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基于冠状动脉血管造影血管形态学的计算流体动力学建模与有创测量的血流储备分数的比较。

Comparison of Fractional Flow Reserve Based on Computational Fluid Dynamics Modeling Using Coronary Angiographic Vessel Morphology Versus Invasively Measured Fractional Flow Reserve.

作者信息

Tröbs Monique, Achenbach Stephan, Röther Jens, Redel Thomas, Scheuering Michael, Winneberger David, Klingenbeck Klaus, Itu Lucian, Passerini Tiziano, Kamen Ali, Sharma Puneet, Comaniciu Dorin, Schlundt Christian

机构信息

Department of Cardiology, University of Erlangen, Erlangen, Germany.

Department of Cardiology, University of Erlangen, Erlangen, Germany.

出版信息

Am J Cardiol. 2016 Jan 1;117(1):29-35. doi: 10.1016/j.amjcard.2015.10.008. Epub 2015 Oct 22.

Abstract

Invasive fractional flow reserve (FFRinvasive), although gold standard to identify hemodynamically relevant coronary stenoses, is time consuming and potentially associated with complications. We developed and evaluated a new approach to determine lesion-specific FFR on the basis of coronary anatomy as visualized by invasive coronary angiography (FFRangio): 100 coronary lesions (50% to 90% diameter stenosis) in 73 patients (48 men, 25 women; mean age 67 ± 9 years) were studied. On the basis of coronary angiograms acquired at rest from 2 views at angulations at least 30° apart, a PC-based computational fluid dynamics modeling software used personalized boundary conditions determined from 3-dimensional reconstructed angiography, heart rate, and blood pressure to derive FFRangio. The results were compared with FFRinvasive. Interobserver variability was determined in a subset of 25 narrowings. Twenty-nine of 100 coronary lesions were hemodynamically significant (FFRinvasive ≤ 0.80). FFRangio identified these with an accuracy of 90%, sensitivity of 79%, specificity of 94%, positive predictive value of 85%, and negative predictive value of 92%. The area under the receiver operating characteristic curve was 0.93. Correlation between FFRinvasive (mean: 0.84 ± 0.11) and FFRangio (mean: 0.85 ± 0.12) was r = 0.85. Interobserver variability of FFRangio was low, with a correlation of r = 0.88. In conclusion, estimation of coronary FFR with PC-based computational fluid dynamics modeling on the basis of lesion morphology as determined by invasive angiography is possible with high diagnostic accuracy compared to invasive measurements.

摘要

有创血流储备分数(FFRinvasive)虽是识别具有血流动力学意义的冠状动脉狭窄的金标准,但耗时且可能伴有并发症。我们开发并评估了一种基于有创冠状动脉造影(FFRangio)所显示的冠状动脉解剖结构来确定病变特异性FFR的新方法:对73例患者(48例男性,25例女性;平均年龄67±9岁)的100处冠状动脉病变(直径狭窄50%至90%)进行了研究。基于在静息状态下从至少相隔30°的两个角度获取的冠状动脉造影图像,一款基于个人电脑的计算流体动力学建模软件使用从三维重建血管造影、心率和血压确定的个性化边界条件来推导FFRangio。将结果与FFRinvasive进行比较。在25处狭窄的子集中确定了观察者间的变异性。100处冠状动脉病变中有29处具有血流动力学意义(FFRinvasive≤0.80)。FFRangio识别这些病变的准确率为90%,灵敏度为79%,特异性为94%,阳性预测值为85%,阴性预测值为92%。受试者工作特征曲线下面积为0.93。FFRinvasive(平均值:0.84±0.11)与FFRangio(平均值:0.85±0.12)之间的相关性为r = 0.85。FFRangio的观察者间变异性较低,相关性为r = 0.88。总之,与有创测量相比,基于有创血管造影确定的病变形态,使用基于个人电脑的计算流体动力学建模来估计冠状动脉FFR具有较高的诊断准确性。

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