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Regional blood circulation and microcirculation

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Software and hardware platform for real time evaluation of cerebral auto-regulation

https://doi.org/10.24884/1682-6655-2023-22-1-110-115

Abstract

Data processing systems for non-invasive evaluation of cerebral autoregulation are time-consuming and take 2–3 hours to collect, convert and process the data. Development of systems of real-time evaluation of cerebral autoregulation seems to be critical to reduce the time of data processing, obtaining results and to monitor its parameters in functional tests and monitoring the treatment of patients in intensive care units. The developed software and hardware platform of real-time non-invasive evaluation of cerebral autoregulation based on continuous recording of the phase shift between the linear blood flow velocity in the arteries at the base of the brain and systemic arterial pressure uses Fourier and wavelet transform in the Mayer wave range. The hardware-software complex was shown to be effective and informative under standardized loads and can be used to real-time diagnose the state of cerebral autoregulation and to study the mechanisms of regulation of cerebral blood flow in healthy volunteers.

About the Authors

V. B. Semenyutin
Almazov National Medical Research Centre
Russian Federation

Semenyutin Vladimir B. – doctor of biological sciences, professor, head of the research laboratory of cerebrovascular pathology

2, Akkuratova str., Saint Petersburg, 197341



V. I. Antonov
Peter the Great St. Petersburg Polytechnic University
Russian Federation

Antonov Valeriy I. – doctor of technical sciences, professor, head of the department of higher mathematics

29, Politehnicheskaya str., Saint Petersburg, 195251



A. A. Vesnina
Almazov National Medical Research Centre
Russian Federation

Vesnina Anastasiya A. – Junior Researcher, Research Laboratory of Cerebral Circulation Pathology

29, Politehnicheskaya str., Saint Petersburg, 195251



G. F. Malykhina
Peter the Great St. Petersburg Polytechnic University
Russian Federation

Malykhina Galina F. – Doctor of Technical Sciences, Professor, Professor of the Higher School of Cyber-Physical Systems and Control

29, Politehnicheskaya str., Saint Petersburg, 195251 



A. A. Nikiforova
Almazov National Medical Research Centre
Russian Federation

Nikiforova Anna A. – Senior Researcher, Research Laboratory of Cerebral Circulation Pathology, PhD

2, Akkuratova str., Saint Petersburg, 197341



G. K. Panuntsev
Almazov National Medical Research Centre
Russian Federation

Panuntsev Grigory K. – Senior Researcher, Research Laboratory of Cerebral Circulation Pathology, PhD

2, Akkuratova str., Saint Petersburg, 197341



V. Yu. Salnikov
Peter the Great St. Petersburg Polytechnic University
Russian Federation

Salnikov Vyacheslav Yu. – Candidate of Technical Sciences, Associate Professor of the Higher School of Cyber-Physical Systems and Control

29, Politehnicheskaya str., Saint Petersburg, 195251



References

1. Ortega-Gutierrez S., Peterson N., Masurkar A. et al. Reiability, Asymmetry, and Age Influence on Dynamic Cerebral Autoregulation Measured by Spontaneous Fluctuations of Blood Pressure and Cerebral Blood Flow Velocities in Healthy Individuals J. Neuroimaging. 2014;24(4):379-86. DOI: 10.1111/jon.12019.

2. Semenyutin V.B., Asaturyan G.A., Nikiforova A.A., Aliev V.A., Panuntsev G.K., Iblyaminov V.B., Savello A.V., Patzak A. Predictive Value of Dynamic Cerebral Autoregulation Assessment in Surgical Management of Patients with HighGrade Carotid Artery Stenosis Front. Physiol. 2017;8:1–10. DOI: 10.3389/fphys.2017.00872.

3. Claassen J.A.H.R., Thijssen D.H.J., Panerai R.B., Faraci F.M. Regulation of cerebral blood flow in humans: physiology and clinical implications of autoregulation. Physiol. Rev. 2021;101(4):1487–1559. DOI: 10.1152/physrev.00022.2020.

