Approaches to classification of microembolic signals in patients recovering from ischemic stroke
- Authors: Orlova E.V.1, Berdalin A.B.1, Lelyuk V.G.1
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Affiliations:
- Federal Сenter of Brain Research and Neurotechnologies
- Issue: Vol 17, No 3 (2023)
- Pages: 74-82
- Section: Technologies
- URL: https://ogarev-online.ru/2075-5473/article/view/253962
- DOI: https://doi.org/10.54101/ACEN.2023.3.9
- ID: 253962
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Abstract
Introduction. Microembolus detection by transcranial Doppler (TCD) is the only non-invasive modality for visualization of cerebral embolism. Currently, there is no unified classification of recorded microembolic signals (MES) that could be used in clinical practice.
The aim of the study is to investigate biophysical MES parameters in patients with ischemic stroke, as well as to assess approaches to microemboli differentiation by structure and origin to improve the diagnostic accuracy of the method and to reduce the risk of recurrent ischemic events.
Materials and methods. The inclusion criterion was TCD-detected signs of MES. We analyzed the data of 28 patients with ischemic stroke (9 women and 19 men; mean age was 58 years ± 13). We recorded power, duration, and frequency for each MES, and calculated an energy index.
Results. A total of 938 MES were reported. In patients with cardioembolic stroke and all other pathogenetic stroke subtypes, biophysical parameter limits were as follows: 14.65 dB for the average power, 9.45 ms for the average duration, and 0.16 J for the average energy index. For patients with atrial fibrillation, characteristic MES power was found to be >13 dB. The MES frequency limit was determined to be 650 Hz for microemboli differentiation by acoustic density.
Conclusion. The data obtained can be used to further search for optimal limit ranges for biophysical parameters of various MES in order to establish a single MES classification, which will increase the diagnostic value of microembolus detection by TCD in stroke treatment practice.
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##article.viewOnOriginalSite##About the authors
Ekaterina V. Orlova
Federal Сenter of Brain Research and Neurotechnologies
Author for correspondence.
Email: ekaterina.shlyk@gmail.com
ORCID iD: 0000-0002-4755-7565
SPIN-code: 3695-9148
Cand. Sci. (Med.), doctor of functional diagnostics, Department of ultrasound and functional diagnostics, Federal Center for Brain and Neurotechnologies, Moscow, Russia
Russian Federation, MoscowAlexandr B. Berdalin
Federal Сenter of Brain Research and Neurotechnologies
Email: alex_berdalin@mail.ru
ORCID iD: 0000-0001-5387-4367
SPIN-code: 3681-6911
Cand. Sci. (Med.), senior researcher Research Center for Radiology and Clinical Physiology, Federal Center for Brain and Neurotechno- logies, Moscow, Russia
Russian Federation, MoscowVladimir G. Lelyuk
Federal Сenter of Brain Research and Neurotechnologies
Email: vglelyuk@fccps.ru
ORCID iD: 0000-0002-9690-8325
SPIN-code: 1066-9840
D. Sci. (Med.), Professor
Russian Federation, MoscowReferences
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