{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T12:28:02Z","timestamp":1780057682300,"version":"3.54.0"},"reference-count":32,"publisher":"Oxford University Press (OUP)","issue":"1171","license":[{"start":{"date-parts":[[2025,4,15]],"date-time":"2025-04-15T00:00:00Z","timestamp":1744675200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100004440","name":"Wellcome","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004440","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Engineering and Physical Sciences Research Council Centre for Medical Engineering at King\u2019s College London","award":["WT 203148\/Z\/16\/Z"],"award-info":[{"award-number":["WT 203148\/Z\/16\/Z"]}]},{"DOI":"10.13039\/100014461","name":"National Institute for Health Research Biomedical Research Centre","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100014461","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guy\u2019s & St Thomas\u2019 Hospitals and King\u2019s College London"},{"name":"Cancer Research UK National Cancer Imaging Translational Accelerator","award":["A27066"],"award-info":[{"award-number":["A27066"]}]},{"name":"UK Research & Innovation London Medical Imaging and Artificial Intelligence Centre"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,7,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objectives<\/jats:title>\n                  <jats:p>To establish how MRI descriptors on standard MRI sequences can be optimally combined to predict idiopathic intracranial hypertension (IIH).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>A retrospective single-institution cross-sectional study evaluated consecutive IIH patients undergoing MRI between 2002 and 2015 and a control group. Six established and 8 exploratory MRI descriptors were evaluated. Two observers independently analysed MRI descriptors on T1w sagittal and T2w axial sequences while blinded to clinical data with consensus obtained. Inter-rater reliability was calculated, and the presence of MRI descriptors was compared between IIH patients and controls (Bonferroni correction, P\u2009&amp;lt;\u20090.004). Forward stepwise logistic regression determined which combination of MRI descriptors best predicted IIH.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Fifty-four IIH patients (mean age 31.2, standard deviation 10.2, 3 men) and 54 control subjects (mean age 31.7, standard deviation 7.1, 3 men) were evaluated. There was excellent inter-rater reliability for 13\/14 MRI descriptors. There were 4\/6 established and 6\/8 exploratory MRI descriptors associated with IIH (P\u2009&amp;lt;\u20090.004). The optimal combination of descriptors to predict IIH was vertical tortuosity of the optic nerve, enlarged optic nerve sheath, globe flattening score \u2265 2, Yuh score \u2265 3, cervical skin folding, and cervical fat thickness \u2265 10.5\u2009mm. The model correctly classified 93.5% of cases (sensitivity 94.4%, specificity 92.6%, area under the receiver operating characteristic curve [AUC] 0.965).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>Evaluating a combination of vertical tortuosity of the optic nerve, enlarged optic nerve sheath, globe flattening, Yuh score, cervical skin folding, and cervical fat thickness optimally predicts IIH.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Advances in knowledge<\/jats:title>\n                  <jats:p>New MRI features are validated for the diagnosis of IIH and the optimal combination for diagnosis is established.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Registration number<\/jats:title>\n                  <jats:p>N006 (local institutional review). The full study protocol can be requested from the corresponding author.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bjr\/tqaf080","type":"journal-article","created":{"date-parts":[[2025,4,15]],"date-time":"2025-04-15T18:41:51Z","timestamp":1744742511000},"page":"1070-1079","source":"Crossref","is-referenced-by-count":3,"title":["How can MRI descriptors be optimally combined to predict idiopathic intracranial hypertension?"],"prefix":"10.1093","volume":"98","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5006-4342","authenticated-orcid":false,"given":"George G","family":"Bitar","sequence":"first","affiliation":[{"name":"Department of Radiology, University College London Hospitals NHS Foundation Trust, London, NW1 2BU,","place":["United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Philip","family":"Touska","sequence":"additional","affiliation":[{"name":"Department of Radiology, Guy\u2019s and St Thomas\u2019 Hospitals NHS Foundation Trust, 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