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The impact of coronary stenosis and risk factors on myocardial flow reserve
International Congress Series 1264 (2004) 257 – 260
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The impact of coronary stenosis and risk factors on myocardial flow reserve Takahiro Tsukamoto *, Koichi Morita, Kazayuki Noriyasu, Chietsugu Katoh, Hiroyuki Kageyama, Megumi Mabuchi, Yuji Kuge, Kunihiro Nakada, Hiroshi Okamoto, Akira Kitabatake, Nagara Tamaki Department of Cardiovascular Medicine, Hokkaido University, Kita 15, Nishi 7, Kitaku, 060-8638 Sapporo, Japan
Abstract. Objective: Myocardial blood flow reserve (MFR) measurement using PET has an important role to assess functional severity of coronary stenosis. However, discrepancy between anatomical severity of coronary stenosis and MFR is often observed. This study was conducted to assess influence of coronary stenosis severity and risk factors upon myocardial blood flow. Methods: 58 patients suspected of having coronary artery disease were enrolled. Myocardial blood flow (MBF) and MFR were measured using PET and oxygen-15-labeled water. MFR was compared with coronary stenosis severity by quantitative coronary angiography (QCA). In addition, a contribution of coronary risk factors to MFR was assessed using multivariate analysis. Results: In the regions with most severe stenosis, MFR correlated inversely with coronary stenosis severity. In multivariate analysis, coronary stenosis severity was the only independent determinant of MFR. In the remote regions, however, MFR did not correlate with coronary stenosis severity. In multivariate analysis, smoking was the only independent predictor for MFR. Conclusion: MFR is determined by not only coronary stenosis severity but also coronary risk factors. Particularly, the influence of risk factor should be considered in the regions with mild coronary stenosis. D 2004 Published by Elsevier B.V. Keywords: Myocardial flow reserve; Coronary risk factor; Coronary stenosis severity; Oxygen-15-labeled water
1. Background Myocardial flow reserve (MFR) measurement using PET has an important role in assessing functional severity of coronary stenosis. However, discrepancy between anatomical severity of coronary stenosis and MFR is often observed. Such discrepancy may
* Corresponding author. Tel.: +81-11-7161161; fax: +81-11-7067874. E-mail address: [email protected] (T. Tsukamoto). 0531-5131/ D 2004 Published by Elsevier B.V. doi:10.1016/j.ics.2003.12.092
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be explained by coronary risk factors, such as diabetes, hypertension, hyperlipidemia, smoking, left ventricular hypertrophy, sex, age and so on [1,2,3,4]. The aim of this study is to assess the influence of coronary stenosis severity and risk factors upon myocardial flow reserve. 2. Methods 2.1. Patients Fifty-eight patients suspected of having coronary artery disease (CAD) were included in this study. All patients underwent both coronary angiography and PET with oxygen-15labeled water. Those with a history of myocardial infarction or CABG were excluded. Patient characteristics are shown in Table 1. 2.2. Protocol Myocardial blood flow (MBF) was measured using PET with oxygen-15-labeled water both at rest and during ATP infusion (0.16 mg/kg/min). MBF was quantified by the use of one-compartment kinetic model. MFR was calculated by the following equation: MFR ¼ MBF during ATP infusion=MBF at rest After a transmission scan, a blood volume image was obtained after inhalation of oxygen-15-labeled carbon monoxide. MBF was measured by infusing oxygen-15-labeled water. All PET scans were performed with PET camera, EXACT HR+ (Fig. 1). Left ventricle was divided into three regions according to coronary territories. MBF and MFR were calculated in the regions with the most severe (>50%) stenosis (most severe regions) and in the remote regions (<50%). Coronary stenosis severity was assessed by quantitative coronary angiography (QCA). In addition, the impact of stenosis severity and coronary risk factors (diabetes, hypertension, hyperlipidemia, smoking, left ventricular hypertrophy, sex and aging) on MFR was assessed by univariate and multivariate analysis.
Table 1 Patient characteristics Age Gender CAG
Risk factors
63F10 years old male/female without stenosis one-vessel disease two-vessel disease three-vessel disease diabetes hypertension hyperlipidemia smoking LVH
42:16 21 (36.2%) 21 (36.2%) 10 (17.2%) 6 (10.3%) 16 (27.6%) 23 (39.7%) 37 (63.8%) 23 (39.7%) 7 (12.1%)
T. Tsukamoto et al. / International Congress Series 1264 (2004) 257–260
259
Fig. 1. PET protcol.
