Academic Journal
Identifying ex vivo acute ischemic stroke thrombus composition using electrochemical impedance spectroscopy
| Τίτλος: | Identifying ex vivo acute ischemic stroke thrombus composition using electrochemical impedance spectroscopy |
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| Συγγραφείς: | Darcourt, Jean, Brinjikji, Waleed, François, Olivier, Giraud, Alice, Johnson, Collin, R, Patil, Smita, Staessens, Senna, Kadirvel, Ramanathan, Mohammaden, Mahmoud, H, Pisani, Leonardo, Rodrigues, Gabriel, Martins, Cancelliere, Nicole, M, Pereira, Vitor, Mendes, Bozsak, Franz, Doyle, Karen, de Meyer, Simon, F, Messina, Pierluca, Kallmes, David, Cognard, Christophe, Nogueira, Raul, G |
| Συνεισφορές: | Institut des Maladies Métaboliques et Casdiovasculaires (UPS/Inserm U1297 - I2MC), Université Toulouse III - Paul Sabatier (UT3), Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service Neuroradiologie Diagnostique et Thérapeutique CHU Toulouse, Pôle imagerie médicale CHU Toulouse, Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Mayo Clinic Rochester, University of Groningen Groningen, Sensome SAS, National University of Ireland Galway (NUI Galway), Catholic University of Leuven = Katholieke Universiteit Leuven (KU Leuven), Emory University Atlanta, GA, University of Toronto, University of Pittsburgh Medical Center Pittsburgh, PA, États-Unis (UPMC) |
| Πηγή: | ISSN: 1591-0199. |
| Στοιχεία εκδότη: | CCSD Edizioni del Centauro |
| Έτος έκδοσης: | 2025 |
| Συλλογή: | Université Toulouse III - Paul Sabatier: HAL-UPS |
| Θεματικοί όροι: | MESH: Aged, MESH: Dielectric Spectroscopy* / methods, MESH: Prospective Studies, MESH: Sensitivity and Specificity, MESH: Thrombectomy, MESH: Thrombosis* / pathology, MESH: Erythrocytes, MESH: Feasibility Studies, MESH: Female, MESH: Humans, MESH: Ischemic Stroke* / surgery, MESH: Machine Learning, MESH: Male, MESH: Middle Aged, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system |
| Περιγραφή: | International audience ; Background:Intra-procedural characterization of stroke thromboemboli might guide mechanical thrombectomy (MT) device choice to improve recanalization rates. Electrochemical impedance spectroscopy (EIS) has been used to characterize various biological tissues in real time but has not been used in thrombus.Objective:To perform a feasibility study of EIS analysis of thrombi retrieved by MT to evaluate: (1) the ability of EIS and machine learning to predict red blood cell (RBC) percentage content of thrombi and (2) to classify the thrombi as “RBC-rich” or “RBC-poor” based on a range of cutoff values of RBC.Methods:ClotbasePilot was a multicentric, international, prospective feasibility study. Retrieved thrombi underwent histological analysis to identify proportions of RBC and other components. EIS results were analyzed with machine learning. Linear regression was used to evaluate the correlation between the histology and EIS. Sensitivity and specificity of the model to classify the thrombus as RBC-rich or RBC-poor were also evaluated.Results:Among 514 MT,179 thrombi were included for EIS and histological analysis. The mean composition in RBC of the thrombi was 36% ± 24. Good correlation between the impedance-based prediction and histology was achieved (slope of 0.9, R2 = 0.53, Pearson coefficient = 0.72). Depending on the chosen cutoff, ranging from 20 to 60% of RBC, the calculated sensitivity for classification of thrombi ranged from 77 to 85% and the specificity from 72 to 88%.Conclusion:Combination of EIS and machine learning can reliably predict the RBC composition of retrieved ex vivo AIS thrombi and then classify them into groups according to their RBC composition with good sensitivity and specificity. |
| Τύπος εγγράφου: | article in journal/newspaper |
| Γλώσσα: | English |
| Relation: | info:eu-repo/semantics/altIdentifier/pmid/37192738; PUBMED: 37192738; PUBMEDCENTRAL: PMC12475314 |
| DOI: | 10.1177/15910199231175377 |
| Διαθεσιμότητα: | https://ut-toulouseinp.hal.science/hal-04935801 https://ut-toulouseinp.hal.science/hal-04935801v1/document https://ut-toulouseinp.hal.science/hal-04935801v1/file/Darcourt_2023.pdf https://doi.org/10.1177/15910199231175377 |
| Rights: | https://creativecommons.org/licenses/by-nc/4.0/ ; info:eu-repo/semantics/OpenAccess |
| Αριθμός Καταχώρησης: | edsbas.E035AAEA |
| Βάση Δεδομένων: | BASE |
| DOI: | 10.1177/15910199231175377 |
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