{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T03:49:35Z","timestamp":1780458575942,"version":"3.54.1"},"reference-count":32,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2023,8,6]],"date-time":"2023-08-06T00:00:00Z","timestamp":1691280000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["movementdisorders.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Movement Disorders"],"published-print":{"date-parts":[[2023,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Brain magnetic resonance imaging (MRI) is used to support the diagnosis of progressive supranuclear palsy (PSP). However, the value of visual descriptive, manual planimetric, automatic volumetric MRI markers and fully automatic categorization is unclear, particularly regarding PSP predominance types other than Richardson's syndrome (RS).<\/jats:p><\/jats:sec><jats:sec><jats:title>Objectives<\/jats:title><jats:p>To compare different visual reading strategies and automatic classification of T1\u2010weighted MRI for detection of PSP in a typical clinical cohort including PSP\u2010RS and (non\u2010RS) variant PSP (vPSP) patients.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Forty\u2010one patients (21 RS, 20 vPSP) and 46 healthy controls were included. Three readers using three strategies performed MRI analysis: exclusively visual reading using descriptive signs (hummingbird, morning\u2010glory, Mickey\u2010Mouse), visual reading supported by manual planimetry measures, and visual reading supported by automatic volumetry. Fully automatic classification was performed using a pre\u2010trained support vector machine (SVM) on the results of atlas\u2010based volumetry.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>All tested methods achieved higher specificity than sensitivity. Limited sensitivity was driven to large extent by false negative vPSP cases. Support by automatic volumetry resulted in the highest accuracy (75.1%\u2009\u00b1\u20093.5%) among the visual strategies, but performed not better than the midbrain area (75.9%), the best single planimetric measure. Automatic classification by SVM clearly outperformed all other methods (accuracy, 87.4%), representing the only method to provide clinically useful sensitivity also in vPSP (70.0%).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Fully automatic classification of volumetric MRI measures using machine learning methods outperforms visual MRI analysis without and with planimetry or volumetry support, particularly regarding diagnosis of vPSP, suggesting the use in settings with a broad phenotypic PSP spectrum. \u00a9 2023 The Authors. <jats:italic>Movement Disorders<\/jats:italic> published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mds.29527","type":"journal-article","created":{"date-parts":[[2023,8,7]],"date-time":"2023-08-07T01:00:25Z","timestamp":1691370025000},"page":"1891-1900","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Brain <scp>MRI<\/scp> in Progressive Supranuclear Palsy with Richardson's Syndrome and Variant Phenotypes"],"prefix":"10.1002","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9298-2897","authenticated-orcid":false,"given":"Mike P.","family":"Wattjes","sequence":"first","affiliation":[{"name":"Department of Neuroradiology Hannover Medical School  Hannover Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3856-9094","authenticated-orcid":false,"given":"Hans\u2010J\u00fcrgen","family":"Huppertz","sequence":"additional","affiliation":[{"name":"Swiss Epilepsy Clinic, Klinik Lengg  Zurich 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