Abstract
BACKGROUND: Microvascular resistance reserve (MRR) is a recently introduced specific index of coronary microcirculation. MRR calculation can utilize parameters deriving from coronary flow reserve (CFR) assessment, provided that intracoronary pressure data are also available. The previously proposed pressure-bounded CFR (CFRpb) defines the possible CFR interval on the basis of resting and hyperemic pressure gradients in the epicardial vessel, however, its correlation to the Doppler wire measurement was reported to be rather poor without the correction for hydrostatic pressure. PURPOSE: We aimed to determine the pressure-bounded coronary MRR interval with hydrostatic pressure correction according to the previously established equations of CFRpb adapted for the MRR concept. Furthermore, we also aimed to design a prediction model using the actual MRR value within the pressure-bounded interval and validate the results against the gold-standard Doppler wire technique. METHODS: Hydrostatic pressure between the tip of the catheter and the sensor of the pressure wire was calculated by height difference measurement from a lateral angiographic view. In the derivation cohort the pressure-bounded MRR interval (between MRRpb(min) and MRRpb(max)) was determined solely from hydrostatic pressure-corrected intracoronary pressure data. The actual MRR was calculated by simple hemodynamic equations incorporating the anatomical data of the three-dimensionally reconstructed coronary artery (MRR(p-3D)). These results were analyzed by regression analyses to find relations between the MRRpb bounds and the actual MRR(p-3D). RESULTS: In the derivation cohort of 23 measurements, linear regression analysis showed a tight relation between MRRpb(max) and MRR(p-3D) (r (2 )= 0.74, p < 0.0001). Using this relation (MRR(p-3D) = 1.04 + 0.51 × MRRpb(max)), the linear prediction of the MRR was tested in the validation cohort of 19 measurements against the gold standard Doppler wire technique. A significant correlation was found between the linearly predicted and the measured values (r = 0.54, p = 0.01). If the area stenosis (AS%) was included to a quadratic prediction model, the correlation was improved (r = 0.63, p = 0.004). CONCLUSIONS: The MRR can be predicted reliably to assess microvascular function by our simple model. After the correction for hydrostatic pressure error, the pressure data during routine FFR measurement provides a simultaneous physiological assessment of the macro- and microvasculature.