Ultrasound-based Registration for the Computer-assisted Navigated Percutaneous Scaphoid Fixation.

An ultrasound-based computer-assisted approach has the potential to improve the accuracy and precision of screw placement for the percutaneous fixation of scaphoid fractures, and also reduce the radiation dose for patient and clinical staff. Therefore, a surgical plan based on preoperative diagnostic computed tomography is registered with intraoperative ultrasound images, enabling a navigated percutaneous fracture fixation. However, approaches published so far rely on semi-manual methods for intraoperative registration and are limited by long computation times. To address these challenges, we propose the employment of deep learning-based methods for ultrasound segmentation and registration in order to achieve a fast and fully automated yet robust registration process. For validation of the proposed ultrasound-based approach, we first provide a comparison of methods for segmentation and registration, assess their contribution to the overall error throughout our pipeline and, finally, evaluate navigated screw placement in an in vitro study on three-dimensional printed carpal phantoms. Successful screw placement has been achieved for all 10 screws, with deviations from the planned axis of 1.0 ± 0.6 and 0.7 ± 0.3 mm at the distal and proximal pole, respectively. The complete automation and total duration of about 12 seconds also allow a seamless integration of our approach into the surgical workflow.