Skip to main content
SpringerLink
Log in

Advanced cardiovascular multimodal imaging and aortic stenosis

  • Published:
Heart Failure Reviews Aims and scope Submit manuscript

Abstract

Aortic valve stenosis has become the most common valvular heart disease on account of aging population and increasing life expectancy. Echocardiography is the primary diagnosis tool for this, but it still has many flaws. Therefore, advanced cardiovascular multimodal imaging techniques are continuously being developed in order to overcome these limitations. Cardiac magnetic resonance imaging (CMR) allows a comprehensive morphological and functional evaluation of the aortic valve and provides important data for the diagnosis and risk stratification in patients with aortic stenosis. CMR can functionally assess the aortic flow using two-dimensional and time-resolved three-dimensional velocity-encoded phase-contrast techniques. Furthermore, by late gadolinium enhancement and T1-mapping, CMR can reveal the presence of both irreversible replacement and diffuse interstitial myocardial fibrosis. Moreover, its role in guiding aortic valve replacement procedures is beginning to take shape. Recent studies have rendered the importance of active and passive biomechanics in risk stratification and prognosis prediction in patients with aortic stenosis, but more work is required is just in its infancy, but data are promising. In addition, cardiac computed tomography is particularly useful for the diagnosis of aortic valve stenosis, and in preprocedural evaluation of the aorta, while positron emission tomography can be also used to assess valvular inflammation and active calcification. The purpose of this review is to provide a comprehensive overview of current available data regarding advanced cardiovascular multimodal imaging in aortic stenosis.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Singh A, Chan DCS, Greenwood JP et al (2019) Symptom onset in aortic stenosis. JACC Cardiovasc Imaging 12:96–105. https://doi.org/10.1016/j.jcmg.2017.09.019

    Article  PubMed  Google Scholar 

  2. Lindroos M, Kupari M, Heikkilä J, Tilvis R (1993) Prevalence of aortic valve abnormalities in the elderly: an echocardiographic study of a random population sample. J Am Coll Cardiol 21:1220–1225. https://doi.org/10.1016/0735-1097(93)90249-Z

    Article  CAS  PubMed  Google Scholar 

  3. Garcia J, Barker AJ, Markl M (2019) The role of imaging of flow patterns by 4D Flow MRI in aortic stenosis. JACC Cardiovasc Imaging 12:252–266. https://doi.org/10.1016/j.jcmg.2018.10.034

    Article  PubMed  Google Scholar 

  4. Sengeløv M, Cheng S, Biering-Sørensen T et al (2018) Ideal cardiovascular health and the prevalence and severity of aortic stenosis in elderly patients. J Am Heart Assoc 7:e007234. https://doi.org/10.1161/JAHA.117.007234

  5. Losenno KL, Goodman RL, Chu MWA (2012) Bicuspid aortic valve disease and ascending aortic aneurysms: gaps in knowledge. Cardiol Res Pract 2012:1–16. https://doi.org/10.1155/2012/145202

    Article  Google Scholar 

  6. Baumgartner H, Hung J, Bermejo J et al (2017) Recommendations on the echocardiographic assessment of aortic valve stenosis: a focused update from the European Association of Cardiovascular Imaging and the American Society of Echocardiography. J Am Soc Echocardiogr 30:372–392. https://doi.org/10.1016/j.echo.2017.02.009

    Article  PubMed  Google Scholar 

  7. Pibarot P, Dumesnil JG (2010) Longitudinal myocardial shortening in aortic stenosis: ready for prime time after 30 years of research? Heart 96:95–96. https://doi.org/10.1136/hrt.2009.177345

    Article  PubMed  Google Scholar 

  8. Kusunose K, Goodman A, Parikh R et al (2014) Incremental prognostic value of left ventricular global longitudinal strain in patients with aortic stenosis and preserved ejection fraction. Circ Cardiovasc Imaging 7:938–945. https://doi.org/10.1161/CIRCIMAGING.114.002041

    Article  PubMed  Google Scholar 

  9. van Dalen BM, Tzikas A, Soliman OII et al (2013) Assessment of subendocardial contractile function in aortic stenosis: a study using speckle tracking echocardiography. Echocardiography 30:293–300. https://doi.org/10.1111/echo.12051

    Article  PubMed  Google Scholar 

  10. Singh A, McCann GP (2019) Cardiac magnetic resonance imaging for the assessment of aortic stenosis. Heart 105:489–497. https://doi.org/10.1136/heartjnl-2018-313003

    Article  PubMed  Google Scholar 

  11. Garcia J, Kadem L, Larose E et al (2011) Comparison between cardiovascular magnetic resonance and transthoracic Doppler echocardiography for the estimation of effective orifice area in aortic stenosis. J Cardiovasc Magn Reson 13:25. https://doi.org/10.1186/1532-429X-13-25

    Article  PubMed  PubMed Central  Google Scholar 

  12. Chai P, Mohiaddin R (2005) How we perform cardiovascular magnetic resonance flow assessment using phase-contrast velocity mapping. J Cardiovasc Magn Reson 7:705–716. https://doi.org/10.1081/JCMR-200065639

    Article  PubMed  Google Scholar 

  13. Garcia J, Markl M, Schnell S et al (2014) Evaluation of aortic stenosis severity using 4D flow jet shear layer detection for the measurement of valve effective orifice area. Magn Reson Imaging 32:891–898. https://doi.org/10.1016/j.mri.2014.04.017

    Article  PubMed  PubMed Central  Google Scholar 

  14. Aoki T, Fukumoto Y, Sugimura K et al (2011) Prognostic impact of myocardial interstitial fibrosis in non-ischemic heart failure. Circ J 75:2605–2613. https://doi.org/10.1253/circj.CJ-11-0568

    Article  CAS  PubMed  Google Scholar 

  15. Kim RJ, Chen E-L, Lima JAC, Judd RM (1996) Myocardial Gd-DTPA kinetics determine MRI contrast enhancement and reflect the extent and severity of myocardial injury after acute reperfused infarction. Circulation 94:3318–3326. https://doi.org/10.1161/01.CIR.94.12.3318

    Article  CAS  PubMed  Google Scholar 

  16. Papanastasiou CA, Kokkinidis DG, Kampaktsis PN et al (2020) The Prognostic Role of Late Gadolinium Enhancement in Aortic Stenosis. JACC Cardiovasc Imaging 13:385–392. https://doi.org/10.1016/j.jcmg.2019.03.029

    Article  PubMed  Google Scholar 

  17. Aquaro GD, Grigoratos C, Bracco A et al (2020) Late gadolinium enhancement–dispersion mapping. Circ Cardiovasc Imaging 13:e010489. https://doi.org/10.1161/CIRCIMAGING.120.010489

  18. Musa TA, Treibel TA, Vassiliou VS et al (2018) Myocardial scar and mortality in severe aortic stenosis. Circulation 138:1935–1947. https://doi.org/10.1161/CIRCULATIONAHA.117.032839

