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Accurate and Standardized Coronary Wave Intensity Analysis
Simone Rivolo1, Tiffany Patterson2, Kaleab N Asrress2
1Division of Imaging Science and Biomedical EngineeringKing's College London.
Insights
A new automated method for coronary wave intensity analysis (cWIA) has been developed, improving standardization and accuracy. This novel approach enables beat-by-beat analysis, advancing the clinical application of cWIA for coronary blood flow assessment.
Area of Science:
- Cardiovascular Physiology
- Biomedical Engineering
- Medical Imaging Analysis
Background:
- Coronary wave intensity analysis (cWIA) is used to assess coronary blood flow dynamics.
- Current cWIA methods have operator-dependent limitations, hindering clinical adoption.
- Previous studies highlighted the prognostic value of cWIA-derived indices post-myocardial infarction.
Purpose of the Study:
- To develop a standardized and automated method for coronary wave intensity analysis (cWIA).
- To evaluate the accuracy and robustness of the novel automated cWIA approach.
- To demonstrate the feasibility of beat-wise cWIA for real-time physiological investigation.
Main Methods:
- An adaptive Savitzky-Golay filter combined with high-order central finite differencing was employed.
- Ensemble-averaging of acquired waveforms preceded data processing.
- The algorithm was modified for automatic beat-wise cWIA and validated with in vivo human data.
Main Results:
- The automated cWIA algorithm demonstrated satisfactory accuracy across various noise levels.
- Errors in wave area and peak estimations were within acceptable limits (≤10% and ≤20%, respectively).
- Beat-by-beat cWIA was successfully performed, confirming the method's feasibility and robustness.
Conclusions:
- An accurate, standardized, and automated cWIA method has been successfully developed.
- The feasibility of beat-wise cWIA was demonstrated for the first time.
- This advancement facilitates broader clinical application of cWIA and multicenter trials.
Objective:
Coronary wave intensity analysis (cWIA) has increasingly been applied in the clinical research setting to distinguish between the proximal and distal mechanical influences on coronary blood flow. Recently, a cWIA-derived clinical index demonstrated prognostic value in predicting functional recovery postmyocardial infarction. Nevertheless, the known operator dependence of the cWIA metrics currently hampers its routine application in clinical practice. Specifically, it was recently demonstrated that the cWIA metrics are highly dependent on the chosen Savitzky-Golay filter parameters used to smooth the acquired traces. Therefore, a novel method to make cWIA standardized and automatic was proposed and evaluated in vivo.
Methods:
The novel approach combines an adaptive Savitzky-Golay filter with high-order central finite differencing after ensemble-averaging the acquired waveforms. Its accuracy was assessed using in vivo human data. The proposed approach was then modified to automatically perform beat wise cWIA. Finally, the feasibility (accuracy and robustness) of the method was evaluated.
Results:
The automatic cWIA algorithm provided satisfactory accuracy under a wide range of noise scenarios (≤10% and ≤20% error in the estimation of wave areas and peaks, respectively). These results were confirmed when beat-by-beat cWIA was performed.
Conclusion:
An accurate, standardized, and automated cWIA was developed. Moreover, the feasibility of beat wise cWIA was demonstrated for the first time.
Significance:
The proposed algorithm provides practitioners with a standardized technique that could broaden the application of cWIA in the clinical practice as enabling multicenter trials. Furthermore, the demonstrated potential of beatwise cWIA opens the possibility investigating the coronary physiology in real time.
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