Skip to main content

Advertisement

SpringerLink
Log in

The Role of Cardiac Computed Tomography in Heart Failure

  • Imaging in Heart Failure (J. Schulz-Menger, Section Editor)
  • Published:
Current Heart Failure Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

Cardiac computed tomography (CT) is becoming a more widely applied tool in the diagnosis and management of a variety of cardiovascular conditions, including heart failure. The aim of this narrative review is to examine the role of cardiac CT in patients with heart failure.

Recent Findings

Coronary computed tomographic angiography has robust diagnostic accuracy for ruling out coronary artery disease. These data are reflected in updated guidelines from major cardiology organizations. New roles for cardiac CT in myocardial imaging, perfusion scanning, and periprocedural planning, execution, and monitoring are being implemented.

Summary

Cardiac CT is useful in ruling out coronary artery disease its diagnostic accuracy, accessibility, and safety. It is also intricately linked to invasive cardiac procedures that patients with heart failure routinely undergo.

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

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance

  1. Virani SS, Alonso A, Benjamin EJ, et al. Heart Disease and Stroke Statistics—2020 Update: A Report From the American Heart Association. Circulation. 2020;141.https://doi.org/10.1161/CIR.0000000000000757.

  2. Cook C, Cole G, Asaria P, et al. The annual global economic burden of heart failure. Int J Cardiol. 2014;171:368–76. https://doi.org/10.1016/j.ijcard.2013.12.028.

    Article  PubMed  Google Scholar 

  3. Shemesh J, Tenenbaum A, Fisman EZ, et al. Coronary calcium as a reliable tool for differentiating ischemic from nonischemic cardiomyopathy. Am J Cardiol. 1996;77:191–4. https://doi.org/10.1016/S0002-9149(96)90596-2.

    Article  CAS  PubMed  Google Scholar 

  4. Budoff MJ, Shavelle DM, Lamont DH, et al. Usefulness of electron beam computed tomography scanning for distinguishing ischemic from nonischemic cardiomyopathy. J Am Coll Cardiol. 1998;32:1173–8. https://doi.org/10.1016/S0735-1097(98)00387-8.

    Article  CAS  PubMed  Google Scholar 

  5. Peng AW, Mirbolouk M, Orimoloye OA, et al. Long-Term All-Cause and Cause-Specific Mortality in Asymptomatic Patients With CAC ≥1,000: Results From the CAC Consortium. JACC Cardiovasc Imaging. 2020;13:83–93. https://doi.org/10.1016/j.jcmg.2019.02.005.

    Article  PubMed  Google Scholar 

  6. Eberhard M, Hinzpeter R, Schönenberger ALN, et al. Incremental Prognostic Value of Coronary Artery Calcium Score for Predicting All-Cause Mortality after Transcatheter Aortic Valve Replacement. Radiology. 2021;301:105–12. https://doi.org/10.1148/radiol.2021204623.

    Article  PubMed  Google Scholar 

  7. Budoff MJ, Jacob B, Rasouli ML, et al. Comparison of Electron Beam Computed Tomography and Technetium Stress Testing in Differentiating Cause of Dilated Versus Ischemic Cardiomyopathy. J Comput Assist Tomogr. 2005;29:699–703. https://doi.org/10.1097/01.rct.0000175503.87578.0d.

    Article  PubMed  Google Scholar 

  8. Le T, Ko JY, Tina Kim H, et al. Comparison of echocardiography and electron beam tomography in differentiating the etiology of heart failure. Clin Cardiol. 2000;23:417–20. https://doi.org/10.1002/clc.4960230608.

    Article  CAS  PubMed  Google Scholar 

  9. Patel AA, Fine J, Naghavi M, Budoff MJ. Radiation exposure and coronary artery calcium scans in the society for heart attack prevention and eradication cohort. Int J Cardiovasc Imaging. 2019;35:179–83. https://doi.org/10.1007/s10554-018-1431-0.

    Article  PubMed  Google Scholar 

  10. Fihn SD, Gardin JM, Abrams J, et al. 2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease. Circulation. 2012;126:e354–471. https://doi.org/10.1161/CIR.0b013e318277d6a0.

    Article  PubMed  Google Scholar 

  11. Stolzmann P, Goetti R, Baumueller S, et al. Prospective and retrospective ECG-gating for CT coronary angiography perform similarly accurate at low heart rates. Eur J Radiol. 2011;7.

