Abstract
ObjectivesTo investigate the value of MRI-based radiomic model based on the radiomic features of different basal nuclei in differentiating idiopathic Parkinson’s disease (IPD) from Parkinsonian variants of multiple system atrophy (MSA-P).MethodsRadiomics was applied to the 3T susceptibility- weighted imaging (SWI) from 102 MSA-P patients and 83 IPD patients (allocated to a training and a testing cohort, 7:3 ratio). The substantia nigra (SN), caudate nucleus (CN), putamen (PUT), globus pallidus (GP), red nucleus (RN), and subthalamic nucleus (STN) were manually segmented, and 396 features were extracted. After feature selection, support vector machine (SVM) was generated, and its predictive performance was calculated in both the training and testing cohorts using the area under receiver operating characteristic curve (AUC).ResultsSeven radiomic features were selected from the PUT, by which the SVM classifier achieved the best diagnostic performance with an AUC of 0.867 in the training cohort and an AUC of 0.862 in the testing cohort. Furthermore, the combined model, which incorporating part III of the Parkinson’s Disease Rating Scale (UPDRSIII) scores into radiomic features of the PUT, further improved the diagnostic performance. However, radiomic features extracted from RN, SN, GP, CN, and STN had moderate to poor diagnostic performance, with AUC values that ranged from 0.610 to 0.788 in the training cohort and 0.583 to 0.766 in the testing cohort.ConclusionRadiomic features derived from the PUT had optimal value in differentiating IPD from MSA-P. A combined radiomic model, which contained radiomic features of the PUT and UPDRSIII scores, further improved performance and may represent a promising tool for distinguishing between IPD and MSA-P.
Highlights
Idiopathic Parkinson’s disease (IPD) and multiple system atrophy (MSA), especially Parkinsonian subtypes of MSA (MSA-P), are common neurodegenerative disorders that share similar Parkinsonism symptom (Ramli et al, 2015; Barbagallo et al, 2016)
Promising MR diagnostic biomarkers have been proposed to be useful for differentiating IPD from atypical Parkinsonism (AP) via Susceptibility-weighted imaging (SWI) based on neurodegenerative patterns that underlie PD and Atypical Parkinsonism (AP) (Meijer et al, 2016; Wang et al, 2017b)
There were no significant differences in age, gender, disease duration, or Montreal Cognitive Assessment (MoCA) score between the IPD and Parkinsonian variant of multiple system atrophy (MSA-P) patients in both the training and testing cohorts
Summary
Idiopathic Parkinson’s disease (IPD) and multiple system atrophy (MSA), especially Parkinsonian subtypes of MSA (MSA-P), are common neurodegenerative disorders that share similar Parkinsonism symptom (Ramli et al, 2015; Barbagallo et al, 2016). Increased attention has been paid to advanced magnetic resonance imaging (MRI) approaches to detect physiological mechanisms underlying PD and to distinguish IPD and MSA, and these approaches include resting-state functional MRI (Wang et al, 2017a), diffusion MRI (Hikishima et al, 2015), and voxel-based morphometry (Peran et al, 2018). These approaches are not generalized to clinical practice due to a lack of consistent results and their time-consuming nature. Tissue-specific physiological patterns in iron concentrations have been proposed, with the highest concentrations found in different basal nuclei [i.e., putamen (PUT), globus pallidus (GP), caudate nucleus (CN), and red nucleus (RN)] in patients with neurodegenerative diseases, which may provide valuable information for differential diagnoses
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