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1.
Neuroimage Clin ; 26: 102185, 2020.
Article in English | MEDLINE | ID: mdl-32050136

ABSTRACT

BACKGROUND: Transcranial B-mode sonography (TCS) can detect hyperechogenic speckles in the area of the substantia nigra (SN) in Parkinson's disease (PD). These speckles correlate with iron accumulation in the SN tissue, but an exact volumetric localization in and around the SN is still unknown. Areas of increased iron content in brain tissue can be detected in vivo with magnetic resonance imaging, using quantitative susceptibility mapping (QSM). METHODS: In this work, we i) acquire, co-register and transform TCS and QSM imaging from a cohort of 23 PD patients and 27 healthy control subjects into a normalized atlas template space and ii) analyze and compare the 3D spatial distributions of iron accumulation in the midbrain, as detected by a signal increase (TCS+ and QSM+) in both modalities. RESULTS: We achieved sufficiently accurate intra-modal target registration errors (TRE<1 mm) for all MRI volumes and multi-modal TCS-MRI co-localization (TRE<4 mm) for 66.7% of TCS scans. In the caudal part of the midbrain, enlarged TCS+ and QSM+ areas were located within the SN pars compacta in PD patients in comparison to healthy controls. More cranially, overlapping TCS+ and QSM+ areas in PD subjects were found in the area of the ventral tegmental area (VTA). CONCLUSION: Our findings are concordant with several QSM-based studies on iron-related alterations in the area SN pars compacta. They substantiate that TCS+ is an indicator of iron accumulation in Parkinson's disease within and in the vicinity of the SN. Furthermore, they are in favor of an involvement of the VTA and thereby the mesolimbic system in Parkinson's disease.


Subject(s)
Iron , Multimodal Imaging/methods , Neuroimaging/methods , Parkinson Disease/diagnostic imaging , Substantia Nigra/diagnostic imaging , Aged , Female , Humans , Image Interpretation, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Male , Middle Aged , Parkinson Disease/pathology , Substantia Nigra/pathology , Ultrasonography, Doppler, Transcranial/methods
2.
J Neurol Sci ; 397: 16-21, 2019 02 15.
Article in English | MEDLINE | ID: mdl-30579060

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%/25.0mm2; 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.


Subject(s)
Parkinson Disease/diagnostic imaging , Substantia Nigra/diagnostic imaging , Ultrasonography, Doppler, Transcranial/methods , Aged , Female , Humans , Male , Middle Aged , Sensitivity and Specificity
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