{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T11:14:01Z","timestamp":1765278841343,"version":"3.46.0"},"posted":{"date-parts":[[2025,12,2]]},"group-title":"Radiology and Imaging","reference-count":20,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T00:00:00Z","timestamp":1764633600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2025,12,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Idiopathic normal pressure hydrocephalus (iNPH) is a reversible cause of dementia in older adults yet remains underdiagnosed due to nonspecific clinical presentation and reliance on invasive confirmatory tests. Conventional MRI biomarkers, including the Evans index and callosal angle, capture ventricular enlargement but incompletely characterize cerebrospinal fluid (CSF) redistribution. Disproportionately enlarged subarachnoid-space hydrocephalus (DESH) features, tight high-convexity sulci and enlarged Sylvian fissures, are more disease-specific but lack standardized quantitative measures.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>We developed the Disproportionately Elevated Sulcal Index (DESI), an automated volumetric biomarker quantifying the ratio of Sylvian fissure volume to superior sulcal space volume. T1-weighted MRI scans were acquired from three independent cohorts: the Baltimore Longitudinal Study of Aging (n = 1,032), Johns Hopkins CSF Disorders Clinic (n = 216), and the Placebo-controlled Efficacy of iNPH Shunting trial (n = 94). Preprocessing included N4 bias correction, standard-space registration, and alignment. A U-Net segmentation model with an EfficientNet-B0 encoder delineated Sylvian fissures and sulcal compartments. DESI was computed from 3D reconstructions and evaluated using Dice similarity coefficients, landmark detection error, and classification performance across diagnostic groups.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Segmentation achieved \u223c0.80 DICE for Sylvian fissures; \u223c0.74 for superior sulci. On external validation, DESI discriminated NPH with DESH from non-DESH NPH with AUC = 0.99, accuracy 97.9%, and from all other groups (healthy controls, Alzheimer\u2019s disease, vascular dementia) with perfect classification (AUC = 1.00, 100% sensitivity and specificity at threshold = 4.83). In cognitively normal adults, DESI showed only a modest age-related increase and no sex differences, confirming specificity for hydrocephalic pathology.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>DESI is a robust, fully automated MRI biomarker that sensitively detects CSF redistribution characteristic of DESH in iNPH. By outperforming traditional indices and achieving near-perfect diagnostic accuracy across independent cohorts, DESI offers a noninvasive tool for early detection, patient selection for shunting, and longitudinal monitoring of disease progression.<\/jats:p>\n                <\/jats:sec>","DOI":"10.64898\/2025.12.01.25341388","type":"posted-content","created":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T11:07:19Z","timestamp":1765278439000},"source":"Crossref","is-referenced-by-count":0,"title":["Disproportionately Elevated Sulcal Index (DESI): An automatically driven index representing disproportionate subarachnoid space enlargement in brain MRI scans"],"prefix":"10.64898","author":[{"given":"Siavash Shirzadeh","family":"Barough","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shin","family":"Ohno","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5042-7422","authenticated-orcid":false,"given":"Murat","family":"Bilgel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haris I.","family":"Sair","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mark G.","family":"Luciano","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9464-1551","authenticated-orcid":false,"given":"Abhay","family":"Moghekar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"54368","reference":[{"key":"2025120903034418000_2025.12.01.25341388v1.1","first-page":"761","article-title":"Normal-pressure hydrocephalus","volume":"12","year":"2001","journal-title":"Neurosurgery Clinics"},{"key":"2025120903034418000_2025.12.01.25341388v1.2","unstructured":"Das, J. M. & Biagioni, M. C. Normal pressure hydrocephalus. in StatPearls [Internet] (StatPearls Publishing, 2023)."