2.3. Statistical analysis All data were expressed as meanFS.D. Regression analysis was performed using a linear regression method. Differences of values were evaluated using a two-tailed unpaired t-test. Multivariate analyses were performed with the use of multiple regression analysis to assess the influence of coronary stenosis and risk factors on MFR. A probable value of P<0.05 was used for statistical significance. 3. Results 3.1. Correlation between stenosis severity and MFR In the most severe regions, the correlation between stenosis severity and MFR was relatively scattered, but statistically significant ( Y=3.870.023X, R=0.42, P<0.05). In the remote regions, there was no significant correlation between stenosis severity and MFR (R=0.233, P=0.11). There was marked variability between coronary stenosis severity and MFR. 3.2. Univariate and multivariate analysis in the most severe regions In the most severe regions, there was no significant difference in MFR between patients with and without the risk factors in univariate analysis. In multivariate analysis, stenosis severity assessed by quantitative coronary angiography was the only significant predictor for MFR ( P<0.01). All risk factors were not significant. 3.3. Univariate and multivariate analysis in the remote regions In the remote regions, MFR significantly decreased with the smoking group in univariate analysis (2.54F0.62 vs. 3.29F1.13, P<0.01). MFR tended to also decrease with the other risk factors, but the difference was not significant. In multivariate analysis, smoking was the
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only independent predictor for MFR ( P<0.05). Stenosis severity was not significant in the remote regions. 3.4. Relationship between MFR and the number of risk factors in the remote regions MFR tended to decrease with the number of risk factors. In the group with more than two risk factors, MFR in the patients with three or more risk factors was significantly lower than that with two or less (2.441F0.571 vs. 3.149F1.066, P<0.05). 4. Discussion It was reported that MFR decreased according to coronary artery stenosis severity [5]. In addition, it is well known that MFR decreases in regions with stenosis over 40% or 50%. MFR is determined by both the large epicardial coronary artery and the microcirculation. Dysfunction of the microcirculation has been found to be caused by coronary risk factors. In our study, in the regions with significant stenosis, MFR decreased with stenosis severity. In the remote regions, however, stenosis severity did not affect MFR, but risk factors did, probably due to microcirculation abnormality. It was reported that patients with CAD had attenuated MBF in the regions without stenosis [6]. In this study, patients with CAD showed decreased MFR in the remote regions, which might be affected by coronary risk factors. Among the risk factors, smoking was the only independent significant determinant of MFR in the remote regions. The other risk factors were not significant due to the fact that patients received specific treatment for these risk factors. By using oxygen-15-labeled water and PET, impaired MFR can be detected in the remote regions, which might be attributed to microcirculatory dysfunction. 5. Conclusions MFR is determined not only by coronary stenosis severity but also by coronary risk factors. Particularly, the influence of risk factors should be considered in the regions without significant coronary stenosis. References [1] I. Yokoyama, S. Momomura, T. Ohtake, et al., Reduced myocardial flow reserve in non-insulin dependent diabetes mellitus, J. Am. Coll. Cardiol. 30 (1997) 1472 – 1477. [2] C.B. Treasure, J.L. Klein, J.A. Vita, et al., Hypertension and left ventricular hypertrophy are associated with impaired endothelium-mediated realization in human coronary resistance vessels, Circulation 87 (1993) 86 – 93. [3] F. Dayanikli, D. Grambow, O. Muzik, et al., Early detection of abnormal coronary flow reserve in asymptomatic men at high risk for coronary artery disease using positron emission tomography, Circulation 90 (1994) 808 – 817. [4] J. Czernin, P. Muller, S. Chan, et al., Influence of age and hemodynamics on myocardial blood flow and flow reserve, Circulation 88 (1993) 62 – 69. [5] N.G. Uren, J.A. Melin, B. De Bruyne, et al., Relation between myocardial blood flow and the severity of coronary-artery stenosis, N. Engl. J. Med. 330 (1994) 1782 – 1788. [6] N.G. Uren, T. Crake, D.C. Lefroy, et al., Reduced coronary vasodilator function in infracted and normal myocardium after myocardial infarction, N. Engl. J. Med. 331 (1994) 222 – 227.
