title: Diagnosis of regional cerebral blood flow abnormalities using spect: agreement between individualized statistical parametric maps and visual inspection by nuclear medicine physicians with different levels of expertise in nuclear neurology.
abstract: BACKGROUND
  Visual analysis is widely used to interpret regional cerebral blood flow (rCBF) SPECT images in clinical practice despite its limitations. Automated methods are employed to investigate between-group rCBF differences in research studies but have rarely been explored in individual analyses.
  
  
  OBJECTIVE
  To compare visual inspection by nuclear physicians with the automated statistical parametric mapping program using a SPECT dataset of patients with neurological disorders and normal control images.
  
  
  METHODS
  Using statistical parametric mapping, 14 SPECT images from patients with various neurological disorders were compared individually with a databank of 32 normal images using a statistical threshold of p<0.05 (corrected for multiple comparisons at the level of individual voxels or clusters). Statistical parametric mapping results were compared with visual analyses by a nuclear physician highly experienced in neurology (A) as well as a nuclear physician with a general background of experience (B) who independently classified images as normal or altered, and determined the location of changes and the severity.
  
  
  RESULTS
  Of the 32 images of the normal databank, 4 generated maps showing rCBF abnormalities (p<0.05, corrected). Among the 14 images from patients with neurological disorders, 13 showed rCBF alterations. Statistical parametric mapping and physician A completely agreed on 84.37% and 64.28% of cases from the normal databank and neurological disorders, respectively. The agreement between statistical parametric mapping and ratings of physician B were lower (71.18% and 35.71%, respectively).
  
  
  CONCLUSIONS
  Statistical parametric mapping replicated the findings described by the more experienced nuclear physician. This finding suggests that automated methods for individually analyzing rCBF SPECT images may be a valuable resource to complement visual inspection in clinical practice.
authors.affiliation: Department of Nuclear Medicine, Hospital de Câncer, Fundação Pio XII - Barretos/SP, Brazil. euclidestimoteo@uol.com.br
authors.forename: Euclides Timóteo da
authors.initials: ET
authors.lastname: Rocha
authors.forename: Carlos Alberto
authors.initials: CA
authors.lastname: Buchpiguel
authors.forename: Ricardo
authors.initials: R
authors.lastname: Nitrini
authors.forename: Sergio
authors.initials: S
authors.lastname: Tazima
authors.forename: Stela Verzinhase
authors.initials: SV
authors.lastname: Peres
authors.forename: Geraldo
authors.initials: G
authors.lastname: Busatto Filho
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001921:Brain / Q000098:blood supply / Q000000981:diagnostic imaging*; D001927:Brain Diseases / Q000000981:diagnostic imaging* / Q000503:physiopathology; D001931:Brain Mapping / Q000379:methods*; D016022:Case-Control Studies; D002560:Cerebrovascular Circulation; D004522:Educational Status; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009683:Nuclear Medicine / Q000592:standards*; D015588:Observer Variation; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D015899:Tomography, Emission-Computed, Single-Photon