In-silico investigation of the neonatal brain physiology using a systems biology approach: modelling birth asphyxia and neuroprotective strategies

Hypoxic ischaemic encephelopathy (HIE), often resulting from intrapartum hypoxic-ischemic injury, is a significant cause of death and morbidity before, during and after birth. In order to identify and monitor HIE, clinicians use non-invasive techniques including magnetic resonance spectroscopy (MRS) and near-infrared spectroscopy (NIRS). However, interpretation of these signals, particularly to determine the effectiveness of treatment and the severity of injury, is a challenging and difficult task. This thesis describes an attempt to use a systems biology approach to better understand the mechanisms behind HIE and its outcomes, using mathematical and computational techniques to analyse multimodal data, including broadband near-infrared spectroscopy (bNIRS). These models incorporate submodels of cerebral blood flow, oxygen transport and metabolism into a single cohesive model that attempts to simulate the observed measurements of tissue oxygenation and metabolism. The scope of this work is to both develop a set of computational tools that can be used to better understand existing systems biology models of the brain and to develop a new model which is able to incorporate the effects of therapeutic hypothermia, a common treatment for HIE, on the underlying physiology and its dynamics. The work begins by redeveloping the existing framework used for running and analysing systems biology models as used previously, before going on to develop a Bayesian framework which allows a better and more comprehensive interpretation of the results. This framework is then used to analyse three new models that incorporate the impact of therapeutic hypothermia on the piglet brain. The model determined to be most effective is then applied to clinical data from neonates that experience spontaneous desaturations in blood oxygen whilst undergoing hypothermic treatment. In all cases data from subjects with both mild and severe injuries are compared to determine if separate parameter spaces (and therefore physiological mechanisms) can be identified for each

Continuous Multi-Modal Monitoring of Cerebrovascular Reactivity in Adult Traumatic Brain Injury

Impaired cerebral autoregulation following traumatic brain injury (TBI) in adults has been linked to worse global outcome. Continuously updating indices of cerebrovascular reactivity provide a convenient and continuous metric regarding an individual patients’ autoregulatory status. To date, the vast majority of the literature has focused on pressure reactivity index (PRx), which has emerged as the “gold standard” for continuous monitoring of cerebrovascular reactivity in adult TBI, but many questions concerning its clinical utility remain unanswered. The focus of this thesis was to address some of these previously unanswered questions, using data from experimental models and from multi-modality monitoring (MMM) in adult TBI patients. Specific questions addressed in this thesis include: [A] Do other ICP-derived indices to assess cerebrovascular reactivity exist? [B] Do ICP-derived indices actually measure autoregulation? [C] What are the inter-index relationships between various MMM techniques? [D] Can one estimate/predict the “gold standard” invasive PRx using non-invasive means? [E] What are the critical thresholds associated with outcome for ICP derived indices? [F] Are any specific ICP derived index/indices superior for outcome prediction? and [G] What role do intra-cranial (IC) and extra-cranial (EC) injury burden play in driving autoregulatory function in TBI? These studies evaluated a newly described index derived from pulse amplitude of ICP and cerebral perfusion pressure (CPP), RAC, which provides information regarding both cerebrovascular reactivity and compensatory reserve. Using experimental models of arterial hypotension and IC hypertension, it was demonstrated that the three ICP derived indices (including RAC) of cerebrovascular reactivity measure the lower limit of autoregulation (LLA), providing some of the first evidence to validate these indices as measures of autoregulation. It still remains unclear as to whether these indices can measure the upper limit of autoregulation (ULA). Indices derived from MMM display reproducible inter-index relationships between various populations of adult TBI patients. Transcranial Doppler (TCD) based systolic flow index is most closely associated with ICP indices, while cortical autoregulation (measured using laser Doppler) is more closely linked to mean flow index. Given these relationships and the potential for non-invasive measurement of systolic flow index, attempts at modelling the “gold standard” PRx were made. From this, it is possible to both estimate and predict PRx using non-invasive systolic flow index, employing complex time-series techniques. Outcome analysis showed that RAC provides superior outcome prediction, with more stable critical thresholds, compared to all other ICP derived indices. Furthermore, IC injury markers (subarachnoid hemorrhage thickness, diffuse axonal injury, and presence of subdural hematoma) were associated with impaired cerebral autoregulation as measured by ICP derived indices, implicating diffuse cerebral injury as a driver of impaired reactivity. The data also suggest that EC injury burden may play a role in impairment of cerebrovascular reactivity.Cambridge International Trust Scholarshi

Global energy minimisation of arterial trees with application to embolic stroke

Computer generation of optimal arterial trees has previously been limited to the production of locally optimal configurations. The application of a global optimisation algorithm allows for the generation of vasculatures with consistent structure. Comparison of this structure to that of in-vivo vasculatures allows the determination of to what extent the vascular structure is the result of energy minimisation. In this thesis an algorithm capable of generation globally optimal vascular trees in geometries derived from medical imaging is developed. We begin by outlining a small set of constraints which capture physiological principles guiding the organisation of arterial trees. The constraints are then used to produce an algorithm capable of finding the minimal energy configuration of a given arterial tree. The algorithm is used to produce both coronary and cerebral vasculature, and the latter is generated in geometries segmented from MRI data of a human brain. The trees are compared both morphologically and structurally to those found in-vivo. The morphological comparisons for the coronary vasculature show excellent agreement with experiment. The positions of the larger coronary arteries in the generated trees agree extremely well with experiment, suggesting that structure of the coronary vasculature is the result of energy minimisation. The generated cerebral vasculature approximates the vascular territories of the major cerebral arteries, however the morphological comparisons show that the structure of the cerebral arteries is likely not the result of energy minimisation. The cerebral vasculatures is used to extend a statistical model of embolic stroke to include the effects of branching asymmetry, and an analytic approximation to the statistical model of embolic stroke is developed and validated. It is found that branching asymmetry produces an overall reduction in the level of blockage occuring during an embolic event

