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Proceedings Paper

A 3D-elastography-guided system for laparoscopic partial nephrectomies
Author(s): Philipp J. Stolka; Matthias Keil; Georgios Sakas; Elliot McVeigh; Mohamad E. Allaf; Russell H. Taylor; Emad M. Boctor
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Paper Abstract

We present an image-guided intervention system based on tracked 3D elasticity imaging (EI) to provide a novel interventional modality for registration with pre-operative CT. The system can be integrated in both laparoscopic and robotic partial nephrectomies scenarios, where this new use of EI makes exact intra-operative execution of pre-operative planning possible. Quick acquisition and registration of 3D-B-Mode and 3D-EI volume data allows intra-operative registration with CT and thus with pre-defined target and critical regions (e.g. tumors and vasculature). Their real-time location information is then overlaid onto a tracked endoscopic video stream to help the surgeon avoid vessel damage and still completely resect tumors including safety boundaries. The presented system promises to increase the success rate for partial nephrectomies and potentially for a wide range of other laparoscopic and robotic soft tissue interventions. This is enabled by the three components of robust real-time elastography, fast 3D-EI/CT registration, and intra-operative tracking. With high quality, robust strain imaging (through a combination of parallelized 2D-EI, optimal frame pair selection, and optimized palpation motions), kidney tumors that were previously unregistrable or sometimes even considered isoechoic with conventional B-mode ultrasound can now be imaged reliably in interventional settings. Furthermore, this allows the transformation of planning CT data of kidney ROIs to the intra-operative setting with a markerless mutual-information-based registration, using EM sensors for intraoperative motion tracking. Overall, we present a complete procedure and its development, including new phantom models - both ex vivo and synthetic - to validate image-guided technology and training, tracked elasticity imaging, real-time EI frame selection, registration of CT with EI, and finally a real-time, distributed software architecture. Together, the system allows the surgeon to concentrate on intervention completion with less time pressure.

Paper Details

Date Published: 27 February 2010
PDF: 12 pages
Proc. SPIE 7625, Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling, 76251I (27 February 2010); doi: 10.1117/12.844589
Show Author Affiliations
Philipp J. Stolka, The Johns Hopkins Univ. (United States)
Matthias Keil, Fraunhofer-Institut für Graphische Datenverarbeitung (Germany)
Georgios Sakas, Fraunhofer-Institut für Graphische Datenverarbeitung (Germany)
Elliot McVeigh, The Johns Hopkins Univ. (United States)
Mohamad E. Allaf, Johns Hopkins Medical Institutions (United States)
Russell H. Taylor, The Johns Hopkins Univ. (United States)
Emad M. Boctor, Johns Hopkins Medical Institutions (United States)


Published in SPIE Proceedings Vol. 7625:
Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling
Kenneth H. Wong; Michael I. Miga, Editor(s)

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