header advert
Orthopaedic Proceedings Logo

Receive monthly Table of Contents alerts from Orthopaedic Proceedings

Comprehensive article alerts can be set up and managed through your account settings

View my account settings

Visit Orthopaedic Proceedings at:



Full Access



8th Combined Meeting Of Orthopaedic Research Societies (CORS)



This work proposes a novel, automatic method to obtain an anatomical reconstruction for 3D segmented bones with large acetabular defects. The method works through the fitting of a Statistical Shape Model to the non-defect parts of the bone.


Patient-specific implants can be used to treat patients with large acetabular bone defects (IIa-c, IIIb, Paprosky 1994). These implants require a full 3D preoperative planning that includes segmentation of volumetric images (CT or MRI), extraction of the 3D shape, reconstruction of the bone defect into its anatomic (non-defect) state, design of an implant with a perfect fit and optimal placement of the screws. The anatomic reconstruction of the bone defect will play a key role in diagnosing the amount of bone loss and in the design of the implant. Previous reconstruction methods rely on a healthy contralateral (Gelaude 2007); however this is not always available (e.g. partial scan or implant present). Statistical shape models (SSM) of healthy bones can help to increase the accuracy and usability of the reconstruction and will decrease the manual labor and user dependency. Skadlubowicz (2009) illustrated the use of an SSM to reconstruct pelvic bones with tumor defects; however tumors generally affect a smaller region of the bone so that the reconstruction will be easier than in large acetabular bone defects. Also, the tumor reconstruction method uses 80 manually indicated landmarks, while the proposed method only uses 14.

Patients & Methods

CT-scans from subjects with a healthy hemi-pelvis (15 male, 33 female, mean age: 69±20) were used to generate an SSM. The CT-scans were segmented using Mimics (Materialise NV, Belgium) to create a triangulated mesh. Preprocessing of the meshes ensured that the triangulation was smooth and uniform to help solve the corresponding point problem. An algorithm based on Redert (1999) was used to morph the template hemi-pelvis onto each dataset entity, creating a dataset with corresponding points. From this dataset the SSM was calculated using principal component analysis, so that the principal components serve as parameters for the mathematical model of the hemi-pelvis. To fit the SSM to a new defect hemi-pelvis, a matching algorithm was used. The algorithm varies the Principal Components independently optimizing the distance of the non-defect parts of the defect hemi-pelvis to the SSM sample. To validate the reconstruction method, 6 healthy bone meshes were used to generate a synthetic defect in the acetabular region. The original mesh was used as ‘golden standard’ to measure the reconstruction error. To illustrate the clinical use of the reconstruction method, one hemi-pelvis with a substantial defect was reconstructed.


The correspondence error for the morphing algorithm was 4.68±0.78 mm. The leave-one-out error for the SSM was 1.30±0.96 mm. The reconstruction error for the non-defect part was 1.44±1.13mm and for the reconstructed part 2.15±1.53mm.


The proposed method performs comparable to the contralateral method and the tumor reconstruction method, without the need of a healthy contralateral geometry. Consequently, the validation and the clinical illustration show that the proposed method is promising for automatic reconstruction of large acetabular defects.