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

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Bibtex

@article{1d1c203d7967408daa6ae98b561aa9df,
title = "Noninvasive Quantification of Pressure-Volume Loops From Brachial Pressure and Cardiovascular Magnetic Resonance",
abstract = "BACKGROUND: 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. METHODS: 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). RESULTS: 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. CONCLUSIONS: 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.",
keywords = "bias, biomarkers, heart failure, humans, magnetic resonance imaging",
author = "Felicia Seemann and Per Arvidsson and David Nordlund and Sascha Kopic and Marcus Carlsson and H{\aa}kan Arheden and Einar Heiberg",
year = "2019",
month = "1",
day = "11",
doi = "10.1161/CIRCIMAGING.118.008493",
language = "English",
volume = "12",
pages = "e008493",
journal = "Circulation Cardiovascular Imaging",
issn = "1942-0080",
publisher = "Lippincott Williams & Wilkins",
number = "1",

}