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.