Skip to main content
SpringerLink
Log in

Creating three dimensional models of the right ventricular outflow tract: influence of contrast, sequence, operator, and threshold

  • Original Paper
  • Published:
The International Journal of Cardiovascular Imaging Aims and scope Submit manuscript

Abstract

The use of 3D printed models of the right ventricular outflow tract (RVOT) for surgical and interventional planning is growing and often requires image segmentation of cardiac magnetic resonance (CMR) images. Segmentation results may vary based on contrast, image sequence, signal threshold chosen by the operator, and manual post-processing. The purpose of this study was to determine potential biases and post-processing errors in image segmentation to enable informed decisions. Models of the RVOT and pulmonary arteries from twelve patients who had contrast enhanced CMR angiography with gadopentetate dimeglumine (GPD), gadofosveset trisodium (GFT), and a post-GFT inversion-recovery (IR) whole heart sequence were segmented, trimmed, and aligned by three operators. Geometric agreement and minimal RVOT diameters were compared between sequences and operators. To determine the contribution of threshold, interoperator variability was compared between models created by the same two operators using the same versus different thresholds. Geometric agreement by Dice between objects was high (intraoperator: 0.89–0.95; interoperator: 0.95–0.97), without differences between sequences. Minimal RVOT diameters differed on average by − 1.9 to − 1.3 mm (intraoperator) and by 0.4 to 1.4 mm (interoperator). The contribution of threshold to interoperator geometric agreement was not significant (same threshold: 0.96 ± 0.06, different threshold: 0.93 ± 0.05; p = 0.181), but minimal RVOT diameters were more variable with different versus constant thresholds (− 9.12% vs. 2.42%; p < 0.05). Thresholding does not significantly change interoperator variability for geometric agreement, but does for minimal RVOT diameter. Minimal RVOT diameters showed clinically relevant variation within and between operators.

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

  1. Farooqi KM, Uppu SC, Nguyen K, Srivastava S, Ko HH, Choueiter N, Wollstein A, Parness IA, Narula J, Sanz J, Nielsen JC (2016) Application of virtual three-dimensional models for simultaneous visualization of intracardiac anatomic relationships in double outlet right ventricle. Pediatr Cardiol 37(1):90–98. https://doi.org/10.1007/s00246-015-1244-z

    Article  PubMed  Google Scholar 

  2. Yoo SJ, van Arsdell GS (2017) 3D printing in surgical management of double outlet right ventricle. Front Pediatr 5:289. https://doi.org/10.3389/fped.2017.00289

    Article  PubMed  Google Scholar 

  3. Valverde I, Sarnago F, Prieto R, Zunzunegui JL (2017) Three-dimensional printing in vitro simulation of percutaneous pulmonary valve implantation in large right ventricular outflow tract. Eur Heart J 38(16):1262–1263. https://doi.org/10.1093/eurheartj/ehw546

    Article  PubMed  Google Scholar 

  4. Byrne N, Velasco Forte M, Tandon A, Valverde I, Hussain T (2016) A systematic review of image segmentation methodology, used in the additive manufacture of patient-specific 3D printed models of the cardiovascular system. JRSM Cardiovasc Dis 5:2048004016645467. https://doi.org/10.1177/2048004016645467

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Taha AA, Hanbury A (2015) Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool. BMC Med Imaging 15:29. https://doi.org/10.1186/s12880-015-0068-x

    Article  PubMed  PubMed Central  Google Scholar 

  6. Burkhardt BE, Byrne N, Velasco Forte MN, Iannaccone F, De Beule M, Morgan GJ, Hussain T (2018) Evaluation of a modified Cheatham-Platinum stent for the treatment of aortic coarctation by finite element modelling. JRSM Cardiovasc Dis 7:2048004018773958. https://doi.org/10.1177/2048004018773958

    Article  PubMed  PubMed Central  Google Scholar 

  7. Valsangiacomo Buechel ER, Grosse-Wortmann L, Fratz S, Eichhorn J, Sarikouch S, Greil GF, Beerbaum P, Bucciarelli-Ducci C, Bonello B, Sieverding L, Schwitter J, Helbing WA, Eacvi Galderisi M, Miller O, Sicari R, Rosa J, Thaulow E, Edvardsen T, Brockmeier K, Qureshi S, Stein J (2015) Indications for cardiovascular magnetic resonance in children with congenital and acquired heart disease: an expert consensus paper of the Imaging Working Group of the AEPC and the Cardiovascular Magnetic Resonance Section of the EACVI. Eur Heart J Cardiovasc Imaging 16(3):281–297. https://doi.org/10.1093/ehjci/jeu129

    Article  CAS  PubMed  Google Scholar 

  8. Baumgartner H, Bonhoeffer P, De Groot NM, de Haan F, Deanfield JE, Galie N, Gatzoulis MA, Gohlke-Baerwolf C, Kaemmerer H, Kilner P, Meijboom F, Mulder BJ, Oechslin E, Oliver JM, Serraf A, Szatmari A, Thaulow E, Vouhe PR, Walma E; Task Force on the Management of Grown-up Congenital Heart Disease of the European Society of C, Association for European Paediatric C, Guidelines ESCCfP (2010) ESC Guidelines for the management of grown-up congenital heart disease (new version 2010). Eur Heart J 31(23):2915–2957. https://doi.org/10.1093/eurheartj/ehq249

