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Water content for clot composition prediction in acute ischemic stroke.
- Source :
-
PloS one [PLoS One] 2024 May 24; Vol. 19 (5), pp. e0304520. Date of Electronic Publication: 2024 May 24 (Print Publication: 2024). - Publication Year :
- 2024
-
Abstract
- Background: Mechanical thrombectomy (MT) has become the gold standard care for treating acute ischemic stroke (AIS) due to large vessel occlusion. Emerging evidence suggests that understanding the composition of clots prior to intervention could be useful for the selection of neuroendovascular techniques, potentially improving the efficacy of treatments. However, current imaging modalities lack the ability to distinguish clot composition accurately and reliably. Since water content can influence signal intensity on CT and MRI scans, its assessment may provide indirect clues about clot composition. This study aimed to elucidate the correlation between water content and clot composition using human clots retrieved from stroke patients and experimentally generated ovine clots.<br />Materials and Methods: This study involved an analysis of ten clots retrieved from patients with AIS undergoing MT. Additionally, we created ten red blood cells (RBC)-rich and ten fibrin-rich ovine blood clots, which were placed in a human intracranial vascular model under realistic flow conditions. The water content and compositions of these clots were evaluated, and linear regression analyses were performed to determine the relationship between clot composition and water content.<br />Results: The regression analysis in human stroke clots revealed a significant negative association between RBC concentration and water content. We also observed a positive correlation between water content and both fibrin and platelets in ovine blood clots. Conclusion.<br />Competing Interests: The authors have declared that no competing interests exist.<br /> (Copyright: © 2024 Sakuta et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Details
- Language :
- English
- ISSN :
- 1932-6203
- Volume :
- 19
- Issue :
- 5
- Database :
- MEDLINE
- Journal :
- PloS one
- Publication Type :
- Academic Journal
- Accession number :
- 38787842
- Full Text :
- https://doi.org/10.1371/journal.pone.0304520