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研究生: 覃昭睿
Tham, Jao Rui Ian
論文名稱: 利用擴散張量成像評估Oxaliplatin化療方案誘發認知神經損傷之效果
Evaluating the Effects of Oxaliplatin Chemotherapy Regimens in Inducing Cognitive Impairments Using Diffusion Tensor Imaging
指導教授: 林宙晴
Lin, Chou-Ching
學位類別: 碩士
Master
系所名稱: 工學院 - 生物醫學工程學系
Department of BioMedical Engineering
論文出版年: 2025
畢業學年度: 113
語文別: 英文
論文頁數: 130
中文關鍵詞: 化學療法Oxaliplatin化療誘發的認知神經病變擴散張量成像神經纖維束造影
外文關鍵詞: Chemotherapy, Oxaliplatin, CICI, DTI, Tractography
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  • 癌症是全球主要死亡原因之一,其主要特徵為不受控制的細胞增生,進而形成腫瘤並且有可能轉移至其他器官。儘管研究已久,癌症的確切致病機制仍未完全釐清,但普遍認為遺傳與生活習慣如飲食、吸菸是其重要的因子。化學治療雖然是治療癌症的重要方法之一,但其無特定性作用機制也會影響正常分裂的細胞,因而導致副作用疲勞、噁心、掉髮或免疫力下降等。
    為了對抗癌症醫學領域也發展出了許多方法像是手術切除、放射療法還有化學療法。其中,化療誘發的認知神經病變(chemotherapy-induced cognitive impairments, CICI)為近幾年受到最多關注的副作用。其常見症狀包括記憶力衰退、注意力不集中與反應遲緩等。而導致CICI發生的可能機制包括化療藥物穿越血腦障壁(BBB)、引發神經細胞發炎與製造細胞內氧化壓力等,進而導致中樞神經系統(CNS)的細胞受損。
    本研究旨在探討常用於結直腸癌、卵巢癌與子宮內膜癌之化療藥物組合(FOLFOX (folinic acid、fluorouracil、oxaliplatin) 和FOLFIRI (folinic acid、fluorouracil、 irinotecan) 結合Bevacizumab)是否會影響腦部中樞神經白質結構,進而引發 CICI (鑒於之前研究皆指出該藥物組合影響周圍神經較多)。本研究從成功大學附設醫院招募共30名受試者,最終納入16名健康對照者與8名已完成化療前後擴散張量成像(DTI)掃描的癌症患者。接著利用FMRIB Software Library(FSL)進行 DTI前處理與張量的形成,並選取與認知功能相關之白質區域進行分析,包括弓形束 (AF)、鈎狀束 (UF)、下額枕束 (IFOF)、扣帶束 (CIN)、放射冠 (CR) 與胼胝體 (CC) 等。DTI 指標涵蓋 FA、MD、AD 與 RD。最後再以魏克生符號等級檢定來比較化療前後變化。另外我們也加入了比較成大余教授的神經心理測驗和神經纖維束造影來加強我們的研究結果。
    結果意外地顯示所有白質區域之各項 DTI 指標均沒有顯著變化。此可能表示所使用Oxaliplatin化療藥物組合對中樞神經白質影響有限,或因為受限於樣本數過少(鑒於之前研究平均接收的癌症病人為18人),導致統計檢定不足與判斷。相反地,在測驗和神經纖維束造影內,病人呈現了認知的退化和白質體積和數量的減少。
    本研究指出DTI是監測CICI潛在變化的潛力工具,未來研究應擴大病人樣本數並結合神經心理評估或生物神經標誌物,以更全面的評估化療對認知功能之影響,進而發展出適合的照顧應對策略。

    Cancer remains a leading cause of death globally, largely due to its ability to cause uncontrolled cellular proliferation that leads to the formation of tumours. These tumours can disrupt normal physiological functions and, in many cases, become metastatic, spreading to other organs. Despite decades of research, the exact cause of cancer is still not fully understood. However, it is widely accepted that genetic and lifestyle factors, such as diet and smoking, play significant roles in cancer development and progression.
    To combat this disease, various approaches have been developed, including surgery, radiation therapy, and chemotherapy. Chemotherapy, particularly, has become one of the most common and powerful methods for treating a wide array of cancers. It involves the systemic administration of chemical drugs that are designed to target and eliminate tumour dividing cells. While effective at killing tumour cells, chemotherapy is non-selective and can also damage healthy cells that divide frequently as well, including those cells in the gastrointestinal tract, hair follicles, and bone marrow. This non-specific target often leads to numerous side effects, including fatigue, nausea, hair loss, and increased susceptibility to other disease.
