A baseline study for detection of Parkinson's disease with 3D-transcranial sonography and uni-lateral reconstruction

Plate, Annika; Maiostre, Juliana; Levin, Johannes; Boetzel, Kai und Ahmadi, Seyed-Ahmad (2019): A baseline study for detection of Parkinson's disease with 3D-transcranial sonography and uni-lateral reconstruction. In: Journal of the Neurological Sciences, Bd. 397: S. 16-21

Abstract

Introduction: TCS is a well-established technique for diagnosis of Parkinson's disease (PD). Volumetric 3D-TCS is a promising complementary approach for objective acquisition and analysis, in particular for less experienced sonographers. This study provides baselines for Parkinson detection (sensitivity and specificity), cutoff values and inter-rater agreement in 3D-TCS. Methods: We performed 3D-TCS in 52 subjects (healthy controls and PD) bilaterally, and reconstructed in 3D space uni-laterally. Ipsi-lateral hyperechogenicities in the substantia nigra are manually segmented slice-by-slice in the 3D volume by two raters at different experience levels. ROC threshold analysis is performed and compared on features representing 3D volume and axial cross-sections (2.5D) of hyperechogenicities. Pearson correlation and intra-class correlation coefficients were evaluated for assessment of inter-rater agreement. Results: 50 subjects were included. Both raters achieved high classification accuracy with 2.5D/3D features extracted from 3D-TCS volumes (best results sensitivity/specificity/cut-off per rater: 84.6%/88.9%/25.0mm(2);77.8%/88.9%/95.9mm3). The inter-rater agreement in 3D was high (ICC(A,1) = 0.777, p < 10(-3)), the classification performance of both sonographers was statistically not significantly different. Conclusion: The study presents first baseline values for uni-lateral 3D-TCS examination, and finds no disadvantage of uni-lateral reconstructions compared to previous bi-lateral fusion. Volumetric 3D-TCS has potential for a high inter-rater agreement and accuracy in detection of PD, in particular for sonographers with less experience.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Medizin
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• ISSN: 0022-510X
• Sprache: Englisch