Validation of deformable image registration techniques is extremely
important, but hard, especially when complex deformations or content mismatch
are involved. These complex deformations and content mismatch, for example,
occur after the placement of an applicator for brachytherapy for cervical
cancer. Virtual phantoms could enable the creation of validation data sets with
ground truth deformations that simulate the large deformations that occur
between image acquisitions. However, the quality of the multi-organ Finite
Element Method (FEM)-based simulations is dependent on the patient-specific
external forces and mechanical properties assigned to the organs. A common
approach to calibrate these simulation parameters is through optimization,
finding the parameter settings that optimize the match between the outcome of
the simulation and reality. When considering inherently simplified organ
models, we hypothesize that the optimal deformations of one organ cannot be
achieved with a single parameter setting without compromising the optimality of
the deformation of the surrounding organs. This means that there will be a
trade-off between the optimal deformations of adjacent organs, such as the
vagina-uterus and bladder. This work therefore proposes and evaluates a
multi-objective optimization approach where the trade-off between organ
deformations can be assessed after optimization. We showcase what the extent of
the trade-off looks like when bi-objectively optimizing the patient-specific
mechanical properties and external forces of the vagina-uterus and bladder for
FEM-based simulations