Towards personalised biomechanical assessment of child birth safety; Automatic generation of personalised bony pelvis geometry by template mesh morphing

Background and objective: Pelvic floor muscle injuries associated with vaginal childbirth can result in pelvic organ disorders. Personalised biomechanical models offer a tool for predicting the risk of complications during childbirth. An important component of such computational models is a geometrically precise description of a pelvis. In this study, we developed an algorithm that automatically generates a discretised surface to define the personalised bony pelvis geometry of individual women from a template mesh. Methods: We developed and implemented in 3D Slicer, a free open-source image computing software platform, the algorithm that applies radial basis function to morph the template mesh to the personalised geometry based on the bony pelvis landmarks identified in the target magnetic resonance image that depicts the analysed pelvis. Results: We demonstrated the performance of our methods by automatically generating personalised bony pelvis meshes for six women. For quantitative evaluation, we used the Hausdorff distance (HD) and birth canal dimensions. The median HD was within two times the voxel dimension of the pelvis magnetic resonance (MR) images. The dimensions of the birth canal determined from the personalised meshes and from manually segmented MR images were, for practical purposes, undistinguishable. Conclusions: Our algorithm generates a personalised bony pelvis model by mesh-morphing based on a template model and bony landmarks. Accuracy and performance of the algorithm were evaluated by morphing six bony pelves. Differences between the key birth canal dimensions derived from the personalised pelvis models and those obtained from pelvis MR images were within the inter-observer variation reported in the literature for MR pelvimetry measurements.