4. Nogueira R.C., Aries M., Minhas J.S., Peterson N.H., Xiong L., Kainerstorfer J.M., Castro P. Review of studies on dynamic cerebral autoregulation in the acute phase of stroke and the relationship with clinical outcome. J. Cereb. Blood Flow Metab. 2022;42(3):430-453. DOI: 10.1177/ 0271678X211045222.

5. Fan J., Brassard P., Rickards C., Nogueira R. et al. Integrative cerebral blood flow regulation in ischemic stroke. J. Cerebral Blood Flow Metab. 2022;42(3):387–403. DOI: 10.1177/0271678X211032029.

6. Papaioannou V., Budohoski K., Placek M. et al. Association of transcranial Doppler blood flow velocity slow waves with delayed cerebral ischemia in patients suffering from subarachnoid hemorrhage: a retrospective study. Intensive Care Med. Exp. 2021;9:11. DOI: 10.1186/s40635-021-00378-8.

7. Lidington D., Wan H., Bolz S.S. Cerebral Autoregulation in Subarachnoid Hemorrhage Front. Neurol. 12:688362. DOI: 10.3389/fneur.2021.688362

8. Longhitano Y., Iannuzzi F., Bonatti G., Zanza C., Messina A., Godoy D., Dabrowski W., Xiuyun L., Czosnyka M., Pelosi P., Badenes R., Robba C. Cerebral Autoregulation in Non-Brain Injured Patients: A Systematic Review. Front. Neurol. 2021;12:732176. DOI: 10.3389/fneur.2021.732176.

9. Panerai R., Intharakham K., Minhas J., Llwyd O., Salinet A., Katsogridakis E., Maggio P., Robinson T. COHmax: an algorithm to maximise coherence in estimates of dynamic cerebral autoregulation Physiol. Meas. 2020;41 085003. DOI: 10.1088/1361-6579/aba67e.

10. Sanders M.L., Claassen J., Aries M. et al. Reproducibility of dynamic cerebral autoregulation parameters: a multi-centre, multi-method study. Physiol. Meas. 2018; 39(12):125002. DOI:10.1088/1361-6579/aae9fd

11. Smielewski P., Czosnyka M., Steiner L., Belestri M., Piechnik S., Pickard J.D. ICM+ software for on-line analysis of bedside monitoring data after severe head trauma // In: Intracranial pressure and brain monitoring XII. Springer Vienna; 2005:43–49.

12. Diehl R. Cerebral autoregulation in clinical practice. Europ. J. Ultrasound. 2002;16(1-2):31–36. DOI: 10.1016/ s0929-8266(02)00048-4.

13. Gooskens I., Schmidt E., Czosnyka M. et al. Pressureautoregulation, CO2 reactivity and asymmetry of haemodynamic parameters in patients with carotid artery stenotic disease. A clinical appraisal. ActaNeurochir (Wien). 2003; 145(7):527-32. DOI: 10.1007/s00701-003-0045-y.

14. Czosnyka M., Smielewski P., Lavinio A. et al. An assessment of dynamic autoregulation from spontaneous fluctuations of cerebral blood flow velocity: a comparison of two models, index of autoregulation and mean flow index. Anesth. Analg. 2008;106(1):234–239. DOI: 10.1213/01.ane. 0000295802.89962.13.


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For citations:


Semenyutin V.B., Antonov V.I., Vesnina A.A., Malykhina G.F., Nikiforova A.A., Panuntsev G.K., Salnikov V.Yu. Software and hardware platform for real time evaluation of cerebral auto-regulation. Regional blood circulation and microcirculation. 2023;22(1):110-115. (In Russ.) https://doi.org/10.24884/1682-6655-2023-22-1-110-115

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ISSN 1682-6655 (Print)
ISSN 2712-9756 (Online)