  12. Pontone G. Diagnostic Accuracy of Coronary Computed Tomography Angiography. 2009;54:10.

  13. Maruyama T, Takada M, Hasuike T, et al. Radiation Dose Reduction and Coronary Assessability of Prospective Electrocardiogram-Gated Computed Tomography Coronary Angiography. J Am Coll Cardiol. 2008;52:1450–5. https://doi.org/10.1016/j.jacc.2008.07.048.

    Article  PubMed  Google Scholar 

  14. Sun M, Lu B, Wu R, et al. Diagnostic accuracy of dual-source CT coronary angiography with prospective ECG-triggering on different heart rate patients. Eur Radiol. 2011;21:1635–42. https://doi.org/10.1007/s00330-011-2107-5.

    Article  PubMed  Google Scholar 

  15. Cornily J-C, Gilard M, Gal GL, et al. Accuracy of 16-detector Multislice Spiral Computed Tomography in the initial evaluation of dilated cardiomyopathy. Eur J Radiol. 2007;61:84–90. https://doi.org/10.1016/j.ejrad.2006.08.010.

    Article  PubMed  Google Scholar 

  16. Andreini D, Pontone G, Pepi M, et al. Diagnostic Accuracy of Multidetector Computed Tomography Coronary Angiography in Patients With Dilated Cardiomyopathy. J Am Coll Cardiol. 2007;49:2044–50. https://doi.org/10.1016/j.jacc.2007.01.086.

    Article  PubMed  Google Scholar 

  17. Andreini D, Pontone G, Bartorelli AL, et al. Sixty-Four–Slice Multidetector Computed Tomography: An Accurate Imaging Modality for the Evaluation of Coronary Arteries in Dilated Cardiomyopathy of Unknown Etiology. Circ Cardiovasc Imaging. 2009;2:199–205. https://doi.org/10.1161/CIRCIMAGING.108.822809.

    Article  PubMed  Google Scholar 

  18. Ghostine S, Caussin C, Habis M, et al. Non-invasive diagnosis of ischaemic heart failure using 64-slice computed tomography. Eur Heart J. 2008;29:2133–40. https://doi.org/10.1093/eurheartj/ehn072.

    Article  PubMed  Google Scholar 

  19. Le Polain de Waroux J-B, Pouleur A-C, Goffinet C, et al. Combined coronary and late-enhanced multidetector-computed tomography for delineation of the etiology of left ventricular dysfunction: comparison with coronary angiography and contrast-enhanced cardiac magnetic resonance imaging. Eur Heart J. 2008;29:2544–51. https://doi.org/10.1093/eurheartj/ehn381.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Boulmier D, Audinet C, Heautot J-F, et al. Clinical contributions of 64-slice computed tomography in the evaluation of cardiomyopathy of unknown origin. Arch Cardiovasc Dis. 2009;102:685–96. https://doi.org/10.1016/j.acvd.2009.06.004.

    Article  PubMed  Google Scholar 

  21. Lee D, Li D, Jug B, et al. Diagnostic accuracy of 64 slice multidetector coronary computed tomographic angiography in left ventricular systolic dysfunction. IJC Heart Vasc. 2015. https://doi.org/10.1016/j.ijcha.2015.04.007

  22. Srichai MB. Dual source computed tomography coronary angiography in new onset cardiomyopathy. World J Radiol. 2012;4:258. https://doi.org/10.4329/wjr.v4.i6.258.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Oncel D, Oncel G, Tastan A. Effectiveness of Dual-Source CT Coronary Angiography for the Evaluation of Coronary Artery Disease in Patients with Atrial Fibrillation: Initial Experience1. Radiology. 2007. https://doi.org/10.1148/radiol.2453070094.

    Article  PubMed  Google Scholar 

  24. Rist C, Johnson TR, Müller-Starck J, et al. Noninvasive Coronary Angiography Using Dual-Source Computed Tomography in Patients With Atrial Fibrillation. Invest Radiol. 2009;44:159–67. https://doi.org/10.1097/RLI.0b013e3181948b05.

    Article  PubMed  Google Scholar 

  25. Marwan M, Pflederer T, Schepis T, et al. Accuracy of dual-source computed tomography to identify significant coronary artery disease in patients with atrial fibrillation: comparison with coronary angiography. Eur Heart J. 2010;31:2230–7. https://doi.org/10.1093/eurheartj/ehq223.

