Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
Department of Cardiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
BMC Med Imaging. 2023 Jun 6;23(1):76. doi: 10.1186/s12880-023-01031-4.
Whether a stenosis can cause hemodynamic lesion-specific ischemia is critical for the treatment decision in patients with coronary artery disease (CAD). Based on coronary computed tomography angiography (CCTA), CT fractional flow reserve (FFR) can be used to assess lesion-specific ischemia. The selection of an appropriate site along the coronary artery tree is vital for measuring FFR. However the optimal site to measure FFR for a target stenosis remains to be adequately determined. The purpose of this study was to determine the optimal site to measure FFR for a target lesion in detecting lesion-specific ischemia in CAD patients by evaluating the performance of FFR measured at different sites distal to the target lesion in detecting lesion-specific ischemia with FFR measured with invasive coronary angiography (ICA) as reference standard.
In this single-center retrospective cohort study, a total of 401 patients suspected of having CAD underwent invasive ICA and FFR between March 2017 and December 2021 were identified. 52 patients having both CCTA and invasive FFR within 90 days were enrolled. Patients with vessels 30%-90% diameter stenosis as determined by ICA were referred to invasive FFR evaluation, which was performed 2-3 cm distal to the stenosis under the condition of hyperemia. For each vessel with 30%-90% diameter stenosis, if only one stenosis was present, this stenosis was selected as the target lesion; if serial stenoses were present, the stenosis most distal to the vessel end was chosen as the target lesion. FFR was measured at four sites: 1 cm, 2 cm, and 3 cm distal to the lower border of the target lesion (FFR-1 cm, FFR-2 cm, FFR-3 cm), and the lowest FFR at the distal vessel tip (FFR-lowest). The normality of quantitative data was assessed using the Shapiro-Wilk test. Pearson's correlation analysis and Bland-Altman plots were used for assessing the correlation and difference between invasive FFR and FFR. Correlation coefficients derived from Chi-suqare test were used to assess the correlation between invasive FFR and the cominbaiton of FFR measred at four sites. The performances of significant obstruction stenosis (diameter stenosis ≥ 50%) at CCTA and FFR measured at the four sites and their combinations in diagnosing lesion-specific ischemia were evaluated by receiver-operating characteristic (ROC) curves using invasive FFR as the reference standard. The areas under ROC curves (AUCs) of CCTA and FFR were compared by the DeLong test.
A total of 72 coronary arteries in 52 patients were included for analysis. Twenty-five vessels (34.7%) had lesion-specific ischemia detected by invasive FFR and 47 vesseles (65.3%) had no lesion-spefifice ischemia. Good correlation was found between invasive FFR and FFR-2 cm and FFR-3 cm (r = 0.80, 95% CI, 0.70 to 0.87, p < 0.001; r = 0.82, 95% CI, 0.72 to 0.88, p < 0.001). Moderate correlation was found between invasive FFR and FFR-1 cm and FFR-lowest (r = 0.77, 95% CI, 0.65 to 0.85, p < 0.001; r = 0.78, 95% CI, 0.67 to 0.86, p < 0.001). FFR-1 cm + FFR-2 cm, FFR-2 cm + FFR-3 cm, FFR-3 cm + FFR-lowest, FFR-1 cm + FFR-2 cm + FFR-3 cm, and FFR-2 cm + FFR-3 cm + FFR-lowest were correatled with invasive FFR (r = 0.722; 0.722; 0.701; 0.722; and 0.722, respectively; p < 0.001 for all). Bland-Altman plots revealed a mild difference between invasive FFR and the four FFR (invasive FFR vs. FFR-1 cm, mean difference -0.0158, 95% limits of agreement: -0.1475 to 0.1159; invasive FFR vs. FFR-2 cm, mean difference 0.0001, 95% limits of agreement: -0.1222 to 0.1220; invasive FFR vs. FFR-3 cm, mean difference 0.0117, 95% limits of agreement: -0.1085 to 0.1318; and invasive FFR vs. FFR-lowest, mean difference 0.0343, 95% limits of agreement: -0.1033 to 0.1720). AUCs of CCTA, FFR-1 cm, FFR-2 cm, FFR-3 cm, and FFR-lowest in detecting lesion-specific ischemia were 0.578, 0.768, 0.857, 0.856 and 0.770, respectively. All FFR had a higher AUC than CCTA (all p < 0.05), FFR-2 cm achieved the highest AUC at 0.857. The AUCs of FFR-2 cm and FFR-3 cm were comparable (p > 0.05). The AUCs were similar between FFR-1 cm + FFR-2 cm, FFR-3 cm + FFR-lowest and FFR-2 cm alone (AUC = 0.857, 0.857, 0.857, respectively; p > 0.05 for all). The AUCs of FFR-2 cm + FFR-3 cm, FFR-1 cm + FFR-2 cm + FFR-3 cm, FFR-and 2 cm + FFR-3 cm + FFR-lowest (0.871, 0.871, 0.872, respectively) were slightly higher than that of FFR-2 cm alone (0.857), but without significnacne differences (p > 0.05 for all).