    Article  PubMed  PubMed Central  Google Scholar 

  19. Bing R, Cavalcante JL, Everett RJ et al (2019) Imaging and impact of myocardial fibrosis in aortic stenosis. JACC Cardiovasc Imaging 12:283–296. https://doi.org/10.1016/j.jcmg.2018.11.026

    Article  PubMed  PubMed Central  Google Scholar 

  20. Lee H, Park J-B, Yoon YE et al (2018) Noncontrast myocardial T1 mapping by cardiac magnetic resonance predicts outcome in patients with aortic stenosis. JACC Cardiovasc Imaging 11:974–983. https://doi.org/10.1016/j.jcmg.2017.09.005

    Article  PubMed  Google Scholar 

  21. Taylor AJ, Salerno M, Dharmakumar R, Jerosch-Herold M (2016) T1 mapping basic techniques and clinical applications. JACC Cardiovasc Imaging 9:67–81. https://doi.org/10.1016/j.jcmg.2015.11.005

    Article  PubMed  Google Scholar 

  22. Inui K, Tachi M, Saito T et al (2016) Superiority of the extracellular volume fraction over the myocardial T1 value for the assessment of myocardial fibrosis in patients with non-ischemic cardiomyopathy. Magn Reson Imaging 34:1141–1145. https://doi.org/10.1016/j.mri.2016.05.008

    Article  PubMed  Google Scholar 

  23. Treibel TA, Kozor R, Schofield R et al (2018) Reverse myocardial remodeling following valve replacement in patients with aortic stenosis. J Am Coll Cardiol 71:860–871. https://doi.org/10.1016/j.jacc.2017.12.035

    Article  PubMed  PubMed Central  Google Scholar 

  24. Tanaka R, Yoshioka K, Niinuma H et al (2010) Diagnostic value of cardiac CT in the evaluation of bicuspid aortic stenosis: comparison with echocardiography and operative findings. Am J Roentgenol 195:895–899. https://doi.org/10.2214/AJR.09.3164

    Article  Google Scholar 

  25. Messika-Zeitoun D, Aubry M-C, Detaint D et al (2004) Evaluation and clinical implications of aortic valve calcification measured by electron-beam computed tomography. Circulation 110:356–362. https://doi.org/10.1161/01.CIR.0000135469.82545.D0

    Article  PubMed  Google Scholar 

  26. Anderson RH (2000) ANATOMY: clinical anatomy of the aortic root. Heart 84:670–673. https://doi.org/10.1136/heart.84.6.670

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Ribeiro HB, Webb JG, Makkar RR et al (2013) Predictive factors, management, and clinical outcomes of coronary obstruction following transcatheter aortic valve implantation. J Am Coll Cardiol 62:1552–1562. https://doi.org/10.1016/j.jacc.2013.07.040

    Article  PubMed  Google Scholar 

  28. Tzolos E, Andrews JP, Dweck MR (2020) Aortic valve stenosis—multimodality assessment with PET/CT and PET/MRI. Br J Radiol 93:20190688. https://doi.org/10.1259/bjr.20190688

    Article  PubMed  Google Scholar 

  29. Roberts WC, Ko JM (2005) Frequency by decades of unicuspid, bicuspid, and tricuspid aortic valves in adults having isolated aortic valve replacement for aortic stenosis, with or without associated aortic regurgitation. Circulation 111:920–925. https://doi.org/10.1161/01.CIR.0000155623.48408.C5

    Article  PubMed  Google Scholar 

  30. John AS, Dill T, Brandt RR et al (2003) Magnetic resonance to assess the aortic valve area in aortic stenosis: how does it compare to current diagnostic standards? J Am Coll Cardiol 42:519–526. https://doi.org/10.1016/S0735-1097(03)00707-1

    Article  PubMed  Google Scholar 

  31. Rutkovskiy A, Malashicheva A, Sullivan G et al (2017) Valve interstitial cells: the key to understanding the pathophysiology of heart valve calcification. J Am Heart Assoc 6. https://doi.org/10.1161/JAHA.117.006339

  32. Cimini M, Rogers KA, Boughner DR (2002) Aortic valve interstitial cells: an evaluation of cell viability and cell phenotype over time. J Heart Valve Dis 11:881–7

    PubMed  Google Scholar 

  33. El-Hamamsy I, Balachandran K, Yacoub MH et al (2009) Endothelium-dependent regulation of the mechanical properties of aortic valve cusps. J Am Coll Cardiol 53:1448–1455. https://doi.org/10.1016/j.jacc.2008.11.056

    Article  CAS  PubMed  Google Scholar 

  34. Otto CM, Kuusisto J, Reichenbach DD et al (1994) Characterization of the early lesion of “degenerative” valvular aortic stenosis. Histological and immunohistochemical studies. Circulation 90:844–853. https://doi.org/10.1161/01.CIR.90.2.844

    Article  CAS  PubMed  Google Scholar 

  35. Wallby L (2002) T lymphocyte infiltration in non-rheumatic aortic stenosis: a comparative descriptive study between tricuspid and bicuspid aortic valves. Heart 88:348–351. https://doi.org/10.1136/heart.88.4.348

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Pompilio G, Rossoni G, Sala A et al (1998) Endothelial-dependent dynamic and antithrombotic properties of porcine aortic and pulmonary valves. Ann Thorac Surg 65:986–992. https://doi.org/10.1016/S0003-4975(98)00075-7

    Article  CAS  PubMed  Google Scholar 

  37. Filip DA, Radu A, Simionescu M (1986) Interstitial cells of the heart valves possess characteristics similar to smooth muscle cells. Circ Res 59:310–320. https://doi.org/10.1161/01.RES.59.3.310

    Article  CAS  PubMed  Google Scholar 

  38. Sverdlov AL, Ngo DT, Chapman MJ et al (2011) Pathogenesis of aortic stenosis: not just a matter of wear and tear. Am J Cardiovasc Dis 1:185–99

    PubMed  PubMed Central  Google Scholar 

  39. Ngo DT, Stafford I, Sverdlov AL et al (2011) Ramipril retards development of aortic valve stenosis in a rabbit model: mechanistic considerations. Br J Pharmacol 162:722–732. https://doi.org/10.1111/j.1476-5381.2010.01084.x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Ngo DTM, Stafford I, Kelly DJ et al (2008) Vitamin D2 supplementation induces the development of aortic stenosis in rabbits: interactions with endothelial function and thioredoxin-interacting protein. Eur J Pharmacol 590:290–296. https://doi.org/10.1016/j.ejphar.2008.05.051

    Article  CAS  PubMed  Google Scholar 

  41. Kaden JJ, Dempfle C-E, Grobholz R et al (2005) Inflammatory regulation of extracellular matrix remodeling in calcific aortic valve stenosis. Cardiovasc Pathol 14:80–87. https://doi.org/10.1016/j.carpath.2005.01.002

