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Automatic correction of background phase offset in 4D-flow of great vessels and of the heart in MRI using a third-order surface model

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Abstract

Objective

To evaluate an automatic correction method for velocity offset errors in cardiac 4D-flow acquisitions.

Materials and methods

Velocity offset correction was done in a plane-by-plane scheme and compared to a volumetric approach. Stationary regions were automatically detected. In vitro experiments were conducted in a phantom using two orientations and two encoding velocities (Venc). First- to third-order models were fit to the time-averaged images of the three velocity components. In vivo experiments included realistic ROIs in a volunteer superimposed to a phantom. In 15 volunteers, blood flow volume of the proximal and distal descending aorta, of the pulmonary artery (Qp) and the ascending aorta (Qs) was compared.

Results

Offset errors were reduced after correction with a third-order model, yielding residual phantom velocities below 0.6 cm/s and 0.4% of Venc. The plane-by-plane correction method was more effective than the volumetric approach. Mean velocities through superimposed ROIs of a volunteer vs phantom were highly correlated (r2 = 0.96). The significant difference between proximal and distal descending aortic flows was decreased after correction from 8.1 to − 1.4 ml (p < 0.001) and Qp/Qs reduced from 1.08 ± 0.09 to 1.01 ± 0.05.

Discussion

An automatic third-order model corrected velocity offset errors in 4D-flow acquisitions, achieving acceptable levels for clinical applications.

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References

  1. Mousseaux E, Tasu JP, Jolivet O, Simonneau G, Bittoun J, Gaux JC (1999) Pulmonary arterial resistance: noninvasive measurement with indexes of pulmonary flow estimated at velocity-encoded MR imaging—preliminary experience. Radiology 212(3):896–902

    Article  CAS  Google Scholar 

  2. Mercer-Rosa L, Yang W, Kutty S, Rychik J, Fogel M, Goldmuntz E (2012) Quantifying pulmonary regurgitation and right ventricular function in surgically repaired tetralogy of Fallot: a comparative analysis of echocardiography and magnetic resonance imaging. Circ Cardiovasc Imaging 5(5):637–643

    Article  Google Scholar 

  3. Dyverfeldt P, Bissell M, Barker AJ, Bolger AF, Carlhall CJ, Ebbers T, Francios CJ, Frydrychowicz A, Geiger J, Giese D, Hope MD, Kilner PJ, Kozerke S, Myerson S, Neubauer S, Wieben O, Markl M (2015) 4D flow cardiovascular magnetic resonance consensus statement. J Cardiovasc Magn Reson 17:72

    Article  Google Scholar 

  4. Bollache E, Redheuil A, Clement-Guinaudeau S, Defrance C, Perdrix L, Ladouceur M, Lefort M, De Cesare A, Herment A, Diebold B, Mousseaux E, Kachenoura N (2010) Automated left ventricular diastolic function evaluation from phase-contrast cardiovascular magnetic resonance and comparison with Doppler echocardiography. J Cardiovasc Magn Reson 12:63

    Article  Google Scholar 

  5. Defrance C, Bollache E, Kachenoura N, Perdrix L, Hrynchyshyn N, Bruguiere E, Redheuil A, Diebold B, Mousseaux E (2012) Evaluation of aortic valve stenosis using cardiovascular magnetic resonance: comparison of an original semiautomated analysis of phase-contrast cardiovascular magnetic resonance with Doppler echocardiography. Circ Cardiovasc Imaging 5(5):604–612

    Article  Google Scholar 

  6. Soulat G, Kachenoura N, Bollache E, Perdrix L, Diebold B, Zhygalina V, Latremouille C, Laurent S, Fabiani JN, Mousseaux E (2017) New estimate of valvuloarterial impedance in aortic valve stenosis: a cardiac magnetic resonance study. J Magn Reson Imaging 45(3):795–803

    Article  Google Scholar 

  7. Chelu RG, van den Bosch AE, van Kranenburg M, Hsiao A, van den Hoven AT, Ouhlous M, Budde RP, Beniest KM, Swart LE, Coenen A, Lubbers MM, Wielopolski PA, Vasanawala SS, Roos-Hesselink JW, Nieman K (2016) Qualitative grading of aortic regurgitation: a pilot study comparing CMR 4D flow and echocardiography. Int J Cardiovasc Imaging 32(2):301–307

