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  1. NTU Theses and Dissertations Repository
  2. 電機資訊學院
  3. 生醫電子與資訊學研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/49452
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor陳志宏
dc.contributor.authorMeng-Chi Hsiehen
dc.contributor.author謝孟錡zh_TW
dc.date.accessioned2021-06-15T11:29:21Z-
dc.date.available2019-10-14
dc.date.copyright2016-10-14
dc.date.issued2016
dc.date.submitted2016-08-17
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/49452-
dc.description.abstract近幾年來,個人化及精準化醫學已經成為二十一世紀最重要的課題之一。藉由專屬之治療方式來提高療效,降低副作用。定量醫學影像之技術可用以評估病灶的發展與治療的反應就成為重要之方法。利用磁振造影為基礎之磁化率權重影像來觀察大腦出血或是中風,已經成為目前臨床診斷的必要方法。相較於傳統的磁化率權重影像技術,磁化率影像技術能夠提供量化資訊,進而幫助個人化醫學影像的發展。然而,此方法於神經科學與臨床應用的可行性仍需要進一步之驗證。
因此,本論文的主要目的為增進磁化率影像技術於臨床應用的可行性,並且可分為下列四部分。第一為利用數值模擬與仿體實驗來驗證磁化率影像技術;第二為利用定量探討高氧狀態下,大鼠顱內的靜脈血氧變化;第三為長期地定量監測大鼠中風後的血氧變化;第四為系統性最佳化人大腦之重建參數與其於臨床上之可行性。
在數值模擬的研究中,我們驗證了磁化率影像演算法有99%的準確率,仿體的實驗也呈現了磁化率數值與鐵離子濃度為線性相關 (R2 = 0.98)。在大鼠的高氧研究中,我們發現到磁化率的變化主要來自於靜脈血管;此外,相較於常氧狀態下,靜脈的血氧上升約10%。在大鼠中風的研究中,我們發現了靜脈的血氧濃度會於七天後恢復至與正常側無顯著差異(p > 0.05)。最後,我們將此方法應用於臨床的定量鐵沉積、出血與鈣化研究中,利用定量磁化率影像可分辨兩病灶於一次磁振造影掃描中。
總結而言,我們呈現了磁化率影像技術於神經科學與臨床上進一步應用之潛力。此外,我們也建立一套最佳化磁化率影像之方法,並針對鼠腦與人腦探討其最適當參數之選擇。本論文成功地建立定量磁化率影像技術由動物研究轉移至臨床上的可行性與最佳化之方法,相信對未來神經科學的研究或是臨床診斷都有極大的助益。
zh_TW
dc.description.abstractSince last few years, personalised or precise medicine has been a crucial issue in 21st century. With exclusive way to improve the outcome of treatment, the side effect could be reduced. For this purpose, a quantitative medical imaging is essential to evaluate the disease progress and the response to treatment. At present, using susceptibility weighted imaging (SWI) based on magnetic resonance imaging (MRI) to observe haemorrhage and stroke has become an essential methodology for clinical diagnosis. Compared to the conventional SWI, quantitative susceptibility mapping (QSM) technique can offer quantitative information to approach to the personalised medicine. However, the capability of QSM technique on neuroscience researches and clinical applications has not been well demonstrated yet.
Therefore, the overall objective of this dissertation is fourfold and targeted to facilitate the QSM technique for clinical use. First, we start from verifying the capability of the QSM technique using numerical simulation and phantom experiment. Second, we investigate the hyperoxic effect in rat brain using the QSM technique. Third, we applied the QSM technique to longitudinally monitor the venous oxygen saturation (SvO2) after stroke. Forth, we optimised the parameters of QSM technique for human brain and tested its potential on cerebral disorders such as haemorrhage, microbleeds, and calcification.
In our results, accuracy of the QSM technique was 99% in numerical simulation, and a linear correlation (R2 = 0.98) was found between estimated susceptibility and iron concentration in the phantom experiment. For hyperoxia study, we found the susceptibility change were mainly from veins and venules. A 10% shift of SvO2 was estimated relative to normoxia. For stroke study, there was no significant difference (p > 0.05) of SvO2 between contralateral and ipsilateral cortex after reperfusion at 7- days. Finally, the QSM technique to quantify iron deposition and differentiate haemorrhage/microbleeds and calcification was demonstrated in one MRI scan.
In summary, we successfully demonstrated the feasibility of QSM technique on neuroscience researches and clinical applications. Additionally, we optimised the QSM technique for rat and human brain. Conclusively, our proposed methods can further advance the translation of QSM technique from animal to clinical applications, which will be potentially useful to facilitate the neuroscience research and clinical applications.
