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Author Notes:

Dr. Ajit P. Yoganathan, Wallace H. Coulter School of Biomedical Engineering, Georgia Institute of Technology and Emory University, 313 Ferst Drive, Atlanta, Georgia 30332-0535. ajit.yoganathan@bme.gatech.edu. .

The authors acknowledge their clinical collaborators Dr. Gil Wernosvky, from the Children’s Hospital of Philadelphia; and Dr. Donald Putman, from Metropediatric Cardiology Associates PC.


Research Funding:

This work was supported by the NIH/NHLBI (grant HL67622); the NSF project (CBET-0625976); the Minnesota Supercomputing Institute; and an American Heart Association pre-doctoral fellowship.

Drs. Sundareswaran and Zélicourt contributed equally to this work.


  • Science & Technology
  • Life Sciences & Biomedicine
  • Cardiac & Cardiovascular Systems
  • Radiology, Nuclear Medicine & Medical Imaging
  • Cardiovascular System & Cardiology
  • Fontan
  • single ventricle congenital heart defects
  • phase-contrast cardiac magnetic resonance
  • computational fluid dynamics

Correction of Pulmonary Arteriovenous Malformation Using Image-Based Surgical Planning


Journal Title:

JACC: Cardiovascular Imaging


Volume 2, Number 8


, Pages 1024-1030

Type of Work:

Article | Post-print: After Peer Review


The objectives of this study were to develop an image-based surgical planning framework that 1) allows for in-depth analysis of pre-operative hemodynamics by the use of cardiac magnetic resonance and 2) enables surgeons to determine the optimum surgical scenarios before the operation. This framework is tailored for applications in which post-operative hemodynamics are important. In particular, it is exemplified here for a Fontan patient with severe left pulmonary arteriovenous malformations due to abnormal hepatic flow distribution to the lungs. Patients first undergo cardiac magnetic resonance for 3-dimensional anatomy and flow reconstruction. After analysis of the pre-operative flow fields, the 3-dimensional anatomy is imported into an interactive surgical planning interface for the surgeon to virtually perform multiple surgical scenarios. Associated hemodynamics are predicted by the use of a fully validated computational fluid dynamic solver. Finally, efficiency metrics (e.g., pressure decrease and hepatic flow distribution) are weighted against surgical feasibility to determine the optimal surgical option.

Copyright information:

© 2009 American College of Cardiology Foundation.

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