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Validity of transcranial Doppler ultrasonography-determined dynamic cerebral autoregulation estimated using transfer function analysis

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Abstract

Transcranial Doppler ultrasonography (TCD) is used widely to evaluate dynamic cerebral autoregulation (dCA). However, the validity of TCD-determined dCA remains unknown because TCD is only capable of measuring blood velocity and thus only provides an index as opposed to true blood flow. To test the validity of TCD-determined dCA, in nine healthy subjects, dCA was evaluated by transfer function analysis (TFA) using cerebral blood flow (CBF) or TCD-measured cerebral blood velocity during a perturbation that induces reductions in TCD-determined dCA, lower body negative pressure (LBNP) at two different stages: LBNP − 15 mmHg and − 50 mmHg. Internal carotid artery blood flow (ICA Q) was assessed as an index of CBF using duplex Doppler ultrasound. The TFA low frequency (LF) normalized gain (ngain) calculated using ICA Q increased during LBNP at − 50 mmHg (LBNP50) from rest (P = 0.005) and LBNP at − 15 mmHg (LBNP15) (P = 0.015), indicating an impaired dCA. These responses were the same as those obtained using TCD-measured cerebral blood velocity (from rest and LBNP15; P = 0.001 and P = 0.015). In addition, the ICA Q-determined TFA LF ngain from rest to LBNP50 was significantly correlated with TCD-determined TFA LF ngain (r = 0.460, P = 0.016) despite a low intraclass correlation coefficient. Moreover, in the Bland–Altman analysis, the difference in the TFA LF ngains determined by blood flow and velocity was within the margin of error, indicating that the two measurement methods can be interpreted as equivalent. These findings suggest that TCD-determined dCA can be representative of actual dCA evaluated with CBF.

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Acknowledgments

The authors appreciate the time and effort expended by the volunteer subjects and staffs. Also, the authors would like to thank Prof. Paul Fadel (University of Texas at Arlington) for his helpful scientific comments for improving this manuscript.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This study was in part supported by a Grant-in-Aid for Scientific Research from the Japanese Ministry of Education, Culture, Sports, Science and Technology (Grant Number 15H003098).

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Authors and Affiliations

  1. Department of Biomedical Engineering, Toyo University, 2100 Kujirai, Kawagoe-Shi, Saitama, 350-8585, Japan

    Hironori Watanabe, Takuro Washio, Shotaro Saito & Shigehiko Ogoh

  2. Research Fellow of Japan Society for the Promotion of Science, Tokyo, Japan

    Takuro Washio

  3. Department of Health and Welfare, Faculty of Health Sciences, Kyorin University, Tokyo, Japan

    Ai Hirasawa

  4. Department of Physical Therapy, Faculty of Health Science, Kyorin University, Tokyo, Japan

    Rina Suzuki & Shigeki Shibata

  5. Department of Kinesiology, University of Texas at Arlington, Arlington, TX, USA

    R. Matthew Brothers

  6. Neurovascular Research Laboratory, Faculty of Life Sciences and Education, University of South Wales, Pontypridd, UK

    Shigehiko Ogoh

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  1. Hironori Watanabe
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Contributions

HW and SO conception and design of research; HW, TW, SS, AH, RS, SS, SO performed experiments; HW analyzed data; HW and SO interpreted results of experiments; HW prepared figures; HW, MB, SO drafted manuscript; all authors edited and revised manuscript; all authors approved final version of manuscript.

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Correspondence to Shigehiko Ogoh.

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The authors declare no conflicts of interest related to the subject matter or materials discussed in this article. All data of the present study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation.

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This study was approved by the ethics committee of Kyorin University (Approval Number 723) in accordance with the Declaration of Helsinki.

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Watanabe, H., Washio, T., Saito, S. et al. Validity of transcranial Doppler ultrasonography-determined dynamic cerebral autoregulation estimated using transfer function analysis. J Clin Monit Comput 36, 1711–1721 (2022). https://doi.org/10.1007/s10877-022-00817-1

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