Determination of Optimal Cerebral Perfusion Pressure by Multimodal Signal Fusion

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The control of cerebral blood flow (CBF) is essential as it ensures adequate delivery of oxygen and metabolites to the brain, and removal of metabolic waste products. Under healthy conditions, CBF homeostasis is provided by an intricate set of global (autonomic neurogenic) and local (autoregulatory) control mechanisms. In patients with severe traumatic brain injury the capability of CBF autoregulation is lost, thus putting the patients at significant risk of cerebral underperfusion and a mismatch between metabolic substrate demand and supply. In neurocritical care, it is crucial to apply a sufficiently high cerebral perfusion pressure (CPP) to maintain CBF. However, in the face of disturbed CBF autoregulation, an increase in CPP may lead to an unfavorable increase in intracranial pressure (ICP).This proposal aims to develop and validate an approach to personalizing the ICP and CPP targets on the basis of the underlying cerebrovascular physiology of each patient by the application of methods of signal analysis and information fusion known from other fields of medical signal processing.The two main research objectives are: i) improvement in the accuracy of pressure reactivity assessment, and ii) optimization of the determination of optimal CPP by providing a better interpretable data output (clearer U-shaped output curve) and by increasing patient safety.The main basis for the analysis planned in this proposal will be formed by bedside monitoring data – including ICP, arterial blood pressure, CBF velocity, tissue oxygenation, and further regularly monitored vitals (heart rate, respiration, pulse oximetry, etc.) – collected from over 200 patients in the neurocritical and trauma care units at Boston Medical Center and Boston Children’s Hospital.