    Article  PubMed  Google Scholar 

  26. Zhang J-J, Liu T, Feng Y, et al. Diagnostic Value of 64-Slice Dual-Source CT Coronary Angiography in Patients with Atrial Fibrillation: Comparison with Invasive Coronary Angiography. Korean J Radiol. 2011;8.

  27. Abdelkarim MJ, Ahmadi N, Gopal A, et al. Noninvasive quantitative evaluation of coronary artery stent patency using 64-row multidetector computed tomography. J Cardiovasc Comput Tomogr. 2010;4:29–37. https://doi.org/10.1016/j.jcct.2009.10.014.

    Article  PubMed  Google Scholar 

  28. Jug B, Papazian J, Gupta M, et al. Diagnostic performance of computed tomographic coronary angiography in patients with end-stage renal disease. Coron Artery Dis. 2013;24:135–41. https://doi.org/10.1097/MCA.0b013e32835be39a.

    Article  PubMed  Google Scholar 

  29. Menke J, Unterberg-Buchwald C, Staab W, et al. Head-to-head comparison of prospectively triggered vs retrospectively gated coronary computed tomography angiography: Meta-analysis of diagnostic accuracy, image quality, and radiation dose. Am Heart J. 2013;165:154-163.e3. https://doi.org/10.1016/j.ahj.2012.10.026.

    Article  PubMed  Google Scholar 

  30. Gulati M, Levy PD, Mukherjee D, et al. 2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: Executive Summary: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2021:CIR0000000000001030. https://doi.org/10.1161/CIR.0000000000001030.

  31. • McDonagh TA, Metra M, Adamo M, et al. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J. 2021;42:3599–726. https://doi.org/10.1093/eurheartj/ehab368. 2021 AHA guidelines on chest pain give a class 1A recommendation to both coronary CTA in intermediate-risk patients with acute chest pain and no known CAD, after a negative or inconclusive evaluation for acute coronary syndrome. This is a large shift from the prior 2012 class IIb recommendation, which represents the influx of new data surrounding coronary CTA in the last 10 years.

    Article  CAS  PubMed  Google Scholar 

  32. • Narula J, Chandrashekhar Y, Ahmadi A, et al. SCCT 2021 Expert Consensus Document on Coronary Computed Tomographic Angiography: A Report of the Society of Cardiovascular Computed Tomography. J Cardiovasc Comput Tomogr. 2021;15:192–217. https://doi.org/10.1016/j.jcct.2020.11.001. 2021 ESC guidelines on heart failure call coronary CTA a “key element” in the workup of patients with heart failure of unknown etiology. This strong, affirmative language from a respected multi-national organization legitimizes the utility of coronary CTA in this patient population.

    Article  PubMed  Google Scholar 

  33. Hamirani YS, Isma’eel H, Larijani V, et al. The Diagnostic Accuracy of 64-Detector Cardiac Computed Tomography Compared With Stress Nuclear Imaging in Patients Undergoing Invasive Cardiac Catheterization. J Comput Assist Tomogr. 2010;34:645–51. https://doi.org/10.1097/RCT.0b013e3181e3d0b1.

    Article  PubMed  Google Scholar 

  34. Budoff MJ, Rasouli ML, Shavelle DM, et al. Cardiac CT Angiography (CTA) and Nuclear Myocardial Perfusion Imaging (MPI)—A Comparison in Detecting Significant Coronary Artery Disease. Acad Radiol. 2007;14:252–7. https://doi.org/10.1016/j.acra.2006.11.006.

    Article  PubMed  Google Scholar 

  35. Budoff MJ, Li D, Kazerooni EA, et al. Diagnostic Accuracy of Noninvasive 64-row Computed Tomographic Coronary Angiography (CCTA) Compared with Myocardial Perfusion Imaging (MPI). Acad Radiol. 2017;24:22–9. https://doi.org/10.1016/j.acra.2016.09.008.

    Article  PubMed  Google Scholar 

  36. Danad I, Raijmakers PG, Driessen RS, et al. Comparison of Coronary CT Angiography, SPECT, PET, and Hybrid Imaging for Diagnosis of Ischemic Heart Disease Determined by Fractional Flow Reserve. JAMA Cardiol. 2017;2:1100. https://doi.org/10.1001/jamacardio.2017.2471.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Ohta Y, Kitao S, Yunaga H, et al. Myocardial Delayed Enhancement CT for the Evaluation of Heart Failure: Comparison to MRI. Radiology. 2018;288:682–91. https://doi.org/10.1148/radiol.2018172523.

