Characterization and Correction of Intraoperative Soft Tissue Deformation in Image-Guided Laparoscopic Liver Surgery
Laparoscopic liver surgery is challenging to perform due to a compromised ability of the surgeon to localize subsurface anatomy in the constrained environment. While image guidance has the potential to address this barrier, intraoperative factors such as insufflation and variable degrees of organ mo...
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ndltd-VANDERBILT-oai-VANDERBILTETD-etd-11142017-1221512017-11-28T05:35:05Z Characterization and Correction of Intraoperative Soft Tissue Deformation in Image-Guided Laparoscopic Liver Surgery Heiselman, Jon Stanley Biomedical Engineering Laparoscopic liver surgery is challenging to perform due to a compromised ability of the surgeon to localize subsurface anatomy in the constrained environment. While image guidance has the potential to address this barrier, intraoperative factors such as insufflation and variable degrees of organ mobilization from supporting ligaments may generate substantial deformation. The severity of laparoscopic deformation in humans has not been characterized, and current laparoscopic correction methods do not account for the mechanics of how intraoperative deformation is applied to the liver. In this work, we first measure the degree of laparoscopic deformation at two insufflation pressures over the course of laparoscopic-to-open conversion in 25 patients. With this clinical data alongside a mock laparoscopic phantom setup, we report a novel biomechanical correction approach that leverages anatomically load-bearing support surfaces including ligament attachments to iteratively reconstruct and account for intraoperative deformations. Laparoscopic deformations were significantly larger than deformations associated with open surgery, and our correction approach yielded subsurface target error of 6.7±1.3 mm and surface error of 0.8±0.4 mm using only sparse surface data with realistic surgical extent. Laparoscopic surface data extents were examined and found to impact registration accuracy. Lastly, we demonstrate viability of the correction method with clinical data. Benoit M. Dawant Michael I. Miga VANDERBILT 2017-11-27 text application/pdf http://etd.library.vanderbilt.edu/available/etd-11142017-122151/ http://etd.library.vanderbilt.edu/available/etd-11142017-122151/ en restricted I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Vanderbilt University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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en |
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Others
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Biomedical Engineering |
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Biomedical Engineering Heiselman, Jon Stanley Characterization and Correction of Intraoperative Soft Tissue Deformation in Image-Guided Laparoscopic Liver Surgery |
description |
Laparoscopic liver surgery is challenging to perform due to a compromised ability of the surgeon to localize subsurface anatomy in the constrained environment. While image guidance has the potential to address this barrier, intraoperative factors such as insufflation and variable degrees of organ mobilization from supporting ligaments may generate substantial deformation. The severity of laparoscopic deformation in humans has not been characterized, and current laparoscopic correction methods do not account for the mechanics of how intraoperative deformation is applied to the liver. In this work, we first measure the degree of laparoscopic deformation at two insufflation pressures over the course of laparoscopic-to-open conversion in 25 patients. With this clinical data alongside a mock laparoscopic phantom setup, we report a novel biomechanical correction approach that leverages anatomically load-bearing support surfaces including ligament attachments to iteratively reconstruct and account for intraoperative deformations. Laparoscopic deformations were significantly larger than deformations associated with open surgery, and our correction approach yielded subsurface target error of 6.7±1.3 mm and surface error of 0.8±0.4 mm using only sparse surface data with realistic surgical extent. Laparoscopic surface data extents were examined and found to impact registration accuracy. Lastly, we demonstrate viability of the correction method with clinical data. |
author2 |
Benoit M. Dawant |
author_facet |
Benoit M. Dawant Heiselman, Jon Stanley |
author |
Heiselman, Jon Stanley |
author_sort |
Heiselman, Jon Stanley |
title |
Characterization and Correction of Intraoperative Soft Tissue Deformation in Image-Guided Laparoscopic Liver Surgery |
title_short |
Characterization and Correction of Intraoperative Soft Tissue Deformation in Image-Guided Laparoscopic Liver Surgery |
title_full |
Characterization and Correction of Intraoperative Soft Tissue Deformation in Image-Guided Laparoscopic Liver Surgery |
title_fullStr |
Characterization and Correction of Intraoperative Soft Tissue Deformation in Image-Guided Laparoscopic Liver Surgery |
title_full_unstemmed |
Characterization and Correction of Intraoperative Soft Tissue Deformation in Image-Guided Laparoscopic Liver Surgery |
title_sort |
characterization and correction of intraoperative soft tissue deformation in image-guided laparoscopic liver surgery |
publisher |
VANDERBILT |
publishDate |
2017 |
url |
http://etd.library.vanderbilt.edu/available/etd-11142017-122151/ |
work_keys_str_mv |
AT heiselmanjonstanley characterizationandcorrectionofintraoperativesofttissuedeformationinimageguidedlaparoscopicliversurgery |
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1718563102467817472 |