    Article  Google Scholar 

  8. Feneis JF, Kyubwa E, Atianzar K, Cheng JY, Alley MT, Vasanawala SS, Demaria AN, Hsiao A (2018) 4D flow MRI quantification of mitral and tricuspid regurgitation: reproducibility and consistency relative to conventional MRI. J Magn Reson Imaging 48(4):1147–1158

    Article  Google Scholar 

  9. Hsiao A, Lustig M, Alley MT, Murphy M, Chan FP, Herfkens RJ, Vasanawala SS (2012) Rapid pediatric cardiac assessment of flow and ventricular volume with compressed sensing parallel imaging volumetric cine phase-contrast MRI. Am J Roentgenol 198(3):W250–W259

    Article  Google Scholar 

  10. Bollache E, Fedak PWM, van Ooij P, Rahman O, Malaisrie SC, McCarthy PM, Carr JC, Powell A, Collins JD, Markl M, Barker AJ (2017) Perioperative evaluation of regional aortic wall shear stress patterns in patients undergoing aortic valve and/or proximal thoracic aortic replacement. J Thorac Cardiovasc Surg 155(6):2277–2286

    Article  Google Scholar 

  11. Wentland AL, Wieben O, Francois CJ, Boncyk C, Munoz Del Rio A, Johnson KM, Grist TM, Frydrychowicz A (2013) Aortic pulse wave velocity measurements with undersampled 4D flow-sensitive MRI: comparison with 2D and algorithm determination. J Magn Reson Imaging 37(4):853–859

    Article  Google Scholar 

  12. Binter C, Gotschy A, Sundermann SH, Frank M, Tanner FC, Luscher TF, Manka R, Kozerke S (2017) Turbulent kinetic energy assessed by multipoint 4-dimensional flow magnetic resonance imaging provides additional information relative to echocardiography for the determination of aortic stenosis severity. Circ Cardiovasc Imaging 10:6

    Article  Google Scholar 

  13. van Ooij P, Allen BD, Contaldi C, Garcia J, Collins J, Carr J, Choudhury L, Bonow RO, Barker AJ, Markl M (2016) 4D flow MRI and T1-mapping: assessment of altered cardiac hemodynamics and extracellular volume fraction in hypertrophic cardiomyopathy. J Magn Reson Imaging 43(1):107–114

    Article  Google Scholar 

  14. Keller EJ, Malaisrie SC, Kruse J, McCarthy PM, Carr JC, Markl M, Barker AJ, Collins JD (2016) Reduction of aberrant aortic haemodynamics following aortic root replacement with a mechanical valved conduit. Interact Cardiovasc Thorac Surg 23(3):416–423

    Article  Google Scholar 

  15. Busch J, Giese D, Kozerke S (2017) Image-based background phase error correction in 4D flow MRI revisited. J Magn Reson Imaging 46(5):1516–1525

    Article  Google Scholar 

  16. Lankhaar JW, Hofman MB, Marcus JT, Zwanenburg JJ, Faes TJ, Vonk-Noordegraaf A (2005) Correction of phase offset errors in main pulmonary artery flow quantification. J Magn Reson Imaging 22(1):73–79

    Article  Google Scholar 

  17. Bernstein MA, Zhou XJ, Polzin JA, King KF, Ganin A, Pelc NJ, Glover GH (1998) Concomitant gradient terms in phase contrast MR: analysis and correction. Magn Reson Med 39(2):300–308

    Article  CAS  Google Scholar 

  18. Markl M, Bammer R, Alley MT, Elkins CJ, Draney MT, Barnett A, Moseley ME, Glover GH, Pelc NJ (2003) Generalized reconstruction of phase contrast MRI: analysis and correction of the effect of gradient field distortions. Magn Reson Med 50(4):791–801