FFR measured at 2 cm distal to the lower border of the target lesion is the optimal measurement site for identifying lesion-specific ischemia in patients with CAD.
对于冠状动脉疾病(CAD)患者,狭窄是否会引起血流动力学特定部位缺血对于治疗决策至关重要。基于冠状动脉计算机断层血管造影术(CCTA),CT 分数流量储备(FFR)可用于评估特定部位缺血。选择冠状动脉树沿线上的合适部位测量 FFR 至关重要。然而,确定目标狭窄处测量 FFR 的最佳部位仍有待充分确定。本研究旨在通过评估与侵入性冠状动脉造影(ICA)参考标准测量的特定部位缺血的 FFR 与在目标病变部位测量的 FFR 之间的相关性,确定检测 CAD 患者特定部位缺血的目标病变部位的最佳 FFR 测量部位。
本单中心回顾性队列研究共纳入 2017 年 3 月至 2021 年 12 月期间疑似患有 CAD 并接受 ICA 和 FFR 检查的 401 例患者。对 52 例在 90 天内同时进行 CCTA 和 ICA 测量的患者进行了研究。对 ICA 确定的血管 30%-90%狭窄的患者进行了 ICA 评估。FFR 测量是在狭窄部位下 2-3cm 的充血条件下进行的。对于血管狭窄 30%-90%的每个血管,如果只有一个狭窄,则选择该狭窄作为目标病变;如果存在连续狭窄,则选择血管末端最远端的狭窄作为目标病变。FFR 分别在距离目标病变下边界 1cm、2cm 和 3cm 处(FFR-1cm、FFR-2cm 和 FFR-3cm)以及血管末端最低处(FFR-lowest)进行测量。使用 Shapiro-Wilk 检验评估定量数据的正态性。采用 Pearson 相关分析和 Bland-Altman 图评估 ICA 和 FFR 之间的相关性和差异。来自卡方检验的相关系数用于评估在四个部位测量的 FFR 与侵入性 FFR 的相关性。使用 ICA 作为参考标准,评估 CCTA 和四个部位(FFR-1cm、FFR-2cm、FFR-3cm 和 FFR-lowest)测量的显著梗阻性狭窄(狭窄程度≥50%)以及它们的组合在诊断特定部位缺血方面的性能。通过接受者操作特征(ROC)曲线比较 CCTA 和 FFR 的曲线下面积(AUC)。使用 DeLong 检验比较 ROC 曲线的 AUC。
共纳入 52 例患者的 72 个冠状动脉进行分析。25 个血管(34.7%)通过 ICA 检测到有特定部位缺血,47 个血管(65.3%)无特定部位缺血。FFR-2cm 和 FFR-3cm 与 ICA 具有良好的相关性(r=0.80,95%CI:0.70-0.87,p<0.001;r=0.82,95%CI:0.72-0.88,p<0.001)。FFR-1cm 和 FFR-lowest 与 ICA 也具有中度相关性(r=0.77,95%CI:0.65-0.85,p<0.001;r=0.78,95%CI:0.67-0.86,p<0.001)。FFR-1cm+FFR-2cm、FFR-2cm+FFR-3cm、FFR-3cm+FFR-lowest、FFR-1cm+FFR-2cm+FFR-3cm 和 FFR-2cm+FFR-3cm+FFR-lowest 与 ICA 也具有相关性(r=0.722;0.722;0.701;0.722;和 0.722,p<0.001)。Bland-Altman 图显示 ICA 和四个 FFR(ICA 与 FFR-1cm、平均差异-0.0158、95%置信区间:-0.1475 至 0.1159;ICA 与 FFR-2cm、平均差异 0.0001、95%置信区间:-0.1222 至 0.1220;ICA 与 FFR-3cm、平均差异 0.0117、95%置信区间:-0.1085 至 0.1318;ICA 与 FFR-lowest、平均差异 0.0343、95%置信区间:-0.1033 至 0.1720)之间存在轻微差异。CCTA、FFR-1cm、FFR-2cm、FFR-3cm 和 FFR-lowest 检测特定部位缺血的 AUC 分别为 0.578、0.768、0.857、0.856 和 0.770。所有 FFR 的 AUC 均高于 CCTA(均 p<0.05),FFR-2cm 的 AUC 最高(0.857)。FFR-2cm 和 FFR-3cm 的 AUC 相当(p>0.05)。FFR-1cm+FFR-2cm、FFR-3cm+FFR-lowest 和 FFR-2cm 单独的 AUC 相似(AUC=0.857、0.857、0.857,p>0.05)。FFR-2cm+FFR-3cm、FFR-1cm+FFR-2cm+FFR-3cm 和 FFR-2cm+FFR-3cm+FFR-lowest(0.871、0.871、0.872)的 AUC 略高于 FFR-2cm 单独的 AUC(0.857),但无显著差异(均 p>0.05)。
在目标病变下边界 2cm 处测量的 FFR 是识别 CAD 患者特定部位缺血的最佳测量部位。