比較擴散張量成像和擴散峰度成像鑑別神經組織特徵的能力: 正常大鼠及高血壓大鼠腦部的研究

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研究生：	傅虹毓 Fu, Hung-Yu
論文名稱：	比較擴散張量成像和擴散峰度成像鑑別神經組織特徵的能力: 正常大鼠及高血壓大鼠腦部的研究 Comparison of diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) in neural tissue characterization: A rodent brain study on Sprague-Dawley (SD) and Spontaneously hypertensive rats (SHR)
指導教授：	王福年 Wang, Fu-Nien
口試委員:	彭旭霞 Peng, Hsu-Hsia 劉益瑞 Liu, Yi-Jui
學位類別：	碩士 Master
系所名稱：	原子科學院 - 生醫工程與環境科學系 Department of Biomedical Engineering and Environmental Sciences
論文出版年：	2018
畢業學年度：	107
語文別：	英文
論文頁數：	57
中文關鍵詞：	擴散峰度成像、擴散張量成像、組織異質性
外文關鍵詞：	DKI, DTI, tissue heterogeneity
相關次數：	點閱：2 下載：0
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擴散張量成像(DTI)在臨床上已經被廣泛使用於診斷神經元損傷及預測神經系統疾病。但DTI無法使用於觀察非高斯擴散的情形，因此擴散峰度成像(DKI)被提出。DKI利用「峰度」的概念來量化非高斯擴散並反映擴散受到阻礙的程度，並且這個方法在未來幾年可能會應用於臨床。本研究的目的是比較DTI和DKI 描述神經組織特徵的能力。我們使用常用的DTI、使用6個b值的DKI和DTI三種方法獲得的參數，並將正常大鼠(SD)和高血壓大鼠(SHR)分組並進行三個模型之間分辨能力的比較。由結果發現DTI 計算得到的Dapp、擴散參數、擴散參數的範圍及變異都比DKI小。在解釋結果時，同時考慮擴散和峰度提供的資訊能使DKI分辨組織的能力提高。在分辨SD及SHR兩種不同品系的大鼠時，DKI能分辨出最多不同種類的組織，是分辨能力最佳的方法，而在分辨不同年齡的SHR時，6b DTI及DKI則是三者中分辨能力較佳的方法。此外，我們觀察大鼠內的組織異質性，並發現這個指標能用來分辨病理及正常組織，可能是有潛力的分辨方法。

Diffusion tensor imaging (DTI) has been used to identify neuronal injury and predict outcome of neurological disorders clinically. Yet this method is unable to investigate non-gaussian diffusion behavior. Diffusion Kurtosis Imaging (DKI) is proposed to probe non-gaussian diffusion property by measuring kurtosis, which reveals the degree of diffusion restriction, and might apply in clinic in the coming year. The aim of this study is to compare the abilities of neural tissue characterization between DTI and DKI models. We studied parameters derived from conventional DTI, DKI with 6 different b values, and DTI fitted with same dataset as DKI. We probed parameters and compared three approaches utilizing mean among rats and tissue heterogeneity with groups of Sprague-Dawley (SD) rats and Spontaneously hypertensive rats (SHR). Results show that DTI-derived Dapp, diffusivities, as well as range and variation of parameters are smaller than those derived from DKI. DKI demonstrates better ability when interpreting results with diffusivities and kurtoses. When it comes to telling apart SHR in different age, 6b DTI showed most significant difference among three approaches, closely followed by DKI, and the 2b DTI has the worst performance among three of them. Moreover, tissue heterogeneity of diffusivities may have potential to tell pathologic tissue from normal one.

摘要    i
Abstract    ii
Contents    iii
Dedication    v
Chapter 1 Introduction    1
1.1 Introduction to Diffusion Tensor Imaging and Diffusion Kurtosis Imaging    1
1.2 Purpose    3
Chapter 2 Theory: DTI and DKI    5
2.1 Introduction of Theory    5
2.2 Diffusion tensor (DT) and Diffusion tensor (DT) derived parameters    8
2.2.1 Diffusion tensor (DT)    8
2.2.2 Derived diffusion parameters from diffusion tensor    10
2.3 Kurtosis tensor (KT) and Kurtosis tensor (KT) derived parameters    11
2.3.1 Kurtosis tensor (KT)    11
2.3.2 Kurtosis tensor (KT) derived parameters    12
Chapter 3 Materials and Methods    14
3.1 Simulation    14
3.2 In vivo rat brain study    15
3.2.1 Rat preparation    15
3.2.2 MRI data acquisition    15
3.2.3 Data analysis    16
3.2.4 Statistical analysis    18
Chapter 4 Results    19
4.1 Examination of models    19
4.1.1 Simulation Study    19
4.1.2 in vivo study on SD rat brains    21
4.2 In vivo study: SD and SHR in early stage    23
4.2.1    Inter- strain comparison of diffusivities    23
4.2.2    Inter-strain comparison of diffusional heterogeneity    30
4.3 in vivo study: SHR in different age    35
4.3.1    Comparison of value of SHR in different age    35
4.3.2    Diffusional heterogeneity of SHR in different age    40
Chapter 5 Discussion    45
5.1 Comparison of 2b DTI, 6b DTI and DKI    45
5.2 Potential application of DKI and tissue heterogeneity    49
5.3 Limitations    51
Chapter 6 Conclusion    53
Future work    54
Reference    55



                                

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