Stroke Mimics and In Depth Analysis of Computed Tomography Perfusion in Patients with Acute Ischemic Stroke
Doctoral thesis
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2024Metadata
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- PhD theses (TN-IDE) [24]
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Stroke Mimics and In Depth Analysis of Computed Tomography Perfusion in Patients with Acute Ischemic Stroke by Liv Jorunn Høllesli, Stavanger : University of Stavanger, 2024 (PhD thesis UiS, no. 772)Abstract
Globally, neurological disorders are the leading cause of disability-adjusted life years (DALYs) and the second leading cause of death1. Cerebral stroke is a major contributor to this burden, being the second leading cause of death and the third leading cause of death and disability combined. 85 % of acute cerebral strokes are caused by ischemia. In eligible patients with acute ischemic stroke (AIS), treatment with intravenous thrombolysis (IVT) alone or in combination with mechanical thrombectomy (MT), or MT alone, is indicated4-6. Whether treatment is applied depends on individual patient characteristics, but also largely on imaging results. Importantly, clinical outcomes of therapy are highly time dependent7,8. Therefore, neuroimaging in acute stroke patients should provide rapid, necessary, and precise diagnostic information. Computed tomography (CT) is the preferred imaging modality at many centers.
In AIS, ischemic brain tissue is usually divided into two levels of ischemia: Ischemic penumbra and ischemic core. Ischemic penumbra is hypoperfused but still viable and potentially salvageable ischemic tissue if blood flow is restored timely. The ischemic core is irreversibly damaged ischemic tissue, which cannot be saved, with inevitable development of infarction. The lack of a perfectly reliable definition for ischemic core presents a major challenge in current stroke imaging. Imaging plays a central role in treatment decision in patients with a suspected AIS4-6. Currently used imaging in AIS, including most commonly used perfusion-based parameters, struggle to accurately differentiate between salvageable and non-salvageable tissue10-12. Calculation tools exploring the microvascular environment in AIS has shown to have the capacity to more accurately describe the ischemic brain tissue compared to conventional methods13,14. A better understanding of the microvascular environment during an ischemic event has the potential to select patients for treatment more precisely and to create the possibility for improving recovery after recanalization therapies. Given the vital importance of imaging in the management of AIS patients, there is a growing need of more studies on tissue viability visualization.
At Stavanger University Hospital, patients with a suspected AIS are routinely investigated with a stroke imaging protocol, usually a non-contrast computed tomography (NCCT) of the head, CT angiography (CTA) of precerebral and intracranial arteries, and CT perfusion (CTP). Additionally, magnetic resonance imaging (MRI) including diffusion-weighted imaging (DWI) is performed in most patients, usually within 24 hours after IVT treatment. All consecutive patients with a suspected AIS having received intravenous thrombolysis are prospectively included in a local thrombolysis registry.
Minimizing time from symptom onset to treatment is of great importance in AIS, as clinical outcomes of therapy are highly time dependent. It has been shown that simulation-based team-training can improve team performance. A revised AIS treatment protocol along with weekly simulation-based team-training for the stroke treatment team was implemented at our institution, leading to reduced treatment times, including a reduction of the median door-to-needle time (for IVT treatment) from 27 to 13 minutes.
This thesis is based on three papers. The overall objective for paper I and II was to assess ischemic brain tissue in patients with acute ischemic stroke by utilizing the CTP dataset, MRI and clinical data. Segmentation of the ischemic lesion was the primary objective for paper I, characterization of the ischemic lesion for paper II. In paper III, possible unwanted effects of simulation training were assessed, including the proportion of SMs among IVT-treated patients for presumed AIS, and the proportion of intracranial hemorrhage (ICH) among IVT-treated SMs. The thesis demonstrated the feasibility of using CTP as input to segment the ischemic regions in AIS (paper I), and the potential for a more accurate delineation of the ischemic core using additional parametric calculations (transit time coefficient variation, CoV) compared to conventional parametric measures alone (paper II). Further, implementation of in situ simulation-based team-training for the acute stroke treatment team seems to be safe, but was associated with a significant increase in the proportion of patients treated with IVT who were later diagnosed as SMs, constituted mainly of patients with peripheral vertigo (paper III).
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PhD thesis in Information technology
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Paper I: Tomasetti, L., Høllesli, L. J., Engan, K., Kurz, K. D., Kurz, M. W., & Khanmohammadi, M. (2021). Machine learning algorithms versus thresholding to segment ischemic regions in patients with acute ischemic stroke. IEEE Journal of Biomedical and Health Informatics, 26(2), 660-672.Paper 2: Høllesli LJ, Tomasetti L, Mouridsen KB, Schulz J, Engan K, Khanmohammadi M, Kurz MW, Kurz KD. Is the parametric calculation “transit time coefficient variation” capable of predicting tissue outcome in patients with acute ischemic stroke? Submitted. Journal of Cerebral Blood Flow & Metabolism, March 2024.
Paper 3: Høllesli, L. J., Ajmi, S. C., Kurz, M. W., Tysland, T. B., Hagir, M., Dalen, I., ... & Kurz, K. D. (2022). Simulation‐based team‐training in acute stroke: Is it safe to speed up?. Brain and Behavior, 12(12), e2814.
Publisher
University of Stavanger, NorwaySeries
PhD thesis UiS;;772