Pulmonary 4D-flow MRI imaging in landrace pigs under rest and stress.

4D-flow MRI Cardiovascular magnetic resonance Flow Pigs Pulmonary circulation Velocity

Journal

The international journal of cardiovascular imaging
ISSN: 1875-8312
Titre abrégé: Int J Cardiovasc Imaging
Pays: United States
ID NLM: 100969716

Informations de publication

Date de publication:
31 May 2024
Historique:
received: 09 11 2023
accepted: 04 05 2024
medline: 31 5 2024
pubmed: 31 5 2024
entrez: 31 5 2024
Statut: aheadofprint

Résumé

4D-flow MRI is a promising technique for assessing vessel hemodynamics. However, its utilization is currently limited by the lack of reference values, particularly for pulmonary vessels. In this work, we have analysed flow and velocity in the pulmonary trunk (PT), left and right pulmonary arteries (LPA and RPA, respectively) in Landrace pigs at both rest and stress through the software MEVISFlow. Nine healthy Landrace pigs were acutely instrumented closed-chest and transported to the CMR facility for evaluation. After rest measurements, dobutamine was administered to achieve a 25% increase in heart rate compared to rest. 4D-flow MRI images have been analysed through MEVISFlow by two independent observers. Inter- and intra-observer reproducibility was quantified using intraclass correlation coefficient. A significant difference between rest and stress regarding flow and velocity in all the pulmonary vessels was observed. Mean flow increased 55% in PT, 75% in LPA and 40% in RPA. Mean peak velocity increased 55% in PT, 75% in LPA and 66% in RPA. A good-to-excellent reproducibility was observed in rest and stress for flow measurements in all three arteries. An excellent reproducibility for velocity was found in PT at rest and stress, a good one for LPA and RPA at rest, while poor reproducibility was found at stress. The current study showed that pulmonary flow and velocity assessed through 4D-flow MRI follow the physiological alterations during cardiac cycle and after stress induced by dobutamine. A clinical translation to assess pulmonary diseases with 4D-flow MRI under stress conditions needs investigation.

Identifiants

pubmed: 38819601
doi: 10.1007/s10554-024-03132-9
pii: 10.1007/s10554-024-03132-9
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024. The Author(s).

