A First-Order Mechanical Device to Model Traumatized Craniovascular Biodynamics

[+] Author and Article Information
Sean S. Kohles

 Kohles Bioengineering, Portland, OR 97214-5135; Department of Surgery, Oregon Health and Science University, Portland, OR 97239-3098; and Department of Mechanical and Materials Engineering, Portland State University, Portland, OR 97207-0751ssk@kohlesbioengineering.com

Ryan W. Mangan

Department of Mechanical and Materials Engineering, Portland State University, Portland, OR 97207-0751

Edward Stan

Department of Electrical and Computer Engineering, Portland State University, Portland, OR 97207-0751

James McNames

Biomedical Signal Processing Laboratory, Department of Electrical and Computer Engineering, Portland State University, Portland, OR 97207-0751

J. Med. Devices 1(1), 89-95 (Jul 30, 2006) (7 pages) doi:10.1115/1.2355689 History: Received April 02, 2006; Revised July 30, 2006

Mathematical models currently exist that explore the physiology of normal and traumatized intracranial function. Mechanical models are used to assess harsh environments that may potentially cause head injuries. However, few mechanical models are designed to study the adaptive physiologic response to traumatic brain injury. We describe a first-order physical model designed and fabricated to elucidate the complex biomechanical factors associated with dynamic intracranial physiology. The uni-directional flow device can be used to study interactions between the cranium, brain tissue, cerebrospinal fluid, vasculature, blood, and the heart. Solid and fluid materials were selected to simulate key properties of the cranial system. Total constituent volumes (solid and fluid) and volumetric flow (650mlmin) represent adult human physiology, and the lengths of the individual segments along the flow-path are in accord with Poiseuille’s equation. The physical model includes a mechanism to simulate autoregulatory vessel dynamics. Intracranial pressures were measured at multiple locations throughout the model during simulations with and without post-injury brain tissue swelling. Two scenarios were modeled for both cases: Applications of vasodilation/constriction and changes in the head of bed position. Statistical results indicate that all independent variables had significant influence over fluid pressures measured throughout the model (p<0.0001) including the vasoconstriction mechanism (p=0.0255). The physical model represents a first-order design realization that helps to establish a link between mathematical and mechanical models. Future designs will provide further insight into traumatic head injury and provide a framework for unifying the knowledge gained from mathematical models, injury mechanics, clinical observations, and the response to therapies.

Copyright © 2007 by American Society of Mechanical Engineers
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Figure 1

Image and schematic showing the linear arrangement of analog tissues within the calvarium model. (a) Multiple and single-path vessels were arranged in series to model the vascular segments. An autoregulatory constricting device was placed at the arteriole segment while the TBI swelling mechanism was located in the veins region. (b) The vertical tubes protruding from the model connected six pressure sensors to the intersegmental vascular fluid ports. A seventh sensor tapped into the CSF volume.

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Figure 2

Three-dimensional schematic of the vasoconstriction mechanism with noted components

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Figure 3

Image of the assembled first-order cranial model and associated peripheral devices

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Figure 4

Representative dynamic segmental pressures scaled to mean values generated during the experimental validation (at HOB=0cm, change in arteriole cross-section, ΔA=0%). Mean adult physiologic pressure levels, which were used as the objective design specifications, are indicated in parentheses.

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Figure 5

Functional influence of the vasoconstriction mechanism on intracranial pressure (ICP) as measured through changes in CSF pressure. A basal tone was selected at an arteriole cross-section=0.46cm2(ΔA=0%). Interestingly, a logarithmic function phenomenologically models the relationship well (10 constriction increments, n=5 trials, mean ± standard deviation).

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Figure 6

Multivariate effects of the modeled therapy applications (arteriole constriction/dilation and head of bed changes) on mean ICP as indicated by pressure changes in the CSF. The gray-scale pressure levels represent three distinct inflation volumes added to the brain swelling balloon (0,0.6,1.0ml) during simulated normal cardiovascular activity.

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Figure 7

Contour plots showing the pressure differential due to swelling as a percent of the normal basal tone state (HOB=0cm, ΔA=0%) within the six vascular segments. Increased pressures were typically caused by simulated brain swelling with variable responses to the modeled therapeutic manipulations of arteriole constriction/dilation and head of bed (HOB) positioning. Contour data are defined by triangulated surface elements or tessellations.



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