},{"key":"2025120903034418000_2025.12.01.25341388v1.3","doi-asserted-by":"publisher","DOI":"10.1186\/2045-8118-9-1"},{"key":"2025120903034418000_2025.12.01.25341388v1.4","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0217705"},{"key":"2025120903034418000_2025.12.01.25341388v1.5","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.0000000000000342"},{"key":"2025120903034418000_2025.12.01.25341388v1.6","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-008-1044-4"},{"key":"2025120903034418000_2025.12.01.25341388v1.7","doi-asserted-by":"publisher","DOI":"10.1186\/1743-8454-7-S1-S18"},{"key":"2025120903034418000_2025.12.01.25341388v1.8","doi-asserted-by":"publisher","DOI":"10.1093\/gerona\/63.12.1416"},{"key":"2025120903034418000_2025.12.01.25341388v1.9","unstructured":"Luciano, M. G. et al. A Randomized Trial of Shunting for Idiopathic Normal-Pressure Hydrocephalus. New England Journal of Medicine (2025)."},{"key":"2025120903034418000_2025.12.01.25341388v1.10","first-page":"1","article-title":"N4ITK: Nick\u2019s N3 ITK implementation for MRI bias field correction","volume":"9","year":"2009","journal-title":"Insight Journal"},{"key":"2025120903034418000_2025.12.01.25341388v1.11","doi-asserted-by":"crossref","unstructured":"shirzadeh barough, siavash et al. BrainSignsNET: A Deep Learning Model for 3D Anatomical Landmark Detection in the Human Brain Imaging. medRxiv 2025\u20132027 (2025).","DOI":"10.1101\/2025.07.31.25332457"},{"key":"2025120903034418000_2025.12.01.25341388v1.12","doi-asserted-by":"crossref","unstructured":"Ronneberger, O. , Fischer, P. & Brox, T. U-net: Convolutional networks for biomedical image segmentation. in International Conference on Medical image computing and computer-assisted intervention 234\u2013241 (Springer, 2015).","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"2025120903034418000_2025.12.01.25341388v1.13","doi-asserted-by":"crossref","first-page":"1362637","DOI":"10.3389\/fnagi.2024.1362637","article-title":"Automatic assessment of disproportionately enlarged subarachnoid-space hydrocephalus from 3D MRI using two deep learning models","volume":"16","year":"2024","journal-title":"Front Aging Neurosci"},{"key":"2025120903034418000_2025.12.01.25341388v1.14","doi-asserted-by":"crossref","first-page":"101605","DOI":"10.1016\/j.nicl.2018.11.015","article-title":"Automated detection of imaging features of disproportionately enlarged subarachnoid space hydrocephalus using machine learning methods","volume":"21","year":"2019","journal-title":"Neuroimage Clin"},{"key":"2025120903034418000_2025.12.01.25341388v1.15","doi-asserted-by":"crossref","first-page":"889","DOI":"10.2174\/1573405616666201223150004","article-title":"The differential diagnostic value of the callosal angle and Evans index in mild cognitive impairment and Alzheimer\u2019s disease","volume":"17","year":"2021","journal-title":"Curr Med Imaging Rev"},{"key":"2025120903034418000_2025.12.01.25341388v1.16","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A4695"},{"key":"2025120903034418000_2025.12.01.25341388v1.17","doi-asserted-by":"crossref","first-page":"1241237","DOI":"10.3389\/fnagi.2023.1241237","article-title":"Comparison of cerebrospinal fluid space between probable normal pressure hydrocephalus and Alzheimer\u2019s disease","volume":"15","year":"2023","journal-title":"Front Aging Neurosci"},{"key":"2025120903034418000_2025.12.01.25341388v1.18","doi-asserted-by":"publisher","DOI":"10.2176\/nmc.52.775"},{"key":"2025120903034418000_2025.12.01.25341388v1.19","doi-asserted-by":"publisher","DOI":"10.1016\/j.clineuro.2017.04.015"},{"key":"2025120903034418000_2025.12.01.25341388v1.20","doi-asserted-by":"crossref","first-page":"umae027","DOI":"10.1093\/radadv\/umae027","article-title":"Deep learning assessment of disproportionately enlarged subarachnoid-space hydrocephalus in Hakim\u2019s disease or idiopathic normal pressure hydrocephalus","volume":"1","year":"2024","journal-title":"Radiology Advances"}],"container-title":[],"original-title":[],"link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.64898\/2025.12.01.25341388","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T11:07:22Z","timestamp":1765278442000},"score":1,"resource":{"primary":{"URL":"http:\/\/medrxiv.org\/lookup\/doi\/10.64898\/2025.12.01.25341388"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,2]]},"references-count":20,"URL":"https:\/\/doi.org\/10.64898\/2025.12.01.25341388","relation":{},"subject":[],"published":{"date-parts":[[2025,12,2]]},"subtype":"preprint"}}