Endovascular treatment of stroke – Key determinants of technical and clinical outcome

Abstract

Background: The overall aim of this thesis is to improve endovascular treatment of ischemic stroke by advancing the understanding of key determinants of outcome. Methods: All four studies were based on registry data and applied multivariable regression modeling. In addition, Paper IV included analyses of histological clot composition and clot size. Paper I focused on procedural quality and prognostication, specifically examining the expansion of a grading scale for assessing reperfusion following mechanical thrombectomy, as well as the definition of successful intervention. Paper II evaluated procedural strategy by comparing the two principal mechanical thrombectomy techniques in terms of performance and clinical outcomes. Paper III addressed workflow efficiency, assessing the system-wide impact of implementing an AI-supported imaging decision-making tool. Finally, Paper IV explored the role of clot biology and clot burden in relation to both technical and clinical outcomes. Results: The main findings of this thesis are as follows: an additional grading step in angiographic evaluation of mechanical thrombectomy improves correlation between imaging and clinical outcomes (1); aspiration approach is associated with reduced procedural time and improved clinical outcomes (2); implementation of an AI-supported decision making tool reduced time to treatment, mainly at primary stroke centers (3); Clot size is a key determinant of both technical and clinical outcomes in aspiration-based mechanical thrombectomy (4). Conclusion: Endovascular treatment of stroke is a complex, system-dependent procedure, requiring improvements across multiple domains to optimize outcomes. This thesis advances the understanding of outcome determinants across four such domains: procedural quality, procedural strategy, system-level organization, and clot biology.