血管造影—FPA血液动力学评估猪心外膜冠状动脉和微血管病变
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摘要
第一部分使用血管造影图像评价猪心外膜冠状动脉狭窄生理学严重程度
目的：在临床实践中,冠状动脉血流储备(coronary flow reserve, CFR)和冠状动脉血流储备分数(fractional flow reserve, FFR)都是评价冠状动脉疾病重要的生理学指标,对评价预后也有重要意义,但是其常规的测量方法需要使用侵入性的压力导丝穿过狭窄病灶来完成。一种基于“首过分布”分析技术(first-pass distribution analysis, FPA)和级联放大定律的定量测量方法可以利用冠状动脉血管造影图像数据测量CFR和FFR。本研究的目的是,在猪的动物模型验证基于血管造影图像测量CFR和FFR技术的可行性。对象和方法：本研究使用12只美国实验小型猪,开胸在冠状动脉左前降支(left anterior descending artery,LAD)近段放置超声流量探头,使用血管外封堵器来制造心外膜冠状动脉血管狭窄,向冠状动脉左主干注射对比剂并采集图像。实验中实时记录超声流量探头测定的冠状动脉血流量(Qq)、主动脉压力(Pa)、冠状动脉末端血压(Pd)及右心房血压(Pv)等生理学指标。在LAD血管造影图像的血管床上画兴趣区来绘制“时间—密度曲线”,并假设在注射对比剂时血液被对比剂暂时完全替代,利用“首过分布”分析技术来计算基于血管造影图像的冠状动脉血流量(Q。)。①绝对冠状动脉血流储备由最大充血状态与静息状态血流量的比值来计算,分别使用Qq和Qa计算基于超声流量探头测定的绝对冠状动脉血流储备(aCFRq)和基于血管造影的绝对冠状动脉血流储备(aCFRa)。②使用最大充血状态LAD与回旋支(LCx)的标准化Qa之比率来计算相对冠状动脉血流储备分数(rFFRa)。③基于血管造影的FFR (FFRa)通过使用最大充血状态下的狭窄冠状动脉血流量(Qs)除以理论上无血管狭窄时正常的血流量(QN)来计算。利用“首过分布”分析技术使用“时间—密度曲线”来计算Qs。根据级联放大定律并使用LAD血管总的管腔容量来评估QN。在最大充血状态下使用超声流量探头测量的狭窄冠状动脉血流量与无狭窄时该血管能达到的最大血流量之比作为基于超声流量探头测定的FFR(FFRq)。实验中实时监测压力衍生的FFR(FFRp)是通过使用(Pd-P,)除以(Pa-Pv)来计算。结果：aCFRa与作为金标准的aCFRq有很好的相关性(aCFRa=0.91aCFRq+0.30, r=0.90, p<0.0001), rFFRa也与FFRq线性相关(rFFRa=0.86FFRq+0.05, r=0.90, p<0.0001),FFRa与FFRq显示了很好的相关性(FFRa=0.97FFRq+0.06,r=0.86,p<0.001),而FFRp的值会较FFRq的值高(FFRp=0.686FFRq+0.271, r=0.87,p<0.0001),特别是在严重狭窄的情况下。另外Bland-Altman分析也显示出基于血管造影方法测量的血液动力学指标与基于超声流量探头的金标准指标有很好的一致性。结论：本研究在猪的动物模型验证了基于冠状动脉血管造影图像测定CFR和FFR技术的可行性。这种无需借助多普勒导丝的基于血管造影图像的定量测定CFR和FFR的方法,有潜力被应用于常规的诊断性心血管造影过程中,为冠状动脉狭窄病灶提供生理学评估。
第二部分利用猪的动物模型评价冠状动脉微循环
目的：冠状动脉微循环功能障碍对病人预后具有重要的指示意义。如绝对冠状动脉血流储备(absolute coronary flow reserve, aCFR)、冠状动脉微血管阻力(microvascular resistance, MR)及零血流状态冠状动脉压力(zero-flow pressure,Pzf)等一些血液动力学指标可以被应用于评价冠状动脉微循环状态。但是常规评价冠状动脉微循环状态的方法需要借助多普勒导丝来测定血流速度,对病人创伤大、风险高。许多研究证实了“首过分布”分析技术(first-pass distribution analysis, FPA)可利用血管造影图像来测量冠状动脉血流量。本研究拟通过动物实验验证血管造影方法定量测定MR技术的可行性,并比较上述三种血液动力学指标在评价冠状动脉微循环方面的优劣。对象和方法：本研究使用15只美国实验小型猪,开胸在冠状动脉左前降支(left anterior descending artery, LAD)近段放置超声流量探头以测量血流量,使用介入导管技术在LAD远端放置压力导丝以测量末端血压力。静脉滴注腺苷(400μg/kg/min)来诱导最大充血状态,使用微球体制作冠状动脉微血管障碍模型,并使用血管外封堵器来制造冠状动脉狭窄。在血管造影图像上,选取LAD动脉血管床作为兴趣区来绘制“时间—密度曲线”,并假设血管造影时血液被对比剂瞬时替代,使用“时间—密度曲线”来计算基于血管造影的冠状动脉血流量(Qa)。实验中实时记录超声流量探头测定的冠状动脉血流量(Qq)、主动脉压力(Pa)、冠状动脉末端血压(Pd)及右房血压(Pv)等生理学参数。分别使用Qq和Qa计算基于超声流量探头测定的aCFR (aCFRq)和基于血管造影的aCFR (aCFRa),基于超声流量探头测定的MR(NMRq)和基于血管造影的MR(NMRa)。利用实时测量的Qq和Pd来计算Pzf。结果：在258组冠状动脉血流量和微血管阻力的测量中,Qa与作为金标准的Qp有很好的相关性(Qa=0.90Qq+6.6ml/min, r=0.956, p<0.0001),NMR。也与NMRq线性相关(NMRa=0.90NMRq+0.02mmHg/ml/min, r=0.956,p<0.0001)。另外Bland-Altman分析也显示出NMRa与NMRq有很好的一致性。在两个冠状动脉微循环障碍模型中分别使用受试者工作特性(receiver operating characteristic, ROC)曲线来评价三种血液动力学指标：正常心外膜冠状动脉(N模型)和心外膜冠状动脉狭窄模型(S模型)。在N模型中,aCFR、aCFRa、NMRq、NMRa及Pzf的ROC曲线下面积分别为：0.855、0.836、0.976、0.956、及0.855；在S模型中,aCFRq、aCFRa、NMRq、NMRa及Pzf的ROC曲线下面积分别为：0.737、0.700、0.935、0.889及0.698。NMRq和NMRa在检测冠状动脉微循环病变方面的能力显著高于其他指标。结论：本研究在猪的动物模型验证了基于冠状动脉血管造影图像测定NMR技术的可行性。相比于CFR和Pzf,NMR可以为冠状动脉微循环提供更加准确的评价,特别是存在心外膜冠状动脉狭窄的情况下。本研究提供了一个无需多普勒导丝的测定NMR的方法,该方法测定的NMR有潜力成为一种微创的评价冠状动脉微循环的方法。
