Pressure, Compliance, and Autoregulation Studies in Intracranial Dynamics
Advancements in neuromonitoring technologies and techniques have led to novel explorations into the physiology and management of traumatic brain injury and normal pressure hydrocephalus. This thesis investigated these pathologies, under approved ethical procedures, with the aid of advanced computational techniques, while maintaining a strong physiological motivation for each analysis. The studies in this thesis provided evidence for the physiological relevance of the optimal cerebral perfusion pressure paradigm, CPPopt, and further demonstrated its potential, alongside CPP-oriented therapy, as clinical tools. Two novel indices were developed: UBP, the compensatory reserve upper breakpoint, which may serve as an indicator for the trigger of life saving physiological mechanisms, and RAMP, reflective of the relationship between intracranial pressure and cerebral blood flow velocity pulse amplitudes. Finally, a dependency between craniospinal compliance and the frequency at which it is calculated was discovered, and deep learning models showed potential for predicting intracranial pressure non-invasively. The results of these studies, several of which have been published, suggest increased potential for individualised treatment paradigms for the brain injured patient. Further research should explore these phenomena in more detail, with the addition of larger and newer datasets reflective of current treatment protocols.
traumatic brain injury, tbi, hydrocephalus, neurotrauma, machine learning, neurocritical care, intracranial pressure, cerebral autoregulation, craniospinal compliance
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