Publications

PelVis: Atlas-based Surgical Planning for Oncological Pelvic Surgery

N. Smit, K. Lawonn, A. Kraima, M. DeRuiter, H. Sokooti, S. Bruckner, E. Eisemann, and A. Vilanova

Abstract

Due to the intricate relationship between the pelvic organs and vital structures, such as vessels and nerves, pelvic anatomy is often considered to be complex to comprehend. In oncological pelvic surgery, a trade-off has to be made between complete tumor resection and preserving function by preventing damage to the nerves. Damage to the autonomic nerves causes undesirable post-operative side-effects such as fecal and urinal incontinence, as well as sexual dysfunction in up to 80 percent of the cases. Since these autonomic nerves are not visible in pre-operative MRI scans or during surgery, avoiding nerve damage during such a surgical procedure becomes challenging. In this work, we present visualization methods to represent context, target, and risk structures for surgical planning. We employ distance-based and occlusion management techniques in an atlas-based surgical planning tool for oncological pelvic surgery. Patient-specific pre-operative MRI scans are registered to an atlas model that includes nerve information. Through several interactive linked views, the spatial relationships and distances between the organs, tumor and risk zones are visualized to improve understanding, while avoiding occlusion. In this way, the surgeon can examine surgically relevant structures and plan the procedure before going into the operating theater, thus raising awareness of the autonomic nerve zone regions and potentially reducing post-operative complications. Furthermore, we present the results of a domain expert evaluation with surgical oncologists that demonstrates the advantages of our approach.

N. Smit, K. Lawonn, A. Kraima, M. DeRuiter, H. Sokooti, S. Bruckner, E. Eisemann, and A. Vilanova, "PelVis: Atlas-based Surgical Planning for Oncological Pelvic Surgery," IEEE Transactions on Visualization and Computer Graphics, vol. 23, iss. 1, p. 741–750, 2017. doi:10.1109/TVCG.2016.2598826
[BibTeX]

Due to the intricate relationship between the pelvic organs and vital structures, such as vessels and nerves, pelvic anatomy is often considered to be complex to comprehend. In oncological pelvic surgery, a trade-off has to be made between complete tumor resection and preserving function by preventing damage to the nerves. Damage to the autonomic nerves causes undesirable post-operative side-effects such as fecal and urinal incontinence, as well as sexual dysfunction in up to 80 percent of the cases. Since these autonomic nerves are not visible in pre-operative MRI scans or during surgery, avoiding nerve damage during such a surgical procedure becomes challenging. In this work, we present visualization methods to represent context, target, and risk structures for surgical planning. We employ distance-based and occlusion management techniques in an atlas-based surgical planning tool for oncological pelvic surgery. Patient-specific pre-operative MRI scans are registered to an atlas model that includes nerve information. Through several interactive linked views, the spatial relationships and distances between the organs, tumor and risk zones are visualized to improve understanding, while avoiding occlusion. In this way, the surgeon can examine surgically relevant structures and plan the procedure before going into the operating theater, thus raising awareness of the autonomic nerve zone regions and potentially reducing post-operative complications. Furthermore, we present the results of a domain expert evaluation with surgical oncologists that demonstrates the advantages of our approach.
@ARTICLE {Smit-2017-PAS,
author = "Noeska Smit and Kai Lawonn and Annelot Kraima and Marco DeRuiter and Hessam Sokooti and Stefan Bruckner and Elmar Eisemann and Anna Vilanova",
title = "PelVis: Atlas-based Surgical Planning for Oncological Pelvic Surgery",
journal = "IEEE Transactions on Visualization and Computer Graphics",
year = "2017",
volume = "23",
number = "1",
pages = "741--750",
month = "jan",
abstract = "Due to the intricate relationship between the pelvic organs and vital  structures, such as vessels and nerves, pelvic anatomy is often considered  to be complex to comprehend. In oncological pelvic surgery, a trade-off  has to be made between complete tumor resection and preserving function  by preventing damage to the nerves. Damage to the autonomic nerves  causes undesirable post-operative side-effects such as fecal and  urinal incontinence, as well as sexual dysfunction in up to 80 percent  of the cases. Since these autonomic nerves are not visible in pre-operative  MRI scans or during surgery, avoiding nerve damage during such a  surgical procedure becomes challenging. In this work, we present  visualization methods to represent context, target, and risk structures  for surgical planning. We employ distance-based and occlusion management  techniques in an atlas-based surgical planning tool for oncological  pelvic surgery. Patient-specific pre-operative MRI scans are registered  to an atlas model that includes nerve information. Through several  interactive linked views, the spatial relationships and distances  between the organs, tumor and risk zones are visualized to improve  understanding, while avoiding occlusion. In this way, the surgeon  can examine surgically relevant structures and plan the procedure  before going into the operating theater, thus raising awareness of  the autonomic nerve zone regions and potentially reducing post-operative  complications. Furthermore, we present the results of a domain expert  evaluation with surgical oncologists that demonstrates the advantages  of our approach.",
pdf = "pdfs/Smit-2017-PAS.pdf",
images = "images/Smit-2017-PAS.jpg",
thumbnails = "images/Smit-2017-PAS.png",
youtube = "https://www.youtube.com/watch?v=vHp05I5-hp8",
doi = "10.1109/TVCG.2016.2598826",
event = "IEEE SciVis 2016",
keywords = "atlas, surgical planning, medical visualization",
location = "Baltimore, USA"
}
projectidprojectid

Media

Downloads

Full paper [PDF]