ABSTRACT NUMBER: ESOC2026A1240 HEMODYNAMIC PHANTOM FOR TESTING MICROEMBOLI DETECTION BY TRANSCRANIAL DOPPLER

Abstract Background and aims Transcranial Doppler (TCD)–detected microembolic signals (MES) are strong predictors of future cerebrovascular events. However, the accuracy, differentiation and comparability of MES detection across different TCD systems remain insufficiently validated. We aimed to develop and test a novel hemodynamic phantom allowing precise and reproducible delivery of predefined number of gaseous and solid microemboli to assess the accuracy of TCD-based MES detection. Methods A hemodynamic system was constructed using dual pumps to generate controlled pulsatile flow and a 3D-printed model simulating cranial bone and intracranial arteries, with porcine blood as the circulating medium. Controlled injections of air bubbles and solid microemboli (thrombotic and polymer-based) were performed. Three commercially available TCD systems (DWL T1, DWL T2, and Delica) were evaluated for their ability to detect and differentiate MES using automatic embolus detection algorithms. Results were compared with expert sonographer assessment based on spectral analysis. Results All TCD systems reliably detected MES showers. However, automatic embolus detection failed to differentiate air from thrombotic MES, and polymer-based MES were undetectable by all systems. Expert spectral analysis identified significantly more gaseous (mean 14.7±8.3 vs. 1.4±2.3 MES/s; p < 0.05) and solid thrombotic MES (mean 7.9±6.3 vs. 0.3±0.4 MES/s; p < 0.05) than automatic detection. Conclusions This novel hemodynamic phantom enables standardized testing of TCD MES detection accuracy. Expert spectral analysis markedly outperforms automated detection algorithms, highlighting important limitations of current TCD systems with direct implications for clinical risk stratification and device validation. Supported by the Czech Health Research Council grant No. NU22-04-00389. Conflict of interest David Skoloudik: nothing to disclose. Roman Matejka: nothing to disclose. David Pakizer: nothing to disclose. Istvan Szegedi: nothing to disclose. Adam Skoloudik@nothing to disclose. David Netuka: nothing to disclose.

Authors

Institutions

Publication Details

Journal
European Stroke Journal
Published
2026-05-01
DOI
https://doi.org/10.1093/esj/aakag023.605
Primary Topic
Cerebrovascular and Carotid Artery Diseases
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ABSTRACT NUMBER: ESOC2026A1240 HEMODYNAMIC PHANTOM FOR TESTING MICROEMBOLI DETECTION BY TRANSCRANIAL DOPPLER

David Pakizer, Roman Matějka, István Szegedi, Adam Školoudík et al.
European Stroke Journal
Cerebrovascular and Carotid Artery Diseases
article

ABSTRACT NUMBER: ESOC2026A1240 HEMODYNAMIC PHANTOM FOR TESTING MICROEMBOLI DETECTION BY TRANSCRANIAL DOPPLER

David Pakizer, Roman Matějka, István Szegedi, Adam Školoudík, David Školoudík, David Netuka
article en

Abstract

Abstract Background and aims Transcranial Doppler (TCD)–detected microembolic signals (MES) are strong predictors of future cerebrovascular events. However, the accuracy, differentiation and comparability of MES detection across different TCD systems remain insufficiently validated. We aimed to develop and test a novel hemodynamic phantom allowing precise and reproducible delivery of predefined number of gaseous and solid microemboli to assess the accuracy of TCD-based MES detection. Methods A hemodynamic system was constructed using dual pumps to generate controlled pulsatile flow and a 3D-printed model simulating cranial bone and intracranial arteries, with porcine blood as the circulating medium. Controlled injections of air bubbles and solid microemboli (thrombotic and polymer-based) were performed. Three commercially available TCD systems (DWL T1, DWL T2, and Delica) were evaluated for their ability to detect and differentiate MES using automatic embolus detection algorithms. Results were compared with expert sonographer assessment based on spectral analysis. Results All TCD systems reliably detected MES showers. However, automatic embolus detection failed to differentiate air from thrombotic MES, and polymer-based MES were undetectable by all systems. Expert spectral analysis identified significantly more gaseous (mean 14.7±8.3 vs. 1.4±2.3 MES/s; p < 0.05) and solid thrombotic MES (mean 7.9±6.3 vs. 0.3±0.4 MES/s; p < 0.05) than automatic detection. Conclusions This novel hemodynamic phantom enables standardized testing of TCD MES detection accuracy. Expert spectral analysis markedly outperforms automated detection algorithms, highlighting important limitations of current TCD systems with direct implications for clinical risk stratification and device validation. Supported by the Czech Health Research Council grant No. NU22-04-00389. Conflict of interest David Skoloudik: nothing to disclose. Roman Matejka: nothing to disclose. David Pakizer: nothing to disclose. Istvan Szegedi: nothing to disclose. Adam Skoloudik@nothing to disclose. David Netuka: nothing to disclose.

European Stroke JournalVol. 11(Supplement_1)
VSB - Technical University of Ostrava (CZ), University of Ostrava (CZ), Military University Hospital Prague (CZ), Czech Technical University in Prague (CZ)
Openalex Percentile: Top 9%
Cerebrovascular and Carotid Artery Diseases
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.