en
dc.description.provenanceMade available in DSpace on 2021-06-15T11:29:21Z (GMT). No. of bitstreams: 1
ntu-105-D96945011-1.pdf: 57074793 bytes, checksum: 5b200dea109b4ec841f54471dd3b8c42 (MD5)
Previous issue date: 2016
en
dc.description.tableofcontents誌謝 ii
中文摘要 iii
Abstract v
Contents viii
List of Figure xii
List of Table xxi
1. Introduction 1
1.1 Background 1
1.2 Motivation and Purpose 3
1.2.1 Motivation 3
1.2.2 Purpose 4
1.3 Outline 5
2. Quantitative Susceptibility Mapping 7
2.1 Introduction 7
2.1.1 Magnetic Susceptibility in MRI 7
2.1.2 Relationship Between MR Phase and Susceptibility 10
2.1.3 Magnetic Field Measurement Using MRI 11
2.1.4 QSM Processing 15
2.2 Numerical Simulation 19
2.2.1 Methods 20
2.2.2 Results and Discussion 26
2.2.3 Summary 36
2.3 Phantom Study 36
2.3.1 Methods 36
2.3.2 Results and Discussion 37
2.3.3 Summary 38
3. Investigating Hyperoxic Effects Using QSM 39
3.1 Introduction 39
3.2 Theory 43
3.2.1 Estimating SvO2 Using QSM 43
3.2.2 ΔSO2 Prediction Using ΔR2* 44
3.3 Methods 45
3.3.1 Animal Preparation 45
3.3.2 Data Acquisition and Analyses 46
3.3.3 Quantitative Susceptibility Mapping Reconstruction 48
3.3.4 SpO2 Measurement Using a Pulse Oximeter 49
3.3.5 ΔR2* Map Reconstruction 50
3.3.6 Image Registration, VOIs, and Statistical Analyses 50
3.4 Results 52
3.5 Discussion 62
3.6 Summary 70
4. QSM in Rat Stroke Model 72
4.1 Introduction 72
4.2 Methods 76
4.2.1 Susceptibility Calculation Based on Phase Information 76
4.2.2 Regularised Approach for QSM 78
4.2.3 SvO2 Calculation with Susceptibility 79
4.2.4 Ethics Statement 80
4.2.5 Middle Cerebral Artery Occlusion (MCAO) 81
4.2.6 Calculating the Ischemic Infarct Area Using TTC Staining 82
4.2.7 Measuring the Pulse Oxygen Saturation (SpO2) in the Infarcted and Non-Infarcted Areas of the Brain Tissue Sections of the Stroke Rat 83
4.2.8 MR Data Acquisition for Control Rats 83
4.2.9 MR Data Acquisition for the MCAO Rat Stroke Model 85
4.2.10 MR Data Processing 85
4.2.11 Image Registration and Statistical Analysis of MRI Data 94
4.3 Results 96
4.3.1 Path-Based and Laplacian-Based Unwrapping Algorithms Compared 96
4.3.2 Influence of the Selection of the Lagrange Parameter λ 99
4.3.3 Using QSM to Quantitatively Visualise Veins 101
4.3.4 QSM and SWI Compared 103
4.3.5 Using QSM to Study Post-Stroke Rehabilitation 107
4.4 Discussion 112
4.5 Summary 120
5. Preliminary Result: Translate Animal to Clinical Study 122
5.1 Introduction 122
5.2 Methods 122
5.2.1 MR Data Acquisition 122
5.2.2 QSM Reconstruction 124
5.2.3 Image Registration and Region-of-interest (ROI) Analysis 125
5.3 Results and Discussion 126
5.3.1 Selection of the Radius of the SHARP Filter 126
5.3.2 Optimisation of Weighted L1 (WL1) Regularisation 128
5.3.3 QSM of Healthy Volunteers 129
5.3.4 QSM of Patients: Microbleeds, Haemorrhage and Calcification 132
5.3.5 QSM of Patients: Parkinson’s Disease (Preliminary result) 135
5.4 Summary 136
6. Discussion, Conclusion and Future Works 138
6.1 Discussion 138
6.1.1 QSM Technique 138
6.1.2 QSM to Investigate the Hyperoxic Effect 147
6.1.3 QSM in Rat Stroke Model 148
6.2 Conclusion 150
6.3 Future works 151
6.3.1 Automated QSM Processing 151
6.3.2 functional QSM (fQSM) 152
6.3.3 Clinical applications 153
Appendix 155
A.1 SHARP Filter 155
A.2 Weighted L1 Regularisation Using the Steepest Gradient Descent 160
A.3 Partial Volume Effect on QSM 162
A.4 Noise Amplification of QSM 177
A.5 Graphical User Interface (GUI) of QSM Processing Tool 179
Reference 180
Honours and Publications 197
dc.language.isoen
dc.subject中風zh_TW
dc.subject鈣化zh_TW
dc.subject出血zh_TW
dc.subject鐵沉積zh_TW
dc.subject靜脈血氧濃度zh_TW
dc.subject磁化率影像zh_TW
dc.subject磁振造影zh_TW
dc.subjecthaemorrhageen
dc.subjectquantitative susceptibility mappingen
dc.subjectvenous oxygenation saturationen
dc.subjectiron depositionen
dc.subjectcalcificationen
dc.subjectstrokeen
dc.subjectmagnetic resonance imagingen
dc.title磁化率影像於大腦之研究與應用:定量靜脈血氧濃度與鐵沉積zh_TW
dc.titleQuantitative Susceptibility Mapping of Brain: Assessing Venous
Blood Oxygenation and Iron Deposition
en
dc.typeThesis
dc.date.schoolyear104-2
dc.description.degree博士
dc.contributor.oralexamcommittee陳中明,張允中,廖漢文,蘇家豪,吳昌衛
dc.subject.keyword磁振造影,磁化率影像,靜脈血氧濃度,鐵沉積,中風,出血,鈣化,zh_TW
dc.subject.keywordmagnetic resonance imaging,quantitative susceptibility mapping,venous oxygenation saturation,iron deposition,stroke,haemorrhage,calcification,en
dc.relation.page200
dc.identifier.doi10.6342/NTU201602277
dc.rights.note有償授權
dc.date.accepted2016-08-17
dc.contributor.author-college電機資訊學院zh_TW
dc.contributor.author-dept生醫電子與資訊學研究所zh_TW
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