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This study aimed to investigate differences and similarities in the brain functional connectomes of IPD and MSA\u2010P patients and use machine learning methods to explore the diagnostic utility of these features. Resting\u2010state fMRI data were acquired from 88 healthy controls, 76 MSA\u2010P patients, and 53 IPD patients using a 3.0\u00a0T scanner. The whole\u2010brain functional connectome was constructed by thresholding the Pearson correlation matrices of 116 regions, and topological properties were evaluated through graph theory approaches. Connectome measurements were used as features in machine learning models (random forest [RF]\/logistic regression [LR]\/support vector machine) to distinguish IPD and MSA\u2010P patients. Regarding graph metrics, early IPD and MSA\u2010P patients shared network topological properties. Both patient groups showed functional connectivity disruptions within the cerebellum\u2010basal ganglia\u2010cortical network, but these disconnections were mainly in the cortico\u2010thalamo\u2010cerebellar circuits in MSA\u2010P patients and the basal ganglia\u2010thalamo\u2010cortical circuits in IPD patients. Among the connectome parameters, <jats:italic>t<\/jats:italic> tests combined with the RF method identified 15 features, from which the LR classifier achieved the best diagnostic performance on the validation set (accuracy\u00a0=\u00a092.31%, sensitivity\u00a0=\u00a090.91%, specificity\u00a0=\u00a093.33%, area under the receiver operating characteristic curve\u00a0=\u00a00.89). MSA\u2010P and IPD patients show similar whole\u2010brain network topological alterations. MSA\u2010P primarily affects cerebellar nodes, and IPD primarily affects basal ganglia nodes; both conditions disrupt the cerebellum\u2010basal ganglia\u2010cortical network. Moreover, functional connectome parameters showed outstanding value in the differential diagnosis of early MSA\u2010P and IPD.<\/jats:p>","DOI":"10.1002\/hbm.26201","type":"journal-article","created":{"date-parts":[[2023,1,20]],"date-time":"2023-01-20T11:44:51Z","timestamp":1674215091000},"page":"2176-2190","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Functional connectome automatically differentiates multiple system atrophy (parkinsonian type) from idiopathic Parkinson's disease at early stages"],"prefix":"10.1002","volume":"44","author":[{"given":"Boyu","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Radiology The First Hospital of China Medical University  Shenyang Liaoning People's Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenzhuo","family":"Cui","sequence":"additional","affiliation":[{"name":"Department of Radiology The First Hospital of China Medical University  Shenyang Liaoning People's Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shanshan","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Radiology The First Hospital of China Medical University  Shenyang Liaoning People's Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anlan","family":"Sun","sequence":"additional","affiliation":[{"name":"Yizhun Medical AI Co. 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