Rivolo Simone, Patterson Tiffany, Asrress Kaleab N, Marber Michael, Redwood Simon, Smith Nicolas P, Lee Jack
Division of Imaging Science and Biomedical EngineeringKing's College London.
Cardiovascular Division, King's College London.
IEEE Trans Biomed Eng. 2017 May;64(5):1187-1196. doi: 10.1109/TBME.2016.2593518. Epub 2016 Aug 3.
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.
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.
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.
An accurate, standardized, and automated cWIA was developed. Moreover, the feasibility of beat wise cWIA was demonstrated for the first time.
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.
冠状动脉波强度分析（cWIA）在临床研究中越来越多地被用于区分冠状动脉血流近端和远端的机械影响。最近，一种源自cWIA的临床指标在预测心肌梗死后功能恢复方面显示出预后价值。然而，目前已知的cWIA指标对操作者的依赖性阻碍了其在临床实践中的常规应用。具体而言，最近有研究表明，cWIA指标高度依赖于用于平滑采集到的波形的Savitzky-Golay滤波器参数。因此，提出了一种使cWIA标准化和自动化的新方法，并在体内进行了评估。
该新方法在对采集到的波形进行总体平均后，将自适应Savitzky-Golay滤波器与高阶中心有限差分相结合。使用体内人体数据评估其准确性。然后对提出的方法进行修改，以自动逐搏执行cWIA。最后，评估该方法的可行性（准确性和稳健性）。
自动cWIA算法在广泛的噪声场景下提供了令人满意的准确性（在估计波面积和峰值时误差分别≤10%和≤20%）。在进行逐搏cWIA时，这些结果得到了证实。
开发了一种准确、标准化和自动化的cWIA。此外，首次证明了逐搏cWIA的可行性。
所提出的算法为从业者提供了一种标准化技术，这可以拓宽cWIA在临床实践中的应用，使其能够开展多中心试验。此外，逐搏cWIA所展示的潜力为实时研究冠状动脉生理学开辟了可能性。
