Brain Bulging: A Personalised Model

This presentation was made at CAASE18, The Conference on Advancing Analysis & Simulation in Engineering. CAASE18 brought together the leading visionaries, developers, and practitioners of CAE-related technologies in an open forum, to share experiences, discuss relevant trends, discover common themes, and explore future issues.

Resource Abstract

The brain sits in a highly tuned environment, where the mechanical conditions are closely controlled. When this environment is altered, most commonly during trauma, stoke, infections or tumors, an increase in intracranial pressure can be life threatening. Pressure inside the skull reduces blood and oxygen supply to the brain causing further damage [1]. As a last resort neurosurgeons perform a decompressive craniectomy – cutting away part of the skull, exposing the brain to let the swelling “buldge out” thus reducing the elevated pressure [2,3]. However, this procedure leaves the brain exposed and prone to infection, while damage to the tissue during the “bulding” process may cause sever long term disabilities [4]. Understanding the correct timing for the procedure along with the location and size of the skull opening is critical to minimising long-term side effects.

Although this surgical operation has been performed since the 1900s [5], little is known about the mechanics of what happens during this process with regards to deformation, stress and strain exhibited at the edge of the skull opening.

This study of “buldging” brains illustrates how swelling-induced deformations propagate across the brain when opening the skill. In particular, studying the kinematics of how this procedure releases an elevated intracranial pressure at the expense of inducing local zones of extreme strain and stretch. This work builds on a mathematical model (a continuum model where swelling brain tissue is modelled as an elastically incompressible Moony Rivlin solid) [6], and uses a personalised head model generated from MRI for finite element simulations. The study covers craniectomy under different conditions by varying swelling area, skull opening size and skull opening location. The displacement, deformation, radial and tangential stretches and maximum principle strains are reported.

Though systematic simulation the common features and trends were identified. In all cases, a unified stretch pattern is shown. This includes three extreme stretch regions:
• a tensile zone deep within the buldge,
• a highly localised compressive zone around the opening,
• a shear zone around the opening.
This means region 1, deep within the buldge, is most vulnerable to damage by stretching the axons. Axons are also known as “nerve fibres”, and are the long thin part of the nerve cells used to transfer information to different neutrons, muscles and glands. This axonal stretch is in agreement with analytical predictions [7]. Regions 2 and 3 near the craniectomy edge, are most vulnerable to damage to the axons through shear forces and herniation. Axonal shear is shown here to be a potential factor in long term brain damage from decompressive craniectomy.

The simulations performed here, suggest that a frontal craniectomy, which provides a larger opening, creates significantly lower displacement, strains and stretches in comparison with a unilateral craniectomy (openings on the side of the skull).

This research along with mathematical models and computational simulations can help identify regions of extreme tissue kinematics. This approach could guide neurosurgeons to optimize the shape and position of the craniectomy with the goal to avoid placing the craniectomy edge near functionally important regions of the brain.

[1] Cooper et. al., New Engl. J. Med. 364 (2011) 1493-1502.
[2] Kolias et. al., Nature Rev. Neurol. 9 (2013) 405-415
[3] Quinn et. al., Acta Neurol. Scandinav. 123 (2011) 239-244.
[4] Hutchinson et. al, Acta Neurochir. Suppl. 96 (2006) 17-20.
[5] T. Kocher, Die Therapie des Hirndruckes. In: Verlag H, editor. Hirnerschütterung, Hirndruck und chirurgische Eingriffe bei Hirnkrankheiten. (1901) 262–266
[6] Weickenmeier et. Al.,Journal of Elasticity. (2017) 129–197
[7] Goriely et al., Phys. Rev. Letters 117 (2016) 138001

Document Details

AuthorGenc. K
Date 6th June 2018


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