    Article  PubMed  Google Scholar 

  38. Scully PR, Bastarrika G, Moon JC, Treibel TA. Myocardial Extracellular Volume Quantification by Cardiovascular Magnetic Resonance and Computed Tomography. Curr Cardiol Rep. 2018;20:15. https://doi.org/10.1007/s11886-018-0961-3.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Bandula S, White SK, Flett AS, et al. Measurement of Myocardial Extracellular Volume Fraction by Using Equilibrium Contrast-enhanced CT: Validation against Histologic Findings. Radiology. 2013;269:396–403. https://doi.org/10.1148/radiol.13130130.

    Article  PubMed  Google Scholar 

  40. Chang S, Han K, Youn J-C, et al. Utility of Dual-Energy CT-based Monochromatic Imaging in the Assessment of Myocardial Delayed Enhancement in Patients with Cardiomyopathy. Radiology. 2018;287:442–51. https://doi.org/10.1148/radiol.2017162945.

    Article  PubMed  Google Scholar 

  41. Wichmann JL, Bauer RW, Doss M, et al. Diagnostic accuracy of late iodine-enhancement dual-energy computed tomography for the detection of chronic myocardial infarction compared with late gadolinium-enhancement 3-T magnetic resonance imaging. Invest Radiol. 2013;48:851–6. https://doi.org/10.1097/RLI.0b013e31829d91a8.

    Article  PubMed  Google Scholar 

  42. Zhao L, Ma X, Delano MC, et al. Assessment of myocardial fibrosis and coronary arteries in hypertrophic cardiomyopathy using combined arterial and delayed enhanced CT: comparison with MR and coronary angiography. Eur Radiol. 2013;23:1034–43. https://doi.org/10.1007/s00330-012-2674-0.

    Article  PubMed  Google Scholar 

  43. Aikawa T, Oyama-Manabe N, Naya M, et al. Delayed contrast-enhanced computed tomography in patients with known or suspected cardiac sarcoidosis: A feasibility study. Eur Radiol. 2017;27:4054–63. https://doi.org/10.1007/s00330-017-4824-x.

    Article  PubMed  Google Scholar 

  44. Deux J-F, Mihalache C-I, Legou F, et al. Noninvasive detection of cardiac amyloidosis using delayed enhanced MDCT: a pilot study. Eur Radiol. 2015;25:2291–7. https://doi.org/10.1007/s00330-015-3642-2.

    Article  PubMed  Google Scholar 

  45. Bing R, Cavalcante JL, Everett RJ, et al. Imaging and Impact of Myocardial Fibrosis in Aortic Stenosis. JACC Cardiovasc Imaging. 2019;12:283–96. https://doi.org/10.1016/j.jcmg.2018.11.026.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Kittleson MM, Maurer MS, Ambardekar AV, et al. Cardiac Amyloidosis: Evolving Diagnosis and Management: A Scientific Statement From the American Heart Association. Circulation. 2020;142:e7–22. https://doi.org/10.1161/CIR.0000000000000792.

    Article  PubMed  Google Scholar 

  47. Garcia-Pavia P, Rapezzi C, Adler Y, et al. Diagnosis and treatment of cardiac amyloidosis: a position statement of the ESC Working Group on Myocardial and Pericardial Diseases. Eur Heart J. 2021;42:1554–68. https://doi.org/10.1093/eurheartj/ehab072.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Mandoli GE, D’Ascenzi F, Vinco G, et al. Novel Approaches in Cardiac Imaging for Non-invasive Assessment of Left Heart Myocardial Fibrosis. Front Cardiovasc Med. 2021;8:614235. https://doi.org/10.3389/fcvm.2021.614235.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Liguori C, Farina D, Vaccher F, et al. Myocarditis: imaging up to date. Radiol Med (Torino). 2020;125:1124–34. https://doi.org/10.1007/s11547-020-01279-8.

    Article  Google Scholar 

  50. Attili AK, Schuster A, Nagel E, et al. Quantification in cardiac MRI: advances in image acquisition and processing. Int J Cardiovasc Imaging. 2010;26 Suppl 1:27–40. https://doi.org/10.1007/s10554-009-9571-x.

