title: Evaluation of MRI and cannabinoid type 1 receptor PET templates constructed using DARTEL for spatial normalization of rat brains.
abstract: OBJECTIVE
  Image registration is one prerequisite for the analysis of brain regions in magnetic-resonance-imaging (MRI) or positron-emission-tomography (PET) studies. Diffeomorphic anatomical registration through exponentiated Lie algebra (DARTEL) is a nonlinear, diffeomorphic algorithm for image registration and construction of image templates. The goal of this small animal study was (1) the evaluation of a MRI and calculation of several cannabinoid type 1 (CB1) receptor PET templates constructed using DARTEL and (2) the analysis of the image registration accuracy of MR and PET images to their DARTEL templates with reference to analytical and iterative PET reconstruction algorithms.
  
  
  METHODS
  Five male Sprague Dawley rats were investigated for template construction using MRI and [(18)F]MK-9470 PET for CB1 receptor representation. PET images were reconstructed using the algorithms filtered back-projection, ordered subset expectation maximization in 2D, and maximum a posteriori in 3D. Landmarks were defined on each MR image, and templates were constructed under different settings, i.e., based on different tissue class images [gray matter (GM), white matter (WM), and GM + WM] and regularization forms ("linear elastic energy," "membrane energy," and "bending energy"). Registration accuracy for MRI and PET templates was evaluated by means of the distance between landmark coordinates.
  
  
  RESULTS
  The best MRI template was constructed based on gray and white matter images and the regularization form linear elastic energy. In this case, most distances between landmark coordinates were <1 mm. Accordingly, MRI-based spatial normalization was most accurate, but results of the PET-based spatial normalization were quite comparable.
  
  
  CONCLUSIONS
  Image registration using DARTEL provides a standardized and automatic framework for small animal brain data analysis. The authors were able to show that this method works with high reliability and validity. Using DARTEL templates together with nonlinear registration algorithms allows for accurate spatial normalization of combined MRI/PET or PET-only studies.
authors.affiliation: Institute of Neuroradiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstraße 1, Mainz 55131, Germany.
authors.forename: Andrea
authors.initials: A
authors.lastname: Kronfeld
authors.affiliation: Department of Nuclear Medicine, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstraße 1, Mainz 55131, Germany.
authors.forename: Hans-Georg
authors.initials: HG
authors.lastname: Buchholz
authors.affiliation: Department of Nuclear Medicine, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstraße 1, Mainz 55131, Germany.
authors.forename: Stephan
authors.initials: S
authors.lastname: Maus
authors.affiliation: Department of Nuclear Medicine, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstraße 1, Mainz 55131, Germany.
authors.forename: Stefan
authors.initials: S
authors.lastname: Reuss
authors.affiliation: Institute of Neuroradiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstraße 1, Mainz 55131, Germany.
authors.forename: Wibke
authors.initials: W
authors.lastname: Müller-Forell
authors.affiliation: Institute of Physiological Chemistry, University Medical Center of the Johannes Gutenberg University Mainz, Duesbergweg 6, Mainz 55128, Germany.
authors.forename: Beat
authors.initials: B
authors.lastname: Lutz
authors.affiliation: Department of Nuclear Medicine, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstraße 1, Mainz 55131, Germany.
authors.forename: Mathias
authors.initials: M
authors.lastname: Schreckenberger
authors.affiliation: Department of Nuclear Medicine, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstraße 1, Mainz 55131, Germany.
authors.forename: Isabelle
authors.initials: I
authors.lastname: Miederer
mesh_terms: D000465:Algorithms; D000818:Animals; D001921:Brain / Q000033:anatomy & histology* / Q000000981:diagnostic imaging* / Q000378:metabolism; D066128:Gray Matter / Q000033:anatomy & histology / Q000000981:diagnostic imaging / Q000378:metabolism; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated / Q000379:methods; D049268:Positron-Emission Tomography / Q000379:methods*; D011725:Pyridines; D019275:Radiopharmaceuticals; D017207:Rats, Sprague-Dawley; D043884:Receptor, Cannabinoid, CB1 / Q000378:metabolism*; D015203:Reproducibility of Results; D066127:White Matter / Q000033:anatomy & histology / Q000000981:diagnostic imaging / Q000378:metabolism
chemical_list: C543264:Cnr1 protein, rat; C528731:MK-9470; D011725:Pyridines; D019275:Radiopharmaceuticals; D043884:Receptor, Cannabinoid, CB1