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Differentiation between true microembolic signals and artefacts using an arbitrary sample volume
D Georgiadis1, F Uhlmann, A Lindner
1Department of Neurology, Martin-Luther University of Halle-Wittenberg, Halle/Saale, Germany. dimitrios.georgiadis@medizin.uni-halle.de
Abstract:
We evaluated a new discrimination technique between microemboli (MES) and artefact signals. Monitoring was performed over the middle cerebral artery (55 mm) and the brain parenchyma (29 mm). Intensity changes were expressed as percent of change compared to the value measured in the proximal depth. The cut-off value providing the highest sensitivity and specificity in the differentiation was evaluated using 250 MES and 250 artefact signals, and subsequently analysed in the first part of the study. Intensity values derived from the distal depth were subsequently evaluated in 10 patients undergoing cardiac surgery and 45 patients with potential arterial or cardioembolic source. Intensity changes of 87% (84%-90%) and -58% (-71%-(-48%)) were measured in the initial 500 signals for MES and artefact signals, respectively. The best intensity cut-off value was calculated at 27%. This value was subsequently applied to a total of 1858 MES and 1958 artefacts, resulting to sensitivity and specificity of 96% and 98%, respectively. The proposed technique provided adequate results, warranting further evaluation.
Insights
This study introduces a new technique to distinguish microemboli (MES) from artefact signals using intensity changes. The method achieved high sensitivity and specificity, proving effective for monitoring brain blood flow.
Area of Science:
- Neuroscience
- Medical Imaging
- Biomedical Engineering
Background:
- Distinguishing microemboli (MES) from artefacts is crucial for accurate neurological monitoring.
- Existing methods may lack the sensitivity or specificity required for reliable differentiation.
- Cerebral blood flow monitoring is essential in various clinical scenarios.
Purpose of the Study:
- To evaluate a novel technique for discriminating between microemboli (MES) and artefact signals.
- To determine the optimal intensity change cut-off for differentiating MES and artefacts.
- To assess the sensitivity and specificity of this technique in clinical settings.
Main Methods:
- Monitoring was conducted on the middle cerebral artery and brain parenchyma.
- Intensity changes were measured as a percentage of proximal depth values.
- A cut-off value was determined using a dataset of 250 MES and 250 artefact signals.
- The technique was further validated in patients undergoing cardiac surgery and those with embolic sources.
Main Results:
- Microemboli (MES) signals showed an 87% intensity change, while artefact signals showed a -58% change.
- An optimal intensity cut-off value of 27% was identified.
- Applied to over 3700 signals, the technique achieved 96% sensitivity and 98% specificity.
- The method demonstrated high accuracy in differentiating MES from artefacts.
Conclusions:
- The developed technique effectively discriminates between microemboli (MES) and artefact signals.
- The identified intensity cut-off provides high sensitivity and specificity.
- This method shows promise for improving the accuracy of cerebral blood flow monitoring and warrants further investigation.