title: Automated detection of local normalization areas for ictal-interictal subtraction brain SPECT.
abstract: Whole-brain activity is often chosen to quantitatively normalize peri-ictal and interictal SPECT scans before their subtraction. This use is not justified, because significant and extended modification of the cerebral blood flow can occur during a seizure. We validated and compared 2 automatic methods able to determine the optimal reference region, using simulation and clinical data.
  
  
  METHODS
  In the first method, the selected reference region is the intersection of peri-ictal-interictal areas with no significantly different z values. The other method relies on a 3-dimensional iterative voxel aggregation. The increase of the selected volume is stopped by using 2 different variance tests (Levene and SE). These algorithms were tested on 39 epileptic patients and were validated using 1 interictal and 10 peri-ictal scans simulated from the mean image of 22 healthy subjects.
  
  
  RESULTS
  In the patient studies, the mean relative activity of the selected regions, compared with whole-brain activity (classic normalization), was 122.6%. Their average relative size (compared with the size of the whole brain) was 33.2% for the z map method, 22.8% for the SE test, and 11.8% for the Levene test. After application of our automatic processes, subtraction of the simulated images revealed a recovery of abnormal regions up to 45% larger than the region obtained with classic normalization.
  
  
  CONCLUSIONS
  These results illustrate the role of normalization on the subtracted peri-ictal and interictal images. Our methods are automatic and objective and give good results on various simulated images. The z map construction is worth considering because it is simple, selects large parts of the brain, and requires little computation time.
authors.affiliation: Equipe d'Accueil 1880, Functional Neurology and Epilepsy Unit, Neuro-Cardiological Hospital, Lyon, France. nicolas.boussion@umontreal.ca
authors.forename: Nicolas
authors.initials: N
authors.lastname: Boussion
authors.forename: Claire
authors.initials: C
authors.lastname: Houzard
authors.forename: Karine
authors.initials: K
authors.lastname: Ostrowsky
authors.forename: Philippe
authors.initials: P
authors.lastname: Ryvlin
authors.forename: François
authors.initials: F
authors.lastname: Mauguière
authors.forename: Luc
authors.initials: L
authors.lastname: Cinotti
mesh_terms: D000328:Adult; D001921:Brain / Q000000981:diagnostic imaging*; D002560:Cerebrovascular Circulation; D004827:Epilepsy / Q000000981:diagnostic imaging* / Q000503:physiopathology; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D015899:Tomography, Emission-Computed, Single-Photon / Q000379:methods