
Proceedings Paper
A multimodal imaging framework for enhanced robot-assisted partial nephrectomy guidanceFormat | Member Price | Non-Member Price |
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Paper Abstract
Robot-assisted laparoscopic partial nephrectomies (RALPN) are performed to treat patients with locally confined renal carcinoma. There are well-documented benefits to performing partial (opposed to radical) kidney resections and to using robot-assisted laparoscopic (opposed to open) approaches. However, there are challenges in identifying tumor margins and critical benign structures including blood vessels and collecting systems during current RALPN procedures. The primary objective of this effort is to couple multiple image and data streams together to augment visual information currently provided to surgeons performing RALPN and ultimately ensure complete tumor resection and minimal damage to functional structures (i.e. renal vasculature and collecting systems). To meet this challenge we have developed a framework and performed initial feasibility experiments to couple pre-operative high-resolution anatomic images with intraoperative MRI, ultrasound (US) and optical-based surface mapping and kidney tracking. With these registered images and data streams, we aim to overlay the high-resolution contrast-enhanced anatomic (CT or MR) images onto the surgeon’s view screen for enhanced guidance. To date we have integrated the following components of our framework: 1) a method for tracking an intraoperative US probe to extract the kidney surface and a set of embedded kidney markers, 2) a method for co-registering intraoperative US scans with pre-operative MR scans, and 3) a method for deforming pre-op scans to match intraoperative scans. These components have been evaluated through phantom studies to demonstrate protocol feasibility.
Paper Details
Date Published: 18 March 2015
PDF: 6 pages
Proc. SPIE 9415, Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling, 94151E (18 March 2015); doi: 10.1117/12.2082775
Published in SPIE Proceedings Vol. 9415:
Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster III; Ziv R. Yaniv, Editor(s)
PDF: 6 pages
Proc. SPIE 9415, Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling, 94151E (18 March 2015); doi: 10.1117/12.2082775
Show Author Affiliations
Ryan J. Halter, Thayer School of Engineering at Dartmouth (United States)
Geisel School of Medicine, Dartmouth College (United States)
Xiaotian Wu, Thayer School of Engineering at Dartmouth (United States)
Alex Hartov, Thayer School of Engineering at Dartmouth (United States)
Geisel School of Medicine, Dartmouth College (United States)
Xiaotian Wu, Thayer School of Engineering at Dartmouth (United States)
Alex Hartov, Thayer School of Engineering at Dartmouth (United States)
John Seigne, Geisel School of Medicine, Dartmouth College (United States)
Dartmouth-Hitchcock Medical Ctr. (United States)
Shadab Khan, Thayer School of Engineering at Dartmouth (United States)
Dartmouth-Hitchcock Medical Ctr. (United States)
Shadab Khan, Thayer School of Engineering at Dartmouth (United States)
Published in SPIE Proceedings Vol. 9415:
Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster III; Ziv R. Yaniv, Editor(s)
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