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研究生:楊德煒
研究生(外文):Te-Wei Yang
論文名稱:利用血管攝影影像評估肝動脈化療栓塞肝癌之治療效果
論文名稱(外文):Evaluated The Therapeutic Effect Of Transcatheter Arterial Chemoembolization For Hepatocellular Carcinoma by Using Angiography
指導教授:黃詠暉陳泰賓陳泰賓引用關係
指導教授(外文):Yung-Hui HuangTai-Been Chen
口試委員:黃詠暉陳泰賓杜維昌
口試委員(外文):Yung-Hui HuangTai-Been ChenWei-Chang Du
口試日期:2013-06-14
學位類別:碩士
校院名稱:義守大學
系所名稱:資訊工程學系碩士在職專班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2013
畢業學年度:101
語文別:中文
論文頁數:69
中文關鍵詞:肝動脈化療栓塞術電腦斷層攝影數位減赘血管攝影多項式回歸ROC曲線
外文關鍵詞:TACECTDSAPolynomial RegressionROC
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研究動機與目的:肝動脈化療栓塞術(Transcatheter Arterial Chemoembolization, TACE)是一種肝癌治療的姑息療法之一。然而,臨床上評估肝動脈化療栓塞術TACE的治療效果,目前多半於術後使用醫學影像來評估,如超音波、電腦斷層、核磁共振等等,欠缺即時性的結果,其中以電腦斷層影像為較常被使用的方式。本研究的動機為提供一個術中即時評估的方法;目的則是利用血管攝影暨電腦斷層影像經由回溯性分析,建立「利用血管攝影影像評估肝動脈化療栓塞肝癌之治療效果的影像特徵預測治療結果模型」。
材料與方法:本研究收集25位受測者,共39個肝腫瘤;每位受測者收集4種影像,包括(1)治療前電腦斷層影像、(2)治療前數位減赘血管攝影影像、(3) 治療後數位血管攝影影像、(4) TACE預後之電腦斷層影像;同時,從 3種影像量測8項影像參數作為TACE治療效果分析變數,包括: 治療前後電腦斷層影像之腫瘤體積變化率、治療後之數位血管影像特徵:平均值、標準差、最小值、最大值、熵值及影像均勻度。壞死率由TACE預後之電腦斷層影像進行估算。最後,將所取得之資料運用t檢定、相關性分析、迴歸分析及ROC (Receiver Operating Characteristic)曲線進行差異性分析暨建立迴歸預測模型。
結果:治療結果模型的依變數為肝癌壞死率,其餘影像特徵則為自變數。將所取得之資料運用t檢定、相關性分析、迴歸分析及ROC (Receiver Operating Characteristic)曲線,發現影像均勻度為解釋能力最佳之影像特徵參數(自變數);多項式迴歸模型為最佳之治療效果預測模型(i.e., 壞死率 = 85.25 + 111.99 x 均勻度 - 192.48 x 均勻度2;R2=0.778、P<0.05);而數位血管影像特徵平均值對腫瘤體積變化率具有差異性(t檢定、P<0.05)。
結論:本研究建立之模型及定義之影像特徵能提供預測腫瘤體積變化率及預測肝癌壞死率給放射科醫師作為治療中即時參考,同時預測四星期後肝癌的治療效果。未來仍需收集更多案例,以提高本研究所提方法之可靠性;同時未來亦可以朝向其他模型之探討與研究,以找出更合適之預測模型。

Motivation and Objective: Transcatheter Arterial Chemoembolization (TACE) is the one of palliative therapeutic methods for liver cancer. However, the medical images are current method to evaluate the therapeutic effects after TACE in clinic including ultrasound, computed tomography (CT), magnetic resonance, and etc. The way of applied computed tomography to monitor the therapeutic effects after TACE is lack of real-time evaluation. The motivation in this study is immediately to provide an intraoperative methods by building a predict model combined with features of angiography and CT for TACE through the retrospective analysis.
Materials and Methods: In this study, 25 subjects were collected with total of 39 liver tumors. Four kinds of image for each subject were involved in this study, including (1) CT images before TACE, (2) digital subtraction angiography before TACE, (3) digital angiography after TACE, and (4) CT images after TACE. Meanwhile, there are total design eight features from three kinds of image. The rate of change in tumor volume was measured from CT images between before and after TACE. The intensities of mean, standard deviation, minimum, maximum, entropy, and homogeneity were computed from digital angiography after TACE. The necrosis rate is measured from CT image after TACE. The t-test, Pearson’s correlation, ROC (Receiver Operating Characteristic) and regression models were applied to analyze the significant difference and build a predict model after TACE.
Results: The dependent and independent variables were necrosis rate and the other features with respectively. The homogeneity is the feasible, important, and significant features after t-test and ROC analysis (P<0.05). The polynomial regression model of homogeneity is the best predicted model for necrosis rate with 77.8% of determination (i.e., necrosis rate = 85.25 + 111.99 x homogeneity - 192.48 x Homogeneity 2; R2 = 0.778, P <0.05). The mean of digital angiography after TACE is the significant difference for the rate of change in tumor volume (t-test, P <0.05).
Conclusion: In this study, the polynomial regression model of homogeneity can provide forecasted ability of necrosis rate after the treatment of liver cancer. By the way, the mean of digital angiography can use to analyze the difference of the rate of change in tumor volume. In the future, more real cases are needed to improve the reliability of the presented method. The other possible and suitable predicted models might need to survey in advance for the future work.

