Brain shift in neuronavigation of brain tumors: A review

doi:10.1016/j.media.2016.08.007

Medical Image Analysis

Volume 35, January 2017, Pages 403-420

https://doi.org/10.1016/j.media.2016.08.007 Get rights and content

Highlights

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A comprehensive review of research on the phenomenon of brain shift.
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A new taxonomy separating brain shift into physical, biological and surgical factors.
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Contrast between brain shift corrections through intraoperative imaging methods.
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Recommendations for future focus of brain shift research.

Abstract

Purpose: Neuronavigation based on preoperative imaging data is a ubiquitous tool for image guidance in neurosurgery. However, it is rendered unreliable when brain shift invalidates the patient-to-image registration. Many investigators have tried to explain, quantify, and compensate for this phenomenon to allow extended use of neuronavigation systems for the duration of surgery. The purpose of this paper is to present an overview of the work that has been done investigating brain shift.

Methods: A review of the literature dealing with the explanation, quantification and compensation of brain shift is presented. The review is based on a systematic search using relevant keywords and phrases in PubMed. The review is organized based on a developed taxonomy that classifies brain shift as occurring due to physical, surgical or biological factors.

Results: This paper gives an overview of the work investigating, quantifying, and compensating for brain shift in neuronavigation while describing the successes, setbacks, and additional needs in the field. An analysis of the literature demonstrates a high variability in the methods used to quantify brain shift as well as a wide range in the measured magnitude of the brain shift, depending on the specifics of the intervention. The analysis indicates the need for additional research to be done in quantifying independent effects of brain shift in order for some of the state of the art compensation methods to become useful.

Conclusion: This review allows for a thorough understanding of the work investigating brain shift and introduces the needs for future avenues of investigation of the phenomenon.

Graphical abstract

Section snippets

Introduction

Since the introduction of the first intraoperative frameless stereotactic navigation device by Roberts et al. (1986), image guided neurosurgery (IGNS), or ``neuronavigation'' has become an essential tool for many neurosurgical procedures due to its ability to minimize surgical trauma by enabling precise localization of surgical targets. Over the past 30 years, the growth of this technology has enabled application to increasingly complicated interventions including the surgical treatment of

Search methodology

The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2009 guidelines without prior publication of the review protocol (Moher et al., 2009). PubMed² was used to search several specific keywords and phrases:

(brain or tissue) and (shift or deformation) or (modeling or predicti^* or registration) or (measure^* or quantif^*) or (intraoperative or imag^*) or (9euronavigation accuracy)

All returned titles were screened and

Causes of brain shift

The first article to report on the phenomenon of brain shift was published in 1986 by Kelly et al. (1986), just prior to the release of the first frameless stereotaxic system developed by Roberts et al. (1986). Kelly et al. (1986) observed a dislocation of small steel balls placed along the line of view of the surgeon during volumetric stereotaxy. While they documented observing the shift, at that time there was no equipment available to perform any extensive quantitative measurements of the

Measurement of brain shift

As the use of 15euronavigation became more prevalent and widespread in neurosurgical interventions, the need for measuring the origins of inaccuracies caused by brain shift also became important. With the effects of brain shift making 15euronavigation systems unreliable for a large part of surgery, many investigators developed techniques to measure the subsequent shifts while attempting to attribute their cause. In order to assess the magnitude of brain shift there have been two main

Compensation of brain shift

When discussing methods for compensating for the effects of brain shift in neuronavigation we find two main streams in the literature; methods that focus on the registration of intraoperative images and methods where intraoperative information is sparse or absent and thus the focus on modeling the shift through biomechanical or predictive models. In many of the different methods a combination of approaches are used and each has different benefits and drawbacks. Registration methods obviously

Discussion

It is evident from the work described above that brain shift is a very complex problem that has widespread causes ranging from the limitations of the technical components of the neuronavigation hardware, surgical causes from equipment resection of tissue and loss of fluid, as well as biological effects related to drug administration and the type of brain tumor present. The work done to describe the contributions from these different factors has led to numerous strategies to quantify the

Conclusion

We presented a review of the research evaluating the causes, measurements and correction methods of brain shift in neuronavigation with a newly proposed taxonomy for classifying the different types of studies. With the increasingly ubiquitous use of neuronavigation systems in neurosurgical interventions, the need for highly accurate information has become of utmost importance. Brain shift is a well-documented phenomenon and one of the largest contributors to inaccurate neuronavigation. While

Disclosure of funding

This work was funded in part by NSERC (238739) and CIHR (MOP-97820) and an NSERC CHRP (385864-10) and a Brain Canada Student Fellowship.

Conflict of interest

All authors declare they have no conflict of interest.

Acknowledgments

We acknowledge funding support from Canadian Institutes of Health Research (MOP-84360 and MOP-111169), the Canadian National Science and Engineering Research Council (238739), and Brain Canada.

Ian J. Gerard, M.Sc. is a Ph.D. candidate in biomedical engineering at McGill University. His current research involves improving the accuracy of neuronavigation tools for image-guided neurosurgery of brain tumors with focus on intraoperative imaging for brain shift management and enhanced visualization techniques for understanding complex medical imaging data.

