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Proceedings Paper

Generating patient-specific pulmonary vascular models for surgical planning
Author(s): Daniel Murff; Jennifer Co-Vu; Walter G. O'Dell
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Paper Abstract

Each year in the U.S., 7.4 million surgical procedures involving the major vessels are performed. Many of our patients require multiple surgeries, and many of the procedures include “surgical exploration”. Procedures of this kind come with a significant amount of risk, carrying up to a 17.4% predicted mortality rate. This is especially concerning for our target population of pediatric patients with congenital abnormalities of the heart and major pulmonary vessels. This paper offers a novel approach to surgical planning which includes studying virtual and physical models of pulmonary vasculature of an individual patient before operation obtained from conventional 3D X-ray computed tomography (CT) scans of the chest. These models would provide clinicians with a non-invasive, intricately detailed representation of patient anatomy, and could reduce the need for invasive planning procedures such as exploratory surgery. Researchers involved in the AirPROM project have already demonstrated the utility of virtual and physical models in treatment planning of the airways of the chest. Clinicians have acknowledged the potential benefit from such a technology. A method for creating patient-derived physical models is demonstrated on pulmonary vasculature extracted from a CT scan with contrast of an adult human. Using a modified version of the NIH ImageJ program, a series of image processing functions are used to extract and mathematically reconstruct the vasculature tree structures of interest. An auto-generated STL file is sent to a 3D printer to create a physical model of the major pulmonary vasculature generated from 3D CT scans of patients.

Paper Details

Date Published: 18 March 2015
PDF: 8 pages
Proc. SPIE 9415, Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling, 94150O (18 March 2015); doi: 10.1117/12.2082647
Show Author Affiliations
Daniel Murff, Univ. of Florida (United States)
Jennifer Co-Vu, Univ. of Florida (United States)
Walter G. O'Dell, Univ. of Florida (United States)


Published in SPIE Proceedings Vol. 9415:
Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster; Ziv R. Yaniv, Editor(s)

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