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The impact of coronary stenosis and risk factors on myocardial flow reserve Takahiro Tsukamoto *, Koichi Morita, Kazayuki Noriyasu, Chietsugu Katoh, Hiroyuki Kageyama, Megumi Mabuchi, Yuji Kuge, Kunihiro Nakada, Hiroshi Okamoto, Akira Kitabatake, Nagara Tamaki Department of Cardiovascular Medicine, Hokkaido University, Kita 15, Nishi 7, Kitaku, 060-8638 Sapporo, Japan
Abstract. Objective: Myocardial blood flow reserve (MFR) measurement using PET has an important role to assess functional severity of coronary stenosis. However, discrepancy between anatomical severity of coronary stenosis and MFR is often observed. This study was conducted to assess influence of coronary stenosis severity and risk factors upon myocardial blood flow. Methods: 58 patients suspected of having coronary artery disease were enrolled. Myocardial blood flow (MBF) and MFR were measured using PET and oxygen-15-labeled water. MFR was compared with coronary stenosis severity by quantitative coronary angiography (QCA). In addition, a contribution of coronary risk factors to MFR was assessed using multivariate analysis. Results: In the regions with most severe stenosis, MFR correlated inversely with coronary stenosis severity. In multivariate analysis, coronary stenosis severity was the only independent determinant of MFR. In the remote regions, however, MFR did not correlate with coronary stenosis severity. In multivariate analysis, smoking was the only independent predictor for MFR. Conclusion: MFR is determined by not only coronary stenosis severity but also coronary risk factors. Particularly, the influence of risk factor should be considered in the regions with mild coronary stenosis. D 2004 Published by Elsevier B.V. Keywords: Myocardial flow reserve; Coronary risk factor; Coronary stenosis severity; Oxygen-15-labeled water
1. Background Myocardial flow reserve (MFR) measurement using PET has an important role in assessing functional severity of coronary stenosis. However, discrepancy between anatomical severity of coronary stenosis and MFR is often observed. Such discrepancy may
* Corresponding author. Tel.: +81-11-7161161; fax: +81-11-7067874. E-mail address: [email protected] (T. Tsukamoto). 0531-5131/ D 2004 Published by Elsevier B.V. doi:10.1016/j.ics.2003.12.092
258
T. Tsukamoto et al. / International Congress Series 1264 (2004) 257–260
be explained by coronary risk factors, such as diabetes, hypertension, hyperlipidemia, smoking, left ventricular hypertrophy, sex, age and so on [1,2,3,4]. The aim of this study is to assess the influence of coronary stenosis severity and risk factors upon myocardial flow reserve. 2. Methods 2.1. Patients Fifty-eight patients suspected of having coronary artery disease (CAD) were included in this study. All patients underwent both coronary angiography and PET with oxygen-15labeled water. Those with a history of myocardial infarction or CABG were excluded. Patient characteristics are shown in Table 1. 2.2. Protocol Myocardial blood flow (MBF) was measured using PET with oxygen-15-labeled water both at rest and during ATP infusion (0.16 mg/kg/min). MBF was quantified by the use of one-compartment kinetic model. MFR was calculated by the following equation: MFR ¼ MBF during ATP infusion=MBF at rest After a transmission scan, a blood volume image was obtained after inhalation of oxygen-15-labeled carbon monoxide. MBF was measured by infusing oxygen-15-labeled water. All PET scans were performed with PET camera, EXACT HR+ (Fig. 1). Left ventricle was divided into three regions according to coronary territories. MBF and MFR were calculated in the regions with the most severe (>50%) stenosis (most severe regions) and in the remote regions (<50%). Coronary stenosis severity was assessed by quantitative coronary angiography (QCA). In addition, the impact of stenosis severity and coronary risk factors (diabetes, hypertension, hyperlipidemia, smoking, left ventricular hypertrophy, sex and aging) on MFR was assessed by univariate and multivariate analysis.
Table 1 Patient characteristics Age Gender CAG
Risk factors
63F10 years old male/female without stenosis one-vessel disease two-vessel disease three-vessel disease diabetes hypertension hyperlipidemia smoking LVH
42:16 21 (36.2%) 21 (36.2%) 10 (17.2%) 6 (10.3%) 16 (27.6%) 23 (39.7%) 37 (63.8%) 23 (39.7%) 7 (12.1%)
T. Tsukamoto et al. / International Congress Series 1264 (2004) 257–260
259
Fig. 1. PET protcol.