    Article  PubMed  Google Scholar 

  51. Li Y, Yu M, Dai X, et al. Detection of Hemodynamically Significant Coronary Stenosis: CT Myocardial Perfusion versus Machine Learning CT Fractional Flow Reserve. Radiology. 2019;293:305–14. https://doi.org/10.1148/radiol.2019190098.

    Article  PubMed  Google Scholar 

  52. Takx Richard AP, Blomberg BA, El AH, et al. Diagnostic Accuracy of Stress Myocardial Perfusion Imaging Compared to Invasive Coronary Angiography With Fractional Flow Reserve Meta-Analysis. Circ Cardiovasc Imaging. 2015;8:e002666. https://doi.org/10.1161/CIRCIMAGING.114.002666.

    Article  PubMed  Google Scholar 

  53. Natarajan N, Patel P, Bartel T, et al. Peri-procedural imaging for transcatheter mitral valve replacement. Cardiovasc Diagn Ther. 2016;6:144–59. https://doi.org/10.21037/cdt.2016.02.04.

    Article  PubMed  PubMed Central  Google Scholar 

  54. • Prosper A, Shinbane J, Maliglig A, et al. Left Atrial Appendage Mechanical Exclusion: Procedural Planning Using Cardiovascular Computed Tomographic Angiography. J Thorac Imaging. 2020;35:W107–18. https://doi.org/10.1097/RTI.0000000000000504. SCCT consensus document on the TAVR solidifies the role of coronary CTA in TAVR programs.

    Article  PubMed  Google Scholar 

  55. Van de Veire NR, Marsan NA, Schuijf JD, et al. Noninvasive Imaging of Cardiac Venous Anatomy With 64-Slice Multi-Slice Computed Tomography and Noninvasive Assessment of Left Ventricular Dyssynchrony by 3-Dimensional Tissue Synchronization Imaging in Patients With Heart Failure Scheduled for Cardiac Resynchronization Therapy. Am J Cardiol. 2008;101:1023–9. https://doi.org/10.1016/j.amjcard.2007.11.052.

    Article  PubMed  Google Scholar 

  56. Shanks M, Delgado V, Ng ACT, et al. Mitral valve morphology assessment: three-dimensional transesophageal echocardiography versus computed tomography. Ann Thorac Surg. 2010;90:1922–9. https://doi.org/10.1016/j.athoracsur.2010.06.116.

    Article  PubMed  Google Scholar 

  57. Yoon S-H, Bleiziffer S, Latib A, et al. Predictors of Left Ventricular Outflow Tract Obstruction After Transcatheter Mitral Valve Replacement. JACC Cardiovasc Interv. 2019;12:182–93. https://doi.org/10.1016/j.jcin.2018.12.001.

    Article  PubMed  Google Scholar 

  58. Batul SA, Gopinathannair R. Atrial Fibrillation in Heart Failure: a Therapeutic Challenge of Our Times. Korean Circ J. 2017;47:644–62. https://doi.org/10.4070/kcj.2017.0040.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Korsholm K, Berti S, Iriart X, et al. Expert Recommendations on Cardiac Computed Tomography for Planning Transcatheter Left Atrial Appendage Occlusion. JACC Cardiovasc Interv. 2020;13:277–92. https://doi.org/10.1016/j.jcin.2019.08.054.

    Article  PubMed  Google Scholar 

  60. Romero J, Husain SA, Kelesidis I, et al. Detection of left atrial appendage thrombus by cardiac computed tomography in patients with atrial fibrillation: a meta-analysis. Circ Cardiovasc Imaging. 2013;6:185–94. https://doi.org/10.1161/CIRCIMAGING.112.000153.

    Article  PubMed  Google Scholar 

  61. Eng MH, Wang DD, Greenbaum AB, et al. Prospective, randomized comparison of 3-dimensional computed tomography guidance versus TEE data for left atrial appendage occlusion (PRO3DLAAO). Catheter Cardiovasc Interv. 2018;92:401–7. https://doi.org/10.1002/ccd.27514.

    Article  PubMed  Google Scholar 

  62. Qamar SR, Jalal S, Nicolaou S, et al. Comparison of cardiac computed tomography angiography and transoesophageal echocardiography for device surveillance after left atrial appendage closure. EuroIntervention. 2019;15:663–70. https://doi.org/10.4244/EIJ-D-18-01107.