目錄
中文摘要i
英文摘要ii
誌謝iii
目錄iv
表目錄viii
圖目錄ix
第一章 緒論1
1.1前言
1.2 研究動機與目的
第二章 理論基礎與文獻探討6
2.1 肝癌之流行病學
2.2肝癌之診斷方法
2.2.1 臨床診斷學
2.2.2 超音波診斷學
2.2.3 電腦斷層診斷學
2.2.4 核磁共振診斷學
2.2.5 血管攝影診斷學
2.2.6 組織切片診斷學
2.3 血管攝影原理及假影
2.4 肝癌治療現況
2.4.1 手術切除
2.4.2 酒精注射治療 (Percutaneous Ethanol Injection, PEI)
2.4.3 經皮高週波熱凝固療法 (Radiofrequency Ablation, RFA)
2.4.4 肝動脈栓塞術(Trans-Arterial Cchemo Embolization, TACE)
2.4.5 經肝動脈化學治療(Intra-Arterial Infusion Chemotherapy, I.A.I.C)
2.4.6 全身性化療(Systemic Chemotherapy)
2.4.7 口服標靶治療
2.4.8 放射線治療及質子治療
2.5 肝動脈化療栓塞(TACE)之化學栓塞藥物與油性顯影劑的特性
2.6 肝動脈化療栓塞術TACE的治療流程
2.7 肝癌治療效益探討
第三章 材料與方法25
3.1研究架構
3.2研究對象與收集樣本
3.3 照影設備及照影條件
3.4 評估模型
3.4.1電腦斷層腫瘤影像之特徵量測
3.4.2血管攝影影像之區域圈選與特徵量測
3.4.3影像定量分析
3.4.4電腦斷層影像評估肝癌壞死率
3.5 差異性與相關分析及迴歸模型
3.5.1相關性分析
3.5.2 迴歸分析
3.5.3 獨立樣本t檢定
3.5.4 ROC (Receiver Operating Characteristic)曲線
第四章 結果38
4.1 壞死率與影像特徵之分析
4.1.1相關性分析
4.1.2 利用迴歸模型篩選重要影像特徵
4.1.3 建立壞死率與影像均勻度之二次曲線迴歸模型
4.2 術後腫瘤體積變化率與影像特徵之分析
4.2.1定義術後腫瘤體積變化率之最適切點
4.2.2利用ROC分析法篩選重要影像特徵
第五章 結論48
第六章 討論50
第七章 未來工作與展望52
參考文獻54
附錄一 臨床試驗證明書58
表目錄
表1.1 100年台灣地區十大主要癌症標準化死亡率3
表2.1 BCLC肝癌分期(HCC Staging)14
表2.2 肝癌病人身體狀態(Performance Status)14
表2.3 肝功能Child-Pugh16
表3.1 肝功能指標評分表26
表4.1 Pearson相關係數分析38
表4.2 標準差與影像均勻度相關分析39
表4.3 標準差、最大值、影像均勻度與壞死率之迴歸模型適合度與平均絶對誤差40
表4.4 壞死率與影像均勻度間二次曲線迴歸模式摘要42
表4.5 壞死率與影像均勻度間二次曲線迴歸42
表4.6 壞死率與影像均勻度間二次曲線迴歸模型係數42
表4.7 二次曲線模型刪除離群值之分析結果44
表4.8 術後腫瘤體積變化率與六項影像特徵獨立樣本t檢定45
表4.9 ROC曲線分析對術後腫瘤體積變化率具有高分辨性之影像特徵47

圖目錄
圖1.1 100及99年台灣地區十大主要死因死亡人數2
圖1.2 100及99年台灣地區十大主要癌症死亡人數占率2
圖1.3 (a)正常肝臟外觀 (b)肝硬化之肝臟外觀 (c)肝癌之外觀3
圖2.1 典型的遮罩模式10
圖2.2 數位減贅血管影像模式11
圖2.3 對位失準假影影像校正11
圖2.4 根據日本肝病醫學會(JSH )肝癌治療準則(2010年本)13
圖2.5 巴塞隆納肝癌分期與肝癌治療準則(2012年修訂版本)15
圖2.6 明膠海綿(Gelatin Sponge)21
圖2.7 碘油(Lipiodol)21
圖2.8 化療藥物(Epirubicin)21
圖3.1 研究流程圖25
圖3.2 動靜脈廔管之血管攝影影像(紅色箭頭處為動靜脈廔管)27
圖3.3 四種肝腫瘤樣本影像29
圖3.4 血管攝影腫瘤影像之區域圈選30
圖3.5 肝腫瘤ROI灰階直方圖30
圖3.6 二維電腦斷層攝影影像早期動脈相顯影期33
圖4.1 壞死率與影像均勻度之間散佈圖41
圖4.2 建立壞死率與影像均勻度之二次曲線迴歸模型43
圖4.3 影像均勻度之殘差值散佈圖43
圖4.4 影像均勻度之殘差值盒形圖44
圖4.5 影像特徵之ROC 曲線46

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