BACKGROUND AND PURPOSE: Increased echogenicity of the substantia nigra is a typical transcranial sonography finding in Parkinson disease. Experimental software for digital analysis of the echogenic substantia nigra area has been developed. The aim of this study was to compare the evaluation of substantia nigra echogenicity by using digital analysis with a manual measurement in patients with Parkinson disease and healthy volunteers. MATERIALS AND METHODS: One hundred thirteen healthy volunteers were enrolled in the derivation cohort, and 50 healthy volunteers and 30 patients with Parkinson disease, in the validation cohort. The substantia nigra was imaged from the right and left temporal bone window by using transcranial sonography. All subjects were examined twice by using different sonographic machines by an experienced sonographer. DICOM images of the substantia nigra were encoded; then, digital analysis and manual measurement of the substantia nigra were performed. The 90th percentile of the derivation cohort values was used as a cut-point for the evaluation of the hyperechogenic substantia nigra in the validation cohort. The Spearman coefficient was used for assessment of the correlation between both measurements. The Cohen κ coefficient was used for the assessment of the correlation between both measurements and Parkinson disease diagnosis. RESULTS: The Spearman coefficient between measurements by using different machines was 0.686 for digital analysis and 0.721 for manual measurement (P < .0001). Hyperechogenic substantia nigra was detected in the same 26 (86.7%) patients with Parkinson disease by using both measurements. Cohen κ coefficients for digital analysis and manual measurement were 0.787 and 0.762, respectively (P < .0001). CONCLUSIONS: The present study showed comparable results when measuring the substantia nigra features conventionally and by using the developed software.

Department of Biophysics Faculty of Medicine and Dentistry Institute of Molecular and Translational Medicine Palacký University Olomouc Czech Republic

Department of Neurology Charles University Faculty of Medicine and University Hospital Hradec Králové Hradec Králové Czech Republic

Department of Neurology Hospital Karviná Ráj Karviná Czech Republic

Department of Neurology University Hospital Ostrava Ostrava Czech Republic

From the Faculty of Health Science University Hospital Ostrava Ostrava Czech Republic

Institute of Computer Science Faculty of Philosophy and Science Silesian University in Opava Opava Czech Republic

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