    Article  PubMed  Google Scholar 

  9. Makowski MR, Wiethoff AJ, Uribe S, Parish V, Botnar RM, Bell A, Kiesewetter C, Beerbaum P, Jansen CH, Razavi R, Schaeffter T, Greil GF (2011) Congenital heart disease: cardiovascular MR imaging by using an intravascular blood pool contrast agent. Radiology 260(3):680–688. https://doi.org/10.1148/radiol.11102327

    Article  PubMed  Google Scholar 

  10. Tandon A, Byrne N, Velasco MLN, Zhang S, Dyer AK, Dillenbeck JM, Greil GF, Hussain T (2016) Use of a semi-automated cardiac segmentation tool improves reproducibility and speed of segmentation of contaminated right heart magnetic resonance angiography. Int J Cardiovasc Imaging 32(8):1273–1279. https://doi.org/10.1007/s10554-016-0906-0

    Article  PubMed  PubMed Central  Google Scholar 

  11. Dice LR (1945) Measures of the amount of ecologic association between species. Ecology 26(3):297–302

    Article  Google Scholar 

  12. Frydrychowicz A, Russe MF, Bock J, Stalder AF, Bley TA, Harloff A, Markl M (2010) Comparison of gadofosveset trisodium and gadobenate dimeglumine during time-resolved thoracic MR angiography at 3T. Acad Radiol 17(11):1394–1400. https://doi.org/10.1016/j.acra.2010.05.022

    Article  PubMed  Google Scholar 

  13. Meier LM, Meineri M, Qua Hiansen J, Horlick EM (2017) Structural and congenital heart disease interventions: the role of three-dimensional printing. Neth Heart J 25(2):65–75. https://doi.org/10.1007/s12471-016-0942-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Karim R, Bhagirath P, Claus P, James Housden R, Chen Z, Karimaghaloo Z, Sohn HM, Lara Rodriguez L, Vera S, Alba X, Hennemuth A, Peitgen HO, Arbel T, Gonzalez Ballester MA, Frangi AF, Gotte M, Razavi R, Schaeffter T, Rhode K (2016) Evaluation of state-of-the-art segmentation algorithms for left ventricle infarct from late Gadolinium enhancement MR images. Med Image Anal 30:95–107. https://doi.org/10.1016/j.media.2016.01.004

    Article  PubMed  Google Scholar 

  15. Veldhoen S, Behzadi C, Derlin T, Rybczinsky M, von Kodolitsch Y, Sheikhzadeh S, Henes FO, Bley TA, Adam G, Bannas P (2015) Exact monitoring of aortic diameters in Marfan patients without gadolinium contrast: intraindividual comparison of 2D SSFP imaging with 3D CE-MRA and echocardiography. Eur Radiol 25(3):872–882. https://doi.org/10.1007/s00330-014-3457-6

    Article  PubMed  Google Scholar 

  16. An G, Hong L, Zhou XB, Yang Q, Li MQ, Tang XY (2017) Accuracy and efficiency of computer-aided anatomical analysis using 3D visualization software based on semi-automated and automated segmentations. Ann Anat 210:76–83. https://doi.org/10.1016/j.aanat.2016.11.009

    Article  PubMed  Google Scholar 

  17. Potthast S, Mitsumori L, Stanescu LA, Richardson ML, Branch K, Dubinsky TJ, Maki JH (2010) Measuring aortic diameter with different MR techniques: comparison of three-dimensional (3D) navigated steady-state free-precession (SSFP), 3D contrast-enhanced magnetic resonance angiography (CE-MRA), 2D T2 black blood, and 2D cine SSFP. J Magn Reson Imaging 31(1):177–184. https://doi.org/10.1002/jmri.22016

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Barbara E. U. Burkhardt, Nicholas K. Brown, Gerald Greil, Tarique Hussain & Animesh Tandon

  2. Pediatric Cardiology, Department of Surgery, Pediatric Heart Center, University Children’s Hospital Zurich, Steinwiesstr. 75, 8032, Zurich, Switzerland

    Barbara E. U. Burkhardt

  3. Division of Imaging Sciences and Biomedical Engineering, King’s College London, London, UK

    Jaclyn E. Carberry, Marí Nieves Velasco Forte, Nicholas Byrne, Gerald Greil & Tarique Hussain

  4. Department of Biomedical Engineering, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Gerald Greil, Tarique Hussain & Animesh Tandon

Authors
  1. Barbara E. U. Burkhardt
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nicholas K. Brown
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jaclyn E. Carberry
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Marí Nieves Velasco Forte
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Nicholas Byrne
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Gerald Greil
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Tarique Hussain
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Animesh Tandon
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Barbara E. U. Burkhardt.

Ethics declarations

Conflict of interest

TH and AT have significant ownership interest in VARYFII Imaging, LLC. Imaging, LLC. All the other authors were not consultants or employees for VARYFII Imaging, LLC and had control of inclusion of any data and information that might present a conflict of interest for TH or AT, and had no other conflicts of interest.

Research involving human participants

This human study has been approved by the appropriate institutional ethics committee and has therefore been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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

Burkhardt, B.E.U., Brown, N.K., Carberry, J.E. et al. Creating three dimensional models of the right ventricular outflow tract: influence of contrast, sequence, operator, and threshold. Int J Cardiovasc Imaging 35, 2067–2076 (2019). https://doi.org/10.1007/s10554-019-01646-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10554-019-01646-1

Keywords

Search

Navigation