    Article  CAS  PubMed  Google Scholar 

  42. Satta J, Melkko J, Pöllänen R et al (2002) Progression of human aortic valve stenosis is associated with tenascin-C expression. J Am Coll Cardiol 39:96–101. https://doi.org/10.1016/S0735-1097(01)01705-3

    Article  CAS  PubMed  Google Scholar 

  43. O’Brien KD, Shavelle DM, Caulfield MT et al (2002) Association of angiotensin-converting enzyme with low-density lipoprotein in aortic valvular lesions and in human plasma. Circulation 106:2224–2230. https://doi.org/10.1161/01.CIR.0000035655.45453.D2

    Article  PubMed  Google Scholar 

  44. Helske S, Syväranta S, Kupari M et al (2006) Possible role for mast cell-derived cathepsin G in the adverse remodelling of stenotic aortic valves. Eur Heart J 27:1495–1504. https://doi.org/10.1093/eurheartj/ehi706

    Article  CAS  PubMed  Google Scholar 

  45. Vongpromek R, Bos S, ten Kate G-JR et al (2015) Lipoprotein(a) levels are associated with aortic valve calcification in asymptomatic patients with familial hypercholesterolaemia. J Intern Med 278:166–173. https://doi.org/10.1111/joim.12335

    Article  CAS  PubMed  Google Scholar 

  46. Capoulade R, Côté N, Mathieu P et al (2014) Circulating levels of matrix Gla protein and progression of aortic stenosis: a substudy of the aortic stenosis progression observation: measuring effects of rosuvastatin (ASTRONOMER) Trial. Can J Cardiol 30:1088–1095. https://doi.org/10.1016/j.cjca.2014.03.025

    Article  PubMed  Google Scholar 

  47. Novo G, Noto D, Averna M, Novo S (2012) Statin therapy in patients with aortic stenosis after the ASTRONOMER trial: is there still any space? Intern Emerg Med 7:35–36. https://doi.org/10.1007/s11739-011-0592-9

    Article  Google Scholar 

  48. Pawade TA, Newby DE (2015) Treating aortic stenosis: arresting the snowball effect. Expert Rev Cardiovasc Ther 13:461–463. https://doi.org/10.1586/14779072.2015.1037284

    Article  CAS  PubMed  Google Scholar 

  49. Liu AC, Joag VR, Gotlieb AI (2007) The emerging role of valve interstitial cell phenotypes in regulating heart valve pathobiology. Am J Pathol 171:1407–1418. https://doi.org/10.2353/ajpath.2007.070251

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Parisi V, Leosco D, Ferro G et al (2015) The lipid theory in the pathogenesis of calcific aortic stenosis. Nutr Metab Cardiovasc Dis 25:519–525. https://doi.org/10.1016/j.numecd.2015.02.001

    Article  CAS  PubMed  Google Scholar 

  51. Bossé Y, Miqdad A, Fournier D et al (2009) Refining molecular pathways leading to calcific aortic valve stenosis by studying gene expression profile of normal and calcified stenotic human aortic valves. Circ Cardiovasc Genet 2:489–498. https://doi.org/10.1161/CIRCGENETICS.108.820795

    Article  CAS  PubMed  Google Scholar 

  52. Ortlepp JR (2001) The vitamin D receptor genotype predisposes to the development of calcific aortic valve stenosis. Heart 85:635–638. https://doi.org/10.1136/heart.85.6.635

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Innasimuthu AL, Katz WE (2011) Effect of bisphosphonates on the progression of degenerative aortic stenosis. Echocardiography 28:1–7. https://doi.org/10.1111/j.1540-8175.2010.01256.x

    Article  PubMed  Google Scholar 

  54. Reszka AA, Rodan GA (2004) Nitrogen-containing bisphosphonate mechanism of action. Mini Rev Med Chem 4:711–719. https://doi.org/10.2174/1389557043403648

    CAS  PubMed  Google Scholar 

  55. Hachicha Z, Dumesnil JG, Bogaty P, Pibarot P (2007) Paradoxical low-flow, low-gradient severe aortic stenosis despite preserved ejection fraction is associated with higher afterload and reduced survival. Circulation 115:2856–2864. https://doi.org/10.1161/CIRCULATIONAHA.106.668681

    Article  PubMed  Google Scholar 

  56. Lancellotti P, Magne J, Donal E et al (2012) Clinical outcome in asymptomatic severe aortic stenosis. J Am Coll Cardiol 59:235–243. https://doi.org/10.1016/j.jacc.2011.08.072

    Article  CAS  PubMed  Google Scholar 

  57. Adda J, Mielot C, Giorgi R et al (2012) Low-flow, low-gradient severe aortic stenosis despite normal ejection fraction is associated with severe left ventricular dysfunction as assessed by speckle-tracking echocardiography. Circ Cardiovasc Imaging 5:27–35. https://doi.org/10.1161/CIRCIMAGING.111.967554

    Article  PubMed  Google Scholar 

  58. Vaquette B (2005) Valve replacement in patients with critical aortic stenosis and depressed left ventricular function: predictors of operative risk, left ventricular function recovery, and long term outcome. Heart 91:1324–1329. https://doi.org/10.1136/hrt.2004.044099

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Lund O, Flo C, Jensen FT et al (1997) Left ventricular systolic and diastolic function in aortic stenosis: prognostic value after valve replacement and underlying mechanisms. Eur Heart J 18:1977–1987. https://doi.org/10.1093/oxfordjournals.eurheartj.a015209

    Article  CAS  PubMed  Google Scholar 

  60. Cengiz B (2018) Subclinical left ventricular systolic dysfunction in patients with severe aortic stenosis: a speckle tracking echocardiography study. Turk Kardiyol Dern Arsivi-Archives Turkish Soc Cardiol 46:18-24. https://doi.org/10.5543/tkda.2017.43037

    Article  Google Scholar 

  61. Kearney LG, Lu K, Ord M et al (2012) Global longitudinal strain is a strong independent predictor of all-cause mortality in patients with aortic stenosis. Eur Hear J Cardiovasc Imaging 13:827–833. https://doi.org/10.1093/ehjci/jes115

    Article  CAS  Google Scholar 

  62. Yingchoncharoen T, Gibby C, Rodriguez LL et al (2012) Association of myocardial deformation with outcome in asymptomatic aortic stenosis with normal ejection fraction. Circ Cardiovasc Imaging 5:719–725. https://doi.org/10.1161/CIRCIMAGING.112.977348

    Article  PubMed  Google Scholar 

  63. Lee H-F, Hsu L-A, Chan Y-H et al (2013) Prognostic value of global left ventricular strain for conservatively treated patients with symptomatic aortic stenosis. J Cardiol 62:301–306. https://doi.org/10.1016/j.jjcc.2013.05.001

