{
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    "slug": "artificial-intelligence-brain-volumetry-differential-diagnosis-dementia",
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    "link": "https:\/\/mediaire.ai\/de\/artificial-intelligence-brain-volumetry-differential-diagnosis-dementia\/",
    "title": {
        "rendered": "Artificial intelligence\u2013based rapid brain volumetry substantially improves differential diagnosis in dementia"
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        "rendered": "<div data-elementor-type=\"wp-post\" data-elementor-id=\"20269\" class=\"elementor elementor-20269\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-4f80ddb3 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"4f80ddb3\" 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-306b3d44\" data-id=\"306b3d44\" 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-c77e4d0 elementor-widget elementor-widget-heading\" data-id=\"c77e4d0\" 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-0d710b2 elementor-widget elementor-widget-text-editor\" data-id=\"0d710b2\" 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>Alzheimer&#8217;s &amp; Dementia: Diagnosis, Assessment &amp; Disease Monitoring, Volume 16, Issue 4, https:\/\/doi.org\/10.1002\/dad2.70037<\/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-d7cc196 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"d7cc196\" 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-bdcb955 elementor-widget elementor-widget-heading\" data-id=\"bdcb955\" 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-6e9e13a elementor-widget elementor-widget-text-editor\" data-id=\"6e9e13a\" 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>Rudolph, J. 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-d7217bf elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"d7217bf\" 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-91d3115 elementor-widget elementor-widget-heading\" data-id=\"91d3115\" 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-14708ef3 elementor-widget elementor-widget-text-editor\" data-id=\"14708ef3\" 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<div class=\"article-section__content en main\">\n<section id=\"dad270037-sec-0010\" class=\"article-section__content\">\n<h3 id=\"dad270037-sec-0010-title\" class=\"article-section__sub-title section1\">Introduction<\/h3>\n<p>This study evaluates the clinical value of a deep learning\u2013based artificial intelligence (AI) system that performs rapid brain volumetry with automatic lobe segmentation and age- and sex-adjusted percentile comparisons.<\/p>\n<\/section>\n<section id=\"dad270037-sec-0020\" class=\"article-section__content\">\n<h3 id=\"dad270037-sec-0020-title\" class=\"article-section__sub-title section1\">Methods<\/h3>\n<p>Fifty-five patients\u201417 with Alzheimer&#8217;s disease (AD), 18 with frontotemporal dementia (FTD), and 20 healthy controls\u2014underwent cranial magnetic resonance imaging scans. Two board-certified neuroradiologists (BCNR), two board-certified radiologists (BCR), and three radiology residents (RR) assessed the scans twice: first without AI support and then with AI assistance.<\/p>\n<\/section>\n<section id=\"dad270037-sec-0030\" class=\"article-section__content\">\n<h3 id=\"dad270037-sec-0030-title\" class=\"article-section__sub-title section1\">Results<\/h3>\n<p>AI significantly improved diagnostic accuracy for AD (area under the curve \u2212AI: 0.800, +AI: 0.926, <i>p<\/i>\u00a0&lt;\u00a00.05), with increased correct diagnoses (<i>p<\/i>\u00a0&lt;\u00a00.01) and reduced errors (<i>p<\/i>\u00a0&lt;\u00a00.03). BCR and RR showed notable performance gains (BCR: <i>p<\/i>\u00a0&lt;\u00a00.04; RR: <i>p<\/i>\u00a0&lt;\u00a00.02). For the diagnosis FTD, overall consensus (<i>p<\/i> &lt;\u00a00.01), BCNR (<i>p<\/i>\u00a0&lt;\u00a00.02), and BCR (<i>p<\/i>\u00a0&lt;\u00a00.05) recorded significantly more correct diagnoses.<\/p>\n<\/section>\n<section id=\"dad270037-sec-0040\" class=\"article-section__content\">\n<h3 id=\"dad270037-sec-0040-title\" class=\"article-section__sub-title section1\">Discussion<\/h3>\n<p>AI-assisted volumetry improves diagnostic performance in differentiating AD and FTD, benefiting all reader groups, including BCNR.<\/p>\n<\/section>\n<section id=\"dad270037-sec-0050\" class=\"article-section__content\">\n<h3 id=\"dad270037-sec-0050-title\" class=\"article-section__sub-title section1\">Highlights<\/h3>\n<div class=\"paragraph-element\">\n<ul class=\"unordered-list\">\n<li>Artificial intelligence (AI)-supported brain volumetry significantly improved the diagnostic accuracy for Alzheimer&#8217;s disease (AD) and frontotemporal dementia (FTD), with notable performance gains across radiologists of varying expertise levels.<\/li>\n<li>The presented AI tool is readily clinically available and reduces brain volumetry processing time from 12 to 24\u00a0hours to under 5 minutes, with full integration into picture archiving and communication systems, streamlining the workflow and facilitating real-time clinical decision making.<\/li>\n<li>AI-supported rapid brain volumetry has the potential to improve early diagnosis and to improve patient management.<\/li>\n<\/ul>\n<\/div>\n<\/section>\n<\/div>\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-6cc9d84 elementor-mobile-align-left elementor-widget elementor-widget-button\" data-id=\"6cc9d84\" 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:\/\/alz-journals.onlinelibrary.wiley.com\/doi\/10.1002\/dad2.70037\" 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>",
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        "rendered": "<p>This study evaluates the clinical value of a deep learning\u2013based artificial intelligence (AI) system that performs rapid brain volumetry with automatic lobe segmentation and age- and sex-adjusted percentile comparisons.<\/p>",
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