PelVis: Atlas-based Surgical Planning for Oncological Pelvic Surgery

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 { SLKDSBEV17,
  author       = "Smit, Noeska Natasja and Lawonn, Kai and Kraima, Anne C. and Deruiter, Marco C. and Sokooti, Hessam and
                  Bruckner, Stefan and Eisemann, Elmar and Vilanova, Anna",
  title        = "PelVis: Atlas-based Surgical Planning for Oncological Pelvic Surgery",
  journal      = "IEEE Transactions on Visualization and Computer Graphics (Proceedings of Scientific Visualization 2016)",
  number       = "01",
  volume       = "23",
  pages        = "741--750",
  year         = "2017",
  url          = "http://graphics.tudelft.nl/Publications-new/2017/SLKDSBEV17"
}