{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T20:12:57Z","timestamp":1789071177856,"version":"build-2803163510"},"reference-count":38,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2025,11,30]],"date-time":"2025-11-30T00:00:00Z","timestamp":1764460800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005089","name":"Natural Science Foundation of Beijing Municipality","doi-asserted-by":"publisher","award":["4252004"],"award-info":[{"award-number":["4252004"]}],"id":[{"id":"10.13039\/501100005089","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005089","name":"Natural Science Foundation of Beijing Municipality","doi-asserted-by":"publisher","award":["L242038"],"award-info":[{"award-number":["L242038"]}],"id":[{"id":"10.13039\/501100005089","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFC2402205"],"award-info":[{"award-number":["2022YFC2402205"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82471498"],"award-info":[{"award-number":["82471498"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["CNS Neurosci Ther"],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>To characterize white matter geometric pathology in cerebellar subtype of multiple system atrophy (MSA\u2010C) using director field analysis (DFA) and identify stage\u2010specific biomarkers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We analyzed single\u2010shell diffusion MRI (\n                      <jats:italic>b<\/jats:italic>\n                      \u2009=\u20091000) in 31 MSA\u2010C patients (15 early\u2010, 16 late\u2010stage) and 33 controls. DFA quantified axonal geometry (splay\/bend\/twist), complemented by fixel\u2010based analysis (FBA) and brainstem volumetry. Group comparisons used threshold free cluster enhancement (TFCE) (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.05 FWE\u2010corrected). DFA\u2010altered regions were correlated with clinical scores. AutoGluon evaluated classification performance using different feature sets.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      MSA\u2010C exhibited distinct geometric degeneration patterns: cerebellar pathways showed reduced splay, bend, and twist (reflecting Wallerian degeneration), whereas brainstem tracts demonstrated dissociated geometry (increased splay\/bend but decreased twist). Brainstem twist reduction strongly differentiated early\u2010 and late\u2010stage MSA\u2010C (AUC\u2009=\u20090.95). Clinically, middle cerebellar peduncle bend correlated with motor progression (UMSARS\u2010II:\n                      <jats:italic>r<\/jats:italic>\n                      \u2009=\u20090.48), while cerebellar splay reduction predicted ataxia severity (SARA:\n                      <jats:italic>r<\/jats:italic>\n                      \u2009=\u2009\u22120.43).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>DFA captures circuit\u2010specific white matter pathology in MSA\u2010C, with brainstem twist emerging as a novel biomarker associated with disease stage. The integration of geometric metrics with automated machine learning provides a robust framework for early diagnosis and disease staging, highlighting distinct neurodegenerative mechanisms in cerebellar versus brainstem pathways.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/cns.70623","type":"journal-article","created":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T05:41:19Z","timestamp":1764567679000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Cerebellar and Brainstem White Matter Geometric Alterations in Multiple System Atrophy: A\n                    <scp>DFA<\/scp>\n                    \u2010Based Biomarker for Disease Staging"],"prefix":"10.1111","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-6719-1044","authenticated-orcid":false,"given":"Hua","family":"Zhu","sequence":"first","affiliation":[{"name":"Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering Beihang University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuxiang","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Neurology, Xuanwu Hospital Capital Medical University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meixin","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine Peking University Third Hospital  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziyan","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Neurology, Xuanwu Hospital Capital Medical University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuxuan","family":"Shao","sequence":"additional","affiliation":[{"name":"Department of Neurology, Xuanwu Hospital Capital Medical University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinxi","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Software Beihang University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Liu","sequence":"additional","affiliation":[{"name":"Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering Beihang University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haogang","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering Beihang University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ni","family":"Shu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Cognitive Neuroscience and Learning &amp; 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