    Article  CAS  Google Scholar 

  19. Gatehouse PD, Rolf MP, Graves MJ, Hofman MB, Totman J, Werner B, Quest RA, Liu Y, von Spiczak J, Dieringer M, Firmin DN, van Rossum A, Lombardi M, Schwitter J, Schulz-Menger J, Kilner PJ (2010) Flow measurement by cardiovascular magnetic resonance: a multi-centre multi-vendor study of background phase offset errors that can compromise the accuracy of derived regurgitant or shunt flow measurements. J Cardiovasc Magn Reson 12:5

    Article  Google Scholar 

  20. Busch J, Vannesjo SJ, Barmet C, Pruessmann KP, Kozerke S (2014) Analysis of temperature dependence of background phase errors in phase-contrast cardiovascular magnetic resonance. J Cardiovasc Magn Reson 16:97

    Article  Google Scholar 

  21. Walker PG, Cranney GB, Scheidegger MB, Waseleski G, Pohost GM, Yoganathan AP (1993) Semiautomated method for noise reduction and background phase error correction in MR phase velocity data. J Magn Reson Imaging 3(3):521–530

    Article  CAS  Google Scholar 

  22. Ebbers T, Haraldsson H, Dyverfeldt P, Sigfridsson A, Warntjes MJB, Wigström L (2008) Higher order weighted least-squares phase offset correction for improved accuracy in phase-contrast MRI. In: ISMRM

  23. Lorenz R, Bock J, Snyder J, Korvink JG, Jung BA, Markl M (2014) Influence of eddy current, Maxwell and gradient field corrections on 3D flow visualization of 3D CINE PC-MRI data. Magn Reson Med 72(1):33–40

    Article  Google Scholar 

  24. Chernobelsky A, Shubayev O, Comeau CR, Wolff SD (2007) Baseline correction of phase contrast images improves quantification of blood flow in the great vessels. J Cardiovasc Magn Reson 9(4):681–685

    Article  Google Scholar 

  25. Lee AT, Pike GB, Pelc NJ (1995) Three-point phase-contrast velocity measurements with increased velocity-to-noise ratio. Magn Reson Med 33(1):122–126

    Article  CAS  Google Scholar 

  26. MacDonald ME, Forkert ND, Pike GB, Frayne R (2016) Phase error correction in time-averaged 3D phase contrast magnetic resonance imaging of the cerebral vasculature. PLoS One 11(2):e0149930

    Article  Google Scholar 

  27. Rigsby CK, Hilpipre N, McNeal GR, Zhang G, Boylan EE, Popescu AR, Choi G, Greiser A, Deng J (2014) Analysis of an automated background correction method for cardiovascular MR phase contrast imaging in children and young adults. Pediatr Radiol 44(3):265–273

    Article  Google Scholar 

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Acknowledgements

The authors thank Prof. Emmanuel Messas, Principal Investigator of the ElastoCardio Project.

Funding

This work was partially supported by grants, PIP no. 1220130100480 (CONICET, Argentine) and PICT no. 2016-0945 (MINCyT, Argentine).

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Authors and Affiliations

Authors

Contributions

Study conception and design: DC, EM. Data acquisition: DC, UG, GS, EM. Data analysis and interpretation: DC, AFP, MEC, UG, JA, GS, EM. Manuscript drafting: DC, AFP, MEC, UG, JA, GS, EM. Critical revision: DC, AFP, MEC, UG, JA, GS, EM

Corresponding author

Correspondence to Damian Craiem.

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Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All experiments were performed in accordance with the Declaration of Helsinki and as approved by the local Ethics Committee.

Informed consent

Informed written consent was obtained from all volunteers.

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Electronic supplementary material

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10334_2019_765_MOESM1_ESM.tif

Figure 4 Sup Each of the 3D velocity components obtained in a representative sagittal plane of the static phantom are represented after adjustment with a third order model and exclusion of 50% of the inner points. Histograms after correction with a third order model are shown for each velocity component. a = anterior, p = posterior, s = superior, i = inferior, r = right, l = left, SD = standard deviation (TIFF 495 kb)

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Craiem, D., Pascaner, A.F., Casciaro, M.E. et al. Automatic correction of background phase offset in 4D-flow of great vessels and of the heart in MRI using a third-order surface model. Magn Reson Mater Phy 32, 629–642 (2019). https://doi.org/10.1007/s10334-019-00765-z

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  • DOI: https://doi.org/10.1007/s10334-019-00765-z

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