{"id":3767,"date":"2022-10-21T12:23:18","date_gmt":"2022-10-21T10:23:18","guid":{"rendered":"https:\/\/staging.mediaire.ai\/?p=3767"},"modified":"2025-09-03T09:12:07","modified_gmt":"2025-09-03T07:12:07","slug":"artificial-intelligence-substantially-improves-differential-diagnosis-of-dementiaadded-diagnostic-value-of-rapid-brain-volumetry","status":"publish","type":"post","link":"https:\/\/mediaire.ai\/en\/artificial-intelligence-substantially-improves-differential-diagnosis-of-dementiaadded-diagnostic-value-of-rapid-brain-volumetry\/","title":{"rendered":"Artificial intelligence substantially improves differential diagnosis of dementia\u2013added diagnostic value of rapid brain volumetry"},"content":{"rendered":"\t\t
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Published in<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Clinical Neuroradiology, 31(Supplement 1), 21-22. (2021)<\/p>\n

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Authors<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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J.\u00a0<\/span>Rudolph, J. R\u00fcckel, J. D\u00f6pfert, X. Ling, J. Opalka, C. Brem et al.<\/p>\n

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Abstract<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Purpose<\/p>\n

Brain volumetry is a key aspect in dementia diagnostics. We applied an artificial intelligence (AI) system based on a Convolutional Neural Network (CNN) which aims to perform lobe-separated rapid brain volumetry (< 1\/2 h) of three-dimensional T1-weighted magnetic resonance imaging (MRI) with automated segmentation as well as comparison to age- and gender-adapted percentiles. Our aim was to quantify the added value in the differential diagnostics of dementia.<\/p>\n

Materials & Methods<\/p>\n

A total of 55 patients\u201317 with confirmed diagnosis of Alzheimer\u2019s disease (AD), 18 with confirmed diagnosis of frontotemporal dementia (FTD) and 20 healthy controls\u2013received T1-weighted three-dimensional magnetization prepared\u2013rapid gradient echo (MPRAGE) MRI. Images were retrospectively assessed by one board-certified neuroradiologist (BCNR) and two radiology residents (RR)\u2013 one of whom had received 6 months of neuroradiology training (RR1). All cases were evaluated in a two-step reading process\u2013beginning without AI- support and followed by an AI- supported reading (AI tool: mdbrain version 3.3.0). For each subject, the suspected diagnostic category (AD, FTD and healthy controls) was determined using a likelihood score (0\u20135), adding up to a sum of 5 for all three diagnostic categories. Individual reader performance with and without AI support was statistically evaluated using receiver operating characteristics (ROC).<\/p>\n

Results<\/p>\n

AI support substantially improved AD diagnosis in all three readers. The effect was most pronounced for RR2 who had not undergone neuroradiology training (area under the curve [AUC] without AI support [\u2013 AI]: 0.629, AI supported [+ AI]: 0.885). But, even for the BCNR, a substantial benefit was measurable (AUCs: BCNR\u2014 AI: 0.827, + AI: 0.882; RR1\u2014AI: 0.713, + AI: 0.834). In diagnosing FTD RR2 improved with AI support (AUCs:\u2014AI: 0.610, + AI: 0.754), while BCNR and RR1 had comparable reading performances with and without AI support (AUCs: BCNR\u2014 AI: 0.843, + AI: 0.828; RR1\u2014AI: 0.865, + AI: 0.868).<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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ROC curves for diagnostic precision of differentiation from healthy to AD patients (left) and FTD patients (right) for radiologists with different levels of training (RR2= 1st year resident, RR1= radiologist; BCNR = neuroradiologist); dashed lines without mdbrain, solid lines with AI support by mdbrain.<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Discussion<\/p>\n

Even experienced BCNR can improve their diagnostic accuracy for AD by using AI based rapid brain volumetry and comparison with the age- and gender-matched reference cohorts. In diagnosing FTD, especially radiologists who are less experienced in dementia differential diagnosis can strongly benefit from AI support. Conclusion: AI support in the radiological work-up of dementia patients is feasible and can substantially improve diagnostic accuracy, which might lead to earlier diagnosis and therefore optimized patient management.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tFind out more<\/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":"

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>","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-3767","post","type-post","status-publish","format-standard","hentry","category-publications"],"acf":[],"_links":{"self":[{"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/posts\/3767","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=3767"}],"version-history":[{"count":5,"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/posts\/3767\/revisions"}],"predecessor-version":[{"id":21641,"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/posts\/3767\/revisions\/21641"}],"wp:attachment":[{"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/media?parent=3767"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/categories?post=3767"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/tags?post=3767"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}