Références

Silber D, Lachmann J (2017) Invasive hemodynamics of Pulmonary Disease and the right ventricle. Interventional Cardiol Clin 6(3):329–343
doi: 10.1016/j.iccl.2017.03.004
Topyła-Putowska W, Tomaszewski M, Wysokiński A, Tomaszewski A (2021) Echocardiography in Pulmonary arterial hypertension: comprehensive evaluation and technical considerations. J Clin Med.;10(15)
Parasuraman S, Walker S, Loudon BL, Gollop ND, Wilson AM, Lowery C et al (2016) Assessment of pulmonary artery pressure by echocardiography-A comprehensive review. Int J Cardiol Heart Vasculature 12:45–51
doi: 10.1016/j.ijcha.2016.05.011
Price RR, Creasy JL, Lorenz CH, Partain CL (1992) Magnetic resonance angiography techniques. Invest Radiol 27(Suppl 2):S27–32
doi: 10.1097/00004424-199212002-00006 pubmed: 1468872
Frydrychowicz A, Bley TA, Zadeh ZA, Harloff A, Winterer JT, Hennig J et al (2008) Image analysis in time-resolved large field of view 3D MR-angiography at 3T. J Magn Reson Imaging: JMRI 28(5):1116–1124
doi: 10.1002/jmri.21554 pubmed: 18972352
Lin SP, Brown JJ (2007) MR contrast agents: physical and pharmacologic basics. J Magn Reson Imaging: JMRI 25(5):884–899
doi: 10.1002/jmri.20955 pubmed: 17457803
Markl M, Harloff A, Bley TA, Zaitsev M, Jung B, Weigang E et al (2007) Time-resolved 3D MR velocity mapping at 3T: improved navigator-gated assessment of vascular anatomy and blood flow. J Magn Reson Imaging: JMRI 25(4):824–831
doi: 10.1002/jmri.20871 pubmed: 17345635
Chai P, Mohiaddin R (2005) How we perform cardiovascular magnetic resonance flow assessment using phase-contrast velocity mapping. J Cardiovasc Magn Resonance: Official J Soc Cardiovasc Magn Reson 7(4):705–716
doi: 10.1081/JCMR-200065639
Srichai MB, Lim RP, Wong S, Lee VS (2009) Cardiovascular applications of phase-contrast MRI. AJR Am J Roentgenol 192(3):662–675
doi: 10.2214/AJR.07.3744 pubmed: 19234262
Hsiao A, Alley MT, Massaband P, Herfkens RJ, Chan FP, Vasanawala SS (2011) Improved cardiovascular flow quantification with time-resolved volumetric phase-contrast MRI. Pediatr Radiol 41(6):711–720
doi: 10.1007/s00247-010-1932-z pubmed: 21221566
Chelu RG, van den Bosch AE, van Kranenburg M, Hsiao A, van den Hoven AT, Ouhlous M et al (2016) Qualitative grading of aortic regurgitation: a pilot study comparing CMR 4D-flow and echocardiography. Int J Cardiovasc Imaging 32(2):301–307
doi: 10.1007/s10554-015-0779-7 pubmed: 26498478
Chelu RG, Wanambiro KW, Hsiao A, Swart LE, Voogd T, van den Hoven AT et al (2016) Cloud-processed 4D CMR flow imaging for pulmonary flow quantification. Eur J Radiol 85(10):1849–1856
doi: 10.1016/j.ejrad.2016.07.018 pubmed: 27666627
Carlsson M, Toger J, Kanski M, Bloch KM, Stahlberg F, Heiberg E et al (2011) Quantification and visualization of cardiovascular 4D velocity mapping accelerated with parallel imaging or k-t BLAST: head to head comparison and validation at 1.5 T and 3 T. J Cardiovasc Magn Resonance: Official J Soc Cardiovasc Magn Reson 13:55
doi: 10.1186/1532-429X-13-55
Hanneman K, Sivagnanam M, Nguyen ET, Wald R, Greiser A, Crean AM et al (2014) Magnetic resonance assessment of pulmonary (QP) to systemic (QS) flows using 4D phase-contrast imaging: pilot study comparison with standard through-plane 2D phase-contrast imaging. Acad Radiol 21(8):1002–1008
doi: 10.1016/j.acra.2014.04.012 pubmed: 25018072
Oechtering TH, Nowak A, Sieren MM, Stroth AM, Kirschke N, Wegner F et al (2023) Repeatability and reproducibility of various 4D flow MRI postprocessing software programs in a multi-software and multi-vendor cross-over comparison study. J Cardiovasc Magn Reson 25(1):22
doi: 10.1186/s12968-023-00921-4 pubmed: 36978131 pmcid: 10052852
Faragli A, Tanacli R, Kolp C, Lapinskas T, Stehning C, Schnackenburg B et al (2020) Cardiovascular magnetic resonance feature tracking in pigs: a reproducibility and sample size calculation study. Int J Cardiovasc Imaging 36(4):703–712
doi: 10.1007/s10554-020-01767-y pubmed: 31950298 pmcid: 7125242
Stam K, Chelu RG, van der Velde N, van Duin R, Wielopolski P, Nieman K et al (2019) Validation of 4D-flow CMR against simultaneous invasive hemodynamic measurements: a swine study. Int J Cardiovasc Imaging 35(6):1111–1118
doi: 10.1007/s10554-019-01593-x pubmed: 30963352 pmcid: 6534524
Wentland AL, Wieben O, Shanmuganayagam D, Krueger CG, Meudt JJ, Consigny D et al (2015) Measurements of wall shear stress and aortic pulse wave velocity in swine with familial hypercholesterolemia. J Magn Reson Imaging 41(5):1475–1485
doi: 10.1002/jmri.24681 pubmed: 24964097
