Top

Published in:

Open Access 25-05-2022 | Magnetic Resonance

Quantitative normal values of helical flow, flow jets and wall shear stress of healthy volunteers in the ascending aorta

Authors: Sebastian Ebel, Alexander Kühn, Abhinav Aggarwal, Benjamin Köhler, Benjamin Behrendt, Robin Gohmann, Boris Riekena, Christian Lücke, Juliane Ziegert, Charlotte Vogtmann, Bernhard Preim, Siegfried Kropf, Bernd Jung, Timm Denecke, Matthias Grothoff, Matthias Gutberlet

Published in: European Radiology | Issue 12/2022

Abstract

Objectives

4D flow MRI enables quantitative assessment of helical flow. We sought to generate normal values and elucidate changes of helical flow (duration, volume, length, velocities and rotational direction) and flow jet (displacement, flow angle) as well as wall shear stress (WSS).

Methods

We assessed the temporal helical existence (TH_EX), maximum helical volume (HV_max), accumulated helical volume (HV_acc), accumulated helical volume length (HVL_acc), maximum forward velocity (maxV_for), maximum circumferential velocity (maxV_circ), rotational direction (RD) and maximum wall shear stress (WSS) as reported elsewhere using the software tool Bloodline in 86 healthy volunteers (46 females, mean age 41 ± 13 years).

Results

WSS decreased by 42.1% and maxV_for by 55.7% across age. There was no link between age and gender regarding the other parameters.

Conclusion

This study provides age-dependent normal values regarding WSS and maxV_for and age- and gender-independent normal values regarding TH_EX, HV_max, HV_acc, HVL_acc, RD and _maxV_circ.

Key Points

• 4D flow provides numerous new parameters; therefore, normal values are mandatory.

• Wall shear stress decreases over age.

• Maximum helical forward velocity decreases over age.

Coady MA, Rizzo JA, Hammond GL et al (1997) What is the appropriate size criterion for resection of thoracic aortic aneurysms? J Thorac Cardiovasc Surg. https://doi.org/10.1016/S0022-5223(97)70360-X

Pape LA, Tsai TT, Isselbacher EM et al (2007) Aortic diameter ≥5.5 cm is not a good predictor of type A aortic dissection: Observations from the International Registry of Acute Aortic Dissection (IRAD). Circulation. https://doi.org/10.1161/CIRCULATIONAHA.107.702720

Callaghan FM, Bannon P, Barin E, Celemajer D, Jeremy R, Figtree G, Grieve SM (2018) Age-Related Changes of Shape and Flow Dynamics in Healthy Adult Aortas: A 4D Flow MRI Study. J Magn Reson Imaging:1–11. https://doi.org/10.1002/jmri.26210

Hope MD, Hope TA, Crook SES, Ordovas KG, Urbania TH, Alley MT, Higgins CB (2011) 4D flow CMR in assessment of valve-related ascending aortic disease. JACC Cardiovasc Imaging 4:781–787. https://doi.org/10.1016/j.jcmg.2011.05.004CrossRefPubMed

Den Reijer PM, Sallee D, Van Der Velden P, Zaaijer E, Parks WJ, Ramamurthy S, Robbie T, Donati G, Lamphier C, Beekman R, Brummer M (2010) Hemodynamic predictors of aortic dilatation in bicuspid aortic valve by velocity-encoded cardiovascular magnetic resonance. J Cardiovasc Magn Reson 12:1–13. https://doi.org/10.1186/1532-429X-12-4CrossRef

Dux-Santoy L, Guala A, Teixidó-Turà G, Ruiz-Muñoz A, Maldonado G, Villalva N, Galian L, Valente F, Gutiérrez L, González-Alujas T, Sao-Avilés A, Johnson KM, Wieben O, Huguet M, García-Dorado D, Evangelista A, Rodríguez-Palomares JF (2019) Increased rotational flow in the proximal aortic arch is associated with its dilation in bicuspid aortic valve disease. Eur Hear J Cardiovasc Imaging 20:1407–1417. https://doi.org/10.1093/ehjci/jez046