2.3. Statistical analysis All data were expressed as meanFS.D. Regression analysis was performed using a linear regression method. Differences of values were evaluated using a two-tailed unpaired t-test. Multivariate analyses were performed with the use of multiple regression analysis to assess the influence of coronary stenosis and risk factors on MFR. A probable value of P<0.05 was used for statistical significance. 3. Results 3.1. Correlation between stenosis severity and MFR In the most severe regions, the correlation between stenosis severity and MFR was relatively scattered, but statistically significant ( Y=3.870.023X, R=0.42, P<0.05). In the remote regions, there was no significant correlation between stenosis severity and MFR (R=0.233, P=0.11). There was marked variability between coronary stenosis severity and MFR. 3.2. Univariate and multivariate analysis in the most severe regions In the most severe regions, there was no significant difference in MFR between patients with and without the risk factors in univariate analysis. In multivariate analysis, stenosis severity assessed by quantitative coronary angiography was the only significant predictor for MFR ( P<0.01). All risk factors were not significant. 3.3. Univariate and multivariate analysis in the remote regions In the remote regions, MFR significantly decreased with the smoking group in univariate analysis (2.54F0.62 vs. 3.29F1.13, P<0.01). MFR tended to also decrease with the other risk factors, but the difference was not significant. In multivariate analysis, smoking was the
260
T. Tsukamoto et al. / International Congress Series 1264 (2004) 257–260
only independent predictor for MFR ( P<0.05). Stenosis severity was not significant in the remote regions. 3.4. Relationship between MFR and the number of risk factors in the remote regions MFR tended to decrease with the number of risk factors. In the group with more than two risk factors, MFR in the patients with three or more risk factors was significantly lower than that with two or less (2.441F0.571 vs. 3.149F1.066, P<0.05). 4. Discussion It was reported that MFR decreased according to coronary artery stenosis severity [5]. In addition, it is well known that MFR decreases in regions with stenosis over 40% or 50%. MFR is determined by both the large epicardial coronary artery and the microcirculation. Dysfunction of the microcirculation has been found to be caused by coronary risk factors. In our study, in the regions with significant stenosis, MFR decreased with stenosis severity. In the remote regions, however, stenosis severity did not affect MFR, but risk factors did, probably due to microcirculation abnormality. It was reported that patients with CAD had attenuated MBF in the regions without stenosis [6]. In this study, patients with CAD showed decreased MFR in the remote regions, which might be affected by coronary risk factors. Among the risk factors, smoking was the only independent significant determinant of MFR in the remote regions. The other risk factors were not significant due to the fact that patients received specific treatment for these risk factors. By using oxygen-15-labeled water and PET, impaired MFR can be detected in the remote regions, which might be attributed to microcirculatory dysfunction. 5. Conclusions MFR is determined not only by coronary stenosis severity but also by coronary risk factors. Particularly, the influence of risk factors should be considered in the regions without significant coronary stenosis. References [1] I. Yokoyama, S. Momomura, T. Ohtake, et al., Reduced myocardial flow reserve in non-insulin dependent diabetes mellitus, J. Am. Coll. Cardiol. 30 (1997) 1472 – 1477. [2] C.B. Treasure, J.L. Klein, J.A. Vita, et al., Hypertension and left ventricular hypertrophy are associated with impaired endothelium-mediated realization in human coronary resistance vessels, Circulation 87 (1993) 86 – 93. [3] F. Dayanikli, D. Grambow, O. Muzik, et al., Early detection of abnormal coronary flow reserve in asymptomatic men at high risk for coronary artery disease using positron emission tomography, Circulation 90 (1994) 808 – 817. [4] J. Czernin, P. Muller, S. Chan, et al., Influence of age and hemodynamics on myocardial blood flow and flow reserve, Circulation 88 (1993) 62 – 69. [5] N.G. Uren, J.A. Melin, B. De Bruyne, et al., Relation between myocardial blood flow and the severity of coronary-artery stenosis, N. Engl. J. Med. 330 (1994) 1782 – 1788. [6] N.G. Uren, T. Crake, D.C. Lefroy, et al., Reduced coronary vasodilator function in infracted and normal myocardium after myocardial infarction, N. Engl. J. Med. 331 (1994) 222 – 227.