title: [Virtual surgical planning in liver surgery].
abstract: The operability of a liver tumour depends on its three-dimensional relation to the intrahepatic vascular trees which define autonomously functioning liver (sub-)segments. The aim of our study was to establish a computer-based three-dimensional volumetric operation planning system for the liver.
  
  
  METHODS
  Using data from routine helical CT scans the three tissue subclasses of liver parenchyma, liver vessels and liver tumour were segmented semiautomatically. A dedicated segmenting tool was established using region growing algorithms in combination with an "intelligent" border finder. Visualisation is performed by the "Heidelberg Raytracer". The vascular trees are visualised as 3D graphs. Pseudoconnections between portal and hepatic venous trees are separated automatically. Security margins are calculated and the system presents a virtual resection proposal.
  
  
  RESULTS
  The 3D anatomy of the liver can be visualised in high quality resulting in good depth perception. Security margins are demonstrated. Dependent liver parenchyma can be recognized automatically on the basis of the vascular trees. The system offers a individualised resection proposal including the tumour, security margin and dependent liver parenchyma.
  
  
  CONCLUSIONS
  Three-dimensional presentation of the individual liver anatomy of a given patient facilitates the perception of the pathology. Virtual reality combined with artificial intelligence allows calculation of complete resection protocols, which can be quantified and modified interactively. This will make operation planning more objective; patient selection may be improved, and in cases of difficult tumour localisation different resection strategies may be tested. Thus virtual reality in liver surgery will improve teaching, surgical training and planning. It may lead to improved surgical care.
authors.affiliation: Chirurgische Klinik und Poliklinik, Universität Heidelberg. J79@ix.urz.uni-heidelberg.de
authors.forename: W
authors.initials: W
authors.lastname: Lamadé
authors.forename: G
authors.initials: G
authors.lastname: Glombitza
authors.forename: A M
authors.initials: AM
authors.lastname: Demiris
authors.forename: C
authors.initials: C
authors.lastname: Cardenas
authors.forename: H P
authors.initials: HP
authors.lastname: Meinzer
authors.forename: G
authors.initials: G
authors.lastname: Richter
authors.forename: T
authors.initials: T
authors.lastname: Lehnert
authors.forename: C
authors.initials: C
authors.lastname: Herfarth
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D005103:Expert Systems; D006498:Hepatectomy / Q000295:instrumentation*; D006499:Hepatic Artery / Q000601:surgery; D006503:Hepatic Veins / Q000601:surgery; D006801:Humans; D008113:Liver Neoplasms / Q000098:blood supply / Q000601:surgery*; D010347:Patient Care Planning; D012680:Sensitivity and Specificity; D012984:Software; D014057:Tomography, X-Ray Computed / Q000295:instrumentation*; D014584:User-Computer Interface