Advanced concepts in orbital wall fractures: Virtual surgical planning, intraoperative imaging, and clinical management

Research output: PhD ThesisPhD-Thesis - Research and graduation internal


The orbital anatomy is complex. The orbital cavity is compact, has a conical shape, and the orbital floor and medial wall are thin and fragile. The soft tissue consists of neurovascular structures, adipose tissue, connective tissue, muscles, and the globe. As a result, recovery after an orbital wall fracture is sometimes unpredictable and the reconstruction can be challenging.
The aim of this thesis is twofold. Firstly, the aim is to investigate the added value of several individual components of computer-assisted surgery. The first study demonstrates a quick, accurate, and efficient semi-automatic software segmentation method to measure the orbital volume. In the second study, it is proven that the human orbital cavities are almost symmetrical. This validates the use of the mirroring technique, where the unaffected orbital cavity is mirrored onto the affected side in order to find the best-fit position for an implant. The outcome of the two cadaver studies is that both preoperative planning and intraoperative imaging improve implant position. Hence, these modern technologies improve the accuracy and predictably in orbital reconstruction.
Secondly, the aim is to upgrade the clinical management of these fractures by evaluating the available literature and convert this into a new clinical protocol. In the prospective cohort study, the emphasis is on nonsurgical treatment, frequent orthoptic measurements, multidisciplinary collaboration, and functional outcome. The results confirm the success of this approach. It can be stated that the body has a good regenerative capacity and that most orbital wall fractures can recover without surgical intervention.
Original languageEnglish
Awarding Institution
  • University of Amsterdam
  • Becking, AG, Supervisor
  • Maal, T.J.J., Supervisor
  • Gooris, P.J.J., Co-supervisor
  • Dubois, L., Co-supervisor
Award date9 Oct 2020
Print ISBNs9789463326520
Publication statusPublished - 2020


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