Noninvasive Quantification of Pressure-Volume Loops From Brachial Pressure and Cardiovascular Magnetic Resonance
(2019) In Circulation. Cardiovascular imaging 12(1). p.008493-008493- 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... (More)
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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- author
- Seemann, Felicia LU ; Arvidsson, Per LU ; Nordlund, David LU ; Kopic, Sascha LU ; Carlsson, Marcus LU ; Arheden, Håkan LU and Heiberg, Einar LU
- organization
- publishing date
- 2019-01-11
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- bias, biomarkers, heart failure, humans, magnetic resonance imaging
- in
- Circulation. Cardiovascular imaging
- volume
- 12
- issue
- 1
- pages
- 008493 - 008493
- publisher
- Lippincott Williams & Wilkins
- external identifiers
-
- pmid:30630347
- scopus:85059828658
- ISSN
- 1942-0080
- DOI
- 10.1161/CIRCIMAGING.118.008493
- project
- Advanced CMR analysis: from pixels to physiology
- language
- English
- LU publication?
- yes
- id
- 1d1c203d-7967-408d-aa6a-e98b561aa9df
- date added to LUP
- 2019-01-23 08:15:30
- date last changed
- 2022-09-08 22:53:34
@article{1d1c203d-7967-408d-aa6a-e98b561aa9df, abstract = {{<p>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.</p>}}, author = {{Seemann, Felicia and Arvidsson, Per and Nordlund, David and Kopic, Sascha and Carlsson, Marcus and Arheden, Håkan and Heiberg, Einar}}, issn = {{1942-0080}}, keywords = {{bias; biomarkers; heart failure; humans; magnetic resonance imaging}}, language = {{eng}}, month = {{01}}, number = {{1}}, pages = {{008493--008493}}, publisher = {{Lippincott Williams & Wilkins}}, series = {{Circulation. Cardiovascular imaging}}, title = {{Noninvasive Quantification of Pressure-Volume Loops From Brachial Pressure and Cardiovascular Magnetic Resonance}}, url = {{http://dx.doi.org/10.1161/CIRCIMAGING.118.008493}}, doi = {{10.1161/CIRCIMAGING.118.008493}}, volume = {{12}}, year = {{2019}}, }