Part I Assessment of the physiological severity for coronary epicardial stenosis by using the angiography images data
Object i ve:Coronary flow reserve (CFR) and fractional flow reserve (FFR) are important physiological determinants for coronary disease in the clinical settings. However, the measurements currently require a sensor wire advanced across the stenosis. While an angiographic technique based on first-pass distribution analysis (FPA) and scaling laws can be used to measure CFR and FFR using only image data. The purpose of this study was to validate the CFR and FFR measurement techniques using only angiographic image data. Materials and Methods:Twelve swine were instrumented with an ultrasound flow probe on the left anterior descending artery (LAD). An extravascular occluder was used to produce stenosis. Contrast material injections were made into the left coronary artery during image acquisition. Volumetric blood flow from the flow probe (Qq), coronary pressure (Pa), distal coronary pressure (Pd) and right atrium pressure (Pv) were continuously recorded. Angiography-based blood flow (Qa) was calculated by using a time-density curve based on the FPA technique.①Flow probe based absolute CFR (aCFRq) and angiography based aCFR (aCFRa) were calculated as the ratio of hyperemic to baseline flow using Qq and Qa, respectively.②Relative angiographic FFR (rFFRa) was calculated as the ratio of the normalized Qa in LAD to the left circumflex artery (LCx) during hyperemia.③To determine the angiography-based FFR (FFRa), the ratio of blood flow in the presence of a stenosis (Qs) to theoretically normal blood flow (QN) was calculated. Qs was measured using a time-density curve and the assumption that blood was momentarily replaced with contrast agent during the injection. QN was estimated from the total coronary arterial volume using scaling laws. Flow probe-based FFR (FFRq) was measured from the ratio of flow with and without stenosis. Pressure-wire measurements of FFR (FFRP), which was calculated from the ratio of (Pd-Py) divided by (Pa-Py), were continuously obtained during the study. Resu I ts:aCFRa showed a strong correlation with the gold standard aCFRq (aCFRa=0.91aCFRq+0.30, r=0.90, p<0.0001). Relative FFRa correlated linearly with FFRq (relative FFRa=0.86FFRq+0.05, r=0.90, p<0.0001). FFRa showed a good correlation with FFRq (FFRa=0.97FFRq+0.06, r=0.86, p<0.001), although FFRP overestimated the FFRq (FFRp=0.686FFRq+0.271, r=0.87, p<0.0001). Additionally, the Bland-Altman analysis showed a close agreement between the angiographic and the gold standard flow probe indices. Conelusions:The quantification of CFR and FFR using angiographic image data was validated in a swine model. This angiographic technique, which does not require a wire across the stenosis, could potentially be used for coronary physiological assessment during routine cardiac catheterization.
Part Ⅱ Assessment of Coronary Microcirculation in a Swine Animal Model