    Article  PubMed  Google Scholar 

  63. Blanke P, Weir-McCall JR, Achenbach S, et al. 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. 2019;13:1–20. https://doi.org/10.1016/j.jcct.2018.11.008.

    Article  PubMed  Google Scholar 

  64. Clavel M-A, Pibarot P, Messika-Zeitoun D, et al. Impact of aortic valve calcification, as measured by MDCT, on survival in patients with aortic stenosis: results of an international registry study. J Am Coll Cardiol. 2014;64:1202–13. https://doi.org/10.1016/j.jacc.2014.05.066.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Pawade T, Clavel M-A, Tribouilloy C, et al. Computed Tomography Aortic Valve Calcium Scoring in Patients With Aortic Stenosis. Circ Cardiovasc Imaging. 2018;11:e007146. https://doi.org/10.1161/CIRCIMAGING.117.007146.

    Article  PubMed  Google Scholar 

  66. Leetmaa T, Hansson NC, Leipsic J, et al. Early aortic transcatheter heart valve thrombosis: diagnostic value of contrast-enhanced multidetector computed tomography. Circ Cardiovasc Interv. 2015;8:e001596. https://doi.org/10.1161/CIRCINTERVENTIONS.114.001596.

    Article  PubMed  Google Scholar 

  67. Pache G, Schoechlin S, Blanke P, et al. Early hypo-attenuated leaflet thickening in balloon-expandable transcatheter aortic heart valves. Eur Heart J. 2016;37:2263–71. https://doi.org/10.1093/eurheartj/ehv526.

    Article  PubMed  Google Scholar 

  68. Blanke P, Schoepf UJ, Leipsic JA. CT in transcatheter aortic valve replacement. Radiology. 2013;269:650–69. https://doi.org/10.1148/radiol.13120696.

    Article  PubMed  Google Scholar 

  69. Godoy Cardiac Computed Tomography (CT) Evaluation of Valvular Heart Disease in Transcatheter Interventions - PubMed. https://library.harbor-ucla.org:3285/31768770/. Accessed 26 Dec 2020.

  70. Otto CM, Nishimura RA, Bonow RO, et al. 2020 ACC/AHA Guideline for the Management of Patients With Valvular Heart Disease. J Am Coll Cardiol. 2021;77:e25–197. https://doi.org/10.1016/j.jacc.2020.11.018.

    Article  PubMed  Google Scholar 

  71. Baumgartner H, Falk V, Bax JJ, et al. 2017 ESC/EACTS Guidelines for the management of valvular heart disease. Eur Heart J. 2017;38:2739–91. https://doi.org/10.1093/eurheartj/ehx391.

    Article  PubMed  Google Scholar 

  72. Naoum C, Blanke P, Cavalcante JL, Leipsic J. Cardiac Computed Tomography and Magnetic Resonance Imaging in the Evaluation of Mitral and Tricuspid Valve Disease. Circ Cardiovasc Imaging. 2017;10:e005331. https://doi.org/10.1161/CIRCIMAGING.116.005331.

    Article  PubMed  Google Scholar 

  73. van Rosendael PJ, Kamperidis V, Kong WKF, et al. Computed tomography for planning transcatheter tricuspid valve therapy. Eur Heart J. 2017;38:665–74. https://doi.org/10.1093/eurheartj/ehw499.

    Article  PubMed  Google Scholar 

  74. Liddy S, Buckley U, Kok HK, et al. Applications of cardiac computed tomography in electrophysiology intervention. Eur Heart J Cardiovasc Imaging. 2018;19:253–61. https://doi.org/10.1093/ehjci/jex312.

    Article  CAS  PubMed  Google Scholar 

  75. Nguyên UC, Cluitmans MJM, Strik M, et al. Integration of cardiac magnetic resonance imaging, electrocardiographic imaging, and coronary venous computed tomography angiography for guidance of left ventricular lead positioning. EP Eur. 2019;21:626–35. https://doi.org/10.1093/europace/euy292.

    Article  Google Scholar 

  76. Sommer A, Kronborg MB, Nørgaard BL, et al. Multimodality imaging-guided left ventricular lead placement in cardiac resynchronization therapy: a randomized controlled trial: Imaging-guided LV lead placement in CRT. Eur J Heart Fail. 2016;18:1365–74. https://doi.org/10.1002/ejhf.530.

