Image Segmentation and Modeling of the Pediatric Tricuspid Valve in Hypoplastic Left Heart Syndrome

  • Alison M. Pouch
  • Ahmed H. Aly
  • Andras Lasso
  • Alexander V. Nguyen
  • Adam B. Scanlan
  • Francis X. McGowan
  • Gabor Fichtinger
  • Robert C. Gorman
  • Joseph H. GormanIII
  • Paul A. Yushkevich
  • Matthew A. Jolley
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10263)

Abstract

Hypoplastic left heart syndrome (HLHS) is a single-ventricle congenital heart disease that is fatal if left unpalliated. In HLHS patients, the tricuspid valve is the only functioning atrioventricular valve, and its competence is therefore critical. This work demonstrates the first automated strategy for segmentation, modeling, and morphometry of the tricuspid valve in transthoracic 3D echocardiographic (3DE) images of pediatric patients with HLHS. After initial landmark placement, the automated segmentation step uses multi-atlas label fusion and the modeling approach uses deformable modeling with medial axis representation to produce patient-specific models of the tricuspid valve that can be comprehensively and quantitatively assessed. In a group of 16 pediatric patients, valve segmentation and modeling attains an accuracy (mean boundary displacement) of 0.8 ± 0.2 mm relative to manual tracing and shows consistency in annular and leaflet measurements. In the future, such image-based tools have the potential to improve understanding and evaluation of tricuspid valve morphology in HLHS and guide strategies for patient care.

Keywords

Medial axis representation Multi-atlas segmentation Tricuspid valve Hypoplastic left heart syndrome  3D echocardiography 

