Effect of Cerebral Vasculatures on the Mechanical Response of Brain Tissue: A Preliminary Study

Omori, Kiyoshi; Zhang, Liying; Yang, King H.; King, Albert I.

doi:10.1115/imece2000-2477

Cited by 8 publications

(3 citation statements)

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“…Instead, we found material properties from relevant tests which accounted for both cortical and bridging veins, to give the most comprehensive estimation we could achieve. Overall, our value of 3.6 MPa was similar to other models which used a linear elastic material model for vessels ( Omori et al, 2000 ; Ho and Kleiven, 2007 ; Zoghi-Moghadam and Sadegh, 2009 ; Mao et al, 2013 ; Knowles et al, 2017 ).…”

Section: Discussionsupporting

confidence: 83%

“…The most common inclusion of vasculature has been bridging veins to allow for the study of subdural hematoma, which frequently occurs when the bridging veins rupture ( Huang et al, 1999 ; Kleiven, 2005 ; Viano et al, 2005 ; Mao et al, 2013 ; Cui et al, 2017 ; Knowles et al, 2017 ). A few studies used FE modelling to explore the effects of the inclusion of cerebral vasculature on the dynamic response of the brain tissue ( Omori et al, 2000 ; Ho and Kleiven, 2007 ; Zhao and Ji, 2020 ). A recent work used a model of vasculature to predict the level of strains in vessels during sporting and road traffic collisions, but the study lacked a description of likely vascular pathologies in the patients ( Zhao and Ji, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

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A Finite Element Model of Cerebral Vascular Injury for Predicting Microbleeds Location

Duckworth

Azor

Wischmann

et al. 2022

Front. Bioeng. Biotechnol.

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Finite Element (FE) models of brain mechanics have improved our understanding of the brain response to rapid mechanical loads that produce traumatic brain injuries. However, these models have rarely incorporated vasculature, which limits their ability to predict the response of vessels to head impacts. To address this shortcoming, here we used high-resolution MRI scans to map the venous system anatomy at a submillimetre resolution. We then used this map to develop an FE model of veins and incorporated it in an anatomically detailed FE model of the brain. The model prediction of brain displacement at different locations was compared to controlled experiments on post-mortem human subject heads, yielding over 3,100 displacement curve comparisons, which showed fair to excellent correlation between them. We then used the model to predict the distribution of axial strains and strain rates in the veins of a rugby player who had small blood deposits in his white matter, known as microbleeds, after sustaining a head collision. We hypothesised that the distribution of axial strain and strain rate in veins can predict the pattern of microbleeds. We reconstructed the head collision using video footage and multi-body dynamics modelling and used the predicted head accelerations to load the FE model of vascular injury. The model predicted large axial strains in veins where microbleeds were detected. A region of interest analysis using white matter tracts showed that the tract group with microbleeds had 95th percentile peak axial strain and strain rate of 0.197 and 64.9 s−1 respectively, which were significantly larger than those of the group of tracts without microbleeds (0.163 and 57.0 s−1). This study does not derive a threshold for the onset of microbleeds as it investigated a single case, but it provides evidence for a link between strain and strain rate applied to veins during head impacts and structural damage and allows for future work to generate threshold values. Moreover, our results suggest that the FE model has the potential to be used to predict intracranial vascular injuries after TBI, providing a more objective tool for TBI assessment and improving protection against it.

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Section: Discussionsupporting

confidence: 83%

Section: Introductionmentioning

confidence: 99%

A Finite Element Model of Cerebral Vascular Injury for Predicting Microbleeds Location

Duckworth

Azor

Wischmann

et al. 2022

Front. Bioeng. Biotechnol.

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“…The system is made of compliant and biocompatible extracellular matrix (ECM) material, gelatin-fibrin hydrogel, which has similar stiffness to the brain tissue, compared to the previous aneurysm models [17,18,22,51]. The brain tissue without vasculature has reported elastic modulus of 0.1-1 kPa [52,53], while the existence of vasculature is likely to increase the mechanical modulus of the brain [54,55]. Since the aim of the study was to analyze the hemodynamics and cellular responses inside the brain vessel that is embedded in the brain tissue, the elastic modulus of the gelatin-fibrin gel (1.1 kPa) [56] was considered suitable for this investigation.…”

Section: Discussionmentioning

confidence: 99%

Three-dimensional bioprinting of aneurysm-bearing tissue structure for endovascular deployment of embolization coils

et al. 2020

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Various types of embolization devices have been developed for the treatment of cerebral aneurysms. However, it is challenging to properly evaluate device performance and train medical personnel for device deployment without the aid of functionally relevant models. Current in vitro aneurysm models suffer from a lack of key functional and morphological features of brain vasculature that limit their applicability for these purposes. These features include the physiologically relevant mechanical properties and the dynamic cellular environment of blood vessels subjected to constant fluid flow. Herein, we developed three-dimensionally (3D) printed aneurysm-bearing vascularized tissue structures using gelatin-fibrin hydrogel of which the inner vessel walls were seeded with human cerebral microvascular endothelial cells (hCMECs). The hCMECs readily exhibited cellular attachment, spreading, and confluency all around the vessel walls, including the aneurysm walls. Additionally, the in vitro platform was directly amenable to flow measurements via particle image velocimetry, enabling the direct assessment of the vascular flow dynamics for comparison to a 3D computational fluid dynamics model. Detachable coils were delivered into the printed aneurysm sac through the vessel using a microcatheter and static blood plasma clotting was monitored inside the aneurysm sac and around the coils. This biomimetic in vitro aneurysm model is a promising method for examining the biocompatibility and hemostatic efficiency of embolization devices and for providing hemodynamic information which would aid in predicting aneurysm rupture or healing response after treatment.

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Dynamic response of the brain with vasculature: A three-dimensional computational study

Kleiven

2007

Journal of Biomechanics

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Effect of Cerebral Vasculatures on the Mechanical Response of Brain Tissue: A Preliminary Study

Cited by 8 publications

References 0 publications

A Finite Element Model of Cerebral Vascular Injury for Predicting Microbleeds Location

A Finite Element Model of Cerebral Vascular Injury for Predicting Microbleeds Location

Three-dimensional bioprinting of aneurysm-bearing tissue structure for endovascular deployment of embolization coils

Dynamic response of the brain with vasculature: A three-dimensional computational study

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