An adequate timely prognosis of cerebral vasospasms and delayed cerebral ischemia (DCI) occuring after spontaneous aneurysmal subarachnoid haemorrhage (aSAH), is vitally essential to selecting an individualized and timely treatment strategy. Cerebral vasospasms (CV) occur in up to 70% of aSAH cases, and in two thirds of those cases DCI develops, thus increasing the mortality rate up to 50%. Every year up to 770 000 people suffer from aSAH and receive neurosurgical treatment. Because of a large amount of factors (blood leak volume and its distribution in the subarachnoid space, reactivity of cerebral blood vessels, biochemical blood composition and demographical factors) and their complex interactions to contribute the development of CV/DCI, currently there are no reliable methods and technologies that would allow us to reliably predict the consequences of SAH.
For a more effective treatment of aSAH patients we offer an innovative method for early warning of CV and DCI phenomena. The method is based on identifying of the associations of different physiological modalities and prognostic factors with the SAH patients’ outcome (factors the obtained from CT images analysis, numerical modelling of SAH evolution and multimodal cerebral hemodynamics monitoring)
Project abjectives are to develop an innovative method for predicting and early warning of CV and DCI after aSAH, to perform clinical studies of this method and to create a software tool for forecasting vasospasm and cerebral ischemia.
The main activities in the project:
– developing the algorithm for automated classification and spatial segmentation of neuroimages,
– numerical modelling of SAH evolution and CV formation,
– clinical multimodal monitoring study on aSAH patients,
– developing the algorithm and software for predicting CV and DCI .
The main result of project will be the developed commercial product (software) for predicting and early warning of CV and DCI after SAH and two patents application (USPTO and EPO) of this innovative product.
Project funding:
This research project is funded by the European Regional Development Fund according to the 2014–2020 Operational Programme for the European Union Funds’ Investments, under measure’s No. 01.2.2-LMT-K-718 activity “Research Projects Implemented by World-class Researcher Groups to develop R&D activities relevant to economic sectors, which could later be commercialized”.
Project coordinator: Kaunas University of Technology
Project partners: Lithuanian University of Health Sciences, VŠĮ Vilniaus universiteto ligoninės Santaros klinikos
