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Validation of pressure drop assessment using 4D flow MRI-based turbulence production in various shapes of aortic stenoses
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Department of Mechanical and Biomedical Engineering, Kangwon National University, Chuncheon, Republic of Korea.
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart and Medicine Center, Department of Thoracic and Vascular Surgery. Department of Cardiothoracic Surgery, Oslo University Hospital, Rikshospitalet, Oslo, Norway.
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0003-1395-8296
2019 (English)In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 81, no 2, p. 893-906Article in journal (Refereed) Published
Abstract [en]

Purpose

To validate pressure drop measurements using 4D flow MRI‐based turbulence production in various shapes of stenotic stenoses.

Methods

In vitro flow phantoms with seven different 3D‐printed aortic valve geometries were constructed and scanned with 4D flow MRI with six‐directional flow encoding (ICOSA6). The pressure drop through the valve was non‐invasively predicted based on the simplified Bernoulli, the extended Bernoulli, the turbulence production, and the shear‐scaling methods. Linear regression and agreement of the predictions with invasively measured pressure drop were analyzed.

Results

All pressure drop predictions using 4D Flow MRI were linearly correlated to the true pressure drop but resulted in different regression slopes. The regression slope and 95% limits of agreement for the simplified Bernoulli method were 1.35 and 11.99 ± 21.72 mm Hg. The regression slope and 95% limits of agreement for the extended Bernoulli method were 1.02 and 0.74 ± 8.48 mm Hg. The regression slope and 95% limits of agreement for the turbulence production method were 0.89 and 0.96 ± 8.01 mm Hg. The shear‐scaling method presented good correlation with an invasively measured pressure drop, but the regression slope varied between 0.36 and 1.00 depending on the shear‐scaling coefficient.

Conclusion

The pressure drop assessment based on the turbulence production method agrees well with the extended Bernoulli method and invasively measured pressure drop in various shapes of the aortic valve. Turbulence‐based pressure drop estimation can, as a complement to the conventional Bernoulli method, play a role in the assessment of valve diseases.

Place, publisher, year, edition, pages
Wiley-Blackwell, 2019. Vol. 81, no 2, p. 893-906
Keywords [en]
4D Flow MRI; 4D PC-MRI; Reynolds stress; magnetic resonance imaging; phase contrast MRI; pressure drop; turbulence
National Category
Physiology
Identifiers
URN: urn:nbn:se:liu:diva-156013DOI: 10.1002/mrm.27437ISI: 000462086300015PubMedID: 30252155Scopus ID: 2-s2.0-85053757763OAI: oai:DiVA.org:liu-156013DiVA, id: diva2:1301616
Available from: 2019-04-02 Created: 2019-04-02 Last updated: 2019-06-28Bibliographically approved

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Escobar Kvitting, John-Peder

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Ha, HojinEscobar Kvitting, John-PederDyverfeldt, PetterEbbers, Tino
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Division of Cardiovascular MedicineFaculty of Medicine and Health SciencesCenter for Medical Image Science and Visualization (CMIV)Department of Thoracic and Vascular SurgeryDepartment of Clinical Physiology in Linköping
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Magnetic Resonance in Medicine
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