Won Yong Kim

Enhancing coronary Wave Intensity Analysis robustness by high order central finite differences

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Standard

Enhancing coronary Wave Intensity Analysis robustness by high order central finite differences. / Rivolo, Simone; Asrress, Kaleab N; Chiribiri, Amedeo; Sammut, Eva; Wesolowski, Roman; Bloch, Lars Ø; Grøndal, Anne K; Hønge, Jesper L; Kim, Won Yong; Marber, Michael; Redwood, Simon; Nagel, Eike; Smith, Nicolas P; Lee, Jack.

In: Artery Research, Vol. 8, No. 3, 09.2014, p. 98-109.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Harvard

Rivolo, S, Asrress, KN, Chiribiri, A, Sammut, E, Wesolowski, R, Bloch, LØ, Grøndal, AK, Hønge, JL, Kim, WY, Marber, M, Redwood, S, Nagel, E, Smith, NP & Lee, J 2014, 'Enhancing coronary Wave Intensity Analysis robustness by high order central finite differences', Artery Research, vol. 8, no. 3, pp. 98-109. https://doi.org/10.1016/j.artres.2014.03.001

APA

Rivolo, S., Asrress, K. N., Chiribiri, A., Sammut, E., Wesolowski, R., Bloch, L. Ø., ... Lee, J. (2014). Enhancing coronary Wave Intensity Analysis robustness by high order central finite differences. Artery Research, 8(3), 98-109. https://doi.org/10.1016/j.artres.2014.03.001

CBE

Rivolo S, Asrress KN, Chiribiri A, Sammut E, Wesolowski R, Bloch LØ, Grøndal AK, Hønge JL, Kim WY, Marber M, Redwood S, Nagel E, Smith NP, Lee J. 2014. Enhancing coronary Wave Intensity Analysis robustness by high order central finite differences. Artery Research. 8(3):98-109. https://doi.org/10.1016/j.artres.2014.03.001

MLA

Vancouver

Rivolo S, Asrress KN, Chiribiri A, Sammut E, Wesolowski R, Bloch LØ et al. Enhancing coronary Wave Intensity Analysis robustness by high order central finite differences. Artery Research. 2014 Sep;8(3):98-109. https://doi.org/10.1016/j.artres.2014.03.001

Author

Rivolo, Simone ; Asrress, Kaleab N ; Chiribiri, Amedeo ; Sammut, Eva ; Wesolowski, Roman ; Bloch, Lars Ø ; Grøndal, Anne K ; Hønge, Jesper L ; Kim, Won Yong ; Marber, Michael ; Redwood, Simon ; Nagel, Eike ; Smith, Nicolas P ; Lee, Jack. / Enhancing coronary Wave Intensity Analysis robustness by high order central finite differences. In: Artery Research. 2014 ; Vol. 8, No. 3. pp. 98-109.

Bibtex

@article{caf5610887054f5f91582255fe520d68,
title = "Enhancing coronary Wave Intensity Analysis robustness by high order central finite differences",
abstract = "BACKGROUND: Coronary Wave Intensity Analysis (cWIA) is a technique capable of separating the effects of proximal arterial haemodynamics from cardiac mechanics. Studies have identified WIA-derived indices that are closely correlated with several disease processes and predictive of functional recovery following myocardial infarction. The cWIA clinical application has, however, been limited by technical challenges including a lack of standardization across different studies and the derived indices' sensitivity to the processing parameters. Specifically, a critical step in WIA is the noise removal for evaluation of derivatives of the acquired signals, typically performed by applying a Savitzky-Golay filter, to reduce the high frequency acquisition noise.METHODS: The impact of the filter parameter selection on cWIA output, and on the derived clinical metrics (integral areas and peaks of the major waves), is first analysed. The sensitivity analysis is performed either by using the filter as a differentiator to calculate the signals' time derivative or by applying the filter to smooth the ensemble-averaged waveforms. Furthermore, the power-spectrum of the ensemble-averaged waveforms contains little high-frequency components, which motivated us to propose an alternative approach to compute the time derivatives of the acquired waveforms using a central finite difference scheme.RESULTS AND CONCLUSION: The cWIA output and consequently the derived clinical metrics are significantly affected by the filter parameters, irrespective of its use as a smoothing filter or a differentiator. The proposed approach is parameter-free and, when applied to the 10 in-vivo human datasets and the 50 in-vivo animal datasets, enhances the cWIA robustness by significantly reducing the outcome variability (by 60{\%}).",
author = "Simone Rivolo and Asrress, {Kaleab N} and Amedeo Chiribiri and Eva Sammut and Roman Wesolowski and Bloch, {Lars {\O}} and Gr{\o}ndal, {Anne K} and H{\o}nge, {Jesper L} and Kim, {Won Yong} and Michael Marber and Simon Redwood and Eike Nagel and Smith, {Nicolas P} and Jack Lee",
year = "2014",
month = "9",
doi = "10.1016/j.artres.2014.03.001",
language = "English",
volume = "8",
pages = "98--109",
journal = "Artery Research",
issn = "1872-9312",
publisher = "Elsevier BV",
number = "3",