    Article  PubMed  Google Scholar 

  64. Ohara Y, Fukuoka Y, Tabuchi I et al (2012) The impairment of endocardial radial strain is related to aortic stenosis severity in patients with aortic stenosis and preserved LV ejection fraction using two-dimensional speckle tracking echocardiography. Echocardiography 29:1172–1180. https://doi.org/10.1111/j.1540-8175.2012.01783.x

    Article  PubMed  Google Scholar 

  65. Nagata Y, Takeuchi M, Wu VC-C et al (2015) Prognostic value of LV deformation parameters using 2D and 3D speckle-tracking echocardiography in asymptomatic patients with severe aortic stenosis and preserved LV ejection fraction. JACC Cardiovasc Imaging 8:235–245. https://doi.org/10.1016/j.jcmg.2014.12.009

    Article  PubMed  Google Scholar 

  66. Santoro A, Alvino F, Antonelli G et al (2014) Left ventricular twisting modifications in patients with left ventricular concentric hypertrophy at increasing after-load conditions. Echocardiography 31:1265–1273. https://doi.org/10.1111/echo.12555

    Article  PubMed  Google Scholar 

  67. Popescu BA, Calin A, Beladan CC et al (2010) Left ventricular torsional dynamics in aortic stenosis: relationship between left ventricular untwisting and filling pressures. A two-dimensional speckle tracking study. Eur J Echocardiogr 11:406–413. https://doi.org/10.1093/ejechocard/jep224

    Article  PubMed  Google Scholar 

  68. Agoston-Coldea L, Bheecarry K, Petra C et al (2018) The value of global longitudinal strain and galectin-3 for predicting cardiovascular events in patients with severe aortic stenosis. Med Ultrason 20:205. https://doi.org/10.11152/mu-1456

    Article  PubMed  Google Scholar 

  69. Hagendorff A, Stoebe S, Tayal B (2018) A systematic approach to 3D echocardiographic assessment of the aortic root. Glob Cardiol Sci Pract. 2018:12 https://doi.org/10.21542/gcsp.2018.12

  70. Muraru D, Badano LP, Vannan M, Iliceto S (2012) Assessment of aortic valve complex by three-dimensional echocardiography: a framework for its effective application in clinical practice. Eur Heart J Cardiovasc Imaging 13:541–555. https://doi.org/10.1093/ehjci/jes075

  71. de Isla LP, Zamorano J, de la Yglesia RP et al (2008) Quantification of aortic valve area using three-dimensional echocardiography. Rev Española Cardiol (English Ed) 61:494–500. https://doi.org/10.1016/S1885-5857(08)60164-4

  72. Jainandunsing JS, Mahmood F, Matyal R et al (2013) Impact of three-dimensional echocardiography on classification of the severity of aortic stenosis. Ann Thorac Surg 96:1343–1348. https://doi.org/10.1016/j.athoracsur.2013.05.018

    Article  PubMed  Google Scholar 

  73. Ezzeldin DA, Roushdy AM, Abdallah AA, El Fiky AA (2020) Feasibility and accuracy of real-time three-dimensional echocardiography in evaluating the aortic valve in children. Egypt Hear J 72:2. https://doi.org/10.1186/s43044-019-0037-8

    Article  Google Scholar 

  74. Myerson SG (2012) Heart valve disease: investigation by cardiovascular magnetic resonance. J Cardiovasc Magn Reson 14:1–23. https://doi.org/10.1186/1532-429X-14-7

    Article  Google Scholar 

  75. Woldendorp K, Bannon PG, Grieve SM (2020) Evaluation of aortic stenosis using cardiovascular magnetic resonance: a systematic review & meta-analysis. J Cardiovasc Magn Reson 22:45. https://doi.org/10.1186/s12968-020-00633-z

    Article  PubMed  PubMed Central  Google Scholar 

  76. Kupfahl C (2004) Evaluation of aortic stenosis by cardiovascular magnetic resonance imaging: comparison with established routine clinical techniques. Heart 90:893–901. https://doi.org/10.1136/hrt.2003.022376

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Reant P, Lederlin M, Lafitte S et al (2006) Absolute assessment of aortic valve stenosis by planimetry using cardiovascular magnetic resonance imaging: comparison with transœsophageal echocardiography, transthoracic echocardiography, and cardiac catheterisation. Eur J Radiol 59:276–283. https://doi.org/10.1016/j.ejrad.2006.02.011

    Article  PubMed  Google Scholar 

  78. Levy F, Iacuzio L, Civaia F et al (2016) Usefulness of 3-Tesla cardiac magnetic resonance imaging in the assessment of aortic stenosis severity in routine clinical practice. Arch Cardiovasc Dis 109:618–625. https://doi.org/10.1016/j.acvd.2016.04.006

    Article  PubMed  Google Scholar 

  79. Kilner PJ, Manzara CC, Mohiaddin RH et al (1993) Magnetic resonance jet velocity mapping in mitral and aortic valve stenosis. Circulation 87:1239–1248. https://doi.org/10.1161/01.CIR.87.4.1239

    Article  CAS  PubMed  Google Scholar 

  80. Caruthers SD, Lin SJ, Brown P et al (2003) Practical value of cardiac magnetic resonance imaging for clinical quantification of aortic valve stenosis: comparison with echocardiography. Circulation 108:2236–2243. https://doi.org/10.1161/01.CIR.0000095268.47282.A1

    Article  PubMed  Google Scholar 

  81. O’Donnell M (1985) NMR blood flow imaging using multiecho, phase contrast sequences. Med Phys 12:59–64. https://doi.org/10.1118/1.595736

    Article  PubMed  Google Scholar 

  82. Bernstein MA, Grgic M, Brosnan TJ, Pelc NJ (1994) Reconstructions of phase contrast, phased array multicoil data. Magn Reson Med 32:330–334. https://doi.org/10.1002/mrm.1910320308

    Article  CAS  PubMed  Google Scholar 

  83. Dyverfeldt P, Bissell M, Barker AJ et al (2015) 4D flow cardiovascular magnetic resonance consensus statement. J Cardiovasc Magn Reson 17:72. https://doi.org/10.1186/s12968-015-0174-5

  84. Puymirat E, Chassaing S, Trinquart L et al (2010) Hakki’s formula for measurement of aortic valve area by magnetic resonance imaging. Am J Cardiol 106:249–254. https://doi.org/10.1016/j.amjcard.2010.03.019

    Article  PubMed  Google Scholar 

  85. Valenti V, Sciarretta S, Levin M et al (2015) An easy and reproducible parameter for the assessment of the pressure gradient in patients with aortic stenosis disease: a magnetic resonance study. J Cardiol 65:369–376. https://doi.org/10.1016/j.jjcc.2014.07.015

    Article  PubMed  Google Scholar 

  86. Rose MJ, Jarvis K, Chowdhary V et al (2016) Efficient method for volumetric assessment of peak blood flow velocity using 4D flow MRI. J Magn Reson Imaging 44:1673–1682. https://doi.org/10.1002/jmri.25305

