Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.789940
Title: Modelling metabolism in the neonatal brain
Author: Hapuarachchi, T. S.
ISNI:       0000 0004 8502 5468
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2015
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Abstract:
Acute changes in cerebral blood flow and oxygen delivery directly affect brain tissue metabolism, often leading to severe life-long disabilities or death. These events can occur during birth with dire consequences to the infant. In order to identify and monitor these events in the neonatal brain clinicians often use non-invasive techniques such as near-infrared spectroscopy (NIRS) and magnetic resonance spectroscopy (MRS). However, clinical interpretation of these signals is challenging. This thesis describes a number of mathematical and computational models of cerebral blood flow, oxygenation and metabolism regulation to assist signals integration from multimodal measurements and to investigate brain tissue metabolic activity in neonatal preclinical and clinical studies. The scope of this work is to construct a set of useful computational tools that will illuminate brain tissue and cellular physiology that give rise to changes in clinical measurements, and hence offer information of clinical significance. The models are composed of differential equations and algebraic relations that mimic the network regulating cellular metabolism. They integrate NIRS and MRS measurements that offer insights into oxygenation and a variety of metabolic products such as ATP and pH. These models are thus able to explore the relation between measured signals and the physiology and biochemistry of the brain. The first three models presented in this thesis focus on the piglet brain - a preclinical animal model of the human neonatal brain. Previously published models are extended to simulate intracellular pH and used to investigate hypoxia-ischaemia experiments conducted in piglets, predicting NIRS and MRS measurements. The fourth model is an adaptation of the piglet model to the human term neonate, to investigate data from bedside NIRS monitoring of patients with birth asphyxia. Finally a previously published, simpler adult model is adapted to the preterm neonate, simulating data from functional response studies and a functional NIRS study in neonates using a visual stimulus.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.789940  DOI: Not available
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