Objective:Structural coronary microcirculation abnormalities are important prognostic determinants in clinical settings. Several hemodynamic indices, such as absolute coronary flow reserve (aCFR), microvascular resistance (MR) and zero-flow pressure (Pzf). However, assessment of coronary microvascular system requires a velocity wire. A first-pass distribution analysis (FPA) technique to measure volumetric blood flow has previously been validated. The aim of this study was the in vivo validation of the MR measurement technique using FPA, to compare and establish the most reliable index to assess coronary microcirculation. Materials and Methods:Twelve anesthetized swine were instrumented with a transit-time ultrasound flow probe on the proximal segment of the left anterior descending (LAD) artery. A pressure wire was advanced into the distal LAD. Intravenous adenosine (400μg/kg/min) was used to produce maximum hyperemia. Microspheres were injected into the LAD to create a model of microvascular dysfunction. An occluder was used to produce stenosis. A region of interest in the LAD arterial bed was drawn to generate time-density curves using angiographic images. Volumetric blood flow measurements (Qa) were made using a time-density curve and the assumption that blood was momentarily replaced with contrast agent during the injection. Blood flow from the probe (Qq), aortic pressure (Pa), distal coronary pressure (Pd) and right atrium pressure (Pv) were continuously recorded. Flow probe based aCFR (aCFRq) and angiographic aCFR (aCFRa) were calculated using Qq and Qa, respectively. Flow probe based normalized MR (NMRq) and angiography based normalized MR (NMRa) were calculated using Qq and Qa, respectively during hyperemia. Pzf was calculated using Qq and Pd. Results:In258measurements, Qa showed a strong correlation with the gold standard Qq (Qa=0.90Qq+6.6ml/min, r=0.956, p<0.0001). NMRa correlated linearly with NMRq (NMRa=0.90NMRq+0.02mmHg/ml/min, r=0.956, p<0.0001). Additionally, the Bland-Altman analysis showed a close agreement between NMRa and NMRq. Two series of ROC curves were generated: normal epicardial artery model (N-model) and stenosis model (S-model). The areas under the ROC curves for aCFRq, aCFRa, NMRq, NMRa, Pzf were0.855,0.836,0.976,0.956,0.855in N-model and0.737,0.700,0.935,0.889,0.698in S-model. Both NMRq and NMRa were significantly more reliable than aCFR and Pzf in detecting the microvascular deterioration. Conelusions:A technique based on angiographic image data for quantifying NMR was validated using a swine model. Compared to aCFR and Pzf, NMR provided a more accurate assessment of microcirculation. This improved accuracy was more prevalent when stenosis existed. This study provides a method to measure NMR, without using a velocity wire, which can potentially be used to evaluate microvascular conditions during coronary arteriography as a less invasive method.