    Article  PubMed  PubMed Central  Google Scholar 

  87. Gabbour M, Schnell S, Jarvis K et al (2015) 4-D flow magnetic resonance imaging: blood flow quantification compared to 2-D phase-contrast magnetic resonance imaging and Doppler echocardiography. Pediatr Radiol 45:804–813. https://doi.org/10.1007/s00247-014-3246-z

    Article  PubMed  Google Scholar 

  88. Archer GT, Elhawaz A, Barker N et al (2020) Validation of four-dimensional flow cardiovascular magnetic resonance for aortic stenosis assessment. Sci Rep 10:10569. https://doi.org/10.1038/s41598-020-66659-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Bollache E, van Ooij P, Powell A et al (2016) Comparison of 4D flow and 2D velocity-encoded phase contrast MRI sequences for the evaluation of aortic hemodynamics. Int J Cardiovasc Imaging 32:1529–1541. https://doi.org/10.1007/s10554-016-0938-5

    Article  PubMed  PubMed Central  Google Scholar 

  90. von Knobelsdorff-Brenkenhoff F, Karunaharamoorthy A, Trauzeddel RF et al (2016) Evaluation of aortic blood flow and wall shear stress in aortic stenosis and its association with left ventricular remodeling. Circ Cardiovasc Imaging 9. https://doi.org/10.1161/CIRCIMAGING.115.004038

  91. Garcia J, Barker AJ, Collins JD et al (2017) Volumetric quantification of absolute local normalized helicity in patients with bicuspid aortic valve and aortic dilatation. Magn Reson Med 78:689–701. https://doi.org/10.1002/mrm.26387

    Article  PubMed  Google Scholar 

  92. Alvarez A, Martinez V, Pizarro G et al (2020) Clinical use of 4D flow MRI for quantification of aortic regurgitation. Open Hear 7:e001158. https://doi.org/10.1136/openhrt-2019-001158

    Article  Google Scholar 

  93. Adriaans BP, Westenberg JJM, Cauteren YJM et al (2020) Clinical assessment of aortic valve stenosis: comparison between 4D flow MRI and transthoracic echocardiography. J Magn Reson Imaging 51:472–480. https://doi.org/10.1002/jmri.26847

    Article  PubMed  Google Scholar 

  94. Markl M, Wallis W, Harloff A (2011) Reproducibility of flow and wall shear stress analysis using flow-sensitive four-dimensional MRI. J Magn Reson Imaging 33:988–994. https://doi.org/10.1002/jmri.22519

    Article  PubMed  Google Scholar 

  95. Morbiducci U, Ponzini R, Rizzo G et al (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/s10237-010-0238-2

    Article  PubMed  Google Scholar 

  96. Sotelo J, Urbina J, Valverde I et al (2018) Three-dimensional quantification of vorticity and helicity from 3D cine PC-MRI using finite-element interpolations. Magn Reson Med 79:541–553. https://doi.org/10.1002/mrm.26687

    Article  PubMed  Google Scholar 

  97. Bissell MM, Hess AT, Biasiolli L et al (2013) Aortic dilation in bicuspid aortic valve disease. Circ Cardiovasc Imaging 6:499–507. https://doi.org/10.1161/CIRCIMAGING.113.000528

    Article  PubMed  Google Scholar 

  98. Katritsis D, Kaiktsis L, Chaniotis A et al (2007) Wall shear stress: theoretical considerations and methods of measurement. Prog Cardiovasc Dis 49:307–329. https://doi.org/10.1016/j.pcad.2006.11.001

    Article  PubMed  Google Scholar 

  99. Callaghan FM, Grieve SM (2018) Normal patterns of thoracic aortic wall shear stress measured using four-dimensional flow MRI in a large population. Am J Physiol Circ Physiol 315:H1174–H1181. https://doi.org/10.1152/ajpheart.00017.2018

    Article  CAS  Google Scholar 

  100. van Ooij P, Markl M, Collins JD et al (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:e005959. https://doi.org/10.1161/JAHA.117.005959

  101. Winter P, Andelovic K, Kampf T et al (2019) Fast self-navigated wall shear stress measurements in the murine aortic arch using radial 4D-phase contrast cardiovascular magnetic resonance at 17.6 T. J Cardiovasc Magn Reson 21:64. https://doi.org/10.1186/s12968-019-0566-z

  102. Krayenbuehl HP, Hess OM, Monrad ES et al (1989) Left ventricular myocardial structure in aortic valve disease before, intermediate, and late after aortic valve replacement. Circulation 79:744–755. https://doi.org/10.1161/01.CIR.79.4.744

    Article  CAS  PubMed  Google Scholar 

  103. Aoki T, Fukumoto Y, Sugimura K et al (2011) Prognostic impact of myocardial interstitial fibrosis in non-ischemic heart failure. Comparison between preserved and reduced ejection fraction heart failure. Circ J 75:2605–2613. https://doi.org/10.1253/circj.cj-11-0568

    Article  CAS  PubMed  Google Scholar 

  104. Tastet L, Kwiecinski J, Pibarot P et al (2020) Sex-related differences in the extent of myocardial fibrosis in patients with aortic valve stenosis. JACC Cardiovasc Imaging 13:699–711. https://doi.org/10.1016/j.jcmg.2019.06.014

    Article  PubMed  Google Scholar 

  105. Hwang I-C, Kim H-K, Park J-B et al (2020) Aortic valve replacement-induced changes in native T1 are related to prognosis in severe aortic stenosis: T1 mapping cardiac magnetic resonance imaging study. Eur Heart J Cardiovasc Imaging 21:653–663. https://doi.org/10.1093/ehjci/jez201

    Article  PubMed  Google Scholar 

  106. Backhaus SJ, Lange T, Beuthner BE et al (2020) Real-time cardiovascular magnetic resonance T1 and extracellular volume fraction mapping for tissue characterisation in aortic stenosis. J Cardiovasc Magn Reson 22:46. https://doi.org/10.1186/s12968-020-00632-0

    Article  PubMed  PubMed Central  Google Scholar 

  107. Park J, Chang H-J, Choi J-H et al (2014) Late gadolinium enhancement in cardiac MRI in patients with severe aortic stenosis and preserved left ventricular systolic function is related to attenuated improvement of left ventricular geometry and filling pressure after aortic valve replacement. Korean Circ J 44:312. https://doi.org/10.4070/kcj.2014.44.5.312

    Article  PubMed  PubMed Central  Google Scholar 

  108. Chin CWL, Everett RJ, Kwiecinski J et al (2017) Myocardial fibrosis and cardiac decompensation in aortic stenosis. JACC Cardiovasc Imaging 10:1320–1333. https://doi.org/10.1016/j.jcmg.2016.10.007

