3D Reconstruction of Coronary Veins from a Single X-Ray Fluoroscopic Image and Pre-operative MR

  • Maria Panayiotou
  • Daniel Toth
  • Tamer Adem
  • Peter Mountney
  • Alexander Brost
  • Jonathan M. Behar
  • C. Aldo Rinaldi
  • R. James Housden
  • Kawal S. Rhode
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10124)

Abstract

Cardiac resynchronization therapy (CRT) is an effective treatment for patients with congestive heart failure and ventricular dyssynchrony. Despite the overall efficacy of CRT, approximately 30% of patients receiving CRT do not improve. One of the main technical problems related to the CRT procedure is inadequate visualisation in X-ray fluoroscopy of the venous anatomy in relation to accurate cardiac chamber visualisation. This paper proposes a novel approach for 3D reconstruction of coronary veins from a single contrast enhanced intra-operative fluoroscopy image. For this application, the method uses back-projection geometry and a Euclidean distance/angle-based cost function. The algorithm is validated on a phantom and five patient datasets, comprising six view-angle orientations for the phantom dataset and two view-angle orientations for each of the patient datasets. Median(inter-quartile range) 3D-reconstruction accuracies of 1.41(0.55–3.00) mm and 3.28(2.10–4.89) mm were established for the phantom and patient data, respectively. The technique can facilitate careful advancement of the cannulating guide over a guidewire or a diagnostic catheter positioned in the coronary sinus, and consequently, improve the chances of response to CRT.

Keywords

Coronary veins 3D reconstruction X-ray fluoroscopy 

Notes

Acknowledgements and Disclaimer

We acknowledge financial support from the Department of Health via the National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre award to Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London, King’s College Hospital NHS Foundation Trust and Innovate UK. This work was supported by the Engineering and Physical Sciences Research Council [grant number EP/L505328/1] and Innovate UK. Concepts and information presented are based on research and are not commercially available.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Maria Panayiotou
    • 1
  • Daniel Toth
    • 1
    • 3
  • Tamer Adem
    • 1
  • Peter Mountney
    • 4
  • Alexander Brost
    • 5
  • Jonathan M. Behar
    • 1
    • 2
  • C. Aldo Rinaldi
    • 2
  • R. James Housden
    • 1
  • Kawal S. Rhode
    • 1
  1. 1.Division of Imaging Sciences and Biomedical EngineeringKing’s College LondonLondonUK
  2. 2.Deparment of CardiologyGuy’s and St. Thomas’ Hospitals NHS Foundation TrustLondonUK
  3. 3.Siemens Healthcare, LtdLondonUK
  4. 4.Medical Imaging Technologies, Siemens HealthineersPrincetonUSA
  5. 5.Siemens Healthcare GmbHForchheimGermany

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