目的：在临床实践中,冠状动脉血流储备(coronary flow reserve, CFR)和冠状动脉血流储备分数(fractional flow reserve, FFR)都是评价冠状动脉疾病重要的生理学指标,对评价预后也有重要意义,但是其常规的测量方法需要使用侵入性的压力导丝穿过狭窄病灶来完成。一种基于“首过分布”分析技术(first-pass distribution analysis, FPA)和级联放大定律的定量测量方法可以利用冠状动脉血管造影图像数据测量CFR和FFR。本研究的目的是,在猪的动物模型验证基于血管造影图像测量CFR和FFR技术的可行性。对象和方法：本研究使用12只美国实验小型猪,开胸在冠状动脉左前降支(left anterior descending artery,LAD)近段放置超声流量探头,使用血管外封堵器来制造心外膜冠状动脉血管狭窄,向冠状动脉左主干注射对比剂并采集图像。实验中实时记录超声流量探头测定的冠状动脉血流量(Qq)、主动脉压力(Pa)、冠状动脉末端血压(Pd)及右心房血压(Pv)等生理学指标。在LAD血管造影图像的血管床上画兴趣区来绘制“时间—密度曲线”,并假设在注射对比剂时血液被对比剂暂时完全替代,利用“首过分布”分析技术来计算基于血管造影图像的冠状动脉血流量(Q。)。①绝对冠状动脉血流储备由最大充血状态与静息状态血流量的比值来计算,分别使用Qq和Qa计算基于超声流量探头测定的绝对冠状动脉血流储备(aCFRq)和基于血管造影的绝对冠状动脉血流储备(aCFRa)。②使用最大充血状态LAD与回旋支(LCx)的标准化Qa之比率来计算相对冠状动脉血流储备分数(rFFRa)。③基于血管造影的FFR (FFRa)通过使用最大充血状态下的狭窄冠状动脉血流量(Qs)除以理论上无血管狭窄时正常的血流量(QN)来计算。利用“首过分布”分析技术使用“时间—密度曲线”来计算Qs。根据级联放大定律并使用LAD血管总的管腔容量来评估QN。在最大充血状态下使用超声流量探头测量的狭窄冠状动脉血流量与无狭窄时该血管能达到的最大血流量之比作为基于超声流量探头测定的FFR(FFRq)。实验中实时监测压力衍生的FFR(FFRp)是通过使用(Pd-P,)除以(Pa-Pv)来计算。结果：aCFRa与作为金标准的aCFRq有很好的相关性(aCFRa=0.91aCFRq+0.30, r=0.90, p<0.0001), rFFRa也与FFRq线性相关(rFFRa=0.86FFRq+0.05, r=0.90, p<0.0001),FFRa与FFRq显示了很好的相关性(FFRa=0.97FFRq+0.06,r=0.86,p<0.001),而FFRp的值会较FFRq的值高(FFRp=0.686FFRq+0.271, r=0.87,p<0.0001),特别是在严重狭窄的情况下。另外Bland-Altman分析也显示出基于血管造影方法测量的血液动力学指标与基于超声流量探头的金标准指标有很好的一致性。结论：本研究在猪的动物模型验证了基于冠状动脉血管造影图像测定CFR和FFR技术的可行性。这种无需借助多普勒导丝的基于血管造影图像的定量测定CFR和FFR的方法,有潜力被应用于常规的诊断性心血管造影过程中,为冠状动脉狭窄病灶提供生理学评估。
第二部分利用猪的动物模型评价冠状动脉微循环
目的：冠状动脉微循环功能障碍对病人预后具有重要的指示意义。如绝对冠状动脉血流储备(absolute coronary flow reserve, aCFR)、冠状动脉微血管阻力(microvascular resistance, MR)及零血流状态冠状动脉压力(zero-flow pressure,Pzf)等一些血液动力学指标可以被应用于评价冠状动脉微循环状态。但是常规评价冠状动脉微循环状态的方法需要借助多普勒导丝来测定血流速度,对病人创伤大、风险高。许多研究证实了“首过分布”分析技术(first-pass distribution analysis, FPA)可利用血管造影图像来测量冠状动脉血流量。本研究拟通过动物实验验证血管造影方法定量测定MR技术的可行性,并比较上述三种血液动力学指标在评价冠状动脉微循环方面的优劣。对象和方法：本研究使用15只美国实验小型猪,开胸在冠状动脉左前降支(left anterior descending artery, LAD)近段放置超声流量探头以测量血流量,使用介入导管技术在LAD远端放置压力导丝以测量末端血压力。静脉滴注腺苷(400μg/kg/min)来诱导最大充血状态,使用微球体制作冠状动脉微血管障碍模型,并使用血管外封堵器来制造冠状动脉狭窄。在血管造影图像上,选取LAD动脉血管床作为兴趣区来绘制“时间—密度曲线”,并假设血管造影时血液被对比剂瞬时替代,使用“时间—密度曲线”来计算基于血管造影的冠状动脉血流量(Qa)。实验中实时记录超声流量探头测定的冠状动脉血流量(Qq)、主动脉压力(Pa)、冠状动脉末端血压(Pd)及右房血压(Pv)等生理学参数。分别使用Qq和Qa计算基于超声流量探头测定的aCFR (aCFRq)和基于血管造影的aCFR (aCFRa),基于超声流量探头测定的MR(NMRq)和基于血管造影的MR(NMRa)。利用实时测量的Qq和Pd来计算Pzf。结果：在258组冠状动脉血流量和微血管阻力的测量中,Qa与作为金标准的Qp有很好的相关性(Qa=0.90Qq+6.6ml/min, r=0.956, p<0.0001),NMR。也与NMRq线性相关(NMRa=0.90NMRq+0.02mmHg/ml/min, r=0.956,p<0.0001)。另外Bland-Altman分析也显示出NMRa与NMRq有很好的一致性。在两个冠状动脉微循环障碍模型中分别使用受试者工作特性(receiver operating characteristic, ROC)曲线来评价三种血液动力学指标：正常心外膜冠状动脉(N模型)和心外膜冠状动脉狭窄模型(S模型)。在N模型中,aCFR、aCFRa、NMRq、NMRa及Pzf的ROC曲线下面积分别为：0.855、0.836、0.976、0.956、及0.855；在S模型中,aCFRq、aCFRa、NMRq、NMRa及Pzf的ROC曲线下面积分别为：0.737、0.700、0.935、0.889及0.698。NMRq和NMRa在检测冠状动脉微循环病变方面的能力显著高于其他指标。结论：本研究在猪的动物模型验证了基于冠状动脉血管造影图像测定NMR技术的可行性。相比于CFR和Pzf,NMR可以为冠状动脉微循环提供更加准确的评价,特别是存在心外膜冠状动脉狭窄的情况下。本研究提供了一个无需多普勒导丝的测定NMR的方法,该方法测定的NMR有潜力成为一种微创的评价冠状动脉微循环的方法。
Part I Assessment of the physiological severity for coronary epicardial stenosis by using the angiography images data
