title: Evaluation of methods to detect interhemispheric asymmetry on cerebral perfusion SPECT: application to epilepsy.
abstract: Detecting perfusion interhemispheric asymmetry in neurologic nuclear medicine imaging is an interesting approach to epilepsy.
  
  
  METHODS
  This study compared 4 methods that detect interhemispheric asymmetries of brain perfusion in SPECT. The first (M1) was conventional side-by-side expert-based visual interpretation of SPECT. The second (M2) was visual interpretation assisted by an interhemispheric difference (IHD) volume. The last 2 were automatic methods: unsupervised analysis using volumes of interest (M3) and unsupervised analysis of the IHD volume (M4). Use of these methods to detect possible perfusion asymmetry was compared on 60 simulated SPECT datasets by controlling the presence and location of asymmetries. From the detection results, localization receiver operating characteristic curves were generated and areas under curves were estimated and compared. Finally, the methods were applied to analyze interictal SPECT datasets to localize the epileptogenic focus in temporal lobe epilepsies.
  
  
  RESULTS
  This study showed an improvement in asymmetry detection on SPECT images with the methods using IHD volume (M2 and M4), in comparison with the other methods (M1 and M3). However, the most useful method for analyzing clinical SPECT datasets appeared to be visual inspection assisted by the IHD volume, since the automatic method using the IHD volume was less specific.
  
  
  CONCLUSIONS
  The use of quantitative methods can improve performance in detection of perfusion asymmetry over visual inspection alone.
authors.affiliation: Laboratoire Intégration de données multimédia en anatomie et physiologie cérébrale pour l'aide à la décision et l'enseignement, Rennes, France.
authors.forename: Bérengère
authors.initials: B
authors.lastname: Aubert-Broche
authors.forename: Pierre
authors.initials: P
authors.lastname: Jannin
authors.forename: Arnaud
authors.initials: A
authors.lastname: Biraben
authors.forename: Anne-Marie
authors.initials: AM
authors.lastname: Bernard
authors.forename: Claire
authors.initials: C
authors.lastname: Haegelen
authors.forename: Florence Prigent
authors.initials: FP
authors.lastname: Le Jeune
authors.forename: Bernard
authors.initials: B
authors.lastname: Gibaud
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000098:blood supply* / Q000000981:diagnostic imaging*; D002560:Cerebrovascular Circulation; D004833:Epilepsy, Temporal Lobe / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D008297:Male; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D015899:Tomography, Emission-Computed, Single-Photon / Q000379:methods*