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Open AccessArticle

Semi-Automatic Signature-Based Segmentation Method for Quantification of Neuromelanin in Substantia Nigra

1
Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1000 Ljubljana, Slovenia
2
Department of Neurology, University Medical Center, Zaloška 2, 1000 Ljubljana, Slovenia
*
Author to whom correspondence should be addressed.
Brain Sci. 2019, 9(12), 335; https://doi.org/10.3390/brainsci9120335
Received: 23 October 2019 / Revised: 18 November 2019 / Accepted: 19 November 2019 / Published: 22 November 2019
(This article belongs to the Section Neuroimaging)
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. View Full-Text
Keywords: neuromelanin; neuroimaging; brainstem; substantia nigra; segmentation; Parkinson’s disease neuromelanin; neuroimaging; brainstem; substantia nigra; segmentation; Parkinson’s disease
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MDPI and ACS Style

Zupan, G.; Šuput, D.; Pirtošek, Z.; Vovk, A. Semi-Automatic Signature-Based Segmentation Method for Quantification of Neuromelanin in Substantia Nigra. Brain Sci. 2019, 9, 335.

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