Optical imaging and spectroscopy for the study of the human brain: status report

This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions

Optical imaging and spectroscopy for the study of the human brain: status report.

This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions

Optical imaging and spectroscopy for the study of the human brain: status report

This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions. Keywords: DCS; NIRS; diffuse optics; functional neuroscience; optical imaging; optical spectroscop

Advanced analyses of physiological signals and their role in Neonatal Intensive Care

Preterm infants admitted to the neonatal intensive care unit (NICU) face an array of life-threatening diseases requiring procedures such as resuscitation and invasive monitoring, and other risks related to exposure to the hospital environment, all of which may have lifelong implications. This thesis examined a range of applications for advanced signal analyses in the NICU, from identifying of physiological patterns associated with neonatal outcomes, to evaluating the impact of certain treatments on physiological variability. Firstly, the thesis examined the potential to identify infants at risk of developing intraventricular haemorrhage, often interrelated with factors leading to preterm birth, mechanical ventilation, hypoxia and prolonged apnoeas. This thesis then characterised the cardiovascular impact of caffeine therapy which is often administered to prevent and treat apnoea of prematurity, finding greater pulse pressure variability and enhanced responsiveness of the autonomic nervous system. Cerebral autoregulation maintains cerebral blood flow despite fluctuations in arterial blood pressure and is an important consideration for preterm infants who are especially vulnerable to brain injury. Using various time and frequency domain correlation techniques, the thesis found acute changes in cerebral autoregulation of preterm infants following caffeine therapy. Nutrition in early life may also affect neurodevelopment and morbidity in later life. This thesis developed models for identifying malnutrition risk using anthropometry and near-infrared interactance features. This thesis has presented a range of ways in which advanced analyses including time series analysis, feature selection and model development can be applied to neonatal intensive care. There is a clear role for such analyses in early detection of clinical outcomes, characterising the effects of relevant treatments or pathologies and identifying infants at risk of later morbidity

The role of leptomeningeal collaterals in redistributing blood flow during stroke

Leptomeningeal collaterals (LMCs) connect the main cerebral arteries and provide alternative pathways for blood flow during ischaemic stroke. This is beneficial for reducing infarct size and reperfusion success after treatment. However, a better understanding of how LMCs affect blood flow distribution is indispensable to improve therapeutic strategies. Here, we present a novel in silico approach that incorporates case-specific in vivo data into a computational model to simulate blood flow in large semi-realistic microvascular networks from two different mouse strains, characterised by having many and almost no LMCs between middle and anterior cerebral artery (MCA, ACA) territories. This framework is unique because our simulations are directly aligned with in vivo data. Moreover, it allows us to analyse perfusion characteristics quantitatively across all vessel types and for networks with no, few and many LMCs. We show that the occlusion of the MCA directly caused a redistribution of blood that was characterised by increased flow in LMCs. Interestingly, the improved perfusion of MCA-sided microvessels after dilating LMCs came at the cost of a reduced blood supply in other brain areas. This effect was enhanced in regions close to the watershed line and when the number of LMCs was increased. Additional dilations of surface and penetrating arteries after stroke improved perfusion across the entire vasculature and partially recovered flow in the obstructed region, especially in networks with many LMCs, which further underlines the role of LMCs during stroke

The role of leptomeningeal collaterals in redistributing blood flow during stroke.

Leptomeningeal collaterals (LMCs) connect the main cerebral arteries and provide alternative pathways for blood flow during ischaemic stroke. This is beneficial for reducing infarct size and reperfusion success after treatment. However, a better understanding of how LMCs affect blood flow distribution is indispensable to improve therapeutic strategies. Here, we present a novel in silico approach that incorporates case-specific in vivo data into a computational model to simulate blood flow in large semi-realistic microvascular networks from two different mouse strains, characterised by having many and almost no LMCs between middle and anterior cerebral artery (MCA, ACA) territories. This framework is unique because our simulations are directly aligned with in vivo data. Moreover, it allows us to analyse perfusion characteristics quantitatively across all vessel types and for networks with no, few and many LMCs. We show that the occlusion of the MCA directly caused a redistribution of blood that was characterised by increased flow in LMCs. Interestingly, the improved perfusion of MCA-sided microvessels after dilating LMCs came at the cost of a reduced blood supply in other brain areas. This effect was enhanced in regions close to the watershed line and when the number of LMCs was increased. Additional dilations of surface and penetrating arteries after stroke improved perfusion across the entire vasculature and partially recovered flow in the obstructed region, especially in networks with many LMCs, which further underlines the role of LMCs during stroke