    Article  PubMed  PubMed Central  Google Scholar 

  109. Rajesh GN, Thottian JJ, Subramaniam G et al (2017) Prevalence and prognostic significance of left ventricular myocardial late gadolinium enhancement in severe aortic stenosis. Indian Heart J 69:742–750. https://doi.org/10.1016/j.ihj.2017.05.027

    Article  PubMed  PubMed Central  Google Scholar 

  110. Treibel TA, López B, González A et al (2018) Reappraising myocardial fibrosis in severe aortic stenosis: an invasive and non-invasive study in 133 patients. Eur Heart J 39:699–709. https://doi.org/10.1093/eurheartj/ehx353

    Article  CAS  PubMed  Google Scholar 

  111. Everett RJ, Tastet L, Clavel MA et al (2018) Progression of hypertrophy and myocardial fibrosis in aortic stenosis. Circ Cardiovasc Imaging 11:e007451. https://doi.org/10.1161/CIRCIMAGING.117.007451

  112. Park S-J, Cho SW, Kim SM et al (2019) Assessment of myocardial fibrosis using multimodality imaging in severe aortic stenosis. JACC Cardiovasc Imaging 12:109–119. https://doi.org/10.1016/j.jcmg.2018.05.028

    Article  PubMed  Google Scholar 

  113. Fujimiya T, Iwai-Takano M, Igarashi T et al (2019) Late gadolinium enhancement predicts improvement in global longitudinal strain after aortic valve replacement in aortic stenosis. Sci Rep 9:15688. https://doi.org/10.1038/s41598-019-51930-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Agoston-coldea L, Bheecarry K, Cionca C et al (2019) Incremental predictive value of longitudinal axis strain and late gadolinium enhancement using standard CMR imaging in patients with aortic stenosis. J Clin Med 8:1–15. https://doi.org/10.3390/jcm8020165

  115. Mewton N, Liu CY, Croisille P et al (2011) Assessment of myocardial fibrosis with cardiovascular magnetic resonance. J Am Coll Cardiol 57:891–903. https://doi.org/10.1016/j.jacc.2010.11.013

    Article  PubMed  Google Scholar 

  116. Iles LM, Ellims AH, Llewellyn H et al (2015) Histological validation of cardiac magnetic resonance analysis of regional and diffuse interstitial myocardial fibrosis. Eur Heart J Cardiovasc Imaging 16:14–22. https://doi.org/10.1093/ehjci/jeu182

    Article  PubMed  Google Scholar 

  117. Croisille P, Revel D, Saeed M (2006) Contrast agents and cardiac MR imaging of myocardial ischemia: from bench to bedside. Eur Radiol 16:1951–1963. https://doi.org/10.1007/s00330-006-0244-z

    Article  PubMed  Google Scholar 

  118. Newby DE, Dweck MR (2019) Imaging and impact of myocardial fibrosis in aortic stenosis. 12:283–296. https://doi.org/10.1016/j.jcmg.2018.11.026

  119. Dweck MR, Joshi S, Murigu T et al (2011) Midwall fibrosis is an independent predictor of mortality in patients with aortic stenosis. J Am Coll Cardiol 58:1271–1279. https://doi.org/10.1016/j.jacc.2011.03.064

    Article  PubMed  Google Scholar 

  120. Quarto C, Dweck MR, Murigu T et al (2012) Late gadolinium enhancement as a potential marker of increased perioperative risk in aortic valve replacement. Interact Cardiovasc Thorac Surg 15:45–50. https://doi.org/10.1093/icvts/ivs098

    Article  PubMed  PubMed Central  Google Scholar 

  121. Messroghli DR, Radjenovic A, Kozerke S et al (2004) Modified Look-Locker inversion recovery (MOLLI) for high-resolution T1 mapping of the heart. Magn Reson Med 52:141–146. https://doi.org/10.1002/mrm.20110

    Article  PubMed  Google Scholar 

  122. Piechnik SK, Ferreira VM, Dall’Armellina E et al (2010) Shortened Modified Look-Locker Inversion recovery (ShMOLLI) for clinical myocardial T1-mapping at 1.5 and 3 T within a 9 heartbeat breathhold. J Cardiovasc Magn Reson 12:69. https://doi.org/10.1186/1532-429X-12-69

  123. Chow K, Flewitt JA, Green JD et al (2014) Saturation recovery single-shot acquisition (SASHA) for myocardial T 1 mapping. Magn Reson Med 71:2082–2095. https://doi.org/10.1002/mrm.24878

    Article  PubMed  Google Scholar 

  124. Jellis C, Wright J, Kennedy D et al (2011) Association of imaging markers of myocardial fibrosis with metabolic and functional disturbances in early diabetic cardiomyopathy. Circ Cardiovasc Imaging 4:693–702. https://doi.org/10.1161/CIRCIMAGING.111.963587

    Article  PubMed  Google Scholar 

  125. Kim PK, Hong YJ, Im DJ et al (2017) Myocardial T1 and T2 mapping: techniques and clinical applications. Korean J Radiol 18:113. https://doi.org/10.3348/kjr.2017.18.1.113

    Article  PubMed  PubMed Central  Google Scholar 

  126. Kockova R, Kacer P, Pirk J et al (2016) Native T1 relaxation time and extracellular volume fraction as accurate markers of diffuse myocardial fibrosis in heart valve Disease – comparison with targeted left ventricular myocardial biopsy –. Circ J 80:1202–1209. https://doi.org/10.1253/circj.CJ-15-1309

    Article  PubMed  Google Scholar 

  127. Bull S, White SK, Piechnik SK et al (2013) Human non-contrast T1 values and correlation with histology in diffuse fibrosis. Heart 99:932–937. https://doi.org/10.1136/heartjnl-2012-303052

    Article  PubMed  Google Scholar 

  128. Lee S-P, Lee W, Lee JM et al (2015) Assessment of diffuse myocardial fibrosis by using MR imaging in asymptomatic patients with aortic stenosis. Radiology 274:359–369. https://doi.org/10.1148/radiol.14141120

    Article  PubMed  Google Scholar 

  129. Mavrogeni S, Apostolou D, Argyriou P et al (2017) T1 and T2 mapping in cardiology: “mapping the obscure object of desire”. Cardiol 138:207–217. https://doi.org/10.1159/000478901

    Article  CAS  Google Scholar 

  130. Treibel TA, Fontana M, Maestrini V et al (2016) Automatic measurement of the myocardial interstitium. JACC Cardiovasc Imaging 9:54–63. https://doi.org/10.1016/j.jcmg.2015.11.008

    Article  PubMed  Google Scholar 

  131. Kammerlander AA, Duca F, Binder C et al (2018) Extracellular volume quantification by cardiac magnetic resonance imaging without hematocrit sampling. Wien Klin Wochenschr 130:190–196. https://doi.org/10.1007/s00508-017-1267-y