Object i ve:Coronary flow reserve (CFR) and fractional flow reserve (FFR) are important physiological determinants for coronary disease in the clinical settings. However, the measurements currently require a sensor wire advanced across the stenosis. While an angiographic technique based on first-pass distribution analysis (FPA) and scaling laws can be used to measure CFR and FFR using only image data. The purpose of this study was to validate the CFR and FFR measurement techniques using only angiographic image data. Materials and Methods:Twelve swine were instrumented with an ultrasound flow probe on the left anterior descending artery (LAD). An extravascular occluder was used to produce stenosis. Contrast material injections were made into the left coronary artery during image acquisition. Volumetric blood flow from the flow probe (Qq), coronary pressure (Pa), distal coronary pressure (Pd) and right atrium pressure (Pv) were continuously recorded. Angiography-based blood flow (Qa) was calculated by using a time-density curve based on the FPA technique.①Flow probe based absolute CFR (aCFRq) and angiography based aCFR (aCFRa) were calculated as the ratio of hyperemic to baseline flow using Qq and Qa, respectively.②Relative angiographic FFR (rFFRa) was calculated as the ratio of the normalized Qa in LAD to the left circumflex artery (LCx) during hyperemia.③To determine the angiography-based FFR (FFRa), the ratio of blood flow in the presence of a stenosis (Qs) to theoretically normal blood flow (QN) was calculated. Qs was measured using a time-density curve and the assumption that blood was momentarily replaced with contrast agent during the injection. QN was estimated from the total coronary arterial volume using scaling laws. Flow probe-based FFR (FFRq) was measured from the ratio of flow with and without stenosis. Pressure-wire measurements of FFR (FFRP), which was calculated from the ratio of (Pd-Py) divided by (Pa-Py), were continuously obtained during the study. Resu I ts:aCFRa showed a strong correlation with the gold standard aCFRq (aCFRa=0.91aCFRq+0.30, r=0.90, p<0.0001). Relative FFRa correlated linearly with FFRq (relative FFRa=0.86FFRq+0.05, r=0.90, p<0.0001). FFRa showed a good correlation with FFRq (FFRa=0.97FFRq+0.06, r=0.86, p<0.001), although FFRP overestimated the FFRq (FFRp=0.686FFRq+0.271, r=0.87, p<0.0001). Additionally, the Bland-Altman analysis showed a close agreement between the angiographic and the gold standard flow probe indices. Conelusions:The quantification of CFR and FFR using angiographic image data was validated in a swine model. This angiographic technique, which does not require a wire across the stenosis, could potentially be used for coronary physiological assessment during routine cardiac catheterization.
Part Ⅱ Assessment of Coronary Microcirculation in a Swine Animal Model
