Optimal design of feasible clinical tests for the identification of physiological models of type 1 diabetes mellitus

Questa tesi concerne la progettazione di test clinici per l'identificazione di modelli fisiologici del diabete mellito di tipo 1. La progettazione ottimale di esperimenti basata su modello si applica a tal proposito e la fattibilità dei test ideati viene valutata tramite una serie di indici introdotti ad hoc. Il lavoro si conclude con l'impiego di tecniche di progettazione robusta che siano in grado di garantire al test i requisiti di applicabilità clinica necessar

A methodology for direct exploitation of available information in the online model-based redesign of experiments

Online model-based design of experiments techniques were proposed to exploit the progressive increase of the information resulting from the running experiment, but they currently exhibit some limitations: the redesign time points are chosen “a-priori” and the first design may be heavily affected by the initial parametric mismatch. In order to face such issues an information driven redesign optimisation (IDRO) strategy is here proposed: a robust approach is adopted and a new design criterion based on the maximisation of a target profile of dynamic information is introduced. The methodology allows determining when to redesign the experiment in an automatic way, thus guaranteeing that an acceptable increase in the information content has been achieved before proceeding with the intermediate estimation of the parameters and the subsequent redesign of the experiment. The effectiveness of the new experiment design technique is demonstrated through two simulated case studies

REGULATION OF BLOOD GLUCOSE IN TYPE I DIABETIC PATIENTS

Ph.DDOCTOR OF PHILOSOPH

Hyperglycaemia, insulin and acute ischaemic stroke

Background: Hyperglycaemia is common in acute stroke and is associated with a poor outcome. Underlying aetiology and mechanism of action is poorly understood. Management remains uncertain. Methods: We undertook a randomised placebo controlled trial to assess the effect of GKI (Glucose-Potassium-Insulin) versus placebo on lesion volume progression and cerebral lactate levels using magnetic resonance imaging (MRI) and spectroscopy (MRS). An observational study of the capillary blood glucose within 48 hours of stroke onset was performed to define the temporal profile of glucose, with a subset followed prospectively to determine the prevalence of abnormal glucose metabolism in patients with stress hyperglycaemia. The association between insular cortex involvement and hyperglycaemia was determined by analysing MRI data sets from two randomised trials. Stroke unit practice for the management of glucose was assessed in a review of the stroke unit trialists’ collaboration data set. Results: • GKI infusion failed to attenuate infarct growth in patients with moderate hyperglycaemia within 24 hours of acute ischaemic stroke. A trend towards attenuation of increased lactate concentration was evident in the GKI treatment arm. Exploratory analyses raised the possibility that GKI may be harmful in patients with persistent arterial occlusion. • Over the 48hour monitoring period 75% of patients developed Hyperglycaemia. Stroke severity was not predictive of admission hyperglycaemia whereas glycosylated haemoglobin was (OR 2.97; 95%CI 1.84-4.78; p<0.001). 50% of patients screened were found to have abnormal glucose metabolism at follow-up. • Insular cortex involvment on MRI was not predictive of admission hyperglycaemia. • Testing for blood glucose concentration in stroke units was infrequent. Of the minority of units that had a protocol in place, the threshold for intervention with insulin was >10mmol/l. Conclusion: We found no evidence that GKI infusion attenuated infarct growth in patients with mild hyperglycaemia following acute ischaemic stroke. In post-hoc analysis the possibility that GKI infusion may be harmful in patients with total occlusion suggests an effect dependent on recanalisation status. A non-significant trend towards attenuation of increased lactate concentration was evident. Stroke severity was not found to be a predictor of post stroke hyperglycaemia. Underlying dysglycaemia was common in non-diabetic patients manifesting hyperglycaemia within 48hours of stroke ictus. Screening of high risk patients with oral glucose tolerance testing is justified and provides a potential opportunity for secondary prevention. Insular cortex involvement did not independently predict hyperglycaemia in acute stroke. Current management of hyperglycaemia is guided by consensus guidelines with little evidence base. Stroke unit practice varies with little change across stroke units over the years

Applications of CT Perfusion-Based Triaging and Prognostication in Acute Ischemic Stroke

