1998) Measurement of intraoperative brain surface deformation under a craniotomy. Neurosurgery 43(3):514–526

    Article  CAS  PubMed  Google Scholar 

  20. Hu J, Jin X, Lee JB, Zhang L, Chaudhary V, Guthikonda M, Yang KH, King AI (2007) Intraoperative brain shift prediction using a 3D inhomogeneous patient-specific finite element model. J Neurosurg 106(1):164–169

    Article  PubMed  Google Scholar 

  21. Joldes GR, Wittek A, Miller K (2009) Computation of intra-operative brain shift using dynamic relaxation. Comput Methods Appl Mech Eng 198(41):3313–3320

    Article  PubMed  PubMed Central  Google Scholar 

  22. Karamalis A, Wein W, Klein T, Navab N (2012) Ultrasound confidence maps using random walks. Med Image Anal 16(6):1101–1112

    Article  PubMed  Google Scholar 

  23. Keles GE, Lamborn KR, Berger MS (2003) Coregistration accuracy and detection of brain shift using intraoperative sononavigation during resection of hemispheric tumors. Neurosurgery 53(3):556–564

    Article  PubMed  Google Scholar 

  24. Lasso A, Heffter T, Rankin A, Pinter C, Ungi T, Fichtinger G (2014) Plus: open-source toolkit for ultrasound-guided intervention systems. IEEE Trans Biomed Eng 61(10):2527–2537

    Article  PubMed  PubMed Central  Google Scholar 

  25. Letteboer MMJ, Willems PW, Viergever MA, Niessen WJ (2005) Brain shift estimation in image-guided neurosurgery using 3-D ultrasound. IEEE Trans Biomed Eng 52(2):268–276

    Article  PubMed  Google Scholar 

  26. Lindner D, Trantakis C, Renner C, Arnold S, Schmitgen A, Schneider J, Meixensberger J (2006) Application of intraoperative 3D ultrasound during navigated tumor resection. min-Minim Invasive Neurosurg 49(04):197–202

    Article  CAS  Google Scholar 

  27. Mahboob S, McPhillips R, Qiu Z, Jiang Y, Meggs C, Schiavone G, Button T, Desmulliez M, Demore C, Cochran S, Eljamel S (2016) Intraoperative ultrasound-guided resection of gliomas: a meta-analysis and review of the literature. World Neurosurg 92:255–263

  28. Mohammadi A, Ahmadian A, Azar AD, Sheykh AD, Amiri F, Alirezaie J (2015) Estimation of intraoperative brain shift by combination of stereovision and Doppler ultrasound: phantom and animal model study. Int J Comput Assist Radiol Surg 10(11):1753–1764

    Article  PubMed  Google Scholar 

  29. Moiyadi AV, Shetty PM, Mahajan A, Udare A, Sridhar E (2013) Usefulness of three-dimensional navigable intraoperative ultrasound in resection of brain tumors with a special emphasis on malignant gliomas. Acta Neurochir 155(12):2217–2225

    Article  PubMed  Google Scholar 

  30. Nimsky C, Ganslandt O, Cerny S, Hastreiter P, Greiner G, Fahlbusch R (2000) Quantification of, visualization of, and compensation for brain shift using intraoperative magnetic resonance imaging. Neurosurgery 47(5):1070–1080

    Article  CAS  PubMed  Google Scholar 

  31. Prada F, Del Bene M, Mattei L, Lodigiani L, DeBeni S, Kolev V, Vetrano I, Solbiati L, Sakas G, DiMeco F (2015) Preoperative magnetic resonance and intraoperative ultrasound fusion imaging for real-time neuronavigation in brain tumor surgery. Eur J Ultrasound 36(02):174–186

    CAS  Google Scholar 

  32. Prada F, Perin A, Martegani A, Aiani L, Solbiati L, Lamperti M, Casali C, Legnani F, Mattei L, Saladino A, Saini M, DiMeco F (2014) Intraoperative contrast-enhanced ultrasound for brain tumor surgery. Neurosurgery 74(5):542–552

    Article  PubMed  Google Scholar 

  33. Rasmussen IA Jr, Lindseth F, Rygh O, Berntsen E, Selbekk T, Xu J, Hernes TN, Harg E, Håberg A, Unsgaard G (2007) Functional neuronavigation combined with intra-operative 3D ultrasound: initial experiences during surgical resections close to eloquent brain areas and future directions in automatic brain shift compensation of preoperative data. Acta Neurochir 149(4):365–378

    Article  PubMed  Google Scholar 

  34. Reinges M, Nguyen HH, Krings T, Hütter BO, Rohde V, Gilsbach J (2004) Course of brain shift during microsurgical resection of supratentorial cerebral lesions: limits of conventional neuronavigation. Acta Neurochir 146(4):369–377

    Article  CAS  PubMed  Google Scholar 

  35. Riva M, Casaceli G, Castellano A, Fava E, Falini A, Bello L (2011) Beautiful eyes guiding powerful hands: the role of intraoperative imaging techniques in the surgical management of gliomas. Eur Neurol Rev 6:208–212

    Article  Google Scholar 

  36. Riva M, Fava E, Gallucci M, Comi A, Casarotti A, Alfiero T, Raneri FA, Pessina F, Bello L (2016) Monopolar high-frequency language mapping: can it help in the surgical management of gliomas? A comparative clinical study. J Neurosurg 124(5):1479–1489

    Article  PubMed  Google Scholar 

  37. Roberts DW, Hartov A, Kennedy FE, Miga MI, Paulsen KD (1998) Intraoperative brain shift and deformation: a quantitative analysis of cortical displacement in 28 cases. Neurosurgery 43(4):749–758

