Abstract
In Parkinson’s disease (PD), there is a reduction of neuromelanin (NM) in the substantia nigra (SN). Manual quantification of the NM volume in the SN is unpractical and time-consuming; therefore, we aimed to quantify NM in the SN with a novel semi-automatic segmentation method. Twenty patients with PD and twelve healthy subjects (HC) were included in this study. T1-weighted spectral pre-saturation with inversion recovery (SPIR) images were acquired on a 3T scanner. Manual and semi-automatic atlas-free local statistics signature-based segmentations measured the surface and volume of SN, respectively. Midbrain volume (MV) was calculated to normalize the data. Receiver operating characteristic (ROC) analysis was performed to determine the sensitivity and specificity of both methods. PD patients had significantly lower SN mean surface (37.7 ± 8.0 vs. 56.9 ± 6.6 mm2) and volume (235.1 ± 45.4 vs. 382.9 ± 100.5 mm3) than HC. After normalization with MV, the difference remained significant. For surface, sensitivity and specificity were 91.7 and 95 percent, respectively. For volume, sensitivity and specificity were 91.7 and 90 percent, respectively. Manual and semi-automatic segmentation methods of the SN reliably distinguished between PD patients and HC. ROC analysis shows the high sensitivity and specificity of both methods.
Highlights
IntroductionParkinson’s disease (PD) is a common neurodegenerative disease with a prevalence of 160/100,000
Parkinson’s disease (PD) is a common neurodegenerative disease with a prevalence of 160/100,000(1.6 percent) in Western Europe [1]
A meta-analysis [3] reports that the accuracy of the initial clinical diagnosis of PD made by a movement disorders specialist is 79.6 percent
Summary
Parkinson’s disease (PD) is a common neurodegenerative disease with a prevalence of 160/100,000. (1.6 percent) in Western Europe [1]. Degeneration of the nigrostriatal dopaminergic system results in characteristic pathological changes in the substantia nigra (SN), a midbrain area that is crucially involved in movement [2]. Clinical diagnosis of PD is sometimes challenging, even when performed by an experienced neurologist. A meta-analysis [3] reports that the accuracy of the initial clinical diagnosis of PD made by a movement disorders specialist is 79.6 percent. The current role of brain magnetic resonance imaging (MRI) in PD is the exclusion of cerebrovascular diseases or other lesions that could cause or be attributed to parkinsonian symptoms [4].
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