Quantitative flow ratio derived pullback pressure gradient and CZT-SPECT measured longitudinal flow gradient for hemodynamically significant coronary artery disease.

BACKGROUND

Whether physiological coronary diffuseness assessed by quantitative flow reserve (QFR) pullback pressure gradient (PPG) correlates with longitudinal myocardial blood flow (MBF) gradient and improves diagnostic performances for myocardial ischemia remains unknown.

METHODS AND RESULTS

MBF was measured in mL g min with Tc-MIBI CZT-SPECT at rest and stress, corresponding myocardial flow reserve (MFR = MBF stress/MBF rest) and relative flow reserve (RFR = MBF stenotic area/MBF reference) were calculated. Longitudinal MBF gradient was defined as apical and basal left ventricle MBF gradient. △longitudinal MBF gradient was calculated by longitudinal MBF gradient at stress and rest. QFR-PPG was acquired from virtual QFR pullback curve. QFR-PPG significantly correlated with hyperemic longitudinal MBF gradient (r = 0.45, P = 0.007) and △longitudinal MBF gradient (stress-rest) (r = 0.41, P = 0.016). Vessels with lower RFR had lower QFR-PPG (0.72 vs. 0.82, P = 0.002), hyperemic longitudinal MBF gradient (1.14 vs. 2.22, P = 0.003) and △longitudinal MBF gradient (0.50 vs. 1.02, P = 0.003). QFR-PPG, hyperemic longitudinal MBF gradient and △longitudinal MBF gradient showed comparable diagnostic performances for predicting decreased RFR (area under curve [AUC]: 0.82 vs. 0.81 vs. 0.75, P = NS) or QFR (AUC: 0.83 vs. 0.72 vs. 0.80, P = NS). In addition, QFR-PPG and QFR in combination showed incremental value compared with QFR for predicting RFR (AUC = 0.83 vs. 0.73, P = 0.046, net reclassification index = 0.508, P = 0.001).

CONCLUSION

QFR-PPG significantly correlated with longitudinal MBF gradient and △longitudinal MBF gradient when used for physiological coronary diffuseness assessment. All three parameters had high accuracy in predicting RFR or QFR. Adding physiological diffuseness assessment increased accuracy for predicting myocardial ischemia.