    Article  PubMed  Google Scholar 

  77. Pang BJ, Lui EH, Joshi SB, et al. Pacing and Implantable Cardioverter Defibrillator Lead Perforation As Assessed by Multiplanar Reformatted ECG-Gated Cardiac Computed Tomography and Clinical Correlates: PACEMAKER AND ICD LEAD PERFORATION BY CT. Pacing Clin Electrophysiol. 2014;37:537–45. https://doi.org/10.1111/pace.12307.

    Article  PubMed  Google Scholar 

  78. Zhuang B, Wang S, Zhao S, Lu M. Computed tomography angiography-derived fractional flow reserve (CT-FFR) for the detection of myocardial ischemia with invasive fractional flow reserve as reference: systematic review and meta-analysis. Eur Radiol. 2020;30:712–25. https://doi.org/10.1007/s00330-019-06470-8.

    Article  PubMed  Google Scholar 

  79. Arrighi JA, Dilsizian V. Multimodality Imaging for Assessment of Myocardial Viability: Nuclear, Echocardiography, MR, and CT. Curr Cardiol Rep. 2012;14:234–43. https://doi.org/10.1007/s11886-011-0242-x.

    Article  PubMed  Google Scholar 

  80. Jacquier A, Revel D, Croisille P, et al. Mécanismes du rehaussement tardif myocardique et apport des produits de contraste en IRM et scanner dans le diagnostic de viabilité myocardique11Ce travail a été rendu possible grâce à la Bourse de la Société Française de Radiologie. J Radiol. 2010;91:751–7. https://doi.org/10.1016/S0221-0363(10)70112-8.

    Article  CAS  PubMed  Google Scholar 

  81. Disertori M, Rigoni M, Pace N, et al. Myocardial Fibrosis Assessment by LGE Is a Powerful Predictor of Ventricular Tachyarrhythmias in Ischemic and Nonischemic LV Dysfunction: A Meta-Analysis. JACC Cardiovasc Imaging. 2016;9:1046–55. https://doi.org/10.1016/j.jcmg.2016.01.033.

    Article  PubMed  Google Scholar 

  82. Siontis KC, Kim HM, Sharaf Dabbagh G, et al. Association of preprocedural cardiac magnetic resonance imaging with outcomes of ventricular tachycardia ablation in patients with idiopathic dilated cardiomyopathy. Heart Rhythm. 2017;14:1487–93. https://doi.org/10.1016/j.hrthm.2017.06.003.

    Article  PubMed  Google Scholar 

  83. Li YY, Rashid S, Craft J, et al. Temporospatial characterization of ventricular wall motion with real-time cardiac magnetic resonance imaging in health and disease. Sci Rep. 2022;12:4070. https://doi.org/10.1038/s41598-022-08094-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Conte E, Mushtaq S, Carbucicchio C, et al. State of the art paper: Cardiovascular CT for planning ventricular tachycardia ablation procedures. J Cardiovasc Comput Tomogr. 2021;15:394–402. https://doi.org/10.1016/j.jcct.2021.01.002.

    Article  PubMed  Google Scholar 

  85. Collet C, Sonck J, Leipsic J, et al. Implementing Coronary Computed Tomography Angiography in the Catheterization Laboratory. JACC Cardiovasc Imaging. 2021;14:1846–55. https://doi.org/10.1016/j.jcmg.2020.07.048.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Internal Medicine, Harbor-UCLA Medical Center, 1000 W Carson St, Box #400, Torrance, CA, 90502, USA

    Spencer S. Kitchin

  2. Department of Internal Medicine, Los Angeles Biomedical Research Institute, Torrance, CA, USA

    Venkat Sanjay Manubolu, Sion K. Roy & Matthew J. Budoff

Authors
  1. Spencer S. Kitchin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Venkat Sanjay Manubolu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sion K. Roy
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Matthew J. Budoff
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Spencer S. Kitchin.

Ethics declarations

Conflict of Interest

The authors declare no competing interests.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Additional information

Publisher's Note

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

This article is part of the Topical Collection on Imaging in Heart Failure

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kitchin, S.S., Manubolu, V.S., Roy, S.K. et al. The Role of Cardiac Computed Tomography in Heart Failure. Curr Heart Fail Rep 19, 213–222 (2022). https://doi.org/10.1007/s11897-022-00553-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11897-022-00553-2

Keywords

Search

Navigation