18 March 2016 Image-guided navigation surgery for pelvic malignancies using electromagnetic tracking
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Abstract
The purpose of this study was to implement and evaluate a surgical navigation system for pelvic malignancies.

For tracking an NDI Aurora tabletop field generator and in-house developed navigation software were used. For patient tracking three EM-sensor stickers were used, one on the back and two on the superior iliac spines. During surgery a trackable pointer was used. One day before surgery a CT scan was acquired with the stickers in-place and marked. From the CT scan the EM-sensors, tumor and normal structures were segmented. During surgery, accuracy was independently checked by pointing at the aorta bifurcation and the common iliac artery bifurcations. Subsequently, the system was used to localize the ureters and the tumor.

Seven patients were included, three rectal tumors with lymph node-involvement, three lymph node recurrences, and one rectal recurrence. The average external marker registration accuracy was 0.75 cm RMSE (range 0.31-1.58 cm). The average distance between the pointer and the arterial bifurcations was 1.55 cm (1SD=0.63 cm). We were able to localize and confirm the location of all ureters. Twelve out of thirteen lymph nodes were localized and removed. All tumors were removed radically. In all cases the surgeons indicated that the system aided in better anatomical insight, and faster localization of malignant tissue and ureters. In 2/7 cases surgeons indicated that radical resection was only possible with navigation.

The navigation accuracy was limited due to the use of skin markers. Nevertheless, preliminary results indicated potential clinical benefit due to better utilization of pre-treatment 3D imaging information.
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Jasper Nijkamp, Jasper Nijkamp, Koert Kuhlmann, Koert Kuhlmann, Jan-Jakob Sonke, Jan-Jakob Sonke, Theo Ruers, Theo Ruers, "Image-guided navigation surgery for pelvic malignancies using electromagnetic tracking", Proc. SPIE 9786, Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling, 97862L (18 March 2016); doi: 10.1117/12.2216213; https://doi.org/10.1117/12.2216213
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