Biomedical Instrument Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China; Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands.
Cardiovascular Institute, Hospital Clinico San Carlos, Madrid, Spain.
JACC Cardiovasc Interv. 2015 Apr 20;8(4):564-74. doi: 10.1016/j.jcin.2014.12.232. Epub 2015 Mar 26.
The aim of this study was to develop a new model for assessment of stenosis severity in a bifurcation lesion including its core. The diagnostic performance of this model, powered by 3-dimensional quantitative coronary angiography to predict the functional significance of obstructive bifurcation stenoses, was evaluated using fractional flow reserve (FFR) as the reference standard.
Development of advanced quantitative models might help to establish a relationship between bifurcation anatomy and FFR.
Patients who had undergone coronary angiography and interventions in 5 European cardiology centers were randomly selected and analyzed. Different bifurcation fractal laws, including Murray, Finet, and HK laws, were implemented in the bifurcation model, resulting in different degrees of stenosis severity.
A total of 78 bifurcation lesions in 73 patients were analyzed. In 51 (65%) bifurcations, FFR was measured in the main vessel. A total of 34 (43.6%) interrogated vessels had an FFR≤0.80. Correlation between FFR and diameter stenosis was poor by conventional straight analysis (ρ=-0.23, p<0.001) but significantly improved by bifurcation analyses: the highest by the HK law (ρ=-0.50, p<0.001), followed by the Finet law (ρ=-0.49, p<0.001), and the Murray law (ρ=-0.41, p<0.001). The area under the receiver-operating characteristics curve for predicting FFR≤0.80 was significantly higher by bifurcation analysis compared with straight analysis: 0.72 (95% confidence interval: 0.61 to 0.82) versus 0.60 (95% confidence interval: 0.49 to 0.71; p=0.001). Applying a threshold of ≥50% diameter stenosis, as assessed by the bifurcation model, to predict FFR≤0.80 resulted in 23 true positives, 27 true negatives, 17 false positives, and 11 false negatives.
The new bifurcation model provides a comprehensive assessment of bifurcation anatomy. Compared with straight analysis, identification of lesions with preserved FFR values in obstructive bifurcation stenoses was improved. Nevertheless, accuracy was limited by using solely anatomical parameters.
本研究旨在建立一种新的模型,用于评估包括分叉核心在内的分叉病变狭窄程度。该模型由三维定量冠状动脉造影驱动,旨在预测阻塞性分叉狭窄的功能意义,使用血流储备分数(FFR)作为参考标准来评估其诊断性能。
开发先进的定量模型可能有助于建立分叉解剖结构与 FFR 之间的关系。
从欧洲 5 个心脏病中心随机选择并分析接受冠状动脉造影和介入治疗的患者。分叉模型中应用了不同的分叉分形律,包括 Murray、Finet 和 HK 定律,导致不同程度的狭窄严重程度。
共分析了 73 例患者的 78 个分叉病变。在 51 个(65%)分叉病变中,主血管内测量了 FFR。在 34 个(43.6%)被检查的血管中,有 34 个(43.6%)FFR≤0.80。常规直线分析显示 FFR 与直径狭窄之间相关性较差(ρ=-0.23,p<0.001),但通过分叉分析显著改善:HK 定律相关性最高(ρ=-0.50,p<0.001),其次是 Finet 定律(ρ=-0.49,p<0.001),Murray 定律(ρ=-0.41,p<0.001)。分叉分析预测 FFR≤0.80 的受试者工作特征曲线下面积明显高于直线分析:0.72(95%置信区间:0.61 至 0.82)与 0.60(95%置信区间:0.49 至 0.71;p=0.001)。分叉模型评估的≥50%直径狭窄作为预测 FFR≤0.80 的阈值,得到 23 个真阳性、27 个真阴性、17 个假阳性和 11 个假阴性。
新的分叉模型提供了对分叉解剖结构的全面评估。与直线分析相比,识别阻塞性分叉狭窄中保留 FFR 值的病变得到了改善。然而,准确性受到仅使用解剖参数的限制。