Interactive virtual stent planning for the treatment of coarctation of the aorta
The coarctation of the aorta (CoA), a local narrowing of the aortic arch, accounts for 7 % of all congenital heart defects. Stenting is a recommended therapy to reduce the pressure gradient. This procedure is associated with complications such as the development of adverse flow conditions. A computer-aided treatment planning based on flow simulations can help to predict possible complications. The virtual stent planning is an important, intermediate step in the treatment planning pipeline. We present a novel approach that automatically suggests a stent setup and provides a set of intuitive parameters that allow for an interactive adaption of the suggested stent placement and induced deformation.
A high-quality mesh and a centerline are automatically generated. The stent-induced deformation is realized through a deformation of the centerline and a vertex displacement with respect to the deformed centerline and additional stent parameters. The parameterization is automatically derived from the underlying data and can be optionally altered through a condensed set of clinically sound parameters.
The automatic deformation can be generated in about 25 s on a consumer system. The interactive adaption can be performed in real time. Compared with manual expert reconstructions of the stented vessel section, the mean difference of vessel path and diameter is below 1 mm.
Our approach enables a medical user to easily generate a plausibly deformed vessel mesh which is necessary as input for a simulation-based treatment planning of CoA.
KeywordsCoarctation of the aorta Computer-aided treatment Virtual stenting Stenting Geometric processing Image processing VTK VMTK CARDIOPROOF
This work is part of the EU project CARDIOPROOF (partially funded by the European Commission under ICT-2013.5.2, Grant Agreement: 611232).
Conflict of interest
The authors declare that they have no conflict of interest.
- 2.Forbes TJ, Kobayashi D (2013) Stenting coarctation of the aorta. Card Interv Today Jan/Feb2013:38–44Google Scholar
- 6.Markl M, Harloff A, Bley TA, Zaitsev M, Jung B, Weigang E, Langer M, Hennig J, Frydrychowicz A (2007) Time-resolved 3D MR velocity mapping at 3T: improved navigator-gated assessment of vascular anatomy and blood flow. J Magn Reson Imaging 25:824–831. doi: 10.1002/jmri.20871 CrossRefPubMedGoogle Scholar
- 8.Meier S, Hennemuth A, Drexl J, Bock J, Jung B, Preusser T (2012) A fast and noise-robust method for computation of intravascular pressure difference maps from 4D PC-MRI Data. Proc STACOM, pp 215–224. doi: 10.1007/978-3-642-36961-2_25
- 9.Hennemuth A, Friman O, Schumann C (2011) Fast interactive exploration of 4D MRI flow data. Proceedings of SPIE. doi: 10.1117/12.878202
- 10.Meier S, Hennemuth A, Tchipev N (2011) Towards patient-individual blood flow simulations based on PC-MRI measurements. Lecture notes in informatics 192Google Scholar
- 12.LaDisa JF Jr, Olson LE, Guler I, Hettrick DA, Audi SH, Kersten JR, Warltier DC, Pagel PS (2004) Stent design properties and deployment ratio influence indexes of wall shear stress: a three-dimensional computational fluid dynamics investigation within a normal artery. J Appl Physiol 97:424–430. doi: 10.1152/japplphysiol.01329.2003 CrossRefPubMedGoogle Scholar
- 16.Gundert TJ, Shadden SC, Williams AR, Koo BK, Feinstein JA, Ladisa JF Jr (2011) A rapid and computationally inexpensive method to virtually implant current and next-generation stents into subject-specific computational fluid dynamics models. Ann Biomed Eng 39:1423–1437. doi: 10.1007/s10439-010-0238-5 CrossRefPubMedGoogle Scholar
- 18.Demirci S, Lee SL, Radeva P, Unal G (2012) 1st International MICCAI-workshop on computer assisted stenting. Proceedings of MICCAI-STENT’12Google Scholar
- 19.Balocco S, Gatta C, Demirci S, Lee SL, Tangen GA (2013) 2nd International MICCAI-workshop on computer assisted stenting. Proceedings of MICCAI-STENT’13Google Scholar
- 21.Egger J, Großkopf S, Freisleben B (2009) Virtual stenting for carotid stenosis with elastic artery wall modeling. Proceedings of IFMBE, pp 2499–2502. doi: 10.1007/978-3-540-89208-3_599
- 25.Schroeder W, Martin K, Lorensen B (1996) The visualization toolkit—an object-oriented approach to 3D graphics. Prentice Hall PTR, Upper Saddle River, N.JGoogle Scholar
- 27.Goubergrits L, Riesenkampff E, Yevtushenko P, Schaller J, Kertzscher U, Hennemuth A, Berger F, Schubert S, Kuehne T (2014) MRI-based computational fluid dynamics for diagnosis and treatment prediction: clinical validation study in patients with coarctation of aorta. J Magn Reson Imaging. doi: 10.1002/jmri.24639
- 28.Zhang Z (1994) Iterative point matching for registration of free-form curves and surfaces. Int J Comput Vis 13:119–152. doi: 10.1007/BF01427149
- 29.Carrascosa P, Capuñay C, Deviggiano A, Rodríguez-Granillo GA, Sagarduy MI, Cortines P, Carrascosa J, Parodi JC (2013) Thoracic aorta cardiac-cycle related dynamic changes assessed with a 256-slice CT scanner. Cardiovasc Diagn Ther 3:125–128. doi: 10.3978/j.issn.2223-3652.2013.07.02 PubMedCentralPubMedGoogle Scholar