title: Computer-assisted system for diagnosis of Alzheimer disease using data base- independent estimation and fluorodeoxyglucose- positron-emission tomography and 3D-stereotactic surface projection.
abstract: OBJECTIVE
  Recently, voxel-based statistical parametric images have been developed as additional diagnostic tools for AD. However these methods require the generation of a data base of healthy brain images. The purpose of this study was to produce and evaluate an automatic method using a data base-independent estimation system for the diagnosis of mild AD.
  
  
  METHODS
  We retrospectively selected 66 subjects, including 33 patients with early AD and 33 age-matched healthy volunteers. Individual brain metabolic images were obtained by using FDG-PET. These were transformed by using 3D-SSP. We then produced CADDIES, which compares the parietal and sensorimotor metabolic counts by using t tests. If parietal metabolism was significantly lower than the sensorimotor metabolism, the subject was automatically diagnosed as having AD. The FDG-PET images were also analyzed by using a previous automatic diagnosis system (CAAD) that is dependent on the construction of a "normal data base" of healthy brain images. Diagnostic performance was compared between the 2 methods.
  
  
  RESULTS
  The CADDIES demonstrated a sensitivity of 88%, specificity of 79%, and accuracy of 85%, while the CAAD system demonstrated a sensitivity of 70%, specificity of 94%, and accuracy of 82%. The area under the ROC curve of CADDIES was 0.964. The areas under ROC curves of the CAAD method in the parietal and posterior cingulate gyri were 0.843 and 0.939, respectively.
  
  
  CONCLUSIONS
  The CADDIES method demonstrated a diagnostic accuracy similar to that of the CAAD system. Our results indicate that this method can be applied to the detection of patients with early AD in routine clinical examinations, with the benefit of not requiring the generation of a normal data base.
authors.affiliation: Department of Radiology and Nuclear Medicine, Hyogo Brain and Heart Center, Himeji, Japan.
authors.forename: T
authors.initials: T
authors.lastname: Uemura
authors.forename: K
authors.initials: K
authors.lastname: Ishii
authors.forename: N
authors.initials: N
authors.lastname: Miyamoto
authors.forename: T
authors.initials: T
authors.lastname: Yoshikawa
mesh_terms: D000368:Aged; D000465:Algorithms; D000544:Alzheimer Disease / Q000000981:diagnostic imaging*; D001185:Artificial Intelligence; D001921:Brain / Q000000981:diagnostic imaging*; D016000:Cluster Analysis; D003196:Computer Graphics; D003198:Computer Simulation; D016208:Databases, Factual; D019788:Fluorodeoxyglucose F18; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D008297:Male; D008954:Models, Biological; D015233:Models, Statistical; D009716:Numerical Analysis, Computer-Assisted; D010363:Pattern Recognition, Automated / Q000379:methods; D049268:Positron-Emission Tomography / Q000379:methods*; D019275:Radiopharmaceuticals; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013382:Subtraction Technique; D014584:User-Computer Interface
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18