University College London
Research Associate in Integrative Cerebral Dynamics
London | United Kingdom
Main Specialties: Biology
Additional Specialties: CFD, FEM, Biomedical Engineering, Numerical Methods
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
PubMed Central Citations
4PubMed Central Citations
Interface Focus. 2017
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.
J Biomech 2017 06 16;58:243-246. Epub 2017 May 16.
Department of Mechanical Engineering, University College London, UK. Electronic address:
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:
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.