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  • 學位論文

台灣老年人磁核造影影像預測認知功能下降之研究

Magnetic Resonance Imaging Measures Predict Cognitive Decline in Taiwanese Elderly

指導教授 : 程蘊菁
共同指導教授 : 洪弘(Hung Hung)

摘要


研究背景: 台灣老年人口比例逐漸增加,因此老年人相關議題是首當其衝(例如:失智症)。腦中結構的細微變化在失智症發生的初期即可以磁核造影偵測到。過去研究主要以探討腦中特定的區塊,顯少探討這些區塊以外的腦區。因此,本研究旨在探討磁核造影影像與預測認知功能下降之關聯。 材料與方法: 本研究為世代追蹤研究,於基線 (2011¬-2013)至兩年後追蹤 (2013-2015),共招募316位臺大醫院老年健康檢查之65歲以上長者。本研究的結果為測量基線到追蹤之認知功能(包括整體與特定範疇認知功能,例如: 記憶、語言流暢、執行功能和專注力)下降。於基線期間進行磁核造影,總共測量114個腦體積與68個腦厚度變項。利用因素分析萃取認知功能因子。切片逆回歸方式將磁核造影影像降維成磁核造影因子。以多變項線性與邏輯式回歸模型評估磁核造影影像與認知功能下降之關聯性,並針對重要混淆因子進行分層分析,例如:年齡 (<75歲、≧75歲)、性別與載脂蛋白E (APOE ε4)狀態。 結果: 本研究經因素分析後得到四個認知功能範疇因子 (記憶、語言流暢、執行功能和專注)。每增加一單位MRI因素1 (包括:邊緣系統、 腦島與前額葉區塊)可減少整體性認知功能下降 (迴歸係數 = 0.002);每增加一單位MRI因素3 (包括:邊緣系統與前額葉區塊)可減少整體性認知功能下降 (調整勝算比= 0.75)。每增加一單位MRI因素3 (包括:邊緣系統、前額葉與顳葉區塊)可預測記憶功能下降 (迴歸係數 = -0.34,調整勝算比 =1.79);每增加一單位MRI因素2 (包括:頂葉、前額葉與顳葉區塊)可預測記憶功能下降 (調整勝算比= 1.59)。每增加一單位MRI因素1 (包括:邊緣系統與顳葉區塊)可預測語言流暢功能下降 (迴歸係數 = -0.20);然而,每增加一單位MRI因素3 (包括:前額葉與頂葉區塊)可減少語言流暢功能下降 (迴歸係數 =0.18,調整勝算比 =0.58)。每增加一單位MRI因素1 (包括:前額葉、與顳葉區塊)可預測執行功能下降(調整勝算比 =0.65)。每增加一單位MRI因素1 (包括:伏隔核、顳葉與前額葉區塊)可減少執行功能下降 (迴歸係數 =0.29,調整勝算比 =0.49);然而,每增加一單位MRI因素3 (包括:第五腦室、顳葉與前額葉區塊)可預測專注功能下降 (迴歸係數 =-0.11)。 結論: 本研究是第一篇以無假設的方法來辨認磁核造影生物標記。本研究大部分的發現與先前研究相同 (例如:前額葉、顳葉和邊緣系通區塊),除了在邊緣系統、伏隔核、腦室、距狀溝與眼眶額葉皮質區塊目前尚未在未失智老年人中發現與認知下降有關。這些相關發現在較老的族群 (年齡≧75歲)、女性與帶有APOEε4基因者依舊存在。因此,本研究可早期偵測與預防老年人認知功能缺損情況。

並列摘要


Background: The proportion of elders in Taiwan increase rapidly and thus age-related health issues (e.g., dementia) become an important topic in the elderly. Brain structural changes begin at the early stage of dementia, and magnetic resonance imaging (MRI) technique can identify these subtle changes. Previous studies using MRI on brain regions of interest, and thus the remaining regions are less explored. Therefore, this study aims to explore the association between MRI measures and cognitive decline in Taiwanese elders. Methods: This cohort study recruited 316 participants aged 65 or older from the annual Elderly Health Checkup Program at National Taiwan University Hospital from 2011 to 2013 (baseline) and followed up from 2013 to 2015. The outcome of this study is global and domain-specific (memory, verbal fluency, executive function and attention) cognitive decline from baseline to follow-up. MRI scans were performed at baseline with a total of 114 volume variables and 68 thickness variables. Factor analysis was performed to identify cognitive factors. Slice inverse regression was performed for dimension reduction of MRI variables to identify MRI factors. Multivariable linear and logistic regressions were used to assess the association between MRI measures and cognitive decline. Stratified analyses were performed by important confounders, which included age groups (<75 and ≧75 years old), sex, and apolipoprotein E (APOE) ε4 status. Results: Four cognitive factors (memory, verbal fluency, executive function and attention factors) were identified by factor analysis. One unit increase in MRI factors 1 (including limbic, insula and frontal regions) protected against the decline of global cognition (MoCA-T, β= 0.002); one unit increase in MRI factor 3 (including limbic and frontal regions) showed similar finding [MoCA-T, adjusted odds ratio (AOR) = 0.75]. One unit increase in MRI factors 3 (including limbic, frontal and temporal regions) was associated with decline of memory factor (β= -0.34, AOR = 1.79); one unit increase in MRI factor 2 (including parietal, frontal and temporal regions) showed similar finding (AOR = 1.59). One unit increase in MRI factor 1 (including limbic and temporal regions) was associated with the decline of verbal fluency factor (β= -0.20). While one unit increase in MRI factor 3 (including frontal and temporal regions) protected against the decline of verbal fluency factor (β= 0.18, AOR = 0.58). One unit increase in MRI factors 1 (including frontal and temporal regions) was associated with the decline of executive function factor (AOR = 0.65). One unit increase in MRI factors 1 (including accumbens, temporal and frontal regions) protected against the decline of attention factor (β= 0.29, AOR = 0.49), while one unit increase in MRI factors 3 (including 5th ventricle, frontal and temporal regions) was associated with decline of attention factor (β= -0.11). Conclusion: This study used hypothesis-free approach to identify MRI markers. Most of our findings are consist with previous studies (e.g., frontal, temporal, and limbic regions) except limbic, accumbens, ventricles, pericalcarine and pars orbitalis regions have not been related to early cognitive decline in non-demented elderly previously. Finding remain significant especially in older group (ages≧75), women, and APOE ε4 carriers. Our findings are useful for early detection and prevention of dementia in the elderly.

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