FFR CT对冠心病诊断的临床应用进展

基于冠状动脉CT血管成像的无创血流储备分数（FFR_CT）测定作为一项能有效诊断冠状动脉血管狭窄程度和相关血流动力学改变的新技术,已日渐发展成熟并开始得到广泛关注。近年来国际上有多项多中心、大规模临床试验陆续展开,分别针对FFR_CT的诊断准确性、临床决策干预指导意义及危险再分级价值进行逐步探究和验证。就近年来FFR_CT临床应用及研究试验进展进行综述,并简要探讨其局限性及未来发展。     

FFR CT的技术原理、注意事项和结果解释

有创性血流储备分数（FFR）是评价冠状动脉血管生理功能的金标准。FFR_CT是基于冠状动脉CT血管成像的影像后处理技术,可用于评估特异性缺血病灶。大量证据支持FFR_CT有很高的诊断准确性,该技术正在从实验研究应用到临床人群。如何在日常临床工作中优化FFR_CT技术以实现病人利益最大化引起了广泛关注。总结FFR_CT的基本原理,对其注意事项和结果解读进行分析,以利于指导FFR_CT的临床应用。      

FFR CT：是否会有美好的未来？

近年来基于冠状动脉CT血管成像的血流储备分数（FFRCT）成为评估冠状动脉生理功能的一项新技术,能同时提供解剖和功能信息,对于冠状动脉疾病的诊疗有望产生积极影响。简要描述了FFRCT的应用现状及本期重点号的内容,以期使更多的读者了解和应用这项新技术,加快其临床转化的进程。      

钙化对FFR CT诊断冠状动脉疾病准确性影响的研究

目的研究钙化对冠状动脉CT血管成像(CCTA)测定的血流储备分数(FFR_(CT))诊断冠状动脉疾病准确性的影响。方法回顾性分析行CCTA检查和有创FFR检查的38例病人共50支血管的资料。用Agatston积分法测量50支血管的钙化积分值,以钙化积分值100为阈值,分为A1组(≤100)和A2组(100)。利用c FFR软件进行FFR_(CT)值测定,FFR及FFR_(CT)0.8定义为病变特异性心肌缺血。采用组内相关系数(ICC)计算总体及A1、A2组FFR_(CT)与FFR的一致性。以有创FFR作为参考标准,以血管为分析单位,分别计算总体及A1、A2两组FFR_(CT)的诊断准确度、敏感度、特异度、阳性预测值及阴性预测值,并采用Fisher确切概率法比较2组间的差异。结果总体FFR_(CT)和FFR的ICC系数为0.771(95%CI:0.597~0.870),A1组FFR_(CT)和FFR的ICC为0.819(95%CI:0.633~0.910),A2组FFR_(CT)和FFR的ICC为0.649(95%CI:0.032~0.873)。总体FFR_(CT)诊断敏感度、特异度、准确度、阳性预测值及阴性预测值分别为90.9%、97.4%、96.0%、90.9%、97.4%;A1组和A2组FFR_(CT)诊断敏感度、特异度、准确度、阳性预测值及阴性预测值分别为85.7%、100%、96.9%、100%、96.0%和100%、92.3%、94.1%、80.0%、100%;A1和A2组间诊断效能各指标的差异均无统计学意义(均P0.05)。结论 FFR_(CT)与FFR在冠状动脉狭窄血流评估方面有较好的一致性,研究未显示钙化影响FFR_(CT)的诊断效能。     

冠状动脉CT血管成像在引导冠心病介入治疗中的应用及进展

冠状动脉CT血管成像(CCTA)在经皮冠状动脉介入术(PCI)术前可以明确病人是否需要进入导管室检查或治疗,可视化斑块特征及预测PCI术后风险;术中可以提供精确的冠状动脉解剖特征和病变特征,协助选择PCI器材和手术方式;PCI术后利用CCTA可以检测支架内再狭窄。就CCTA在PCI术前、术中和术后的应用价值及研究进展予以综述。     

