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  • 11 May 2025

Cardiovascular Fluid Mechanics Laboratory

Fontan Surgical Planning

Surgical planning in the Fontan procedure has been used in the most complex single ventricle cases, and the aim is to find the best surgical option on a patient-specific basis[1, 2]. An overview of the process is shown in the figure below, and the steps are described as follows. 1) First we obtain medical images with all the information necessary. 2) Then we used previously developed tools to reconstruct the patient-specific anatomy and flow[3,4]. 3) Afterwards we used a novel surgical planning tool to create the surgical options taking into account the surrounding anatomy that limits the surgical options. 4) Lastly, computational fluid dynamic solver[5] are used to simulate the blood flow inside the options generated. Based on all this information, the best surgical planning option is suggested to the clinical team for implementation.

This project is done in collaboration with clinicians at the main Children’s Hospitals in the East coast and represents a collaborative effort between engineers, scientists and medical doctors.

FontanPlanning_1

Select Publications

  1. de Zelicourt, D.A., et al., Individualized computer-based surgical planning to address pulmonary arteriovenous malformations in patients with a single ventricle with an interrupted inferior vena cava and azygous continuation. J Thorac Cardiovasc Surg, 2011. 141(5): 1170-7.
  2. Sundareswaran, K.S., et al., Correction of pulmonary arteriovenous malformation using image-based surgical planning. JACC Cardiovasc Imaging, 2009. 2(8): 1024-30.
  3. Frakes, D.H., et al., New techniques for the reconstruction of complex vascular anatomies from MRI images. J Cardiovasc Magn Reson, 2005. 7(2): 425-32.
  4. Sundareswaran, K.S., et al., Optimum fuzzy filters for phase-contrast magnetic resonance imaging segmentation. J Magn Reson Imaging, 2009. 29(1): 155-65.
  5. Zélicourt, D.d., et al., Flow simulations in arbitrarily complex cardiovascular anatomies – An unstructured Cartesian grid approach. Computers & Fluids, 2009. 38(9): 1749-1762.

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