Electrical impedance measurements can identify red blood cell-rich content in acute ischemic stroke clots
acute ischemic stroke
clot composition
electrical impedance
first-pass effect
mechanical thrombectomy
Journal
Research and practice in thrombosis and haemostasis
ISSN: 2475-0379
Titre abrégé: Res Pract Thromb Haemost
Pays: United States
ID NLM: 101703775
Informations de publication
Date de publication:
Mar 2024
Mar 2024
Historique:
received:
22
02
2024
accepted:
07
03
2024
medline:
15
4
2024
pubmed:
15
4
2024
entrez:
15
4
2024
Statut:
epublish
Résumé
Electrochemical impedance spectroscopy can determine characteristics such as cell density, size, and shape. The development of an electrical impedance-based medical device to estimate acute ischemic stroke (AIS) clot characteristics could improve stroke patient outcomes by informing clinical decision making. To assess how well electrical impedance combined with machine learning identified red blood cell (RBC)-rich composition of AIS clots A total of 253 clots from 231 patients who underwent thrombectomy in 5 hospitals in France, Japan, Serbia, and Spain between February 2021 and October 2023 were analyzed in the Clotbase International Registry. Electrical impedance measurements were taken following clot retrieval by thrombectomy, followed by Martius Scarlet Blue staining. The clot components were quantified via Orbit Image Analysis, and RBC percentages were correlated with the RBC estimations made by the electrical impedance machine learning model. Quantification by Martius Scarlet Blue staining identified RBCs as the major component in clots (RBCs, 37.6%; white blood cells, 5.7%; fibrin, 25.5%; platelets/other, 30.3%; and collagen, 1%). The impedance-based RBC estimation correlated well with the RBC content determined by histology, with a slope of 0.9 and Spearman's correlation of r = 0.7. Clots removed in 1 pass were significantly richer in RBCs and clots with successful recanalization in 1 pass (modified first-pass effect) were richer in RBCs as assessed using histology and impedance signature. Electrical impedance estimations of RBC content in AIS clots are consistent with histologic findings and may have potential for clinically relevant parameters.
Sections du résumé
Background
UNASSIGNED
Electrochemical impedance spectroscopy can determine characteristics such as cell density, size, and shape. The development of an electrical impedance-based medical device to estimate acute ischemic stroke (AIS) clot characteristics could improve stroke patient outcomes by informing clinical decision making.
Objectives
UNASSIGNED
To assess how well electrical impedance combined with machine learning identified red blood cell (RBC)-rich composition of AIS clots
Methods
UNASSIGNED
A total of 253 clots from 231 patients who underwent thrombectomy in 5 hospitals in France, Japan, Serbia, and Spain between February 2021 and October 2023 were analyzed in the Clotbase International Registry. Electrical impedance measurements were taken following clot retrieval by thrombectomy, followed by Martius Scarlet Blue staining. The clot components were quantified via Orbit Image Analysis, and RBC percentages were correlated with the RBC estimations made by the electrical impedance machine learning model.
Results
UNASSIGNED
Quantification by Martius Scarlet Blue staining identified RBCs as the major component in clots (RBCs, 37.6%; white blood cells, 5.7%; fibrin, 25.5%; platelets/other, 30.3%; and collagen, 1%). The impedance-based RBC estimation correlated well with the RBC content determined by histology, with a slope of 0.9 and Spearman's correlation of r = 0.7. Clots removed in 1 pass were significantly richer in RBCs and clots with successful recanalization in 1 pass (modified first-pass effect) were richer in RBCs as assessed using histology and impedance signature.
Conclusion
UNASSIGNED
Electrical impedance estimations of RBC content in AIS clots are consistent with histologic findings and may have potential for clinically relevant parameters.
Identifiants
pubmed: 38617048
doi: 10.1016/j.rpth.2024.102373
pii: S2475-0379(24)00062-1
pmc: PMC11015511
doi:
Types de publication
Journal Article
Langues
eng
Pagination
102373Informations de copyright
© 2024 The Author(s).