Author, Institution: Solventa Krakauskaitė, Kaunas University of Technology
Science Area, Field of Science: Technological Sciences, Electrical and Electronics Engineering – 01T
Scientific supervisor: Arminas RAGAUSKAS, Prof., DSc (Kaunas University of Technology, Technological Sciences, Electrical and Electronics Engineering – 01T).
Medical advisor: Teodoro Forcht DAGI, MD, DMedSc (Harvard University, Biomedical Sciences, Medicine – 06B).
Dissertation Defence Board of Electrical and Electronics Engineering Science Field:
Prof. Dr. Algimantas Valinevičius (Kaunas University of Technology, Technological Sciences, Electrical and Electronics Engineering – 01T) – chairman
Prof. Dr. Inga Bumblytė (Lithuanian University of Health Sciences, Biomedical Sciences, Medicine – 06B),
Prof. Dr. Vaidotas Marozas (Kaunas University of Technology, Technological Sciences, Electrical and Electronics Engineering – 01T),
Prof. Dr. Liudas Mažeika (Kaunas University of Technology, Technological Sciences, Electrical and Electronics Engineering – 01T),
Dr. Ian Piper (University of Glasgow, Scotland, Biomedical Sciences, Biophysics – 02B).
The doctoral dissertation is available at the library of Kaunas University of Technology (K. Donelaičio g. 20,Kaunas)
Annotation:
The human brain has a great metabolic demand and requires adequate nutritional flow. The brain’s vascular system must respond to changes in arterial blood pressure (ABP) or intracranial pressure to sustain constant cerebral blood flow. A mechanism which maintains cerebral blood flow stable despite fluctuations of perfusion pressure is called cerebrovascular autoregulation (CA). Unfortunately, the impairment of CA has an impact on patients’ outcome. CA status monitoring of these patients allows a physician to establish the optimal, individualized CA-targeted treatment, which is associated with better clinical outcomes and higher survival rates. Thus, it is essential to know the real-time status of CA and the individualized treatment strategy should be re-valuated regularly over the time-course of the CA status. In doctoral dissertation it is assessed a fully non-invasive cerebrovascular autoregulation monitoring system. This CA monitoring technology is based on Pressure-Reactivity index calculation using non-invasively recorded intracranial blood volume fluctuations together with ABP slow waves. The results of prospective clinical trials by using a combination of apparatus showed significant correlation between Pressure-Reactivity index and outcomes of the patients. The most important finding of the doctoral dissertation is a comprehensive explanation of cerebrovascular autoregulation mechanism that emerges from a synergistic application of the new technology and conceptual structures developed under this thesis. It has been shown that patient’s outcome is related to the longest cerebrovascular autoregulation impairment episode, and the technological approach proposed in the thesis solves the problem of the lack of “Gold Standard”.
