Relationship between Myogenic Reaction and Autoregulation of Cerebral Circulation

Александрин, В. В.

doi:10.1007/s10517-010-1095-9

Cited by 3 publications

(7 citation statements)

References 7 publications

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“…The studies with animal cohorts utilized various animals, including albino mature outbred male rats [ 99 ], Wistar male rats [ 101 ], female hooded lister rats [ 102 ], and, in one instance, goats [ 100 ]. The studies measured either CBF with a laser Doppler flowmetry [ 99 , 102 ] or an electromagnetic flow probe [ 100 ], or CBFv using a TCD probe [ 101 ]. All studies carried out modeling tasks and reported an effective modeling of CBFv or CBF signals to assess CA.…”

Section: Resultsmentioning

confidence: 99%

“…Wavelet analysis was employed by Alexandrin to study the myogenic response of pial arteries [ 99 ]. Doblar et al employed Fourier analysis to examine the effects of hypoxia on the dynamic characteristics of cerebrovascular responses [ 100 ].…”

Section: Resultsmentioning

confidence: 99%

“…Details of the included studies can be found in Supplementary Appendix SB, in Tables S1-S8. In this systematic review, 38 of the included studies investigated healthy population data [1,13,, 46 studied patient populations [2,3,, while the remaining 4 studies focused on animal subjects [99][100][101][102]. Figure 2 illustrates the distribution of studies based on the methods employed in their research as well as the medical diagnostic tests with respect to the studied pathology.…”

Section: Resultsmentioning

confidence: 99%

“…Notably, TFA was the focus of investigation in six studies conducted on healthy cohorts [ 19 , 26 , 32 , 43 , 47 , 54 ] and four studies on patient cohorts [ 56 , 65 , 78 , 82 ]. Wavelet analysis emerged as another prominent technique, featuring nine studies conducted on healthy cohorts [ 1 , 21 , 22 , 23 , 28 , 36 , 50 , 52 , 53 ], four studies on patient cohorts [ 64 , 69 , 90 , 92 ], and one study conducted on an animal cohort [ 99 ]. Furthermore, variations in AR models for time-series modeling were explored in six studies involving healthy cohorts [ 27 , 30 , 31 , 37 , 38 , 46 ] and five studies focusing on patient cohorts [ 59 , 80 , 89 , 95 , 96 ].…”

Section: Discussionmentioning

confidence: 99%

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Time-Series Modeling and Forecasting of Cerebral Pressure–Flow Physiology: A Scoping Systematic Review of the Human and Animal Literature

Vakitbilir,

Froese,

Gomez

et al. 2024

Sensors

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The modeling and forecasting of cerebral pressure–flow dynamics in the time–frequency domain have promising implications for veterinary and human life sciences research, enhancing clinical care by predicting cerebral blood flow (CBF)/perfusion, nutrient delivery, and intracranial pressure (ICP)/compliance behavior in advance. Despite its potential, the literature lacks coherence regarding the optimal model type, structure, data streams, and performance. This systematic scoping review comprehensively examines the current landscape of cerebral physiological time-series modeling and forecasting. It focuses on temporally resolved cerebral pressure–flow and oxygen delivery data streams obtained from invasive/non-invasive cerebral sensors. A thorough search of databases identified 88 studies for evaluation, covering diverse cerebral physiologic signals from healthy volunteers, patients with various conditions, and animal subjects. Methodologies range from traditional statistical time-series analysis to innovative machine learning algorithms. A total of 30 studies in healthy cohorts and 23 studies in patient cohorts with traumatic brain injury (TBI) concentrated on modeling CBFv and predicting ICP, respectively. Animal studies exclusively analyzed CBF/CBFv. Of the 88 studies, 65 predominantly used traditional statistical time-series analysis, with transfer function analysis (TFA), wavelet analysis, and autoregressive (AR) models being prominent. Among machine learning algorithms, support vector machine (SVM) was widely utilized, and decision trees showed promise, especially in ICP prediction. Nonlinear models and multi-input models were prevalent, emphasizing the significance of multivariate modeling and forecasting. This review clarifies knowledge gaps and sets the stage for future research to advance cerebral physiologic signal analysis, benefiting neurocritical care applications.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Time-Series Modeling and Forecasting of Cerebral Pressure–Flow Physiology: A Scoping Systematic Review of the Human and Animal Literature

