title: Statistical study of parameters for deep brain stimulation automatic preoperative planning of electrodes trajectories.
abstract: OBJECTIVE
  Automatic methods for preoperative trajectory planning of electrodes in deep brain stimulation are usually based on the search for a path that resolves a set of surgical constraints to propose an optimal trajectory. The relative importance of each surgical constraint is usually defined as weighting parameters that are empirically set beforehand. The objective of this paper is to analyze the use of these parameters thanks to a retrospective study of trajectories manually planned by neurosurgeons. For that purpose, we firstly retrieved weighting factors allowing to match neurosurgeons manually planned choice of trajectory on each retrospective case; secondly, we compared the results from two different hospitals to evaluate their similarity; and thirdly, we compared the trends to the weighting factors empirically set in most current approaches.
  
  
  METHODS
  To retrieve the weighting factors best matching the neurosurgeons manual plannings, we proposed two approaches: one based on a stochastic sampling of the parameters and the other on an exhaustive search. In each case, we obtained a sample of combinations of weighting parameters with a measure of their quality, i.e., the similarity between the automatic trajectory they lead to and the one manually planned by the surgeon as a reference. Visual and statistical analyses were performed on the number of occurrences and on the rank means.
  
  
  RESULTS
  We performed our study on 56 retrospective cases from two different hospitals. We could observe a trend of the occurrence of each weight on the number of occurrences. We also proved that each weight had a significant influence on the ranking. Additionally, we observed no influence of the medical center parameters, suggesting that the trends were comparable in both hospitals. Finally, the obtained trends were confronted to the usual weights chosen by the community, showing some common points but also some discrepancies.
  
  
  CONCLUSIONS
  The results tend to show a predominance of the choice of a trajectory close to a standard direction. Secondly, the avoidance of the vessels or sulci seems to be sought in the surroundings of the standard position. The avoidance of the ventricles seems to be less predominant, but this could be due to the already reasonable distance between the standard direction and the ventricles. The similarity of results between two medical centers tends to show that it is not an exceptional practice. These results suggest that manual planning software may introduce a bias in the planning by proposing a standard position.
authors.affiliation: ICube, Université de Strasbourg/CNRS (UMR 7357), 300 bd Sébastien Brant, BP 10413, 67412, Illkirch, France. essert@unistra.fr.
authors.forename: Caroline
authors.initials: C
authors.lastname: Essert
authors.affiliation: ICM CENIR, CNRS (UMR 7225)/INSERM (U975)/UPMC/Hôpital Pitié-Salpêtrière, 47 boulevard de l'Hôpital, 75013, Paris, France.
authors.forename: Sara
authors.initials: S
authors.lastname: Fernandez-Vidal
authors.affiliation: ICube, Université de Strasbourg/CNRS (UMR 7357), 300 bd Sébastien Brant, BP 10413, 67412, Illkirch, France.
authors.forename: Antonio
authors.initials: A
authors.lastname: Capobianco
authors.affiliation: LTSI, INSERM (UMR 1099)/Université Rennes 1, CS34317, 35043, Rennes, France.|Department of Neurosurgery, Rennes University Hospital, 35000, Rennes, France.
authors.forename: Claire
authors.initials: C
authors.lastname: Haegelen
authors.affiliation: Department of Neurosurgery, Sorbonne Universités, UPMC Université Paris 6, INSERM, CNRS, INRIA, ICM AP-HP, Hôpital Pitié-Salpêtrière, 47 boulevard de l'Hôpital, 75013, Paris, France.
authors.forename: Carine
authors.initials: C
authors.lastname: Karachi
authors.affiliation: ICM CENIR, CNRS (UMR 7225)/INSERM (U975)/UPMC/Hôpital Pitié-Salpêtrière, 47 boulevard de l'Hôpital, 75013, Paris, France.
authors.forename: Eric
authors.initials: E
authors.lastname: Bardinet
authors.affiliation: INRIA Rennes Bretagne-Atlantique/IRISA/INSA Rennes, France, Campus de Beaulieu, 35042, Rennes Cedex, France.
authors.forename: Maud
authors.initials: M
authors.lastname: Marchal
authors.affiliation: LTSI, INSERM (UMR 1099)/Université Rennes 1, CS34317, 35043, Rennes, France.
authors.forename: Pierre
authors.initials: P
authors.lastname: Jannin
mesh_terms: D001927:Brain Diseases / Q000601:surgery*; D046690:Deep Brain Stimulation / Q000379:methods*; D004567:Electrodes, Implanted; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging; D038361:Neuronavigation / Q000379:methods; D057234:Preoperative Period; D012189:Retrospective Studies; D012984:Software; D025321:Surgery, Computer-Assisted / Q000379:methods*
keywords: Deep brain stimulation; Neurosurgery; Statistical analysis; Surgical planning; Trajectory optimization