Bissell MM, Hess AT, Biasiolli L, Glaze SJ, Loudon M, Pitcher A, Davis A, Prendergast B, Markl M, Barker AJ, Neubauer S, Myerson SG (2013) Aortic dilation in bicuspid aortic valve disease: Flow pattern is a major contributor and differs with valve fusion type. Circ Cardiovasc Imaging 6:499–507. https://doi.org/10.1161/CIRCIMAGING.113.000528CrossRefPubMed

Rodríguez-Palomares JF, Dux-Santoy L, Guala A, Kale R, Maldonado G, Teixidó-Turà G, Galian L, Huguet M, Valente F, Gutiérrez L, González-Alujas T, Johnson KM, Wieben O, García-Dorado D, Evangelista A (2018) Aortic flow patterns and wall shear stress maps by 4D-flow cardiovascular magnetic resonance in the assessment of aortic dilatation in bicuspid aortic valve disease. J Cardiovasc Magn Reson 20:28. https://doi.org/10.1186/s12968-018-0451-1CrossRefPubMedPubMedCentral

van der Geest RJ, Garg P (2016) Advanced Analysis Techniques for Intra-cardiac Flow Evaluation from 4D Flow MRI. Curr Radiol Rep 4:38. https://doi.org/10.1007/s40134-016-0167-7CrossRefPubMedPubMedCentral

10.

Ebel S, Josefin D, Köhler B, Preim B, Benjamin B, Riekena B, Bernd J, Stehning C, Kropf S, Grotho M, Gutberlet M (2020) Automated Quantitative Extraction and Analysis of 4D flow Patterns in the Ascending Aorta : An intraindividual comparison at 1 . 5 T and 3 T. Sci Rep:1–13. https://doi.org/10.1038/s41598-020-59826-2

11.

Ebel S, Dufke J, Köhler B, Preim B, Rosemeier S, Jung B, Dähnert I, Lurz P, Borger M, Grothoff M, Gutberlet M (2019) Comparison of two accelerated 4D-flow sequences for aortic flow quantification. Sci Rep 9:1–10. https://doi.org/10.1038/s41598-019-45196-xCrossRef

12.

Ebel S, Hübner L, Köhler B, Kropf S, Preim B, Jung B, Grothoff M, Gutberlet M (2019) Validation of two accelerated 4D flow MRI sequences at 3 T : a phantom study. Eur Radiol Exp 3:12

13.

Köhler B, Grothoff M, Gutberlet M, Preim B (2019) Bloodline: A system for the guided analysis of cardiac 4D PC-MRI data. Comput Graph 82:32–43

14.

Koehler B, Gasteiger R, Preim U, Theisel H, Gutberlet M, Preim B (2013) Semi-automatic vortex extraction in 4D PC-MRI cardiac blood flow data using line predicates. IEEE Trans Vis Comput Graph 19:2773–2782. https://doi.org/10.1109/TVCG.2013.189CrossRef

15.

Köhler B, Preim U, Grothoff M, Gutberlet M, Fischbach K, Preim B (2015) Guided Analysis of Cardiac 4D PC-MRI Blood Flow Data. Eurographics (Dirk Bartz Prize) 2015 2–5

16.

Köhler B, Grothoff M, Gutberlet M, Preim B (2018) Visual and quantitative analysis of great arteries’ blood flow jets in cardiac 4D PC-MRI data. Comput Graph Forum 37:195–204. https://doi.org/10.1111/cgf.13412CrossRef

17.

Köhler B, Grothoff M, Gutberlet M, Preim B (2019) Computers & Graphics Bloodline : A system for the guided analysis of cardiac 4D PC-MRI data [DRAFT]. Comput Graph

18.

Bock J, Kreher BW, Hennig J, Markl M (2007) Optimized pre-processing of time-resolved 2D and 3D Phase Contrast MRI data. Proc 15th Annu Meet ISMRM 15:3138

19.

