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2 Journal of Medical Informatics & Technologies

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Patient-specific graft design method for cranofacial surgical planning

Król Z., Chlebiej M., Zerfass P., Zeilhofer H.-F., Sader R., Mikołajczak P., Keeve E.

Journal of Medical Informatics & Technologies

2002

Vol. 3

MI189--197

This paper presents a method for computer assisted selection of optimal donor sites for autologous osseous grafts in the craniofacial surgery. At the initial graft design stage the surgeon defines in the CT data set the shape of the bone segment to be reconstructed and in the donor region CT data set a set of constraints for the optimization task. This non-automatic step is followed by a fully automatic optimization stage, which delivers a set of sub-optimal and optimal donor sites for a given template. Such approach permits the surgeon to find the best site for harvesting the graft and enables an exact anatomical reconstruction of the osseous section.

An automated osteotomy design for autologous bone grafts in craniofacial surgery

Król Z., Zerfass P., Sader R., Zeilhofer H.-F., Keeve E.

Journal of Medical Informatics & Technologies

2001

Vol. 2, Part. 2

MT117--MT124

In the treatment of craniofacial osseous defects it is frequently required that the surgeon has to graft bone to replace a missing or surgically removed segment. The reconstruction of this area poses a difficult challenge owing to the complexity of its bony structures as well as to its great importance for the chewing and speech ability. A common method of surgically reconstructing the craniofacial region involves using autologous grafts. By using the registration framework a novel surgery planning method has been developed. The method enables computer-aided selection of optimal donor sites for autologous bone grafts in the craniofacial surgery. The main advantage of the method is that after determination of the initial conditions and constraints it provides an automatic procedure to find the best fitting position. All generated solutions can be explored interactively on the computer display via an efficient graphical interface. Applying different similarity measures enables the surgeon to select the optimal donor site not only in terms of bone surface correlation but also according to the whole volumetric information contained in both data sets. This new approach permits more precise planning of the surgical procedure, reducing intraoperative time and improving the postoperative outcome.