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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

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.

Keywords

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

Notes

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).

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)

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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

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