缺血性中風之異常腦功能網路分析

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蔡文千(Wen-Chien Tsai) 查詢紙本館藏

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電機工程學系

論文名稱

缺血性中風之異常腦功能網路分析
(Disrupted brain functional connectivity networks in ischemic stroke patients)

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摘要(中)

缺血性腦中風倖存病人往往面臨到程度不一上下肢偏癱的困擾，中風後三到六個月間是復原的關鍵。本研究欲透過靜息態功能性磁振照影 (resting-state functional magnetic resonance imaging , rs-fMRI) 搭配圖論的拓樸特性分析來了解復原機制。由於過去文獻較少探討網路的動態變化，本研究蒐集了三個時間點 (中風後數天、1個月、3個月) 的rs-fMRI以及運動功能量表，並搭配機器學習來開發上肢運動預後模型。研究結果顯示病患與健康組功能性網路皆呈現小世界網路特性、兩者間全域特性沒有差異，然而病患具異常的區域拓樸特性，發生於中風後1個月前後，此時間點也是兩半球不對稱活化、病患組間差異最明顯的時期。患者組間的樞紐變化情形相近，腦島、扣帶區域內樞紐顯著增加、感覺運動皮質區略為增加。與右半球相比，左半球出現更大規模的功能性網路重組，說明兩半球之間的復原機制可能有所不同。值得注意的是當運動功能下降時，跨半球間的扣帶迴與運動皮質區的連接強度上升、跨半球運動皮質間連接強度下降。本研究將功能性連接視為特徵所提出新的上肢預後模型具有高度預測力，適用於單側偏癱患者。以上結果將爲亞急性缺血性患者的動態功能性網路重組帶來新的見解。

摘要(英)

Hemiparesis are common in survivors of ischemic stroke patients, days to three to six months of recovery after stroke is crucial. By using resting-state functional magnetic resonance imaging and graph theoretical analysis, we investigated the topology properties underlying the functional networks to interpret the recovery mechanism. Since little is known about the dynamic alterations during this period, we assessed three time points (i.e. days, 1 month, and 3 months after stroke) scans and motor function evaluations in this study. Following by the acquired information, we aimed to develop a machine learning model for upper limb prognosis. Results showed that functional networks of patients and normal controls (NC) were both small-world organization, and there was no significant global topologies difference among the groups. Both the local dysfunctions and the most asymmetrical distribution of homotopic hubs occurred at 1 month after stroke. Alterations of hub regions across patient groups were approximately consistent, suggesting the number of hubs tend to considerably increased within insula, cingulate, and slightly increased in sensorimotor regions among ischemic stroke patients. Compared with right hemisphere, a larger-scale of reorganizations appeared in the left hemisphere, indicating there were possibly different recovery processes. It is worth noting that the inter-hemispheric functional connections between PCG.R and M1 regions were negatively correlated with FMA-UE while the inter-hemispheric ones between M1 regions and M1 regions were positively correlated with FMA-UE. A new method with the affiliated funciotnal connections specified as features, highly predictive Machine Learning models applied to unilateral hemiparesis patients were proposed in this study. These findings provide insights into dynamic brain reorganization of subacute ischemic stroke patients.

關鍵字(中)

★ 缺血性中風
★ 靜息態磁振照影
★ 腦網路
★ 上肢運動功能

關鍵字(英)

★ ischemic stroke
★ rs-fMRI
★ brain network
★ upper-limb motor function

論文目次

摘要 I
ABSTRACT II
誌謝 IV
目錄 V
圖目錄 VIII
表目錄 XIII
第一章緒論 1
1-1 靜息態磁振照影的原理與分析方法 3
1-1-1 功能性磁振照影的掃描原理 3
1-1-2 靜息態磁振照影的興起 4
1-1-3 影像前處理與分析方法 5
1-2 腦網路的探討―圖論應用於功能性網路分析 8
1-2-1 圖論的觀點 8
1-2-2 腦網路的建構 10
1-2-3 拓樸特性的統計分析 12
1-3 上肢運動功能與預後影響因子 14
1-3-1 運動皮質與皮質脊隨束 14
1-3-2 上肢運動預後與預後影響因子 16
1-4 研究目的 19
第二章文獻回顧 20
2-1 中風後的異常功能特性 20
2-2 圖論應用於中風患者的功能性網路分析 22
2-3 上肢運動預後模型探討 27
第三章研究方法 31
3-1 研究設計 31
3-2 受試者來源 35
3-3 影像與前處理 36
3-4 相關係數矩陣 38
3-5 受試者特徵 39
3-6 拓樸特性分析―節點的 43
3-6-1 拓樸特性 43
3-6-2 拓樸特性分析 44
3-6-3 拓樸特性統計檢驗與相似度計算 45
3-7 拓樸特性分析―邊的 48
3-7-1 上肢運動相關子網路分析 48
3-7-2 機器學習―回歸器建模 49
第四章實驗結果 51
4-1 節點的 51
4-1-1 健康受試者原始的/正規化的全域拓樸特性 51
4-1-2 全域拓樸特性的組間比較 52
4-1-3 區域拓樸特性的組間比較 52
4-1-4 樞紐分布與統計檢驗 55
4-2 邊的 62
4-2-1 上肢運動功能復原趨勢 62
4-2-2 子網路與上肢運動功能量表相關性分析 65
4-2-3 回歸模型訓練結果 69
第五章討論 80
5-1節點的 80
5-2 邊的 83
5-3 研究限制 86
第六章結論 87
參考文獻 88
附錄 94

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指導教授

蔡章仁(Jang-Zern Tsai)

審核日期

2021-1-23

推文