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基于虚拟狭窄法计算的新型血流动力学指标预测冠状动脉斑块进展

Prediction of Plaque Progression in Coronary Arteries Based on a Novel Hemodynamic Index Calculated From Virtual Stenosis Method.

作者信息

Lee Kyung Eun, Shin Sung Woong, Kim Gook Tae, Choi Jin Ho, Shim Eun Bo

机构信息

Department of Mechanical and Biomedical Engineering, Kangwon National University, Chuncheon, South Korea.

Bio-Convergence Technology Group, Korea Institute of Industrial Technology, Jeju, South Korea.

出版信息

Front Physiol. 2019 May 9;10:400. doi: 10.3389/fphys.2019.00400. eCollection 2019.

Abstract

RATIONALE

Predicting the sites in coronary arteries that are susceptible to plaque deposition is essential for the development of clinical treatment strategies and prevention. However, to date, no physiological biomarkers for this purpose have been developed. We hypothesized that the possibility of plaque deposition at a specific site in the coronary artery is associated with wall shear stress (WSS) and fractional flow reserve (FFR).

BACKGROUND AND OBJECTIVE

We proposed a new biomarker called the stenosis susceptibility index (SSI) using the FFR and WSS derived using virtual stenosis method. To validate the clinical efficacy of this index, we applied the method to actual pilot clinical cases. This index non-invasively quantifies the vasodilation effects of vascular endothelial cells relative to FFR variation at a specific coronary artery site.

METHODS AND RESULTS

Using virtual stenosis method, we computed maximum WSS and FFR according to the variation in stenotic severity at each potential stenotic site and then plotted the variations of maximum WSS (-axis) and FFR (-axis). The slope of the graph indicated a site-specific SSI value. Then we determined the most susceptible sites for plaque deposition by comparing SSI values between the potential sites. Applying this method to seven patients revealed 71.4% in per-patient basis analysis 77.8% accuracy in per-vessel basis analysis in percutaneous coronary intervention (PCI) site prediction.

CONCLUSION

The SSI index can be used as a predictive biomarker to identify plaque deposition sites. Patients with relatively smaller SSI values also had a higher tendency for myocardial infarction. In conclusion, sites susceptible to plaque deposition can be identified using the SSI index.

摘要

原理

预测冠状动脉中易发生斑块沉积的部位对于临床治疗策略的制定和预防至关重要。然而,迄今为止,尚未开发出用于此目的的生理生物标志物。我们假设冠状动脉特定部位斑块沉积的可能性与壁面剪应力(WSS)和血流储备分数(FFR)有关。

背景与目的

我们使用虚拟狭窄方法得出的FFR和WSS提出了一种名为狭窄易感性指数(SSI)的新生物标志物。为了验证该指数的临床疗效,我们将该方法应用于实际的试点临床病例。该指数非侵入性地量化了特定冠状动脉部位血管内皮细胞相对于FFR变化的血管舒张作用。

方法与结果

使用虚拟狭窄方法,我们根据每个潜在狭窄部位狭窄严重程度的变化计算最大WSS和FFR,然后绘制最大WSS(x轴)和FFR(y轴)变化图。该图的斜率表示特定部位的SSI值。然后,我们通过比较潜在部位之间的SSI值来确定斑块沉积最易发生的部位。将该方法应用于7例患者,在经皮冠状动脉介入治疗(PCI)部位预测中,基于患者的分析准确率为71.4%,基于血管的分析准确率为77.8%。

结论

SSI指数可作为预测斑块沉积部位的生物标志物。SSI值相对较小的患者发生心肌梗死的倾向也较高。总之,使用SSI指数可以识别易发生斑块沉积的部位。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c75c/6526757/c8bfb2c31258/fphys-10-00400-g001.jpg

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