A Novel Interventional Guidance Framework for Transseptal Puncture in Left Atrial Interventions

  • Pedro MoraisEmail author
  • João L. Vilaça
  • Sandro Queirós
  • Pedro L. Rodrigues
  • João Manuel R. S. Tavares
  • Jan D’hooge
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11042)


Access to the left atrium is required for several percutaneous cardiac interventions. In these procedures, the inter-atrial septal wall is punctured using a catheter inserted in the right atrium under image guidance. Although this approach (transseptal puncture - TSP) is performed daily, complications are common. In this work, we present a novel concept for the development of an interventional guidance framework for TSP. The pre-procedural planning stage is fused with 3D intra-procedural images (echocardiography) using manually defined landmarks, transferring the relevant anatomical landmarks to the interventional space and enhancing the echocardiographic images. In addition, electromagnetic sensors are attached to the surgical instruments, tracking and including them in the enhanced intra-procedural world. Two atrial phantom models were used to evaluate this framework. To assess its accuracy, a metallic landmark was positioned in the punctured location and compared with the ideal one. The intervention was possible in both models, but in one case positioning of the landmark failed. An error of approximately of 6 mm was registered for the successful case. Technical characteristics of the framework showed an acceptable performance (frame rate ~5 frames/s). This study presented a proof-of-concept for an interventional guidance framework for TSP. However, a more automated solution and further studies are required.


Image-guided cardiac interventions Transseptal puncture Image fusion Echocardiography Integrated interventional guidance framework 



The authors acknowledge Fundação para a Ciência e a Tecnologia (FCT), in Portugal, and the European Social Found, European Union, for funding support through the “Programa Operacional Capital Humano” (POCH) in the scope of the PhD grants SFRH/BD/95438/2013 (P. Morais) and SFRH/BD/93443/2013 (S. Queirós).

This work was funded by projects NORTE-01-0145-FEDER-000013, NORTE-01-0145-FEDER-000022 and NORTE-01-0145-FEDER-024300, supported by Northern Portugal Regional Operational Programme (Norte2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER), and has also been funded by FEDER funds, through Competitiveness Factors Operational Programme (COMPETE), and by national funds, through the FCT, under the scope of the project POCI-01-0145-FEDER-007038.

The authors would like to acknowledge Walter Coudyzer and Steven Dymarkowski (Department of Radiology, UZLeuven, Leuven, Belgium) for performing the CT acquisitions. Moreover, the authors would like to thank General Electric (GE VingMed, Horten, Norway) for giving access to the 3D streaming option.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Pedro Morais
    • 1
    • 2
    • 3
    • 4
    Email author
  • João L. Vilaça
    • 3
    • 4
    • 5
  • Sandro Queirós
    • 2
    • 3
    • 4
    • 6
  • Pedro L. Rodrigues
    • 3
    • 4
  • João Manuel R. S. Tavares
    • 1
  • Jan D’hooge
    • 2
  1. 1.Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial, Departamento de Engenharia MecânicaFaculdade de Engenharia, Universidade do PortoPortoPortugal
  2. 2.Lab on Cardiovascular Imaging and Dynamics, Department of Cardiovascular SciencesKULeuven - University of LeuvenLeuvenBelgium
  3. 3.Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
  4. 4.ICVS/3B’s-PT, Government Associate LaboratoryBraga, GuimarãesPortugal
  5. 5.2Ai-Technology SchoolPolytechnic Institute of Cávado and AveBarcelosPortugal
  6. 6.Algoritmi Center, School of EngineeringUniversity of MinhoGuimarãesPortugal

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