Objective:Structural coronary microcirculation abnormalities are important prognostic determinants in clinical settings. Several hemodynamic indices, such as absolute coronary flow reserve (aCFR), microvascular resistance (MR) and zero-flow pressure (Pzf). However, assessment of coronary microvascular system requires a velocity wire. A first-pass distribution analysis (FPA) technique to measure volumetric blood flow has previously been validated. The aim of this study was the in vivo validation of the MR measurement technique using FPA, to compare and establish the most reliable index to assess coronary microcirculation. Materials and Methods:Twelve anesthetized swine were instrumented with a transit-time ultrasound flow probe on the proximal segment of the left anterior descending (LAD) artery. A pressure wire was advanced into the distal LAD. Intravenous adenosine (400μg/kg/min) was used to produce maximum hyperemia. Microspheres were injected into the LAD to create a model of microvascular dysfunction. An occluder was used to produce stenosis. A region of interest in the LAD arterial bed was drawn to generate time-density curves using angiographic images. Volumetric blood flow measurements (Qa) were made using a time-density curve and the assumption that blood was momentarily replaced with contrast agent during the injection. Blood flow from the probe (Qq), aortic pressure (Pa), distal coronary pressure (Pd) and right atrium pressure (Pv) were continuously recorded. Flow probe based aCFR (aCFRq) and angiographic aCFR (aCFRa) were calculated using Qq and Qa, respectively. Flow probe based normalized MR (NMRq) and angiography based normalized MR (NMRa) were calculated using Qq and Qa, respectively during hyperemia. Pzf was calculated using Qq and Pd. Results:In258measurements, Qa showed a strong correlation with the gold standard Qq (Qa=0.90Qq+6.6ml/min, r=0.956, p<0.0001). NMRa correlated linearly with NMRq (NMRa=0.90NMRq+0.02mmHg/ml/min, r=0.956, p<0.0001). Additionally, the Bland-Altman analysis showed a close agreement between NMRa and NMRq. Two series of ROC curves were generated: normal epicardial artery model (N-model) and stenosis model (S-model). The areas under the ROC curves for aCFRq, aCFRa, NMRq, NMRa, Pzf were0.855,0.836,0.976,0.956,0.855in N-model and0.737,0.700,0.935,0.889,0.698in S-model. Both NMRq and NMRa were significantly more reliable than aCFR and Pzf in detecting the microvascular deterioration. Conelusions:A technique based on angiographic image data for quantifying NMR was validated using a swine model. Compared to aCFR and Pzf, NMR provided a more accurate assessment of microcirculation. This improved accuracy was more prevalent when stenosis existed. This study provides a method to measure NMR, without using a velocity wire, which can potentially be used to evaluate microvascular conditions during coronary arteriography as a less invasive method.
引文
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