}

RIS

TY - JOUR

T1 - Enhancing coronary Wave Intensity Analysis robustness by high order central finite differences

AU - Rivolo, Simone

AU - Asrress, Kaleab N

AU - Chiribiri, Amedeo

AU - Sammut, Eva

AU - Wesolowski, Roman

AU - Bloch, Lars Ø

AU - Grøndal, Anne K

AU - Hønge, Jesper L

AU - Kim, Won Yong

AU - Marber, Michael

AU - Redwood, Simon

AU - Nagel, Eike

AU - Smith, Nicolas P

AU - Lee, Jack

PY - 2014/9

Y1 - 2014/9

N2 - BACKGROUND: Coronary Wave Intensity Analysis (cWIA) is a technique capable of separating the effects of proximal arterial haemodynamics from cardiac mechanics. Studies have identified WIA-derived indices that are closely correlated with several disease processes and predictive of functional recovery following myocardial infarction. The cWIA clinical application has, however, been limited by technical challenges including a lack of standardization across different studies and the derived indices' sensitivity to the processing parameters. Specifically, a critical step in WIA is the noise removal for evaluation of derivatives of the acquired signals, typically performed by applying a Savitzky-Golay filter, to reduce the high frequency acquisition noise.METHODS: The impact of the filter parameter selection on cWIA output, and on the derived clinical metrics (integral areas and peaks of the major waves), is first analysed. The sensitivity analysis is performed either by using the filter as a differentiator to calculate the signals' time derivative or by applying the filter to smooth the ensemble-averaged waveforms. Furthermore, the power-spectrum of the ensemble-averaged waveforms contains little high-frequency components, which motivated us to propose an alternative approach to compute the time derivatives of the acquired waveforms using a central finite difference scheme.RESULTS AND CONCLUSION: The cWIA output and consequently the derived clinical metrics are significantly affected by the filter parameters, irrespective of its use as a smoothing filter or a differentiator. The proposed approach is parameter-free and, when applied to the 10 in-vivo human datasets and the 50 in-vivo animal datasets, enhances the cWIA robustness by significantly reducing the outcome variability (by 60%).

AB - BACKGROUND: Coronary Wave Intensity Analysis (cWIA) is a technique capable of separating the effects of proximal arterial haemodynamics from cardiac mechanics. Studies have identified WIA-derived indices that are closely correlated with several disease processes and predictive of functional recovery following myocardial infarction. The cWIA clinical application has, however, been limited by technical challenges including a lack of standardization across different studies and the derived indices' sensitivity to the processing parameters. Specifically, a critical step in WIA is the noise removal for evaluation of derivatives of the acquired signals, typically performed by applying a Savitzky-Golay filter, to reduce the high frequency acquisition noise.METHODS: The impact of the filter parameter selection on cWIA output, and on the derived clinical metrics (integral areas and peaks of the major waves), is first analysed. The sensitivity analysis is performed either by using the filter as a differentiator to calculate the signals' time derivative or by applying the filter to smooth the ensemble-averaged waveforms. Furthermore, the power-spectrum of the ensemble-averaged waveforms contains little high-frequency components, which motivated us to propose an alternative approach to compute the time derivatives of the acquired waveforms using a central finite difference scheme.RESULTS AND CONCLUSION: The cWIA output and consequently the derived clinical metrics are significantly affected by the filter parameters, irrespective of its use as a smoothing filter or a differentiator. The proposed approach is parameter-free and, when applied to the 10 in-vivo human datasets and the 50 in-vivo animal datasets, enhances the cWIA robustness by significantly reducing the outcome variability (by 60%).

U2 - 10.1016/j.artres.2014.03.001

DO - 10.1016/j.artres.2014.03.001

M3 - Journal article

VL - 8

SP - 98

EP - 109

JO - Artery Research

JF - Artery Research

SN - 1872-9312

IS - 3

ER -