CARE 2016: Computer-Assisted and Robotic Endoscopy pp 114-126 | Cite as
A System for Augmented Reality Guided Laparoscopic Tumour Resection with Quantitative Ex-vivo User Evaluation
Abstract
Augmented Reality (AR) guidance systems are currently being developed to help laparoscopic surgeons locate hidden structures such as tumours and major vessels. This can be achieved by registering pre-operative 3D data such as CT or MRI with the laparoscope’s live video. For soft organs this is very challenging, and quantitative evaluation is both difficult and limited in the literature. It has been done previously by measuring registration accuracy using retrospective (non-live) data. However a performance evaluation of a real-time system in live use has not been presented. The clinical benefit has therefore not been measured. We describe an AR guidance system based on an existing one with several important improvements, that has been evaluated in an ex-vivo pre-clinical study for guiding tumour resections with porcine kidneys. The main improvement is a considerably better way to visually guide the surgeon, by showing them how to access the tumour with an incision tool. We call this Tool Access Visualisation. Performance was measured with the negative margin rate across 59 resected pseudo-tumours. This was 85.2% with AR guidance and 41.9% without, showing a very significant improvement (\(p=0.0010\), two-tailed Fisher’s exact test).
Keywords
Point Cloud Augmented Reality Iterative Close Point Porcine Kidney Initial RegistrationNotes
Acknowledgements
This research was funded by the EU FP7 ERC research grant 307483 FLEXABLE and Almerys Corporation.
References
- 1.Agisoft photoscan. http://www.agisoft.com. Accessed 07 Feb 2016
- 2.Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-up robust features (SURF). Comput. Vis. Image Underst. 110(3), 346–359 (2008)CrossRefGoogle Scholar
- 3.Collins, T., Pizarro, D., Bartoli, A., Canis, M., Bourdel, N.: Realtime wide-baseline registration of the uterus in laparoscopic videos using multiple texture maps. In: Liao, H., Linte, C.A., Masamune, K., Peters, T.M., Zheng, G. (eds.) AE-CAI/MIAR -2013. LNCS, vol. 8090, pp. 162–171. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-40843-4_18 CrossRefGoogle Scholar
- 4.Collins, T., Pizarro, D., Bartoli, A., Canis, M., Bourdel, N.: Computer-assisted laparoscopic myomectomy by augmenting the uterus with pre-operative MRI data. In: ISMAR (2014)Google Scholar
- 5.Egorov, V., Tsyuryupa, S., Kanilo, S., Kogit, M., Sarvazyan, A.: Soft tissue elastometer. Med. Eng. Phys. 30, 206–212 (2008)CrossRefGoogle Scholar
- 6.Haouchine, N., Dequidt, J., Berger, M.-O., Cotin, S.: Monocular 3D reconstruction and augmentation of elastic surfaces with self-occlusion handling. Trans. Vis. Comput. Graph., 14 (2015)Google Scholar
- 7.Haouchine, N., Dequidt, J., Peterlik, I., Kerrien, E., Berger, M.-O., Cotin, S.: Image-guided simulation of heterogeneous tissue deformation for augmented reality during hepatic surgery. In: ISMAR (2013)Google Scholar
- 8.Mortensen, E.N., Barrett, W.A.: Intelligent scissors for image composition. In: SIGGRAPH, pp. 191–198 (1995)Google Scholar
- 9.Nosrati, M.S., Peyrat, J.-M., Abinahed, J., Al-Alao, O., Al-Ansari, A., Abugharbieh, R., Hamarneh, G.: Simultaneous multi-structure segmentation and 3D non-rigid pose estimation in image guided robotic surgery. Trans. Med. Imaging 35(1), 1–12 (2016)CrossRefGoogle Scholar
- 10.Pearsall, G., Roberts, V.: Passive mechanical properties of uterine muscle (myometrium) tested in vitro. J. Biomech. 4(11), 167–176 (1978)CrossRefGoogle Scholar
- 11.Plantefève, R., Peterlik, I., Haouchine, N., Cotin, S.: Patient-specific biomechanical modeling for guidance during minimally-invasive hepatic surgery. Ann. Biomed. Eng. (2015)Google Scholar
- 12.Puerto-Souza, G., Cadeddu, J.A., Mariottini, G.: Toward long-term and accurate AR for monocular endoscopic videos. Biomed. Eng. (2014)Google Scholar
- 13.Su, L.-M., Vagvolgyi, B.P., Agarwal, R., Reiley, C.E., Taylor, R.H., Hager, G.D.: Augmented reality during robot-assisted laparoscopic partial nephrectomy: toward real-time 3D-CT to stereoscopic video registration. Urology 73, 896–900 (2009)CrossRefGoogle Scholar
- 14.Wolf, I., Vetter, M., Wegner, I., Nolden, M., Böttger, T., Hastenteufel, M., Schöbinger, M., Kunert, T., Meinzer, H.-P.: The medical imaging interaction toolkit (MITK). http://www.mitk.org/