    Article  PubMed  Google Scholar 

  132. Chin CWL, Semple S, Malley T et al (2014) Optimization and comparison of myocardial T1 techniques at 3T in patients with aortic stenosis. Eur Heart J Cardiovasc Imaging 15:556–565. https://doi.org/10.1093/ehjci/jet245

    Article  PubMed  Google Scholar 

  133. Yang EY, Ghosn MG, Khan MA et al (2019) Myocardial extracellular volume fraction adds prognostic information beyond myocardial replacement fibrosis. Circ Cardiovasc Imaging 12:e009535. https://doi.org/10.1161/CIRCIMAGING.119.009535

  134. Esson G, Jenkins W, Koo M et al (2017) Myocardial fibrosis and cardiac decompensation in aortic stenosis. 10:1320–1333. https://doi.org/10.1016/j.jcmg.2016.10.007

  135. Everett RJ, Treibel TA, Fukui M et al (2020) Extracellular myocardial volume in patients with aortic stenosis. J Am Coll Cardiol 75:304–316. https://doi.org/10.1016/j.jacc.2019.11.032

    Article  PubMed  PubMed Central  Google Scholar 

  136. Cohn JN, Ferrari R, Sharpe N (2000) Cardiac remodeling—concepts and clinical implications: a consensus paper from an international forum on cardiac remodeling. J Am Coll Cardiol 35:569–582. https://doi.org/10.1016/S0735-1097(99)00630-0

    Article  CAS  PubMed  Google Scholar 

  137. Dobson LE, Fairbairn TA, Musa TA et al (2016) Sex-related differences in left ventricular remodeling in severe aortic stenosis and reverse remodeling after aortic valve replacement: a cardiovascular magnetic resonance study. Am Heart J 175:101–111. https://doi.org/10.1016/j.ahj.2016.02.010

    Article  PubMed  Google Scholar 

  138. Debry N, Maréchaux S, Rusinaru D et al (2017) Prognostic significance of left ventricular concentric remodelling in patients with aortic stenosis. Arch Cardiovasc Dis 110:26–34. https://doi.org/10.1016/j.acvd.2016.05.010

    Article  PubMed  Google Scholar 

  139. Kwiecinski J, Chin CWL, Everett RJ et al (2018) Adverse prognosis associated with asymmetric myocardial thickening in aortic stenosis. Eur Heart J Cardiovasc Imaging 19:347–356. https://doi.org/10.1093/ehjci/jex052

    Article  Google Scholar 

  140. Dweck MR, Joshi S, Murigu T et al (2012) Left ventricular remodeling and hypertrophy in patients with aortic stenosis: insights from cardiovascular magnetic resonance. J Cardiovasc Magn Reson 14:50. https://doi.org/10.1186/1532-429X-14-50

    Article  PubMed  PubMed Central  Google Scholar 

  141. Treibel TA, Kozor R, Fontana M et al (2018) Sex dimorphism in the myocardial response to aortic stenosis. JACC Cardiovasc Imaging 11:962–973. https://doi.org/10.1016/j.jcmg.2017.08.025

    Article  PubMed  PubMed Central  Google Scholar 

  142. Rassi AN, Pibarot P, Elmariah S (2014) Left ventricular remodelling in aortic stenosis. Can J Cardiol 30:1004–1011. https://doi.org/10.1016/j.cjca.2014.04.026

    Article  PubMed  Google Scholar 

  143. Elmariah S (2015) Patterns of left ventricular remodeling in aortic stenosis: therapeutic implications. Curr Treat Options Cardiovasc Med 17:31. https://doi.org/10.1007/s11936-015-0391-0

    Article  Google Scholar 

  144. Scatteia A, Baritussio A, Bucciarelli-Ducci C (2017) Strain imaging using cardiac magnetic resonance. Heart Fail Rev 22:465–476. https://doi.org/10.1007/s10741-017-9621-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  145. Katbeh A, Ondrus T, Barbato E et al (2018) Imaging of myocardial fibrosis and its functional correlates in aortic stenosis: a review and clinical potential. Cardiology 141:141–149. https://doi.org/10.1159/000493164

    Article  PubMed  Google Scholar 

  146. Kim MY, Park E-A, Lee W, Lee S-P (2020) Cardiac magnetic resonance feature tracking in aortic stenosis: exploration of strain parameters and prognostic value in asymptomatic patients with preserved ejection fraction. Korean J Radiol 21:268. https://doi.org/10.3348/kjr.2019.0441

    Article  PubMed  PubMed Central  Google Scholar 

  147. Spath NB, Gomez M, Everett RJ et al (2019) Global longitudinal strain analysis using cardiac MRI in aortic stenosis: comparison with left ventricular remodeling, myocardial fibrosis, and 2-year clinical outcomes. Radiol Cardiothorac Imaging 1:e190027. https://doi.org/10.1148/ryct.2019190027

    Article  PubMed  PubMed Central  Google Scholar 

  148. Al Musa T, Uddin A, Swoboda PP et al (2017) Cardiovascular magnetic resonance evaluation of symptomatic severe aortic stenosis: association of circumferential myocardial strain and mortality. J Cardiovasc Magn Reson 19:13. https://doi.org/10.1186/s12968-017-0329-7

    Article  Google Scholar 

  149. Buckert D, Cieslik M, Tibi R et al (2018) Longitudinal strain assessed by cardiac magnetic resonance correlates to hemodynamic findings in patients with severe aortic stenosis and predicts positive remodeling after transcatheter aortic valve replacement. Clin Res Cardiol 107:20–29. https://doi.org/10.1007/s00392-017-1153-7

    Article  PubMed  Google Scholar 

  150. Villemain O, Correia M, Mousseaux E et al (2019) Myocardial stiffness evaluation using noninvasive shear wave imaging in healthy and hypertrophic cardiomyopathic adults. JACC Cardiovasc Imaging 12:1135–1145. https://doi.org/10.1016/j.jcmg.2018.02.002

    Article  PubMed  PubMed Central  Google Scholar 

  151. Young AA, Cowan BR (2012) Evaluation of left ventricular torsion by cardiovascular magnetic resonance. J Cardiovasc Magn Reson 14:49. https://doi.org/10.1186/1532-429X-14-49

    Article  PubMed  PubMed Central  Google Scholar 

  152. Moghaddam AN, Saber NR, Wen H et al (2010) Analytical method to measure three-dimensional strain patterns in the left ventricle from single slice displacement data. J Cardiovasc Magn Reson 12:33. https://doi.org/10.1186/1532-429X-12-33

    Article  PubMed  PubMed Central  Google Scholar 

  153. Rüssel IK, Götte MJW, Bronzwaer JG et al (2009) Left ventricular torsion. JACC Cardiovasc. Imaging 2:648–655. https://doi.org/10.1016/j.jcmg.2009.03.001

    Article  Google Scholar 

  154. Cameli M, Lisi M, Righini FM et al (2013) Left ventricular remodeling and torsion dynamics in hypertensive patients. Int J Cardiovasc Imaging 29:79–86. https://doi.org/10.1007/s10554-012-0054-0

