期刊
CIRCULATION-CARDIOVASCULAR IMAGING
卷 12, 期 1, 页码 -出版社
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1161/CIRCIMAGING.118.008493
关键词
bias; biomarkers; heart failure; humans; magnetic resonance imaging
资金
- Swedish Research Council, Stockholm, Sweden [2016-01617]
- Swedish Heart Lung Foundation, Stockholm, Sweden [20140524, 20150593]
- ALF (Avtal om Lakarutbildning och Forskning) Medical Faculty grants at Lund University, Lund, Sweden [17401, 446881, 442941, 2014354]
- Swedish Medical Association, Stockholm, Sweden [502641]
- Medtech4Health/VINNOVA, Stockholm, Sweden [2017-01451]
- Knut and Alice Wallenberg Foundation, Stockholm, Sweden
- Vinnova [2017-01451, 2016-01617] Funding Source: Vinnova
- Swedish Research Council [2016-01617] Funding Source: Swedish Research Council
- Forte [2017-01451] Funding Source: Forte
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.
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