CT Perfusion (CTP) is a minimally invasive imaging technique that aids acute ischemic stroke (AIS) triage and prognostication by determining tissue viability based on hemodynamic parameters. The goals of this research are to determine: 1) CTP thresholds for estimation of infarct and penumbra volume, 2) how CTP scan duration impacts infarct and penumbra volume estimates, and 3) reliability of CTP for predicting functional outcomes following intra-arterial therapy (IAT). Chapter 2 introduced an experimental study for determining ischemia-time dependent thresholds for brain infarction using multimodal imaging in a porcine stroke model that is easier to implement than previous large animal stroke models. CTP determined an absolute cerebral blood flow (CBF) threshold of 12.6±2.8mL∙min-1∙100g-1 for brain infarction after 3h of ischemia, which was close to that derived using hydrogen clearance in a previous study by Jones et al (Journal of Neurosurgery, 1981;54(6):773-782). Chapter 3 retrospectively investigated the impact of CTP scan duration on cerebral blood volume (CBV), CBF, and time-to-maximum (Tmax) and found optimal scan durations that minimized radiation dose while not under- or over-estimating infarct volumes measured using two previously derived CBF thresholds for infarction. We found that CBV and Tmax decreased at shorter scan durations, whereas CBF was independent of scan duration, consequently, infarct volume estimated by both CBF thresholds was independent of scan duration. Chapter 4 compared reperfusion seen on follow-up CTP to reperfusion predicted by post-IAT digital subtraction angiography (DSA) and the ability of the two modalities to predict good 90-day functional outcome in a retrospective study. We found that patients with ‘complete reperfusion’ grades on DSA often had ischemic tissue on follow-up CTP and that follow-up CTP had superior specificity and accuracy for predicting functional outcome compared to DSA. In summary, this research has shown that CBF thresholds can reliably detect infarct in AIS and are independent of scan duration, allowing radiation dose to be minimized by limiting scans to 40s without compromising accuracy of infarct volume estimates. Finally, CTP is a more specific and accurate predictor of functional outcome than the commonly used post-procedural DSA, this could help select patients for neuroprotective therapy

Improving Acute Stroke Management with CT Perfusion Imaging: Approaches to Treatment Guidance and Brain Tissue Salvage

CT Perfusion (CTP) provides measurement of perfusion at the capillary level which can be used to characterize tissue viability, and blood-brain-barrier (BBB) compromise. Using CTP, the goals of this research are to: 1) select patients that will benefit from acute stroke treatment, and 2) determine if pre-stroke neuroprotection reduces stroke severity. Chapter two investigates the cerebral blood volume (CBV) parameter in a small acute ischemic stroke (AIS) patient set. Overestimation of the acute CBV defect is caused by incomplete wash-out of the CT contrast due to a shortened CTP acquisition time (“truncation artifact”). In chapter three we examine the prognostic reliability of the acute CBV defect to predict infarct core and penumbra in AIS. We determine that hypervolemia, the “truncation artifact” and recanalization are all important variables which affect the relationship between the acute CBV defect volume and the final infarct volume. Chapter four implements a novel porcine model of ischemic stroke using the transient vasoconstrictor, endothelin-1. Using this model, we show that the CTP-cerebral blood flow (CBF) parameter is as good as MR-DWI for acute infarct core delineation, and the CBF/CBV mismatch may not indicate penumbral tissue in the acute stroke setting. In Chapter five, it we show that vascular integrity measured with the CTP-BBB permeability surface area product (PS) is a strong predictor of sub-acute bleeding in the brain (hemorrhagic transformation). Chapter six shows that different rates of CT contrast extravasation exist for primary intracerebral hemorrhage (ICH) patients with/without the CTA-Spot Sign and/or post-contrast leakage. Furthermore, early rates of extravasation are correlated with sub-acute hematoma expansion. Chapter seven describes the development of an improved, reproducible and survivable rabbit large clot embolic model (RLCEM) of cerebral ischemia for testing treatment options for AIS. We demonstrate that pre-stroke treatment with dipyridamole provides a neurovascular advantage post stroke onset. In summary, the current uses of CTP imaging in acute stroke include: 1) quantifying ischemia to define infarct core and penumbra in AIS, 2) predicting hemorrhagic transformation of AIS, 3) predicting hematoma expansion in primary ICH, and 4) assessing treatment response in animal models of stroke to facilitate new drug development

Modeling and Prediction in Diabetes Physiology

Diabetes is a group of metabolic diseases characterized by the inability of the organism to autonomously regulate the blood glucose levels. It requires continuing medical care to prevent acute complications and to reduce the risk of long-term complications. Inadequate glucose control is associated with damage, dysfunction and failure of various organs. The management of the disease is non trivial and demanding. With today’s standards of current diabetes care, good glucose regulation needs constant attention and decision-making by the individuals with diabetes. Empowering the patients with a decision support system would, therefore, improve their quality of life without additional burdens nor replacing human expertise. This thesis investigates the use of data-driven techniques to the purpose of glucose metabolism modeling and short-term blood-glucose predictions in Type I Diabetes Mellitus (T1DM). The goal was to use models and predictors in an advisory tool able to produce personalized short-term blood glucose predictions and on-the-spot decision making concerning the most adequate choice of insulin delivery, meal intake and exercise, to help diabetic subjects maintaining glycemia as close to normal as possible. The approaches taken to describe the glucose metabolism were discrete-time and continuous-time models on input-output form and statespace form, while the blood glucose short-term predictors, i.e., up to 120 minutes ahead, used ARX-, ARMAX- and subspace-based prediction