冠状动脉CT血流储备分数评估心肌缺血：基于计算流体力学仿真技术

目的:探讨国产首款基于计算流体力学仿真技术的计算软件测量的冠状动脉CT血流储备分数(CT-FFR)对心肌缺血的诊断价值。方法:回顾性将临床疑似或已知为冠心病而在本院行冠状动脉CTA和有创性冠脉动脉造影(ICA)检查且有完整FFR测量(ICA-FFR)数据的44例患者(共55支血管)纳入本研究。由独立核心实验室基于CTA图像重建三维血管模型,通过仿真计算得到血管狭窄处的CT-FFR值(≤0.8为心肌缺血风险高),同时计算狭窄位置近端和远端2cm处CT-FFR值的差值(△CT-FFR)。基于CTA和ICA,分别获得冠脉狭窄处的血管狭窄率(SR)。以ICA-FFR≤0.8作为心肌缺血的诊断标准,采用ROC曲线分析评估CT-FFR、△CT-FFR、ICA-SR和CTA-SR对心肌缺血的诊断效能。分别采用Pearson相关分析和Bland-Altman分析评估CT-FFR和ICA-FFR之间的相关性和一致性。结果:基于血管水平,CT-FFR、△CT-FFR、ICA-SR和CTA-SR诊断心肌缺血的AUC分别为0.914(95%CI:0.807～0.973,P<0.001)、0.902(95...     

人工智能冠状动脉CT血管成像在冠心病诊断中的应用

【摘要】目的：探讨人工智能（artificial intelligence,AI）冠状动脉CT血管成像（CCTA）在冠心病诊断中的应用价值。方法：选取本院2018年3-8月,临床疑诊为冠心病的患者50例,对所有患者常规行CCTA扫描,对上传至后处理Sigovia工作站的图像分别由两位高年资医生进行手动冠状动脉分析软件的图像处理、完成报告和由冠心病智能辅助诊断工作站的自动识别图像中的血管和病变并生成报告。评价AI在冠心病中的诊断价值。结果：冠心病诊断中,与常规高年资医生相比,AI对冠心病诊断的阳性预测值为80%,阴性预测值为70%,敏感度为80%,特异度为70%。AI对冠脉病变定位识别的敏感度和特异度分别为73.91%,82.69%。AI对冠脉病变斑块性质识别的敏感度和特异度分别为54.35%,81.73%。在冠脉病变管腔狭窄程度的诊断中,AI和高年资医生对冠脉狭窄的总检出率分别为30.67%、32%,差异无统计学意义（P＞0.05）,AI对冠脉病变管腔狭窄程度识别的敏感度和特异度分别为60.87%,80.77%。结论：与高年资医生相比,AI辅助CCTA对冠心病的诊断具有一定的价值。     

引起冠状动脉功能学缺血性的斑块特征分析

目的 以有创分数血流储备(FFR)为标准,鉴别引起冠状动脉功能性缺血斑块的影像学特征,进一步提高冠状动脉CT血管造影(CCTA)的诊断效能。方法 回顾性纳入2012年9月至2020年1月在本院30天内接受CCTA、有创性冠状动脉造影(ICA)以及导丝FFR检查患者,在CCTA上记录血管狭窄度以及斑块参数,包括非钙化斑块、病变长度、钙化的形态、正性重构、“餐巾环征”、狭窄程度。FFR<0.80的病变被认为功能性缺血性病变。将单因素逻辑回归中有统计学意义的斑块参数纳入多因素模型,受试者工作特征曲线(ROC)分析模型的曲线下面积(AUC),并与单独血管狭窄率模型比较。结果 共纳入173例患者[男112例(61.73±8.34岁]的204枚斑块。将3个单因素有意义的参数(即“餐巾环征”、正性重构、点状钙化)与血管狭窄率共同建立的模型,AUC达到0.837,显著高于单独以血管狭窄率建立的模型(AUC为0.679,P<0.001)。结论 研究表明部分高危斑块特征与血管狭窄率组合建模后对于预测有血流动力学意义的狭窄有着更高的准确率。     

