ArticleJournal of neurointerventional surgery2023
Impedance-based sensors discriminate among different types of blood thrombi with very high specificity and sensitivity.
Article in Journal of neurointerventional surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 13 citations in OpenAlex.
- Transforming stroke care: the promise of feedback-guided thrombolytic nanomedicine.Journal of nanobiotechnology · 2026Review
- Electrical impedance spectroscopy signatures of red blood cells and platelets in acute ischemic stroke clots in the Clotbase International Registry: Significance for etiology and first pass effect.Journal of neurointerventional surgery · 2026Article
- Identifying ex vivo acute ischemic stroke thrombus composition using electrochemical impedance spectroscopy.Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences · 2025Article
- Potential of Guidewire-Clot Interaction Forces for Clot Detection in Robotic Mechanical Thrombectomy.The international journal of medical robotics + computer assisted surgery : MRCAS · 2025Article
- The use of the NeVa stent-retriever for bail-out mechanical thrombectomy.Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences · 2025Article
- Can micro-guidewire advancement forces predict clot consistency and location to assist the first-line technique for mechanical thrombectomy?Journal of neurointerventional surgery · 2025Article
- Detection of Blood Clots Using a Whole Stent as an Active Implantable Biosensor.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Electrical impedance measurements can identify red blood cell-rich content in acute ischemic stroke clotsResearch and practice in thrombosis and haemostasis · 2024Article
- Granulocytes-Rich Thrombi in Cerebral Large Vessel Occlusion Are Associated with Increased Stiffness and Poorer Revascularization Outcomes.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2023Article
- First Experience with the Nimbus Stentretriever : A Novel Device to Handle Fibrin-rich Clots.Clinical neuroradiology · 2023Article
- Unmet Needs in Acute Ischemic Stroke: Overcoming Recalcitrant Clots.Cardiology in reviewReview
Corrections and comments
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Authors and funding
14 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIntracranial occlusion recanalization fails in 20% of endovascular thrombectomy procedures, and thrombus composition is likely to be an important factor. In this study, we demonstrate that the combination of electrical impedance spectroscopy (EIS) and machine learning constitutes a novel and highly accurate method for the identification of different human thrombus types.
methods134 samples, subdivided into four categories, were analyzed by EIS: 29 'White', 26 'Mixed', 12 'Red' thrombi, and 67 liquid 'Blood' samples. Thrombi were generated in vitro using citrated human blood from five healthy volunteers. Histological analysis was performed to validate the thrombus categorization based on red blood cell content. A machine learning prediction model was trained on impedance data to differentiate blood samples from any type of thrombus and in between the four sample categories.
resultsHistological analysis confirmed the similarity between the composition of in vitro generated thrombi and retrieved human thrombi. The prediction model yielded a sensitivity/specificity of 90%/99% for distinguishing blood samples from thrombi and a global accuracy of 88% for differentiating among the four sample categories.
conclusionsCombining EIS measurements with machine learning provides a highly effective approach for discriminating among different thrombus types and liquid blood. These findings raise the possibility of developing a probe-like device (eg, a neurovascular guidewire) integrating an impedance-based sensor. This sensor, placed in the distal part of the smart device, would allow the characterization of the probed thrombus on contact. The information could help physicians identify optimal thrombectomy strategies to improve outcomes for stroke patients.
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