    One increasingly recognized side effect of chemotherapy is chemotherapy induced cognitive impairments (CICI), often referred to as "chemobrain." CICI is characterized by cognitive impairments such as memory loss, difficulty concentrating, and reduced action processing speed. The pathophysiology of CICI is not entirely clear, but several mechanisms have been proposed. These include the ability of chemotherapy drugs to cross the blood-brain barrier (BBB), the start of neuroinflammation, and the generation of oxidative stress that damages BBB integrity. Once the BBB is disrupted, chemotherapeutic agents may enter the brain and damage neurons and glial cells, particularly in the central nervous system (CNS), leading to long-term cognitive deficits on the patient.
    This study investigates whether chemotherapy regimens commonly used in treating colorectal, ovarian, and endometrial cancers have an effect on CNS, which will lead to CICI. We focus on regimens FOLFOX (folinic acid, fluorouracil, and oxaliplatin) and FOLFIRI (folinic acid, fluorouracil, and irinotecan) combined with bevacizumab, a monoclonal antibody targeting vascular endothelial growth factor (VEGF). While previous studies have shown that oxaliplatin is associated with damage in the peripheral nervous system (PNS), its impact on the CNS remains less understood. The goal of this research is to assess whether these regimens contribute to CICI using magnetic resonance imaging (MRI) diffusion tensor imaging (DTI) technique as the primary method.
    DTI is a MRI technique that measures the diffusion of water molecules within tissues, providing insights into the microstructural integrity of white matter (WM) in the brain. Several DTI metrics are commonly used, including fractional anisotropy (FA), which measures the directionality of water diffusion, mean diffusivity (MD), representing the overall rate of diffusion, axial diffusivity (AD), measuring the diffusion along the principal axis, which is a marker of axonal integrity, and Radial Diffusivity (RD), measuring the diffusion perpendicular to the main axis, which is a marker of myelin integrity. Alterations in these parameters can suggest neuronal injury or degeneration of the neural cells.
    For this study, 30 participants were initially recruited from National Cheng Kung University Hospital (NCKUH). The subjects included 18 healthy controls, and 12 cancer patients scheduled to undergo chemotherapy. Each participant was scanned using DTI at NCKUH before treatment and six months following treatment completion. However, due to participant dropout and failure to follow-up, the final dataset included only 16 healthy controls and 8 cancer patients who completed both DTI scans.
    DTI preprocessing and tensor fitting were then done using the FMRIB Software Library (FSL). From each subject’s data, brain maps of FA, MD, AD, and RD were generated. To specify the analysis to regions associated with cognition, a set of white matter tract masks were applied. These masks highlight structures including the arcuate fasciculus (AFL, AFR), the inferior frontal occipital fasciculus (IFOFL, IFOFR), the uncinate fasciculus (UFL, UFR), the cingulum bundle (CINL, CINR), the corona radiata (CRL, CRR), and the corpus callosum (CC). These regions are known to support memory, attention, language, and executive functions, which are functions often affected in CICI. Finally, to determine whether chemotherapy had a statistically significant impact on DTI metrics within these regions, we conducted a Wilcoxon signed-rank test, a non-parametric test suitable for small, paired samples without assuming the normality. Each respective DTI metric was compared pre- and post-treatment for each patient within each mask. An addition of neuropsychological tests provided by Professor Yu and DTI tractography of each region is also added to complement the findings.
    Surprisingly, our statistical analysis revealed no significant changes in FA, MD, AD, or RD across any of the regions examined. This result suggests two possible interpretations. First, it is likely that the chemotherapy regimens of the experiment, especially those involving oxaliplatin, do not significantly impact the WM of the CNS. This aligns with previous studies showing that oxaliplatin affected the PNS rather than the CNS. Alternatively, the small sample size in this study may also have limited our ability to detect subtle changes in the WM structure. Previous studies examining CICI included an average of 18 cancer patients, which provided more statistical power to detect group-level effects. However, in the neuropsychological assessment and tractography, declines in cognitive function and reduced WM tracts were shown.
    In conclusion, this study shows the potential usage of DTI as a non-invasive tool to monitor WM changes following oxaliplatin chemotherapy. However, our findings also highlight the limitations of small sample sizes in neuroimaging research regarding WM. Future studies should aim to recruit larger patient population and consider incorporating additional evaluation methods, such as neuropsychological testing or molecular biomarkers, in order to allow a more comprehensive assessment on the presence of CICI. These efforts will be crucial for developing targeted interventions and supportive care strategies to cancer survivors with CICI.

