Dynamic pressure-volume loop analysis by simultaneous real-time cardiovascular magnetic resonance and left heart catheterization

Abstract

Background: Left ventricular (LV) contractility and compliance are derived from pressure-volume (PV) loops during dynamic preload reduction, but reliable simultaneous measurements of pressure and volume are challenging with current technologies. We have developed a method to quantify contractility and compliance from PV loops during a dynamic preload reduction using simultaneous measurements of volume from real-time cardiovascular magnetic resonance (CMR) and invasive LV pressures with CMR-specific signal conditioning.

Methods: Dynamic PV loops were derived in 16 swine (n = 7 naïve, n = 6 with aortic banding to increase afterload, n = 3 with ischemic cardiomyopathy) while occluding the inferior vena cava (IVC). Occlusion was performed simultaneously with the acquisition of dynamic LV volume from long-axis real-time CMR at 0.55 T, and recordings of invasive LV and aortic pressures, electrocardiogram, and CMR gradient waveforms. PV loops were derived by synchronizing pressure and volume measurements. Linear regression of end-systolic- and end-diastolic- pressure-volume relationships enabled calculation of contractility. PV loops measurements in the CMR environment were compared to conductance PV loop catheter measurements in 5 animals. Long-axis 2D LV volumes were validated with short-axis-stack images.

Results: Simultaneous PV acquisition during IVC-occlusion was feasible. The cardiomyopathy model measured lower contractility (0.2 ± 0.1 mmHg/ml vs 0.6 ± 0.2 mmHg/ml) and increased compliance (12.0 ± 2.1 ml/mmHg vs 4.9 ± 1.1 ml/mmHg) compared to naïve animals. The pressure gradient across the aortic band was not clinically significant (10 ± 6 mmHg). Correspondingly, no differences were found between the naïve and banded pigs. Long-axis and short-axis LV volumes agreed well (difference 8.2 ± 14.5 ml at end-diastole, -2.8 ± 6.5 ml at end-systole). Agreement in contractility and compliance derived from conductance PV loop catheters and in the CMR environment was modest (intraclass correlation coefficient 0.56 and 0.44, respectively).

Conclusions: Dynamic PV loops during a real-time CMR-guided preload reduction can be used to derive quantitative metrics of contractility and compliance, and provided more reliable volumetric measurements than conductance PV loop catheters.

Keywords: CMR-guided catheterization; Myocardial compliance; Myocardial contractility; Pressure–volume loops; Real-time CMR.

Fig. 1

Dynamic pressure–volume (PV) loops were acquired during preload alteration challenge by inferior vena cava (IVC) occlusion. 1 Extraction of the portion of the pressure and electrocardiogram (ECG) signals recorded simultaneously to imaging were detected from the cardiovascular magnetic resonance (CMR) gradient activity (grey rectangle). 2 In the first ten heartbeats post balloon inflation, end-diastole (red) was detected from the R peaks in the ECG and end-systole (blue) as the onset isovolumic relaxation in the pressure signal. 3 3D left ventricular (LV) volume was derived from long-axis segmentations. End-diastole and end-systole were detected as the maximum and minimum volumes, respectively. 4 PV loops were derived by pairing pressure and volume. Contractility and compliance were derived from the slopes of the end-systolic pressure–volume relationship (ESPVR) and end-diastolic pressure–volume relationship (EDPVR) linear fits, respectively

Fig. 2

Examples of ten consecutive derived PV loops (black) with corresponding ESPVR (blue) and EDPVR (red) lines in A a naïve pig, B a pig 30 days after aortic banding, and C pig 30 days after induction of ischemic cardiomyopathy. D Combined ESPVR and EDPVR from naïve, banded, and cardiomyopathy pigs. The modest pressure gradient over the aortic banding resulted in similar results compared to naïve pigs

Fig. 3

Comparison of short-axis and long-axis measurements of LV end-diastolic and end-systolic volumes (EDV, ESV). Naïve animals are shown as circles, aortic banded animals as squares, and ischemic cardiomyopathy animal models as triangles. A Scatter plot of EDV. B Bland–Altman plot of EDV. Bias and limits of agreement are shown as solid and dashed lines, respectively. C Scatter plot of ESV. D Bland–Altman plot of EDV. ICC, intraclass correlation coefficient; SD, standard deviation

Fig. 4

Example of LV pressures and volumes in a naïve animal, measured in the CMR environment (black) and with a conductance PV loop conductance catheter (gray). Corresponding illustrations of end-diastole and end-systole time points are shown in red and blue, respectively. A LV pressure measured with a fluid-filled catheter in the CMR environment and with a conductance PV loop catheter. Damping was visible in systole and diastole in the fluid-filled pressure measurement. B LV volume measured with short-axis-stack CMR (dashed black line), long-axis real-time CMR, and a PV loop catheter. Volumes measured with real-time CMR were comparable to reference standard short-axis-stack over the entire cardiac cycle, while the PV loop catheter measured larger volumes despite being calibrated using short-axis CMR volumes. C PV loops derived from combined pressure and volumes measurements in the CMR environment using real-time long-axis volumes, and with a PV loop catheter

Fig. 5

Comparison of A contractility and B compliance in the naïve, 30 days after aortic banding, and ischemic cardiomyopathy animal models. Quantitative values were derived from measurements in the CMR environment and are reported as mean ± standard deviation. Animal models were unpaired. ns non-significant; *p < 0.05; **p < 0.01

Fig. 6

Comparison of contractility and compliance measured in the CMR environment and with a conductance PV loop catheter. Naïve animals are shown as circles, and ischemic cardiomyopathy animal models as triangles. A Scatter plot of contractility. B Bland–Altman plot of contractility. Bias and limits of agreement are shown as solid and dashed lines, respectively. C Scatter plot of compliance. D Bland–Altman plot of compliance. ICC intraclass correlation coefficient, SD standard deviation