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Kevin Petrecca, M.D. Ph.D. is a neurosurgeon, assistant professor of neurology and neurosurgery at McGill University, and head of neurosurgery at the Montreal Neurological Hospital, specializing in neurosurgical oncology. His research at the Montreal Neurological Institute and Hospital Brain Tumor Research Center focuses on understanding fundamental molecular mechanisms that regulate cell motility with a focus on malignant glial cell invasion. His clinical research program focuses on developing intraoperative tools to improve brain cancer surgery including MRI-coregistered ultrasound and spectroscopy-guided surgery.

Denis Sirhan, M.D. is a neurosurgeon at the Montreal Neurological Institute and Hospital who specializes in skullbase approaches for complex tumors. He has wide experience in microvascular decompressions for different pathologies. His current research, in collaboration with other MNI clinician-scientists, involves the development of augmented reality visualizations in neuronavigation systems during image-guided tumor and vascular surgeries.

Jeffery A. Hall, M.D. M.Sc. is a neurosurgeon and assistant professor of neurology and neurosurgery at McGill University's Montreal Neurological Institute and Hospital, specializing in the surgical treatment of epilepsy and cancer. His current research, in collaboration with other MNI clinician-scientists includes: developing non-invasive means of delineating epileptic foci, intraoperative imaging in combination with neuronavigation systems and the application of image-guided neuronavigation to epilepsy surgery.

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Survey PaperBrain shift in neuronavigation of brain tumors: A review

Highlights

Abstract

Graphical abstract

Section snippets

Introduction

Search methodology

Causes of brain shift

Measurement of brain shift

Compensation of brain shift

Discussion

Conclusion

Disclosure of funding

Conflict of interest

Acknowledgments

Neuroimage

Surg. Neurol.

Neuroimage

Neuroimage

Neuroimage

Med. Image Anal.

Parkinsonism Relat. Disord

Med. Image. Anal.

Med. Image. Anal.

Med. Image Anal.

Med. Image Anal.

Magn. Reson. Imag.

Neuroimage

Comput. Methods Appl. Mech. Eng.

J. Mech. Behav. Biomed. Mater

Magn. Reson. Imag.

Med. Image Anal.

Med. Image Anal.

Ultrasound Med. Biol.

Ultrasound Med. Biol.

Image-guided microneurosurgical management of small arteriovenous malformation: role of neuronavigation and intraoperative Doppler sonography

Min. Invasive. Neurosurg.

In-silico oncology: an approximate model of brain tumor mass effect based on directly manipulated free form deformation

Int. J. Comput. Assist. Radiol. Surg.

Automatic trajectory planning of DBS neurosurgery from multi-modal MRI datasets

Med. Image Comput. Comput. Assist. Interv.

Neuronavigation using susceptibility-weighted venography: application to deep brain stimulation and comparison with gadolinium contrast

J. Neurosurg.

Towards computer-assisted deep brain stimulation targeting with multiple active contacts

Med. Image Comput. Comput. Assist. Interv.

An experimental approach to image guided skull base surgery employing a microscope-based neuronavigation system

Acta Neurochir. (Wien)

The correction of stereotactic inaccuracy caused by brain shift using an intraoperative ultrasound device

Framework for a low-cost intra-operative image-guided neuronavigator including brain shift compensation

Conf. Proc. IEEE Eng. Med. Biol. Soc.

Laser range scanning for image-guided neurosurgery: Investigation of image-to-physical space registrations

Med. Phys.

Reliability of neuronavigation-assisted trans-sphenoidal tumor resections

Neurol. Res.

Neuronavigation applied to epilepsy monitoring with subdural electrodes

Neurosurg. Focus

Intraoperative brain shift compensation: accounting for dural septa

IEEE Trans. Biom. Eng.

Integrating retraction modeling into an atlas-based framework for brain shift prediction

IEEE Trans. Biomed. Eng.

Evaluation of an ultrasonic echo-tracking method for measurements of arterial wall movements in two dimensions

IEEE Trans. Ultrason. Ferroelectr. Freq. Control

Robust nonrigid registration to capture brain shift from intraoperative MRI

IEEE Trans. Med. Imag.

Minimizing brain shift during functional neurosurgical procedures - a simple burr hole technique that can decrease CSF loss and intracranial air

Cent. Eur. Neurosurg.

Three-dimensional visualization of the pyramidal tract in a neuronavigation system during brain tumor surgery: first experiences and technical note

Neurosurgery

Intraoperative ultrasound for guidance and tissue shift correction in image-guided neurosurgery

Med. Phys.

Combining pyramidal tract mapping, microscopic-based neuronavigation, and intraoperative magnetic resonance imaging improves outcome of epilepsy foci resection in the sensorimotor cortex

Turk Neurosurg.

Volumetric intraoperative brain deformation compensation: model development and phantom validation

IEEE Trans. Med. Imag.

Estimation of intra-operative brain shift using a tracked laser range scanner

Conf. Proc. IEEE Eng. Med. Biol. Soc.

Postimaging brain distortion: magnitude, correlates, and impact on neuronavigation

J. Neurosurg.

Real-time geometric distortion correction for interventional imaging with echo-planar imaging (EPI)

Magn. Reson. Med.

Survey Paper
Brain shift in neuronavigation of brain tumors: A review