title: A new program for highly reproducible automatic evaluation of the substantia nigra from transcranial sonographic images.
abstract: OBJECTIVE
  Recent studies report increased echogenicity of the substantia nigra (SN) in patients with Parkinson's disease (PD) using transcranial sonography (TCS). However, the main limitation to TCS is its dependence on the sonographer's experience. Experimental software for quantitative evaluation of the echogenic SN area was thus developed by us. The aim of this study was to test the reliability of the data using developed B-Mode Assist software in patients with parkinsonism and in healthy volunteers.
  
  
  METHODS
  The SN was imaged from the right temporal bone window in mesencephalic plane using TCS. DICOM images of SN were saved, converted into JPEG format, encoded and processed. Two observers performed 3 automatic evaluations of the SN area (measurements of SN area in each gray scale intensity inside the region of interest) by counting the standard deviation of all 6 measurements using developed software. The average value of all 3 measurements of each observer was used for computing Cohen's kappa coefficient to determine inter-observer correlations. Cohen's kappa coefficients as an intra-observer correlation for observer 1 and observer 2 were counted from the first 2 measurements of both observers.
  
  
  RESULTS
  In total, 92 images were evaluated using this software. The mean of the standard deviations was 3.87; Cohen's kappa for intra-observer agreement of two observers were 0.947, and 0.943, resp.; Cohen's kappa for inter-observers agreement was 0.880. The agreement between visual and automatic detection of SN pathology was in 97.8% images. The sensitivity, specificity, positive and negative predictive values of automatic measurement were 100, 96.2, 95.1, 100%, resp.
  
  
  CONCLUSIONS
  The results show very reliable measurement of SN features using designed application with "almost perfect" inter-observer and intra-observer agreements.
authors: Institute of Computer Science, Faculty of Philosophy and Science, Silesian University in Opava, Opava, Czech Republic.
authors: Jiri
authors: J
authors: Blahuta
authors: Tomas
authors: T
authors: Soukup
authors: Monika
authors: M
authors: Jelinkova
authors: Petra
authors: P
authors: Bartova
authors: Petr
authors: P
authors: Cermak
authors: Roman
authors: R
authors: Herzig
authors: David
authors: D
authors: Skoloudik
mesh_terms: D000368:Aged; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010300:Parkinson Disease / Q000000981:diagnostic imaging*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013378:Substantia Nigra / Q000000981:diagnostic imaging*; D017585:Ultrasonography, Doppler, Transcranial / Q000379:methods*