OBJECTIVES: We developed a quantitative Dynamic Contrast-Enhanced CT (DCE-CT) technique for measuring Myocardial Perfusion Reserve (MPR) and Volume Reserve (MVR) and studied their relationship with coronary stenosis. METHODS: Twenty-six patients with Coronary Artery Disease (CAD) were recruited. Degree of stenosis in each coronary artery was classified from catheter-based angiograms as Non-Stenosed (NS, angiographically normal or mildly irregular), Moderately Stenosed (MS, 50-80% reduction in luminal diameter), Severely Stenosed (SS, >80%) and SS with Collaterals (SSC). DCE-CT at rest and after dipyridamole infusion was performed using 64-slice CT. Mid-diastolic heart images were corrected for beam hardening and analyzed using proprietary software to calculate Myocardial Blood Flow (MBF, in mL∙min(-1)∙100 g(-1)) and Blood Volume (MBV, in mL∙100 g(-1)) parametric maps. MPR and MVR in each coronary territory were calculated by dividing MBF and MBV after pharmacological stress by their respective baseline values. RESULTS: MPR and MVR in MS and SS territories were significantly lower than those of NS territories (p < 0.05 for all). Logistic regression analysis identified MPR∙MVR as the best predictor of ≥50% coronary lesion than MPR or MVR alone. CONCLUSIONS: DCE-CT imaging with quantitative CT perfusion analysis could be useful for detecting coronary stenoses that are functionally significant.
OBJECTIVES: We developed a quantitative Dynamic Contrast-Enhanced CT (DCE-CT) technique for measuring Myocardial Perfusion Reserve (MPR) and Volume Reserve (MVR) and studied their relationship with coronary stenosis. METHODS: Twenty-six patients with Coronary Artery Disease (CAD) were recruited. Degree of stenosis in each coronary artery was classified from catheter-based angiograms as Non-Stenosed (NS, angiographically normal or mildly irregular), Moderately Stenosed (MS, 50-80% reduction in luminal diameter), Severely Stenosed (SS, >80%) and SS with Collaterals (SSC). DCE-CT at rest and after dipyridamole infusion was performed using 64-slice CT. Mid-diastolic heart images were corrected for beam hardening and analyzed using proprietary software to calculate Myocardial Blood Flow (MBF, in mL∙min(-1)∙100 g(-1)) and Blood Volume (MBV, in mL∙100 g(-1)) parametric maps. MPR and MVR in each coronary territory were calculated by dividing MBF and MBV after pharmacological stress by their respective baseline values. RESULTS: MPR and MVR in MS and SS territories were significantly lower than those of NS territories (p < 0.05 for all). Logistic regression analysis identified MPR∙MVR as the best predictor of ≥50% coronary lesion than MPR or MVR alone. CONCLUSIONS:DCE-CT imaging with quantitative CT perfusion analysis could be useful for detecting coronary stenoses that are functionally significant.
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