{"id":21507,"date":"2024-07-03T18:00:00","date_gmt":"2024-07-03T16:00:00","guid":{"rendered":"https:\/\/mediaire.ai\/?p=21507"},"modified":"2025-09-03T09:04:17","modified_gmt":"2025-09-03T07:04:17","slug":"brain-and-ventricle-volume-alterations-in-idiopathic-normal-pressure-hydrocephalus-determined-by-artificial-intelligence-based-mri-volumetry","status":"publish","type":"post","link":"https:\/\/mediaire.ai\/en\/brain-and-ventricle-volume-alterations-in-idiopathic-normal-pressure-hydrocephalus-determined-by-artificial-intelligence-based-mri-volumetry\/","title":{"rendered":"Brain and Ventricle Volume Alterations in Idiopathic Normal Pressure Hydrocephalus Determined by Artificial Intelligence-Based MRI Volumetry"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"21507\" class=\"elementor elementor-21507\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-dd3ab7d elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"dd3ab7d\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-8fc7c79\" data-id=\"8fc7c79\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-66882e6 elementor-widget elementor-widget-heading\" data-id=\"66882e6\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Published in<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-708ca13 elementor-widget elementor-widget-text-editor\" data-id=\"708ca13\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><em>Diagnostics<\/em> 2024, <em>14<\/em>, 1422. https:\/\/doi.org\/10.3390\/diagnostics14131422<\/p>\n<p><!-- \/wp:paragraph --><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0646ca2 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"0646ca2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-16c8e6c elementor-widget elementor-widget-heading\" data-id=\"16c8e6c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Authors<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-00b6282 elementor-widget elementor-widget-text-editor\" data-id=\"00b6282\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><!-- wp:heading --><\/p>\n<p>Bendella, Z., Purrer, V., Haase, R., Z\u00fclow, S., Kindler, C., Borger, V., Banat, M., Dorn, F., W\u00fcllner, U., Radbruch, A., et al.<\/p>\n<p><!-- \/wp:paragraph --><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-86510d2 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"86510d2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0260970 elementor-widget elementor-widget-heading\" data-id=\"0260970\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Abstract<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1a8bbf3 elementor-widget elementor-widget-text-editor\" data-id=\"1a8bbf3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The aim of this study was to employ artificial intelligence (AI)-based magnetic resonance imaging (MRI) brain volumetry to potentially distinguish between idiopathic normal pressure hydrocephalus (iNPH), Alzheimer\u2019s disease (AD), and age- and sex-matched healthy controls (CG) by evaluating cortical, subcortical, and ventricular volumes.<\/p>\n<p>Additionally, correlations between the measured brain and ventricle volumes and two established semi-quantitative radiologic markers for iNPH were examined. An IRB-approved retrospective analysis was conducted on 123 age- and sex-matched subjects (41 iNPH, 41 AD, and 41 controls), with all of the iNPH patients undergoing routine clinical brain MRI prior to ventriculoperitoneal shunt implantation. Automated AI-based determination of different cortical and subcortical brain and ventricular volumes in mL, as well as calculation of population-based normalized percentiles according to an embedded database, was performed; the CE-certified software mdbrain v4.4.1 or above was used with a standardized T1-weighted 3D magnetization-prepared rapid gradient echo (MPRAGE) sequence.<\/p>\n<p>Measured brain volumes and percentiles were analyzed for between-group differences and correlated with semi-quantitative measurements of the Evans\u2019 index and corpus callosal angle: iNPH patients exhibited ventricular enlargement and changes in gray and white matter compared to AD patients and controls, with the most significant differences observed in total ventricular volume (+67%) and the lateral (+68%), third (+38%), and fourth (+31%) ventricles compared to controls.<\/p>\n<p>Global ventriculomegaly and marked white matter reduction with concomitant preservation of gray matter compared to AD and CG were characteristic of iNPH, whereas global and frontoparietally accentuated gray matter reductions were characteristic of AD. Evans\u2019 index and corpus callosal angle differed significantly between the three groups and moderately correlated with the lateral ventricular volumes in iNPH patients [Evans\u2019 index (r &gt; 0.83, <span class=\"html-italic\">p<\/span> \u2264 0.001), corpus callosal angle (r &lt; \u22120.74, <span class=\"html-italic\">p<\/span> \u2264 0.001)].<\/p>\n<p>AI-based MRI volumetry in iNPH patients revealed global ventricular enlargement and focal brain atrophy, which, in contrast to healthy controls and AD patients, primarily involved the supratentorial white matter and was marked temporomesially and in the midbrain, while largely preserving gray matter. Integrating AI volumetry in conjunction with traditional radiologic measures could enhance iNPH identification and differentiation, potentially improving patient management and therapy response assessment.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0a4e542 elementor-mobile-align-left elementor-widget elementor-widget-button\" data-id=\"0a4e542\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;_animation&quot;:&quot;none&quot;}\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/www.mdpi.com\/2075-4418\/14\/13\/1422\" target=\"_blank\" download=\"poster_effectofmriacquisition.pdf\" rel=\"nofollow noopener\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Read Full Publication<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>The aim of this study was to employ artificial intelligence (AI)-based magnetic resonance imaging (MRI) brain volumetry to potentially distinguish between idiopathic normal pressure hydrocephalus (iNPH), Alzheimer\u2019s disease (AD), and age- and sex-matched healthy controls (CG) by evaluating cortical, subcortical, and ventricular volumes.<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[14],"tags":[],"class_list":["post-21507","post","type-post","status-publish","format-standard","hentry","category-publications"],"acf":[],"_links":{"self":[{"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/posts\/21507","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/comments?post=21507"}],"version-history":[{"count":6,"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/posts\/21507\/revisions"}],"predecessor-version":[{"id":21623,"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/posts\/21507\/revisions\/21623"}],"wp:attachment":[{"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/media?parent=21507"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/categories?post=21507"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/tags?post=21507"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}