    Abstract i 摘要 iv Acknowledgements vi Contents vii Figure Contents x Table Contents xi Anatomical Glossary xiv Chapter 1 Introduction 1 1.1 Research background 1 1.2 Chemotherapy Induced Cognitive Impairments (CICI) 1 1.2.1 Cancer and Chemotherapy 1 1.2.1.1 Cancer Introduction 1 1.2.1.2 Chemotherapy and chemotherapeutical agents 2 1.2.1.3 Oxaliplatin 3 1.2.1.4 Fluorouracil 3 1.2.1.5 Folinic acid (Leucovorin) 3 1.2.1.6 Irinotecan 3 1.2.1.7 Bevacizumab 4 1.2.2 Cause and Effects 4 1.2.2.1 Neuroinflammation 4 1.2.2.2 Oxidative stress 5 1.2.2.3 Reduced spinal and dendritic arborization 6 1.2.2.4 Neurotransmitters 7 1.3 Evaluation Methods in studies 8 1.3.1 Neural Imaging Evaluation 8 1.3.1.1 Magnetic Resonance Imaging (MRI) 8 1.3.1.1.1 Structural Magnetic Resonance Imaging 8 1.3.1.1.1.1 T1-weighted Voxel-based Morphometry (T1-VBM) 9 1.3.1.1.2 Diffusion Magnetic Resonance Imaging (DMRI) 9 1.3.1.1.3 Functional Magnetic Resonance Imaging (fMRI) 10 1.3.1.2 Positron Emission Tomography (PET) 12 1.3.2 Electroencephalogram (EEG) 12 1.3.3 Neuropsychology Test 13 1.4 Summary and Choice 13 Chapter 2 Materials and Methods 14 2.1 Study Introduction 14 2.2 Subject Criteria 14 2.2.1 Subjects 14 2.2.2 Inclusion Criteria 14 2.2.3 Exclusion Criteria 14 2.3 Imaging Data Acquisition 15 2.3.1 Data acquisition 15 2.3.2 MRI scans acquisition 16 2.4. Pre-processing of Images 16 2.4.1 DICOM To NIfTI - Chris Rorden dcm2nii 17 2.4.2 Brain extraction (skull stripping) - BET 19 2.4.3 Eddy Current and Motion Correction - FSL 20 2.4.4 Diffusion Tensor Fitting - FSL 20 2.4.5 Normalisation - FSL 22 2.4.5.1 Linear Registration 23 2.4.5.2 Non-Linear Registration 24 2.5 DTI Metrics Assessment - FSL 26 2.6 Tractography – DSI Studio 27 2.6.1 Streamline (Euler) Algorithm 28 2.7 Statistical Tests 28 2.7.1 Parametric Statistical Test Approach: Paired t-test 28 2.7.2 Non-parametric Statistical Test Approach: Wilcoxon Signed-Rank Test 29 Chapter 3 Results 29 3.1 MNI152 masked ROIs DTI metrics 29 3.1.1 Results for Cancer Patients 30 3.1.2 Results for Healthy Controls 32 3.1.3 Summary 34 3.2 Tractography 34 3.2.1 Results for Cancer Patients 35 3.2.2 Results for Healthy Controls 38 3.2.3 Summary and Comparisons 42 3.3 Tractography masked ROIs DTI metrics 43 3.3.1 Results for Cancer Patients 43 3.3.2 Results for Healthy Controls 45 3.3.3 Summary 47 3.4 Neuropsychological Assessment 48 Chapter 4 Discussion 48 4.1 Considerations on MNI152 masked ROIs Results 48 4.2 Considerations on the Tractography Results 52 4.3 Considerations on Tractography masked ROIs Results 52 4.4 Considerations on Neuropsychological Assessment Results 52 4.5 Methods Improvements 53 Chapter 5 Conclusion and Future Work 54 Chapter 6 References 55 Chapter 7 Appendices 66 7.1 Cancer patients detailed DTI metrics values (MNI152 ROI mask) 66 7.2 Healthy Controls detailed DTI metrics values (MNI152 ROI mask) 74 7.3 Cancer patients detailed DTI metrics values (Tractography ROI mask) 89 7.4 Healthy Controls detailed DTI metrics values (Tractography ROI mask) 98 7.5 Machine Learning 113

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