Literature DB >> 28440860

Doppler ultrasonographic measurement of short-term effects of valsalva maneuver on retrobulbar blood flow.

Sabit Kimyon1, Ahmet Mete2, Alper Mete1, Duçem Mete3.   

Abstract

BACKGROUND: To investigate the effects of Valsalva maneuver (VM) on retrobulbar blood flow parameters in healthy subjects.
METHODS: Participants without any ophthalmologic or systemic pathology were examined in supine position with color and pulsed Doppler imaging for blood flow measurement, via a paraocular approach, in the ophthalmic artery (OA), central retinal artery (CRA), central retinal vein (CRV), nasal posterior ciliary artery (NPCA), and temporal posterior ciliary artery (TPCA), 10 seconds after a 35- to 40-mm Hg expiratory pressure was reached. Peak systolic velocity (PSV), end-diastolic velocity (EDV), pulsatility index (PI), and resistivity index (RI) values were recorded for each artery. PSV and EDV values were recorded for CRV.
RESULTS: There were significant differences between resting and VM values of PSV and EDV of CRA, RI of NPCA, and PI, RI, and EDV of TPCA. Resting CRA-EDV, CRV-PSV, and CRV-EDV were positively correlated whereas resting OA-PSV and CRA-PI, and OA-PSV, CRA-PSV, and CRA-EDV during VM, were negatively correlated with age.
CONCLUSIONS: VM induces a short-term increase in CRA blood flow and a decrease in NPCA and TPCA RI. Additional studies with a longer Doppler recording during VM, in a larger population sample, are required to allow definitive interpretation.
© 2017 Wiley Periodicals, Inc. J Clin Ultrasound 45:551-555, 2017. © 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  Valsalva maneuver; blood flow parameters; color Doppler imaging; retrobulbar blood flow

Mesh:

Year:  2017        PMID: 28440860     DOI: 10.1002/jcu.22487

Source DB:  PubMed          Journal:  J Clin Ultrasound        ISSN: 0091-2751            Impact factor:   0.910


  1 in total

Review 1.  Neurodegenerative Disorders of the Eye and of the Brain: A Perspective on Their Fluid-Dynamical Connections and the Potential of Mechanism-Driven Modeling.

Authors:  Giovanna Guidoboni; Riccardo Sacco; Marcela Szopos; Lorenzo Sala; Alice Chandra Verticchio Vercellin; Brent Siesky; Alon Harris
Journal:  Front Neurosci       Date:  2020-11-12       Impact factor: 4.677

  1 in total

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