title: Assessment of pedophilia using hemodynamic brain response to sexual stimuli.
abstract: BACKGROUND
  Accurately assessing sexual preference is important in the treatment of child sex offenders. Phallometry is the standard method to identify sexual preference; however, this measure has been criticized for its intrusiveness and limited reliability.
  
  
  OBJECTIVE
  To evaluate whether spatial response pattern to sexual stimuli as revealed by a change in the blood oxygen level-dependent signal facilitates the identification of pedophiles.
  
  
  METHODS
  During functional magnetic resonance imaging, pedophilic and nonpedophilic participants were briefly exposed to same- and opposite-sex images of nude children and adults. We calculated differences in blood oxygen level-dependent signals to child and adult sexual stimuli for each participant. The corresponding contrast images were entered into a group analysis to calculate whole-brain difference maps between groups. We calculated an expression value that corresponded to the group result for each participant. These expression values were submitted to 2 different classification algorithms: Fisher linear discriminant analysis and κ -nearest neighbor analysis. This classification procedure was cross-validated using the leave-one-out method.
  
  
  METHODS
  Section of Sexual Medicine, Medical School, Christian Albrechts University of Kiel, Kiel, Germany.
  
  
  METHODS
  We recruited 24 participants with pedophilia who were sexually attracted to either prepubescent girls (n = 11) or prepubescent boys (n = 13) and 32 healthy male controls who were sexually attracted to either adult women (n = 18) or adult men (n = 14).
  
  
  METHODS
  Sensitivity and specificity scores of the 2 classification algorithms.
  
  
  RESULTS
  The highest classification accuracy was achieved by Fisher linear discriminant analysis, which showed a mean accuracy of 95% (100% specificity, 88% sensitivity).
  
  
  CONCLUSIONS
  Functional brain response patterns to sexual stimuli contain sufficient information to identify pedophiles with high accuracy. The automatic classification of these patterns is a promising objective tool to clinically diagnose pedophilia.
authors.affiliation: Section of Sexual Medicine, Christian Albrechts University, Kiel, Germany. ponseti@sexmed.uni-kiel.de
authors.forename: Jorge
authors.initials: J
authors.lastname: Ponseti
authors.forename: Oliver
authors.initials: O
authors.lastname: Granert
authors.forename: Olav
authors.initials: O
authors.lastname: Jansen
authors.forename: Stephan
authors.initials: S
authors.lastname: Wolff
authors.forename: Klaus
authors.initials: K
authors.lastname: Beier
authors.forename: Janina
authors.initials: J
authors.lastname: Neutze
authors.forename: Günther
authors.initials: G
authors.lastname: Deuschl
authors.forename: Hubertus
authors.initials: H
authors.lastname: Mehdorn
authors.forename: Hartwig
authors.initials: H
authors.lastname: Siebner
authors.forename: Hartmut
authors.initials: H
authors.lastname: Bosinski
mesh_terms: D000293:Adolescent; D000328:Adult; D001921:Brain / Q000098:blood supply / Q000503:physiopathology*; D016022:Case-Control Studies; D002648:Child; D005260:Female; D020010:Heterosexuality / Q000502:physiology / Q000523:psychology; D018451:Homosexuality, Male / Q000523:psychology; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D010378:Pedophilia / Q000175:diagnosis* / Q000503:physiopathology / Q000523:psychology; D012725:Sexual Behavior / Q000502:physiology; D055815:Young Adult