Computer aided reconstruction of complex bone fractures

The reposition of bone fragments after a fracture, a process also referred to as fracture reduction, is a crucial task during the operative treatment of complex bone fractures. Anatomically incorrect fracture reduction can result in severe post-traumatic complications. In order to avoid such problems and obtain an optimal fit between all relevant fracture fragments, the surgeon traditionally exposes the fractured bone by cutting the soft tissue envelope in order to be able to access the fragments directly. The subsequent repositioning of fracture fragments often requires a trial and error approach, which leads to a significant prolongation of the surgery and causes additional trauma to the fragments and the surrounding soft tissue. Wound healing failure, infections, or joint stiffness can be the consequence. Therefore, there is a clear trend towards the development of less invasive techniques to reconstruct complex fractures. In order to support this trend, software tools for calculating and visualizing the optimal way of repositioning fracture fragments based on the usage of segmented CT images as input data have been developed. In several studies, they have successfully demonstrated their potential to decrease operation times and increase reduction accuracy. However, the clinical usability of these tools is limited since the time requirement as well as the necessary amount of user interaction for the virtual reconstruction is too high. Moreover, existing software tools are often restricted to particular types of fractures. Hence, the main objective of the proposed project is to overcome these limitations by developing an algorithmic pipeline that is calculating and visualizing the optimal way of repositioning fracture fragments without user interaction and without restriction to particular types of bones. For this purpose, novel concepts like an extensive usage of (statistical) prior knowledge on the shape of the healthy (=non-fractured) bone during the reconstruction process will be applied. Moreover, information coming from CT volumes will be combined with information on geometric surface properties in order to identify corresponding (fragment) surface points. In order to be able to provide an easy to use software tool that is freely available worldwide and can be used for surgical planning purposes, the resulting algorithmic pipeline will be integrated into a widely used open-source software package for computer-assisted surgery called 3D Slicer. 3D Slicer is offering different types of modern algorithms for 3D volume visualization and is providing the technical and methodical environment that is a precondition for a successful and time-efficient achievement of the project objectives. Beside of this, the integration of the developed algorithms into 3D Slicer will provide the possibility to use them as a basis for continuing algorithmic developments in related fields of research like robot-assisted surgery, bone quality assessment, or computer aided fracture classification. The accuracy of the resulting virtual reconstruction will be evaluated quantitatively using real and synthetic test data as well as qualitatively by visual inspection of the three- dimensional visualizations of the virtual reconstructions performed by surgeons. Moreover, surgeons will judge the user-friendliness of the software and time efficiency of the proposed approach in combination with a state-of-the- art algorithm for the segmentation of fractured bones in CT images. The duration of the proposed project will be 12 months. It will be carried out in close cooperation with the Surgical Planning Lab (Brigham and Women`s Hospital, Boston), the Minerva Research Group (Georgia Institute of Technology, Atlanta) and the Computer Vision Lab (ETH Zürich).