Roldán-Alzate A, Frydrychowicz A, Johnson KM, Kellihan H, Chesler NC, Wieben O et al (2014) Non-invasive assessment of cardiac function and pulmonary vascular resistance in an canine model of acute thromboembolic pulmonary hypertension using 4D flow cardiovascular magnetic resonance. J Cardiovasc Magn Resonance: Official J Soc Cardiovasc Magn Reson 16(1):23
doi: 10.1186/1532-429X-16-23
Dyverfeldt P, Bissell M, Barker AJ, Bolger AF, Carlhall CJ, Ebbers T et al (2015) 4D flow cardiovascular magnetic resonance consensus statement. J Cardiovasc Magn Resonance: Official J Soc Cardiovasc Magn Reson 17:72
doi: 10.1186/s12968-015-0174-5
Markl M, Chan FP, Alley MT, Wedding KL, Draney MT, Elkins CJ et al (2003) Time-resolved three-dimensional phase-contrast MRI. J Magn Reson Imaging: JMRI 17(4):499–506
doi: 10.1002/jmri.10272 pubmed: 12655592
Meier S, Hennemuth A, Drexl J, Bock J, Jung B, Preusser T (2013) A fast and noise-robust method for computation of intravascular pressure difference maps from 4D PC-MRI Data. In: Camara, O., Mansi, T., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds) Statistical atlases and computational models of the heart. Imaging and modellingchallenges. STACOM 2012. Lecture notes in computer science, 7746. Springer, Berlin.  https://doi.org/10.1007/978-3-642-36961-2_25
Faragli A, Tanacli R, Kolp C, Abawi D, Lapinskas T, Stehning C et al (2020) Cardiovascular magnetic resonance-derived left ventricular mechanics-strain, cardiac power and end-systolic elastance under various inotropic states in swine. J Cardiovasc Magn Resonance: Official J Soc Cardiovasc Magn Reson 22(1):79
doi: 10.1186/s12968-020-00679-z
Faragli A, Alogna A, Lee CB, Zhu M, Ghorbani N, Lo Muzio FP et al (2021) Non-invasive CMR-Based quantification of myocardial power and efficiency under stress and ischemic conditions in Landrace Pigs. Front Cardiovasc Med 8:689255
doi: 10.3389/fcvm.2021.689255 pubmed: 34381823 pmcid: 8352437
Alogna A, Faragli A, Kolp C, Doeblin P, Tanacli R, Confortola G et al (2023) Blood-oxygen-level dependent (BOLD) T2-Mapping reflects invasively measured central venous Oxygen Saturation in Cardiovascular patients. JACC Cardiovasc Imaging 16(2):251–253
doi: 10.1016/j.jcmg.2022.08.020 pubmed: 36648039
Hennemuth A, Friman O, Schumann C, Bock J, Drexl J, Huellebrand M et al (2011) Fast interactive exploration of 4D MRI flow data. 7964(1):79640E–E
Lankhaar J-W, Hofman MBM, Marcus JT, Zwanenburg JJM, Faes TJC, Vonk-Noordegraaf A (2005) Correction of phase offset errors in main pulmonary artery flow quantification. J Magn Reson Imaging 22(1):73–79
doi: 10.1002/jmri.20361 pubmed: 15971181
Sigovan M, Hope MD, Dyverfeldt P, Saloner D (2011) Comparison of four-dimensional flow parameters for quantification of flow eccentricity in the ascending aorta. J Magn Reson Imaging 34(5):1226–1230
doi: 10.1002/jmri.22800 pubmed: 21928387
Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1(8476):307–310
doi: 10.1016/S0140-6736(86)90837-8 pubmed: 2868172
Hope MD, Sigovan M, Wrenn SJ, Saloner D, Dyverfeldt P (2014) MRI hemodynamic markers of progressive bicuspid aortic valve-related aortic disease. J Magn Reson Imaging 40(1):140–145
doi: 10.1002/jmri.24362 pubmed: 24788592
Garcia J, Barker AJ, Murphy I, Jarvis K, Schnell S, Collins JD et al (2015) Four-dimensional flow magnetic resonance imaging-based characterization of aortic morphometry and haemodynamics: impact of age, aortic diameter, and valve morphology. Eur Heart J - Cardiovasc Imaging 17(8):877–884
doi: 10.1093/ehjci/jev228 pubmed: 26377908 pmcid: 4955292
Burris NS, Sigovan M, Knauer HA, Tseng EE, Saloner D, Hope MD (2014) Systolic flow displacement correlates with future ascending aortic growth in patients with bicuspid aortic valves undergoing magnetic resonance surveillance. Invest Radiol 49(10):635–639
doi: 10.1097/RLI.0000000000000064 pubmed: 24784460
von Knobelsdorff-Brenkenhoff F, Karunaharamoorthy A, Trauzeddel RF, Barker AJ, Blaszczyk E, Markl M et al (2016) Evaluation of Aortic Blood Flow and Wall Shear Stress in Aortic Stenosis and Its Association With Left Ventricular Remodeling. Circulation: Cardiovascular Imaging. ;9(3):e004038
Hertel JN, Jerltorp K, Hansen MEH, Isaksen JL, Sattler SM, Linz B et al (2023) 3D-electroanatomical mapping of the left atrium and catheter-based pulmonary vein isolation in pigs: a practical guide. ;10
Pewowaruk R, Mendrisova K, Larrain C, Francois CJ, Roldán-Alzate A, Lamers L (2021) Comparison of pulmonary artery dimensions in swine obtained from catheter angiography, multi-slice computed tomography, 3D-rotational angiography and phase-contrast magnetic resonance angiography. Int J Cardiovasc Imaging 37(2):743–753
doi: 10.1007/s10554-020-02043-9 pubmed: 33034866