References

  1. 1.
    Gordon, B.M., Rodriguez, S., Lee, M., Chang, R.K.: Decreasing number of deaths of infants with hypoplastic left heart syndrome. J. Pediatr. 153(3), 354 (2008)CrossRefGoogle Scholar
  2. 2.
    Reller, M.D., Strickland, M.J., Riehle-Colarusso, T., Mahle, W.T., Correa, A.: Prevalence of congenital heart defects in metropolitan Atlanta, 1998–2005. J. Pediatr. 153(6), 807 (2008)CrossRefGoogle Scholar
  3. 3.
    Barber, G., Helton, J.G., Aglira, B.A., Chin, A.J., Murphy, J.D., Pigott, J.D., Norwood, W.I.: The significance of tricuspid regurgitation in hypoplastic left-heart syndrome. Am. Heart J. 116, 1563–1567 (1988)CrossRefGoogle Scholar
  4. 4.
    Elmi, M., Hickey, E.J., Williams, W.G., Van Arsdell, G., Caldarone, C.A., McCrindle, B.W.: Long-term tricuspid valve function after Norwood operation. J. Thorac. Cardiovasc. Surg. 142, 1341–1347 (2011). e4CrossRefGoogle Scholar
  5. 5.
    Kutty, S., Colen, T., Thompson, R.B., Tham, E., Li, L., Vijarnsorn, C., Polak, A., Truong, D.T., Danford, D.A., Smallhorn, J.F., Khoo, N.S.: Tricuspid regurgitation in hypoplastic left heart syndrome. Circ. Cardiovasc. Imaging 7, 765–772 (2014)CrossRefGoogle Scholar
  6. 6.
    Bharucha, T., Honjo, O., Seller, N., Atlin, C., Redington, A., Caldarone, C.A., van Arsdell, G., Mertens, L.: Mechanisms of tricuspid valve regurgitation in hypoplastic left heart syndrome: a case-matched echocardiographic-surgical comparison study. Eur. Heart J. Cardiovasc. Imaging 14, 135–141 (2013)CrossRefGoogle Scholar
  7. 7.
    Takahashi, K., Mackie, A.S., Rebeyka, I.M., Ross, D.B., Robertson, M., Dyck, J.D., Inage, A., Smallhorn, J.F.: Two-dimensional versus transthoracic real-time three-dimensional echocardiography in the evaluation of the mechanisms and sites of atrioventricular valve regurgitation in a congenital heart disease population. J. Am. Soc. Echocardiogr. 23, 726–734 (2010)CrossRefGoogle Scholar
  8. 8.
    Badano, L.P., Agricola, E., Perez de Isla, L., Gianfagna, P., Zamorano, J.L.: Evaluation of the tricuspid valve morphology and function by transthoracic real-time three-dimensional echocardiography. Eur. J. Echocardiogr. 10, 477–484 (2009)CrossRefGoogle Scholar
  9. 9.
    Anwar, A.M., Geleijnse, M.L., Soliman, O.I., McGhie, J.S., Frowijn, R., Nemes, A., van den Bosch, A.E., Galema, T.W., Ten Cate, F.J.: Assessment of normal tricuspid valve anatomy in adults by real-time three-dimensional echocardiography. Int. J. Cardiovasc. Imaging 23, 717–724 (2007)CrossRefGoogle Scholar
  10. 10.
    Pouch, A.M., Wang, H., Takabe, M., Jackson, B.M., Gorman 3rd, J.H., Gorman, R.C., Yushkevich, P.A., Sehgal, C.M.: Fully automatic segmentation of the mitral leaflets in 3D transesophageal echocardiographic images using multi-atlas joint label fusion and deformable medial modeling. Med. Image Anal. 18, 118–129 (2014)CrossRefGoogle Scholar
  11. 11.
    Pouch, A.M., Tian, S., Takebe, M., Yuan, J., Gorman, R., Cheung, A.T., Wang, H., Jackson, B.M., Gorman, J.H., Gorman, R.C., Yushkevich, P.A.: Medially constrained deformable modeling for segmentation of branching medial structures: application to aortic valve segmentation and morphometry. Med. Image Anal. 26, 217–231 (2015)CrossRefGoogle Scholar
  12. 12.
    Jassar, A.S., Vergnat, M., Jackson, B.M., McGarvey, J., Cheung, A.T., Ferrari, G., Woo, Y.J., Acker, M.A., Gorman, R.C., Gorman III, J.H.: Regional annular geometry in patients with mitral regurgitation: Implications for annuloplasty ring selection. Ann. Thorac. Surg. 97(1), 64–70 (2014)CrossRefGoogle Scholar
  13. 13.
    Fedorov, A., Beichel, R., Kalpathy-Cramer, J., Finet, J., Fillion-Robin, J.-C., Pujol, S., Bauer, C., Jennings, D., Fennessy, F.M., Sonka, M., Buatti, J., Aylward, S.R., Miller, J.V., Pieper, S., Kikinis, R.: 3D slicer as an image computing platform for the quantitative imaging network. Magn. Reson. Imaging 30(9), 1323–1341 (2012)CrossRefGoogle Scholar
  14. 14.
    Wang, H., Suh, J.W., Das, S., Pluta, J., Craige, C., Yushkevich, P.: Multi-atlas segmentation with joint label fusion. IEEE Trans. Pattern Anal. Mach. Intell. 35(3), 611–623 (2013)CrossRefGoogle Scholar
  15. 15.
    Blum, H.: A transformation for extracting new descriptors of shape. In: Wathen-Dunn, W. (ed.) Models for the Perception of Speech and Visual Form, pp. 362–380. MIT Press, Cambridge (1967)Google Scholar
  16. 16.
    Yushkevich, P.A., Zhang, H., Gee, J.C.: Continuous medial representation for anatomical structures. IEEE Trans. Med. Imaging 25(12), 1547–1564 (2006)CrossRefGoogle Scholar
  17. 17.
    Fukuda, S., Saracino, G., Matsumura, Y., Daimon, M., Tran, H., Greenberg, N.L., Hozumi, T., Yoshikawa, J., Thomas, J.D., Shiota, T.: Three-dimensional geometry of the tricuspid annulus in healthy subjects and in patients with functional tricuspid regurgitation. Circulation 114(suppl I), I-492–I-498 (2006)Google Scholar
  18. 18.
    Sluysmans, T., Colan, D.: Theoretical and empirical derivation of cardiovascular allometric relationships in children. J. Appl. Physiol. 99, 445–457 (2005)CrossRefGoogle Scholar
  19. 19.
    Ionasec, R.I., Voigt, I., Georgescu, B., Wang, Y., Houle, H., Vega-Higuera, F., Navab, N., Comaniciu, D.: Patient-specific modeling and quantification of the aortic and mitral valves from 4-D cardiac CT and TEE. IEEE Trans. Med. Imaging 29, 1636–1651 (2010)CrossRefGoogle Scholar
  20. 20.
    Schneider, R.J., Tenenholtz, N.A., Perrin, D.P., Marx, G.R., del Nido, P.J., Howe, R.D.: Patient-specific mitral leaflet segmentation from 4D ultrasound. Med. Image Comput. Comput. Assist. Interv. 14, 520–527 (2011)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Alison M. Pouch
    • 1
  • Ahmed H. Aly
    • 2
  • Andras Lasso
    • 3
  • Alexander V. Nguyen
    • 4
  • Adam B. Scanlan
    • 4
  • Francis X. McGowan
    • 4
  • Gabor Fichtinger
    • 3
  • Robert C. Gorman
    • 5
  • Joseph H. GormanIII
    • 5
  • Paul A. Yushkevich
    • 1
  • Matthew A. Jolley
    • 4
  1. 1.Department of RadiologyUniversity of PennsylvaniaPhiladelphiaUSA
  2. 2.Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaUSA
  3. 3.Laboratory for Percutaneous SurgeryQueen’s UniversityKingstonCanada
  4. 4.Department of Anesthesiology and Critical Care Medicine, Children’s Hospital of PhiladelphiaUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaUSA
  5. 5.Gorman Cardiovascular Research Group, Department of Surgery, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaUSA

Personalised recommendations