Noninvasive Quantification of Pressure-Volume Loops From Brachial Pressure and Cardiovascular Magnetic Resonance

• Published in: Circulation. Cardiovascular imaging Vol. 12; no. 1; p. e008493
• Main Authors: Seemann, Felicia, Arvidsson, Per, Nordlund, David, Kopic, Sascha, Carlsson, Marcus, Arheden, Håkan, Heiberg, Einar
• Format: Journal Article
• Language: English
• Published: United States 01-12-2019
• Subjects: bias; biomarkers; Cardiac and Cardiovascular Systems; Clinical Medicine; heart failure; humans; Kardiologi; Klinisk medicin; magnetic resonance imaging; Medical and Health Sciences; Medicin och hälsovetenskap; Radiologi och bildbehandling; Radiology, Nuclear Medicine and Medical Imaging; heart failure; magnetic resonance imaging; humans; biomarkers; bias
• ISSN: 1941-9651; 1942-0080; 1942-0080
• DOI: 10.1161/circimaging.118.008493

Pressure-volume (PV) loops provide a wealth of information on cardiac function but are not readily available in clinical routine or in clinical trials. This study aimed to develop and validate a noninvasive method to compute individualized left ventricular PV loops.
The proposed method is based on time-varying elastance, with experimentally optimized model parameters from a training set (n=5 pigs), yielding individualized PV loops. Model inputs are left ventricular volume curves from cardiovascular magnetic resonance imaging and brachial pressure. The method was experimentally validated in a separate set (n=9 pig experiments) using invasive pressure measurements and cardiovascular magnetic resonance images and subsequently applied to human healthy controls (n=13) and patients with heart failure (n=28).
There was a moderate-to-excellent agreement between in vivo-measured and model-calculated stroke work (intraclass correlation coefficient, 0.93; bias, -0.02±0.03 J), mechanical potential energy (intraclass correlation coefficient, 0.57; bias, -0.04±0.03 J), and ventricular efficiency (intraclass correlation coefficient, 0.84; bias, 3.5±2.1%). The model yielded lower ventricular efficiency ( P<0.0001) and contractility ( P<0.0001) in patients with heart failure compared with controls, as well as a higher potential energy ( P<0.0001) and energy per ejected volume ( P<0.0001). Furthermore, the model produced realistic values of stroke work and physiologically representative PV loops.
We have developed the first experimentally validated, noninvasive method to compute left ventricular PV loops and associated quantitative measures. The proposed method shows significant agreement with in vivo-derived measurements and could support clinical decision-making and provide surrogate end points in clinical heart failure trials.