Improvement in Coronary Blood Flow Velocity With Acute Biventricular Pacing Is Predominantly Due to an Increase in a Diastolic Backward-Travelling Decompression (Suction) Wave

Kyriacou, Andreas; Whinnett, Zachary I.; Sen, Sayan; Pabari, Punam A.; Wright, Ian; Cornelussen, Richard; Lefroy, David; Davies, D. Wyn; Peters, Nicholas S.; Kanagaratnam, Prapa; Mayet, Jamil; Hughes, Alun D.; Francis, Dárrel P.; Davies, Justin E.

doi:10.1161/circulationaha.111.075606

Cited by 40 publications

(52 citation statements)

References 53 publications

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“…The study would be focused on the integral areas, the main metric used in literature [2], [3], [5]. However, the main waves' peaks accuracy provided by the adaptive S-G algorithms is discussed in the Section IV.…”

Section: Analysis Of Adaptive S-g Accuracymentioning

confidence: 99%

“…Each of the 6 main waves identifiable from the cWIA output [2] are related to a specific event through the cardiac cycle (left ventricle relaxation, aortic valve closure) allowing the coronary measurements to be directly related to their physiological origin. Initially used to investigate the unique feature of the coronary blood flow of being mainly diastolic [2], [3], cWIA recently received increasing attention as a powerful technique to establish a mechanistic link between coronary haemodynamic measurements and the underlying pathopysiology [3]. More recently, De Silva et al [4] demonstrated the prognostic value of a cWIA-derived index in predicting functional recovery following myocardial infarction.…”

Section: Introductionmentioning

confidence: 99%

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Automatic selection of optimal Savitzky-Golay filter parameters for Coronary Wave Intensity Analysis

Rivolo

Nagel

Smith

et al. 2014

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Coronary Wave Intensity Analysis (cWIA) is a technique capable of separating the effects of proximal arterial haemodynamics from cardiac mechanics. The cWIA ability to establish a mechanistic link between coronary haemodynamics measurements and the underlying pathophysiology has been widely demonstrated. Moreover, the prognostic value of a cWIA-derived metric has been recently proved. However, the clinical application of cWIA has been hindered due to the strong dependence on the practitioners, mainly ascribable to the cWIA-derived indices sensitivity to the pre-processing parameters. Specifically, as recently demonstrated, the cWIA-derived metrics are strongly sensitive to the Savitzky-Golay (S-G) filter, typically used to smooth the acquired traces. This is mainly due to the inability of the S-G filter to deal with the different timescale features present in the measured waveforms. Therefore, we propose to apply an adaptive S-G algorithm that automatically selects pointwise the optimal filter parameters. The newly proposed algorithm accuracy is assessed against a cWIA gold standard, provided by a newly developed in-silico cWIA modelling framework, when physiological noise is added to the simulated traces. The adaptive S-G algorithm, when used to automatically select the polynomial degree of the S-G filter, provides satisfactory results with ≤ 10% error for all the metrics through all the levels of noise tested. Therefore, the newly proposed method makes cWIA fully automatic and independent from the practitioners, opening the possibility to multi-centre trials.

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Section: Analysis Of Adaptive S-g Accuracymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automatic selection of optimal Savitzky-Golay filter parameters for Coronary Wave Intensity Analysis

Rivolo

Nagel

Smith

et al. 2014

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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show abstract

“…2011; Kyriacou et al. 2012). Recently, a landmark predictive application of WIA was demonstrated for the first time in de Silva et al.…”

Section: Introductionmentioning

confidence: 99%

In silico coronary wave intensity analysis: application of an integrated one-dimensional and poromechanical model of cardiac perfusion

Lee

Nordsletten

Cookson

et al. 2016

Biomech Model Mechanobiol

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Coronary wave intensity analysis (cWIA) is a diagnostic technique based on invasive measurement of coronary pressure and velocity waveforms. The theory of WIA allows the forward- and backward-propagating coronary waves to be separated and attributed to their origin and timing, thus serving as a sensitive and specific cardiac functional indicator. In recent years, an increasing number of clinical studies have begun to establish associations between changes in specific waves and various diseases of myocardium and perfusion. These studies are, however, currently confined to a trial-and-error approach and are subject to technological limitations which may confound accurate interpretations. In this work, we have developed a biophysically based cardiac perfusion model which incorporates full ventricular–aortic–coronary coupling. This was achieved by integrating our previous work on one-dimensional modelling of vascular flow and poroelastic perfusion within an active myocardial mechanics framework. Extensive parameterisation was performed, yielding a close agreement with physiological levels of global coronary and myocardial function as well as experimentally observed cumulative wave intensity magnitudes. Results indicate a strong dependence of the backward suction wave on QRS duration and vascular resistance, the forward pushing wave on the rate of myocyte tension development, and the late forward pushing wave on the aortic valve dynamics. These findings are not only consistent with experimental observations, but offer a greater specificity to the wave-originating mechanisms, thus demonstrating the value of the integrated model as a tool for clinical investigation.

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“…In a recent study Kyriacou et al 10 . used cWIA to identify the optimal atrioventricular delay in biventricular pacing in order to improve ventricular contractility and relaxation thereby increasing the cardiac output.…”

Section: Introductionmentioning

confidence: 99%

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

Rivolo

Asrress

Chiribiri

et al. 2014

ARTRES

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BackgroundCoronary 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.MethodsThe 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 ConclusionThe 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%).

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Improvement in Coronary Blood Flow Velocity With Acute Biventricular Pacing Is Predominantly Due to an Increase in a Diastolic Backward-Travelling Decompression (Suction) Wave

Cited by 40 publications

References 53 publications

Automatic selection of optimal Savitzky-Golay filter parameters for Coronary Wave Intensity Analysis

Automatic selection of optimal Savitzky-Golay filter parameters for Coronary Wave Intensity Analysis

In silico coronary wave intensity analysis: application of an integrated one-dimensional and poromechanical model of cardiac perfusion

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

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