AIMS: The severity of coronary artery narrowing is a poor predictor of functional significance, in particular in intermediate coronary lesions (30-70% diameter narrowing). The aim of this work was to compare the performance of a quantitative hyperaemic myocardial blood flow (MBF) index derived from adenosine dynamic computed tomography perfusion (CTP) imaging with that of visual CT coronary angiography (CTCA) and semi-automatic quantitative CT (QCT) in the detection of functionally significant coronary lesions in patients with stable chest pain. METHODS AND RESULTS: CTCA and CTP were performed in 80 patients (210 analysable coronary vessels) referred to invasive coronary angiography (ICA). The MBF index (mL/100 mL/min) was computed using a model-based parametric deconvolution method. The diagnostic performance of the MBF index in detecting functionally significant coronary lesions was compared with visual CTCA and QCT. Coronary lesions with invasive fractional flow reserve of ≤0.75 were defined as functionally significant. The optimal cut-off value of the MBF index to detect functionally significant coronary lesions was 78 mL/100 mL/min. On a vessel-territory level, the MBF index had a larger area under the curve (0.95; 95% confidence interval [95% CI]: 0.92-0.98) compared with visual CTCA (0.85; 95% CI: 0.79-0.91) and QCT (0.89; 95% CI: 0.84-0.93) (both P-values <0.001). In the analysis restricted to intermediate coronary lesions, the specificity of visual CTCA (69%) and QCT (77%) could be improved by the subsequent use of the MBF index (89%). CONCLUSION: In this proof-of-principle study, the MBF index performed better than visual CTCA and QCT in the identification of functionally significant coronary lesions. The MBF index had additional value beyond CTCA anatomy in intermediate coronary lesions. This may have a potential to support patient management.
AIMS: The severity of coronary artery narrowing is a poor predictor of functional significance, in particular in intermediate coronary lesions (30-70% diameter narrowing). The aim of this work was to compare the performance of a quantitative hyperaemic myocardial blood flow (MBF) index derived from adenosine dynamic computed tomography perfusion (CTP) imaging with that of visual CT coronary angiography (CTCA) and semi-automatic quantitative CT (QCT) in the detection of functionally significant coronary lesions in patients with stable chest pain. METHODS AND RESULTS: CTCA and CTP were performed in 80 patients (210 analysable coronary vessels) referred to invasive coronary angiography (ICA). The MBF index (mL/100 mL/min) was computed using a model-based parametric deconvolution method. The diagnostic performance of the MBF index in detecting functionally significant coronary lesions was compared with visual CTCA and QCT. Coronary lesions with invasive fractional flow reserve of ≤0.75 were defined as functionally significant. The optimal cut-off value of the MBF index to detect functionally significant coronary lesions was 78 mL/100 mL/min. On a vessel-territory level, the MBF index had a larger area under the curve (0.95; 95% confidence interval [95% CI]: 0.92-0.98) compared with visual CTCA (0.85; 95% CI: 0.79-0.91) and QCT (0.89; 95% CI: 0.84-0.93) (both P-values <0.001). In the analysis restricted to intermediate coronary lesions, the specificity of visual CTCA (69%) and QCT (77%) could be improved by the subsequent use of the MBF index (89%). CONCLUSION: In this proof-of-principle study, the MBF index performed better than visual CTCA and QCT in the identification of functionally significant coronary lesions. The MBF index had additional value beyond CTCA anatomy in intermediate coronary lesions. This may have a potential to support patient management.
Authors: A M Bucher; C N De Cecco; U J Schoepf; R Wang; F G Meinel; S R Binukrishnan; J V Spearman; T J Vogl; B Ruzsics Journal: Br J Radiol Date: 2014-08-19 Impact factor: 3.039
Authors: Kelley R Branch; Ryan D Haley; Marcio Sommer Bittencourt; Amit R Patel; Edward Hulten; Ron Blankstein Journal: Cardiovasc Diagn Ther Date: 2017-10