    Article  PubMed  Google Scholar 

  155. Suzuki R, Mochizuki Y, Yoshimatsu H et al (2016) Myocardial torsional deformations in cats with hypertrophic cardiomyopathy using two-dimensional speckle-tracking echocardiography. J Vet Cardiol 18:350–357. https://doi.org/10.1016/j.jvc.2016.06.004

    Article  CAS  PubMed  Google Scholar 

  156. Zhang Y, Li S, Xie J, Wu Y (2020) Twist/untwist parameters are promising evaluators of myocardial mechanic changes in heart failure patients with preserved ejection fraction. Clin Cardiol 43:587–593. https://doi.org/10.1002/clc.23353

    Article  PubMed  PubMed Central  Google Scholar 

  157. Nagel E (2000) Cardiac rotation and relaxation in patients with aortic valve stenosis. Eur Heart J 21:582–589. https://doi.org/10.1053/euhj.1999.1736

    Article  CAS  PubMed  Google Scholar 

  158. Stuber M, Scheidegger MB, Fischer SE et al (1999) Alterations in the local myocardial motion pattern in patients suffering from pressure overload due to aortic stenosis. Circulation 100:361–368. https://doi.org/10.1161/01.CIR.100.4.361

    Article  CAS  PubMed  Google Scholar 

  159. Sandstede JJW, Johnson T, Harre K et al (2002) Cardiac Systolic Rotation and Contraction Before and After Valve Replacement for Aortic Stenosis. Am J Roentgenol 178:953–958. https://doi.org/10.2214/ajr.178.4.1780953

    Article  Google Scholar 

  160. Clavel M-A, Malouf J, Messika-Zeitoun D et al (2015) Aortic valve area calculation in aortic stenosis by CT and Doppler echocardiography. JACC Cardiovasc Imaging 8:248–257. https://doi.org/10.1016/j.jcmg.2015.01.009

    Article  PubMed  Google Scholar 

  161. Baumgartner H, Falk V, Bax JJ et al (2017) 2017 ESC/EACTS guidelines for the management of valvular heart disease. Eur Heart J 38:2739–2791. https://doi.org/10.1093/eurheartj/ehx391

    Article  PubMed  Google Scholar 

  162. Pawade T, Clavel MA, Tribouilloy C et al (2018) Computed tomography aortic valve calcium scoring in patients with aortic stenosis. Circ Cardiovasc Imaging 11:e007146. https://doi.org/10.1161/CIRCIMAGING.117.007146

  163. Doris MK, Jenkins W, Robson P et al (2020) Computed tomography aortic valve calcium scoring for the assessment of aortic stenosis progression. Heart 106:1906–1913. https://doi.org/10.1136/heartjnl-2020-317125

    Article  CAS  PubMed  Google Scholar 

  164. Blanke P, Weir-McCall JR, Achenbach S et al (2019) Computed tomography imaging in the context of transcatheter aortic valve implantation (TAVI)/transcatheter aortic valve replacement (TAVR): an expert consensus document of the Society of Cardiovascular Computed Tomography. J Cardiovasc Comput Tomogr 13:1–20. https://doi.org/10.1016/j.jcct.2018.11.008

    Article  PubMed  Google Scholar 

  165. Hansson NC, Nørgaard BL, Barbanti M et al (2015) The impact of calcium volume and distribution in aortic root injury related to balloon-expandable transcatheter aortic valve replacement. J Cardiovasc Comput Tomogr 9:382–392. https://doi.org/10.1016/j.jcct.2015.04.002

    Article  PubMed  Google Scholar 

  166. Jilaihawi H, Chen M, Webb J et al (2016) A bicuspid aortic valve imaging classification for the TAVR era. JACC Cardiovasc Imaging 9:1145–1158. https://doi.org/10.1016/j.jcmg.2015.12.022

    Article  PubMed  Google Scholar 

  167. Dweck MR, Jenkins WSA, Vesey AT et al (2014) 18F-sodium fluoride uptake is a marker of active calcification and disease progression in patients with aortic stenosis. Circ Cardiovasc Imaging 7:371–378. https://doi.org/10.1161/CIRCIMAGING.113.001508

    Article  PubMed  Google Scholar 

  168. Pawade TA, Cartlidge TRG, Jenkins WSA et al (2016) Optimization and reproducibility of aortic valve 18F-fluoride positron emission tomography in patients with aortic stenosis. Circ Cardiovasc Imaging 9:e005131. https://doi.org/10.1161/CIRCIMAGING.116.005131

  169. Zheng KH, Tsimikas S, Pawade T et al (2019) Lipoprotein(a) and oxidized phospholipids promote valve calcification in patients with aortic stenosis. J Am Coll Cardiol 73:2150–2162. https://doi.org/10.1016/j.jacc.2019.01.070

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  170. Marincheva-Savcheva G, Subramanian S, Qadir S et al (2011) Imaging of the aortic valve using fluorodeoxyglucose positron emission tomography. J Am Coll Cardiol 57:2507–2515. https://doi.org/10.1016/j.jacc.2010.12.046

    Article  PubMed  Google Scholar 

  171. Dweck MR, Jones C, Joshi NV et al (2012) Assessment of valvular calcification and inflammation by positron emission tomography in patients with aortic stenosis. Circulation 125:76–86. https://doi.org/10.1161/CIRCULATIONAHA.111.051052

    Article  CAS  PubMed  Google Scholar 

  172. Dweck MR, Khaw HJ, Sng GKZ et al (2013) Aortic stenosis, atherosclerosis, and skeletal bone: is there a common link with calcification and inflammation? Eur Heart J 34:1567–1574. https://doi.org/10.1093/eurheartj/eht034

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by internal institutional doctoral fellowship from the Iuliu Hatieganu University of Medicine and Pharmacy of Cluj-Napoca.

Author information

Authors and Affiliations

  1. Physiology Department, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania

    Carmen Cionca & Teodora Mocan

  2. Department of Radiology, Affidea Hiperdia Diagnostic Imaging Center, Cluj-Napoca, Romania

    Carmen Cionca

  3. Department of Internal Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania

    Alexandru Zlibut & Lucia Agoston-Coldea

  4. Department of Nanomedicine, Regional Institute of Gastroenterology and Hepatology, Cluj-Napoca, Romania

    Teodora Mocan

Authors
  1. Carmen Cionca
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alexandru Zlibut
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lucia Agoston-Coldea
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Teodora Mocan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lucia Agoston-Coldea.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cionca, C., Zlibut, A., Agoston-Coldea, L. et al. Advanced cardiovascular multimodal imaging and aortic stenosis. Heart Fail Rev 27, 677–696 (2022). https://doi.org/10.1007/s10741-021-10131-8

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10741-021-10131-8

Keywords

Search

Navigation