کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5738760 | 1615054 | 2017 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Identifying the presence of Parkinson's disease using low-frequency fluctuations in BOLD signals
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کلمات کلیدی
Parkinson’s disease - بیماری پارکینسونResting-state functional magnetic resonance imaging - تصویربرداری رزونانس مغناطیسی عملکرد حالت حالت استراحتFractional amplitude of low-frequency fluctuations - دامنه فراوانی نوسانات فرکانس پایینamplitude of low-frequency fluctuations - دامنه نوسانات فرکانس پایین
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب (عمومی)
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Parkinson's disease (PD) is a chronic, progressive, and degenerative neurological disorder that is characterized by the degeneration of dopamine neurons in the substantia nigra and the formation of intracellular Lewy inclusion bodies. Resting-state functional magnetic resonance imaging (RS-fMRI) has demonstrated evidence of changes in metabolic patterns in individuals with PD. The purpose of this study was to determine whether the presence of PD could be “predicted” based on resting fluctuations in the blood oxygenation level dependent signal. We utilized RS-fMRI to measure the amplitude of low-frequency fluctuation (ALFF) and the fractional ALFF (fALFF) in 51 patients with PD and 50 age- and sex-matched healthy controls. Compared with the healthy controls, the individuals with PD exhibited altered ALFFs in the bilateral lingual gyrus and left putamen and an altered fALFF in the right cerebellum posterior lobe. Support vector machines (SVMs), which comprise a supervised pattern recognition method that enables predictions at the individual level, were trained to separate individuals with PD from healthy controls based on the ALFF and fALFF. Using the leave-one-out cross-validation method to analyze our sample, we reliably distinguished the participants with PD from the controls with 92% sensitivity and 87% specificity. Overall, these findings suggest that the SVM-neuroimaging approach may be of particular clinical value because it enables the accurate identification of PD at the individual level. RS-fMRI should be considered for development as a biomarker and an analytical tool for the evaluation of PD.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neuroscience Letters - Volume 645, 3 April 2017, Pages 1-6
Journal: Neuroscience Letters - Volume 645, 3 April 2017, Pages 1-6
نویسندگان
Yan Tang, Li Meng, Chang-min Wan, Zhen-hua Liu, Wei-hua Liao, Xin-xiang Yan, Xiao-yu Wang, Bei-sha Tang, Ji-feng Guo,