Dyverfeldt P, Bissell M, Barker AJ, Bolger AF, Carlhäll 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. https://doi.org/10.1186/s12968-015-0174-5CrossRefPubMedPubMedCentral

20.

Köhler B, Grothoff M, Gutberlet M, Preim B (2018) Pressure-based vortex extraction in cardiac 4D PC-MRI blood flow data. EUROVIS 0–4. https://doi.org/10.2312/eurovisshort.20181071

21.

Meuschke M, Köhler B, Preim U, Preim B, Lawonn K (2016) Semi-automatic Vortex Flow Classification in 4D PC-MRI Data of the Aorta. Comput Graph Forum 35:351–360. https://doi.org/10.1111/cgf.12911CrossRef

22.

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 34:1226–1230. https://doi.org/10.1002/jmri.22800CrossRefPubMed

23.

Potters WV, Marquering HA, VanBavel E, Nederveen AJ (2014) Measuring Wall Shear Stress Using Velocity-Encoded MRI. Curr Cardiovasc Imaging Rep 7:1–12. https://doi.org/10.1007/s12410-014-9257-1CrossRef

24.

Markl M, Frydrychowicz A, Kozerke S, Hope M, Wieben O (2012) 4D flow MRI. J Magn Reson Imaging 36:1015–1036. https://doi.org/10.1002/jmri.23632CrossRefPubMed

25.

Stankovic Z, Allen BD, Garcia J, Jarvis KB, Markl M (2014) 4D flow imaging with MRI. Cardiovasc Diagn Ther 4:173–192. https://doi.org/10.3978/j.issn.2223-3652.2014.01.02CrossRefPubMedPubMedCentral

26.

Stalder AF, Russe MF, Frydrychowicz A, Bock J, Hennig J, Markl M (2008) Quantitative 2D and 3D phase contrast MRI: Optimized analysis of blood flow and vessel wall parameters. Magn Reson Med 60:1218–1231. https://doi.org/10.1002/mrm.21778CrossRefPubMed

27.

Rogers WJ, Hu Y, Coast D, Vido DA, Kramer CM, Pyeritz RE, Reichek N (2001) Age-Associated Changes in Regional Aortic Pulse Wave Velocity. J Am Coll Cardiol 38:1123–1129. https://doi.org/10.1016/S0735-1097(01)01504-2CrossRefPubMed

28.

Svensson LG, Rodriguez ER (2005) Aortic organ disease epidemic, and why do balloons pop? Circulation 112:1082–1084. https://doi.org/10.1161/CIRCULATIONAHA.105.564682CrossRefPubMed

29.

Frydrychowicz A, Stalder AF, Russe MF, Bock J, Bauer S, Harloff A, Berger A, Langer M, Hennig J, Markl M (2009) Three-dimensional analysis of segmental wall shear stress in the aorta by flow-sensitive four-dimensional-MRI. J Magn Reson Imaging 30:77–84. https://doi.org/10.1002/jmri.21790CrossRefPubMed

30.

Kilner PJ, Yang GZ, Mohiaddin RH, Firmin DN, Longmore DB (1993) Helical and retrograde secondary flow patterns in the aortic arch studied by three-directional magnetic resonance velocity mapping. Circulation 88:2235–2247. https://doi.org/10.1161/01.CIR.88.5.2235CrossRefPubMed

31.

Morbiducci U, Ponzini R, Rizzo G, Cadioli M, Esposito A, Montevecchi FM, Redaelli A (2011) Mechanistic insight into the physiological relevance of helical blood flow in the human aorta: An in vivo study. Biomech Model Mechanobiol 10:339–355. https://doi.org/10.1007/s10237-010-0238-2CrossRefPubMed

32.

Van Ooij P, Garcia J, Potters WV, Malaisrie SC, Collins JD, Carr JC, Markl M, Barker AJ (2016) Age-related changes in aortic 3D blood flow velocities and wall shear stress: Implications for the identification of altered hemodynamics in patients with aortic valve disease. J Magn Reson Imaging 43:1239–1249. https://doi.org/10.1002/jmri.25081CrossRefPubMed

33.