Auteurs

A Faragli (A)

Department of Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité, Augustenburger Platz 1, 13353, Berlin, Germany.
Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Berlin Institute of Health (BIH), Berlin, Germany.
DZHK (German Centre for Cardiovascular Research) partner site Berlin, Berlin, Germany.

M Hüllebrand (M)

Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Deutsches Herzzentrum der Charité (DHZC), Institute of Computer-assisted Cardiovascular Medicine, Berlin, Germany.
Fraunhofer Institute for Digital Medicine MEVIS, Berlin, Germany.

A J Berendsen (AJ)

Department of Biomedical Engineering, Cardiovascular Biomechanics Group, Eindhoven University of Technology, Eindhoven, The Netherlands.

L Tirapu Solà (LT)

Hospital Moises Broggi, Barcelona, Spain.

F P Lo Muzio (FP)

Department of Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité, Augustenburger Platz 1, 13353, Berlin, Germany.
Department of Medicine and Surgery, University of Parma, Parma, Italy.

C Götze (C)

Department of Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité, Augustenburger Platz 1, 13353, Berlin, Germany.
Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.

R Tanacli (R)

Department of Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité, Augustenburger Platz 1, 13353, Berlin, Germany.
Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Berlin Institute of Health (BIH), Berlin, Germany.
DZHK (German Centre for Cardiovascular Research) partner site Berlin, Berlin, Germany.

P Doeblin (P)

Department of Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité, Augustenburger Platz 1, 13353, Berlin, Germany.
Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
DZHK (German Centre for Cardiovascular Research) partner site Berlin, Berlin, Germany.

C Stehning (C)

Clinical Science, Philips Healthcare, Hamburg, Germany.

B Schnackenburg (B)

Clinical Science, Philips Healthcare, Hamburg, Germany.

F N Van der Vosse (FN)

Fraunhofer Institute for Digital Medicine MEVIS, Berlin, Germany.

E Nagel (E)

Institute of Experimental and Translational Cardiac Imaging, DZHK Centre for Cardiovascular Imaging, Goethe University Hospital Frankfurt, Frankfurt am Main, Germany.

H Post (H)

Department of Cardiology, Contilia Heart and Vessel Centre, St. Marien-Hospital Mülheim, Mülheim, Germany.

A Hennemuth (A)

Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Deutsches Herzzentrum der Charité (DHZC), Institute of Computer-assisted Cardiovascular Medicine, Berlin, Germany.
Fraunhofer Institute for Digital Medicine MEVIS, Berlin, Germany.

A Alogna (A)

Department of Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité, Augustenburger Platz 1, 13353, Berlin, Germany.
Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Berlin Institute of Health (BIH), Berlin, Germany.
DZHK (German Centre for Cardiovascular Research) partner site Berlin, Berlin, Germany.

Sebastian Kelle (S)

Department of Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité, Augustenburger Platz 1, 13353, Berlin, Germany. sebastian.kelle@dhzc-charite.de.
Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany. sebastian.kelle@dhzc-charite.de.
DZHK (German Centre for Cardiovascular Research) partner site Berlin, Berlin, Germany. sebastian.kelle@dhzc-charite.de.

Classifications MeSH