{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T14:59:49Z","timestamp":1787065189139,"version":"build-2736575974"},"reference-count":68,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2023,3,2]],"date-time":"2023-03-02T00:00:00Z","timestamp":1677715200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,3,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>To better understand the pathological and phenotypic heterogeneity of progressive supranuclear palsy and the links between the two, we applied a novel unsupervised machine learning algorithm (Subtype and Stage Inference) to the largest MRI data set to date of people with clinically diagnosed progressive supranuclear palsy (including progressive supranuclear palsy\u2013Richardson and variant progressive supranuclear palsy syndromes).<\/jats:p>\n                  <jats:p>Our cohort is comprised of 426 progressive supranuclear palsy cases, of which 367 had at least one follow-up scan, and 290 controls. Of the progressive supranuclear palsy cases, 357 were clinically diagnosed with progressive supranuclear palsy\u2013Richardson, 52 with a progressive supranuclear palsy\u2013cortical variant (progressive supranuclear palsy\u2013frontal, progressive supranuclear palsy\u2013speech\/language, or progressive supranuclear palsy\u2013corticobasal), and 17 with a progressive supranuclear palsy\u2013subcortical variant (progressive supranuclear palsy\u2013parkinsonism or progressive supranuclear palsy\u2013progressive gait freezing). Subtype and Stage Inference was applied to volumetric MRI features extracted from baseline structural (T1-weighted) MRI scans and then used to subtype and stage follow-up scans. The subtypes and stages at follow-up were used to validate the longitudinal consistency of subtype and stage assignments. We further compared the clinical phenotypes of each subtype to gain insight into the relationship between progressive supranuclear palsy pathology, atrophy patterns, and clinical presentation.<\/jats:p>\n                  <jats:p>The data supported two subtypes, each with a distinct progression of atrophy: a \u2018subcortical\u2019 subtype, in which early atrophy was most prominent in the brainstem, ventral diencephalon, superior cerebellar peduncles, and the dentate nucleus, and a \u2018cortical\u2019 subtype, in which there was early atrophy in the frontal lobes and the insula alongside brainstem atrophy. There was a strong association between clinical diagnosis and the Subtype and Stage Inference subtype with 82% of progressive supranuclear palsy\u2013subcortical cases and 81% of progressive supranuclear palsy\u2013Richardson cases assigned to the subcortical subtype and 82% of progressive supranuclear palsy\u2013cortical cases assigned to the cortical subtype. The increasing stage was associated with worsening clinical scores, whilst the \u2018subcortical\u2019 subtype was associated with worse clinical severity scores compared to the \u2018cortical subtype\u2019 (progressive supranuclear palsy rating scale and Unified Parkinson\u2019s Disease Rating Scale). Validation experiments showed that subtype assignment was longitudinally stable (95% of scans were assigned to the same subtype at follow-up) and individual staging was longitudinally consistent with 90% remaining at the same stage or progressing to a later stage at follow-up.<\/jats:p>\n                  <jats:p>In summary, we applied Subtype and Stage Inference to structural MRI data and empirically identified two distinct subtypes of spatiotemporal atrophy in progressive supranuclear palsy. These image-based subtypes were differentially enriched for progressive supranuclear palsy clinical syndromes and showed different clinical characteristics. Being able to accurately subtype and stage progressive supranuclear palsy patients at baseline has important implications for screening patients on entry to clinical trials, as well as tracking disease progression.<\/jats:p>","DOI":"10.1093\/braincomms\/fcad048","type":"journal-article","created":{"date-parts":[[2023,2,27]],"date-time":"2023-02-27T17:08:33Z","timestamp":1677517713000},"source":"Crossref","is-referenced-by-count":32,"title":["Uncovering spatiotemporal patterns of atrophy in progressive supranuclear palsy using unsupervised machine learning"],"prefix":"10.1093","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0607-3190","authenticated-orcid":false,"given":"William J","family":"Scotton","sequence":"first","affiliation":[{"name":"Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London , London WC1N 3AR , 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3AR , UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7833-616X","authenticated-orcid":false,"given":"David M","family":"Cash","sequence":"additional","affiliation":[{"name":"Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London , London WC1N 3AR , UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lawren","family":"VandeVrede","sequence":"additional","affiliation":[{"name":"Department of Neurology, Memory and Aging Center, University of California , San Francisco, CA 94158 , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hilary","family":"Heuer","sequence":"additional","affiliation":[{"name":"Department of Neurology, Memory and Aging Center, University of California , San Francisco, CA 94158 , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"PROSPECT Consortium, 4RTNI 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