Vakitbilir,

Froese,

Gomez

et al. 2024

Sensors

View full text Add to dashboard Cite

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“…The main aim was to test the arteriolar responses to the following substances able to dilate or inhibit the dilation of vessels: acetylcholine (Ach), known to facilitate endothelium-dependent arteriolar dilation; Nω-nitro- L -arginine ( L -NNA), inhibitor of eNOS; indomethacin (INDO), inhibitor of prostaglandin endoperoxidase; and charybdotoxin plus apamin, inhibitors of EDHF [15]. Previous studies have indicated that dilation of pial vessels is resistant to inhibitors of NO synthase and cyclooxygenase, suggesting a role for a third endothelium-dependent mechanism in cerebral vessel tone modulation and blood flow distribution [16,17,18,19,20,21]. Consequently, we tested arteriolar responses to papaverine (Pap), known as an NO-independent vasodilator.…”

Section: Introductionmentioning

confidence: 99%

Low-Frequency Components in Rat Pial Arteriolar Rhythmic Diameter Changes

et al. 2017

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This study aimed to analyze the frequency components present in spontaneous rhythmic diameter changes in rat pial arterioles. Pial microcirculation was visualized by fluorescence microscopy. Rhythmic luminal variations were evaluated via computer-assisted methods. Spectral analysis was carried out on 30-min recordings under baseline conditions and after administration of acetylcholine (Ach), papaverine (Pap), Nω-nitro-L-arginine (L-NNA) prior to Ach, indomethacin (INDO), INDO prior to Ach, charybdotoxin and apamin, and charybdotoxin and apamin prior to Ach. Under baseline conditions all arteriolar orders showed 3 frequency components in the ranges of 0.0095-0.02, 0.02-0.06, and 0.06-0.2 Hz, another 2 in the ranges of 0.2-2.0 and 2.5-4.5 Hz, and another ultra-low-frequency component in the range of 0.001-0.0095 Hz. Ach caused a significant increase in the spectral density of the frequency components in the range of 0.001-0.2 Hz. Pap was able to slightly increase spectral density in the ranges of 0.001-0.0095 and 0.0095-0.02 Hz. L-NNA mainly attenuated arteriolar responses to Ach. INDO prior to Ach did not affect the endothelial response to Ach. Charybdotoxin and apamin, suggested as endothelium-derived hyperpolarizing factor inhibitors, reduced spectral density in the range of 0.001-0.0095 Hz before and after Ach administration. In conclusion, regulation of the blood flow distribution is due to several mechanisms, one of which is affected by charibdotoxin and apamin, modulating the vascular tone.

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Application of wavelet analysis to detect dysfunction in cerebral blood flow autoregulation during experimental hyperhomocysteinaemia

et al. 2018

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The purpose of the present study was to investigate the use of laser Doppler flowmetry (LDF) signals coupled with spectral wavelet analysis to detect endothelial link dysfunction in the autoregulation of cerebral blood flow in the setting of hyperhomocysteinaemia (HHcy). Fifty-one rats were assigned to three groups (intact, control, and HHcy) according to the results of biochemical assays of homocysteine level in blood plasma. LDF signals on the rat brain were recorded by LAKK-02 device to measure the microcirculatory blood flow. The laser operating wavelength and output power density were1064 nm and 0.051 W/mm, respectively. A Morlet mother wavelet transform was applied to the measured 8-min LDF signals, and periodic oscillations with five frequency intervals were identified (0.01-0.04 Hz, 0.04-0.15 Hz, 0.15-0.4 Hz, 0.4-2 Hz, and 2-5 Hz) corresponding to endothelial, neurogenic, myogenic, respiratory, and cardiac origins, respectively. In initial state, the amplitude of the oscillations decreased by 38% (P < 0.05) in the endothelial range in HHcy rats than in control rats. Cerebral autoregulation was challenged by hemorrhagic hypotension. The lower limit of autoregulation raised in a rat model of chronic HHcy (71.5 ± 0.7 mmHg in HHcy vs. 62.3 ± 0.5 mmHg in control). The data obtained indicate that the laser Doppler method and wavelet analysis may be successfully applied to detect the dysfunction of the endothelial link in cerebral vessel tone and to reveal the pathological shift of lower limit of autoregulation.

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Relationship between Myogenic Reaction and Autoregulation of Cerebral Circulation

Cited by 3 publications

References 7 publications

Time-Series Modeling and Forecasting of Cerebral Pressure–Flow Physiology: A Scoping Systematic Review of the Human and Animal Literature

Time-Series Modeling and Forecasting of Cerebral Pressure–Flow Physiology: A Scoping Systematic Review of the Human and Animal Literature

Low-Frequency Components in Rat Pial Arteriolar Rhythmic Diameter Changes

Application of wavelet analysis to detect dysfunction in cerebral blood flow autoregulation during experimental hyperhomocysteinaemia

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