Substantia Nigra Radiomics Feature Extraction of Parkinson’s Disease Based on Magnitude Images of Susceptibility-Weighted Imaging
Open Access
- 31 May 2021
- journal article
- research article
- Published by Frontiers Media SA in Frontiers in Neuroscience
Abstract
Background: It is reported that radiomic features extracted from quantitative susceptibility mapping (QSM) had promising clinical value for the diagnosis of Parkinson’s disease (PD). We aimed to explore the usefulness of radiomics features based on magnitude images to distinguish PD from non-PD controls. Methods: We retrospectively recruited PD patients and controls who underwent brain 3.0T MR including susceptibility-weighted imaging (SWI). A total of 396 radiomics features were extracted from the SN of 95 PD patients and 95 non-PD controls based on SWI. Intra-/inter-observer correlation coefficients (ICCs) were applied to measure the observer agreement for the radiomic feature extraction. Then the patients were randomly grouped into training and validation sets in a ratio of 7:3. In the training set, the maximum correlation minimum redundancy algorithm (mRMR) and the least absolute shrinkage and selection operator (LASSO) were conducted to filter and choose the optimized subset of features, and a radiomics signature was constructed. Moreover, radiomics signatures were constructed by different machine learning models. Area under the ROC curves (AUCs) were applied to evaluate the predictive performance of the models. Then correlation analysis was performed to evaluate the correlation between the optimized features and clinical factors. Results: The intro-observer CC ranged from 0.82 to 1.0, and the inter-observer CC ranged from 0.77 to 0.99. The LASSO logistic regression model showed good prediction efficacy in the training set [AUC = 0.82, 95% confidence interval (CI, 0.74–0.88)] and the validation set [AUC = 0.81, 95% CI (0.68–0.91)]. One radiomic feature showed a moderate negative correlation with Hoehn-Yahr stage (r = −0.49, P = 0.012). Conclusion: Radiomic predictive features based on SWI magnitude images could reflect the Hoehn-Yahr stage of PD to some extent.This publication has 23 references indexed in Scilit:
- Determinants of iron accumulation in the normal aging brainNeurobiology of Aging, 2016
- Radiomics: Images Are More than Pictures, They Are DataRadiology, 2016
- Freezing of gait in early Parkinson's disease: Nigral iron content estimated from magnetic resonance imagingJournal of the Neurological Sciences, 2015
- MDS clinical diagnostic criteria for Parkinson's diseaseMovement Disorders, 2015
- The ‘Swallow Tail’ Appearance of the Healthy Nigrosome – A New Accurate Test of Parkinson's Disease: A Case-Control and Retrospective Cross-Sectional MRI Study at 3TPLOS ONE, 2014
- Seven‐tesla magnetic resonance images of the substantia nigra in Parkinson diseaseAnnals of Neurology, 2011
- Combined stimulation of the substantia nigra pars reticulata and the subthalamic nucleus is effective in hypokinetic gait disturbance in Parkinson’s diseaseZeitschrift für Neurologie, 2011
- Systematic review of levodopa dose equivalency reporting in Parkinson's diseaseMovement Disorders, 2010
- Substantia nigra echogenicity: A structural correlate of functional impairment of the dopaminergic striatal projection in Parkinson's diseaseMovement Disorders, 2009
- AGEING AND PARKINSON'S DISEASE: SUBSTANTIA NIGRA REGIONAL SELECTIVITYBrain, 1991