Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2007. / Includes bibliographical references (leaves 152-157). / There is a pressing need in minimally-invasive surgery for novel imaging methods that can rapidly and accurately localize the surgical instrument and its target. We have developed two novel localization methods for the guidance of cardiac ablation and other minimally-invasive therapies. The first method, the Inverse Solution Guidance Algorithm (ISGA), is for the non-invasive and rapid localization of the site of origin of an arrhythmia and an ablation catheter tip from body-surface ECG signals. We have substantially developed ISGA to provide accurate catheter guidance even in the presence of significant electrical inhomogeneities, and we have evaluated the method in numerical simulations and phantom studies. Due to the rapidity of arrhythmic origin localization, ISGA may prove a highly effective means of guiding the ablative therapy of hemodynamically-unstable VT. The second method, the Bioelectrical Image Guidance (BIG) Method, is a novel algorithm for the accurate and inexpensive guidance of a wide-range of minimally-invasive surgeries, from cardiac ablation to breast cancer biopsy. / (cont.) The surgical instrument is localized within a detailed 3-D MRI or CT image by applying currents to the body surface and comparing the potentials measured at the instrument tip with potential distributions simulated prior to the surgery. We have developed and evaluated this method in numerical simulations. We have also built an experimental guidance system and tested it in a phantom model. Our results indicate that the BIG Method may one day provide an accurate and convenient means by which to guide minimally-invasive surgery within a highly detailed anatomical image. / by Maya E. Barley. / Ph.D.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/39571 |
| Date | January 2007 |
| Creators | Barley, Maya |
| Contributors | Richard J. Cohen., Harvard University--MIT Division of Health Sciences and Technology., Harvard University--MIT Division of Health Sciences and Technology. |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 157 leaves, application/pdf |
| Rights | M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission., http://dspace.mit.edu/handle/1721.1/39571, http://dspace.mit.edu/handle/1721.1/7582 |
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