title: Effect of heart rate on hemodynamic endpoints under concomitant microvascular disease in a porcine model.
abstract: Diagnosis of the ischemic power of epicardial stenosis with concomitant microvascular disease (MVD) is challenging during coronary interventions, especially under variable hemodynamic factors like heart rate (HR). The goal of this study is to assess the influence of variable HR and percent area stenosis (%AS) in the presence of MVD on pressure drop coefficient (CDP; ratio of transstenotic pressure drop to the distal dynamic pressure) and lesion flow coefficient (LFC; ratio of %AS to the CDP at the throat region). We hypothesize that CDP and LFC are independent of HR. %AS and MVD were created using angioplasty balloons and 90-μm microspheres, respectively. Simultaneous measurements of pressure drop (DP) and velocity were done in 11 Yorkshire pigs. Fractional flow reserve (FFR), CDP, and LFC were calculated for the groups HR < 120 and HR > 120 beats/min, %AS < 50 and %AS > 50, and additionally for DP < 14 and DP > 14 mmHg, and analyzed using regression and ANOVA analysis. Regression analysis showed independence between HR and the FFR, CDP, and LFC while it showed dependence between %AS and the FFR, CDP, and LFC. In the ANOVA analysis, for the HR < 120 beats/min and HR > 120 beats/min groups, the values of FFR (0.82 ± 0.02 and 0.82 ± 0.02), CDP (83.15 ± 26.19 and 98.62 ± 26.04), and LFC (0.16 ± 0.03 and 0.15 ± 0.03) were not significantly different (P > 0.05). However, for %AS < 50 and %AS > 50, the FFR (0.89 ± 0.02 and 0.75 ± 0.02), CDP (35.97 ± 25.79.10 and 143.80 ± 25.41), and LFC (0.09 ± 0.03 and 0.22 ± 0.03) were significantly different (P < 0.05). A similar trend was observed between the DP groups. Under MVD conditions, FFR, CDP, and LFC were not significantly influenced by changes in HR, while they can significantly distinguish %AS and DP groups.
authors.affiliation: School of Dynamic Systems, Department of Mechanical Engineering, University of Cincinnati, Cincinnati, Ohio 45220, USA.
authors.forename: S V
authors.initials: SV
authors.lastname: Peelukhana
authors.forename: R K
authors.initials: RK
authors.lastname: Banerjee
authors.forename: K K
authors.initials: KK
authors.lastname: Kolli
authors.forename: M A
authors.initials: MA
authors.lastname: Effat
authors.forename: T A
authors.initials: TA
authors.lastname: Helmy
authors.forename: M A
authors.initials: MA
authors.lastname: Leesar
authors.forename: E W
authors.initials: EW
authors.lastname: Schneeberger
authors.forename: P
authors.initials: P
authors.lastname: Succop
authors.forename: W
authors.initials: W
authors.lastname: Gottliebson
authors.forename: A
authors.initials: A
authors.lastname: Irif
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D000818:Animals; D001783:Blood Flow Velocity / Q000502:physiology; D001794:Blood Pressure / Q000502:physiology; D002196:Capillaries / Q000503:physiopathology; D002404:Catheterization; D003326:Coronary Circulation / Q000502:physiology; D003627:Data Interpretation, Statistical; D023381:Endpoint Determination; D006339:Heart Rate / Q000502:physiology*; D006439:Hemodynamics / Q000502:physiology*; D008833:Microcirculation / Q000502:physiology; D008863:Microspheres; D012044:Regression Analysis; D013552:Swine; D014652:Vascular Diseases / Q000503:physiopathology*