title: Acquisition models in intraoperative positron surface imaging.
abstract: OBJECTIVE
  Intraoperative imaging aims at identifying residual tumor during surgery. Positron Surface Imaging (PSI) is one of the solutions to help surgeons in a better detection of resection margins of brain tumor, leading to an improved patient outcome. This system relies on a tracked freehand beta probe, using [Formula: see text]F-based radiotracer. Some acquisition models have been proposed in the literature in order to enhance image quality, but no comparative validation study has been performed for PSI.
  
  
  METHODS
  In this study, we investigated the performance of different acquisition models by considering validation criteria and normalized metrics. We proposed a reference-based validation framework to perform the comparative study between acquisition models and a basic method. We estimated the performance of several acquisition models in light of four validation criteria: efficiency, computational speed, spatial accuracy and tumor contrast.
  
  
  RESULTS
  Selected acquisition models outperformed the basic method, albeit with the real-time aspect compromised. One acquisition model yielded the best performance among all according to the validation criteria: efficiency (1-Spe: 0.1, Se: 0.94), spatial accuracy (max Dice: 0.77) and tumor contrast (max T/B: 5.2). We also found out that above a minimum threshold value of the sampling rate, the reconstruction quality does not vary significantly.
  
  
  CONCLUSIONS
  Our method allowed the comparison of different acquisition models and highlighted one of them according to our validation criteria. This novel approach can be extended to 3D datasets, for validation of future acquisition models dedicated to intraoperative guidance of brain surgery.
authors.affiliation: LTSI INSERM, UMR 1099, Campus de Villejean, Université de Rennes 1, 2, Avenue du Pr. Léon Bernard, 35043, Rennes Cedex, France. frederic.monge@univ-rennes1.fr.
authors.forename: Frédéric
authors.initials: F
authors.lastname: Monge
authors.affiliation: Translational Imaging Group/CMIC, University College London, London, UK.
authors.forename: Dzhoshkun I
authors.initials: DI
authors.lastname: Shakir
authors.affiliation: Centre Eugène Marquis, Rennes, 35000, France.
authors.forename: Florence
authors.initials: F
authors.lastname: Lejeune
authors.affiliation: LTSI INSERM, UMR 1099, Campus de Villejean, Université de Rennes 1, 2, Avenue du Pr. Léon Bernard, 35043, Rennes Cedex, France.|CHU Rennes, Service de Neurochirurgie, Rennes, 35000, France.
authors.forename: Xavier
authors.initials: X
authors.lastname: Morandi
authors.affiliation: CAMP, Technische Universität München, Munich, Germany.
authors.forename: Nassir
authors.initials: N
authors.lastname: Navab
authors.affiliation: LTSI INSERM, UMR 1099, Campus de Villejean, Université de Rennes 1, 2, Avenue du Pr. Léon Bernard, 35043, Rennes Cedex, France.
authors.forename: Pierre
authors.initials: P
authors.lastname: Jannin
mesh_terms: D001921:Brain / Q000000981:diagnostic imaging* / Q000601:surgery; D001932:Brain Neoplasms / Q000000981:diagnostic imaging* / Q000601:surgery; D006801:Humans; D008866:Microsurgery; D008962:Models, Theoretical; D049268:Positron-Emission Tomography / Q000379:methods*
keywords: Freehand beta probe; Functional imaging; Intraoperative imaging; Neuronavigation; Radiation detection physics; Reconstruction; Validation assessment