    Article  CAS  PubMed  Google Scholar 

  38. Rueckert D, Sonoda LI, Hayes C, Hill DL, Leach MO, Hawkes DJ (1999) Nonrigid registration using free-form deformations: application to breast MR images. IEEE Trans Med Imaging 18(8):712–721

    Article  CAS  PubMed  Google Scholar 

  39. Rygh OM, Selbekk T, Torp SH, Lydersen S, Hernes TAN, Unsgaard G (2008) Comparison of navigated 3D ultrasound findings with histopathology in subsequent phases of glioblastoma resection. Acta Neurochir 150(10):1033–1042

    Article  PubMed  Google Scholar 

  40. Selbekk T, Jakola AS, Solheim O, Johansen TF, Lindseth F, Reinertsen I, Unsgård G (2013) Ultrasound imaging in neurosurgery: approaches to minimize surgically induced image artefacts for improved resection control. Acta Neurochir 155(6):973–980

    Article  PubMed  PubMed Central  Google Scholar 

  41. Shiro O, Kumon Y, Nagato S, Kohno S, Harada H, Nakagawa K, Kikuchi K, Hitoshi M, Ohnishi T (2010) Evaluation of intraoperative brain shift using an ultrasound-linked navigation system for brain tumor surgery. Neurol Med Chir 50(4):291–300

    Article  Google Scholar 

  42. Sinha TK, Dawant BM, Duay V, Cash DM, Weil RJ, Thompson RC, Weaver KD, Miga MI (2005) A method to track cortical surface deformations using a laser range scanner. IEEE Trans Med Imaging 24(6):767–781

    Article  PubMed  Google Scholar 

  43. Stieglitz LH, Fichtner J, Andres R, Schucht P, Krähenbühl AK, Raabe A, Beck J (2013) The silent loss of neuronavigation accuracy: a systematic retrospective analysis of factors influencing the mismatch of frameless stereotactic systems in cranial neurosurgery. Neurosurgery 72(5):796–807

    Article  PubMed  Google Scholar 

  44. Tokuda J, Fischer GS, Papademetris X, Yaniv Z, Ibanez L, Cheng P, Liu H, Blevins J, Arata J, Golby AJ, Kapur T, Pieper S, Burdette EC, Fichtinger G, Tempany CM, Hata N (2009) Openigtlink: an open network protocol for image-guided therapy environment. Int J Med Robot Comput Assist Surg 5(4):423–434

    Article  Google Scholar 

  45. Unsgaard G, Rygh O, Selbekk T, Müller T, Kolstad F, Lindseth F, Hernes TN (2006) Intra-operative 3D ultrasound in neurosurgery. Acta Neurochir 148(3):235–253

    Article  CAS  PubMed  Google Scholar 

  46. Valencia A, Blas B, Ortega JH (2012) Modeling of brain shift phenomenon for different craniotomies and solid models. J Appl Math 2012:409127. doi:10.1155/2012/409127

  47. Wang MN, Song ZJ (2011) Classification and analysis of the errors in neuronavigation. Neurosurgery 68(4):1131–1143

    Article  PubMed  Google Scholar 

  48. Watanabe E, Mayanagi Y, Kosugi Y, Manaka S, Takakura K (1991) Open surgery assisted by the neuronavigator, a stereotactic, articulated, sensitive arm. Neurosurgery 28(6):792–800

    Article  CAS  PubMed  Google Scholar 

  49. Winkler D, Tittgemeyer M, Schwarz J, Preul C, Strecker K, Meixensberger J (2005) The first evaluation of brain shift during functional neurosurgery by deformation field analysis. J Neurol Neurosurg Psychiatry 76(8):1161–1163

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We would like to show our gratitude to all the staff of the operating room, in particular to Mauro Ziano, Antonietta De Rinaldis, Matteo Magistrelli, Fabrizio Calì, and Daniele Schillaci, for their timeless and precious efforts in setting up the intra-operative hardware and in performing the experiments. We appreciated the precious advices and tips Dr. D. Del Fabbro provided us on the intra-operative use of US from an experienced surgical perspective. The technical assistance received from Dr. Ing. Riccardo Ascoli and Dr. Uli Mezger from Brainlab AG were crucial to conduct this study: we do thank them for their supportive and open attitude.

Funding   This work partially received funding from the European Union’s Project Grant ACTIVE FP7-ICT-2009-6-270460 and from the European Union’s Horizon 2020 research and innovation program EDEN2020 under Grant Agreement No. 688279. M.R. is supported by the Fellowship for Abroad 2013 of the Fondazione Italiana per la Ricerca sul Cancro (FIRC).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Christoph Hennersperger.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Ethical disclosure

This article does contain studies with intra-operative human data acquisitions. Prior to acquisitions, patient consent was retrieved for each acquisition. The patients and their families are warmly acknowledged for their understanding, cooperation and support. The study was approved by the local ethical committee (Authorization No. 1299, Protocol No. 260/14, Determinants of glioma recurrence and progression).

Additional information

M. Riva and C. Hennersperger contributed equally to this work.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (mov 14599 KB)

Supplementary material 2 (mov 7608 KB)

Supplementary material 3 (mov 8752 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Riva, M., Hennersperger, C., Milletari, F. et al. 3D intra-operative ultrasound and MR image guidance: pursuing an ultrasound-based management of brainshift to enhance neuronavigation. Int J CARS 12, 1711–1725 (2017). https://doi.org/10.1007/s11548-017-1578-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11548-017-1578-5

Keywords

Navigation