Evaluation of a novel navigation platform for laparoscopic liver surgery with organ deformation compensation using injected fiducials
| Autor: | Tobias Rudolph, Amilcar Alzaga, Benjamin Eigl, Rahul Prasanna Kumar, Davit L. Aghayan, Ole Jakob Elle, Egidijus Pelanis, Carina Riediger, Niclas Kvarnström, Bjørn Edwin, Andrea Teatini, Alois Regensburger |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Liver surgery
medicine.medical_specialty Computer science Swine Health Informatics 030218 nuclear medicine & medical imaging Compensation (engineering) 03 medical and health sciences 0302 clinical medicine Imaging Three-Dimensional medicine Animals Radiology Nuclear Medicine and imaging Augmented Reality Radiological and Ultrasound Technology Navigation system Computer Graphics and Computer-Aided Design Visualization Image-guided surgery Liver Surgery Computer-Assisted Resection margin Augmented reality Laparoscopy Computer Vision and Pattern Recognition Radiology Fiducial marker 030217 neurology & neurosurgery |
| Zdroj: | Pelanis, Egidijus; Teatini, Andrea; Eigl, Benjamin Peter; Regensburger, Alois; Alzaga, Amilcar; Kumar, Rahul Prasanna; Rudolph, Tobias; Aghayan, Davit L.; Riediger, Carina; Kvarnström, Niclas; Elle, Ole Jakob; Edwin, Bjørn (2021). Evaluation of a novel navigation platform for laparoscopic liver surgery with organ deformation compensation using injected fiducials. Medical image analysis, 69, p. 101946. Elsevier 10.1016/j.media.2020.101946 Medical Image Analysis |
| DOI: | 10.1016/j.media.2020.101946 |
| Popis: | In laparoscopic liver resection, surgeons conventionally rely on anatomical landmarks detected through a laparoscope, preoperative volumetric images and laparoscopic ultrasound to compensate for the challenges of minimally invasive access. Image guidance using optical tracking and registration procedures is a promising tool, although often undermined by its inaccuracy. This study evaluates a novel surgical navigation solution that can compensate for liver deformations using an accurate and effective registration method. The proposed solution relies on a robotic C-arm to perform registration to preoperative CT/MRI image data and allows for intraoperative updates during resection using fluoroscopic images. Navigation is offered both as a 3D liver model with real-time instrument visualization, as well as an augmented reality overlay on the laparoscope camera view. Testing was conducted through a pre-clinical trial which included four porcine models. Accuracy of the navigation system was measured through two evaluation methods: liver surface fiducials reprojection and a comparison between planned and navigated resection margins. Target Registration Error with the fiducials evaluation shows that the accuracy in the vicinity of the lesion was 3.78 ± 1.89 mm. Resection margin evaluations resulted in an overall median accuracy of 4.44 mm with a maximum error of 9.75 mm over the four subjects. The presented solution is accurate enough to be potentially clinically beneficial for surgical guidance in laparoscopic liver surgery. |
| Databáze: | OpenAIRE |
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