Literature DB >> 21136207

Inter-subject correlation exists between morphological metrics of cerebral blood flow velocity and intracranial pressure pulses.

Sunghan Kim1, Xiao Hu, David McArthur, Robert Hamilton, Marvin Bergsneider, Thomas Glenn, Neil Martin, Paul Vespa.   

Abstract

BACKGROUND: The prototypical intracranial pressure (ICP) pulse morphology has been well known to be triphasic. Several studies suggest that the morphology of ICP pulse reflects the physiological and pathophysiological conditions of the intracranial dynamics. Recently, there has been a renaissance of studying ICP pulse using new ICP signal processing technologies in various clinical contexts. Cerebral blood flow velocity (CBFV) pulse is another important pulsatile signal originated from the complex circulatory systems of cerebral blood flow. However, CBFV pulse morphology has not been well studied mainly due to the noise level and lack of signal processing techniques.
METHODS: Our group recently developed a technique called the morphological clustering and analysis of intracranial pressure that can extract a comprehensive set of pulse morphological metrics. We extend this algorithm to extract various morphological metrics from ICP and CBFV pulses that were simultaneously recorded from 47 brain injury patients and investigate the mutual correlation between those metrics utilizing the robust percentage bend correlation analysis.
RESULTS: Our results show that CBFV pulses are also triphasic as ICP pulses and 15.2% of 128 pulse morphological metrics extracted from ICP and CBFV pulses are highly correlated (P < 0.01) in an inter-subject fashion. In addition, mean ICP does not correlate (P = 0.45) with the pulsatility index of CBFV pulses but correlates (P < 0.05) with several novel CBFV pulse morphological metrics such as the time interval between the onset of CBFV pulses and ECG QRS peak.
CONCLUSIONS: Our results suggest that characterizing CBFV pulse morphology is clinically important because it may offer a potential noninvasive alternative to assess various aspects of ICP such as mean ICP.

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Year:  2010        PMID: 21136207      PMCID: PMC3071636          DOI: 10.1007/s12028-010-9471-x

Source DB:  PubMed          Journal:  Neurocrit Care        ISSN: 1541-6933            Impact factor:   3.210


  36 in total

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Authors:  C J Kirkness; P H Mitchell; R L Burr; K S March; D W Newell
Journal:  J Neurosci Nurs       Date:  2000-10       Impact factor: 1.230

2.  Transcranial Doppler pulsatility index: not an accurate method to assess intracranial pressure.

Authors:  Anders Behrens; Niklas Lenfeldt; Khalid Ambarki; Jan Malm; Anders Eklund; Lars-Owe Koskinen
Journal:  Neurosurgery       Date:  2010-06       Impact factor: 4.654

3.  Intracranial pressure waveform morphology and intracranial adaptive capacity.

Authors:  Jun-Yu Fan; Catherine Kirkness; Paolo Vicini; Robert Burr; Pamela Mitchell
Journal:  Am J Crit Care       Date:  2008-11       Impact factor: 2.228

4.  Intracranial pressure pulse morphological features improved detection of decreased cerebral blood flow.

Authors:  Xiao Hu; Thomas Glenn; Fabien Scalzo; Marvin Bergsneider; Chris Sarkiss; Neil Martin; Paul Vespa
Journal:  Physiol Meas       Date:  2010-03-26       Impact factor: 2.833

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Journal:  Stroke       Date:  1997-03       Impact factor: 7.914

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Journal:  Neurosurgery       Date:  1981-07       Impact factor: 4.654

8.  Changes in intracranial pulse pressure amplitudes after shunt implantation and adjustment of shunt valve opening pressure in normal pressure hydrocephalus.

Authors:  Per Kristian Eide; Wilhelm Sorteberg
Journal:  Acta Neurochir (Wien)       Date:  2008-10-21       Impact factor: 2.216

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Authors:  T Matsumoto; H Nagai; Y Kasuga; K Kamiya
Journal:  Acta Neurochir (Wien)       Date:  1986       Impact factor: 2.216

10.  Transcranial Doppler ultrasound in hypertensive versus normotensive patients after aneurysmal subarachnoid hemorrhage.

Authors:  A Ekelund; H Säveland; B Romner; L Brandt
Journal:  Stroke       Date:  1995-11       Impact factor: 7.914

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  4 in total

1.  Steady-state indicators of the intracranial pressure dynamic system using geodesic distance of the ICP pulse waveform.

Authors:  Xiao Hu; Nestor Gonzalez; Marvin Bergsneider
Journal:  Physiol Meas       Date:  2012-11-15       Impact factor: 2.833

2.  Noninvasive intracranial hypertension detection utilizing semisupervised learning.

Authors:  Sunghan Kim; Robert Hamilton; Stacy Pineles; Marvin Bergsneider; Xiao Hu
Journal:  IEEE Trans Biomed Eng       Date:  2012-11-15       Impact factor: 4.538

3.  Non-invasive detection of intracranial hypertension using a simplified intracranial hemo- and hydro-dynamics model.

Authors:  Kwang Jin Lee; Chanki Park; Jooyoung Oh; Boreom Lee
Journal:  Biomed Eng Online       Date:  2015-05-30       Impact factor: 2.819

4.  Toward automated classification of pathological transcranial Doppler waveform morphology via spectral clustering.

Authors:  Samuel G Thorpe; Corey M Thibeault; Nicolas Canac; Kian Jalaleddini; Amber Dorn; Seth J Wilk; Thomas Devlin; Fabien Scalzo; Robert B Hamilton
Journal:  PLoS One       Date:  2020-02-06       Impact factor: 3.240

  4 in total

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