FFR CT对CCTA判定冠状动脉临界狭窄病变血流动力学变化的分析

目的评价基于冠状动脉CT血管成像（CCTA）的冠状动脉血流储备分数（FFR_CT）对CCTA判定临界狭窄病变冠状动脉血流动力学变化的诊断价值。方法回顾性分析了18例同时进行CCTA和有创冠状动脉造影（ICA）的病人,男13例,女5例,年龄49~76岁,平均（61±9）岁。选择冠状动脉临界狭窄病变（狭窄率为50%~70%）为靶血管,经ICA测定血流储备分数（FFR）;记录CCTA影像数据,计算FFR_CT。FFR及FFR_CT均以≤0.80表示受累冠状动脉出现血流动力学改变并需要进一步治疗。以FFR为金标准,计算CCTA及FFR_CT的诊断准确度、敏感度、特异度、阴性预测值及阳性预测值,通过绘制受试者操作特征（ROC）曲线并采用Bland-Altman分析及Spearman相关分析评价CCTA狭窄及FFR_CT对冠状动脉缺血的诊断效能。结果18例病人共27段冠状动脉接受评价,以FFR为金标准,FFR_CT诊断准确度88.9%,敏感度100%,特异度62.5%,阳性预测值86.4%,阴性预测值100%;FFR_CT与FFR呈中等程度相关（r=0.663,P<0.001）;Bland-Altman分析显示FFR_CT与FFR的一致性较好（95%CI：-0.23~0.20）,96.3%（26/27）的点落在一致性界限内,3.7%（1/27）的点在?95%一致性界限外。FFR_CT?ROC曲线下面积大于CCTA的（分别为0.947、0.500,P<0.001）。结论对于冠状动脉临界狭窄病变血流动力学变化的评价,FFR_CT能够提高CCTA在冠状动脉临界狭窄病变缺血方面的诊断能力。     

CT冠状动脉成像在冠心病诊断中的应用

目的:研究CT冠状动脉成像在冠心病早期诊断冠状动脉狭窄定性定量判读的作用。方法:对34例临床未发生急性冠脉综合征的冠心病患者,先后进行冠状动脉造影、128排双源CT冠状动脉成像。以冠状动脉造影为"金标准",计算CT冠状动脉成像敏感性、特异性、阳性预测值、阴性预测值。结果:①与冠状动脉造影相比,CT冠状动脉成像的敏感性为68%,特异性为97%,阳性预测值为89%,阴性预测值为90%。②CT冠状动脉成像有65个血管段图像质量差,约占12%,造成图像质量差的原因主要为钙化,心跳、呼吸伪影,少部分为管腔显示不良。结论:冠心病早期诊断中,CT冠状动脉成像可用作冠状动脉造影前筛选,CT冠状动脉成像阴性的患者不必行冠状动脉造影检查;CT冠状动脉成像阳性的患者,可行冠状动脉造影进一步确认病变。     

Comparison of invasively measured FFR with FFR derived from coronary CT angiography for detection of lesion-specific ischemia: Results from a PC-based prototype algorithm

BackgroundWe evaluated the diagnostic accuracy of a novel prototype for on-site determination of CT-based FFR (cFFR) on a standard personal computer (PC) compared to invasively measured FFR in patients with suspected coronary artery disease.MethodsA total of 91 vessels in 71 patients (mean age 65 ± 9 years) in whom coronary CT angiography had been performed due to suspicion of coronary artery disease, and who subsequently underwent invasive coronary angiography with FFR measurement were analyzed. For both cFFR and FFR, a threshold of ≤0.80 was used to indicate a hemodynamically relevant stenosis. The mean time needed to calculate cFFR was 12.4 ± 3.4 min. A very close correlation between cFFR and FFR could be shown (r = 0.85; p < 0.0001) with Bland-Altman analysis showing moderate agreement between FFR and cFFR with mild systematic overestimation of FFR values in CT (mean difference 0.0049, 95% limits of agreement ±2SD −0.007 to 0.008). Compared to FFR, the sensitivity of cFFR to detect hemodynamically significant lesions was 91% (19/21, 95% CI: 70%–99%), specificity was 96% (67/70, 95% CI: 88%–99%), positive predictive value 86% (95% CI: 65%–97%) and negative predictive value was 97% (95% CI: 90%–100%) with an accuracy of 93%.ConclusioncFFR obtained using an on-site algorithm implemented on a standard PC shows high diagnostic accuracy to detect lesions causing ischemia as compared to FFR. Importantly, the time needed for analysis is short which may be useful for improving clinical workflow.     

Optimized interpretation of fractional flow reserve derived from computed tomography: Comparison of three interpretation methods

