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

  • Marco Riva
  • Christoph HennerspergerEmail author
  • Fausto Milletari
  • Amin Katouzian
  • Federico Pessina
  • Benjamin Gutierrez-Becker
  • Antonella Castellano
  • Nassir Navab
  • Lorenzo Bello
Original Article



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.


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.


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.


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.


Intra-operative imaging Ultrasound imaging Sonography 3D imaging Brainshift Compensation Iterative registration Clinical evaluation Brain tumor 



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).

Compliance with ethical standards

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).

Supplementary material

Supplementary material 1 (mov 14599 KB)

Supplementary material 2 (mov 7608 KB)

Supplementary material 3 (mov 8752 KB)


  1. 1.
    Bal J, Camp S, Nandi D (2016) The use of ultrasound in intracranial tumor surgery. Acta Neurochir 158(6):1179–1185CrossRefPubMedGoogle Scholar
  2. 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. 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 459–466Google Scholar
  4. 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):667–685CrossRefPubMedPubMedCentralGoogle Scholar
  5. 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):1227–1233CrossRefPubMedGoogle Scholar
  6. 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):366–375CrossRefPubMedGoogle Scholar
  7. 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):133–141CrossRefGoogle Scholar
  8. 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):787–800CrossRefPubMedGoogle Scholar
  9. 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):331–341CrossRefPubMedGoogle Scholar
  10. 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):473–481CrossRefPubMedGoogle Scholar
  11. 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):721CrossRefPubMedPubMedCentralGoogle Scholar
  12. 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):1312–1319CrossRefPubMedGoogle Scholar
  13. 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 35:403–420CrossRefPubMedGoogle Scholar
  14. 14.
    Grady L (2006) Random walks for image segmentation. IEEE Trans Pattern Anal Mach Intell 28(11):1768–1783CrossRefPubMedGoogle Scholar
  15. 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):82–92CrossRefPubMedGoogle Scholar
  16. 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):447–464CrossRefPubMedGoogle Scholar
  17. 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 459–466Google Scholar
  18. 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 68–77Google Scholar
  19. 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):514–526CrossRefPubMedGoogle Scholar
  20. 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):164–169CrossRefPubMedGoogle Scholar
  21. 21.
    Joldes GR, Wittek A, Miller K (2009) Computation of intra-operative brain shift using dynamic relaxation. Comput Methods Appl Mech Eng 198(41):3313–3320CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Karamalis A, Wein W, Klein T, Navab N (2012) Ultrasound confidence maps using random walks. Med Image Anal 16(6):1101–1112CrossRefPubMedGoogle Scholar
  23. 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):556–564CrossRefPubMedGoogle Scholar
  24. 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):2527–2537CrossRefPubMedPubMedCentralGoogle Scholar
  25. 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):268–276CrossRefPubMedGoogle Scholar
  26. 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):197–202CrossRefGoogle Scholar
  27. 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 92:255–263Google Scholar
  28. 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):1753–1764CrossRefPubMedGoogle Scholar
  29. 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):2217–2225CrossRefPubMedGoogle Scholar
  30. 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):1070–1080CrossRefPubMedGoogle Scholar
  31. 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):174–186Google Scholar
  32. 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):542–552CrossRefPubMedGoogle Scholar
  33. 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):365–378CrossRefPubMedGoogle Scholar
  34. 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):369–377CrossRefPubMedGoogle Scholar
  35. 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 6:208–212CrossRefGoogle Scholar
  36. 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):1479–1489CrossRefPubMedGoogle Scholar
  37. 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):749–758CrossRefPubMedGoogle Scholar
  38. 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):712–721CrossRefPubMedGoogle Scholar
  39. 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):1033–1042CrossRefPubMedGoogle Scholar
  40. 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):973–980CrossRefPubMedPubMedCentralGoogle Scholar
  41. 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):291–300CrossRefGoogle Scholar
  42. 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):767–781CrossRefPubMedGoogle Scholar
  43. 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):796–807CrossRefPubMedGoogle Scholar
  44. 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):423–434CrossRefGoogle Scholar
  45. 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):235–253CrossRefPubMedGoogle Scholar
  46. 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. 47.
    Wang MN, Song ZJ (2011) Classification and analysis of the errors in neuronavigation. Neurosurgery 68(4):1131–1143CrossRefPubMedGoogle Scholar
  48. 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):792–800CrossRefPubMedGoogle Scholar
  49. 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):1161–1163CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© CARS 2017

Authors and Affiliations

  • Marco Riva
    • 1
    • 2
  • Christoph Hennersperger
    • 3
    Email author
  • Fausto Milletari
    • 3
  • Amin Katouzian
    • 3
    • 4
  • Federico Pessina
    • 2
  • Benjamin Gutierrez-Becker
    • 3
    • 8
  • Antonella Castellano
    • 5
  • Nassir Navab
    • 3
    • 6
  • Lorenzo Bello
    • 2
    • 7
  1. 1.Department of Medical Biotechnology and Translational MedicineUniversità degli Studi di MilanoMilanItaly
  2. 2.Unit of Surgical Neuro-OncologyHumanitas Research HospitalRozzanoItaly
  3. 3.Computer Aided Medical Procedures (CAMP)Technische Universität MünchenGarching b. MünchenGermany
  4. 4.IBM Almaden Research CenterSan JoseUSA
  5. 5.Neuroradiology Unit and CERMAC, IRCCS San Raffaele Scientific InstituteVita-Salute San Raffaele UniversityMilanItaly
  6. 6.Computer Aided Medical Procedures (CAMP)Johns Hopkins UniversityBaltimoreUSA
  7. 7.Department of Oncology and Hemato-OncologyUniversità degli Studi di MilanoMilanItaly
  8. 8.Department of Child and Adolescent Psychiatry, Psychosomatic and PsychotherapyLudwig-Maximilian-UniversityMunichGermany

Personalised recommendations