Huang Wenhao, Liu Yajun, Wang Qianqian, Jin Hongfeng, Tang Yiming, Wang Jiangting, Liu Xiaowei, Guo Yitao, Ye Chen, Tang Lijiang, Du Changqing
Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou, 311321, China.
Department of Cardiology, Zhejiang Hospital, Hangzhou, 310013, China.
BMC Cardiovasc Disord. 2025 May 2;25(1):345. doi: 10.1186/s12872-025-04757-x.
We aim to compare with the diagnostic performance of target-position quantitative flow ratio derived from Murray Law (target-μFR) and vessel quantitative flow ratio derived from Murray Law (vessel-μFR) using the fractional flow reserve (FFR) as reference standard. This study may provide more evidence for the novel clinical usage of target-μFR in the diagnosis of coronary artery disease.
Six hundreds and fifty-six patients (685 lesions) with known or suspected coronary artery disease were screened for this retrospective analysis between January 2021 to March 2023. A total of 161 patients (190 lesions) underwent quantitative coronary angiography and FFR evaluations. In the final analysis, 137 patients (146 lesions) were included in this study. Both of target-μFR and vessel-μFR were compared the diagnostic performance using the FFR ≤ 0.80 as the reference standard.
Both target-μFR (R = 0.84) and vessel-μFR (R = 0.83) demonstrated a strong correlation with FFR, and both methods showed great agreement with FFR. The area under the receiver operating characteristic curve was 0.937 for target-μFR and 0.936 for vessel-μFR in predicting FFR ≤ 0.80. FFR ≤ 0.80 were predicted with high sensitivity (86.44%) and specificity (88.51%) using the pre-defined cutt-off of 0.80 for target-μFR. A good diagnostic performance (sensitivity 92.98% and specificity 91.01%) was also demonstrated by vessel-μFR which the pre-defined cutt-off was 0.80.
The target-μFR has the similar diagnostic performance with vessel-μFR. The accuracy of μFR does not seem to be affected by the selection of the measurement point. Both of the virtual models have been validated as computational tools for diagnosing ischemia and are instrumental in aiding clinical decision-making.
我们旨在以血流储备分数(FFR)作为参考标准,比较基于默里定律得出的目标位置定量血流比(目标-μFR)和基于默里定律得出的血管定量血流比(血管-μFR)的诊断性能。本研究可能为目标-μFR在冠状动脉疾病诊断中的新型临床应用提供更多证据。
对2021年1月至2023年3月期间656例已知或疑似冠状动脉疾病的患者(685处病变)进行筛选以进行这项回顾性分析。共有161例患者(190处病变)接受了冠状动脉定量血管造影和FFR评估。在最终分析中,本研究纳入了137例患者(146处病变)。以FFR≤0.80作为参考标准,比较目标-μFR和血管-μFR的诊断性能。
目标-μFR(R = 0.84)和血管-μFR(R = 0.83)均与FFR表现出强相关性,且两种方法与FFR的一致性都很好。在预测FFR≤0.80时,目标-μFR的受试者工作特征曲线下面积为0.937,血管-μFR为0.936。使用预先定义的目标-μFR截断值0.80预测FFR≤0.80时,具有高敏感性(86.44%)和特异性(88.51%)。血管-μFR在预先定义的截断值为0.80时也表现出良好的诊断性能(敏感性92.98%,特异性91.01%)。
目标-μFR与血管-μFR具有相似的诊断性能。μFR的准确性似乎不受测量点选择的影响。这两种虚拟模型均已被验证为诊断缺血的计算工具,有助于临床决策。