Dr John C Vardakis, BEng, PhD - University College London - Research Associate in Integrative Cerebral Dynamics

Dr John C Vardakis

BEng, PhD

University College London

Research Associate in Integrative Cerebral Dynamics

London | United Kingdom

Main Specialties: Biology

Additional Specialties: CFD, FEM, Biomedical Engineering, Numerical Methods

ORCID logohttps://orcid.org/0000-0003-2391-5257


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Dr John C Vardakis, BEng, PhD - University College London - Research Associate in Integrative Cerebral Dynamics

Dr John C Vardakis

BEng, PhD

Introduction

I'm a Research Associate in Integrative Cerebral Dynamics working with Professor Y. Ventikos at UCL. My main focus is developing a computational framework that will aid in the understanding of cerebral diseases arising from Dementia (such as Alzheimer's Disease, Vascular Dementia and Normal Pressure Hydrocephalus). We work within the VPH-DARE@IT project, which aims to deliver the first patient-specific predictive models for early differential diagnosis of dementias and their evolution. The foundations of the mathematical modelling that we work on lie in Multiple-Network Poroelastic Theory, adapted to patient specific cases and simulated through a combination of Computational Fluid Dynamics (currently aided by High Performance Computing) and the Finite Element Method. We are developing a modelling platform that can handle, in an anatomically accurate and patient specific manner, the transport and interplay of blood and cerebrospinal fluid with the parenchyma – the neuronal and astrocytic tissue that constitutes the functioning brain.

Primary Affiliation: University College London - London , United Kingdom

Specialties:

Additional Specialties:

Research Interests:

Education

Feb 2015
University of Oxford
DPhil
Engineering Science
Jan 2010 - Oct 2014
University of Oxford
Doctor of Philosophy (PhD), Integrative Cerebral Dynamics
Engineering Science

Experience

May 2015
VPH-DARE@IT
Research Associate

Publications

8Publications

237Reads

1381Profile Views

Disturbed flow induces a sustained, stochastic NF-κB activation which may support intracranial aneurysm growth in vivo

Scientific Reports. 2019. 4738(9)

Scientific Reports

Intracranial aneurysms are associated with disturbed velocity patterns, and chronic inflammation, but the relevance for these findings are currently unknown. Here, we show that (disturbed) shear stress induced by vortices is a sufficient condition to activate the endothelial NF-kB pathway, possibly through a mechanism of mechanosensor de-activation. We provide evidence for this statement through in-vitro live cell imaging of NF-kB in HUVECs exposed to different flow conditions, stochastic modelling of flow induced NF-kB activation and induction of disturbed flow in mouse carotid arteries. Finally, CFD and immunofluorescence on human intracranial aneurysms showed a correlation similar to the mouse vessels, suggesting that disturbed shear stress may lead to sustained NF-kB activation thereby offering an explanation for the close association between disturbed flow and intracranial aneurysms.

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March 2019

Subject-specific multi-poroelastic model for exploring the risk factors associated with the early stages of Alzheimer's disease

Interface Focus. 2017

Interface Focus

There is emerging evidence suggesting that Alzheimer's disease is a vascular disorder, caused by impaired cerebral perfusion, which may be promoted by cardiovascular risk factors that are strongly influenced by lifestyle. In order to develop an understanding of the exact nature of such a hypothesis, a biomechanical understanding of the influence of lifestyle factors is pursued. An extended poroelastic model of perfused parenchymal tissue coupled with separate workflows concerning subject-specific meshes, permeability tensor maps and cerebral blood flow variability is used. The subject-specific datasets used in the modelling of this paper were collected as part of prospective data collection. Two cases were simulated involving male, non-smokers (control and mild cognitive impairment (MCI) case) during two states of activity (high and low). Results showed a marginally reduced clearance of cerebrospinal fluid (CSF)/interstitial fluid (ISF), elevated parenchymal tissue displacement and CSF/ISF accumulation and drainage in the MCI case. The peak perfusion remained at 8 mm s−1 between the two cases.

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December 2017
47 Reads

Response to letter to the editor concerning "A fully dynamic multi-compartmental poroelastic system: Application to aqueductal stenosis".

J Biomech 2017 06 16;58:243-246. Epub 2017 May 16.

Department of Mechanical Engineering, University College London, UK. Electronic address:

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http://dx.doi.org/10.1016/j.jbiomech.2017.04.032DOI Listing
June 2017
40 Reads
2.751 Impact Factor

A fully dynamic multi-compartmental poroelastic system: Application to aqueductal stenosis.

J Biomech 2016 07 28;49(11):2306-2312. Epub 2015 Nov 28.

Department of Mechanical Engineering, University College London, Torrington Place, London WC1E 7JE, UK. Electronic address:

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http://dx.doi.org/10.1016/j.jbiomech.2015.11.025DOI Listing
July 2016
43 Reads
2.751 Impact Factor

Investigating cerebral oedema using poroelasticity.

Med Eng Phys 2016 Jan 31;38(1):48-57. Epub 2015 Dec 31.

Department of Mechanical Engineering, University College London, Torrington Place, London WC1E 7JE, UK. Electronic address:

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http://dx.doi.org/10.1016/j.medengphy.2015.09.006DOI Listing
January 2016
46 Reads
1.825 Impact Factor

Exploring the efficacy of endoscopic ventriculostomy for hydrocephalus treatment via a multicompartmental poroelastic model of CSF transport: a computational perspective.

PLoS One 2013 31;8(12):e84577. Epub 2013 Dec 31.

Department of Mechanical Engineering, University College London, Torrington Place, London, United Kingdom.

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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0084577PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3877339PMC
September 2014
42 Reads
3.234 Impact Factor

Multicompartmental Poroelasticity as a Platform for the Integrative Modeling of Water Transport in the Brain

n: GA. Holzapfel & E Kuhl (ed.), Computer Models in Biomechanics: From Nano to Macro, Springer-Verlag, Heidelberg

This work proposes the implementation of a multiple-network poroelastic theory (MPET) model for the purpose of investigating in detail the transport of water within the cerebral environment. The key advantage of using the MPET representation is that it accounts for fluid transport between CSF, brain parenchyma and cerebral blood. A further novelty in the model is the amalgamation of anatomically accurate Choroid Plexus regions, with their individual feeding arteries. This model is used to demonstrate and discuss the impact of aqueductal stenosis on the cerebral ventricles, along with possible future treatment techniques.

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October 2012
45 Reads