Lorenz R, Bock J, Barker AJ, von Knobelsdorff-Brenkenhoff F, Wallis W, Korvink JG, Bissell MM, Schulz-Menger J, Markl M (2014) 4D flow magnetic resonance imaging in bicuspid aortic valve disease demonstrates altered distribution of aortic blood flow helicity. Magn Reson Med. https://doi.org/10.1002/mrm.24802

34.

Dyverfeldt P, Hope MD, Sigovan M, Wrenn J (2013) Reproducibility of quantitative analysis of aortic 4D flow data. J Cardiovasc Magn Reson 15:305–306. https://doi.org/10.1186/1532-429X-15-S1-P126CrossRef

35.

Sigovan M, Dyverfeldt P, Wrenn J, Tseng EE, Saloner D, Hope MD (2015) Extended 3D Approach for Quantification of Abnormal Ascending Aortic Flow. Magn Reson Imaging 33:695–700. https://doi.org/10.1016/j.clinbiochem.2015.06.023.Gut-LiverCrossRefPubMedPubMedCentral

36.

van Ooij P, Markl M, Collins JD, Carr JC, Rigsby C, Bonow RO, Chris Malaisrie S, McCarthy PM, Fedak PWM, Barker AJ (2017) Aortic valve stenosis alters expression of regional aortic wall shear stress: New insights from a 4-dimensional flow magnetic resonance imaging study of 571 subjects. J Am Heart Assoc 6:1–13. https://doi.org/10.1161/JAHA.117.005959CrossRef

37.

Bürk J, Blanke P, Stankovic Z, Barker A, Russe M, Geiger J, Frydrychowicz A, Langer M, Markl M (2012) Evaluation of 3D blood flow patterns and wall shear stress in the normal and dilated thoracic aorta using flow-sensitive 4D CMR. J Cardiovasc Magn Reson 14:1–11. https://doi.org/10.1186/1532-429X-14-84CrossRef

38.

Naim WNWA, Ganesan PB, Sun Z, Liew YM, Qian Y, Lee CJ, Jansen S, Hashim SA, Lim E (2016) Prediction of thrombus formation using vortical structures presentation in Stanford type B aortic dissection: A preliminary study using CFD approach. Appl Math Model 40:3115–3127. https://doi.org/10.1016/j.apm.2015.09.096CrossRef

Title: Quantitative normal values of helical flow, flow jets and wall shear stress of healthy volunteers in the ascending aorta
Authors: Sebastian Ebel
Alexander Kühn
Abhinav Aggarwal
Benjamin Köhler
Benjamin Behrendt
Robin Gohmann
Boris Riekena
Christian Lücke
Juliane Ziegert
Charlotte Vogtmann
Bernhard Preim
Siegfried Kropf
Bernd Jung
Timm Denecke
Matthias Grothoff
Matthias Gutberlet
Publication date: 25-05-2022
Publisher: Springer Berlin Heidelberg
Published in: European Radiology / Issue 12/2022
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-022-08866-5

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Quantitative normal values of helical flow, flow jets and wall shear stress of healthy volunteers in the ascending aorta

Abstract

Objectives

Methods

Results

Conclusion

Key Points

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Objectives

Methods

Results

Conclusion

Key Points

Please log in to get access to this content

Other articles of this Issue 12/2022

Comparison of expected imaging findings following percutaneous microwave and cryoablation of pulmonary tumors: ablation zones and thoracic lymph nodes

Prognostic value of post-treatment fluid-attenuated inversion recovery vascular hyperintensity in ischemic stroke after endovascular thrombectomy

Predicting ultrasound-guided thermal ablation benefit in primary hyperparathyroidism

Automated segmentation of whole-body CT images for body composition analysis in pediatric patients using a deep neural network

Possible strategies for use of artificial intelligence in screen-reading of mammograms, based on retrospective data from 122,969 screening examinations

Quantitative analysis of enhanced CT in differentiating well-differentiated pancreatic neuroendocrine tumors and poorly differentiated neuroendocrine carcinomas