Indirect Assessment of Hyperechogenicity of Substantia Nigra Utilizing Sleep-based Biomarkers

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dc.contributor.authorMikulec, Marekcs
dc.contributor.authorMekyska, Jiřícs
dc.contributor.authorGaláž, Zoltáncs
dc.date.accessioned2025-04-04T11:56:30Z
dc.date.available2025-04-04T11:56:30Z
dc.date.issued2024-01-03cs
dc.description.abstractTranscranial sonography of the substantia nigra (TCS-SN) may serve as a suitable test for screening groups at a high risk of developing Lewy body diseases (LBDs) such as Parkinson's disease or dementia with Lewy bodies. Although one of the most prominent early markers of these neurodegenerative disorders is the idiopathic rapid eye movement (REM) sleep behavior disorder, the relationship between TCS-SN and sleep alterations has not been fully explored. The aim of this study is to investigate whether sleep-based biomarkers could be used to stratify subjects into three groups with different echogenic areas of the substantia nigra. To achieve this goal, we enrolled 93 participants who underwent TCS-SN and 7-night actigraphy. Additionally, participants completed a sleep diary and the REM sleep behavior disorder screening questionnaire. To assess the severity of pathological echogenicity, we employed a machine learning algorithm utilizing the XGBoost algorithm. The results show that a multimodal assessment of sleep was able to predict the outcomes of TCS-SN with a balanced accuracy of 96 %. Overall, these findings underscore the potential of a comprehensive approach to model the results of TCS-SN and its implications for the prodromal diagnosis of LBDs.en
dc.formattextcs
dc.format.extent1-6cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citation2023 14th International Conference on Intelligent Systems: Theories and Applications (SITA). 2024, p. 1-6.en
dc.identifier.doi10.1109/SITA60746.2023.10373593cs
dc.identifier.isbn9798350308211cs
dc.identifier.orcid0000-0002-9405-9796cs
dc.identifier.orcid0000-0002-6195-193Xcs
dc.identifier.orcid0000-0002-8978-351Xcs
dc.identifier.other188163cs
dc.identifier.researcheridK-4001-2015cs
dc.identifier.researcheridT-8761-2019cs
dc.identifier.scopus35746344400cs
dc.identifier.scopus56888706700cs
dc.identifier.urihttps://hdl.handle.net/11012/250745
dc.language.isoencs
dc.publisherInstitute of Electrical and Electronics Engineers Inc.cs
dc.relation.ispartof2023 14th International Conference on Intelligent Systems: Theories and Applications (SITA)cs
dc.relation.urihttps://doi.org/10.1109/SITA60746.2023.10373593cs
dc.rights(C) Institute of Electrical and Electronics Engineers Inc.cs
dc.rights.accessopenAccesscs
dc.subjectactigraphyen
dc.subjectLewy body diseasesen
dc.subjectREM sleep behavior disorderen
dc.subjectscreening questionnairesen
dc.subjectsleep diaryen
dc.subjectsubstantia nigraen
dc.subjecttranscranial sonographyen
dc.titleIndirect Assessment of Hyperechogenicity of Substantia Nigra Utilizing Sleep-based Biomarkersen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionacceptedVersionen
sync.item.dbidVAV-188163en
sync.item.dbtypeVAVen
sync.item.insts2025.04.04 13:56:30en
sync.item.modts2025.04.03 13:32:13en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav telekomunikacícs
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