Ozge Can Kaplan, Dilek Betul Arslan, Sevim Cengiz, Ani Kiçik, Emel Erdogdu, G. H. Hatay, Z. Tufekcioglu, B. Bilgiç, H. Hanagasi, H. Gurvit, T. Demiralp, A. Uluğ, E. O. Isik
{"title":"Determination of Diffusion Weighted Magnetic Resonance Imaging Based Biomarkers of Mild Cognitive Impairment in Parkinson’s Disease","authors":"Ozge Can Kaplan, Dilek Betul Arslan, Sevim Cengiz, Ani Kiçik, Emel Erdogdu, G. H. Hatay, Z. Tufekcioglu, B. Bilgiç, H. Hanagasi, H. Gurvit, T. Demiralp, A. Uluğ, E. O. Isik","doi":"10.1109/BIYOMUT.2017.8479249","DOIUrl":null,"url":null,"abstract":"This study aims to specify biomarkers of Parkinson's disease mild cognitive impairment (PD-MCI) based on fractional anisotropy (FA) and mean diffusivity (MD) maps obtained from diffusion weighted magnetic resonance imaging (DWMRI). T1 and diffusion weighted MR images collected from 27 cognitively normal Parkinson's disease (PD-CN), 32 mild cognitively impaired Parkinson's disease (PD-MCI), and 18 healthy control (HC) volunteers, at a clinical 3T MR scanner, were processed using FMRIB Software Library (FSL)'s toolboxes. Average regional values of FA and MD maps and tract based spatial statistics (TBSS) were utilized to define statistically significant differences between the participant subject groups.","PeriodicalId":330319,"journal":{"name":"2017 21st National Biomedical Engineering Meeting (BIYOMUT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 21st National Biomedical Engineering Meeting (BIYOMUT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIYOMUT.2017.8479249","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study aims to specify biomarkers of Parkinson's disease mild cognitive impairment (PD-MCI) based on fractional anisotropy (FA) and mean diffusivity (MD) maps obtained from diffusion weighted magnetic resonance imaging (DWMRI). T1 and diffusion weighted MR images collected from 27 cognitively normal Parkinson's disease (PD-CN), 32 mild cognitively impaired Parkinson's disease (PD-MCI), and 18 healthy control (HC) volunteers, at a clinical 3T MR scanner, were processed using FMRIB Software Library (FSL)'s toolboxes. Average regional values of FA and MD maps and tract based spatial statistics (TBSS) were utilized to define statistically significant differences between the participant subject groups.