BackgroundAn optimal system for interpreting fractional flow reserve (FFR) values derived from CT (FFRCT) is lacking. We sought to evaluate performance of three FFR_CT measurements in detecting ischemia by comparing them with invasive FFR.MethodsFor 73 vessels in 50 patients who underwent coronary CT angiography (CCTA) and FFR_CT analysis followed by invasive FFR, the greatest diameter stenosis on CCTA, FFR_CT difference between distal and proximal to the stenosis (ΔFFR_CT), FFR_CT 2 cm distal to the stenosis (lesion-specific FFR_CT), and the lowest FFR_CT in distal vessel tip were calculated. Significant obstruction (≥50% diameter stenosis) and ischemia (lesion-specific FFR_CT ≤0.80, the lowest FFR_CT ≤0.80, or ΔFFR_CT ≥0.12 based on the greatest Youden index) were compared with invasive FFR (≤0.80).ResultsForty (55%) vessels demonstrated ischemia during invasive FFR. On multivariable generalized estimating equations, ΔFFR_CT (odds ratio [OR] 10.2, p < 0.01) remained a predictor of ischemia over CCTA (OR 2.9), lesion-specific FFR_CT (OR 3.1), and the lowest FFR_CT (OR 0.9) (p > 0.05 for all). Area under the curve (AUC) of ΔFFR_CT (0.86) was higher than CCTA (0.66), lesion-specific FFR_CT (0.71), and the lowest FFR_CT (0.65) (p < 0.01 for all). Addition of each FFR_CT measure to CCTA showed improvement of AUC and significant net reclassification improvement (NRI): ΔFFR_CT (AUC 0.84, NRI 1.24); lesion-specific FFR_CT (AUC 0.77, NRI 0.83); and the lowest FFR_CT (AUC 0.76, NRI 0.59) (p < 0.01 for all).ConclusionsCompared with diameter stenosis, ΔFFR_CT, lesion-specific FFR_CT, and the lowest FFR_CT improved ischemia discrimination and reclassification, with ΔFFR_CT being superior in identifying and discriminating ischemia.     

基于机器学习的FFRCT对冠状动脉功能性狭窄的诊断准确性研究

目的以有创性冠状动脉血流储备分数（FFR）为金标准,探讨不同区间内基于机器深度学习的CT冠状动脉血流储备分数（FFR_CT）对冠状动脉功能性狭窄的诊断准确性。方法?回顾性收集先后行冠状动脉CT血管成像（CCTA）及FFR检查的病人125例（162处病变）,年龄42.0~88.0岁,平均（61.0±8.2）岁,男79例,女46例。两项检查时间间隔≤2周。在CCTA影像上获得病变直径狭窄程度,采用西门子cFFR原型软件（cFFR,version3.0.0）计算FFR_CT数值。以FFR≤0.8为具有血流动力学意义的狭窄,绘制FFR_CT及CCTA的受试者操作特征曲线,获得曲线下面积（AUC）。并计算两种方法的敏感度、特异度、阳性预测值、阴性预测值及准确度。结果FFR_CT及CCTA对于诊断功能性狭窄的AUC分别为0.85、0.76（P<0.05）。基于病人水平分析,CCTA和FFR_CT的诊断敏感度、特异度、准确度分别为77.6%、69.7%、76.8%和85.7%、78.9%和86.1%。当FFR_CT数值≤0.69、0.7~0.8、0.81~0.89、≥0.9时,FFR_CT诊断功能性狭窄的准确度分别为86.4%、61.2%、88.6%、98.2%。结论以FFR为金标准,FFR_CT数值在0.7~0.8之外的病变结果具有良好的诊断准确性,而数值在0.7~0.8区域内的病变诊断准确性欠佳。     

Trans-lesional fractional flow reserve gradient as derived from coronary CT improves patient management: ADVANCE registry

BackgroundThe role of change in fractional flow reserve derived from CT (FFR_CT) across coronary stenoses (ΔFFR_CT) in guiding downstream testing in patients with stable coronary artery disease (CAD) is unknown.ObjectivesTo investigate the incremental value of ΔFFR_CT in predicting early revascularization and improving efficiency of catheter laboratory utilization.MaterialsPatients with CAD on coronary CT angiography (CCTA) were enrolled in an international multicenter registry. Stenosis severity was assessed as per CAD-Reporting and Data System (CAD-RADS), and lesion-specific FFR_CT was measured 2 ?cm distal to stenosis. ΔFFR_CT was manually measured as the difference of FFR_CT across visible stenosis.ResultsOf 4730 patients (66 ?± ?10 years; 34% female), 42.7% underwent ICA and 24.7% underwent early revascularization. ΔFFR_CT remained an independent predictor for early revascularization (odds ratio per 0.05 increase [95% confidence interval], 1.31 [1.26–1.35]; p ?< ?0.001) after adjusting for risk factors, stenosis features, and lesion-specific FFR_CT. Among the 3 models (model 1: risk factors ?+ ?stenosis type and location ?+ ?CAD-RADS; model 2: model 1 ?+ ?FFR_CT; model 3: model 2 ?+ ?ΔFFR_CT), model 3 improved discrimination compared to model 2 (area under the curve, 0.87 [0.86–0.88] vs 0.85 [0.84–0.86]; p ?< ?0.001), with the greatest incremental value for FFR_CT 0.71–0.80. ΔFFR_CT of 0.13 was the optimal cut-off as determined by the Youden index. In patients with CAD-RADS ≥3 and lesion-specific FFR_CT ≤0.8, a diagnostic strategy incorporating ΔFFR_CT >0.13, would potentially reduce ICA by 32.2% (1638–1110, p ?< ?0.001) and improve the revascularization to ICA ratio from 65.2% to 73.1%.ConclusionsΔFFR_CT improves the discrimination of patients who underwent early revascularization compared to a standard diagnostic strategy of CCTA with FFR_CT, particularly for those with FFR_CT 0.71–0.80. ΔFFR_CT has the potential to aid decision-making for ICA referral and improve efficiency of catheter laboratory utilization.     

Assessment of lesion-specific ischemia using fractional flow reserve (FFR) profiles derived from coronary computed tomography angiography (FFRCT) and invasive pressure measurements (FFRINV): Importance of the site of measurement and implications for patient referral for invasive coronary angiography and percutaneous coronary intervention

BackgroundFractional flow reserve (FFR)-derived from computed tomography angiography (CTA; FFRCT) and invasive FFR (FFRINV) are used to assess the need for invasive coronary angiography (ICA) and percutaneous coronary intervention (PCI). The optimal location for measuring FFR and the impact of measurement location have not been well defined.Methods930 patients (age 60.7 + 10 years, 59% male) were included in this study. Normal and diseased coronary arteries were classified into stenosis grades 0–4 in the left anterior descending artery (LAD, n = 518), left circumflex (LCX, n = 112) and right coronary artery (RCA, n = 585). FFRCT (n = 1215 arteries) and FFRINV (n = 26 LAD) profiles were developed by plotting FFR values (y-axis) versus site of measurement (x-axis: ostium, proximal, mid, distal segments). The best location to measure FFR was defined relative to the distal end of the stenosis. FFR ≤0.8 was considered positive for ischemia.ResultsIn normal and stenotic coronary arteries there are significant declines in FFRCT and FFRINV from the ostium to the distal vessel (p < 0.001), due to lesion-specific ischemia and to effects unrelated to the lesion. A reliable location (distal to the stenosis) is 10.5 mm [IQR 7.3–14.8 mm] for FFRCT and within 20–30 mm for FFRINV. Rates of positive FFR (from the distal vessel) reclassified to negative FFR (distal to the stenosis) are 61% (FFRCT) and 33% (FFRINV).ConclusionFFRCT and FFRINV values are influenced by stenosis severity and the site of measurement. FFR measurements from the distal vessel may over-estimate lesion-specific ischemia and result in unnecessary referrals for ICA and PCI.     

Diagnostic concordance and discordance between angiography-based quantitative flow ratio and fractional flow reserve derived from computed tomography in complex coronary artery disease

BackgroundBoth quantitative flow ratio (QFR) and fractional flow reserve derived from computed tomography (FFR_CT) have shown significant correlations with invasive wire-based fractional flow reserve. However, the correlation between QFR and FFR_CT is not fully investigated in patients with complex coronary artery disease (CAD). The aim of this study is to investigate the correlation and agreement between QFR and FFR_CT in patients with de novo three-vessel disease and/or left main CAD.MethodsThis is a post-hoc sub-analysis of the international, multicenter, and randomized SYNTAX III REVOLUTION trial, in which both invasive coronary angiography and coronary computed tomography angiography were prospectively obtained prior to the heart team discussion. QFR was performed in an independent core laboratory and compared with FFR_CT analyzed by HeartFlow?. The correlation and agreement between QFR and FFR_CT were assessed per vessel. Furthermore, independent factors of diagnostic discordance between QFR and FFR_CT were evaluated.ResultsOut of 223 patients, 40 patients were excluded from this analysis due to the unavailability of FFR_CT and/or QFR, and a total of 469 vessels (183 patients) were analyzed. There was a strong correlation between QFR and FFR_CT (R ?= ?0.759; p ?< ?0.001), and the Bland-Altman analysis demonstrated a mean difference of ?0.005 and a standard deviation of 0.116. An independent predictor of diagnostic concordance between QFR and FFR_CT was the lesion location in right coronary artery (RCA) (odds ratio 0.395; 95% confidence interval 0.174–0.894; P ?= ?0.026).ConclusionIn patients with complex CAD, QFR and FFR_CT were strongly correlated. The location of the lesion in RCA was associated with the highest diagnostic concordance between QFR and FFR_CT.